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Abstract Background Retinol binding protein 4 (RBP4) is a mediator of inflammation and related to skin lesion formation, which suggests its engagement in psoriasis pathology and progression. This study intended to explore the change in RBP4 after systemic treatments, and its ability to predict treatment response in psoriasis patients. Methods This prospective study enrolled 85 psoriasis patients and 20 healthy subjects. Plasma RBP4 was detected by enzyme-linked immunosorbent assay at baseline and 12th week (W12) after systemic treatments in psoriasis patients, as well as after enrollment in healthy subjects. Psoriasis Area and Severity Index (PASI) 75 and PASI 90 were evaluated at W12 in psoriasis patients. Results RBP4 at baseline was higher in psoriasis patients than in healthy subjects [median (interquartile range): 13.39 (9.71–22.92) versus 9.59 (6.57–13.72) µg/mL] (P = 0.003). In psoriasis patients, 50 (58.8%) patients achieved PASI 75 at W12, and 25 (29.4%) patients achieved PASI 90 at W12. RBP4 was decreased at W12 compared to its level at baseline (P 0.7. Conclusion Plasma RBP4 is decreased after systemic treatments, and its low baseline level and greater decline after treatments predict good treatment response in psoriasis patients.

Abstract Background Since its discovery, severe fever with thrombocytopenia syndrome (SFTS) has been characterized by rapid progression and poor prognosis, and no specific treatment is available. The aim of this study was to investigate the early warning indicators of mortality in SFTS patients. Methods This is a retrospective cross-sectional study. The study subjects were patients who were admitted to the hospital with a confirmed diagnosis of SFTS from January 2023 to October 2023, and their clinical symptoms and signs at the time of admission, as well as the laboratory indexes of the first blood collection after admission were collected, grouped according to the prognosis, and statistically analyzed. Results A total of 141 patients were collected, of which 27 patients died and 114 patients were in the survival group. Through statistical analysis, patients with combined hemorrhagic manifestations, disturbance of consciousness, lymphopenia, elevated lipase, and prolonged thrombin time on admission were independent risk factors for patients’ death. By plotting the working characteristic curve of the subjects, as well as calculating the area under the curve, the results showed that the AUC of lymphopenia count was 0.670, 95% CI (0.563–0.776), P = 0.006; the AUC of elevated serum lipase index was 0.789, 95% CI (0.699–0.878), p

Understanding how the bacteriomes in tuberculous lesions can be influenced by the susceptibility of Mycobacterium tuberculosis (MTB) can provide valuable information for preventing and treating drug resistant tuberculosis (DR-TB). High-throughput 16S rRNA sequencing was employed to analyze the bacteriome in pulmonary TB lesions from 14 patients with DR-TB and 47 patients with drug sensitive tuberculosis (DS-TB), along with 18 normal lung tissues (NT) from 18 lung cancer patients serving as the bacterial baseline. The phylogenetic investigation of communities by reconstruction of unobserved states2 (PICRUSt2) algorithm was utilized to predict bacterial metabolic functions. The major phyla of pulmonary bacteriomes included Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes and Fusobacteria. Alpha diversity indices, including ACE, Chao1, Shannon and OTU observed, all demonstrated different bacterial communities of DS-TB samples from that of NT samples; while only Shannon indicated difference between DR-TB and NT samples. The analysis of similarity (ANOSIM) showed significantly different bacterial communities within TB lesions compared to NT samples (R = 0.418, p = 0.001). However, difference was not observed between DR-TB and DS-TB samples (ANOSIM, R = 0.069, p = 0.173). The bacterial profiles within each DR-TB individual appeared unique, with no obvious clusters corresponding to drug-resistant phenotypes. Nevertheless, indicator genera identified in DR-TB and DS-TB lesions demonstrated distinctive micro-ecological environments. Most COG functions were enriched in TB lesions, and the most significant one was [J] translation, ribosomal structure and biogenesis. The distinct enrichment patterns of bacterial enzymes in DR-TB and DS-TB lesions suggest that pulmonary bacterial activities can be modulated by the susceptibility of MTB bacilli. This study provides fresh perspectives and strategies for the precise diagnosis and assessment of drug resistance tuberculosis.

