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The nexus between environmental concern and future childbearing aspirations among university students in Bangladesh

This study investigates the relationship between environmental concerns and future childbearing aspirations among university students in Bangladesh. It included 380 final-year and master’s students from various academic disciplines at Shahjalal University of Science and Technology (SUST), Bangladesh, who completed a structured questionnaire. The binary logistic regression model and Poisson regression model were employed to examine the effects of these variables (environmental concern, gender, religion, academic performance, university courses related to the environment or climate change, field of study, and perceived vulnerability to extreme weather events or climate change in their home region) on intentions to have children in the future. The findings demonstrate that environmental concerns significantly impact university students’ intentions to have children. Additionally, students who are concerned about environmental issues are more likely to desire children in the future and plan to limit their family size due to these concerns. Students’ future parenting plans are strongly influenced by their perceptions of environmental challenges. According to this study, female students are less likely to intend to have children if environmental conditions worsen. The findings suggest that several factors, including gender, disciplinary background, and environmental degradation, may influence future fertility intentions and, consequently, affect population dynamics. Such factors may also play a crucial role in shaping future population policies aimed at addressing the effects of climate change and achieving environmental sustainability.

Principal fitted component framework for robust support vector regression based on bounded loss: A simulation study with potential applications

The inferential results regarding estimates of Support Vector Regression (SVR) are highly influenced by anomalies and ill-conditioned predictors. Excessive dimensions of data also make the model complex. To improve estimation accuracy, this paper introduces two modelling frameworks, Principal Component Robust Support Vector Regression (PCRSVR) and Principal Fitted Component Robust Support Vector Regression (PFCRSVR). These techniques are developed by incorporating PCs and PFCs with Exponential Quantile SVR (EQSVR), which is capable of dealing with ill-conditioned regressors, extreme observations, and high-dimensional data settings simultaneously. An extensive simulation study has been conducted to evaluate the performance of the proposed methods. Different evaluation criteria are chosen in this regard. Additionally, real-life data applications illustrate the efficacy of the proposed techniques as compared to competing ones.

In-hospital mortality outcomes of favipiravir in patients with moderate to severe COVID-19 infection: An emulated target trial using real-world data from the largest field hospital in Thailand

Background Favipiravir, an antiviral agent, has been widely used to treat COVID-19 due to its potential mechanism of action, despite limited evidence of its efficacy in moderate to severe cases. Aim This study aimed to evaluate the efficacy of favipiravir in improving in-hospital mortality outcomes among patients with moderate to severe COVID-19 through an emulation of a target trial. Methods We emulated a target trial using observational data from Bussarakham field hospital, Thailand between May 14 and September 20, 2021. Patients were categorized into three groups: those receiving favipiravir with dexamethasone (FPV with Dexa), favipiravir alone (FPV), and symptomatic treatment (ST). In-hospital mortality within 30 days was the primary outcome. Results From 18,184 patients admitted to the hospital, a total of 3,193 moderate to severe COVID-19 cases were included. Of these, 2,256 (70.65%) received FPV with Dexa, 828 (25.93%) received FPV, and 109 (3.41%) received ST. The restricted mean survival times were 29.68 days (95% CI: 29.52, 29.84) for FPV with Dexa, 29.46 days (95% CI: 29.22, 29.71) for FPV, and 28.14 days (95% CI: 26.51, 29.76) for ST. Only FPV showed marginally significant difference when compared to ST. However, there was a trend in prolonging survival time in FPV with Dexa group, and the results were more pronounced in severe and hypoxic patients. Conclusion Our emulated target trial suggests favipiravir, especially with dexamethasone, offers a modest survival benefit in moderate to severe COVID-19, particularly in hypoxic patients. It supports favipiravir as a practical antiviral in settings where other antivirals are not available. Further randomized controlled studies are needed to confirm its role, alongside standard corticosteroid therapy.

