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Patient preoperative positioning for THA affects postoperative acetabular cup angle and leg length discrepancy: a prospective case series

Myasthenia gravis and autoimmune overlap: Prognostic insight

Background Autoimmune diseases (ADs) frequently coexist with myasthenia gravis (MG), suggesting shared genetic and immunological mechanisms. However, the impact of comorbid ADs on MG prognosis remains unclear. This study aimed to investigate the prevalence, clinical characteristics, and prognosis of MG patients with comorbid ADs in a Turkish cohort. Methods We retrospectively analyzed 302 MG patients treated at a tertiary center between 2010 and 2024. Patients were grouped based on the presence of comorbid ADs. Clinical characteristics, disease severity, treatment response, and prognosis were compared. Results Among 302 MG patients, 41 (13.6%) had at least one comorbid AD, with autoimmune thyroid disease (AITD) being the most common (10.6%). ADs were more frequent in females. Patients with and without comorbid ADs showed no significant differences in MG severity, thymectomy rates, myasthenic exacerbations, or overall outcomes (p > 0.05). However, female patients with ADs experienced more frequent myasthenic exacerbations and had a higher rate of rituximab use (p < 0.05). Conclusions Comorbid ADs do not significantly impact MG severity or prognosis. Female MG patients with ADs have a higher frequency of myasthenic exacerbations and rituximab use, warranting further research. Early identification of ADs remains essential for optimal patient management.

Author Correction: Mechanism of BRCA1–BARD1 function in DNA end resection and DNA protection

Rapamycin alleviates hypothalamic injury in exertional heat stroke rats by activating mitophagy through the mTOR/Pink1/Parkin pathway

Alignment of PrEP adherence and HIV exposure risk among pregnant and postpartum women in Lilongwe, Malawi

Objective When measured continuously, adherence to HIV pre-exposure prophylaxis (PrEP) is consistently low in studies of pregnant and postpartum women. We investigated how PrEP adherence aligned with HIV exposure risk. Methods We conducted a trial of a PrEP adherence support intervention in Lilongwe, Malawi. Pregnant women who met eligibility criteria for PrEP had visits at three and six months following enrollment. At each visit, HIV exposure risk was categorized as low or moderate/high (i.e., higher) risk based on an algorithm. PrEP adherence was measured via tenofovir concentrations, with functional adherence defined at levels consistent with ≥4 doses/week. HIV exposure risk and PrEP adherence were classified as either aligned (i.e., higher HIV risk/PrEP adherence, low HIV risk/PrEP non-adherence) or not aligned (i.e., higher HIV risk/PrEP non-adherence, low HIV risk/PrEP adherence). Probability differences (PD) were used to estimate the effect of the PrEP adherence intervention on aligned PrEP adherence. Results 164 women were included in the analysis. HIV exposure risk was higher for 81 participants (49%) at three months and 89 (54%) at six months. PrEP adherence was low at three months (34%) and at six months (29%). Aligned PrEP adherence was observed in 89 (54%) participants at three months and 83 (51%) at six months. 62% at higher HIV exposure risk were not aligned at month three, which increased to 68% at month six. The probability of aligned PrEP adherence was greater among those randomized to the intervention than those receiving standard of care at three months (PD:15.7%; 95%CI:0.8%, 30.6%). This was also evident in analyses that considered women with high HIV risk but low adherence. Conclusion Alignment of PrEP adherence with HIV exposure risk was dynamic. PrEP adherence should be considered in the context of evolving HIV exposure risk during pregnancy and postpartum, with greater emphasis on periods of elevated HIV risk exposure.

Association of intermediate monocytes with dengue severity among the pediatric population of Odisha, India

Sliding mode dynamics of a non-smooth Filippov predator-prey system for integrated pest management

