PLOS One

Kinase-related gene fusion and point mutations play pivotal roles as drivers in cancer, necessitating optimized, targeted therapy against these alterations. The efficacy of molecularly targeted therapeutics varies depending on the specific alteration, with great success reported for such therapeutics in the treatment of cancer with kinase fusion proteins. However, the involvement of actionable alterations in solid tumors, especially regarding kinase fusions, remains unclear. Therefore, in this study, we aimed to compare the number of actionable alterations in patients with tyrosine or serine/threonine kinase domain fusions, mutations, and copy number alterations (CNAs). We analyzed 613 patients with 40 solid cancer types who visited our division between June 2020 and April 2024. Furthermore, to detect alterations involving multiple-fusion calling, we performed comprehensive genomic sequencing using FoundationOne® companion diagnostic (F1CDx) and FoundationOne® Liquid companion diagnostic (F1LCDx). Patient characteristics and genomic profiles were analyzed to assess the frequency and distribution of actionable alterations across different cancer types. Notably, 44 of the 613 patients had fusions involving kinases, transcriptional regulators, or tumor suppressors. F1CDx and F1LCDx detected 13 cases with kinase-domain fusions. We identified 117 patients with kinase-domain mutations and 58 with kinase-domain CNAs. The number of actionable alterations in patients with kinase-domain fusion, mutation, or CNA (median [interquartile range; IQR]) was 2 (1–3), 5 (3–7), and 6 (4–8), respectively. Patients with kinase fusion had significantly fewer actionable alterations than those with kinase-domain mutations and CNAs. However, those with fusion involving tumor suppressors tended to have more actionable alterations (median [IQR]; 4 [2–9]). Cancers with kinase fusions exhibited fewer actionable alterations than those with kinase mutations and CNAs. These findings underscore the importance of detecting kinase alterations and indicate the pivotal role of kinase fusions as strong drivers of cancer development, highlighting their potential as prime targets for molecular therapeutics.

Objective This study aimed to develop and validate a nomogram to predict the risk of sepsis in non-traumatic subarachnoid hemorrhage (SAH) patients using data from the MIMIC-IV database. Methods A total of 803 SAH patients meeting the inclusion criteria were randomly divided into a training set (563 cases) and a validation set (240 cases). Independent prognostic factors were identified through forward stepwise logistic regression, and a nomogram was created based on these factors. The discriminative ability of the nomogram was assessed using the area under the receiver operating characteristic curve (AUC) and compared with the SOFA score. The model’s consistency was evaluated using the C-index, and the improvement in performance over the SOFA score was calculated using integrated discrimination improvement (IDI) and net reclassification improvement (NRI). Results Five independent predictive factors were identified through LASSO regression analysis: mechanical ventilation, hyperlipidemia, temperature, white blood cell count, and red blood cell count. The AUC of the nomogram in the training and validation sets were 0.854 and 0.824, respectively, both higher than the SOFA score. NRI and IDI results indicated that the nomogram outperformed the SOFA score in identifying sepsis risk. Calibration curves and the Hosmer-Lemeshow test demonstrated good calibration of the nomogram. Decision curve analysis showed that the nomogram had higher net benefit in clinical application. Conclusion The nomogram developed in this study performed excellently in predicting the risk of sepsis in SAH patients, surpassing the traditional SOFA scoring system, and has significant clinical application value.

This study aims to determine the factors affecting the happiness levels of older individuals in Türkiye during the COVID-19 pandemic. The microdata set from the 2020 Life Satisfaction Survey conducted by the Turkish Statistical Institute was utilized, involving 1,863 individuals aged 60 and above. The relationship between happiness levels and various factors was investigated using the chi-square independence test, and the factors affecting happiness were further analyzed through generalized ordered logistic regression. According to the generalized ordered logistic regression model, participants in the 60–64 age group are 10.1% less likely to report happiness compared to those aged 65 and older. Men are 4.3% less likely than women to report happiness. Furthermore, individuals with no formal education and those with primary school education have a 14.4% and 9.4% higher likelihood of happiness, respectively, compared to university graduates. The literature on happiness demonstrates the relationship between different factors and happiness. This study determined that such factors as gender, age, educational status, source of happiness, health satisfaction, hope scale, and homeownership have an impact on the happiness levels of older individuals. The amount of societal support provided to older individuals can be an indicator of their level of happiness.

