Scientific Reports

Volatile organic compounds (VOCs) are considered one of the most important causes of air pollution in sterilized and enclosed environments, especially in hospitals. Since the first step for effective control of air pollutants is determining their level of emission and identification of their manner of distribution, this study was conducted to determine the level of emission and concentration of VOCs in different wards of one of the university hospitals in Tehran and to compare the measured values against international standards

Species range contractions both contribute to, and result from, biological annihilation, yet do not receive the same attention as extinctions. Range contractions can lead to marked impacts on populations but are usually characterized only by reduction in extent of range. For effective conservation, it is critical to recognize that not all range contractions are the same. We propose three distinct patterns of range contraction: shrinkage, amputation, and fragmentation. We tested the impact of these patterns on populations of a generalist species using forward-time simulations. All three patterns caused 86–88% reduction in population abundance and significantly increased average relatedness, with differing patterns in declines of nucleotide diversity relative to the contraction pattern. The fragmentation pattern resulted in the strongest effects on post-contraction genetic diversity and structure. Defining and quantifying range contraction patterns and their consequences for Earth’s biodiversity would provide useful and necessary information to combat biological annihilation.

New cellulose carbamates and cellulose acetate carbamates were prepared by classical addition reaction of isocyanates with alcohols. A Telomerization technique was used to make the grafted molecules strongly anchored and more hydrophobic. These molecules were grafted into cellulose and CA chains, respectively. The structures of the synthesized derivatives were confirmed using Nuclear Magnetic Resonance Spectroscopy, Fourier Transform Infrared and Thermogravimetric Analysis, and their solubility phenomenon was also established, and the carbamate derivatives showed better solubility compared to cellulose. Their ability to biodegrade was investigated, and it was concluded that Cell-P 1 and CAP 1 derivatives are more biodegradable than the other samples. These results suggest that the resulting compounds can be used effectively in many useful industrial fields, for instance, eco-friendly food packaging, domains that use materials that are environmentally friendly and sustainable and the development of green chemistry. In this period of having emergent necessity for natural resources preservation and environmental protection, as a result of global concerns about hygiene and health matters. Continuous research and development in the realm of sustainable and ecologically friendly compounds are exponentially important for current generations and even more vital so for future generations 1. Cellulose is considered to be the dominant constituent present in the vast majority of plants 2. It has specific characteristics such as, regular structure, renewable resources, biodegradability, and abundance. Cellulose structure and characteristics offer unique and outstanding options for systematic projects in order to develop appropriate substances for many relevant fields, including but not limited to, membrane technology 3-5 , pharmaceutical applications 6-8 , removal of organic dyes, toxic heavy metals, anions and cations from groundwater and other aqueous solutions 9-12 , bioelectronics 13 and other industries, for example; food, textile, and paper 14. Cellulose exploitation represents a very rapidly growing sector that includes the high-volume commodities industry, for instance, paper and textiles, as well as, the production of novel high-added-value materials, for example; functionalized fibers and natural reinforcing elements that exist in fiber-based composite substances 15. Cellulose represents a multifunctional biological material with a high molar mass. In order to improve its processing ability, precursors are used for providing diverse varieties of cellulose derivatives 2. The cellulose chemical modification was performed on the reactive hydroxyl groups as various processes can be carried out, resulting in a broad variety of novel commercial substances 16,17. Being the most abundant polymer in nature does not mean it's easy to handle. The presence of inter-and intramolecular hydrogen bonds in cellulose can result in the lack of its processability and solubility. One of the significant processes, in order to make this polymer a highly processable one, is the preparation of cellulose acetate such that hydroxyl groups will be converted into acetates. There are other cellulose modification achievements that were reported, such as; esterification 18 , etherification 19 , oxidation 2 , etc. Chemical modification of cellulose with isocyanate or blocked diisocyanate groups has been largely investigated 17. It was found that this OPEN

One of the parameters affecting the leachability of heavy metals from waste is their contact time with the leachant. In this paper, the leaching behaviour of Zn, Cu, Pb and Ni was evaluated in relation to the liquid to solid ratio (L/S), which is a reflection of time after which a certain volume of water permeates the material, e.g. in slag heaps or landfills. A leaching study was carried out by different leaching methods with using three test materials, i.e. hazardous zinc slag, lump copper slag and mineral-organic composite. It was found that the highest amount of metals leached in the long term in the maximum availability test, under the following leaching conditions: L/S = 50 dm ³ /kg, reduced pH of the leachant, fragmentation of the materials to particle size < 0.125 mm. Comparing the results obtained in the batch test and the percolation test, no strict trend was observed in the release of a given metal from different test materials. The analysis using the tank test showed that processes controlling leachability can result in the release of the highest metal loads immediately after contact between the material and the leachant, but can also contribute to the release of metals only after prolonged contact.

Several studies have attempted to validate the relationship between hepatic steatosis and sarcopenia. The crucial limitation is to establish the status of hepatic steatosis by costly or invasive methods. Therefore, several models predicting non-alcoholic fatty liver disease (NAFLD) have been developed but have exhibited heterogeneous results. In this study, we aimed to review and compare four representative models and analyze their relationship with the risk of low muscle mass. Korea National Health and Nutrition Examination Surveys from 2008 to 2011 were used to confirm our hypothesis. Dual-energy X-ray absorptiometry was used to measure the amount of skeletal muscle mass. We used four hepatic steatosis indices: hepatic steatosis index (HSI), Framingham steatosis index (FSI), liver fat score (LFS), and fatty liver index (FLI). Multivariate linear and logistic regressions were used to reveal the relationship between NAFLD and low skeletal muscle index (LSMI). Pairs of FSI-FLI and HSI-FLI exhibited the best and second-best correlations among all possible pairs. The four hepatic steatosis models were associated with increased risk for LSMI. After removing the body mass index effect, HSI and FLI remained robust predictors for LSMI. NAFLD was a significant and potent risk factor for low skeletal muscle.

Cancer genomics tailors diagnosis and treatment based on an individual’s genetic information and is the crux of precision medicine. However, analysis and maintenance of high volume of genetic mutation data to build a machine learning (ML) model to predict the cancer type is a computationally expensive task and is often outsourced to powerful cloud servers, raising critical privacy concerns for patients’ data. Homomorphic encryption (HE) enables computation on encrypted data, thus, providing cryptographic guarantees to protect privacy. But restrictive overheads of encrypted computation deter its usage. In this work, we explore the challenges of privacy preserving cancer type prediction using a dataset consisting of more than 2 million genetic mutations from 2713 patients for several cancer types by building a highly accurate ML model and then implementing its privacy preserving version in HE. Our solution for cancer type inference encodes somatic mutations based on their impact on the cancer genomes into the feature space and then uses statistical tests for feature selection. We propose a fast matrix multiplication algorithm for HE-based model. Our final model achieves 0.98 micro-average area under curve improving accuracy from 70.08 to 83.61% , being 550 times faster than the standard matrix multiplication-based privacy-preserving models. Our tool can be found at https://github.com/momalab/octal-candet .

