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Screening for developmental delay at 18 months using the Infant Toddler Checklist: A validation study

Objective The Infant Toddler Checklist (ITC) may be promising as a single tool at the 18-month visit to detect a range of developmental concerns. We examined the predictive validity of the ITC; and the association between positive ITC screening and health care utilization (HCU). Methods Prospective cohort study of children at average-risk for developmental delay attending their 18-month visit in primary care in Toronto, Canada. Parents completed the ITC. HCU from the single-payer provincial health system was collected from health administrative databases ensuring complete follow-up. Physician billing code for a neurodevelopmental consultation was the primary outcome and criterion measure. Six other HCU types were assessed. Results Of 1460 children with a mean age at screening of 18 months, 11% screened ITC positive. Mean age at follow-up was 8 years, 2.6% had a neurodevelopmental consultation. Screening test properties (with neurodevelopmental consultation as the criterion measure): 40% sensitivity (95% CI 24%, 57%), 90% specificity (95% CI 88%, 91%), 10% false positive rate (95% CI 9%, 12%). Using multivariable negative binomial regression, a positive ITC was associated with higher rates of 6 of 7 HCU types, including neurodevelopmental consultation (aRR 2.78, 95% CI 1.37, 5.67, p = 0.005). Conclusion The ITC had high specificity and a low false positive rate, suggesting that most children with a negative ITC will not have a later neurodevelopmental consultation, and use of the tool may minimize unintended harms such as anxiety and resource use. The low sensitivity highlights the importance of ongoing developmental surveillance. Low sensitivity of other screening tools is discussed.

The association between agricultural activities and arthritis in middle-aged and elderly people: Findings from a cohort study based on CHARLS

The number of arthritis samples in China has been increasing. Currently, there is limited research on the relationship between agricultural activities and arthritis. This study aimed to investigate the correlation between agricultural activities and arthritis risk based on the China Health and Retirement Longitudinal Study (CHARLS). A total of 694 participants from the 2015 CHARLS study were included, with 443 samples as controls and 251 samples classified as affected. Baseline characteristics of all participants were compared using the Student t-test and Chi-square test. Subsequently, the association between agricultural activities and arthritis risk was explored through multivariable generalized linear models (GLM) and weighted logistic regression models. Additionally, the diagnostic performance and clinical utility of agricultural activities for arthritis were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis. Finally, the difference in model prediction performance before and after adjusting for covariates was assessed using the net reclassification index (NRI) and integrated discrimination improvement (IDI). Five covariates showed significant associations with arthritis, and agricultural activities had a significant effect (P = 0.026). Furthermore, a significant positive correlation was observed between agricultural activities and arthritis (Model 1: odds ratio (OR)=1.44, 95% confidence interval (95%CI): 1.06–1.97, P = 0.021; Model 2: OR=1.61, 95%CI: 1.17–2.24, P = 0.004; Model 3: OR=1.74, 95%CI: 1.17–2.60, P = 0.007). Risk stratification analysis further indicated that agricultural activities were a risk factor for arthritis (OR=1.736, 95%CI: 1.168–2.597, P < 0.01). Moreover, after adjusting for covariates, ROC curve analysis and decision curve analysis demonstrated good predictive performance of agricultural activities for arthritis. Lastly, the NRI and IDI indices indicated that Model 3 outperformed Models 1 and 2 in prediction performance. In conclusion, a significant positive correlation existed between agricultural activities and arthritis risk, providing insights for the early detection and prevention of arthritis.