Purpose Competitive horse racing is the second largest sport in Great Britain by spectator attendance, employability, and revenue. It is a lucrative yet hazardous sport, with high injury rates, particularly from falls. Clavicular fractures are one of the most common injuries reported, yet their management, especially regarding return to racing, is under-researched. The purpose of this study was to explore the factors associated with the time to return to competition following a clavicular fracture in jockeys competing in Great Britain. Materials and methods This review of medical records utilised data from the British Horseracing Authority spanning 2011–2018, inclusive. Data included the jockey’s age, sex, type of licence, race discipline, location of incident, and fracture management. Descriptive statistics and univariable and multivariable generalised linear models were constructed to analyse the impact of these factors on the time to return to racing. Results Out of 212 records of clavicular fractures, 169 were analysed. The majority (82.8%) of fractures were managed conservatively, with the remainder requiring surgery. The median time to return to racing was 40 days, with an interquartile range of 34 days. Following a clavicular fracture, the results from the univariable and multivariable models indicated that the management approach, whether the fracture is displaced, and the type of race in which the injury occurred have the greatest influence on extending the time to return to racing. In contrast, professional, conditional and amateur licence types, as well as experiencing the injury at a racecourse, were associated with reduced time to return to racing, which may indicate greater risk-taking behaviour. Conclusion This study offers unique insights into key medical and contextual factors that influence the time to return to racing among jockeys in Great Britain, contributing to tailoring medical management and return to racing protocols to support jockeys’ health and career longevity. Clinicians working within horse racing can use the findings of this study to provide return to racing guidance to trainers, riders and other medical professionals based on the key contextual information reported in this study.

Background Hospital Frailty Risk Score (HFRS) has recently been used to predict adverse health outcomes including length of stay (LOS) in hospital. LOS is an important indicator for patient quality of care, the measurement of hospital performance, efficiency and costs. Tools to predict LOS may enable earlier interventions in those identified at higher risk of a long stay. Previous work focused on patients over 75 years of age, but we explore the relationship between HFRS and LOS for all adults. Methods This is a retrospective cohort study using data from a large acute hospital during the period from 01/01/2010 to 30/06/2018. The study included patients aged 16 years and older. We calculated HFRS for patients who had been previously admitted to the hospital within the previous 2 years. The study developed Logistic Regression models (crude and adjusted) for nine prediction periods of LOS to assess association between (LOS and HFRS) and (LOS and Charlson Comorbidity Index-CCI), using odds ratios, and AUROC to assess model performance. Results An increase in HFRS is associated with prolonged LOS. HFRS alone or combined with CCI were more important predictor of long LOS in most of periods to predict LOS. However, crude HFRS was superior to the models where HFRS was combined with any other variable for LOS in excess of 21 days, which had AUROCs ranging from 0·867 to 0·890. Regarding eight age groups, crude HFRS remained the first or second most effective predictor of long LOS. HFRS alone or combined with CCI was superior to other models for patients older than 44 years for all periods of LOS; whereas for patients younger than 44 years it was superior for all LOS except 45, 60, and 90 days. Conclusion This study has demonstrated the utility of HFRS to predict hospital LOS in patients across all ages.

Objectives This study aimed to systematically incorporate the post-traumatic growth experience of breast cancer patients and furnish insights for the formulation of targeted psychological care measures. Methods The search period we were ranged from establishing the database to February 2024. We systematically searched four Chinese databases and seven English databases. The focus was on collecting qualitative research literature regarding the post-traumatic growth experience of breast cancer patients. Literature was screened and analyzed using Endnote20 software. Quality evaluation was conducted using the authenticity evaluation criteria (2016 edition) recommended by the JBI. The results were synthesized utilizing the meta-integration methodology established by the Joanna Briggs Institute (JBI) and adhered to the reporting standards delineated in the PRISMA checklist, as well as the ENTREQ reporting guidelines. Results This study encompassed 11 studies, from which 42 themes and 68 sub-themes were extracted. Similar research findings were categorized into 11 new classifications, leading to the formulation of four integrative conclusions: self-reconstruction, enhancement of spirituality and religious beliefs, appreciation of the new philosophy of life, and transformations associated with others. Conclusions Medical professionals should possess a precise comprehension of the concept of post-traumatic growth, and actively encourage patients to engage in deliberate rumination, facilitate emotional release, support effective coping strategies, enhance social support systems, foster post-traumatic growth in patients, and promote their overall well-being. Trial registration Systematic review registration: CRD42024519850.

