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Deep learning for wetland vegetation mapping in the southeastern United States: evaluating site-specific accuracy and classification challenges
Discovery of an isoflavone biosynthetic pathway in Iridaceae plants
Why do people comply with health guidelines in a competing information environment?
The COVID-19 pandemic unfolded in parallel with an infodemic where competing information from formal and informal sources shaped protective behavior. This study conducted a secondary analysis of cross-sectional survey data from 742 U.S. adults to examine how reliance on different information channels influenced risk perceptions, socio-political beliefs, and protective intentions. Structural equation modeling revealed that reliance on formal sources, such as government websites and mainstream news, was positively associated with perceived severity, reduced conspiracy endorsement, and more liberal political orientation, all of which increased mask-wearing and vaccination intentions. Reliance on informal sources, including social media and peer networks, reduced severity perceptions, heightened conspiracy beliefs, and reinforced more conservative orientations, which in turn undermined compliance. Perceived severity functioned as a central mediator, directly encouraging mask use and indirectly promoting vaccination through reduced conspiracy endorsement. Political ideology and conspiracy beliefs further shaped vaccine intentions, highlighting the ideological pathways through which information exerts influence. Mask-wearing and vaccination clustered together, indicating a generalized orientation toward protective action. The model underscored the critical role of information environments as upstream determinants of health behavior during crises. These findings emphasize that managing both formal and informal channels is essential for effective crisis communication and for strengthening public compliance in future health emergencies.
Soil pollution and health risk assessment from potentially harmful elements at various land types in the dust center of West Asia (Sistan, Iran)
Early-Stage Corticostriatal Hyperactivity Impairs Cognitive Flexibility Alongside Striatal Cholinergic Dysfunction in an Alzheimer’s Disease Model
Abstract Cognitive flexibility declines early in Alzheimer’s disease, yet the underlying circuit mechanisms remain unknown. Here, we report that young 5xFAD mice exhibit deficits in instrumental reversal learning prior to spatial memory impairment. This behavioral inflexibility is associated with abnormal neuronal reactivation in the medial prefrontal cortex and dorsomedial striatum. Electrophysiological recordings reveal that medial prefrontal cortex neurons are hyperexcitable and receive increased excitatory input. Furthermore, glutamatergic transmission from the medial prefrontal cortex to striatal direct-pathway medium spiny neurons is enhanced and coincides with strengthened inhibitory transmission onto striatal cholinergic interneurons, reduced spontaneous firing, and diminished striatal acetylcholine release. Critically, sustained chemogenetic inhibition of this corticostriatal circuit attenuates cortical amyloid accumulation, reduces glutamatergic transmission, and increases acetylcholine levels. This also rescues reversal learning deficits in 5xFAD mice. Here, we show that pathological corticostriatal hyperactivity contributes to early cognitive inflexibility in a mouse model of Alzheimer’s disease.
Research on trajectory tracking control of tracked vehicles based on hydraulic motor system identification and Laguerre-MPC
To address the high computational cost of model predictive control and the high complexity associated with physics-based modeling of hydraulic drive systems in trajectory tracking of tracked unmanned vehicles, a hierarchical control framework is proposed to enhance trajectory tracking performance. In the upper-layer control, a Laguerre function-based model predictive control (Laguerre-MPC) strategy is developed to reduce the computational burden while maintaining control performance. In the lower-layer control, Hammerstein-Wiener identification is employed to establish control models for the left and right hydraulic motors, thereby avoiding the modeling complexity inherent to hydraulic systems. Moreover, a proportional-integral-derivative (PID) controller is incorporated into the lower-layer control to improve disturbance rejection during operation. Simulation results indicate that Laguerre-MPC yields substantially lower computational complexity than conventional MPC, with the average time required for a single optimization being only 24.3% of that required by conventional MPC, which improves the real-time capability of the control algorithm. Furthermore, field experiments are conducted on a tracked unmanned vehicle equipped with relevant sensors, including speed tracking and trajectory tracking tests under specified operating conditions. The results confirm the effectiveness of the proposed framework: compared with the conventional MPC + PID scheme, the proposed method achieves higher tracking accuracy, improving the average speed tracking accuracy by 28.7%, the straight-line trajectory tracking accuracy (root mean square error) by 65.5%, and the curved trajectory tracking accuracy (root mean square error) by 10.1%. The proposed framework provides a practical and efficient solution for trajectory tracking control of tracked unmanned vehicles with clear engineering applicability.