Health behavior and mental health by gender in Korean adults before, during, and after the COVID-19 pandemic

Objective Coronavirus disease 2019 (COVID-19) has been a global health crisis, and its aftermath has had a profound impact on mental health and health behaviors of Korean adults. This study aimed to determine the health behavior and mental health among adults aged 19 years and older before, during, and after the COVID-19 pandemic. Methods We used 2019–2022 data from Korea National Health and Nutrition Examination Survey (KNHANES) to analyze a comparative assessment of drinking, smoking, sleep, and stress in 2019, 2020, 2021, and 2022. Chi-square, one-way ANOVA and logistic regression analysis was performed with using Stata version 18.5. Results The proportion of drinking more than four times a week was slightly lower in the early- and with-COVID-19 and higher in the pre- and post-COVID-19, and was the same in the analysis of gender. The proportion of smoking in men decreased over time, whereas that in women increased. Both gender increased weekday sleep time in the pre- and early-COVID-19, and decreased in the post-COVID-19. Stress was slightly reduced in the pre- and post-COVID-19 compared to early-COVID-19 in men, and has decreased in the post-COVID-19 in women. Comparing these variables adjusting for the sociodemographic variables by years, frequency of drinking decreased in 2020 and 2021 for both men and women, but there was no difference in 2022. There was no statistically significant difference in current smoking for both men and women. Suicidal ideation decreased in men in 2022, but increased in women during the early-COVID-19. Conclusions Drinking and smoking showed a somewhat positive pattern of behavior change, but in the post-COVID-19, unhealthy behaviors have increased again, requiring active health interventions.

The interplay between foraging choices and population growth dynamics

Population growth models typically incorporate attributes observable at the population scale, often overlooking the trade-off between individual-level reproductive and behavioral traits and their influence on population size. Individuals’ survival and reproductive abilities are expected to dynamically evolve depending on the population size, which is affected by the aggregation of individual decisions. Reconciling individual-level incentives with population-level dynamics requires an integrative framework that explicitly addresses the intertwined relationships between population growth and individual decision-making processes. We formulate a multiscale modeling framework that integrates the logistic population growth model with an optimal foraging model to study the interplay between individual-level behavioral incentives and population growth dynamics. Specifically, we explicitly model individuals’ decision-making process, which shapes their reproductive fitness and, ultimately, influences population growth. Moreover, we incorporate the concept of resource limitations from the logistic growth model to account for dynamic incentives that depend on population size. Our results yield insights into the multiscale processes, such as the selection pressure of behavioral choices and the cost-benefit of social activities that influence population robustness beyond mere size and aggregated reproductive traits. We found that populations exhibiting similar limiting sizes may undergo significantly different transient dynamics. This variation may be induced by environments imposing distinct behavioral cost-benefit trade-offs that require individuals to exert different levels of foraging effort to maintain reproductive viability.

Superior cardiovascular protection with GLP-1 RAs over SGLT2 inhibitors in DM and HFpEF: A propensity score matching study

Background Heart failure with preserved ejection fraction (HFpEF) and diabetes mellitus (DM) are interrelated conditions associated with high morbidity and mortality. This study compared the cardiovascular protective effects of glucagon-like peptide-1 receptor agonists (GLP-1 RAs) versus sodium-glucose cotransporter-2 (SGLT2) inhibitors in this population. Methods This retrospective cohort study used data from the TriNetX database. It included 2,177 matched pairs of patients with HFpEF and DM treated with either GLP-1 RAs or SGLT2 inhibitors. Outcomes assessed over three years were a composite of all-cause mortality and progression to systolic heart failure, acute myocardial infarction, or stroke. Results GLP-1 RAs significantly reduced the risk of composite outcomes at one year (Hazard Ratio, HR 0.784; 95% CI, 0.658–0.934), two years (HR 0.813; 95% CI, 0.702–0.941), and three years (HR 0.825; 95% CI, 0.717–0.950). Specifically, GLP-1 RAs showed significantly reduced risks of progression to systolic heart failure (HR 0.60) and stroke (HR 0.75) compared to SGLT2 inhibitors. These protective effects were most pronounced in the first year and showed a slightly diminishing trend. While not statistically significant, GLP-1 RAs also exhibited a trend towards fewer myocardial infarctions (HR 0.83) and lower mortality rates (HR 0.83) than SGLT2 inhibitors. Subgroup analyses revealed more significant benefits in patients aged ≥60, women, Caucasians, those without moderate-to-severe chronic kidney disease or chronic ischemic heart disease, and those with better-controlled DM. Conclusions Among HFpEF patients with DM, GLP-1 RAs demonstrated superior cardiovascular protective effects compared with SGLT2 inhibitors over a 3-year follow-up period. Further randomized trials are required to confirm these findings.