Gender disparities in bladder cancer: A population-based study on life expectancy and health spending in Asia

Background The aim of this study was to elucidate the disparities in life expectancy, loss-of-life expectancy, and lifetime medical expenditure between sexes in patients with bladder cancer. Methods In this retrospective study, we used three Taiwanese databases to analyze the data of patients diagnosed with bladder cancer between 2008 and 2019. Patients aged <30 years or >90 years were excluded. Survival and lifetime costs were estimated using the Kaplan–Meier and semiparametric methods. Subgroup analyses were performed to examine the effects of cancer stage, age, and factors such as hemodialysis on patient outcomes and costs. Results This study included 30,390 new diagnoses of bladder cancer. Disparities in loss-of-life expectancy between men and women were observed in both non-muscle-invasive bladder cancer (3.17 [0.55] years for men vs. 7.14 [0.76] years for women) and muscle-invasive bladder cancer (8.86 [0.43] years for men vs. 10.64 [0.63] years for women). Carcinoma in situ revealed its profound impact, with the associated loss-of-life expectancy mirroring those of advanced stages (combined sex carcinoma in situ: 8.58 years, stage 2 men: 9.48 years, stage 2 women: 9.53 years). The cost per life-year showed a marked difference, especially for non-muscle-invasive bladder cancer ($4,631 for men vs. $7,636 for women) and muscle-invasive bladder cancer ($6,033 for men vs. $7,753 for women). Hemodialysis accounted for a significant portion of these costs, with hemodialysis rates of 4.6% in men and 18.5% in women. Conclusions Women have a higher prevalence of high-grade histopathology and an extended duration of hemodialysis, culminating in inferior outcomes in non-muscle-invasive bladder cancer and muscle-invasive bladder cancer and augmented costs, compared with men. The role of hemodialysis and the carcinoma in situ stage highlights the need for vigilant monitoring and early aggressive treatment strategies.

Identification of key genes and signaling pathways of liver cancer and model construction for prognosis and diagnosis based on bioinformatics analysis

Objective This study aims to identify key genes, biomarkers, and associated signaling pathways involved in liver cancer progression by analyzing differentially expressed genes (DEGs) between normal and cancerous liver tissues, with the goal of establishing diagnostic and prognostic models for liver cancer. Methods Two datasets, GSE39791 and GSE84402 from GEO, and clinical data from TCGA were selected. Differentially expressed genes (DEGs) were identified using the “limma” package in R, and volcano plots were generated. Functional enrichment of DEGs was performed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Logistic regression and multivariate Cox regression models were established for diagnostic and prognostic prediction. The immortalized liver cell line THLE-3 and HepG2 cells were used to verify key gene expression via RT-qPCR and Western blot. HepG2 cells were transfected to up- and down-regulate SNAPC2 expression, and cell proliferation, migration, and apoptosis were assessed using CCK-8, colony formation, scratch, transwell migration assays, and flow cytometry with Annexin V-PE/7-AAD staining. Additionally, Gene Set Enrichment Analysis (GSEA) of SNAPC2 revealed its involvement in cancer-related pathways. Results Bioinformatics analysis identified 10,961 down-regulated and 3,321 up-regulated genes in the GSE39791 and GSE84402 datasets, and 272 down-regulated and 4,855 up-regulated genes in TCGA data. GO and KEGG analysis revealed 3,820 co-DEGs associated with processes like cell differentiation and morphogenesis. CDCA8, GRPEL2, HAVCR1, MT3, MYCN, NDRG1, PHOSPHO2, SNAPC2, SOCS2, and TXNRD1 were selected to construct prognostic models, and MYCN, NDRG1, TXNRD1, SNAPC2, PHOSPHO2, and CDCA8 for diagnostic models. Western blot validation showed upregulation of CDCA8, GRPEL2, HAVCR1, MYCN, NDRG1, PHOSPHO2, SNAPC2, and TXNRD1 in liver cancer tissues, correlating with poor prognosis. Moreover, reduced SNAPC2 expression in HepG2 cells led to decreased proliferation and migration, and increased apoptosis, suggesting SNAPC2 plays a role in liver cancer progression by promoting cell proliferation and migration. Conclusion CDCA8, GRPEL2, HAVCR1, MT3, MYCN, NDRG1, PHOSPHO2, SNAPC2, SOCS2, TXNRD1 were key genes for liver cancer prognosis and diagnosis. Moreover, lowering SNAPC2 expression could improve the prognosis of liver cancer through decreasing proliferation and migration s and increasing apoptosis of cancer cell.