Abstract Mechanically robust hydrogel fibers have demonstrated great potential in energy dissipation and shock‐absorbing applications. However, developing such materials that are recyclable, energy‐efficient, and environmentally friendly remains an enormous challenge. Herein, inspired by spider silk, a continuous and scalable method is introduced for spinning a polyacrylamide hydrogel microfiber with a hierarchical sheath‐core structure under ambient conditions. Applying pre‐stretch and twist in the as‐spun hydrogel microfibers results in a tensile strength of 525 MPa, a toughness of 385 MJ m−3, and a damping capacity of 99%, which is attributed to the reinforcement of hydrogen‐bond nanoclusters within the microfiber matrix. Moreover, it maintains both structural and mechanical stability for several days, and can be directly dissolved in water, providing a sustainable spinning dope for re‐spinning into new microfibers. This work provides a new strategy for the spinning of robust and recyclable hydrogel‐based fibrous materials.

Background Wearable technology is used in healthcare to monitor the health of individuals. This study presents an updated systematic literature review of the use of wearable technology in promoting child and adolescent health, accompanied by recommendations for future research. Methods This review focuses on studies involving children and adolescents aged between 2 and 18 years, regardless of their health condition or disabilities. Studies that were published from 2016 to 2024, and which met the inclusion criteria, were extracted from four academic databases (i.e. PubMed, Cochrane, Embase, and Web of Science) using the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol. Data on intervention purposes, interventions deployed, intervention duration, measurements, and the main outcomes of the studies were collected. Results A total of 53 studies involving 14,852 participants were reviewed. They focused on various aspects, including the ownership and use of wearable devices ( n = 3), the feasibility ( n = 22), effectiveness ( n = 4), and adherence ( n = 2) of intervention strategies, or a combination of multiple aspects ( n = 22). Among the interventions deployed, Fitbit was the most frequently used, featuring in 26 studies, followed by ActiGraph ( n = 11). In intervention studies, the majority of studies focused on pre-morbidity prevention ( n = 26) and the treatment of illnesses ( n = 20), with limited attention given to postoperative monitoring ( n = 4). Conclusions The use of wearable technology by children and adolescents has proven to be both feasible and effective for health promotion. This systematic review summarizes existing research by exploring the use of wearable technology in promoting health across diverse youth populations, including healthy and unhealthy individuals. It examines health promotion at various stages of the disease continuum, including pre-disease prevention, in-disease treatment, and postoperative monitoring. Additionally, the review provides directions for future research.

Understanding customer sentiment through product reviews is important for businesses aiming to enhance their products and services. Traditional sentiment analysis often struggles to detect the wide range of emotional nuances, particularly those expressed through emojis, in online reviews. To address this challenge, our paper introduces a novel technique called Emoji-Enhanced BERT (EEBERT) based, on the BERT architecture. The Sentiment Adjustment Factor (SAF), created for emoji tokenization with the embeddings layer, is applied to analyze sentiment and emotion within review text content. Sentiments classification is evaluated using three different methods: (1) evaluating the full review text; (2) analyzing the text with emojis; and (3) integrating star ratings and total votes in EEBERT. These methods were fine-tuned using a labeled Amazon product reviews dataset. The approach utilizes a well-vetted dataset comprising approximately 10 million customer reviews from four different categories. This dataset is condensed to 26,818 reviews to only consider emoji contained reviews, covering 3,275 distinct emojis. A systematic approach to classifying reviews and an innovative technique for assessing the emotional semantics of emojis are developed. The proposed model achieves an accuracy of 97.00%, further applies continuous testing via 5-fold cross-validation, achieving an average accuracy of 99.21%, which supports the reliability of the EEBERT model.

