People with schizophrenia have difficulty understanding figurative expressions, such as metaphors, humor or irony. The present study investigated the specificity of figurative language impairment in schizophrenia and its relation with cognitive and psychotic symptoms. It included 54 schizophrenia and 54 age and sex-matched healthy subjects who performed a cognitive screening (ACE-III) and figurative language comprehension task consisting of 60 short stories with three types of endings: a figurative one and its literal and an absurd (mean-ingless) counterparts. Each figurative domain-metaphor, humor, irony-was split into two sub-domains, i.e., conventional and novel metaphors, intended-to-be-funny and social-norm-violation jokes, simple irony and critical sarcasm, respectively. The main findings are: i) in schizophrenia, figurative language deficit manifests itself in each domain; ii) the most pronounced subdomain-specific impairment has been found for novel vs conventional metaphors and irony vs sarcasm; iii) altered figurative language comprehension was related to diminished cognitive abilities but not to psychopathology symptoms (PANSS) or other clinical characteristics. This may suggest that figurative language impairment, as a specific part of communication deficit, may be regarded as an essential characteristic of schizophrenia, related to primary cognitive deficits but independent of psychopathology.
Zeolites are highly efficient industrial catalysts and sorbents with microporous framework structures. Approximately 10% of the frameworks, but eventually all in the long run, produced both 3D crystals and 2D layers. The latter can be intercalated and expanded like all 2D materials but proved difficult to exfoliate directly into suspensions of monolayers in solution as precursors for unique synthetic opportunities. Successful exfoliations have been reported recently and are overviewed in this perspective article. The discussion highlights 3 primary challenges in this field, namely finding suitable 2D zeolite preparations that exfoliate directly in high yield, proving uniform layer thickness in solution and identifying application to exploit the unique synthetic capabilities and properties. There are altogether 4 zeolites confirmed to exfoliate directly into monolayers: 3 with known structures – MWW, MFI and RWR and one unknown, bifer with a unit cell close to ferrierite. The exfoliation into monolayers is confirmed by the combination of 5–6 experimental techniques including AFM, in situ and in‐plane XRD, and microscopies. The promising areas of development are oriented films and membranes, intimately mixed zeolite phases, and hierarchical nanoscale composites with other active species like nanoparticles and clusters that are unfeasible by solid state processes. This article is protected by copyright. All rights reserved
Background An obesity paradox has been described in relation to adverse clinical outcomes (e.g., mortality) with lower body mass index (BMI). Aims We sought to evaluate the association between BMI and weight loss with long-term all-cause mortality in adult populations under the care of family physicians. Methods LIPIDOGRAM studies were conducted in primary care in Poland in 2004, 2006, and 2015 and enrolled a total of 45,615 patients. The LIPIDOGRAM Plus study included 1627 patients recruited in the LIPIDOGRAM 2004 and repeated measurements in 2006 edition. Patients were classified by BMI categories as underweight, normal weight, overweight and class I, II, or III (obesity). Follow-up data up to December 2021 were obtained from the Central Statistical Office. Differences in all-cause mortality were analyzed using Kaplan‒Meier and Cox regression analyses. Results Of 45,615 patients, 10,987 (24.1%) were normal weight, 320 (0.7%) were underweight, 19,134 (41.9%) were overweight, and 15,174 (33.2%) lived with obesity. Follow-up was available for 44,620 patients (97.8%, median duration 15.3 years, 61.7% females). In the crude analysis, long-term all-cause mortality was lowest for the normal-weight group (14%) compared with other categories. After adjusting for comorbidities, the highest risk of death was observed for the class III obesity and underweight categories (hazard ratio, HR 1.79, 95% CI [1.55–2.05] and HR 1.57, 95% CI [1.22–2.04]), respectively. The LIPIDOGRAM Plus analysis revealed that a decrease in body weight (by 5 and 10%) over 2 years was associated with a significantly increased risk of death during long-term follow-up—HR 1.45 (95% CI 1.05–2.02, p = 0.03) and HR 1.67 (95% CI 1.02–2.74, p < 0.001). Patients who experienced weight loss were older and more burdened with comorbidities. Conclusions Being underweight, overweight or obese is associated with a higher mortality risk in a population of patients in primary care. Patients who lost weight were older and more burdened with cardiometabolic diseases, which may suggest unintentional weight loss, and were at higher risk of death in the long-term follow-up. In nonsmoking patients without comorbidities, the lowest mortality was observed in those with a BMI < 25 kg/m2, and no U-curve relationship was observed.