Individualized diagnosis of rheumatoid arthritis: A rank-based qualitative T cell-related signature

Rheumatoid arthritis (RA) is a systemic autoimmune disease with persistent synovitis and joint destruction, leading to a huge economic and physical burden on patients. The detection of RA is important for the individual’s guiding therapeutic. However, current signatures lacked enough effects for the diagnosis of RA. Here, a pariwise signature, including genes ICAM2 and OSTF1, was derived based on a rank-based method, which was called ICAM2-OSTF1 signature (IOS). The sensitivity and specificity of IOS in the training dataset were 87.39% and 86.79%, respectively. The accuracy of IOS was 91.07% in the validation dataset that contained a total of 280 samples from two independent datasets. Besides, when using eight methods, such as ssGSEA, xCell and TIMER, to quantitate the immune infiltration characteristics in RA. We found that RA presented elevated pro-inflammation immune infiltration and immune score. In addition, transcriptome analysis demonstrated that the consistent transcriptional differences between RA and healthy control were significantly enriched in some pathways typically related to the immune microenvironments, such as T cell activation. Finally, network analysis demonstrated that ICAM2, CXCL16, CKLF and SLPI may be related to the occurrence of RA. In brief, IOS can individually distinguish RA from healthy controls measured by different laboratories, and be an auxiliary test for diagnosing RA.

Enhancing reproducibility in stable isotope analysis (SIA) of fish eye lenses: A comparison between lamina number and diameter

Analyzing stable isotopes in archival tissues, such as fish eye lenses, is used to document shifts in feeding ecology, diet, habitat use, and to reconstruct life history. Fish eye lenses grow throughout their ontogeny, forming multiple sequential layers, or laminae. These laminae represent the chronology of the fish’s life, much like tree rings, which record environmental conditions over time. Lenses are protein-rich, which makes them an ideal structure for analyzing light isotopes such as δ¹³C, δ¹⁵N, and δ34S. These light isotopes are primarily integrated into the lens tissue through the fish’s diet, where they are bound to amino acid structures during protein synthesis. As research begins to emerge using eye lenses to reconstruct the life histories of fishes, the need for a reproducible method of delamination grows. For this study, each researcher independently delaminated one lens from each of the 10 adult Chinook Salmon (Oncorhynchus tshawytscha). Lens lamina number, diameter (mm), and mass (mg) of each lamina were recorded. Laminae were then submitted for stable isotope analysis of both δ¹³C and δ¹⁵N. Isotope values were used as a validation to compare delamination patterns between researchers. δ¹³C and δ¹⁵N values from the lenses were then plotted using both the assigned lamina number and lens diameter to compare the difference between researchers. Analysis based on lamina number showed significant shifts in isotope values and variability in lamina counts between researchers. However, when lens diameter was used instead of lamina number, isotope patterns throughout the lenses of the same fish were nearly identical. Using lens diameter removes subjectivity between researchers, thereby increasing the reproducibility of the technique and providing a more robust interpretation of the data.