Technical report: Efficient and accurate assessment of neurite outgrowth in spiral ganglion explants using Sholl analysis and repeated measurement ANOVA

Cultivating three-dimensional spiral ganglion explants is a well-established in-vitro assay for assessing the neurotrophic potential of compounds. The manual neurite measurement remains common but hinders high-throughput experimentation. The present study aimed to automate this process, comparing two methods, Sholl and Gray Value analysis, with manual neurite measurement to enhance this time-consuming and labor-intensive evaluation. The explants were cultured with brain-derived neurotrophic factor (BDNF), and both neurons and neurites were marked immunohistochemically. The comparison of methods included significance of treatment group differences, accuracy, precision, time and interference. Sholl analysis outperformed manual measurements in time and precision, exhibiting fewer interferences compared to Gray Value analysis. It effectively distinguished between control and BDNF concentrations, paralleling manual tracing outcomes. The Sholl intersections per radius analysis, employing repeated measures (rm) ANOVA across 31 measurement points, exhibited the smallest deviation from manual measurement. Gray Value analysis introduced inner explant brightness as a parameter that parallels neuronal survival within the explant. The present study demonstrates, that Sholl analysis with rm ANOVA emerged as the most efficient, with reduced time and manpower requirements. This positions the improved Sholl analysis as a potent tool for high-throughput, automated assessments of neurotrophic potential, marking a significant advancement in the field.

The effect of Nigella Sativa emulgel on episiotomy wound healing and pain intensity in primiparous women: A triple-blind randomized controlled trial

Background Episiotomy, a common surgical procedure during childbirth, often leads to complications such as pain, infection, and delayed healing. Nigella sativa has demonstrated anti-inflammatory and wound-healing properties in prior studies and have received United States Food and Drug Administration (FDA) approval for food use, indicating their safety. This study aimed to evaluate the efficacy of Nigella sativa emulgel on episiotomy wound healing and pain intensity in primiparous women. Methods A triple-blind, randomized controlled trial was conducted at Taleghani Hospital, Tabriz, Iran (May 2023–April 2024). Seventy-four primiparous women with mediolateral episiotomy were randomized to receive either Nigella sativa emulgel or placebo, applied topically three times daily for 7 days post-discharge. Wound healing was assessed using the REEDA scale (Redness, Edema, Ecchymosis, Discharge, Approximation; primary outcome), and pain intensity was measured via visual analog scale (VAS; secondary outcome). Outcomes were evaluated at discharge (baseline) and 10 ± 1 days postpartum. Data were analyzed using independent t-tests, ANCOVA (adjusted for baseline scores), and Mann-Whitney U tests for non-normal distributions (SPSS v26). Results At 10 ± 1 days postpartum, the Nigella sativa group showed significantly better wound healing (REEDA score: MD −0.79, 95% CI −1.20 to −0.39; p = 0.001) and lower pain scores (VAS: MD −0.74, 95% CI −1.3 to −0.11; p = 0.021) compared to placebo. Subscale analysis revealed improvements in redness (p = 0.037), edema (p = 0.041), and ecchymosis (p = 0.043). No adverse effects were reported, and satisfaction was higher in the Nigella sativa group (86.5% vs. 56.7%; p = 0.046). Conclusions Topical Nigella sativa emulgel significantly improved episiotomy wound healing and reduced pain intensity, with high patient satisfaction. These findings support its potential as a natural therapeutic option, though larger multi-center trials are needed for broader validation. Trial registration Iranian Registry of Clinical Trials IRCT20120718010324N68.

Influence of ZrO2 content on the mechanical, electrical, and microstructural characteristics of La1-xZrxCo1−yMnyO3 perovskites for IT-SOFC cathodes

In this research, the doping effects of ZrO2 and MnO2 on La1-xZrxCo1−yMnyO3 cathode were investigated in terms of physical, mechanical and electrical properties. The amount of ZrO2 was varied by 5wt%, 10wt%, and 15wt% for different compositions of the composites and MnO2 was varied accordingly. The composite cathode is prepared to enhance the structural and functional properties of La1-xZrxCo1−yMnyO3 composites by varying ZrO2 doping levels, optimizing their suitability for high-performance applications through detailed material characterization in powder and pellet form, followed by calcination at 1000°C and sintering at 1200°C. The final sintered composites were then examined by SEM-EDX, XRD, and AFM. Investigations were also conducted on density, porosity, compressive strength, thermal expansion coefficient (TEC), electronic conductivity, and diametral tensile strength (DTS). SEM and EDX shows both imaging and chemical analysis of the composites which indicates the results of reactions during sintering. XRD indicates that significant structural change had been taken place with the addition of ZrO2. These defects in perovskite structure will increase the ionic and electronic conductivity of the composites. The highest value of DTS, compressive strength was obtained for 15LZCM sample and lowest value of DTS, and compressive strength was observed for the 5LZCM sample. Some properties like microhardness, thermal expansion, and electrical conductivity were also determined. XRD analysis shows ZrO2 doping caused transformation of the perovskite structure and the leading crystal system was monoclinic (P 1 21/c1). SEM shows the porous microstructure of the perovskite oxide. AFM reveals the addition of the ZrO2 decreasing roughness; the rms roughness of 5LZCM was 61.46 nm but the rms roughness was 37.12 nm for 15LZCM.