Support vector machine (SVM) and genetic algorithm were successfully used to predict the changes in the prevalence rate (ΔPR) measured by the increase of reported cases per million population from the 16th to the 45th day during a nation’s lockdown after the COVID-19 outbreak. The national cultural indices [individualism–collectivism (Ind), tightness–looseness (Tight)], and the number of people per square kilometer (Pop_density) were used to develop the SVM model of lnΔPR. The SVM model has R ² of 0.804 for the training set (44 samples) and 0.853 for the test set (11 samples), which were much higher than those (0.416 and 0.593) of the multiple linear regression model. The statistical results indicate that there are nonlinear relationships between lnΔPR and Tight, Ind, and Pop_density. It is feasible to build the model for lnΔPR with SVM algorithm. The results suggested that the risk of COVID-19 epidemic spread will be reduced if a nation implements severe measures to strengthen the tightness of national culture and individuals realize the importance of collectivism.

The instability of rock slope is still a very frequent geological disaster, which seriously affects people's life and production activities. Previous studies have mainly focused on deformation mechanism, prediction, and control of hard rock with single lithology, while there are limited studies on the theoretic computational method of the stability for soft–hard interbedded anti-inclined rock strata. In this study, a geomechanical model for the toppling failure of soft–hard-interbedded anti-inclined rock slope is established. The modes of failure for soft and hard rock strata are analyzed, the computational formula of the downward thrust for each anti-inclined rock stratum is derived, and the stability safety factor of each rock stratum is defined. A theoretical computational method for determining the potentially most dangerous failure surface of soft–hard-interbedded anti-inclined rock slope is proposed. By comparing with the existing research results, the theoretical solving method proposed in this study can well solve the location of the potentially most dangerous failure surface of soft–hard-interbedded anti-inclined rock slope. The potentially most dangerous failure surface of this kind of slope is approximately planar, and the angle between it and the normal plane of the rock strata is an acute angle within 30°. It provides theoretical support for the stability analysis of this kind of slope.

Weakened circadian activity rhythms (CARs) were associated with mild cognitive impairment (MCI) in the general population. However, it remains unclear among pneumoconiosis patients. We aimed to address this knowledge gap. This cross-sectional study comprised 186 male pneumoconiosis patients (71.3 ± 7.8 years) and 208 healthy community men. Actigraphy was used to determine CARs parameters (percent rhythm, amplitude, MESOR, and acrophase). Values below the corresponding medians of the CARs parameters represented weakened CARs. The Cantonese version of Mini-Mental State Examination (CMMSE) was used to assess cognitive function, MCI, and the composite outcome of MCI plus cognitive impairment. Compared with the community referents, pneumoconiosis patients had worse cognition and dampened CARs. Compared with the community referents or pneumoconiosis patients with robust circadian rhythm, pneumoconiosis patients with weakened circadian rhythm were consistently associated with increased risk of MCI and the composite outcome. However, significant association was only observed between MESOR and the composite outcome (adjusted OR = 1.99, 95%: 1.04–3.81). A delayed phase of CARs was insignificantly associated with MCI and the composite outcome. Our findings showed that weakened CARs were associated with worse cognitive function among male pneumoconiosis workers. Intervention in improving CARs may mitigate cognitive deterioration in male pneumoconiosis workers.

We propose a hetero-nano-fin structure to further improve the efficiency of Pancharatnam–Berry phase metasurfaces. Two hetero-nano-fin types, MgF 2 /GaN and MgF 2 /Nb 2 O 5 , were investigated. The overall polarization conversion efficiency (PCE) improved from 52.7 to 54% for the MgF 2 /GaN nano-fin compared with the bare GaN nano-fin. The overall PCE of the Nb 2 O 5 nano-fin was 1.7 times higher than that of the GaN nano-fin. The overall PCE improved from 92.4% up to 96% after the application of MgF 2 antireflection. Moreover, the antireflection improves efficiency by an average of 4.3% in wavelengths from 450 to 700 nm. Although the increment of energy seems minimal, antireflection is crucial for a metasurface, not only enhancing efficiency but also reducing background signal of a meta-device.

Soil contamination by Pb can result from different anthropogenic sources such as lead-based paints, gasoline, pesticides, coal burning, mining, among others. This work aimed to evaluate the potential of P-loaded biochar (Biochar-based slow-release P fertilizer) to remediate a Pb-contaminated soil. In addition, we aim to propose a biomonitoring alternative after soil remediation. First, rice husk-derived biochar was obtained at different temperatures (450, 500, 550, and 600 °C) (raw biochars). Then, part of the resulting material was activated. Later, the raw biochars and activated biochars were immersed in a saturated KH 2 PO 4 solution to produce P-loaded biochars. The ability of materials to immobilize Pb and increase the bioavailability of P in the soil was evaluated by an incubation test. The materials were incorporated into doses of 0.5, 1.0, and 2.0%. After 45 days, soil samples were taken to biomonitor the remediation process using two bioindicators: a phytotoxicity test and enzyme soil activity. Activated P-loaded biochar produced at 500 °C has been found to present the best conditions for soil Pb remediation. This material significantly reduced the bioavailability of Pb and increased the bioavailability of P. The phytotoxicity test and the soil enzymatic activity were significantly correlated with the decrease in bioavailable Pb but not with the increase in bioavailable P. Biomonitoring using the phytotoxicity test is a promising alternative for the evaluation of soils after remediation processes.

Increasing the intensity of tumor treating fields (TTF) within a tumor bed improves clinical efficacy, but reaching sufficiently high field intensities to achieve growth arrest remains challenging due in part to the insulating nature of the cranium. Using MRI-derived finite element models (FEMs) and simulations, we optimized an exhaustive set of intracranial electrode locations to obtain maximum TTF intensities in three clinically challenging high-grade glioma (HGG) cases (i.e., thalamic, left temporal, brainstem). Electric field strengths were converted into therapeutic enhancement ratios (TER) to evaluate the predicted impact of stimulation on tumor growth. Concurrently, conventional transcranial configurations were simulated/optimized for comparison. Optimized intracranial TTF were able to achieve field strengths that have previously been shown capable of inducing complete growth arrest, in 98–100% of the tumor volumes using only 0.54–0.64 A current. The reconceptualization of TTF as a targeted, intracranial therapy has the potential to provide a meaningful survival benefit to patients with HGG and other brain tumors, including those in surgically challenging, deep, or anatomically eloquent locations which may preclude surgical resection. Accordingly, such an approach may ultimately represent a paradigm shift in the use of TTFs for the treatment of brain cancer.

Lung cancer is the second most common cancer in Taiwan. After Taiwan implemented the Tobacco Hazards Prevention Act in 1997, smoking rates declined. However, the incidence rates of lung cancer for both sexes are still increasing, possibly due to risk factors other than smoking. We used age–period–cohort analysis to examine the secular trends of lung cancer incidence rates by histological type in Taiwan. A stabilized kriging method was employed to map these lung cancer incidence rates. Lung adenocarcinoma incidence rates increased, but lung squamous cell carcinoma incidence rates decreased, for both the sexes in recent birth cohorts, particularly in women. In Taiwan, the hotspots of lung adenocarcinoma incidence rates were in the northern, northeastern, and western coastal areas; the incidence rates increased rapidly in the western and southern coastal regions and southern mountainous regions. The high incidence rates of lung squamous cell carcinoma in men were in the southwestern and northeastern coastal areas. The incidence rates rapidly increased in the central and southern coastal and mountainous regions. For both sexes in Taiwan, lung squamous cell carcinoma incidence rates declined from 1997 to 2017, but lung adenocarcinoma increased. The increased incidence rates of lung adenocarcinoma may be related to indoor and outdoor air pollution. Some areas in Taiwan have increasing lung cancer incidence rates, including the northwestern and southern coasts and mountains, and warrant particular attention.