School closures are a safe and important strategy for preventing infectious diseases in schools. However, the effects of school closures have not been fully demonstrated, and prolonged school closures have a negative impact on students and communities. This study evaluated class-specific school closure strategies to prevent the spread of seasonal influenza and determine the optimal timing and duration. We constructed a new model to describe the incidence of influenza in each class based on a stochastic susceptible-exposed-infected-removed model. We collected data on the number of infected absentees and class-specific school closures due to influenza from four high schools and the number of infected cases from the community in a Japanese city over three seasons (2016–2017, 2017–2018, and 2018–2019). The parameters included in the model were estimated using epidemic data. We evaluated the effects of class-specific school closures by measuring the reduced cumulative incidence of class closures per day. The greatest reduction in the cumulative absences per day was observed in the four-day class closure. When class-specific school closures lasted for four days, the reduction in the cumulative number of infections per class closure day was greater when the closure was timed earlier. The highest reduction in the number of class closures per person-day occurred when the threshold was around 5.0%. Large variations in the reduction of cumulative incidence were noted owing to stochastic factors. Reactive, class-specific school closures for seasonal influenza were most efficient when the percentage of newly infected students exceeded around 5.0%, with a closure duration of four days. The optimal strategy of class-specific school closure provides good long-term performance but may be affected by random variations.

This work aimed to evaluate the use of Visible and Near-infrared Spectroscopy (Vis-NIRS) as a tool in the classification of bovine carcasses. A total of 133 animals (77 females, 29 males surgically castrated and 27 males immunologically castrated) were used. Vis-NIRS spectra were collected in a chilling room 24 h postmortem directly on the hanging carcasses over the longissimus thoracis between the surface of the 5th and 6th ribs. The data were evaluated by principal component analysis (PCA) and the partial least squares regression (PLSR) method. For the prediction of sex, the best model was the Standard Normal Variate (SNV) because it presented a relatively high coefficient of determination for prediction, presenting a percentage of correctness of 75.51% and an error of 24.49%. Regarding age, none of the models were able to differentiate the samples through Vis-NIRS. The findings confirm that Vis-NIRS prediction models are a valuable tool for differentiating carcasses based on sex. To further enhance the precision of these predictions, we recommend using Vis-NIRS equipment with the full infrared wavelength range to collect and predict sex and age in intact beef samples.

Previous studies have indicated the great performance of electrooxidation (EO) to mineralize per- and polyfluoroalkyl substances (PFASs) in water, but different anions presented in wastewater may affect the implementation of EO treatment in field applications. This study invetigated EO treatment of perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), two representative perfluoroalkyl acids (PFAAs), using porous Magnéli phase titanium suboxide anodes in electrolyte solutions with different anions present, including NO3⁻, SO4²⁻, CO3²⁻ and PO4³⁻. The experiment results indicate that CO3²⁻ enhanced PFAS degradation, while NO3⁻ suppressed the degradation reactions with its concentration higher than 10 mM. SO4²⁻ and PO4³⁻ exhibited less impact. Further studies with electrochemical characterizations and radical quenching experiments illustrate the mechanisms of how the anions may impact EO performance.