Genetically modified organisms and sustainable development goals: A survey of Taiwanese public opinion

This study investigates public opinion of genetically modified organisms (GMOs), the role of GMOs in achieving the Sustainable Development Goals (SDGs), and economic preferences in Taiwan. A survey of 977 Taiwanese adults assessed their knowledge, attitudes, and willingness to pay (WTP) for non-GMO and organic products. The results show that while awareness of GMOs is high, there is a significant gap in understanding, as many respondents struggled with basic genetic concepts. Public attitudes are generally neutral, with moderate concerns about health and environmental risks. Notably, males and those with a science background exhibit more favorable attitudes towards GMO. The WTP analysis reveals a stronger preference for paying premiums on organic products over non-GMO items, indicating a higher perceived value of organic agriculture. Public perception of GMOs’ contributions to SDGs is largely positive, particularly for enhancing food security (SDG 2) and alleviating poverty (SDG 1), though concerns remain regarding environmental sustainability (SDGs 14 and 15). These findings underscore the need for targeted educational initiatives and effective communication strategies to close knowledge gaps and build public trust in GMO regulation, which are essential for informed public discourse and maximizing GMOs’ potential in sustainable development.

Adaptive DDoS detection mode in software-defined SIP-VoIP using transfer learning with boosted meta-learner

The Internet has continued to provision its infrastructure as a platform for competitive marketing, enhanced productivity, and monetization efficacy. However, it has become a means for adversaries to exploit unsuspecting users and, in turn, compromise network resources. The utilization of filters, gateways, firewalls, and intrusion detection systems has only minimized the effects of adversaries. Thus, with the constant evolution of exploitation and penetrative techniques in network security, security experts are required to also evolve their mitigation and defensive measures by using advanced tools such as machine learning approach(es) poised to help detect and stop as close to its source, any attack or threat. This will help to quickly identify malicious packets and prevent resource exploits and service disruption. To curb these, studies have sought to minimize the effects of these attacks via advanced machine learning (ML) inspired tools. Traditional ML performance is often degraded due to: (a) its simplistic design that is unsuitable to handle categorical datasets effectively, and (b) its adoption of hill-climbing mode that yields solution(s) that are stuck at local maxima. To avoid such pitfalls, we use deep learning (DL) schemes based on recurrent networks. They present the demerits of the vanishing gradient problem and require longer training time. To curb the challenges of ML and DL, we propose a transfer learning scheme with 3-base (BiGRU, BiLSTM, and Random Forest) classifiers and XGBoost meta-learner to aid effective identification of DDoS. The ensemble yields Accuracy and F1 of 1.000 to effectively classify 314,102-DDoS-cases during its evaluation. The proposed ensemble demonstrates that it can efficiently identify malicious packets for DDoS attacks in network transactions.

Measurement properties of health-related quality of life instruments for people living with scoliosis in China: A systematic review

Purpose Scoliosis is a three-dimensional structural deformity of the spine that leads to restricted spinal motion, weakness in the paraspinal muscles, reduced cardiopulmonary function, and chronic physical and psychological pain. It also impacts patients’ quality of life. According to statistics, as of 2022, the number of Chinese primary and secondary school students with scoliosis has exceeded 5 million, and continues to grow at an annual rate of approximately 300,000 new cases, while the incidence of scoliosis in adults is even higher. Therefore, it is crucial to evaluate health-related quality of life (HR-QoL) in this population. This systematic review examined the frequency of use of HR-QoL outcome measurement instruments among patients with scoliosis in China and synthesized evidence on their measurement properties. Methods Stage 1: We searched databases including MEDLINE, EMBASE, Scopus, PubMed, and the Web of Science from inception to December 2023 to identify studies that examined HR-QoL among patients with scoliosis in China. A list of patient reported outcome measures used in clinical HR-QOL measurement for this population was derived from the selected studies. Stage 2: Reporting followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and AMSTAR (Assessing the methodological quality of systematic reviews) Guidelines. First, we used the COSMIN checklist to assess the methodological quality of studies that reported the measurement properties of the patient reported outcome measures used. Second, the COSMIN tool was used to assess the measurement properties of these instruments, and ratings (excellent, good, fair, or poor) were assigned for each measurement property. Finally, the best evidence was synthesized. Results In total, 155 studies were included, and 47 instruments were identified. The top five frequently used HR-QoL instruments for patients with scoliosis in China were the C-SRS-22, ODI, VAS, SF-36, and TC-SRS-22r. The measurement properties assessed included internal consistency (12 instruments), reliability (13 instruments), construct validity (9 instruments), ceiling and floor effects (8 instruments), and responsiveness (3 instruments). The C-ISYQOL had the best methodological quality. No studies assessing measurement properties of instruments for adults with scoliosis were found. Conclusions Based on limited research evidence, the C-ISYQOL currently demonstrates the best measurement performance among HR-QoL assessment instruments for Chinese scoliosis patients. However, due to potential publication bias resulting from the restriction of literature searches to published works (excluding grey literature), as well as minor impacts that strict adherence to COSMIN guidelines may still exert on measurement evaluations due to their inherent limitations, the number of studies supporting the favorable measurement properties of the C-ISYQOL remains insufficient. Therefore, it cannot currently be recommended as the preferred instrument for clinical measurement. Although the C-SRS-22 is widely used and has good reliability and validity for HR-QoL assessment in adolescent patients with scoliosis, its measurement properties have not been adequately evaluated in adult populations, and it is not currently supported for use in HR-QoL assessment of adults with scoliosis. Further studies assessing the measurement properties of these instruments are urgently needed.