The black-box nature of deep neural networks (DNN) has brought to attention the issues of transparency and fairness. Deep Reinforcement Learning (Deep RL or DRL), which uses DNN to learn its policy, value functions etc, is thus also subject to similar concerns. This paper proposes a way to circumvent the issues through the bottom-up design of neural networks with detailed interpretability, where each neuron or layer has its own meaning and utility that corresponds to humanly understandable concept. The framework introduced in this paper is called the Self Reward Design (SRD), inspired by the Inverse Reward Design, and this interpretable design can (1) solve the problem by pure design (although imperfectly) and (2) be optimized like a standard DNN. With deliberate human designs, we show that some RL problems such as lavaland and MuJoCo can be solved using a model constructed with standard NN components with few parameters. Furthermore, with our fish sale auction example, we demonstrate how SRD is used to address situations that will not make sense if black-box models are used, where humanly-understandable semantic-based decision is required.

Norovirus infections are a leading cause of acute gastroenteritis outbreaks worldwide, with genotypes GII.2 and GII.4 being the most prevalent. The aim of this study was to compare the characteristics of GII.2 and GII.4 norovirus outbreaks reported in Catalonia in closed or semi-closed institutions in 2017 and 2018. The epidemiological and clinical characteristics of GII.2 and GII.4 outbreaks were compared using the chi-square test or Fisher's exact test for categorical variables and the Mann–Whitney U test for continuous variables. Odds ratios and their 95% confidence intervals were estimated. 61 outbreaks were reported: GII.4 was the causative agent in 12 outbreaks (30%) and GII.2 in 9 outbreaks (22.5%). GII.2 outbreaks were detected more frequently in schools or summer camps (66.7%) and GII.4 outbreaks in nursing homes (91.7%) ( p = 0.01). Ninety-three people were affected in GII.2 outbreaks and 94 in GII.4 outbreaks. The median age was 15 years (range: 1–95 years) in GII.2 outbreaks and 86 years (range: 0–100 years) in GII.4 outbreaks ( p < 0.001). Nausea, abdominal pain, and headache were observed more frequently in persons affected by GII.2 outbreaks ( p < 0.05). Symptomatic cases presented a higher viral load suggestive of greater transmission capacity, although asymptomatic patients presented relevant loads indicative of transmission capacity.

Advanced deep learning architectures consist of tens of fully connected and convolutional hidden layers, currently extended to hundreds, are far from their biological realization. Their implausible biological dynamics relies on changing a weight in a non-local manner, as the number of routes between an output unit and a weight is typically large, using the backpropagation technique. Here, a 3-layer tree architecture inspired by experimental-based dendritic tree adaptations is developed and applied to the offline and online learning of the CIFAR-10 database. The proposed architecture outperforms the achievable success rates of the 5-layer convolutional LeNet. Moreover, the highly pruned tree backpropagation approach of the proposed architecture, where a single route connects an output unit and a weight, represents an efficient dendritic deep learning.

The total synthesis of four novel mono-methoxy and hydroxyl substituted ring-A dihydronarciclasine derivatives enabled identification of the 7-hydroxyl derivative as a potent and selective antiviral agent targeting SARSCoV-2 and HSV-1. The concentration of this small molecule that inhibited HSV-1 infection by 50% (IC50), determined by using induced pluripotent stem cells (iPCS)-derived brain organ organoids generated from two iPCS lines, was estimated to be 0.504 µM and 0.209 µM. No significant reduction in organoid viability was observed at concentrations up to 50 mM. Genomic expression analyses revealed a significant effect on host-cell innate immunity, revealing activation of the integrated stress response via PERK kinase upregulation, phosphorylation of eukaryotic initiation factor 2α (eIF2α) and type I IFN, as factors potentiating multiple host-defense mechanisms against viral infection. Following infection of mouse eyes with HSV-1, treatment with the compound dramatically reduced HSV-1 shedding in vivo.

Genomic information on alfalfa adaptation to long-term grazing is useful for alfalfa genetic improvement. In this study, 14 alfalfa populations were collected from long-term grazing sites (> 25 years) across four soil zones in western Canada. Alfalfa cultivars released between 1926 and 1980 were used to compare degree of genetic variation of the 14 populations. Six agro-morphological and three nutritive value traits were evaluated from 2018 to 2020. The genotyping-by-sequencing (GBS) data of the alfalfa populations and environmental data were used for genotype-environment association (GEA). Both STRUCTURE and UPGMA based on 19,853 SNPs showed that the 14 alfalfa populations from long-term grazing sites had varying levels of parentages from alfalfa sub-species Medicago sativa and M. falcata . The linear regression of STRUCTURE membership probability on phenotypic data indicated genetic variations of forage dry matter yield, spring vigor and plant height were low, but genetic variations of regrowth, fall plant height, days to flower and crude protein were still high for the 14 alfalfa populations from long-term grazing sites. The GEA identified 31 SNPs associated with 13 candidate genes that were mainly associated with six environmental factors of. Candidate genes underlying environmental factors were associated with a variety of proteins, which were involved in plant responses to abiotic stresses, i.e., drought, cold and salinity-alkali stresses.

Sarcopenia is a common complication in patients with chronic liver disease (CLD); however, the progression of sarcopenia over the course of CLD is unclear. The present study therefore determined the natural course of the progression of sarcopenia in patients with CLD and the effect of liver cirrhosis (LC) on this progression. This observational study analyzed patients with chronic hepatitis (CH) (n = 536) and LC (n = 320) who underwent evaluations of the grip strength and skeletal muscle mass of the arms, trunk, and legs for sarcopenia between 2016 and 2021. A bioelectrical impedance analysis was used to evaluate skeletal muscle mass. The annual rate of change (%/year) in two tests were compared between patients with CH and LC. The annual rates of change in grip strength and skeletal muscle of arms, trunk, and legs of patients with CH and LC were − 0.84% vs. − 2.93%, − 0.54% vs. − 1.71%, − 0.43% vs. − 1.02%, and − 0.76% vs. − 1.70% for men and − 0.12% vs. − 1.71%, − 0.66% vs. − 1.71%, − 0.49% vs. − 1.31%, and − 0.76% vs. − 1.54% for women, respectively. The progression of sarcopenia was greater in LC patients than in CH patients and that the decrease in grip strength was most prominent in the progression of sarcopenia in patients with LC.

In this study, formaldehyde-urea prepolymer (FUP) were synthesized, which were used to modify the raw lacquer (RL) and this composition named LF, while the basic properties of the RL were tested. Thermal gravimetric (TG) analysis and scanning electron microscopy (SEM) were used to analyze the degradative characteristics and the surface morphology of RL before and after modification. The result indicated that FUP can significantly improve the performance of RL. The drying time of the LF is significantly shortened, the gloss, the pencil hardness, and the impact performance are significantly enhanced at the same time. TG analysis and thermal decomposition kinetics analysis illustrated that the thermal stability and the activation energy of LF2 were stronger than that of RL. In addition, SEM analysis illustrated that the surface smoothness of RL were also improved.