Objective This study aimed to evaluate the positive effects on anti-oxidation, anti-inflammation, and microbial composition optimization of diabetic mice using tussah (Antheraea pernyi) silk fibroin peptides (TSFP), providing the theoretical foundation for making the use of silk resources of A. pernyi and incorporating as a supplement into the hypoglycemic foods. Method The animal model of diabetes was established successfully. Alloxan-induced diabetic mice were orally administered using TSFP, and the hypoglycaemic effects in vivo were systematically investigated. Results The results indicated that TSFP could significantly reduce the fasting blood glucose (FBG) levels and suppress the mRNA expression of glycometabolism genes of diabetic mice. In addition, the TSFP could ameliorate the lipid dysbolism and contribute to a higher anti-oxidation capacity. Moreover, TSFP could alleviate pathological damages and hinder inflammatory processes of diabetic mice. Besides, the supplementation of TSFP presented a greater ability to shape and optimize the gut microbial composition by enriching the profitable bacteria and inhibiting the pathogenic microorganisms. Correlation analysis also revealed that the abundances of functional bacteria in the TSFP-treated groups exhibited better correlations with serum parameters, which would be of positive significance for blood glucose regulation and inflammation remission. Conclusions These results collectively corroborated the feasibility and superiority of using TSFP for hyperglycaemia remission via anti-oxidation enhancement, inflammation alleviation, and microbial composition optimization, contributing to a safely feasible and biologically efficient strategy for improving anti-diabetic effects.

Background Visual dysfunction, including abnormal stereopsis, is a significant non-motor symptom in Parkinson’s disease (PD) that can reduce quality of life and appears early in the disease. Abnormal stereopsis is associated with worsening of bradykinesia and freezing of gait, though the exact pathways linking stereopsis to motor symptoms remain unclear. Furthermore, in PD patients, the pedunculopontine nucleus and laterodorsal tegmental complex play an active role in sensorimotor control, and these areas provide cholinergic projections. Cholinergic degeneration may be associated with symptoms such as abnormal stereopsis, postural instability, gait disturbances and cognitive impairment. Therefore, in this study, we hypothesized that a high postural instability and gait disturbance score would increase the risk of abnormal stereopsis in PD. Methods We designed a cross-sectional study and included 240 early PD patients without ophthalmologic problems other than abnormal stereopsis. To evaluate stereopsis, we used Titmus stereo test plates. Stereopsis testing was performed only once at the time of the patient’s initial PD diagnosis. We collected data from medical history taking, scales, cognitive function tests, gait analysis, and tilt table tests. To analyze the potential risk factors for abnormal stereopsis in PD, we conducted a binary logistic stepwise selection analysis. Results Among the total of 240 PD patients, 185 were in the normal stereopsis group and 55 were in the abnormal stereopsis group. In the analysis for risk factors related to abnormal stereopsis, the postural instability and gait difficulties (PIGD) subtype score was significantly associated with abnormal stereopsis. (95% confidence interval: 1.37–5.15). Conclusions In PD, particularly in PIGD subtype patients, abnormal stereopsis can lead to a decrease in the quality of sensory information, potentially interfering with feedback and adaptation processes. This, in turn, can negatively affect posture and gait, creating a vicious cycle.

Background Multiple studies across Ethiopia have investigated the occurrence of DKA, showing significant variations and conflicting findings. This systematic review and meta-analysis seek to consolidate the overall prevalence of diabetic ketoacidosis and its associated factors in the Ethiopian context. Methods The study adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P) guidelines. Data was collected from PubMed/MEDLINE, Science direct, Google Scholar, and gray literature sources. Microsoft Excel was used for data extraction and summary, while the analysis was performed with R software version 4.3.2. The overall pooled prevalence of diabetic ketoacidosis and its components was estimated using a random effects model. Publication bias was assessed both graphically, using funnel plots, and statistically, with tests such as Egger’s regression test. Subgroup analysis were carried out to minimize random variations in the estimates from the primary studies. Result The pooled estimated prevalence of diabetic ketoacidosis among diabetic patients in Ethiopia was 46% (95% CI; 36, 57; I2 = 100%, P≤0.001). Medication discontinuations (AOR = 1.30, 95 CI 1.20, 1.64), presence of comorbidity (AOR = 1.53, 95 CI 1.10, 2.20) and presence of infection (AOR = 1.62, 95 CI 1.31, 1.98) had an association with diabetic ketoacidosis among diabetic patients. Conclusions Medication discontinuations, comorbidity, and infection are individual contributors to diabetic ketoacidosis in diabetic patients. Implementing initiatives to enhance medication adherence and establish comprehensive diabetes management programs covering glycemic control, comorbidities, and infection management can effectively address these factors.

