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Glycosylation is a common post-translational modification that occurs during the production of antibodies. Glycans attached to antibodies play an important role in the pharmacokinetics, efficacy, and safety of therapeutic antibodies. In the modern antibody industry, it is important to adjust and control glycosylation modifications. The formation of specific sugar structures via glycosylation engineering is constantly evolving. This review summarizes the recent progress in glycosylation modifications, as well as the major discoveries and current understanding of the mechanisms involved, to provide new ideas for the research and development of therapeutic antibodies.

Terpenes, representing one of the most extensive classes of natural products, hold significant value in the fields of pharmaceuticals, fragrances, and biofuels. Extracting these compounds from natural sources is often environmentally unsustainable, and the structural diversity found in nature is inherently limited. Metabolic engineering using microbial hosts offers a scalable and sustainable alternative, utilizing optimized biosynthetic pathways—such as the mevalonate (MVA) and the methylerythritol phosphate (MEP) pathways—to achieve high-yield production of natural terpene scaffolds. This review focuses on the various strategies in developing microbial cell factories, ranging from enhancing precursor supply to optimizing terpene synthase systems. A new and promising frontier is the increase in structural diversity of terpenes by integration of non-biological chemical transformations into engineered biosynthetic pathways. We discuss the use of artificial metalloenzymes such as engineered cytochrome P450 variants that catalyze non-natural carbene transfer reactions (cyclopropanation). The merging of synthetic biology and synthetic chemistry goes beyond the normal synthesizing capabilities found in nature, which may pave the way for the design of “non-natural” terpenoids that contain new additions and better capabilities.

Global social and policy concerns regarding young carers’ care burden are increasing, but the outcomes of their caring responsibilities, especially in Asian countries, remain inadequately explored. We empirically examined the associations of care burden with psychological distress and cognitive–emotional aspects using cross‑sectional online surveys of young carers aged 15–19 living throughout Japan in 2021 (during the COVID‑19 pandemic) and 2024 (post‑pandemic). Each survey sampled a different group of young carers. The Kessler Psychological Distress Scale and Positive and Negative Outcomes of Caring were used to assess outcomes, which were analyzed in relation to care complexity and intensity. The mean psychological distress score was 7.33, with significantly higher scores observed during the pandemic compared with 2024. However, both positive and negative scores on the cognitive and emotional outcomes instrument were significantly elevated post-pandemic. We observed a heavy care burden, associated with worsened psychological distress. Regarding cognitive–emotional aspects, greater care task complexity was associated with an increase in both negative and positive responses. Policies should offer tailored support for young carers, especially during emergencies, ensure that they receive mental health support, tackle issues associated with young carers’ isolation, and deliver accessible and youth-friendly social resources.

We present a new pore‐scale model for multicomponent advective‐diffusive transport with coupled mineral dissolution and precipitation. Both dissolution and precipitation are captured simultaneously by introducing a phase transformation vector field representing the direction and magnitude of the overall phase change. An effective viscosity model is adopted in simulating fluid flow during mineral dissolution‐precipitation that can accurately capture the velocity field without introducing any empirical parameters. The proposed approach is validated against analytical solutions and interface tracking simulations in simplified structures. After validation, the proposed approach is employed in modeling realistic rocks where mineral dissolution and precipitation are dominant at different locations. We have identified three regimes for mineral dissolution‐precipitation coupling: (a) compact dissolution‐precipitation where dissolution is dominant near the inlet and precipitation is dominant near the outlet, (b) wormhole dissolution with clustered precipitation where dissolution generates wormholes in the main flow paths and precipitation clogs the secondary flow paths, and (c) dissolution dominant where all solid grains are gradually dissolved. In the three regimes, the proposed approach provides reliable porosity‐permeability relationships that cannot be described well by traditional macroscale models. We find that the permeability can increase while the overall porosity decreases when the main flow paths are expanded by dissolution and adjacent pore spaces are clogged by precipitation. Key Points A new pore‐scale model is developed for multicomponent reactive flow with coupled mineral dissolution and precipitation The proposed model is validated against analytical solutions and reference simulations, and then applied to realistic rocks Three dissolution‐precipitation coupling regimes with different flow patterns and porosity‐permeability relationships have been identified