Assessing influenza activity variations in the Asian region during the pre- and post-pandemic period (2017–2023)

Background The year 2021 witnessed a decline in seasonal influenza cases across Southeast Asia and the broader Asian region. However, a sudden surge in influenza cases during 2022–2023 necessitates comprehensive exploration and analysis to inform future prediction models. Objective Our study aims to evaluate the disease burden of influenza in Asian countries post-COVID-19, while comparing seasonal variations to the pre-pandemic influenza patterns. Methods We conducted an extensive analysis of data spanning from January 2017 to September 2023 across ten Asian countries, categorizing them into three WHO regions. Data was sourced from the WHO Flunet system, falling under the purview of the WHO Global Influenza Program. Findings and conclusion In conclusion, influenza epidemiology during the inter-pandemic period is characterized by seasonality influenced by factors such as population contact patterns, virus survival, and host immunity. The year 2020 witnessed a global decrease in influenza circulation due to widespread lockdowns and travel restrictions. However, a resurgence was observed in late 2021, notably with out-of-season activity in the Southern Hemisphere. Our analysis based on reviews indicates a probable significant increase in influenza cases in the upcoming seasons. To address this, the implementation of influenza vaccination programs and the promotion of vaccination for both children and adults are essential measures to alleviate the dual burden of influenza in the post-COVID era.

Aripiprazole use and lowering the risk of breast cancer in patient with schizophrenia in a national cohort study

Prediction and accuracy improvement of insulin pump in-fusion deviation based on LSTM and PID

In order to further improve the injection precision of the PH300 insulin pump, this paper optimizes and improves the mechanical structure and control algorithm of the PH300. The improved PH300 uses a proportional-integral-derivative controller based on back propagation neural network (BP-PID) algorithm to control operation, and the experimental results show that the minimum effective single infusion dose of the improved PH300 is 0.047 U, which is reduced by 50.52%. The deviation reduction of low-dose infusion (0.1U-0.9U) ranged from 1.47% to 10.87%, with a mean of 4.91%. The mean deviation of the improved PH300 decreases by 12.85% after a 24h low basal rate (0.5U/h) injection. In addition, Long Short-Term Memory (LSTM) was used to predict the deviation during injection, and the predicted values were uniformly compensated for in subsequent injection experiments. The LSTM model performed best with a training set of 85%, a test set of 15%, an epoch of 300, a batch number of 256, and 32 hidden layer neurons. After compensation, the mean infusion deviation for large doses was reduced by 12.05%, and the maximum deviation by 14.12%.

Mathematical modeling and nonlinear bilateral multivalued stochastic integral equations

In this paper, we begin our study by exploring a hypothetical model of stochastic growth of a population, using a single-valued stochastic integral equation that incorporates the control of feeding and harvest. Taking into account the inaccuracies and uncertainties in the measurements, we are led to a nonlinear bilateral multivalued stochastic integral equation that contains multivalued stochastic integrals on both sides of the equation. Due to the possibility of absence of an element opposite to a fixed set, such an equation cannot be reduced to classical unilateral notation with the sign of sum of sets only on one side. The fundamental question arises: Is there a solution to the equation under consideration, and is it the only one? By imposing on the coefficients of the equation the condition of satisfying a certain integral inequality, we prove the existence and uniqueness of solution of the considered equation. The result is preceded by a few lemmas with the sequence of approximate solutions. We also show that solutions have the property of stability. Finally, it has been demonstrated that the results obtained can be applied to establish corresponding theorems for deterministic bilateral multivalued integral equations.