A novel dual-branch network for comprehensive spatiotemporal information integration for EEG-based epileptic seizure detection

Epilepsy is a neurological disorder characterized by recurrent seizures caused by abnormal brain activity, which can severely affects people’s normal lives. To improve the lives of these patients, it is necessary to develop accurate methods to predict seizures. Electroencephalography (EEG), as a non-invasive and real-time technique, is crucial for the early diagnosis of epileptic seizures by monitoring abnormal brain activity associated with seizures. Deep learning EEG-based detection methods have made significant progress, but still face challenges such as the underutilization of spatial relationships, inter-individual physiological variability, and sequence intricacies. To tackle these challenges, we introduce the Dual-Branch Deepwalk-Transformer Spatiotemporal Fusion Network (Deepwalk-TS), which effectively integrates spatiotemporal information from EEG signals to enable accurate and reliable epilepsy diagnosis. Specifically, the Spatio-branch introduces an adaptive multi-channel deepwalk-based graph framework for capturing intricate relationships within EEG channels. Furthermore, we develop a Guided-CNN Transformer branch to optimize the utilization of temporal sequence features. The novel dual-branch networks co-optimize features and achieve mutual gains through fusion strategies. The results of extensive experiments demonstrate that our method achieves the state-of-the-art performance in multiple datasets, such as achieving 99.54% accuracy, 99.07% sensitivity and 98.87% specificity. This shows that the Deepwalk-TS model achieved accurate epilepsy detection while analyzing the spatiotemporal relationship between EEG and seizures. The method further offers an optimized solution for addressing health issues related to seizure diagnosis.

Whole genome sequencing revealed esophageal squamous cell carcinoma related biomarkers

Esophageal squamous cell carcinoma (ESCC) is among the most frequently diagnosed cancer types, and affected patients frequently experience poor prognostic outcomes and high mortality rates. Many genomic studies of ESCC have been performed in recent years, yet the mutational mechanisms driving ESCC and their clinical implications remain incompletely understood. In this study, paired tumor and normal tissue samples from 22 patients with ESCC were used for whole genome sequencing-based analyses of genome-wide mutational events. These comprehensive analyses enabled the detection and characterization of various mutation subtypes in ESCC including somatic single-nucleotide variants, small insertions and deletions, copy number variations, structural variations, and circular extrachromosomal DNA. Of identified genes harboring non-silent mutations, TP53, NOTCH1, CSMD3, EP300, and FAM135B were the most frequently mutated genes in this study and they were annotated in the COSMIC Cancer Gene Census. With the exception of aging-related signatures, an APOBEC-associated mutational signature was the dominant mutational feature detected in ESCC samples, suggesting that APOBEC-mediated cytidine deamination is likely a major driver of mutations in this cancer type. Notably, our study also detected circular extrachromosomal DNA (ecDNA) events in these ESCC patient samples. The oncogenes COX6C, PVT1, and MMP12 as well as the oncogenic long non-coding RNA AZIN1-AS1 which were detected in ecDNA regions in these analyses may be associated with worse disease-free survival in ESCC patients.