Biological modularity enhances evolutionary adaptability. This principle is vividly exemplified by bacterial viruses (phages), which display extensive genomic modularity. Phage genomes are composed of independent functional modules that evolve separately and recombine in various configurations. While genomic modularity in phages has been extensively studied, less attention has been paid to protein modularity—proteins consisting of distinct building blocks that can evolve and recombine, enhancing functional and genetic diversity. Here, we use a set of 133,574 representative phage proteins and highly sensitive homology detection to capture instances of domain mosaicism, defined as fragment sharing between two otherwise unrelated proteins, and to understand its relationship with functional diversity in phage genomes. We discover that unrelated proteins from diverse functional classes frequently share homologous domains. This phenomenon is particularly pronounced within receptor-binding proteins, endolysins, and DNA polymerases. We also identify multiple instances of recent diversification via domain shuffling in receptor-binding proteins, neck passage structures, endolysins and some members of the core replication machinery, often transcending distant taxonomic and ecological boundaries. Our findings suggest that ongoing diversification via domain shuffling is reflective of a co-evolutionary arms race, driven by the need to overcome various bacterial resistance mechanisms against phages.
Over the years, the UCTD has become one of the core EU directives aiming at the protection of both businesses and consumers (B2C), i.e., at the achievement of the appropriate balance between the parties’ rights and obligations. However, the UCTD has also left quite a number of important legal questions unanswered. Besides the general clauses on the assessment of the unfairness of contractual terms, there remains a high degree of uncertainty as to the meaning of the transparency requirement and the legal consequences of unfair contractual terms. As a result, in spite of CJEU settled case law, as well as European Commission interpretation guidelines, there are diverging patterns in the national case law of the Member States. The aim of this paper is to investigate these diverging patterns by looking more closely into national case law and into the relationship between the CJEU and the Member States courts, taking as a case study the way in which the UCTD was applied in five countries (Austria, Croatia, France, Italy and Poland) in cases involving consumer loans indexed to the Swiss franc. The survey shows that there are noticeable differences in the interpretation of core concepts underlying the UCTD, such as the unfairness test, the exclusions from the unfairness assessment, and the transparency requirement. The most problematic areas, however, concern the legal consequences of the unfairness of contractual terms. By relying on the analysis of these and related issues, the authors have come to the conclusion that 347 even after 30 years of the existence of the UCTD, there are still many important legal questions that need solving.
Microparticles (MPs) packaged with numerous bioactive molecules are essential vehicles in cellular communication in various pathological conditions, including systemic inflammation, Whereas MPs are studied mostly upon isolation, their detection in vivo is limited. Impact of MPs might depend on target cell type and cargo they carry; thus herein, we aimed at verifying MPs’ impact on macrophages. Unlike neutrophils, monocytes/macrophages are rather inactive during sepsis, and we hypothesized this might be at least partially controlled by MPs. For the above reasons, we focused on the detection of MPs with intravital microscopy (IVM) and report the presence of putative neutrophil-derived MPs in the vasculature of cremaster muscle of endotoxemic mice. Subsequently, we characterized MPs isolated not only from their blood but also from the peritoneal cavity and observed differences in their size, concentration, and cargo. Such MPs were then used to study their impact on RAW 264.7 macrophage cell line performance (cell viability/activity, cytokines, oxygen, and nitrogen reactive species). Addition of MPs to macrophages with or without co-stimulation with lipopolysaccharide did not affect respiratory burst, somewhat decreased mitochondrial activity but increased inducible nitric oxide synthase (iNOS) expression, and NO production especially in case of plasma-derived MPs. The latter MPs carried more iNOS-controlling ceruloplasmin than those discharged into the peritoneal cavity. We conclude that MPs can be detected in vivo with IVM and their cellular origin identified. They are heterogeneous in nature depending on the site of their release. Consequently, microparticles released during systemic inflammation to various body compartments differentially affect macrophages.