Willow plantation shapes the properties of arable soils under temperate climatic conditions
Stepwise emergence of recombination suppression precedes fissiparous asexuality in the planarian Schmidtea mediterranea
Abstract A central paradox in evolutionary biology is the rarity of asexual reproduction, often attributed to developmental constraints and long-term costs. Yet, fissiparous asexuality—where animals split and regenerate—is widespread among planarians, hinting at genomic features predisposing them to asexuality. We investigate the genomic underpinnings and evolutionary consequences of asexuality in the planarian Schmidtea mediterranea , which exists as both obligately fissiparous and sexual strains. We generate a haplotype-phased genome assembly of the asexual strain and collect population genomic data to uncover extensive heterozygous chromosomal rearrangements affecting all chromosomes. We show that these rearrangements arose in a sexually reproducing ancestor without directly disrupting reproductive genes but instead progressively suppressing recombination across the genome. The asexual genome exhibits minimal deleterious mutation accumulation, indicating a low cost of asexuality. Population-genomic data indicate that persistent asexuality originated recently (0.17–0.4 Ma), however the young age is insufficient to explain the low mutational burden. Instead, planarians may exploit the lack of a single-cell bottleneck in fissiparous reproduction to mitigate the costs of asexuality. Altogether, our results are consistent with a model in which stepwise recombination suppression due to structural rearrangements eroded the benefits of sex and enabled the emergence of fissiparous asexuality in S. mediterranea .
A multimodal ConvNeXt-Tiny deep learning model for simultaneous prediction of IDH mutation and Ki-67 expression in gliomas
Objective To construct and validate a multi-task deep learning model based on ConvNeXt-Tiny for synchronous prediction of isocitrate dehydrogenase (IDH) mutation status and Ki-67 expression level in gliomas. Materials and Methods This retrospective multicenter study included adult patients with diffuse glioma from two hospitals, which served as the training set and the independent validation set, respectively. All patients underwent multimodal MRI examinations within 4 weeks before surgery, including T2-weighted imaging (T2WI), T2-fluid attenuated inversion recovery (T2-FLAIR), contrast-enhanced T1-weighted imaging (T1CE), and three-dimensional arterial spin labeling imaging (ASL). MRI data were uniformly preprocessed to extract traditional radiomics features, and a dual-task deep learning model based on ConvNeXt-Tiny was constructed. Clinical characteristics, radiomics features, and deep learning features were multimodally fused to establish the multimodal model and were compared with other prediction models. Model performance and clinical utility were evaluated using receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis, and the net reclassification index (NRI). SHapley additive explanations (SHAP) analysis and gradient-weighted class activation mapping (Grad-CAM) were applied for visual interpretation of model decisions. Results The multimodal model demonstrated the best diagnostic performance for both IDH mutation status and Ki-67 expression level prediction. For IDH prediction, the multimodal model achieved AUCs of 0.901 and 0.883 in the training set and test set, respectively, while for Ki-67 prediction, the area under the curves (AUCs) reached 0.939 and 0.924. NRI analysis further confirmed that the multimodal model significantly improved case reclassification in both tasks. Calibration curves and the Hosmer–Lemeshow test indicated good model fit, and decision curve analysis showed a higher net clinical benefit. SHAP analysis revealed that model predictions mainly relied on deep learning features, particularly those derived from T1CE, ADC, and cerebral blood flow (CBF) images, whereas radiomics features and clinical variables contributed less. Grad-CAM visualizations demonstrated that the model primarily focused on tumor-related regions. Conclusion This study developed a ConvNeXt-Tiny-based multi-task model that enables preoperative synchronous prediction of IDH mutation and Ki-67 status in adult diffuse glioma and exhibits robust performance superior to single-task and traditional models.
Slowing the spread of treatment failure to artemisinin-based combination therapies in Uganda
Clinical features, disease severity, and outcomes of pertussis in hospitalized children: A retrospective study from Serbia
Background Severe pertussis remains a major cause of morbidity and mortality in early infancy, particularly among unvaccinated and preterm infants who lack sufficient maternally derived antibody protection. This study aimed to identify clinical and laboratory predictors of severe disease and fatal outcomes in hospitalized infants and young children with PCR- or serologically confirmed pertussis. Methods We conducted a retrospective study of 107 pediatric patients hospitalized with pertussis at a tertiary care center in Serbia between 2015 and 2025. Clinical characteristics, laboratory parameters, and outcomes were analyzed. Logistic regression—including Firth’s penalized models where appropriate—was used to explore predictors of PICU admission, mechanical ventilation (MV), and mortality. Viral coinfections were assessed using multiplex PCR, and leukocyte dynamics were monitored through standardized follow-up testing. Results Thirteen children (12.1%) required PICU admission and 12 (11.2%) underwent MV. Five patients (4.7%) died; all were unvaccinated infants younger than 2 months of age. Prematurity was a strong independent predictor of PICU admission and MV. Higher absolute lymphocyte counts and an elevated neutrophil-to-lymphocyte ratio at admission were also associated with severe disease. Viral coinfection was documented in 22.4% of patients and was associated with increased mortality. In exploratory analyses, both viral coinfection and elevated N/L ratio were associated with fatal outcome; however, these findings should be interpreted with caution due to the small number of events. Conclusions Severe and fatal pertussis predominantly affected infants in the first months of life, especially those born preterm and those without maternal or postnatal vaccine-derived protection. Viral coinfection was associated with worse clinical outcomes. These findings highlight the importance of early identification of high-risk patients and support preventive strategies targeting early infancy, including maternal pertussis immunization.