Pneumococcal colonization dynamics among young children with and without respiratory symptoms during the first year of the SARS-CoV-2 pandemic

Background Non-pharmaceutical interventions to mitigate the spread of SARS-CoV-2 were implemented across the United States in 2020. These public health measures might influence pneumococcal colonization in younger children and their subsequent risk of invasive pneumococcal disease. Our objective was to evaluate pneumococcal colonization rates in children ≤ 5 years of age with and without respiratory symptoms during the first 12 months of SARS-CoV-2 pandemic (April 2020 – March 2021). Study design This is a retrospective cross-sectional study evaluating pneumococcal colonization rates, density and serotype distribution across three study periods (April-July [Period 1], August-November [Period 2] and December-March [Period 3]) after implementation of non-pharmaceutical interventions in Kansas City, Missouri. Children aged ≤5 years with and without respiratory symptoms seeking care at Children’s Mercy Kansas City hospital system with a residual standard of care nasal mid-turbinate sample were included. The odds of pneumococcal colonization across study periods were calculated using multivariable logistic regression. Results A total of 311 children met inclusion criteria (126 symptomatic and 185 asymptomatic). The overall pneumococcal colonization (23% vs. 13%, p = 0.03) and SARS-CoV-2 positivity (34.1% vs. 17.8%, p = 0.001) rates were higher in symptomatic children than in asymptomatic children. The odds of pneumococcal colonization of symptomatic (Period 2: OR 1.09; 95% CI 0.33–3.64, and Period 3: OR 0.46; 95% CI 0.13–1.59) and asymptomatic (Period 2: OR 0.55; 95% CI 0.18–1.7, and Period 3: OR 0.37; 95% CI 0.11–1.2) children did not statistically differ across study periods. Pneumococcal colonization density was also not different across study periods among study groups. Overall, non-PCV15, non-PCV20 serotypes were the most frequently identified serotypes (56.8%). Conclusions Pneumococcal colonization rates and density did not significantly change across study periods as adherence to non-pharmaceutical interventions gradually relaxed during the first year of the SARS-CoV-2 pandemic.

The pivot penalty in research

Breaking the deadlock: A study on the pathway and effects of reshaping the sustainable marketing capability of Chinese time-honored brands

Numerous Chinese Time-Honored Brands are facing decline due to their limited ability to adapt to rapidly changing environments. This study identifies the core barrier as a lack of focus on developing Sustainable Marketing Capability (SMC) within the firms that own these brands. While prior research has examined the link between general marketing capabilities and corporate performance, limited attention has been paid to SMC and its effects. To address this gap, we investigated both the antecedents and outcomes of SMC. Drawing on survey data from managers and selected employees at 47 heritage enterprises in Southwest China, all of which own China Time-Honored Brands, our findings reveal that ambidextrous marketing—comprising proactive marketing exploration and exploitation—significantly enhances SMC. In turn, SMC positively impacts corporate performance and mediates the relationship between ambidextrous marketing and performance by strengthening firms’ responsiveness to market and policy conditions. This study provides actionable strategies for heritage enterprises seeking to build sustainable marketing capabilities and offers practical insights into maintaining competitiveness and achieving long-term success.