As the behavior analysis of human body is more and more used in the fields of intelligent monitoring and motion analysis, it is of great significance to conduct research.The current two-dimensional regression network algorithm models in human motion recognition and estimation do not consider the interrelationships between human joint points, resulting in missing connections between joint points and low accuracy of feature maps. Therefore, this study proposes an improved two-dimensional regression network algorithm model based on local constraints and relational networks, and verifies its effectiveness. The experimental results show that, considering only local constraints, the proportion of the head in the correct key points of the improved algorithm in the wrist joint score is 84.72%, while the comparison algorithm is 84.55%, an increase of 1.17%. The maximum value is 88.7% when the number of regression network modules is 8. In practical applications, the actual label results of indoor and outdoor environments are basically consistent with those of the detected image, but there are errors under indoor occlusion conditions. Considering both local constraints and relational networks, the improved algorithm has variant standard scores of 98.8%, 95.3%, 93.3%, 89.4%, 95.1%, 96.2%, and 94.2% for the correct percentage of 7 joint points, respectively, which are higher than the comparison algorithm. Overall, the proposed two-dimensional regression network algorithm based on local constraints and relationship networks has practicality and effectiveness, which can be effectively applied in practical human motion recognition.

Obesity presents a significant global health challenge, increasing the susceptibility to chronic conditions such as diabetes, cardiovascular disease, and hypertension. Within the context of obesity, lipid metabolism, adipose tissue formation, and inflammation are intricately linked to endoplasmic reticulum stress (ERS). ERS modulates metabolism, insulin signaling, inflammation, as well as cell proliferation and death through the unfolded protein response (UPR) pathway. Serving as a crucial nexus, ERS bridges the functionality of adipose tissue and the inflammatory response. In this review, we comprehensively elucidate the mechanisms by which ERS impacts adipose tissue function and inflammation in obesity, aiming to offer insights into targeting ERS for ameliorating metabolic dysregulation in obesity-associated chronic diseases such as hyperlipidemia, hypertension, fatty liver, and type 2 diabetes.

Abstract Diabetic nephropathy (DN) is a serious microvascular complication of diabetes. Ferroptosis, a new form of cell death, plays a crucial role in the pathogenesis of DN. Renal tubular injury triggered by ferroptosis might be essential in this process. Numerous studies demonstrate that the vitamin D receptor (VDR) exerts beneficial effects by suppressing ferroptosis. However, the underlying mechanism has not been fully elucidated. Thus, they verified the nephroprotective effect of VDR activation and explored the mechanism by which VDR activation suppressed ferroptosis in db/db mice and high glucose‐cultured proximal tubular epithelial cells (PTECs). Paricalcitol (PAR) is a VDR agonist that can mitigate kidney injury and prevent renal dysfunction. PAR treatment could inhibit ferroptosis of PTECs through decreasing iron content, increasing glutathione (GSH) levels, reducing malondialdehyde (MDA) generation, decreasing the expression of positive ferroptosis mediator transferrin receptor 1 (TFR‐1), and enhancing the expression of negative ferroptosis mediators including ferritin heavy chain (FTH‐1), glutathione peroxidase 4 (GPX4), and cystine/glutamate antiporter solute carrier family 7 member 11 (SLC7A11). Mechanistically, VDR activation upregulated the NFE2‐related factor 2/heme oxygenase‐1 (Nrf2/HO‐1) signaling pathway to suppress ferroptosis in PTECs. These findings suggested that VDR activation inhibited ferroptosis of PTECs in DN via modulating the Nrf2/HO‐1 signaling pathway.

Recently, image generation technology has demonstrated surprising effects. However, precisely recognizing the emotion in sound to accurately express it on the face of a designated person is a huge challenge. To address this challenge, a new framework, Sound to Expression (S2E), which can use the emotion in sound to guide facial expression image generation, is proposed. A speech dataset for emotion recognition is constructed. S2E can edit facial expressions with different emotions in sounds for different people. S2E consists of Continuous Wavelet Transform (CWT), YOLOv3, ChatGPT-3, and facial expression diffusion editing model (FEDEM). CWT is utilized to extract emotional features from different sounds. YOLOv3 is employed to identify the emotion categories. The emotion category and a specific person's name are input into ChatGPT-3 to randomly generate a description of the person and emotion. The description is input into FEDEM to generate a facial expression image. To generate more accurate images and address emotional semantic deviation, a new facial detail emotional preservation loss is proposed. The experimental results show that S2E can accurately recognize the emotion in the voice and use this emotion to guide the editing of the facial expression for the specified person to generate more accurate images.