In recent years, the problem of pests seriously affects the yield and quality of crop, posing a major challenge to the safe production of crop, which have seriously hindered the development of China’s agriculture. How to quickly and accurately monitor pests, timely grasp the occurrence dynamics of pests, and prevent and control pests is of great significance for reducing crop yield losses. Considering the discontinuity of spraying pesticides and releasing natural enemies in the process of pest control, and the Filippov system’s ability to accurately depict switching states and human intervention measures, a non-smooth Filippov predator-prey system with threshold strategies is investigated incorporating several different functional responses, such as Holling II functional response and ratio functional response etc, which should be selectively applied dependent on the population of the prey. The aim of this study is to investigate the complex dynamics including bistabilities of the ecosystem when the relative populations of the prey and predator is substantially different, by modelling the non-smooth Filippov system with multiple switchable functional responses for the very first time, which is believed to be more realistic for modeling the dynamics of real ecosystem, thus the solution of the present work may be more suitable for real world applications such as for the integrated pest management. The validity of the proposed system is assessed by simulation, and bifurcation set of equilibria and the global stability of equilibria has been numerically obtained through an arbitrary set of parameters. Moreover, the dynamic behaviors of proposed system, such as the existence of various equilibria and their global stabilities; the existence of various domains such as the sliding domain, escaping domain and crossing domain, have been analyzed in great details in the present work. It is shown that the sliding region and escaping region cannot coexist when the density of the prey and predators is substantially different. It is further demonstrated that the real equilibrium and pseudo-equilibrium points can coexist when the population of the prey is less than that of the predator; and only the virtual equilibrium and pseudo-equilibrium can coexist in the case of when the population of the prey is more than that of the predator.In particular, it is noted that all trajectories of the prey and predators population are eventually converging into certain equilibrium points as it is demonstrated in the numerical simulation. This implies that there exists global asymptotic stability of equilibrium points under the proposed system, in which the population of preys eventually reaches a steady state of density at the real equilibrium and pseudo-equilibrium points. This work also highlights the significant role of the threshold in the process of pest controls: it is seen from this work that different types of equilibrium points can occur dependent on the choice of the economic threshold (ET). The conclusions obtained will be applied to Unmanned Aerial Vehicle (UAV) to spray pesticides and release natural enemies in a timely and quantitative manner, thereby achieving efficient and rapid monitoring and control of large-scale crop. This can more effectively ensure stable and high crop yields, provide theoretical guidance for scientific prevention and control, and is of great significance for reducing the burden on farmers, promoting agricultural development, and realizing agricultural modernization.

Artificial intelligence based sonographic differentiation between skull fractures and normal sutures in young children

Polyadic synapses introduce unique wiring architectures in T5 cells of Drosophila

Connectomes provide neuronal wiring diagrams and allow for investigating the detailed synaptic morphology of each connection. In the visual system of Drosophila , T5 cells are the primary motion-sensing neurons in the OFF-pathway and receive dendritic input from the excitatory Tm1, Tm2, Tm4, Tm9 and the inhibitory CT1 neurons. This connectivity, however, has not yet been investigated with respect to polyadic synapses known to be abundant in the fly nervous system. In this study, we use the FlyWire database and identify that Tm and CT1 cells wire on T5a dendrites via eight polyadic synapse types. We then explore the distribution of the different synapse types on T5a dendrites and find differences in their spatial patterns. Finally, we show that the polyadic morphology is setting a directional wiring architecture at the T5 network level. Our work showcases the directionality that polyadic synapses introduce in T5 connectivity.

Enhanced lymphocyte infiltration in the liver of LDL receptor and Myeloid Differentiation 1 double knockout mice on high fat diet

Abstract Myeloid differentiation 1 (MD-1; gene name: ly86 ), a glycoprotein that forms a complex with radioprotective protein 105 (RP105), is involved in the regulation of inflammation, obesity, and insulin resistance. Previous reports have shown an exacerbation of cardiac pathology in MD-1 deficient mice, including pressure overload-induced cardiac remodeling and high fat diet (HFD) -induced inflammatory atrial fibrosis. Furthermore, MD-1 expression is upregulated in atherosclerosis, as indicated by DEG database analysis, and is present in human atherosclerotic plaques. However, its involvement in atherosclerosis is unclear. In this study, we analyzed the effect of MD-1 deficiency on the development of HFD-induced atherosclerosis in littermates of low-density lipoprotein (LDL) receptor-deficient mice (LDLr −/− /MD-1 +/− and LDLr −/− /MD-1 −/− ). In contrast to RP105 deficient mice in previous reports, MD-1 deficiency did not clearly influence atherosclerosis development. However, LDLr −/− /MD-1 −/− mice exhibited significantly higher serum levels of total protein, triglycerides, cholesterol, LC/MS-detected lipophilic compounds, and an increased peripheral B-cell percentage with a Th2 antibody shift after 24 weeks of HFD. Furthermore, lymphocyte infiltration, predominantly of B2B cells and CD4 + T cells, was visible in random cross-sectional liver sections from LDLr −/− /MD-1 −/− mice. Our results indicated that MD-1 deficiency leads to further hyperlipidemia, Th2 shift, and enhances lymphocyte infiltration in the LDLr −/− liver.

Auditory discrimination improvement in young adults by a digital auditory game-based training protocol

Auditory training is a technique that has demonstrated to be beneficial, improving auditory processing response as a supplement to hearing loss management. Recently, game-based training approaches have also demonstrated to increase the effect of traditional auditory training. Hence, the general aim of this work is to develop a game-based auditory discrimination training to enhance the auditory processing response and measure performance in comparison to traditional methods. The evaluation of the methods will be in three directions: (1) user experience, (2) perceptual and behavioral responses, and (3) neurophysiological performance. For this purpose, the project will be conducted as follows: (1) to develop and validate a game-based auditory discrimination training method in line with the usability level, and (2) to evaluate the auditory training in terms of method performance, and neurophysiological responses, before and after the procedure. The game-based auditory training will be focused on basic sound features discrimination tasks, which will be applied for 15 hours with 4 different modules. This will contribute to understand experience processes that yield to a better training performance.

