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Formulation of a spatiotemporal model for the analysis of neonatal mortality amidst SDG interventions: The case of Uganda
This study aimed to formulate a dynamic linear model within a Bayesian framework to conduct a spatiotemporal analysis of neonatal mortality in Uganda during SDG interventions. This study formulated a model based on appropriate health-related covariates while considering the spatial and temporal dimensions of the data whose variable of interest (dependent variable) was a quantitative variable measuring the monthly rates of neonatal mortality (number of newborns dying within their first 28 days of life) at the district level. Through Markov chain Monte Carlo (MCMC) simulations, the applicability of the model could be assessed using simulated data covering 14 years, starting in January 2010, to evaluate the situation before and after the implementation of interventions to achieve the SDGs targets. Using a Bayesian approach through the Kalman filtering technique, the parameters of the formulated model were estimated. This study used the same technique through Gibbs sampling to extract meaningful information from the simulated data and provide reliable forecasts for the rates of neonatal mortality.
Optimization and comparison research on adaptive modularization BERT-SPAN model for named entity recognition of SARS-CoV-2 virus proteins
Epsilon-near-zero time-gate for high-fidelity spatial information transfer through dynamic scattering media
The role of computer technology in motion tracking method of basketball shot
With the rapid development of modern science and technology, with the gradual maturity of computer-aided training system, it has also been applied in sports training, and has achieved good results. The application of new technology can not only clearly see the mastery of sports technical skills and the training level of athletes, but also provide a more systematic basis for the next training plan of trainer system, and provide a set of scientific and reliable guidance for the development of athletes ’ sports potential. However, in complex scenes, there are some problems, such as occlusion object interference, which affect the tracking accuracy of target action. To address this problem, a basketball shooting action tracking method for complex scenes is proposed. The method first integrates the imaging system into a trackable invariant feature-fusion framework, allowing motion information in complex environments to be extracted more reliably. Through the visual measurement system, the motion of the target in the scene is detected, and the spatial node corresponding to the detected action is treated as the initial tracking point. An ant colony algorithm is then employed to construct an ant-colony tracking model, enabling robust tracking of the basketball shot-release motion under complex scene conditions. Simulation results demonstrate that the proposed method achieves strong tracking performance, with high accuracy, reduced tracking deviation, and improved preservation of motion details.
Entropy-regularized dual-stream attention fusion for multi-disease lung classification
Abstract Accurate and reliable classification of lung diseases from medical imaging remains challenging due to overlapping radiological patterns, disease heterogeneity, and variations in image quality. To address these challenges, this paper proposes an Adaptive Dual-Stream Attention Fusion (ADSAF) framework for automated lung disease classification. The proposed model integrates convolutional neural networks and vision transformers to jointly capture fine-grained local textures and long-range global contextual dependencies. An adaptive attention fusion mechanism dynamically learns image-specific weighting between the two feature streams, overcoming the limitations of static fusion strategies. In addition, a Self-Attention Refinement Module enhances disease-relevant regions while suppressing background noise, improving both discriminative capability and interpretability. ADSAF is designed as a general multi-class lung disease classification framework and is validated in this study through task-specific evaluations on pneumonia and COVID-19 datasets, demonstrating strong accuracy, robustness, and generalization. Experimental results demonstrate consistent performance gains over state-of-the-art CNN, transformer, and ensemble models in terms of accuracy, F-score, sensitivity, and robustness under noisy conditions and domain shifts, achieving up to 98.3% accuracy. Grad-CAM visualizations further confirm the model’s focus on clinically meaningful lung regions, highlighting its potential for reliable clinical decision support.