Recent advances in bioengineering have made it possible to develop increasingly complex biological systems to recapitulate organ functions as closely as possible in vitro. Monitoring the assembly and growth of multi-cellular aggregates, micro-tissues or organoids and extracting quantitative information is a crucial but challenging task required to decipher the underlying morphogenetic mechanisms. We present here an imaging platform designed to be accommodated inside an incubator which provides high-throughput monitoring of cell assemblies over days and weeks. We exemplify the capabilities of our system by investigating human induced pluripotent stem cells (hiPSCs) enclosed in spherical capsules, hiPSCs in tubular capsules and yeast cells in spherical capsules. Combined with a customized pipeline of image analysis, our solution provides insight into the impact of confinement on the morphogenesis of these self-organized systems.

Salmonella Dublin is a serovar that causes severe infections and cattle. Despite the importance of this agent, research on achieving its elimination from dairy farms is limited, which complicates risk mitigation and control efforts. This study thus aimed to assess the prevalence of S. Dublin on a farm with a history of outbreaks, to understand the dynamics of the infection, characterize the antimicrobial resistance of the isolates, and evaluate their genetic similarity. Multiparous cows in the postpartum phase are nearly five times more likely to shed Salmonella sp. A total of 39 cases of fatal septicemic salmonellosis caused by S. Dublin were confirmed in calves aged 3–5 months. Antimicrobial susceptibility was evaluated in 45 strains of S. Dublin, with 48.9% of the isolates classified as multidrug resistant, including resistance to penicillin (48.9%), tetracyclines (42.2%), and fluoroquinolones (33.3%). Seven multidrug-resistant isolates were selected for genomic sequencing. Among the resistance determinants identified, a mutation in the gyrA gene, present in all sequenced isolates, was notable. Analyses of cgMLST and SNPs revealed that the isolates from healthy animals were closely related to those found in animals with confirmed cases of S. Dublin, confirming that the agent was circulating among healthy animals across various categories. A high similarity was also found between the isolates in this study and strains causing salmonellosis in humans in Brazil, thus reinforcing the zoonotic nature and possible epidemiological link between cattle, and the occurrence of this disease in humans.

Background Latine populations in the United States continue to be disproportionately affected by COVID-19 with high rates of infection and mortality. Our community-based participatory research partnership examined factors associated with COVID-19 testing and vaccination within a particularly hidden, underserved, and vulnerable population: Spanish-speaking Latines. Methods In 2023, native Spanish-speaking Latine interviewers conducted phone-based structured individual assessments with 180 Spanish-speaking, predominantly immigrant Latines across North Carolina. We used univariate and multivariable logistic regression analyses to examine associations between participant characteristics and COVID-19 testing and vaccination. Results Participant mean age was 41.7 (SD = 13), and 77.2% of the sample reported being cisgender women. Most participants reported immigrating from Latin American countries (89.9%), being uninsured (66.1%), and lacking US immigration documentation (51.1%). While most reported ever being COVID-19 tested (83.3%) and ever being vaccinated against COVID-19 (84.4%), only 24% were up to date with vaccination. Nearly half of the sample reported one or more barriers to COVID-19 testing, and over one-quarter reported one or more barriers to COVID-19 vaccination. Higher educational attainment was significantly associated with ever being tested (P = .031). Fewer concerns about the vaccine, including fewer worries about side effects and having more confidence in vaccine effectiveness and safety, was associated with ever being vaccinated (P < .001). Conclusions Spanish-speaking Latines face barriers to getting tested and vaccinated against COVID-19. Although ever testing and ever vaccination rates were high, being up to date with recommended vaccinations was low. Educational attainment and concerns about the vaccine were associated with COVID-19 testing and vaccination, respectively. Our findings suggest the need for culturally congruent strategies to address the challenges facing Spanish-speaking Latines in the United States.