European bats capture migrating birds and eat them on the wing

Impact of sustainable lighting on guest psychological performance in coastal beach resorts

Abstract This research investigates the impact of sustainable lighting solutions on the psychological performance of guests in beach resorts, with a focus on the coastal region of Karnataka, India. Psychological performance is operationally defined as a combination of four measurable dimensions: mood enhancement, stress reduction, relaxation, and sleep quality, assessed using guest self-report surveys on a Likert scale. As the hospitality industry faces increasing pressure to implement sustainable practices without compromising guest comfort, this study explores whether and how lighting design contributes to guest well-being. A mixed-methods approach was adopted, combining quantitative surveys with qualitative insights. The study surveyed 100 participants across four beach resorts using structured questionnaires to examine guest preferences, satisfaction levels, and awareness of sustainable lighting practices. Findings reveal a strong guest preference for a balanced blend of natural and artificial lighting, with many recognizing the role of sustainable lighting in enhancing relaxation and reducing stress. Statistical analysis demonstrated a positive correlation between sustainable lighting features and improved guest psychological outcomes. The results offer valuable implications for resort designers and operators striving to align luxury hospitality with environmental responsibility. Integrating sustainable lighting not only enhances guest experience but also supports broader sustainability goals—ultimately promoting a more eco-conscious tourism model.

Healthcare navigation services support access to gender-affirming care: A qualitative analysis of chat conversations

Background As transgender and gender diverse (TGD) people become increasingly visible, healthcare solutions in the United States have also expanded to meet their needs. As TGD people and their families pursue gender affirming care (GAC), they also seek support to navigate complex healthcare and insurance systems. With increased demand for GAC, virtual healthcare navigation services in the U.S. have developed tailored approaches to address gaps in systems for this population. Purpose The purpose of this study was to qualitatively explore the role and influence of trained care coordinators (CCs) from a virtual navigation service in meeting commercially-insured TGD people’s GAC needs. Methods We examined and analyzed redacted chat conversations between CCs from a virtual healthcare navigation service in the U.S. and members seeking assistance. Reflexive thematic analysis of the data set involved multiple rounds of coding and reflexive analytic processes to develop themes. Findings We developed three intersecting themes: 1) Provide Dignified Experiences , 2) Promote Affirming Patient-Provider Relationships , and 3) Navigate Complex Insurance Systems . Sub-themes associated with each of the themes include: 1) Shared life experience; Exploring gender identity and GAC options in safe spaces; 2) Connections with vetted providers; 3) Access accurate information about insurance policies; Assistance with appeals process; and Obtaining letters of support. Discussion/Conclusion Navigating U.S. healthcare and insurance systems presents unique challenges for TGD people. While challenges to accessing care are well documented, our findings suggest that healthcare navigation services supported by trained CCs substantively assist TGD patients overcome obstacles. Our findings revealed multiple levels at which the service provides benefits -- individual, interpersonal, and structural. These levels of influence have clinical and policy implications for improved care for TGD people. Interventions like tailored, virtual healthcare navigation services are scalable and should be evaluated for reach and magnitude of impact beyond commercially-insured populations.

Automating wastewater characteristic parameter quantitation using neural architecture search in AutoML systems on spectral reflectance data