Feasibility of a combined online and in-person training model on Infant and Young Child Feeding (IYCF) counselling for village health workers in rural Qinghai, China

Background Counselling is an effective behavior change intervention for improving infant and young child feeding (IYCF). The Maternal and Health Department of National Health Commission China and United Nations Children’s Fund (UNICEF) China Office jointly developed a combined online and in-person IYCF counselling training course for primary health workers in rural China. This study aims to test feasibility of the combined training model in rural China. Methods The study was conducted between September 2021 and February 2022 in five counties in Qinghai Province, China. We implemented a “2+1” training model for village health workers in the five counties. This model consisted of a 2-day online training session followed by a 1-day in-person training session. After completing the training, each village health workers were requested to provide 12 IYCF counselling services to caregivers of children aged 6–23 months in their villages. We assessed the IYCF knowledge score of village health workers before and after online training, and collected satisfaction level of village health workers and caregivers by using a scale of 1–5. Values ≥4 were considered a high degree of satisfaction. Furthermore, we presented the per-person cost of the “2+1” training model. Results There were a total of 861 village health workers in the five counties, with 802 (93.1%) completed the 2-day online training course and 838 (97.3%) completed the 1-day in-person training course. The mean score of village health workers on IYCF knowledge significantly improved after 2-day online training (72.14 ± 17.84 before training vs. 82.00 ± 17.87 after training, P < 0.001), and their average satisfaction scores on the training were more than 4.5 for all items. Furthermore, more than 95% surveyed caregivers expressed satisfaction with the counselling services provided by village health workers, and around 80% caregivers reported that the counselling solved their feeding problems. The cost of “2+1” training model was ¥238.72 (US$33.38) per person. Conclusions This study showed that the combined online and in-person IYCF counselling training is acceptable and feasible with lower cost in rural of Qinghai, which can be scaled up in other rural areas in China.

Lactoferrin combined with Coenzyme Q10 ameliorate sarcopenia in an aging mouse model induced by D-galactose

Sarcopenia is an age-related condition with a slow and prolonged decrease in muscular mass, strength, and function. As the population ages, the frequency of sarcopenia rises, and aggressive prevention methods and effective treatment options are in urgent need. Here, we explore the hypothesis that nutritional interventions can ameliorate skeletal muscle aging in mice affected by sarcopenia, and the aforementioned hypothesis was validated through histopathological characterization and behavioral experiments. The model group exhibited reduced muscle mass (Lean Mass, GAS Index), muscular strength (Maximum Limb Muscle Strength), and muscular function (Exhaustion Time, Inverted Grid Time), along with increased fat content and smaller myofiber size compared to the control group. Treatments with lactoferrin and CoQ10, both individually and in combination, enhanced muscle indices and facilitated muscle tissue regeneration, with the combined treatment showing the most significant improvement. Research further shows that Lactoferrin and CoQ10, whether administered alone or in combination, were discovered to restrain the progression of sarcopenia by inhibiting both protein metabolism and mitochondrial energy metabolism, and compared to groups treated with lactoferrin or CoQ10 alone, the combined treatment demonstrated varying degrees of improvement across all evaluated metrics, such as Lean Mass (2.273 ~ 5.365%), Fat Mass (−1.058 ~ −0.359%), GAS index (0.259 ~ 0.335%), Maximum Limb Muscle Strength (6.83 ~ 53.498 g), Inverted Grid Time (563 ~ 859 s), Exhaustion Time (386 ~ 468 s).

Method for assessing rodent infestation in plateau based on SegFormer

Rodent infestation is a critical factor contributing to grassland degradation, which significantly negatively affects grassland ecosystems. To assess rodent infestation on the plateau, there is an urgent need for a scientifically sound and effective method to detect the distribution of rodent burrows. In response, this study proposes a semantic segmentation approach utilizing the SegFormer model to detect rodent infestation in highland areas. First, we used an unmanned aerial vehicle to collect video data from the plateau and constructed a rodent burrows dataset after processing and precise labeling. Second, to address the issue of SegFormer’s suboptimal performance in segmenting small targets within complex backgrounds and among similar objects, we implemented targeted modifications to enhance its effectiveness for this task. Incorporating the efficient multi-scale attention (EMA) mechanism into SegFormer’s encoder improves the model’s capacity to capture global contextual information. Meanwhile, integrating the multi-kernel convolution feed-forward network (MCFN) into the decoder optimizes the problem of detail recovery and fusion of multi-scale features. We name this method EM-SegFormer (Efficient Multi-scale SegFormer). The experimental results demonstrate that the method achieves relatively good performance on the rodent burrows dataset. This study introduces a novel approach for plateau rodent infestation detection and offers reliable technical support for grassland restoration and management.