Oil viscosity plays a prominent role in all areas of petroleum engineering, such as simulating reservoirs, predicting production rate, evaluating oil well performance, and even planning for thermal enhanced oil recovery (EOR) that involves fluid flow calculations. Experimental methods of determining oil viscosity, such as the rotational viscometer, are more accurate than other methods. The compositional method can also properly estimate oil viscosity. However, the composition of oil should be determined experimentally, which is costly and time-consuming. Therefore, the occasional inaccessibility of experimental data may make it inevitable to look for convenient methods for fast and accurate prediction of oil viscosity. Hence, in this study, the error in viscosity prediction has been minimized by taking into account the amount of dissolved gas in oil (solution gas–oil ratio: Rs) as a representative of oil composition along with other conventional black oil features including temperature, pressure, and API gravity by employing recently developed machine learning methods based on the gradient boosting decision tree (GBDT): extreme gradient boosting (XGBoost), CatBoost, and GradientBoosting. Moreover, the advantage of the proposed method lies in its independence to input viscosity data in each pressure region/stage. The results were then compared with well-known correlations and machine-learning methods employing the black oil approach applying least square support vector machine (LSSVM) and compositional approach implementing decision trees (DTs). XGBoost is offered as the best method with its greater precision and lower error. It provides an overall average absolute relative deviation (AARD) of 1.968% which has reduced the error of the compositional method by half and the black oil method (saturated region) by five times. This shows the proper viscosity prediction and corroborates the applied method's performance.

We assessed the impact of the first wave of COVID-19 pandemic on non-COVID hospital admissions, non-COVID mortality, factors associated with non-COVID mortality, and changes in the profile of non-COVID patients admitted to hospital. We used the Spanish Minimum Basic Data Set with diagnosis grouped according to the Diagnostic Related Groups. A total of 10,594 patients (3% COVID-19; 97% non-COVID) hospitalised during the first wave in 2020 (27-February/07-June) were compared with those hospitalised within the same dates of 2017–2019 (average annual admissions: 14,037). We found a decrease in non-COVID medical (22%) and surgical (33%) hospitalisations and a 25.7% increase in hospital mortality among non-COVID patients during the first pandemic wave compared to pre-pandemic years. During the officially declared sub-period of excess mortality in the area (17-March/20-April, in-hospital non-COVID mortality was even higher (58.7% higher than the pre-pandemic years). Non-COVID patients hospitalised during the first pandemic wave (compared to pre-pandemic years) were older, more frequently men, with longer hospital stay and increased disease severity. Hospitalisation during the first pandemic wave in 2020, compared to hospitalisation during the pre-pandemic years, was an independent risk factor for non-COVID mortality (HR 1.30, 95% CI 1.07–1.57, p = 0.008), reflecting the negative impact of the pandemic on hospitalised patients.

Social insects are very successful invasive species, and the continued increase of global trade and transportation has exacerbated this problem. The yellow-legged hornet, Vespa velutina nigrithorax (henceforth Asian hornet), is drastically expanding its range in Western Europe. As an apex insect predator, this hornet poses a serious threat to the honey bee industry and endemic pollinators. Current suppression methods have proven too inefficient and expensive to limit its spread. Gene drives might be an effective tool to control this species, but their use has not yet been thoroughly investigated in social insects. Here, we built a model that matches the hornet’s life history and modelled the effect of different gene drive scenarios on an established invasive population. To test the broader applicability and sensitivity of the model, we also incorporated the invasive European paper wasp Polistes dominula. We find that, due to the haplodiploidy of social hymenopterans, only a gene drive targeting female fertility is promising for population control. Our results show that although a gene drive can suppress a social wasp population, it can only do so under fairly stringent gene drive-specific conditions. This is due to a combination of two factors: first, the large number of surviving offspring that social wasp colonies produce make it possible that, even with very limited formation of resistance alleles, such alleles can quickly spread and rescue the population. Second, due to social wasp life history, infertile individuals do not compete with fertile ones, allowing fertile individuals to maintain a large population size even when drive alleles are widespread. Nevertheless, continued improvements in gene drive technology may make it a promising method for the control of invasive social insects in the future.

Considering that the subtropical highs and tropical convections are observed as negative and positive vorticities respectively, the large-scale features of the atmospheric environment can be effectively represented using streamfunctions as defined by the Laplacian. By investigating the geographical patterns of streamfunctions from different modes of environmental variability, this study conceptualizes how the subtropical high expands and the region for tropical convections migrates in the western North Pacific. It is confirmed that, owing to the expansion of the subtropical high, the limited ocean area for tropical convections even bounded by the equator becomes narrower in the “La Niña mode” than that in the “El Niño mode”. This study finds that a warmer environment is likely to further expand the subtropical high to the west, and then the westernmost shift in the region for tropical convections appears in the “warmer La Niña mode”. A linear perspective suggests that every warmer La Niña environment could be one that people have scarcely experienced before.

The zizphus seeds are considered as a biomaterial residues that has been used for removing of organic industrial waste such as 2-((10-octyl-9,10-dihydroanthracene-2-yl) methylene) malononitrile (PTZS-CN) dye from aqueous solutions utilizing graphene oxide-Ziziphus (GO-Ziziphus). A batch study explored the impacts of various experimental circumstances, including solution pH, initial dye concentration, temperature, and contact time. General order, nonlinear pseudo-first order and pseudo-second order, elvoich model and intraparticiple diffusion were utilized to analyze the kinetic data. The adsorption kinetics of dye onto GO-ziziphus adsorption was best mentioned by nonlinear pseudo-first order. Similarly, the intra-particle diffusion plots revealed one exponential line throughout the adsorption process. The Freundlich, Dubinin-Radushkevich, and Langmuir models were employed to examine isothermal data. It provided the best fit of the dye adsorption isothermal data onto GO-ziziphus Freundlich models. Besides, the calculated free energies showed that the adsorption progression was physical adsorption. Thermodynamic calculations revealed that dye adsorption onto GO-ziziphus was exothermic and spontaneous. The combined results indicated that GO-ziziphus powder might be used to treat dye-rich wastewater effectively.

Autophagy induction by starvation has been shown to enhance lysosomal delivery to mycobacterial phagosomes, resulting in the restriction of the Mycobacterium tuberculosis reference strain H37Rv. In contrast to H37Rv, our previous study showed that strains belonging to the notorious M. tuberculosis Beijing genotype could evade autophagic elimination. Our recent RNA-Seq analysis also discovered that the autophagy-resistant M. tuberculosis Beijing strain (BJN) evaded autophagic control by upregulating the expression of Kxd1, a BORC complex component, and Plekhm2, both of which function in lysosome positioning towards the cell periphery in host macrophages, thereby suppressing enhanced lysosomal delivery to its phagosome and sparing the BJN from elimination as a result. In this work, we further characterised the other specific components of the BORC complex, BORC5-8, and Kinesin proteins in autophagy resistance by the BJN. Depletion of BORCS5-8 and Kinesin-1, but not Kinesin-3, reverted autophagy avoidance by the BJN, resulting in increased lysosomal delivery to the BJN phagosomes. In addition, the augmented lysosome relocation towards the perinuclear region could now be observed in the BJN-infected host cells depleted in BORCS5-8 and Kinesin-1 expressions. Taken together, the data uncovered new roles for BORCS5-8 and Kinesin-1 in autophagy evasion by the BJN.