Plants of the Meliaceae family have long attracted researchers’ interest due to their various insecticidal activities, with triterpenes being the main active ingredients. In this paper, we discuss 93 triterpenoids with insecticidal activity from 37 insecticidal plant species of 15 genera (Munronia, Neobeguea, Pseudocedrela, Nymania, Quivisia, Ruagea, Dysoxylum, Soymida, Lansium, Sandoricum, Walsura, Trichilia, Swietenia, Turraea, and Xylocarpus) in the family Meliaceae. Among these genera, Trichilia deserves further research, with twelve species possessing insecticidal activity. The 93 insecticidal molecules included 27 ring-seco limonoids (comprising 1 ring A-seco group chemical, 1 ring B-seco group chemical, 5 ring D-seco group chemicals, 14 rings A,B-seco group chemicals, 5 rings B,D-seco group chemicals, and 1 rings A,B,D-seco group chemical), 22 ring-intact limonoids (comprising 5 cedrelone-class chemicals, 6 trichilin-class chemicals, 7 havanensin-class chemicals, 2 azadirone-class chemicals, 1 vilasinin-class chemical, and 1 other chemical), 33 2,30-linkage chemicals (comprising 25 mexicanolide-class chemicals and 8 phragmalin-class chemicals), 3 1,n-linkage-group chemicals, 3 onoceranoid-type triterpenoids, 2 apotirucallane-type terpenoids, 2 kokosanolide-type tetranortriterpenoids, and 1 cycloartane triterpene. In particular, 59 molecules showed antifeedant activity, 30 molecules exhibited poisonous effects, and 9 molecules possessed growth regulatory activity. Particularly, khayasin, beddomei lactone, 3β,24,25-trihydroxycycloartane, humilinolides A–E and methyl-2-hydroxy-3β-isobutyroxy-1-oxomeliac-8(30)-enate showed excellent insecticidal activities, which were comparable to that of azadirachtin and thus deserved more attention. Moreover, it was noteworthy that various chemicals (such as 12α-diacetoxywalsuranolide, 11β,12α-diacetoxycedrelone, 1α,7α,12α-triacetoxy-4α-carbomethoxy-11β-hydroxy-14β,15β-epoxyhavanensin, and 11-epi-21-hydroxytoonacilide, etc.) from Turraea showed excellent insecticidal activity. Specially, the insecticidal activity of khayasin from Neobeguea against the coconut leaf beetle were similar to that of rotenone. Therefore, it was a promising candidate insecticide for the control of the coconut leaf beetle.

ObjectiveAnalyzing the epidemiological characteristics of influenza cases among children aged 0–17 years in Guangzhou from 2019 to 2022. Assessing the relationships between multiple meteorological factors and influenza, improving the early warning systems for influenza, and providing a scientific basis for influenza prevention and control measures.MethodsThe influenza data were obtained from the Chinese Center for Disease Control and Prevention. Meteorological data were provided by Guangdong Meteorological Service. Spearman correlation analysis was conducted to examine the relevance between meteorological factors and the number of influenza cases. Distributed lag non-linear models (DLNM) were used to explore the effects of meteorological factors on influenza incidence.ResultsThe relationship between mean temperature, rainfall, sunshine hours, and influenza cases presented a wavy pattern. The correlation between relative humidity and influenza cases was illustrated by a U-shaped curve. When the temperature dropped below 13°C, Relative risk (RR) increased sharply with decreasing temperature, peaking at 5.7°C with an RR of 83.78 (95% CI: 25.52, 275.09). The RR was increased when the relative humidity was below 66% or above 79%, and the highest RR was 7.50 (95% CI: 22.92, 19.25) at 99%. The RR was increased exponentially when the rainfall exceeded 1,625 mm, reaching a maximum value of 2566.29 (95% CI: 21.85, 3558574.07) at the highest rainfall levels. Both low and high sunshine hours were associated with reduced incidence of influenza, and the lowest RR was 0.20 (95% CI: 20.08, 0.49) at 9.4 h. No significant difference of the meteorological factors on influenza was observed between males and females. The impacts of cumulative extreme low temperature and low relative humidity on influenza among children aged 0–3 presented protective effects and the 0–3 years group had the lowest RRs of cumulative extreme high relative humidity and rainfall. The highest RRs of cumulative extreme effect of all meteorological factors (expect sunshine hours) were observed in the 7–12 years group.ConclusionTemperature, relative humidity, rainfall, and sunshine hours can be used as important predictors of influenza in children to improve the early warning system of influenza. Extreme weather reduces the risk of influenza in the age group of 0–3 years, but significantly increases the risk for those aged 7–12 years.

