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Fibers, with over 100 million tons produced each year, have been widely used in various areas. Recent efforts have focused on improving mechanical properties and chemical resistance of fibers via covalent cross-linking. However, the covalently cross-linked polymers are usually insoluble and infusible, and thus fiber fabrication is difficult. Those reported require complex multiple-step preparation processes. Herein, we present a facile and effective strategy to prepare adaptable covalently cross-linked fibers by direct melt spinning of covalent adaptable networks (CANs). At processing temperature, dynamic covalent bonds are reversibly dissociated/associated and the CANs are temporarily disconnected to enable melt spinning; at the service temperature, the dynamic covalent bonds are frozen, and the CANs exhibit favorable structural stability. We demonstrate the efficiency of this strategy via dynamic oxime-urethane based CANs, and successfully prepare adaptable covalently cross-linked fibers with robust mechanical properties (maximum elongation of 2639%, tensile strength of 87.68 MPa, almost complete recovery from an elongation of 800%) and solvent resistance. Application of this technology is demonstrated by an organic solvent resistant and stretchable conductive fiber. Covalent cross-linking can be used to improve the mechanical properties of fibers, but can be complicated to prepare and process. Here, the authors report fibers prepared with dynamic covalent bonds, which can reversibly dissociate to enable processing, while maintaining improved mechanical properties in the final material.

During the COVID-19 pandemic, many people devoted longer time to screen viewing due to the need for study, work, and online social activities, instead of outdoor activities, which may have led to an increase in dry eye symptoms. This study aimed to evaluate the prevalence of dry eye during the COVID-19 pandemic. PubMed, Cochrane Library, Embase, and Web of Science were searched from January 1, 2020 to October 20, 2022. Cross-sectional surveys on dry eye prevalence conducted after January 1, 2020 were included. Two review authors independently performed data extraction and assessed study quality. The random-effects model was used to analyze the prevalence of dry eye, and the odds ratio was used to assess the strength of the association between variables. Subgroup analysis was performed to detect heterogeneity, the leave-one-out method for sensitivity analysis, and the Egger test for publication bias. A total of eleven studies with 15692 individuals met the eligibility criteria. The prevalence of dry eye during the COVID-19 pandemic was 61.0% (95%CI: 51.8%-70.2%) globally and 56.7% (95%CI: 45.3%-68.1%) in Asia. The prevalence of dry eye had significant differences in sex and visual display time, with higher prevalence among females and visual display time of more than 4 hours per day. Subgroup analysis was performed based on diagnostic tools, study population, and average age. A significant difference was found in diagnostic tools, but no significant change in heterogeneity (P<0.05). The leave-one-out method showed stable results, and the Egger test identified no significant publication bias. The prevalence of dry eye during the COVID-19 pandemic is significantly higher than before, and a higher prevalence is found among females and those having a visual display time of more than 4 hours per day.

Background This systematic review and network meta-analysis assessed via direct and indirect comparisons the recovery effects of hydrotherapy and cold therapy at different temperatures on exercise induced muscle damage. Methods Five databases were searched in English and Chinese. The included studies included exercise interventions such as resistance training, high-intensity interval training, and ball games, which the authors were able to define as activities that induce the appearance of EIMD. The included RCTs were analyzed using the Cochrane Risk of Bias tool. Eligible studies were included and and two independent review authors extracted data. Frequentist network meta-analytical approaches were calculated based on standardized mean difference (SMD) using random effects models. The effectiveness of each intervention was ranked and the optimal intervention was determined using the surface under the cumulative ranking curve (SUCRA) indicator. Results 57 studies with 1220 healthy participants were included, and four interventions were examined: Cold Water Immersion (CWI), Contrast Water Therapy (CWT), Thermoneutral or Hot Water Immersion (TWI/HWI), and Cryotherapy(CRYO). According to network meta-analysis, Contrast Water Immersion (SUCRA: 79.9% )is most effective in recovering the biochemical marker Creatine Kinase. Cryotherapy (SUCRA: 88.3%) works best to relieve Delayed Onset Muscle Soreness. In the recovery of Jump Ability, cryotherapy (SUCRA: 83.7%) still ranks the highest. Conclusion We found that CWT was the best for recovering biochemical markers CK, and CRYO was best for muscle soreness and neuromuscular recovery. In clinical practice, we recommend the use of CWI and CRYO for reducing EIMD. Systematic Review Registration [PROSPERO], identifier [CRD42023396067].