In recent years, research on transducers and system architectures for self-powered devices has gained attention for their direct impact on the Internet of Things in terms of cost, power consumption, and environmental impact. The concept of a wireless sensor node that uses a single thermoelectric generator as a power source and as a temperature gradient sensor in an efficient and controlled manner is investigated. The purpose of the device is to collect temperature gradient data in data centres to enable the application of thermal-aware server load management algorithms. By using a maximum power point tracking algorithm, the operating point of the thermoelectric generator is kept under control while using its power-temperature transfer function to measure the temperature gradient. In this way, a more accurate measurement of the temperature gradient is achieved while harvesting energy with maximum efficiency. The results show the operation of the system through its different phases as well as demonstrate its ability to efficiently harvest energy from a temperature gradient while measuring it. With this system architecture, temperature gradients can be measured with a maximum error of 0.14 ∘C and an efficiency of over 92% for values above 13 ∘C and a single transducer.

Increasing thermal performance and preventing heat loss are very important in energy conversion systems, especially for new and complex products that exacerbate this need. Therefore, to solve this challenge, a trapezoidal cavity with a wavy top wall containing water/ethylene glycol GO–Al2O3 nanofluid is simulated using Galerkin finite element method. The effects of physical parameters affecting thermal performance and fluid flow, including porosity (ℇ), thermal radiation (Rd), magnetic field angle (α), Rayleigh number (Ra) and Hartmann number (Ha), are investigated in the determined ratios. The results of applied boundary conditions showed that the optimal values for Ra, Ha, ℇ, Rd and α are 1214.46, 2.86, 0.63, 0.24 and 59.35, respectively. Considering that changes in radiation have little effect on streamlines and isothermal lines. Optimization by RSM and Taguchi integration resulted in optimal Nu detection. It provided a correlation for the average Nu based on the investigated determinants due to the conflicting influence of the study factors, which finally calculated the highest average Nusselt number of 3.07. Therefore, the ideal design, which is the primary goal of this research, increases the thermal performance.

Magnetic Resonance Imaging of hard biological tissues is very challenging due to small proton abundance and ultra-short T2 decay times, especially at low magnetic fields, where sample magnetization is weak. While several pulse sequences, such as Ultra-short Echo Time (UTE), Zero Echo Time (ZTE) and SWeep Imaging with Fourier Transformation (SWIFT), have been developed to cope with ultra-short lived MR signals, only the latter two hold promise of imaging tissues with sub-millisecond T2 times at low fields. All these sequences are intrinsically volumetric, thus 3D, because standard slice selection using a long soft radio-frequency pulse is incompatible with ultra-short lived signals. The exception is UTE, where double half pulses can perform slice selection, although at the cost of doubling the acquisition time. Here we demonstrate that spin-locking is a versatile and robust method for slice selection for ultra-short lived signals, and present three ways of combining this pulse sequence with ZTE imaging of the selected slice. With these tools, we demonstrate slice-selected 2D ex vivo imaging of the hardest tissues in the body at low field (260 mT) within clinically acceptable times.

The subsistence practices of Later Stone Age (LSA) foragers and herders living in Namaqualand South Africa are often difficult to differentiate based on their archaeological signatures but characterizing their dietary choices is vital to understand the economic importance of domesticates. However, ethnohistoric accounts have provided information on the cooking/boiling of marine mammal fat, mutton, plants, and milk by early herders and foragers across the Western Cape. To further investigate these reports, we use lipid residue analysis to characterize 106 potsherds from four open-air LSA sites, spanning in time from the early first millennium to the late second millennium AD. Two sites (SK2005/057A, SK2006/026) are located on the Atlantic coast whereas sites Jakkalsberg K and Jakkalsberg M are located further inland on the southern bank of the Orange River. Notably, at the coastal sites, the presence of marine biomarkers suggests the intensive and/or specialized processing of marine products in many vessels. The dominance of ruminant carcass products at inland sites and probable sheep remains confirms the importance of stockkeeping. Furthermore, and in good agreement with ethnohistoric accounts for its use, our results provide the first direct chemical evidence for the use of dairy products in LSA western South Africa.

Thrombocytopenia is the most frequent haematologic disorder in patients with cirrhosis, and it is perceived as a contributory factor for bleeding events. Cirrhosis patients with portal hypertension (PHT) is often accompanied with mild to moderate thrombocytopenia when they treated with transjugular intrahepatic portosystemic shunt (TIPS). To address whether the risk of variceal hemorrhage after TIPS varies with different platelet count in patients with normal platelet count and thrombocytopenia, we conducted the retrospective controlled study to evaluate the association of platelet count with the risk of variceal bleeding after TIPS. 304 patients were selected to the study. Propensity score matching was performed to adjust for potential selection bias. 63 patients from each group could be paired. Cox proportional hazards models were used to evaluate the association between platelet and variceal bleeding after TIPS. Platelet counts of two groups are 185.0 ± 98.7 × 109/L (normal platelet count) and 70.6 ± 39.3 × 109/L (thrombocytopenia) respectively. The bleeding rates of two groups in overall cohort are 10.9% (normal platelet count) and 12.9% (thrombocytopenia). After matched, the bleeding rates of two groups are 11.1% (normal platelet count) and 14.3% (thrombocytopenia) There was no statistically significant difference in bleeding rates between the two groups, either in the whole cohort (P = 0.671) or in the matched cohort (P = 0.593). Platelet count was not associated with bleeding events after TIPS (hazard ratio (HR) 95% confidence interval: 0.986–1.005, P = 0.397 in normal platelet count and 95% confidence interval: 0.968–1.020, P = 0.648 in thrombocytopenia). Thrombocytopenia in patients with cirrhosis was not associated with the risk of variceal bleeding episodes post-TIPS. Thrombocytopenia should not be viewed as an absolute contraindication for TIPS.

Due to digitalization, small and medium-sized enterprises (SMEs) have significantly enhanced their efficiency and productivity in the past few years. The process to automate SME transaction execution is getting highly multifaceted as the number of stakeholders of SMEs is connecting, accessing, exchanging, adding, and changing the transactional executions. The balanced lifecycle of SMEs requires partnership exchanges, financial management, manufacturing, and productivity stabilities, along with privacy and security. Interoperability platform issue is another critical challenging aspect while designing and managing a secure distributed Peer-to-Peer industrial development environment for SMEs. However, till now, it is hard to maintain operations of SMEs' integrity, transparency, reliability, provenance, availability, and trustworthiness between two different enterprises due to the current nature of centralized server-based infrastructure. This paper bridges these problems and proposes a novel and secure framework with a standardized process hierarchy/lifecycle for distributed SMEs using collaborative techniques of blockchain, the internet of things (IoT), and artificial intelligence (AI) with machine learning (ML). A blockchain with IoT-enabled permissionless network structure is designed called “B-SMEs” that provides solutions to cross-chain platforms. In this, B-SMEs address the lightweight stakeholder authentication problems as well. For that purpose, three different chain codes are deployed. It handles participating SMEs' registration, day-to-day information management and exchange between nodes, and analysis of partnership exchange-related transaction details before being preserved on the blockchain immutable storage. Whereas AI-enabled ML-based artificial neural networks are utilized, the aim is to handle and optimize day-to-day numbers of SME transactions; so that the proposed B-SMEs consume fewer resources in terms of computational power, network bandwidth, and preservation-related issues during the complete process of SMEs service deliverance. The simulation results present highlight the benefits of B-SMEs, increases the rate of ledger management and optimization while exchanging information between different chains, which is up to 17.3%, and reduces the consumption of the system’s computational resources down to 9.13%. Thus, only 14.11% and 7.9% of B-SME’s transactions use network bandwidth and storage capabilities compared to the current mechanism of SMEs, respectively.