For now, the data we used were static. There is a group of sets where the data change over time. One of such examples is the sound. When we take a CT scan, we receive a set of images, but the set is a capture of a small piece (slice) of our body. It is even possible to combine the MRI slices into a 3D model as the distance between the slices is fixed. A different approach is proposed in videos, such as ultrasound videos, in which we see changes in an organ, usually in a short period of time. The time series usually does not rely on images only but, in most cases, on sets of tabular sets. We can observe how the observed organ changes its behavior over time, making it possible to recognize different types of anomalies or diseases compared to data captured in one time, such as typical MRI scans.
In medicine, as in every other discipline, language is one of the main forms of communication. In addition to others, difficulties are the domain knowledge and the terms that in the case of medicine can be in Latin. This means that most of the publicly available language models are not trained to recognize the medical terms. For each NLP exercise, most of the models are developed in English.
The most typical types of data in machine learning challenges are tabular data. A set of body mass index (BMI) values for a group of people is just a simple example of this type of data. We have the weight, age, and height values divided by the person to which they are assigned. Such data might be too simple to be used with a deep neural network or even most shallow methods, but we can use methods such as linear regression to see the correlation between these metrics. The tabular type of data consists of numbers and text values divided by features saved usually as a comma-separated values (CSV) or similar file format. Each value is separated by a semicolon or other sign, making it easy to load the data into a numpy or pandas matrix.
The images are widely used in the medical diagnostics. Most people who visited any kind of physician encountered one of the devices that are used in the medical diagnostics on a daily basis. The most typical are X-ray and ultrasound scans. Some General Practitioners have a dermatoscope to take pictures of the skin. Similarly, thermography can be used to take kind of heatmap images of our body. If the diagnosis of a disease is more complex, magnetic resonance imaging (MRI), computer tomography (CT), or even positron emission tomography is used before surgery. A specific type of X-ray is mammography (MMG) that is used to investigate the breast diseases. A bit more invasive device are endoscopes that can be used to diagnose an illness while introduced into the body through the i.e. mouth. In some cases, when surgery is done, cells must be invested to cure the disease. This procedure is performed on a histopathological image, where the physician checks the image at high magnification.
Investigating soil pipes and pipe collapses that lead to gully headcut formation, and considering the role of biological activities leads to a better understanding of soil erosion processes. Soil organisms and animal activities can both increase soil erosion by creating underground tunnels that may lead to the formation of soil pipes, and decrease it by reinforcing plant presence, soil porosity, and soil stability as a result of their mixing activities. The main aim of this study was to assess the role of plant and animal species on soil pipe formation in a semi-arid region affected severely by piping and gully erosion. The study was conducted in the Sarakhs Plain, in the Razavi Khorasan Province in Iran. Four study sites were selected: a slope with erosion (i.e., gully headcuts and pipe collapses), a slope without erosion, a location with dominant plant species (i.e., Artemisia annua, Camphorosma monspeliaca), and a location with dominant animal species [i.e., Formicidae (ants), termites, and Libycus Merio]. Four groups of methods were applied: bioecological tests (microbial respiration and biomass, ecological stoichiometry, and spatial point pattern analysis), geophysical test (ground penetration radar—GPR), geochemical–microscopic tests (scanning electron microscope—SEM, energy-dispersive X-ray—EDX, microanalysis TIN section, X-ray diffraction), and pedological analyses (doing soil profiles in the field and laboratory analyses of physical and chemical properties of soil samples taken in the field) to design models which can help to explain the formation of closed depressions, underground tunnels, and gully headcuts. The results showed that wherever the microbial respiration was increased, the greater the number of underground tunnels was formed. In the case of ecological stoichiometry, there was a significant difference between the slope without erosion and other test locations. The positive relationship between soil piping and biological activities was proved by bivariate pair correlation tests. The effects of soil organisms on piping were positively recognized using GPR. The results of EDX in the slope with erosion showed the presence of SiO2 and Al2O3, although there were small amounts of Na (Albite) and Ca (Wollastonite) in regions with dominant animal species, and K (MAD-10 Feldspar) in regions with dominant plant species. The TIN section made on the slope with erosion showed high silt content in comparison with the slope without erosion. The physical and chemical soil properties in four test groups, using the Duncan statistical test, showed the highest levels of significance in silt content, calcium carbonate, and bulk density. Finally, we have presented models of soil piping processes resulting from the action of living organisms. We confirmed a complex relationship between biological activity and soil pipe formation underlining the need for further interdisciplinary research on these relationships to better understand land degradation processes.