This study proposes an efficient fine art image classification method integrating lightweight deep learning to address the limitations of low efficiency and poor generalization in art image classification tasks. The approach designs a lightweight hybrid network, MobileNet-Transformer Hybrid (MTH), that combines depthwise separable convolution with multi-head self-attention mechanisms to achieve efficient fusion of local details and global semantics. A dynamic channel-spatial attention module (DCSAM) adaptively enhances style-sensitive feature responses, while a cross-style feature transfer (CSFT) framework employs contrastive learning to align different style distributions and improve model robustness. Experiments conducted on the ArtBench-10 and WikiArt datasets validate the model’s performance in both classification accuracy and computational efficiency. The results demonstrate: (1) The proposed method enhances local style-discriminative features such as brushstrokes and colors through the DCSAM module, effectively alleviating the misjudgment problem of similar artistic styles. Among them, the CSFT framework constrains the cross-style feature distance through contrastive loss, improving the generalization of rare styles in long-tailed data. (2) The parameter count of the proposed model (1.2 M) is 14.8% of that of EfficientNetV2-S (8.1 million (M)) and 4.2% of that of Swin Tiny (28.3 M). Under this lightweight condition, the proposed model still maintains an ArtBench-10 classification accuracy of 85.2%. Overall, this study provides an efficient solution for art design automation and cultural heritage digitization, offering theoretical innovation and practical application value.

As stretchable conductive materials, ionogels have gained increasing attention. However, it still remains crucial to integrate multiple functions including mechanically robust, room temperature self‐healing capacity, facile processing, and recyclability into an ionogel‐based device with high potential for applications such as soft robots, electronic skins, and wearable electronics. Herein, inspired by the structure of spider silk, a multilevel hydrogen bonding strategy to effectively produce multi‐functional ionogels is proposed with a combination of the desirable properties. The ionogels are synthesized based on N‐isopropylacrylamide (NIPAM), N, N‐dimethylacrylamide (DMA), and ionic liquids (ILs) 1‐ethyl‐3‐methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMI][TFSI]). The synergistic hydrogen bonding interactions between PNIPAM chains, PDMA chains, and ILs endow the ionogels with improved mechanical strength along with fast self‐healing ability at ambient conditions. Furthermore, the synthesized ionogels show great capability for the continuous fabrication of the ionogel‐based fibers using the melt‐spinning process. The ionogel fibers exhibit spider‐silk‐like features with hysteresis behavior, indicating their excellent energy dissipation performance. Moreover, an interwoven network of ionogel fibers with strain and thermal sensing performance can accurately sense the location of objects. In addition, the ionogels show great recyclability and processability into different shapes using 3D printing. This work provides a new strategy to design superior ionogels for diverse applications. Inspired by the structure of spider silk, a multilevel hydrogen bonding strategy is proposed to effectively produce multi‐functional ionogels with a combination of mechanically robust, room‐temperature self‐healing capacity, facile processing, and recyclable properties. The ionogels have shown great potential for use in wearable electronics, electronic skins, and soft robotics. The molecular strategy will be powerful tools to develop high‐performance materials.

Locally advanced pancreatic cancer (LAPC) is a borderline unresectable malignancy that presents significant treatment challenges. The management of LAPC remains a complex issue, particularly in patients who are not eligible for surgical resection. Here, we report the case of a 60-year-old woman diagnosed with LAPC through pathological biopsy who subsequently underwent targeted immunotherapy following the failure of a gemcitabine, oxaliplatin, and S-1 (G&S) chemotherapy regimen. Based on next-generation sequencing (NGS), the patient's treatment regimen was adjusted to include albumin-bound paclitaxel and capecitabine chemotherapy, along with the PD-1 inhibitor camrelizumab (200 mg/cycle) for six cycles. Throughout the treatment period, the patient consistently declined surgical intervention. Imaging studies, including an upper abdominal computed tomography (CT), revealed the formation of a calcified layer surrounding the cancerous tissue in the pancreatic head. Remarkably, the patient has shown stable disease and no evidence of metastasis since the initiation of targeted immunotherapy. This case highlights the potential of targeted immunotherapy for the treatment of LAPC, particularly in non-surgical patients. A personalized approach guided by NGS, combined with immunotherapy, is an effective alternative to traditional treatment strategies for managing this challenging malignancy.

Background An increasing number of clinical trials require biomarker-driven patient stratification, especially for revolutionary immune checkpoint blockade therapy. Due to the complicated interaction between a tumor and its microenvironment, single biomarkers, such as PDL1 protein level, tumor mutational burden (TMB), single gene mutation and expression, are far from satisfactory for response prediction or patient stratification. Recently, combinatorial biomarkers were reported to be more precise and powerful for predicting therapy response and identifying potential target populations with superior survival. However, there is a lack of dedicated tools for such combinatorial biomarker analysis. Results Here, we present dualmarker , an R package designed to facilitate the data exploration for dual biomarker combinations. Given two biomarkers, dualmarker comprehensively visualizes their association with drug response and patient survival through 14 types of plots, such as boxplots, scatterplots, ROCs, and Kaplan–Meier plots. Using logistic regression and Cox regression models, dualmarker evaluated the superiority of dual markers over single markers by comparing the data fitness of dual-marker versus single-marker models, which was utilized for de novo searching for new biomarker pairs. We demonstrated this straightforward workflow and comprehensive capability by using public biomarker data from one bladder cancer patient cohort (IMvigor210 study); we confirmed the previously reported biomarker pair TMB/TGF-beta signature and CXCL13 expression/ARID1A mutation for response and survival analyses, respectively. In addition, dualmarker de novo identified new biomarker partners, for example, in overall survival modelling, the model with combination of HMGB1 expression and ARID1A mutation had statistically better goodness-of-fit than the model with either HMGB1 or ARID1A as single marker. Conclusions The dualmarker package is an open-source tool for the visualization and identification of combinatorial dual biomarkers. It streamlines the dual marker analysis flow into user-friendly functions and can be used for data exploration and hypothesis generation. Its code is freely available at GitHub at  https://github.com/maxiaopeng/dualmarker under MIT license.