Plasmonic Dirac-vortex lasers via three-dimensional photonic mass vortices engineering
Correction: Highly efficient production of transgenic rats with long DNA insertions using piggyBac transposase mRNA and piezo-assisted microinjection
Difficult biliary cannulation among patients with compensated liver cirrhosis: predictors and impact on complications
Abstract This study investigated prospectively how frequent is difficult biliary cannulation (DBC) among patients with compensated liver cirrhosis and how it will impact the ERCP related complications. Over a period of 2-years, patients with compensated liver cirrhosis undergoing their first time ERCP with naive papilla were evaluated by history, clinical examination, investigations, imaging and ERCP and followed up for any adverse events. Out of 131 compensated cirrhotic patients; 127 were successfully cannulated and included in the final analysis and divided into easy ( n = 72) and difficult ( n = 55) cannulation groups. The mean age of the studied cases was 51.86 ± 11.98 years (19–78) with male predominance (51.2% versus 48.8%). The most frequent indication for ERCP was calcular obstructive jaundice. DBC was reported among 45.5% of cases. DBC was associated with 12.6% complication rate of them 8.7% had pancreatitis and 3.9% had intraoperative minor bleeding. Older age, type 2 and 3 papillae, duodenal diverticulum and precut sphincterotomy were predictors of DBC. DBC is not uncommon among compensated cirrhotic patients experiencing their first time ERCP. Because DBC is associated with ERCP complications, its predictors should be considered especially the type of papilla, the presence of duodenal diverticulum and assisted cannulation techniques.
Dual-axis myelination covariance drives the functional connectivity emergence during infancy
Enhancing second harmonic generation-mediated photodynamic therapy via external electric field modulation
Photodynamic therapy (PDT) utilizes light-activated photosensitizers (PS) to produce reactive oxygen species (ROS) for targeted bacterial destruction; however, its efficacy is often limited by inadequate light penetration, necessitating novel enhancements, such as the integration of second harmonic generation (SHG) through harmonic nanoparticles (HNPs) that convert two photons into one of higher frequency, thereby advancing the approach of SHG-based PDT for improved bacterial eradication. Our novel technique explores the impact of an e (EEF) on SHG intensity to augment PDT efficacy against Staphylococcus aureus ( S. aureus ). We investigated a novel conjugate, Bismuth Ferrite (BFO) in conjunction with protoporphyrin IX (PPIX), and compared it to the Barium Titanate (BT)-PPIX conjugate, under EEF of 0 V, 10 V, and 20 V for a duration of 5 minutes. The experiments utilized a near-infrared (NIR) femtosecond pulsed laser at 798 nm for excitation. Our findings show that EEF significantly enhances SHG intensity, improving photodynamic activity. Notably, BFO-PPIX conjugates significantly decreased bacterial survival to 35.8 ± 3.0% under EEF exposure, in contrast to 48.1 ± 3.2% without EEF. Similarly, to further substantiate the impact of EEF on SHG-based PDT efficacy, BT-PPIX conjugates resulted in bacterial survival of 57.1 ± 1.0% with EEF exposure, in contrast to 78.4 ± 3.7% without EEF. Our findings confirm the first study of EEF-modulated SHG in PDT, demonstrating its capacity to augment SHG intensity in HNPs-PPIX conjugates and improve therapeutic efficacy. These results highlight the potential of SHG-enhanced PDT, particularly with optimized EEF.
Sex-biased plasma inflammatory protein profile in obesity
Abstract Obesity-associated inflammation predisposes to cardiovascular disease (CVD). We investigated the association of biological sex with the plasma inflammatory protein profile in individuals with obesity. Clinical and proteomic data from 450 women and men with a body mass index (BMI) > 27 kg/m² without known CVD participating in the FAT associated CardiOvasculaR dysfunction study were analysed. The Olink Target 96 inflammation panel was employed in biobank samples. Hypertension was more prevalent among men, while age, BMI, and prevalences of obesity, diabetes and smoking did not differ between the sexes (all p > 0.05). In multivariable analyses, obesity was associated with downregulation of interleukin (IL) 7, IL 12 subunit beta, IL 6, and C-X-C motif chemokine 11, and upregulation of sulfotransferase 1A1 and SIR2-like protein 2 in women (all p < 0.05). In men, obesity was associated with downregulation of monocyte chemotactic protein 3, tumour necrosis factor superfamily member 12, IL 10 and protein S100-A12, and upregulation of neurotrophin-3 (all p < 0.05). In sum, the targeted protein profile in obesity differed by biological sex and there was no overlap in the differentially regulated proteins between women and men with obesity. The results suggest that pathophysiological mechanisms in obesity-associated inflammation and immune dysregulation may be sex-biased.