Energy-based jamming pattern open set recognition via spiking wavelet transformer

Jamming pattern recognition (JPR) is critical in modern communication systems, including civil, and industrial applications, where complex and unpredictable jamming patterns (JPs) frequently disrupt normal operations. Accurately identifying known JPs while detecting unknown JPs is essential for maintaining robust communication. This paper tackles the jamming pattern open set recognition (JP-OSR) challenge by proposing a novel framework that integrates three key components: Spiking Wavelet Transformer (SWT), Hyperspherical Maximum Class Separation (MCS), and an energy-based model with an adaptive threshold. The framework begins by extracting high-resolution time-frequency features through the SWT, effectively capturing the intricate temporal and spectral patterns of jamming signals. These features are then aligned in a hyperspherical space using MCS to maximize class separation and improve inter-class distinctions. To address the variability in feature distributions across different Jamming-to-Signal Ratios (JSR) and JPs, the proposed energy-based model dynamically adjusts the threshold, enabling accurate recognition of both known and unknown jamming types. Simulation experiments have validated the effectiveness and superiority of the proposed method for JP-OSR.

Level and determinants of pentavalent vaccine dropout during infancy: A hierarchical analysis of community-level longitudinal study

Background An estimated 23 million children under the age of one do not get the recommended basic vaccinations globally, and Ethiopia is one of the 10 countries where almost 60% of these children live. The alarming decline in childhood vaccination is leaving millions of children at risk of devastating but preventable diseases. Vaccination dropout poses a significant challenge in ensuring that children receive the full protection provided by vaccines. In Ethiopia, individual vaccine coverage has improved, but the proportion of fully vaccinated children with all recommended vaccines remains low. The study aimed to examine the level and determinants of pentavalent vaccine dropouts during infancy. Methods The study utilized data from the PMA Ethiopia panel survey, which was conducted in three regions: Amhara, Oromia, and the former SNNP. A multi-stage cluster design with urban-rural stratification was used to draw a probability sample of households and women of reproductive age. We employed a multilevel logistic regression analysis in light of the hierarchically clustered nature of PMA data and the results are reported in odds ratio. The measures of variation were explained by intra-cluster correlation, median odds ratio, and proportional change in variance. Results A total of 1295 infants were included in the final analysis. The result shows that a dropout from the first to the third dose of pentavalent was 37.48%. Pentavalent dropout rates were about two times (AOR = 1.84, 95% CI: 1.24–2.72) higher for infants born at home than for babies born at a health facility, and two times (AOR = 1.77, 95% CI: 1.04 2.99) higher for infants born to mothers who perceived the community did not support postnatal care than for babies born to mothers who believed the community supported it. Infants whose mothers had trouble accessing PNC following the COVID-19 pandemic were dropped out of Pentavalent five times higher (AOR = 5.06, 95% CI: 1.32–19.48). Pentavalent dropout is more than three times (AOR = 3.78, 95% CI: 1.75–8.16) higher among those who lived in the former SNNP region and more than two times (AOR = 2.75, 95% CI: 1.17–6.43) higher among infants born to mothers who lived in a community with a high level of poverty. Conclusion and recommendation The dropout rate from the first to the third pentavalent vaccine is higher than what has been reported in other studies in Ethiopia and abroad. Residing in a high-poverty community, giving birth at home, perceiving that the community did not support postnatal care, and having trouble accessing PNC following COVID 19 significantly determined pentavalent dropout. Improving health education, healthcare access, institutional delivery, and the health systems linkage are therefore essential to addressing these problems in the targeted population.