Abstract Wastewater (WW) analyses are required to establish optimal operation of treatment facilities, and rapid treatment assessment can greatly improve operational efficiency. WWTPs function through complex biochemical processes that exhibit high variability and are difficult to predict. This work presents the first in-depth study towards an original application of Auto Machine Learning (AutoML) models to accurately predict quality parameters of wastewater. This study aims to demonstrate the efficiency of neural network (NN) regression models built by applying the Neural Architectural Space (NAS) applying different search algorithms such as random search, grid search, Bayesian Optimization, and Hyperband search to predict the concentrations of various wastewater (WW) parameters such as biochemical oxygen demand (BOD), chemical oxygen demand (COD), ammonia (NH 3 -N), total dissolved solids (TDS), total alkalinity (TA), and total hardness (TH). The models are trained on data based on WW spectral reflectance data in the visible-near infrared range (400–2000 nm). The input variables consisted of spectral reflectance intensity of wastewater, while the output variables consisted of levels of six wastewater (WW) parameters, namely BOD, COD, NH 3 -N, TDS, TA, and TH. Different search algorithms were employed to identify the neural network (NN) architectures that provided single and multiple target variable (two to six target variables) predictions to the analysis. Experimental results indicate that the NN architecture optimized via Bayesian Optimization outperforms others, achieving the lowest mean absolute error (MAE) and a high coefficient of determination (R 2 ). For single-target predictions on the validation set, the model attained R 2 values of 0.9770 for BOD, 0.9860 for COD, 0.9800 for NH 3 -N, 0.9776 for TDS, 0.9847 for TA, and 0.9639 for TH. For two target predictions on the validation set, the model obtained R 2 values of 0.988 for BOD and 0.993 for COD. Similarly R 2 for predictions for three target variables are 0.961 for BOD, 0.962 for COD and 0.946 for NH3-N; for four target predictions 0.972 for BOD, 0.970 for COD, 0.955 for NH 3 -N and 0.972 for TDS; for five predictions 0.966 for BOD, 0.966 for COD, 0.951 for NH 3 -N, 0.966 for TDS and 0.966 for TA; and for six target predictions 0.987 for BOD, 0.99 for COD, 0.982 for NH 3 -N, 0.99 for TDS, 0.99 for TA and 0.718 for TH. Bayesian optimization search-based NN predicted the TH value with an R 2 of 0.718. The Hyperband search NN obtained better results for TH prediction during six target predictions i.e. 0.9772 for BOD, 0.976 for COD, 0.975 for NH 3 -N, 0.976 for TDS, 0.976 for TA, and 0.899 for TH. This work automates the neural network architecture optimization process using NAS techniques. These methods systematically explore the hyperparameter space, removing the need for manual trial-and-error tuning across different datasets and target prediction tasks (both single and multi-target). The resulting neural network models are further interpreted using the LIME Explainable Artificial Intelligence (XAI) method.

Seismoacoustic monitoring of eastern mediterranean earthquakes toward a tsunami early warning system for Egypt

Reno-protective CT contrast nanoagent targets proximal tubular epithelium for kidney disease imaging and repair in a mouse model

Rising prevalence of parent-reported learning disabilities among U.S. children and adolescents aged 6–17 years: NSCH, 2016–2023

The prevalence of learning disabilities (LD) among children is a critical public health issue; however, recent LD prevalence estimates among children and adolescents aged 6–17 years, as reported by the National Survey of Children’s Health (NSCH), remain largely unexplored. Data for this population-based cross-sectional study were obtained from NSCH to estimate the prevalence of LD diagnosis among U.S. children at both national and state levels, and to inspect the 8-year trends in these estimates from 2016 to 2023. Among 221,244 U.S. children, 20,644 had a history of LD diagnosis, with a weighted prevalence of 8.85% (95% CI  = 8.59–9.10). Of these, 19,289 were currently diagnosed with LD, yielding a weighted prevalence of 8.26% (95% CI  = 8.01–8.51). From 2016 to 2023, the prevalence of ever-diagnosed LD increased from 7.86% to 9.15%, while that of current-diagnosed LD rose from 7.32% to 8.66%, representing relative increases of 16.4% and 18.3%, respectively. The state with the highest prevalence (New Hampshire) had twice that of the state with the lowest prevalence (Utah). This study highlights a critical escalation in LD prevalence among U.S. children and adolescents between 2016 and 2023. Comprehensive screening and support programs must be implemented to enhance early identification and intervention.

Tunable photon-recoil forces and negative torque at flat-top beam edges

ZPBP and fertility-associated proteomes as novel biomarkers: A shotgun proteomics approach in Murrah buffalo (Bubalus bubalis) bulls’ seminal plasma and cryopreserved spermatozoa

Comprehensive identification of seminal plasma and spermatozoa proteins is essential to understand sperm biology and the molecular mechanisms underlying bull fertility. In this study, we conducted a quantitative proteomic analysis of seminal plasma and cryopreserved spermatozoa from Murrah buffalo ( Bubalus bubalis ) bulls using a comparative shotgun proteomics approach to identify proteins associated with reproduction. 1,893 and 1,913 proteins were identified in seminal plasma and spermatozoa, respectively. Among these, 232 proteins were selectively identified in both seminal plasma and spermatozoa. Notably, zona pellucida binding protein (ZPBP) was explicitly expressed in spermatozoa, while no reproduction-associated proteins were detected in the seminal plasma proteome. Gene ontology (GO) analysis revealed that most proteins were involved in reproduction-related cellular and metabolic processes. Protein–protein interaction (PPI) network analysis further indicated that ZPBP is involved in biological processes, including acrosome formation and spermatid development. ZPBP was identified with a low false discovery rate (FDR = 0.0021), underscoring its statistical significance. Several proteins were associated with key reproductive functions, including spermatogenesis, sperm motility, energy metabolism, and cellular stress responses. These findings reveal distinct proteomic signatures with strong potential as candidate biomarkers for assessing bull fertility, supporting more accurate reproductive evaluations, and the strategic selection of genetically and reproductively superior breeding bulls in buffalo reproductive management programs.