Hearing loss has been associated with individual cardiovascular disease (CVD) risk factors and, to a lesser extent, CVD risk metrics. However, these relationships are understudied in clinical populations. We conducted a retrospective study of electronic health records to evaluate the relationship between hearing loss and CVD risk burden. Hearing loss was defined as puretone average (PTA0.5,1,2,4) > 20 dB hearing level (HL). Optimal CVD risk was defined as nondiabetic, nonsmoking, systolic blood pressure (SBP) < 120 and diastolic (D)BP < 80 mm Hg, and total cholesterol < 180 mg/dL. Major CVD risk factors were diabetes, smoking, hypertension, and total cholesterol ≥ 240 mg/dL or statin use. We identified 6332 patients (mean age = 62.96 years; 45.5% male); 64.0% had hearing loss. Sex-stratified logistic regression adjusted for age, noise exposure, hearing aid use, and body mass index examined associations between hearing loss and CVD risk. For males, diabetes, hypertension, smoking, and ≥ 2 major CVD risk factors were associated with hearing loss. For females, diabetes, smoking, and ≥ 2 major CVD risk factors were significant risk factors. Compared to those with no CVD risk factors, there is a higher likelihood of hearing loss in patients with ≥ 2 major CVD risk factors. Future research to better understand sex dependence in the hearing loss-hypertension relationship is indicated.

Epithelial cells control a variety of immune cells by secreting cytokines to maintain tissue homeostasis on mucosal surfaces. Regulatory T (Treg) cells are essential for immune homeostasis and for preventing tissue inflammation; however, the precise molecular mechanisms by which epithelial cell-derived cytokines function on Treg cells in the epithelial tissues are not well understood. Here, we show that peripheral Treg cells preferentially respond to thymic stromal lymphoprotein (TSLP). Although TSLP does not affect thymic Treg differentiation, TSLP receptor-deficient induced Treg cells derived from naïve CD4+ T cells are less activated in an adoptive transfer model of colitis. Mechanistically, TSLP activates induced Treg cells partially through mTORC1 activation and fatty acid uptake. Thus, TSLP modulates the activation status of induced Treg through the enhanced uptake of fatty acids to maintain homeostasis in the large intestine.

The research of novel implantable medical devices is one of the most attractive, yet complex areas in the biomedical field. The design and development of sufficiently small devices working in an in vivo environment is challenging but successful encapsulation of such devices is even more so. Industry-standard methods using glass and titanium are too expensive and tedious, and epoxy or silicone encapsulation is prone to water ingress with cable feedthroughs being the most frequent point of failure. This paper describes a universal and straightforward method for reliable encapsulation of circuit boards that achieves ISO10993 compliance. A two-part PVDF mold was machined using a conventional 3-axis machining center. Then, the circuit board with a hermetic feedthrough was placed in the mold and epoxy resin was injected into the mold under pressure to fill the cavity. Finally, the biocompatibility was further enhanced with an inert P3HT polymer coating which can be easily formulated into an ink. The biocompatibility of the encapsulants was assessed according to ISO10993. The endurance of the presented solution compared to silicone potting and epoxy potting was assessed by submersion in phosphate-buffered saline solution at 37 °C. The proposed method showed superior results to PDMS and simple epoxy potting.

The ecological conservation of large rivers is impossible unless immediate attention is given to protecting their small tributaries at local levels. The natural boundaries of large river basins are shrinking because their tributaries and streams of different orders are disappearing at an unprecedented rate. Delineation of the fixed administrative boundaries (AB) to protect the natural boundary of small rivers and their classification into appropriate threatened categories, the present study was carried out on the 54.08 km long Banki River in the Ganga River basin. The > 70% irreversible loss in the number of streams (Nu), length of streams (Lu), and drainage density (Dd) resulted in the conversion of the 6th order Banki into the 4th order river. The extreme morphometric changes result in the Banki watershed being under the “Critically Endangered” category. The drainage density ratio (DdR) and mean stream width (Msw) were used to determine the width of AB (WAB). The “River Red List Categories and Criteria” are being proposed to strengthen global initiatives at the local levels to protect and conserve inland water bodies and transboundary rivers.

Increased intra-individual variability of a variety of biomarkers is generally associated with poor health and reflects physiological dysregulation. Correlations among these biomarker variabilities should then represent interactions among heterogeneous biomarker regulatory systems. Herein, in an attempt to elucidate the network structure of physiological systems, we probed the inter-variability correlations of 22 biomarkers. Time series data on 19 blood-based and 3 hemodynamic biomarkers were collected over a one-year period for 334 hemodialysis patients, and their variabilities were evaluated by coefficients of variation. The network diagram exhibited six clusters in the physiological systems, corresponding to the regulatory domains for metabolism, inflammation, circulation, liver, salt, and protein. These domains were captured as latent factors in exploratory and confirmatory factor analyses (CFA). The 6-factor CFA model indicates that dysregulation in each of the domains manifests itself as increased variability in a specific set of biomarkers. Comparison of a diabetic and non-diabetic group within the cohort by multi-group CFA revealed that the diabetic cohort showed reduced capacities in the metabolism and salt domains and higher variabilities of the biomarkers belonging to these domains. The variability-based network analysis visualizes the concept of homeostasis and could be a valuable tool for exploring both healthy and pathological conditions.

The interest in active packaging for extending food shelf life has increased lately. Moreover, the negative impact of synthetic plastic wastes on the environmental motivated the researchers to seek for bio-based alternatives. In this context, active packaging film made of a composite composed of Lepidium sativum extract (LSE), polyvinyl alcohol (PVA), and a fixed amount of hyperbranched polyamide amine (PAMAM) were prepared. The chemical, thermal, and mechanical properties of the film were investigated. Moreover, we examined the extract’s constituents and antioxidant properties. Cheddar cheese samples were coated with films of different compositions. The samples coated with active packaging films showed a longer preservation time of up to 4 weeks compared to other samples, which noticeably deteriorated. The films showed potent antimicrobial activity against five food-borne bacteria: three gram-negative bacteria including Escherichia coli O157.H7, Pseudomonas aeruginosa, and Salmonella Typhimurium, and two gram-positive bacteria, Listeria monocytogenes, and Staphylococcus aureus. Applying PVA films containing LSE improved the microbiological quality and delayed the visible decay of cheddar cheese. The oxidizability of the fat extracted from different cheese samples was 0.40–0.98, confirming oxidation resistance. Finally, cheese samples coated with treated films were protected from forming trans fats compared to other samples, demonstrating the effectiveness of modified films as antioxidant, antimicrobial, and food-preserving packaging.