IVNS1ABP mutation drives cellular senescence in newly identified progeroid neuropathy
Robust 3D Pose estimation and Parkinson’s Disease classification via Dual-Stage Adaptive Temporal Perception and graph topology modeling network
This paper proposes a unified skeleton-based framework for 3D human pose estimation and Parkinson’s disease classification, integrating a Dual-Stage Adaptive Temporal Perception (DATP) strategy and an Adaptive Graph Topology Modeling Network (AGTM-Net). DATP enhances robustness to joint occlusion and sequence degradation through occlusion-aware interpolation, trend-extrapolated frame padding, and multi-scale spatiotemporal modeling. On the MPI-INF-3DHP dataset with 16 missing joints, DATP achieves 77.72 PCK and 43.57 AUC, outperforming state-of-the-art methods. On Human3.6M, DATP also shows strong generalization with MPJPE reduced to 32.68 mm. For clinical classification, AGTM-Net dynamically models skeletal structure variations and achieves an F1-score of 0.898 and accuracy of 0.881 in distinguishing healthy individuals from Parkinson’s patients with a score of 0 based on the “3.9 Arising from Chair” task. Interpretability analyses—based on gradient and perturbation methods—highlight the spine, chest, and hips as decisive joints, aligning with clinical understanding of gait disorders and enhancing the model’s transparency and clinical reliability.
How the Pokémon franchise has helped to shape neuroscience
Pivoting colloidal assemblies exhibit mechanical metamaterial behaviour
A new isolated fungus Talaromyces sp. MC-F2 efficiently solubilizes phosphate through media-dependent metabolic regulation
Photoresist-guided indirect photopatterning of quantum dots via carbene-mediated ligand thermocrosslinking
Mediating factors in the relationship between combat-related traumatic injury and myocardial blood flow reserve: The ADVANCE cohort study
Introduction Combat-related traumatic injury (CRTI) has been linked to reduced myocardial blood-flow- reserve (MBFR), measured using the subendocardial viability ratio (SEVR). We aimed to assess the mediating role of known cardiovascular risk factors on SEVR. Materials and Methods We examined 1018 UK servicemen (prospective ADVANCE Cohort Study) comprising 504 with CRTI (140 amputees) and 514 uninjured men, frequency-matched at sampling, by age, rank and deployment (Afghanistan 2003–2014). We examined the mediating role of cardiovascular risk factors, shown to significantly greater with CRTI at study baseline (~8 years post-injury/deployment), on SEVR, measured three-years later (FU1). The cardiovascular risk measures were heart-rate variability (HRV, root-mean-square-of-successive-differences [RMSSD]), visceral-fat-mass (VFM, using DEXA), venous-blood high-sensitivity C-reactive protein (Hs-CRP, inflammation), six-minute walk distance (6MWD, physical function) and weekly leisure-time moderate-to-vigorous physical activity (LT-MVPA, physical activity). Results At baseline, VFM was significantly greater and RMSSD, 6MWD and LT-MVPA lower with CRTI compared to the uninjured. VFM and Hs-CRP were significantly greater and RMSSD, 6MWD and LT-MVPA lower in the injured amputees versus the injured non-amputees and uninjured. The SEVR at FU1 was significantly lower in the injured (mean ± standard deviation; 187.2 ± 39.7) compared to the uninjured (194.1 ± 31.5) and lowest in the amputee sub-group (181.9 ± 30.0). The association between CRTI and SEVR was mediated by VFM (natural indirect effect −1.80: 95%CI: −2.90, −0.67), RMSSD (−1.82: −3.45, −0.19) and 6MWD (−1.79: −3.16, −0.41) but not Hs-CRP and LT-MVPA. The association between traumatic amputation and SEVR was mediated by VFM, HRV and LT-MVPA. Conclusions VFM, HRV and physical function/activity were significant mediators of the link between CRTI and SEVR. Interventions on physical activity/function could mitigate the association between CRTI and SEVR. Data from longer-term follow up are required to robustly determine the temporal effects of this relationship.