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Background Salpingitis is a leading cause of female infertility and ectopic pregnancy worldwide. Despite advances in reproductive medicine, its early diagnosis and effective prevention of long-term sequelae remain challenging due to its often silent clinical course and complex pathogenesis. Objective This review synthesizes current knowledge on the infectious, immunological, and molecular mechanisms underlying salpingitis, with an emphasis on diagnostic limitations and therapeutic challenges. Methods A comprehensive evaluation of recent literature was conducted focusing on pathogen-induced inflammation, host immune responses, molecular signaling pathways, and emerging diagnostic and therapeutic strategies, including omics-based biomarkers and molecular imaging approaches. Results Persistent inflammation, cytokine imbalance, and oxidative stress contribute to tubal scarring and ciliary dysfunction, ultimately leading to reproductive failure. While antibiotics are effective in treating acute infection, they do not prevent chronic complications. Advances in molecular diagnostics and non-invasive imaging show promise for early detection, although biomarker validation remains a major limitation. Rising antimicrobial resistance further complicates clinical management. Conclusion: Integrated approaches combining molecular diagnostics, imaging, and targeted therapies are essential to bridge laboratory research and clinical practice. Standardized diagnostic criteria, validated biomarkers, and improved reproductive health equity are critical to reducing the global burden of salpingitis.

In Wireless Body Area Networks (BAN), energy consumption, energy harvesting, and data communication are the three most important issues. In this paper, we develop an optimal allocation algorithm (OAA) for sensor devices, which are carried by or implanted in human body, harvest energy from their surroundings, and are powered by batteries. Based on the optimal allocation algorithm that uses a two-timescale Lyapunov optimization approach, we design a framework for joint optimization of network service cost and network utility to study energy, communication, and allocation management at the network edge. Then, we formulate the utility maximization problem of network service cost management based on the framework. Specifically, we use OAA, which does not require prior knowledge of energy harvesting to decompose the problem into three subproblems: battery management, data collection amount control and transmission energy consumption control. We solve these through OAA to achieve three main goals: (1) balancing the cost of energy consumption and the cost of data transmission on the premise of minimizing the service cost of the devices; (2) keeping the balance of energy consumption and energy collection under the condition of stable queue; and (3) maximizing network utility of the device. The simulation results show that the proposed algorithm can actually optimize the network performance.

Infertility affects 1 in 6 people of reproductive age and remains difficult to treat because causes are heterogeneous and diagnostics are incomplete. Recent evidence reframes the female reproductive tract as a low‐biomass but biologically active microbial ecosystem. Dysbiosis, typically loss of protective Lactobacillus species (notably L. crispatus) with overgrowth of anaerobic pathobionts, is associated with implantation failure and recurrent pregnancy loss. Framing conditions such as chronic endometritis and reproducible low‐Lactobacillus endometrial profiles as dysbiosis‐related disorders clarifies opportunities for prevention, companion diagnostics and microbiome‐directed therapies. This narrative review contrasts receptive (Lactobacillus‐dominant) versus dysbiotic states and summarises mechanisms linking microbiota to fertility: microbial metabolites (lactic acid, short‐chain fatty acids) support epithelial barrier function and immune tolerance, whereas dysbiosis provokes inflammation that impairs implantation. Although observational data consistently associate Lactobacillus dominance with better outcomes, evidence quality is low‐to‐moderate due to retrospective designs, methodological heterogeneity, and a lack of adequately powered, diagnostic‐stratified randomised trials. The review highlights precision microbial therapeutics under development, single‐strain next‐generation probiotics, synthetic consortia, engineered live biotherapeutics, postbiotics, targeted phage/endolysins and vaginal microbiota transplantation, and proposes a diagnostic‐driven roadmap that matches microbiome endotypes and clinical contexts (e.g., preconception vs. immediate embryo transfer) to specific interventions. Regulatory and safety issues for reproductive biologics are also considered. The reproductive microbiome is a promising translational frontier but currently offers a consistent signal rather than definitive proof of benefit. To translate promise into practice requires standardised low‐biomass sampling/reporting, mechanistic validation in human‐relevant models and diagnostic‐stratified randomised trials with staged endpoints, alongside strategies to address engraftment, formulation and regulatory pathways. Major reproductive‐tract microbiome endotypes and their clinical associations. L. crispatus dominance supports acidification and immune tolerance conducive to implantation. L. iners dominance represents an unstable state linked to bacterial vaginosis and reduced implantation. Anaerobe‐dominant and pathobiont‐enriched states induce inflammation and immune imbalance, leading to implantation failure and recurrent loss.