Social support and technophobia in older patients with coronary heart disease: The mediating roles of eHealth literacy and healthcare technology self-efficacy

Objectives The purpose of this study was to explore the relationship between social support, eHealth literacy, healthcare technology self-efficacy, and technophobia. It also analyzed the mediating effect of eHealth literacy and healthcare technology self-efficacy between social support and technophobia. Methods Older patients with coronary heart diseases (n = 396) from four communities in Qingdao were interviewed using the Technophobia Scale, Social Support Rating Scale, eHealth Literacy Scale and Healthcare Technology Self-Efficacy Scale. Data were analyzed using common method deviation test, Pearson’s bivariate correlation analysis, and mediation analysis using the PROCESS macro. Results Social support was significantly positively correlated with eHealth literacy (r = 0.614, p < 0.01) and healthcare technology self-efficacy (r = 0.635, p < 0.01), and significantly negatively correlated with technophobia (r = −0.578, p < 0.01). eHealth literacy was significantly positively correlated with healthcare technology self-efficacy (r = 0.822, p < 0.01), and significantly negatively correlated with technophobia (r = −0.651, p < 0.01). Healthcare technology self-efficacy was significantly negatively correlated with technophobia (r = −0.700, p < 0.01). Social support had a total indirect effect on technophobia of −0.410, with eHealth literacy and healthcare technology self-efficacy mediating 24.9% and 30.2% of this effect respectively, and the chain mediating effect accounting for 44.9%. Conclusions Our findings provide a theoretical reference for nursing to develop appropriate interventions to alleviate technophobia among older patients with CHD.

Impact of window design on the lighting environment of GAP-certified naturally illuminated broiler houses

Recent changes in consumers’ desire for alternative rearing programs have prompted integrators to adopt varying fenestration designs in commercial broiler houses, most notably the inclusion of natural light (NL) via windows. The objectives of this study were to compare light intensity, spatial distribution, and uniformity in two 18.2 × 182.9 m commercial broiler houses in southeast Alabama with different window designs. Window designs in both houses met Global Animal Partnership (GAP) NL standards. The one-sided window (1SW) design had 23 translucent windows (1.42 × 1.09 m) that were all located on the north wall. The two-sided window (2SW) design had 58 translucent windows (0.95 × 0.60 m) located on both the north and south sidewalls and two additional windows of the same size on the west end wall (brooding end). Data acquisition systems were constructed to collect floor light intensity at 750 locations per replicate in both houses. Two replicates were collected for tunnel and brooding conditions in each house at solar noon ± 1 h. Mean light intensity in three house sections (fan, mid, and pad) were compared as well as whole house data for both tunnel and brood conditions. The GSTAT package in R was used to spatially map light intensities. During tunnel ventilation conditions, mean light intensity values were 1.8 times and 6.5 times higher in the mid and pad sections, respectively, in the 2SW design than the 1SW design. Light intensities during brood conditions were similar between designs (1SW = 44.7 lx; 2SW = 43.7 lx) due to the masking effect of the brighter artificial lighting targets (brooding = 43 lx; tunnel = 1 lx). Coefficients of variation (CV) were higher in the 1SW than the 2SW during brooding [63.7% (1SW) vs 56.4% (2SW)] and tunnel [192.2% (1SW) vs 143.9% (2SW)], indicating reduced spatial uniformity in the 1SW house. This study showed that the 2SW design can lead to higher overall intensities and improved spatial uniformity during tunnel conditions. Results from this study could help inform future window designs in commercial broiler houses.

Does population agglomeration of urban clusters boost total factor productivity of enterprises? Evidence from listed companies in China

Introduction The role of agglomeration economics in enhancing productivity is well-recognized, yet the influence of population agglomeration of urban clusters on Total Factor Productivity (TFP) within the enterprises of the agglomerates remains a relatively uncharted area. This study aims to investigate the impact of population agglomeration of urban clusters on the TFP of enterprises and its underlying mechanisms. Data sources The data for firm-levelwere sourced from the CSMAR and Wind databases. City-level data were obtained from the China City Statistical Yearbook and the China Urban Construction Statistical Yearbook. Research method A fixed-effects model was employed. Key findings ① The baseline regression shows that population agglomeration of urban clusters significantly bolsters the TFP of enterprises. ② Heterogeneity tests further reveal that this simulative effect is more pronounced in the eastern region, inter-provincial city clusters, and large cities.. ③ The underlying mechanisms indicate that population agglomeration of urban clusters, through its market effects and scale economic effects effectively reduce production costs, thereby boosting overall production efficiency and promoting the elevation of TFP in enterprises. Policy implications To scientifically guide the orderly population agglomeration of urban clusters, it is essential to fully leverage the marketization effects of population agglomeration of urban clusters and deepen the specialization and division of labor within these clusters. This study provides empirical evidence and important references for policymakers to effectively leverage the marketization and specialization effects of urban cluster population agglomeration, thereby promoting new urbanization and achieving high-quality development.