The incidence of thyroid nodules is increasing year by year. Accurate determination of benign and malignant nodules is an important basis for formulating treatment plans. Ultrasonography is the most widely used methodology in the diagnosis of benign and malignant nodules, but diagnosis by doctors is highly subjective, and the rates of missed diagnosis and misdiagnosis are high. To improve the accuracy of clinical diagnosis, this paper proposes a new diagnostic model based on deep learning. The diagnostic model adopts the diagnostic strategy of localization-classification. First, the distribution laws of the nodule size and nodule aspect ratio are obtained through data statistics, a multiscale localization network structure is a priori designed, and the nodule aspect ratio is obtained from the positioning results. Then, uncropped ultrasound images and nodule area image are correspondingly input into a two-way classification network, and an improved attention mechanism is used to enhance the feature extraction performance. Finally, the deep features, the shallow features, and the nodule aspect ratio are fused, and a fully connected layer is used to complete the classification of benign and malignant nodules. The experimental dataset consists of 4021 ultrasound images, where each image has been labeled under the guidance of doctors, and the ratio of the training set, validation set, and test set sizes is close to 3:1:1. The experimental results show that the accuracy of the multiscale localization network reaches 93.74%, and that the accuracy, specificity, and sensitivity of the classification network reach 86.34%, 81.29%, and 90.48%, respectively. Compared with the champion model of the TNSCUI 2020 classification competition, the accuracy rate is 1.52 points higher. Therefore, the network model proposed in this paper can effectively diagnose benign and malignant thyroid nodules.

We examined the potential mediating roles of anxiety and loneliness on the association of concurrent food insecurity (FI) and being bullied (BB) with suicidal behavior (SB) in Eswatini, a lower-middle-income country. We used data from the Global School-based Student Health Survey (GSHS; N = 3264), which employed a two-stage cluster sampling: first, 25 schools were selected based on the proportionate probability of enrollment; second, classes were randomly selected. A self-reported 84-item GSHS questionnaire was used to collect data for students aged 13–17 years. FI was measured by requesting students to recall how often they went hungry because of a lack of food at home in the 30 days before the study. Multiple logistic regressions and binary mediation function was applied to examine mediating factors of SB. The prevalence of SB, FI, and BB among adolescents was 27.5%, 7.7%, and 30.2%, respectively. Moreover, the relationship between FI and BB with SB was partly (approximately 24%) mediated by anxiety and loneliness. Our results highlight the mediating roles of anxiety and loneliness in suicidal adolescents who experience FI and BB. In conclusion, interventions for alleviating SB in high-risk adolescents experiencing FI and BB should also be aimed at ameliorating anxiety and loneliness.

In the current scenario, scaling up the microbial production of nanoparticles with diverse biological applications is an emerging prospect for NPs’ sustainable industry. Thus, this paper was conducted to develop a suitable applicative process for the myco-fabrication of cobalt-ferrite (CoFeNPs), selenium (SeNPs), and zinc oxide (ZnONPs) nanoparticles. A strain improvement program using gamma irradiation mutagenesis was applied to improve the NPs-producing ability of the fungal strains. The achieved yields of CoFeNPs, SeNPs, and ZnONPs were intensified by a 14.47, 7.85, and 22.25-fold increase from the initial yield following gamma irradiation and isolation of stable mutant strains. The myco-fabricated CoFeNPs, SeNPs, and ZnONPs were then exploited to study their wound healing, and anti-inflammatory. In addition, the acetylcholinesterase inhibition activities of the myco-fabricated NPs were evaluated and analyzed by molecular docking. The obtained results confirmed the promising wound healing, anti-inflammatory, and acetylcholinesterase inhibition potentials of the three types of NPs. Additionally, data from analyzing the interaction of NPs with acetylcholinesterase enzyme by molecular docking were in conformation with the experimental data.

Together, the Yinggehai and Qiongdongnan basins have received a large amount of terrigenous sediments, but the provenance evolution of Cenozoic sediments in the two basins remains disputable. Combined with previous studies in the Yinggehai and Qiongdongnan basins, the elemental geochemistry of Oligocene to Pliocene sediment samples in the junction area of the two basins were analyzed to explore the tectonic implications, parent rock characteristics, and provenance evolution of the two basins during the Cenozoic. The results reveal that all the sediment samples were derived from continental island arc to passive continental margin settings. The light REE enrichment and stable content of heavy REE with large negative Eu anomalies indicate that they were probably derived from Hainan Island. The reconstructed provenance evolution model showed that the Red River Source (RRS) provided sedimentary materials for the Central Depression of Yinggehai Basin from the Oligocene to the Pliocene, and Hainan Island Source (HIS) was also one of the sources for sediments deposited in the Central Depression of Yinggehai Basin during the Miocene. However, most of the sediments preserved in the Yingdong Slope and Qiongdongnan Basin were derived from the HIS from the Oligocene to the Pliocene, and sediments deposited in the Yingdong Slope were also derived from the RRS during the Miocene. Furthermore, the junction area of the two basins had a mixed source of the RRS and HIS during the Cenozoic.

In computer-aided diagnosis (CAD), diagnosing untrained diseases as known categories will cause serious medical accidents, which makes it crucial to distinguish the new class (open set) meanwhile preserving the known classes (closed set) performance so as to enhance the robustness. However, how to accurately define the decision boundary between known and unknown classes is still an open problem, as unknown classes are never seen during the training process, especially in medical area. Moreover, manipulating the latent distribution of known classes further influences the unknown’s and makes it even harder. In this paper, we propose the Centralized Space Learning (CSL) method to address the open-set recognition problem in CADs by learning a centralized space to separate the known and unknown classes with the assistance of proxy images generated by a generative adversarial network (GAN). With three steps, including known space initialization, unknown anchor generation and centralized space refinement, CSL learns the optimized space distribution with unknown samples cluster around the center while the known spread away from the center, achieving a significant identification between the known and the unknown. Extensive experiments on multiple datasets and tasks illustrate the proposed CSL’s practicability in CAD and the state-of-the-art open-set recognition performance.

Recent research has looked at how people infer the moral character of others based on how they resolve sacrificial moral dilemmas. Previous studies provide consistent evidence for the prediction that those who endorse outcome-maximizing, utilitarian judgments are disfavored in social dilemmas and are seen as less trustworthy in comparison to those who support harm-rejecting deontological judgments. However, research investigating this topic has studied a limited set of sacrificial dilemmas and did not test to what extent these effects might be moderated by specific features of the situation described in the sacrificial dilemma (for instance, whether the dilemma involves mortal or non-mortal harm). In the current manuscript, we assessed the robustness of previous findings by exploring how trust inference of utilitarian and deontological decision makers is moderated by five different contextual factors (such as whether the sacrificial harm is accomplished by an action or inaction), as well as by participants’ own moral preferences. While we find some evidence that trust perceptions of others are moderated by dilemma features, we find a much stronger effect of participants’ own moral preference: deontologists favored other deontologists and utilitarians favored utilitarians. Protocol registration The stage 1 protocol for this Registered Report was accepted in principle on 21 September 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.6084/m9.figshare.21325953 .

