Critical role of minor eggcase silk component in promoting spidroin chain alignment and strong fiber formation.

Natural spider silk with extraordinary mechanical properties is typically spun from more than one type of spidroin. Although the main components of various spider silks have been widely studied, little is known about the molecular role of the minor silk components in spidroin self-assembly and fiber formation. Here, we show that the minor component of spider eggcase silk, TuSp2, not only accelerates self-assembly but remarkably promotes molecular chain alignment of spidroins upon physical shearing. NMR structure of the repetitive domain of TuSp2 reveals that its dimeric structure with unique charged surface serves as a platform to recruit different domains of the main eggcase component TuSp1. Artificial fiber spun from the complex between TuSp1 and TuSp2 minispidroins exhibits considerably higher strength and Young's modulus than its native counterpart. These results create a framework for rationally designing silk biomaterials based on distinct roles of silk components.

The solution structure of human leptin reveals a conformational plasticity important for receptor recognition.

Leptin is a multi-potency cytokine that regulates various physiological functions, including weight control and energy homeostasis. Signaling of leptin is also important in many aging-related diseases. Leptin is required for the noncovalent crosslinking of different extracellular domains of leptin receptors, which is critical for receptor activation and downstream signaling. Nevertheless, the structure of intact apo-form leptin and the structural transition leptin undergoes upon receptor binding are not fully understood yet. Here, we determined the monomeric structure of wild-type human leptin by solution-state nuclear magnetic resonance spectroscopy. Leptin contains an intrinsically disordered region (IDR) in the internal A-B loop and the flexible helix E in the C-D loop, both of which undergo substantial local structural changes when leptin binds to its receptor. Our findings provide further insights into the molecular mechanisms of leptin signaling.

[Mechanism of electroacupuncture for vascular dementia based on proteomics].

OBJECTIVE: To explore the potential mechanism of electroacupuncture (EA) for vascular dementia (VD) using tandem mass tag (TMT) quantitative proteomics technology. METHODS: Among 80 male SPF SD rats, 78 rats which met the selection criteria through the Morris water maze test were selected and randomly divided into a sham surgery group (18 rats) and a surgery group (60 rats). VD model was established by four-vessel occlusion (4-VO) method in the surgery group, and 36 rats with successful modeling were randomly assigned to a model group (18 rats) and an EA group (18 rats). Each group was further divided into three subgroups based on intervention duration, with each subgroup containing 6 rats. Seven days after model establishment, the EA group received EA intervention at left and right "Sishencong" (EX-HN 1) and bilateral "Fengchi" (GB 20), with continuous wave at a frequency of 2 Hz and current intensity of 1 mA, daily for 30 min, with subgroups receiving EA for 7, 14, or 21 d respectively. Cognitive function before and after interventions was assessed using Morris water maze. Proteomic analysis was conducted on the optimal EA subgroup and corresponding sham surgery and model subgroups, identifying differentially expressed proteins and analyzing them through bioinformatics. Differentially expressed target proteins was performed using parallel reaction monitoring (PRM) and Western blot techniques. RESULTS: Compared to the sham surgery group, the model group exhibited prolonged escape latency and reduced number of platform crossings (P<0.01); compared with model group, the EA group showed reductions in escape latency and increased platform crossings after 7, 14, and 21 days of intervention (P<0.01, P<0.05). Compared to the 7 and 14-day intervention, the rats in the EA group of 21-day intervention showed the most significant improvements in reductions of escape latency and increased platform crossings (P<0.01, P<0.05), and was selected for further proteomic, PRM analyses, and Western blot validation. Compared to the sham surgery group, the model group displayed 71 differentially expressed proteins, with 50 up-regulated and 21 down-regulated proteins; compared to the model group, the EA group had 54 differentially expressed proteins, with 30 up-regulated and 24 down-regulated proteins. Functional enrichment and clustering analyses indicated that these proteins were primarily associated with cellular processes, metabolic processes, phagocytosis recognition, immune response, and regulation of extracellular matrix, etc. Enrichment was observed in the mammalian target of rapamycin (mTOR) signaling pathway and neurotrophic factors signaling pathways, involving glycogen synthase kinase 3ß (GSK3ß) and mitogen-activated protein kinase kinase 2 (Map2k2), with PRM and Western blot findings consistent with the proteomic results. Which meant that compared with the model group, the protein expression of GSK3ß and Map2k2 of hippocampus was increased in the EA group (P<0.01, P<0.05). CONCLUSION: EA at "Sishencong" (EX-HN 1) and "Fengchi" (GB 20) could improve cognitive function in VD rats, with the mechanism involving multiple targets and pathways, potentially related to GSK3ß, Map2k2 proteins, and the mTOR and neurotrophic factor signaling pathways.

Chemical shift assignments of wildtype human leptin.

Leptin is an adipose tissue-expressed 16-kDa hormone encoded by the ob/ob gene. It serves a crucial role in regulating diverse physiological processes, including body weight control, energy homeostasis regulation, promotion of cell proliferation, and more. Emerging research has also revealed potential implications of leptin in various aging-related diseases, suggesting multifaceted physiological roles of leptin. Structural investigation of wild-type leptin in apo form is of particular importance to understand its conformational plasticity for receptor interaction and recognition. Here, we report backbone and side-chain resonance assignments of wild-type human leptin as a basis for structural and functional studies on leptin-mediated signaling.

An Integrative Disease Information Network Approach to Similar Disease Detection.