Identification of potentially effective drugs for metabolic dysfunction-associated steatotic liver disease against liver cirrhosis: In-silico drug repositioning-based retrospective cohort study

Background Metabolic dysfunction-associated steatotic liver disease (MASLD) is a major risk factor for liver cirrhosis, yet effective prevention or treatment strategies remain limited. To address this, we utilized a signature-based in silico drug repositioning approach to identify potential therapeutics for MASLD that may reduce the risk of cirrhosis. Methods We analyzed gene expression datasets to identify differentially expressed genes (DEGs) in MASLD and matched them to candidate drugs using L1000CDS2. We further validated potential drugs by cross-referencing with prescription data from the Korea National Health Insurance Service (NHIS). Participants who underwent health screenings between 2013 and 2014 were included. MASLD was diagnosed in individuals with hepatic steatosis (fatty liver index ≥60) and at least one cardiometabolic risk factor. Results We identified 11 drug candidates and analyzed 49,555 MASLD patients (mean age: 63.0 years, SD: 8.6). Atenolol (SHR: 0.81; 95% CI: 0.72–0.92; P < 0.001), isosorbide dinitrate (SHR: 0.82; 95% CI: 0.73–0.93; P = 0.001), and valsartan (SHR: 0.52; 95% CI: 0.45–0.60; P < 0.001) were associated with a reduced risk of cirrhosis. Conversely, amlodipine-based combinations (SHR: 1.24; 95% CI: 1.11–1.39; P < 0.001), torasemide (SHR: 1.39; 95% CI: 1.24–1.56; P < 0.001), and valsartan-based combinations (SHR: 1.22; 95% CI: 1.09–1.37; P < 0.001) were linked to an increased risk. Conclusions Our findings suggest that antihypertensive drugs such as atenolol and isosorbide dinitrate may protect MASLD patients from cirrhosis, providing valuable insights for clinical applications and treatment strategies. Limitations This study is limited to drugs registered in the Korean NHIS, potentially excluding other relevant candidates. Additionally, the absence of dietary and genetic data in the NHIS database may introduce residual confounding. Lastly, as the study population consists solely of Korean adults, the findings may not be generalizable to other populations.

Comparative analysis of pattern-triggered and effector-triggered immunity gene expression in susceptible and tolerant cassava genotypes following begomovirus infection

South African cassava mosaic virus (SACMV) is one of several bipartite begomoviruses that cause cassava mosaic disease (CMD) which reduces the production yield of the cassava (Manihot esculenta Crantz) crop in many tropical and subtropical regions. SACMV DNA-A and DNA-B encoded-proteins act as virulence factors that aid in inducing different disease severity depending on the host response. Recent evidence suggests a mutual potentiation of cell membrane receptor-associated pattern-triggered immunity (PTI) and nucleotide leucine-rich repeat (NLR) effector-associated immunity (ETI) in plant immune responses. This study aimed to compare expression of SACMV virulence factors, and PTI/ETI, in SACMV-infected susceptible T200 and tolerant TME3 cultivars. Expression of SACMV virulence factors differed between SACMV-infected T200 and TME3 plants at 12, 32 and 67 days post infection (dpi). Notably, at the early stage of infection (12 dpi), expression in TME3 of AV1 and AC2 virulence factors were 10-fold and 30-fold down-regulated, respectively, compared to susceptible T200. At systemic infection (32 dpi) AV1 expression was also significantly lower (4-fold) in TME3 compared to T200. Expression of AC2 (that targets host innate immunity), while significantly lower in both T200 and TME3 at 32 dpi compared to 12 dpi, was also significantly down-regulated (16-fold) in TME3 compared to T200. TME3 recovers around 67 dpi and virus load decreases by 33%, while in T200, symptoms and high SACMV replication persist. Identification and comparison of induced PTI and ETI associated genes upon SACMV-infection in susceptible T200 and tolerant/recovery TME3 cassava genotypes was achieved by whole transcriptome sequencing (RNA-seq) and by reverse transcriptase quantitative PCR (RT-qPCR). Analyses revealed reduced expression of PTI-associated signalling and response genes during SACMV systemic/symptomatic infection (32 dpi) in cassava genotypes. In addition, hydrogen peroxide (H2O2) production, a PTI indicator, was significantly reduced in the symptomatic viral infection stage at 32 dpi. Concurrently at 32 dpi, transcription of ETI signalling and response genes as well as SA biosynthesis and response genes, were upregulated during SACMV systemic infection in TME3. These results indicate that SACMV targets PTI-associated genes during systemic infection at 32 dpi to subvert PTI-mediated antiviral immunity in cassava, which results in reduced induction of ROS production. Differential expression of specific NLR-associated genes also differed between susceptible and tolerant cultivars at 12, 32 and 67 dpi. SACMV virulence factors were shown to play a role in symptom severity in T200 and TME3.