Bovine babesiosis is one of the most economically important tick-borne diseases in tropical and subtropical countries. A conventional microscopic diagnosis is typically used because it is inexpensive and expeditious. However, it is highly dependent on well-trained microscopists and tends to be incapable of detecting subpatent and chronic infections. Here, we developed a novel nucleic acid-based amplification method using loop-mediated isothermal amplification (LAMP) in conjunction with a colori-fluorometric dual indicator for the rapid and accurate detection of Babesia bovis based on the mitochondrial cytochrome b gene. We aimed to improve the thermostability, sensitivity, specificity, and alternative visualization of LAMP-based methods. We assessed its diagnostic performance compared to two conventional PCR agarose gel electrophoresis (PCR-AGE) methods. The thermostability of LAMP reaction mixtures and DNA templates in variable conditions was also assessed. In addition, we evaluated alternative visualization methods using different light sources including neon, LED, and UV lights. We found that the LAMP-neon was ten times more sensitive than the PCR-AGE, while the LAMP-LED and LAMP-UV were 1,000 times more sensitive. The current LAMP method showed no cross-amplification with uninfected cattle DNA or other common blood parasites in cattle, including Babesia bigemina, Theileria orientalis, Anaplasma marginale, and Trypanosoma evansi. In addition, the developed LAMP method has good thermostability and the potential for on-site utility as B. bovis DNA could still be detected up to 72 hours after initial preparation. Our findings suggested that the developed LAMP method provides an alternative approach for B. bovis detection with sensitivity higher than PCR-AGE diagnostics, high specificity, and the flexibility to use neon, LED, and UV light sources for positive signal observations.

Opsins, light-sensitive G protein-coupled receptors, have been identified in corals but their properties are largely unknown. Here, we identified six opsin genes (acropsins 1–6) from a coral species Acropora millepora, including three novel opsins (acropsins 4–6), and successfully characterized the properties of four out of the six acropsins. Acropsins 1 and 6 exhibited light-dependent cAMP increases in cultured cells, suggesting that the acropsins could light-dependently activate Gs-type G protein like the box jellyfish opsin from the same opsin group. Spectral sensitivity curves having the maximum sensitivities at ~ 472 nm and ~ 476 nm were estimated for acropsins 1 and 6, respectively, based on the light wavelength-dependent cAMP increases in these opsins-expressing cells (heterologous action spectroscopy). Acropsin 2 belonging to the same group as acropsins 1 and 6 did not induce light-dependent cAMP or Ca2+ changes. We then successfully estimated the acropsin 2 spectral sensitivity curve having its maximum value at ~ 471 nm with its chimera mutant which possessed the third cytoplasmic loop of the Gs-coupled jellyfish opsin. Acropsin 4 categorized as another group light-dependently induced intracellular Ca2+ increases but not cAMP changes. Our results uncovered that the Acropora coral possesses multiple opsins coupling two distinct cascades, cyclic nucleotide and Ca2+signaling light-dependently.

The volume of epicardial adipose tissue (EATV) is increased in type-2 diabetes (T2D), while its attenuation (EATA) appears to be decreased. Similar patterns have been suggested in pre-diabetes, but data is scarce. In both pre-diabetes and T2D, any independent role of EATV and EATA in disease development remains to be proven, a task complicated by their substantial co-variation with other anthropometrics, e.g. BMI, waist circumference, and abdominal visceral adipose tissue (VAT). EATV and EATA was quantified in computed tomography (CT) images in a population study (n = 1948) using an automatic technique. Data was available on BMI, waist circumference, abdominal visceral adipose tissue (VAT) area, insulin resistance (IR) and glucose tolerance, the latter ranging from normal (NGT), over pre-diabetes (impaired fasting glucose [IFG, n = 414] impaired glucose tolerance [IGT, n = 321] and their combination [CGI, n = 128]), to T2D. EATV was increased in pre-diabetes, T2D and IR in univariable analyses and when adjusting for BMI, however not when adjusting for waist or VAT. EATA was reduced in pre-diabetes, T2D and IR in univariable analyses and when adjusting for BMI and waist, however not when adjusting for VAT. Adjustment for other co-variates had little influence on the results. In conclusion, EATV is increased and EATA reduced in pre-diabetes, T2D and IR, however, significant co-variation with other anthropometrics, especially VAT, obscures their function in disease development. The current results do not exclude a pathophysiological role of epicardial fat, but future studies need to adjust for anthropometrics, or focus on the microenvironment within the pericardial sac.

Half-Heusler (HH) phase TmNiSb was obtained by arc-melting combined with high-pressure high-temperature sintering in conditions: p = 5.5 GPa, THPHT = 20, 250, 500, 750, and 1000 ∘C. Within pressing temperatures 20–750 ∘C the samples maintained HH structure, however, we observed intrinsic phase separation. The material divided into three phases: stoichiometric TmNiSb, nickel-deficient phase TmNi1-xSb, and thulium-rich phase Tm(NiSb)1-y. For TmNiSb sample sintered at 1000 ∘C, we report structural transition to LiGaGe-type structure (P63mc, a = 4.367(3) Å, c = 7.138(7) Å). Interpretation of the transition is supported by X-ray powder diffraction, electron back-scattered diffraction, ab-initio calculations of Gibbs energy and phonon dispersion relations. Electrical resistivity measured for HH samples with phase separation shown non-degenerate behavior. Obtained energy gaps for HH samples were narrow (≤ 260 meV), while the average hole effective masses in range 0.8–2.5me. TmNiSb sample pressed at 750 ∘C achieved the biggest power factor among the series, 13 μWK-2cm-1, which proves that the intrinsic phase separation is not detrimental for the electronic transport.

The intermetallic compound Eu5In2Sb6, an antiferromagnetic material with nonsymmorphic crystalline structure, is investigated by magnetic, electronic transport and specific heat measurements. Being a Zintl phase, insulating behavior is expected. Our thermodynamic and magnetotransport measurements along different crystallographic directions strongly indicate polaron formation well above the magnetic ordering temperatures. Pronounced anisotropies of the magnetic and transport properties even above the magnetic ordering temperature are observed despite the Eu2+ configuration which testify to complex and competing magnetic interactions between these ions and give rise to intricate phase diagrams discussed in detail. Our results provide a comprehensive framework for further detailed study of this multifaceted compound with possible nontrivial topology.

Digital in-line holography (DIH) is an established method to image small particles in a manner where image reconstruction is performed computationally post-measurement. This ability renders it ideal for aerosol characterization, where particle collection or confinement is often difficult, if not impossible. Conventional DIH provides a gray-scale image akin to a particle’s silhouette, and while it gives the particle size and shape, there is little information about the particle material. Based on the recognition that the spectral reflectance of a surface is partly determined by the material, we demonstrate a method to image free-flowing particles with DIH in color with the eventual aim to differentiate materials based on the observed color. Holograms formed by the weak backscattered light from individual particles illuminated by red, green, and blue lasers are recorded by a color sensor. Images are reconstructed from the holograms and then layered to form a color image, the color content of which is quantified by chromaticity analysis to establish a representative signature. A variety of mineral dust aerosols are studied where the different signatures suggest the possibility to differentiate particle material. The ability of the method to resolve the inhomogeneous composition within a single particle in some cases is shown as well.