Background The triglyceride glucose (TyG) index has been proposed as a reliable marker of insulin resistance (IR) and an independent predictor of cardiovascular disease risk. However, its prognostic value in patients with acute decompensated heart failure (ADHF) remains unclear. Methods A total of 932 hospitalized patients with ADHF from January 1st, 2018 to February 1st, 2021 were included in this retrospective study. The TyG index was calculated as ln [fasting triglyceride level (mg/dL) × fasting plasma glucose level (mg/dL)/2]. Patients were divided into tertiles according to TyG index values. The primary endpoints were all-cause death, cardiovascular (CV) death and major adverse cardiac and cerebral events (MACCEs) during follow-up. We used multivariate adjusted Cox proportional hazard models and restricted cubic spline analysis to investigate the associations of the TyG index with primary endpoints. Results During a median follow-up time of 478 days, all-cause death, CV death and MACCEs occurred in 140 (15.0%), 103 (11.1%) and 443 (47.9%) cases, respectively. In multivariate Cox proportional hazard models, the risk of incident primary endpoints was associated with the highest TyG tertile. After adjustment for confounding factors, hazard ratios (HRs) for the highest tertile (TyG index ≥ 9.32) versus the lowest tertile (TyG index < 8.83) were 2.09 (95% confidence interval [CI], 1.23–3.55; p = 0.006) for all-cause death, 2.31 (95% CI, 1.26–4.24; p = 0.007) for CV death and 1.83 (95% CI, 1.18–3.01; p = 0.006) for MACCEs. Restricted cubic spline analysis also showed that the cumulative risk of primary endpoints increased as TyG index increased. When the TyG index was used as a continuous variable, the hazard ratios of the three primary endpoints rapidly increased within the higher range of the TyG index (all cause death, TyG > 9.08; CV death, TyG > 9.46; MACCEs, TyG > 9.87). Conclusions The elevated TyG index was independently associated with poor prognosis, and thus would be useful in the risk stratification in patients with ADHF.

Tobacco smoking is a major global health threat. Pharmacological aids, including nicotine-replacement therapy (NRT), varenicline, and bupropion, improve quit rates but are associated with gastrointestinal (GI) adverse events (AEs) that can compromise adherence. The real-world reporting profiles of these GI AEs, particularly the differences between sexes, have not been comprehensively characterized. We analyzed the FDA Adverse Event Reporting System (FAERS) database from 2004 Q1 to 2024 Q2. After deduplication, reports designating NRT, varenicline, or bupropion as the primary suspect drug were extracted. Disproportionality analyses, including the Proportional Reporting Ratio (PRR) and Reporting Odds Ratio (ROR), were conducted to quantify drug-event associations. The Breslow-Day test was used to assess the homogeneity of RORs between male and female strata. Varenicline was associated with the highest proportion of GI reports (36.0% of its total reports). The disproportionality signal was significantly stronger in women than in men (ROR 6.41 vs. 5.10 for nausea, p < 0.001). NRT was linked to 24.3% of GI reports, with hiccups (PRR = 60.1) being the most prominent signal. In contrast to varenicline, several key GI AE signals for NRT were significantly stronger in men (e.g., nausea, ROR 3.09 in men vs. 2.45 in women, p < 0.001). Bupropion had the lowest proportion of GI reports (2.1%) but still generated significant disproportionality signals (overall ROR 4.50), particularly for anorexia (PRR = 4.80) and dry mouth (PRR = 4.42), with most signals being stronger in women. NRT, varenicline, and bupropion exhibit distinct and statistically significant sex-specific GI AE reporting profiles in a real-world setting. These hypothesis-generating findings underscore the importance of considering sex as a variable in pharmacovigilance studies and may inform future research aimed at personalizing smoking cessation therapy.

Existing remote sensing object detection methods struggle with challenges such as complex background interference, variable object scales, and class imbalance due to a lack of coordinated internal optimization. This paper proposes AFDNet, a novel RSOD algorithm that establishes an internal collaborative evolution mechanism to systematically enhance the model’s feature perception and localization capabilities in complex scenes. AFDNet achieves this through three tightly coupled, co-evolving components: (1) A channel–spatial dual-sensing module that adaptively focuses on crucial features and suppresses background noise. (2) A dynamic bounding box optimization module that integrates distance-aware and scale-normalization strategies, significantly boosting localization accuracy and regression robustness for multi-scale objects. (3) A Gaussian adaptive activation unit that enhances the model’s nonlinear fitting capability for better detail extraction under weak conditions. Extensive experiments on two public datasets, RSOD and NWPU VHR-10, verify the excellent performance of AFDNet. AFDNet achieved a leading 95.16% mAP@50 on the RSOD dataset and an astonishing 96.52% mAP@50 on the NWPU VHR-10 dataset, which is significantly better than the mainstream detection models. This study verifies the effectiveness of introducing internal co-evolution mechanisms and provides a novel and reliable solution for high-precision remote sensing target detection.