The Late Jurassic fossil deposits of southern Germany, collectively known as the ’Solnhofen Archipelago’, are one of the world’s most important sources of Mesozoic vertebrates. Complete skeletons of cartilaginous fishes (Chondrichthyes), whose skeletal remains are rare in the fossil record and therefore all the more valuable, are represented, among others, by exceptionally well-preserved rays (superorder Batomorphii). Despite their potential for research in several areas, including taxonomy, morphology, ecology, and phylogeny, the number of studies on these chondrichthyans is still very limited. Here, we identify a previously unknown ray, †Apolithabatis seioma gen. et sp. nov., which represents the first record of a ray species from the upper Kimmeridgian of Painten, Germany, and thus the oldest Late Jurassic ray taxon from Germany based on skeletal remains. This new batomorph is characterised by a unique body shape and a combination of skeletal features that distinguish it readily from all other known Late Jurassic rays. Two different morphometric approaches confirm differences in body shape and proportions to all known Late Jurassic conspecifics. We thus extend the recent taxonomic revision of these rays and include all described holomorphic specimens in a phylogenetic framework using strict cladistic principles. The phylogenetic analysis reveals all Late Jurassic batomorphs to represent a monophyletic group, for which we introduce the new order Apolithabatiformes, which is sister to all other batomorphs representing a stem group. While the phylogenetic relationships within Apolithabatiformes ord. nov. remain largely unresolved, †Apolithabatis gen. nov. is placed as the sister to †Aellopobatis. This highlights that, despite considerable progress in our understanding of the diversity and phylogeny of early rays, difficulties remain in establishing robust relationships within batomorphs. We therefore emphasise the importance of comprehensive studies of completely preserved fossil cartilaginous fishes to obtain a better understanding of chondrichthyan evolution and their systematics in deep time.

Mushrooms are considered one of the safe and effective medications because they have great economic importance due to countless biological properties. Cordyceps militaris contains bioactive compounds with antioxidant, antimicrobial and anti-cancerous properties. This study was projected to analyze the potentials of biometabolites and to extract antimicrobial peptides and protein from the C. militaris. An in-vitro analysis of biometabolites and antimicrobial peptides was performed to investigate their pharmacological potentials followed by quantification and characterization of extracted protein. Computational analysis on non-small cell lung cancer genes (NSCLC) was performed on quantified compounds to interpret the biometabolites from C. militaris that could be potential drug candidate molecules with high specificity and potency. A total of 34 compounds representing 100% of total detected constituents identified were identified using GCMS analysis and 20 compounds using LC-MS which showed strong biological activities. FT-IR spectroscopy manifest powerful instant peaks to have different bioactive components including carboxylic acid, phenols, amines and alkanes present in methanolic extract of C. militaris. In C. militaris, higher protein concentration was observed in 70% concentration of protein extract (500 μg/ml ± 0.025). The best antioxidant activity (% Radical scavenging activity) of methanolic extracts was 80a ± 0.03, antidiabetic activity was 37 ± 0.057 and anti-inflammatory activity was 40 ± 0.021 at 12 mg/ml. Antibacterial activity for different concentrations of Cordyceps protein and methanolic extracts was significantly (p < 0.05). Indolizine, 2-(4-methylphenyl) has most binding affinity (micromolar) and optimized properties to be selected as the lead inhibitor. It interacts favorably with the active site of RET gene of NSCLC and is neuroprotective and hepatoprotective.

This paper presents a low-power, second-order composite source-follower-based filter architecture optimized for biomedical signal processing, particularly ECG and EEG applications. Source-follower-based filters are recommended in the literature for high-frequency applications due to their lower power consumption when compared to filters with alternative topologies. However, they are not suitable for biomedical applications requiring low cutoff frequencies as they are designed to operate in the saturation region. The major contribution in this work are the filter is made to operate in the weak inversion zone to reduce the area needed for the capacitor and the amount of power dissipated. Process variation is one of the major issues in the weak inversion regime. To overcome this, a unique method of compensating against fluctuations in process, voltage, and temperature is put forth based on magnitude comparison is another contribution. Key findings from post-layout simulations and experimental measurements demonstrate that the filter achieves a tunable cutoff frequency range of 0.5 Hz to 150 Hz, with a total power dissipation of only 6nW at 150 Hz. The design occupies a compact silicon area of 0.065 mm² and offers a dynamic range of 75 dB. The measured results indicate that for a 300 mVpp signal swing, the top bound on THD is -40 dB. The filter’s robustness against process, voltage, and temperature variations is validated through on-chip tuning using a current steering DAC, ensuring stable performance across different operating conditions. These results make the proposed filter a promising candidate for low-power biomedical devices. The recommended filter is developed and implemented using UMC-0.18μm CMOS technology with a 1.0V supply, and the IC is tapped out using an MPW run of Euro practice IC services.