The nodes in the opportunistic network make up communities according to the relevance between them. Some of the structural characteristics of an opportunistic network can be reflected by the structure of the communities that exist in the network. Therefore, finding community from the network is of great significance for people to better study, use, and transform the network. The overlap of communities is considered to be an important feature of communities. Almost all community discovery algorithms were based on nonoverlapping communities in the past. A node in a nonoverlapping community belongs to only one community. However, there are overlapping and interrelated characteristics between communities, so it is not in line with the actual environment of the network. As a result, the previous algorithms have many shortcomings in the face of practical application scenarios, coupled with the limitation of the computing capacity of mobile devices; data transmission for low delay and the low energy consumption is difficult to meet the requirements. In the study, we formulate the problem of dividing nodes into several communities in the opportunistic social network as how to build communities dynamically according to weight distribution. Then, we propose a modified data delivery strategy based on stochastic block model and community detection (DDBSC). The simulation results show that, compared with other algorithms in the experiments, the strategy proposed in this paper exhibits good performance in terms of overhead, energy consumption, and delivery rate.

Ammonia gas sensors were fabricated from polyaniline nanofibers, which were synthesized by a simple dilute polymerization method without external template. The films of polyaniline nanofibers were deposited on interdigitated array electrodes by drop casting method. The ammonia gas sensing mechanism arises from the deprotonation process of acid doped polyaniline. The sensors exhibited the sensitivity of 1.06 and response time of 10 s for 50 ppm of ammonia gas. Such high sensitivity and fast response are attributed to the large surface-to-volume ratio and interconnected network structures. These results suggest that polyaniline nanofibers are promising materials for ammonia gas sensors with high performance.

Billions of people around the world send and receive data over online networks daily. Sufficient and redundant data are transmitted over social platforms with AI-assisted in 5G networks. In opportunistic social networks, the main challenge faced by traditional methods is that numerous user nodes participate in data transmission, causing a lot of message copy redundancy and node cache consumption. As a result, the transmission delay of the algorithm is high, the node energy consumption is too large, and even information is lost. To solve these problems, this study establishes an artificial intelligence-based optimization multiple evaluation method. The main purpose of this method is to avoid information loss caused by data loss when reducing data noise, reasonably select communication nodes in opportunistic social network scenarios, optimize data transmission performance, and avoid network congestion. Moreover, our method can effectively identify and exclude potential malicious nodes, reducing the situation that packets are intercepted and discarded. The experiment confirms that the optimized transmission evaluation scheme can effectively reduce routing overheads and energy consumption of a user node, improve the delivery ratio of node data transmission, and ensure the reliability and security of data transmission.

In response to resource shortage and carbon dioxide emissions, an innovative type of sustainable concrete containing LC3, seawater, sea sand, and surface-treated recycled aggregates is proposed in this study to replace traditional concrete. To understand the bond properties between the sustainable concrete and CFRP bars, an investigation was conducted on the bond behavior between sand-coated CFRP bars and advanced sustainable concrete. Pull-out tests were carried out to reveal the failure mechanisms and performance of this bond behavior. The results showed that the slip increased monotonically along with the increase in confinement. The bond strength increased up to approximately 15 MPa, and the critical ratio of C/D was reached. The critical ratio approached 3.5 for the Portland cement groups, while the ratio was determined as approximately 4.5 when LC3 was introduced. When the proportion of LC3 reached 50%, there was a reduction in bond strength. A multisegmented modified bond–slip model was developed to describe the four-stage bond behavior. In terms of bond strength and slip, the proposed advanced concrete exhibited almost identical bond behavior to other types of concrete.