Rising tree mortality in France is associated with distinct seasonal climate anomalies
Abstract Tree mortality is rising across European forests, yet its dominant drivers remain difficult to disentangle. Analyzing over 500,000 trees from the French National Forest Inventory (2015-2023), we observe increasing mortality rates across major species. Using ensemble modelling and explainable machine learning, we identify tree size, competition, and seasonal climate anomalies as the primary mortality drivers. Warmer winters and springs are the most frequent and influential climate-related predictors, likely reflecting disturbed phenology and enhanced pest survival during milder cold seasons. Warmer summers are less frequently selected but similarly influential, possibly related to increased pest activity and drought stress. We further identify three drought-related anomaly patterns, each consistent with a distinct mortality pathway: long, intense droughts likely induce acute hydraulic failure; on-average drier summers might drive gradual carbon starvation; and insufficient post-drought rainfall possibly constrains recovery. Anomalously wet springs also frequently emerge as strong predictors of elevated mortality risk, particularly in tall temperate tree species. We hypothesize that this reflects the influence of structural overshoot, whereby wet spring conditions promote rapid canopy growth that may increase vulnerability to subsequent drought. Together, our findings indicate that tree mortality is shaped by interacting and potentially compounding seasonal climate anomalies rather than a single extreme event.
Influence of internal migration on antenatal care utilization in Bangladesh: Findings from a nationally representative cross-sectional survey
Internal migration plays a crucial role in shaping healthcare utilization patterns, particularly in developing countries. However, its influence on maternal healthcare utilization, especially on antenatal care (ANC) utilization, remains underexplored. This study examines the association between internal migration and receiving antenatal care services among women aged 15–49 years using nationally representative cross-sectional data from the 2022 Bangladesh Demographic and Health Survey. This study analyzed 4,306 currently married women who had at least one live birth in the three years preceding the survey. Descriptive statistics, chi-square tests, and multivariable logistic regression models were employed to examine the association of migration status with receiving professional ANC and quality ANC visits. Our analysis shows that rural-to-urban migrants had the highest likelihood of receiving both professional ANC and quality ANC visits (68.5% and 38.2%, respectively). The adjusted odds ratios show that rural-to-urban migrants were significantly more likely to receive a professional ANC visit (AOR = 1.58, 95% CI: 1.11–2.24) than the urban residents, whereas urban-to-rural migrants were significantly less likely to receive that service (AOR = 0.74, 95% CI: 0.60–0.91) than their urban counterparts. A similar pattern was observed for the utilization of quality ANC (AOR = 0.73, 95% CI: 0.58–0.94) among urban-to-rural migrants. These findings indicate apparent inequalities among different groups of migrant women in their access to maternal healthcare services. Strengthening rural healthcare infrastructure and enhancing awareness about the importance of ANC could help ensure equitable access to maternal health care services in Bangladesh and other countries with similar contexts.