Background Approval of proteasome inhibitors, immunomodulatory drugs, and anti-CD38 monoclonal antibodies (mAbs), such as daratumumab, has reshaped treatment patterns in patients with multiple myeloma (MM) in Japan. This retrospective study evaluated patient characteristics, treatment patterns, and trends in MM patients using Medical Data Vision, the largest electronic health records database in Japan with anonymous inpatient and outpatient health information. Methods Patients aged ≥18 years, with ≥2 records of an MM diagnostic and disease code and ≥1 record of MM treatment between 01 April 2008 and 30 June 2023 were included. Patients starting first-line (1L) treatment on or after 01 January 2020 were categorized into the 1+L cohort; those starting second-line (2L) treatment on or after 01 January 2018 were allocated to the 2+L cohort. Results Within the study period, 21,066 patients had an MM diagnosis, including 6,337 and 5,964 patients in the 1+L and 2+L cohorts, respectively. Median age was 74 years in both cohorts and gender distribution was similar (52.4% and 51.3% males, respectively). In the 1+L cohort, most patients (5,754/6,337; 90.8%) did not receive transplant, among whom 51.0% received 1L lenalidomide-based therapy, primarily daratumumab/lenalidomide/dexamethasone (DRd; 15.0%) or lenalidomide/dexamethasone (Rd;14.0%). In non-transplant patients, 1L DRd use increased from 6.0% in January–June 2020 to 28.0% in January–June 2023. In the 2+L cohort, 2L lenalidomide-based therapy use decreased from 65.0% in January–June 2018 to 37.0% in January–June 2023; daratumumab-based therapy increased from 14.0% to 39.0%. Retreatment with lenalidomide-, daratumumab-, and isatuximab-based therapy occurred in 44.1%, 35.2%, and 5.6% of patients, respectively. Conclusion The high use of lenalidomide and DRd in 1L, and high rates of retreatment with lenalidomide and anti-CD38 mAbs in 2L+ indicate a substantial need for new treatment modalities that can be used in 2L+ patients who previously received lenalidomide with/without an anti-CD38 mAb therapy.

Disposable filtering face piece respirators (FFRs) are not approved for reuse as standard of care. However, lessons learnt from the SARS-CoV-2 pandemic, FFRs decontamination and reuse may be needed as crisis capacity strategy to ensure availability in medical facilities. We studied a decontamination methodology based on atmospheric pressure plasma technology, which allows for rapid, contact-free decontamination without utilisation of harmful chemicals, and suitable to access small pores and microscopic filters openings. Promising performances in terms of bioburden reduction (Log6) were achieved while imparting mainly transient chemical surface modifications to the masks filtering layers. The plasma decontamination process proposed was also considered in terms of the environmental impact of re-use technology for FFR medical devices in order to understand its sustainability. This study assessed the feasibility of an atmospheric pressure plasma approach for the decontamination of disposable filtering face piece respirators (FFR) or respiratory masks commonly used in hospital settings.

This study presents a comprehensive comparative analysis of Machine Learning (ML) and Deep Learning (DL) models for predicting Wind Turbine (WT) power output based on environmental variables such as temperature, humidity, wind speed, and wind direction. Along with Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN), the following ML models were looked at: Linear Regression (LR), Support Vector Regressor (SVR), Random Forest (RF), Extra Trees (ET), Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM). Using a dataset of 40,000 observations, the models were assessed based on R-squared, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). ET achieved the highest performance among ML models, with an R-squared value of 0.7231 and a RMSE of 0.1512. Among DL models, ANN demonstrated the best performance, achieving an R-squared value of 0.7248 and a RMSE of 0.1516. The results show that DL models, especially ANN, did slightly better than the best ML models. This means that they are better at modeling non-linear dependencies in multivariate data. Preprocessing techniques, including feature scaling and parameter tuning, improved model performance by enhancing data consistency and optimizing hyperparameters. When compared to previous benchmarks, the performance of both ANN and ET demonstrates significant predictive accuracy gains in WT power output forecasting. This study’s novelty lies in directly comparing a diverse range of ML and DL algorithms while highlighting the potential of advanced computational approaches for renewable energy optimization.