Neurodegenerative diseases, such as Alzheimer’s disease (AD) and various types of amyloidosis, are incurable; therefore, understanding the mechanisms of amyloid decomposition is crucial to develop an effective drug against them for future therapies. It has been reported that one out of three people over the age of 85 are suffering from dementia as a comorbidity to AD. Amyloid beta (Aβ), the hallmark of AD, transforms structurally from monomers into β-stranded aggregates (fibrils) via multiple oligomeric states. Astrocytes in the central nervous system secrete the human cystatin C protein (HCC) in response to various proteases and cytokines. The codeposition of Aβ and HCC in the brains of patients with AD led to the hypothesis that cystatin C is implicated in the disease process. In this study, we investigate the intermolecular interactions between different atomic structures of fibrils formed by Aβ peptides and HCC to understand the pathological aggregation of these polypeptides into neurotoxic oligomers and then amyloid plaques. To characterize the interactions between Aβ and HCC, we used a complementary approach based on the combination of small-angle neutron scattering analysis, atomic force microscopy and computational modelling, allowing the exploration of the structures of multicomponent protein complexes. We report here an optimized protocol to study that interaction. The results show a dependency of the sequence length of the Aβ peptide on the ability of the associated HCC to disaggregate it.
Understanding the factors that affect the reactivity of gold nanoparticles (Au NPs) in the catalytic oxidation of organic compounds remains an emerging issue. Of particular significance is tuning the effect of metal‐support interaction toward improving the catalytic performance of Au NPs. The main goal of this study is to provide new insight into the role of the amino‐organosilane (APMS) modifier, used for anchoring of gold species on ZnO support, in controlling the reactivity of Au NPs in H2O2 activation and the subsequent catalytic oxidation of benzyl alcohol. This study reveals that APMS modifier weakens the electronic interaction between ZnO and Au NPs, leading to a lower catalase‐like activity toward H2O2 in comparison to that observed for modifier‐free gold catalyst of similar size of nanoparticles. As a result, a slower rate of oxygen evolution resulted in higher activity in the oxidation of benzyl alcohol and enabled more efficient utilization of H2O2 under base‐free conditions. No radical species were formed during the oxidation reaction, and molecular oxygen formed in situ in the reaction medium was the primary oxidant responsible for the catalytic conversion of benzyl alcohol.
Renal cell carcinoma (RCC) represents 2% of all diagnosed malignancies worldwide, with disease recurrence affecting 20% to 40% of patients. Existing prognostic recurrence models based on clinicopathological features continue to be a subject of controversy. In this meta‐analysis, we summarized research findings that explored the correlation between clinicopathological characteristics and post‐surgery survival outcomes in non‐metastatic RCC patients. Our analysis incorporates 99 publications spanning 140 568 patients. The study's main findings indicate that the following clinicopathological characteristics were associated with unfavorable survival outcomes: T stage, tumor grade, tumor size, lymph node involvement, tumor necrosis, sarcomatoid features, positive surgical margins (PSM), lymphovascular invasion (LVI), early recurrence, constitutional symptoms, poor performance status (PS), low hemoglobin level, high body‐mass index (BMI), diabetes mellitus (DM) and hypertension. All of which emerged as predictors for poor recurrence‐free survival (RFS) and cancer‐specific survival. Clear cell (CC) subtype, urinary collecting system invasion (UCSI), capsular penetration, perinephric fat invasion, renal vein invasion (RVI) and increased C‐reactive protein (CRP) were all associated with poor RFS. In contrast, age, sex, tumor laterality, nephrectomy type and approach had no impact on survival outcomes. As part of an additional analysis, we attempted to assess the association between these characteristics and late recurrences (relapses occurring more than 5 years after surgery). Nevertheless, we did not find any prediction capabilities for late disease recurrences among any of the features examined. Our findings highlight the prognostic significance of various clinicopathological characteristics potentially aiding in the identification of high‐risk RCC patients and enhancing the development of more precise prediction models.
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