Disease similarity analysis impacts significantly in pathogenesis revealing, treatment recommending, and disease-causing genes predicting. Previous works study the disease similarity based on the semantics obtaining from biomedical ontologies (e.g., disease ontology) or the function of disease-causing molecules. However, such methods almost focus on a single perspective for obtaining disease features, which may lead to biased results for similar disease detection. To address this issue, we propose a disease information network-based integrative approach named MISSION for detecting similar diseases. By leveraging the associations between diseases and other biomedical entities, the disease information network is established first. Then, the disease similarity features extracted from the aspects of disease taxonomy, attributes, literature, and annotations are integrated into the disease information network. Finally, the top-k similar disease query is performed based on the integrative disease information. The experiments conducted on real-world datasets demonstrate that MISSION is effective and useful in similar disease detection.

Effectiveness of acupuncture for patients with vascular dementia: A systematic review and meta-analysis.

OBJECTIVES: This meta-analysis assessed the treatment effectiveness of acupuncture in patients with vascular dementia. METHODS: The PubMed, Embase, Cochrane library, and China National Knowledge Infrastructure were searched to identify eligible randomized controlled trials (RCTs). The odds ratios (ORs) and weighted mean differences (WMDs) with 95 % confidence intervals (CIs) were used to assess the pooled effect estimates using a random-effects model for categorical and continuous outcomes, respectively. RESULTS: Thirty-four RCTs (2672 patients) were selected for the final meta-analysis. The use of acupuncture showed association with an increased incidence of effective rate (OR: 3.28; 95 % CI: 2.54-4.24; P < 0.001). The pooled WMDs revealed that acupuncture was significantly associated with an improvement in the Hasegawa dementia scale (HDS) (WMD: 4.31; 95 % CI: 3.15-5.47; P < 0.001), and Mini-Mental State Examination scores (MMSE) (WMD: 3.07; 95 % CI: 2.40-3.74; P < 0.001). However, the use of acupuncture showed no association with the level of Activities of daily living (ADL) (WMD: 1.93; 95 % CI: - 2.53 to 6.38; P = 0.397). Finally, acupuncture was associated with lower levels of Scale for the differentiation of syndromes of vascular dementia (SDSVD) (WMD: - 2.15; 95 % CI: - 4.14 to - 0.16; P = 0.034), and National Institutes of Health stroke scale (NIHSS) (WMD: - 3.90; 95 % CI: - 4.87 to - 2.94; P < 0.001). CONCLUSIONS: Acupuncture is probably helpful in vascular stroke, but strong supportive data are not yet available. Acupuncture should be used cautiously, owing to the analysis of this study based on low to moderate evidence. Further high-quality, large-scale RCTs should be conducted.

Mining Similar Aspects for Gene Similarity Explanation Based on Gene Information Network.

Analysis of gene similarity not only can provide information on the understanding of the biological roles and functions of a gene, but may also reveal the relationships among various genes. In this paper, we introduce a novel idea of mining similar aspects from a gene information network, i.e., for a given gene pair, we want to know in which aspects (meta paths) they are most similar from the perspective of the gene information network. We defined a similarity metric based on the set of meta paths connecting the query genes in the gene information network and used the rank of similarity of a gene pair in a meta path set to measure the similarity significance in that aspect. A minimal set of gene meta paths where the query gene pair ranks the highest is a similar aspect, and the similar aspect of a query gene pair is far from trivial. We proposed a novel method, SCENARIO, to investigate minimal similar aspects. Our empirical study on the gene information network, constructed from six public gene-related databases, verified that our proposed method is effective, efficient, and useful.

An Ontology-Independent Representation Learning for Similar Disease Detection Based on Multi-Layer Similarity Network.

To identify similar diseases has significant implications for revealing the etiology and pathogenesis of diseases and further research in the domain of biomedicine. Currently, most methods for the measurement of disease similarity utilize either associations of ontological disease concepts or functional interactions between disease-related genes. These methods are heavily dependent on the ontology, which are not always available, and the selection of datasets. Moreover, many methods suffer from a drawback that they only use a single metric to evaluate disease similarity from an individual data source, which may result in biased conclusions without consideration of other aspects. In this study, we proposed a novel ontology-independent framework, namely RADAR, for learning representations for diseases to deduce their similarities from an integrative perspective. By leveraging the associations between diseases and disease-related biomedical entities, a disease similarity network was built under various metrics. Then, a multi-layer disease similarity network was constructed by integrating multiple disease similarity networks derived from multiple data sources, where the representation learning was derived to provide a comprehensive evaluation of disease similarities. The performance of RADAR was assessed by a benchmark disease set and 100 random disease sets. Experimental results demonstrated that RADAR can detect similar diseases effectively.

Self-assembly of tubuliform spidroins driven by hydrophobic interactions among terminal domains.

Spider silk has remarkable physical and biocompatible properties. Investigation of structure-function relationship and self-assembly process of spidroins is necessary for uncovering the mechanism of silk fiber formation. Nevertheless, how the terminal domains initiate self-assembly of soluble tubuliform spidroins to form solid eggcase silk is still not fully understood. Here we investigate the roles of both terminal domains of tubuliform spidroin 1 (TuSp1) in the silk fiber formation. We found that interactions among the terminal domains drive rapid TuSp1 self-assembly and fiber formation, which is insensitive to pH changes from 6.0 to 7.0. These interactions also contribute to the spidroin chain alignment in fiber formation upon shear-force exposure. Structural analysis and site-directed mutagenesis identified eight critical surface-exposed residues involved in hydrophobic interactions among terminal domains. Spidroins with single-point mutations of these residues fail to form intermediate micelle-like structures. The structural docking model indicates that multiple terminal domains of TuSp1 may interact with each other based on hydrophobic interactions and surface complementarity, which may lead to forming the surface of the micelle-like structure. Our results provide new insights into the structural mechanism of eggcase silk formation and the basis for designing and producing novel biomaterials derived from spider eggcase silk.