Towards sustainable solutions: Effective waste classification framework via enhanced deep convolutional neural networks

As industrialization and the development of smart cities progress, effective waste collection, classification, and management have become increasingly vital. Recycling processes depend on accurately identifying and restoring waste materials to their original states, essential for reducing pollution and promoting environmental sustainability. In recent years, deep learning (DL) techniques have been applied strategically to enhance waste management processes, including capturing, classifying, composting, and disposing of waste. In light of the current context, the study presents an innovative waste classification model that utilizes a tailored DenseNet201 architecture coupled with an integrated Squeeze and Excitation (SE) attention mechanism and the fusion of parallel Convolutional Neural Network (CNN) branches. The integration of SE attention enables squeezing the irrelevant features and excites the important ones and the fusion of parallel CNN branches enhances the extraction of intricate, deeper, and more distinguishable features from waste data. The evaluation of the model across four publicly available datasets, along with three additional datasets to enhance waste diversity and the model’s reliability, and the incorporation of Grad-CAM to visualize and interpret the model’s focus areas for transparent decision-making, confirms its effectiveness in improving waste management practices. Furthermore, this model’s successful deployment in a web-based sorting system marks a tangible stride in translating theoretical advancements into on-the-ground implementation, promising heightened efficiency and scalability in waste management practices. This work presents a precise solution for adaptable waste classification, heralding a paradigm shift in global waste disposal norms.

Mesoporous Single-Crystal High-Entropy Alloy

Prevalence of crisis pregnancy center attendance among women in four U.S. states

Objectives Crisis pregnancy centers (CPCs) typically hold missions of preventing abortion, opposing contraception, and promoting abstinence outside of marriage. They often lack transparency about their services, posing as medical facilities or even as abortion clinics. Given the lack of evidence on the extent to which people use crisis pregnancy centers, we sought to quantify the prevalence of ever attendance at a CPC among adult, reproductive-aged women from Survey of Women data from four states. Study design We analyzed cross-sectional data from population-representative surveys conducted among adult, reproductive-age women in 2018–2019 in Iowa (N = 2,425) and in 2019–2020 in Arizona (N = 2,132), New Jersey (N = 2,132), and Wisconsin (N = 2,095). Using survey weights, we calculated the prevalences of ever CPC attendance among those with a history of pregnancy or testing for pregnancy. We focused on this subset as this comprises the women who might have had cause to attend a CPC. We also used Poisson regression to test associations between demographic correlates and ever attendance by state. Results Prevalence of ever CPC attendance in adult, reproductive-age women with a history of pregnancy or testing for pregnancy was statistically significantly higher in Arizona (20.2%; 95% CI, 17.6%-23.1%) compared to Iowa (14.5%; 95% CI, 12.6%-16.7%), Wisconsin (14.3%; 95% CI, 12.1%-16.8%).), and New Jersey (11.6%; 95% CI, 9.6%-13.8%). Age, race/ethnicity, and socioeconomic status were not correlated with ever CPC attendance among women with a history of pregnancy or testing for pregnancy in Arizona, Iowa, and New Jersey. In Wisconsin, prevalence was lower among those in the lowest socioeconomic stratum. Conclusions Ever attendance at CPCs is not rare, ranging from 11.6%-20.2% in the four states evaluated. The present study serves as an important baseline given that the prevalence may change as pregnancy options become increasingly restricted.