Peptides present an alternative modality to immunoglobulin domains or small molecules for developing therapeutics to either agonize or antagonize cellular pathways associated with diseases. However, peptides often suffer from poor chemical and physical stability, limiting their therapeutic potential. Disulfide-constrained peptides (DCP) are naturally occurring and possess numerous desirable properties, such as high stability, that qualify them as drug-like scaffolds for peptide therapeutics. DCPs contain loop regions protruding from the core of the molecule that are amenable to peptide engineering via direct evolution by use of phage display technology. In this study, we have established a robust platform for the discovery of peptide therapeutics using various DCPs as scaffolds. We created diverse libraries comprising seven different DCP scaffolds, resulting in an overall diversity of 2 x 1011. The effectiveness of this platform for functional hit discovery has been extensively evaluated, demonstrating a hit rate comparable to that of synthetic antibody libraries. By utilizing chemically synthesized and in vitro folded peptides derived from selections of phage displayed DCP libraries, we have successfully generated functional inhibitors targeting the HtrA1 protease. Through affinity maturation strategies, we have transformed initially weak binders against Notch2 with micromolar Kd values to high-affinity ligands in the nanomolar range. This process highlights a viable hit-to-lead progression. Overall, our platform holds significant potential to greatly enhance the discovery of peptide therapeutics.

Dendritic cells (DCs), the most efficient antigen-presenting cells (APCs), bridge the innate and adaptive immune systems. As such, the turn-over of DCs is critical during autoimmune responses, and the dysregulation of DC apoptosis could cause severe immune destruction in the host. For example, reduction of immunogenic DCs by increased apoptosis could lead to immune tolerance to pathogen infection that might allow exposure of nuclear autoantigens, whereas reduced apoptosis could result in long-term lymphocyte activation to break the immune tolerance for the development of autoimmune disease. Thus, keeping a balance between survival and apoptosis of DCs is crucial to maintain immune homeostasis. In this review, we summarize the recent development on the factors inducing DC apoptosis and their underlying mechanisms to provide insights into the immunopathogenesis of some autoimmune diseases, which could lead to effective therapeutic interventions in the clinics.

Objective: To examine the effectiveness of psychoeducational interventions on depression, anxiety, and health-related quality of life (HRQOL) for people undergoing maintenance hemodialysis (MHD). Methods: This review used systematic review and meta-analysis as the research design. Nine databases, including PubMed, Web of Science, Embase, CINAHL Complete, Cochrane Library, CNKI, WanFang, VIP, and Chinese Biomedical Literature Database, were searched from the inception to the 8th of July 2023. Two reviewers independently identified randomized controlled trials (RCT) examining the effects of psychoeducational interventions on MHD patients. Results: Fourteen studies involving 1134 MHD patients were included in this review. The results of meta-analyses showed that psychoeducational intervention had significant short-term (< 1m) (SMD: −0.87, 95% CI: −1.54 to −0.20, p=0.01, I² = 91%; 481 participants), and medium-term (1–3m) (SMD: −0.29, 95% CI: −0.50 to −0.08, p=0.01, I² = 49%; 358 participants) on anxiety in MHD patients, but the effects could not be sustained at longer follow-ups. Psychoeducational interventions can also have short-term (< 1m) (SMD: −0.65, 95% CI: −0.91 to −0.38, p<0.00001, I² = 65%; 711 participants) and medium-term (1–3m) (SMD: −0.42, 95% CI: −0.76 to −0.09, p=0.01, I² = 69%; 489 participants) effects in reducing depression levels in MHD patients. Psychoeducational interventions that use coping strategies, goal setting, and relaxation techniques could enhance the QOL in MHD patients in the short term (< 1m) (SMD: 0.86, 95% CI: 0.42 to 1.30, p=0.02, I² = 86%; 241 participants). Conclusions: Psychoeducational interventions have shown great potential to improve anxiety, depression, and quality of life in patients with MHD at the short- and medium-term follow-ups. Trial registration number: CRD42023440561. [ABSTRACT FROM AUTHOR]