Parallel execution of nonlinear logic circuits using reconfigurable free-space diffractive optics
Pneumococcal conjugate vaccine effectiveness against hypoxemia in children with suspected pneumonia in Kenya; analysis from a real-world sentinel surveillance platform
The 10-valent pneumococcal conjugate vaccine (PCV-10) has reduced the burden of pneumococcal disease in children. Integrated facility-based sentinel surveillance (IFBS) monitors a range of common causes of febrile illnesses in Kenya. We used this system to assess the real-world vaccine effectiveness (VE) of PCV-10 against hypoxemia among children with suspected pneumonia in Kenya. We analysed IFBS data collected from 13 sites across Kenya from 2017 to 2024. We included children aged 6 weeks to 59 months with reported fever or temperature ≥38.0°C, respiratory features consistent with suspected pneumonia, and a copy of their vaccination records (i.e., child health booklet). We excluded children with a positive test result indicating a non-Pneumococcal aetiology (i.e., positive result on a multiplex PCR, malaria microscopy or rapid diagnostic test, or SARS-CoV-2 PCR). We assessed the association of vaccination status with hypoxemia, defined as an oxygen saturation of ≤90%, adjusting for age, sex, and year. VE was calculated as 1 minus the odds ratio of hypoxemia among children with suspected pneumonia calculated using generalized estimating equations to account for clustering by site. Overall, 3,533 children were analysed, with 94% being up to date with PCV-10 vaccination. The median patient age was 11 months (interquartile range: 6–17). Hypoxemia was observed in 37% of fully vaccinated children, 41% in partially vaccinated children, and 52% in unvaccinated children (χ² test, p = 0.03). The adjusted VE for full vaccination against hypoxemia in children with suspected pneumonia was 39% (95% confidence interval: 6–61%). Among children with suspected pneumonia in Kenya, PCV-10 vaccination was associated with reduced hypoxemia. The PCV-10 coverage in this dataset was high, potentially reflecting a robust routine vaccination effort since PCV-10 was introduced in Kenya in 2011. High-quality surveillance data can be used to provide real-world evidence to support routine immunization programs.
Programmable Spatial Demixing in Prebiotic Coacervates
Editorial Note: Machine learning–assisted optimization of a terahertz photonic metamaterial absorber for blood cancer detection
Inherent tissue homeostasis of the juvenile metaphysis provides a foundation for osteosarcoma development
Abstract Osteosarcomas preferentially arise in the metaphysis of juvenile long bones, near the growth plate, unlike most cancers, whose incidence increases with age. Here, we show that p21, a negative regulator of the cell cycle, is induced in proliferating juvenile metaphyseal osteoblasts in response to DNA replication-associated damage. Single-cell RNA sequencing defines a differentiation hierarchy from multipotent progenitors to mature osteoblasts and identifies immature osteoblasts enriched for proliferation and replication stress responses. p21-positive metaphyseal osteoblasts associate with growth plate Indian hedgehog expression and decline after growth plate maturation or Hedgehog inhibition. c-Myc induction selectively promotes juvenile osteoblast proliferation despite p53 activation, but this proliferative response remains Hedgehog-dependent and ceases after growth plate maturation. By contrast, p53 inactivation enables sustained Hedgehog-independent proliferation of c-Myc -induced osteoblasts and lung metastasis. These findings reveal juvenile metaphyseal tissue homeostasis as a potential basis for the age of onset, anatomical specificity, and mutational profile of human osteosarcomas.
In-silico identification of bacterial key-genes directly or indirectly associated with the development and progression of colorectal cancer for exploring anti-bacterial agents
Colorectal cancer (CRC), which includes malignancies of the colon and rectum, constitutes a major global health challenge. Though there are several drugs that targets CRC-related genes/proteins, but their performance is not yet reach to the satisfactory level. Moreover, their effectiveness gradually decreases over time with long-term use, a phenomenon known as drug resistance. Therefore, it is required to explore new alternative candidate drugs against CRC. Several studies recommended CRC-related dysregulated host-genes guided candidate drugs. However, microbiome guided drug discovery particularly targeting bacterial key genes (bKGs) within CRC-associated gut microbiota remains very limited. This study aims to identify bKGs as antibacterial targets within CRC-associated bacterial taxa for exploring anti-bacterial agents. At first, we analysed a 16S rRNA-seq profile dataset that contained 24 CRC and 50 healthy samples, where beta diversity analysis results showed significant differences in bacterial compositions between CRC and HC groups. Differential abundance analysis with threshold values at |log 2 FC| > 1.0 and adjusted p -value < 0.05 identified 42 significantly altered bacterial taxa of which Bacteroides fragilis, Bacteroides ovatus, Bacteroides uniformis, and Flavonifractor plautii were prioritized based on effect size and published literature reporting their association with CRC. Further, an integrative subtractive genomics and protein-protein interaction (PPI) network analyses was used to identify top-ranked 10 essential bKGs ( ribD, ribBA, murA, alr, hisI, hisE, hisD, hisG, hisH, and hisB ) from these four CRC-associated bacterial taxa as putative antibacterial targets. Finally, three candidate drug molecules (Sulfasalazine, Aminoglutethimide, and Tipiracil) were recommended as the preliminary bKGs-guided candidate anti-bacterial agents for CRC through molecular docking and ADME/T analyses. Further experimental and clinical validation is required to establish these compounds as the effective drugs targeting the bKGs for CRC. Thus, these findings may provide insights for developing innovative anti-bacterial treatment approach relevant to CRC.