To study the effects of water stress on the fluorescence parameters and photosynthetic characteristics of rice under drip irrigation and mulching, so as to determine the response mechanisms to water stress during the tillering stage. A two-year trial was carried out at Shihezi University, China. Three water gradients were investigated. The results showed that the chlorophyll content (a + b), photosynthetic rate (Pn), and leaf area index (LAI) decreased with decreasing soil moisture content at the tillering stage. The chlorophyll content (a + b) and Pn in the flooding irrigation (CK) treatment were significantly higher than those in the stress treatments, and the chlorophyll content (a + b) and Pn in the W1 and W2 treatments were significantly lower than those in the other treatments. The maximum LAI of the CK, W1, and W2 treatments were similar, while the W3 produced lower values; stress treatment improved the ability of tillering in the early and middle stages, while the decrease in soil water content in the tillering stage resulted in a decrease in the final tillering rate; drought stress in the tillering stage resulted in decreased rice yields. The yield of the W1 and W2 treatments were similar, while that of the W3 treatment was seriously reduced. The main reasons for the reduction in yield was the significant decrease in the number of effective panicles, the seed setting rate, and a decrease in the 1000-grains weight. Water consumption in the stress treatments decreased by 51.69%–58.78% compared to the CK treatment; water-use efficiency in the CK treatment was only 0.25 kg·m−3, and the water-use efficiency of the stress treatments increased by 40%–72%. We should make full use of the compensation effect of drought stress in the water regulation of drip irrigation in covered rice and adopt the water control measure of the W2 treatment in the tillering stage. These measures are conducive to improving water-use efficiency and achieving the goal of high quality, high yield, and high efficiency.

Inflammation is the phenotypic form of various diseases. Recent development in molecular imaging provides new insights into the diagnostic and therapeutic evaluation of different inflammatory diseases as well as diseases involving inflammation such as cancer. While conventional imaging techniques used in the clinical setting provide only indirect measures of inflammation such as increased perfusion and altered endothelial permeability, optical imaging is able to report molecular information on diseased tissue and cells. Optical imaging is a quick, noninvasive, nonionizing, and easy-to-use diagnostic technology which has been successfully applied for preclinical research. Further development of optical imaging technology such as optoacoustic imaging overcomes the limitations of mere fluorescence imaging, thereby enabling pilot clinical applications in humans. By means of endogenous and exogenous contrast agents, sites of inflammation can be accurately visualized in vivo. This allows for early disease detection and specific disease characterization, enabling more rapid and targeted therapeutic interventions. In this review, we summarize currently available optical imaging techniques used to detect inflammation, including optical coherence tomography (OCT), bioluminescence, fluorescence, optoacoustics, and Raman spectroscopy. We discuss advantages and disadvantages of the different in vivo imaging applications with a special focus on targeting inflammation including immune cell tracking.

Coronavirus disease 2019 (COVID-19) cases in China has grown rapidly after adjustment of the dynamic zero-COVID-19 strategy. However, how different vaccination states affect symptoms, severity and post COVID conditions was unclear. Here, we used an online questionnaire to investigate the infection status of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among 11,897 participants, with 55.55% positive and 28.42% negative. The common COVID-19 symptoms were fatigue (73.31%), cough (70.02%), fever (65.25%) and overall soreness (58.64%); self-reported asymptomatic infection accounted for 0.7% of participants. The persistent symptoms at 1 month after infection included fatigue (48.7%), drowsiness (34.3%), cough (30.1%), decreased exercise ability (23.1%) and pharyngeal discomfort (19.4%), which was reduced by more than 200% at 2 months. Participants with complications such as chronic obstructive pulmonary disease, respiratory diseases, diabetes, hypertension, etc. have a higher proportion of hospitalization and longer recovery time ( < = 0.01). Multiple vaccination statuses reduced the infection (  < 0.001) and severity rates (  = 0.022) by varying degrees as well as reduced the risk of high fever (>39.1 °C), chills, diarrhea and ageusia/anosmia, respectively (  < 0.05). Vaccination may enhance some upper respiratory symptoms, including sore throat, nasal congestion and runny nose, respectively (  < 0.05). Participants who had been vaccinated within 3 months were better protected by helping reduce their risk of overall soreness, chills and ageusia/anosmia, respectively (  < 0.05). In conclusion, our work has updated the epidemic characteristics of the breakthrough infection (BTI) wave after the dynamic zero-COVID-19 strategy, providing data and insights on how different vaccination statuses affect COVID-19 symptoms and disease prognosis.