Background Social isolation among older adults has intensified during the coronavirus disease 2019 (COVID-19) pandemic, disproportionately affecting frail older adults. This study examines the role of information and communication technology (ICT) in reducing social isolation and explores its differential effects between frail and healthy older adults. Methods This study employed a quantitative research design with cross-sectional data obtained from the “Survey on Older Adults of Sakai City” in Japan. Social isolation is measured in terms of three dimensions: loneliness, social participation, and access to social support. Ordered probit techniques were employed to estimate the effects of ICT use frequency while controlling for individual characteristics. Results Frequent ICT use, including smartphones and voice calls, was significantly associated with reduced loneliness, with frail older adults benefiting more significantly. However, ICT use had a limited impact on increasing the diversity of social participation, likely due to the substitution of in-person activities with online interactions during the pandemic. Access to social support yielded mixed results, with no consistent improvement across the entire sample. Conclusions ICT serves as a valuable tool to alleviate loneliness among older adults, especially frail older adults, but it cannot fully replace face-to-face interactions to foster diverse forms of social participation. Simplified ICT tools and tailored training programs are essential to improve accessibility for frail older adults. Future efforts should explore integrating ICT with offline activities and leveraging emerging technologies, such as video conferencing, to address social isolation more comprehensively. Trial registration Not applicable.

ObjectivesTo systematically evaluate the effect of exercise interventions on mental health outcomes (encompassing anxiety, depression and stress) and alcohol consumption (encompassing daily or weekly standardised alcohol consumption) in individuals with alcohol use disorder (AUD).DesignWe performed a systematic review and meta-analysis of eligible randomised controlled trials (RCTs).Data sourcesWeb of Science, PubMed and the Cochrane Library were searched from database inception to February 2025 using both manual and software-assisted methods (NoteExpress).Eligibility criteriaRCTs examining the effects of exercise interventions on individuals diagnosed with AUD were included. Studies were required to report outcomes related to mental health (anxiety, depression and stress) and/or alcohol consumption. Studies without a control group or a before–after intervention design lacking a comparison were excluded. Language was restricted to English.Data extraction and synthesisTwo researchers independently extracted data. A random-effects model was used to synthesise results, reported as standardised mean differences (SMDs) with 95% CIs. Risk of bias, heterogeneity (I²) and publication bias were assessed using Stata version 14. Sensitivity and subgroup analyses were conducted to evaluate robustness and explore sources of heterogeneity.ResultsA total of 15 studies met the inclusion criteria and were included in this systematic review and meta-analysis. Exercise interventions significantly improved mental health outcomes in individuals with AUD, reducing self-reported symptoms of anxiety (SMD −0.53, 95% CI −0.87 to –0.18, p=0.003), depression (SMD −0.84, 95% CI −1.20 to –0.48, p<0.001) and stress (SMD −1.14, 95% CI −1.91 to –0.3, p=0.004). However, no significant reductions were observed in daily or weekly alcohol consumption, although a non-significant decreasing trend was noted, particularly in European populations. Heterogeneity was moderate to high across anxiety (I² = 64.5%), depression (I² = 75.6%), stress (I² = 81.8%) and daily alcohol use (I² = 55.8%). Subgroup analyses revealed that short-term interventions (<14 weeks) were more effective for anxiety and depression. Yoga demonstrated superior effects on depression compared with aerobic exercise, particularly when session durations were <60 min.ConclusionsExercise-based interventions are effective in improving mental health in individuals with AUD, particularly in alleviating anxiety, depression and stress. Although effects on alcohol consumption were not statistically significant, consistent trends suggest potential benefits, influenced by geography, intervention duration and exercise modality. Tailored exercise programmes may enhance AUD treatment outcomes.PROSPERO registration numberCRD420251122437.

Background At present, the analysis of abnormal gait in post-stroke patients predominantly relies on wearable devices. However, with the advancements in computer vision technology, the integration of deep learning algorithms has introduced new possibilities for research. In particular, multi-modal fusion technology can effectively combine various modalities obtained through vision-based approaches, enabling more comprehensive and accurate representation of abnormal gait information in post-stroke patients. Methods The study recruited 70 post-stroke patients and 70 healthy individuals to capture video recordings of their gait. We used Human Pose Estimation (HPE) to extract skeleton points from each frame and computed the optical flow information of these points and the corresponding angular variations of the lower limbs. Additionally, depth space features were extracted using ResNet-50 and subsequently integrated. For classification, a Long Short-Term Memory (LSTM) network was employed to analyze the fused features. Results To evaluate the effectiveness of the feature extraction method, we tested it on both an open dataset and a self-collected clinical dataset, comparing it with CNN-RNN and Vision Transformer (ViT). The results from the LSTM network, after inputting the fused features, demonstrated optimal performance with 2 layers and 128 hidden units, achieving accuracies of 0.8794±0.0447 and 0.8778±0.0347, respectively. Conclusion It was found that optical flow information calculated based on skeleton points, combined with variations in knee flexion and ankle dorsiflexion angles, improved the interpretability of the analytical framework. This improvement enables clinicians to gain a clearer understanding of the model’s decision-making process, thereby increasing their confidence in its outputs. By employing a multi-modal fusion approach, information from different modalities is integrated, which not only broadens the analytical perspectives but also facilitates clinicians’ deeper insights into the patient’s gait characteristics.