Fiber-reinforced polymer (FRP) composites have been used in various industries, thus a large amount of FRP wastes have been generated due to the out-of-service of FRP products. Recycling FRP wastes into coarse aggregates to replace natural coarse aggregates (NCA) to form the recycled FRP aggregate concrete (RFAC) is a potential approach to dispose of huge quantities of FRP wastes with low environmental impact. In this paper, waste glass FRP (GFRP) bars were cut into particles of 12 sizes to enable the grading of recycled FRP aggregate (RFA) as similar as possible to that of NAC. The influence of different RFA volume replacement ratios (0%, 30%, 50%, 70%, 100%) on the compressive performance of RFAC was investigated based on uniaxial compression tests of 15 standard cylinders. The results showed that the failure mode of RFAC was different from that of NAC. As the RFA replacement ratio increased, the compressive strength and elastic modulus of the RFAC gradually decreased, but its post-peak brittleness was significantly mitigated compared to NAC. The Poisson’s ratio of RFAC increased with the increase in the RGFA replacement ratio at the elastic stage and was smaller than that of NCA concrete. Both the existing stress–strain models developed for NAC and recycled aggregate concrete (RAC) were found not fit for the RFAC. Thus, a new stress–strain model that was applicable to RFAC was developed by modifying the classical existing model, and a good agreement between the model predictions and test data was reached.

Introductin and hypothesisMixed urinary incontinence (MUI) comprises a combination of urgency and stress. The efficacy and safety of electroacupuncture (EA) for the treatment of MUI remain unclear.ObjectiveTo assess the efficacy and safety of EA in treating MUI.MethodsWe searched PubMed, CENTRAL, Embase, Web of Science, four Chinese databases, clinical research registration platforms, grey literature, and the reference lists of the selected studies. Risk of bias and quality were evaluated using the Revman 5.4 and Jadad scores. Meta-analysis was performed using Stata 15.1 software. Trial sequential analysis (TSA) was used to assess the stability of the results.ResultsEight randomized controlled trials comprising 847 patients were included. The meta-analysis results showed that compared with antimuscarinic drugs plus pelvic floor muscle training, EA resulted in significantly less pad weight on the 1-h pad test and statistically significantly lower severity scores on the International Consultation on Incontinence Questionnaire Short Form. The change in the 72-h incontinence episode frequency difference was not statistically significant, and there was no outcome of overall response rate and quality of life in this meta-analysis. Few adverse events occurred in the EA group. The TSA results suggested that the result of change from baseline in the 1-h pad test was stable and the evidence was conclusive.ConclusionsEA could be a potential treatment option for MUI and is relatively safe. Nevertheless, because of the limitations of this study, our conclusions should be interpreted with caution, and further studies are needed to confirm the comprehensive clinical efficacy and placebo effect of EA.

The limitations of protein-based hydrogels, including their insufficient mechanical properties and restricted biological functions, arise from the highly specific functions of proteins as natural building blocks. A potential solution to overcome these shortcomings is the development of protein-protein hydrogels, which integrate structural and functional proteins. In this study, we introduce a protein-protein hydrogel formed by crosslinking bovine serum albumin (BSA) and a genetically engineered intrinsically disordered collagen-like protein (CLP) through Ag-S bonding. Our approach involves thiolating lysine residues of BSA and crosslinking CLP with Ag+ ions, utilizing thiolation of BSA and the free-cysteines of CLP. The resulting protein-protein hydrogels exhibit exceptional properties, including notable plasticity, inherent self-healing capabilities, and gel-sol transition in response to redox conditions. Furthermore, in comparison to standalone BSA hydrogels, these protein-protein hydrogels demonstrate remarkable antibacterial properties, enhanced cellular viability, and improved cellular migration. In vivo experiments provide conclusive evidence of accelerated wound healing, observed not only in murine models with streptozotocin (Step)-induced diabetes but also in zebrafish models subjected to UV-burn injuries. Detailed mechanistic insights, combined with assessments of pro-inflammatory cytokines and the expression of epidermal differentiation-related proteins, robustly validate the protein-protein hydrogel’s effectiveness in promoting wound repair. This pioneering approach advances the development of protein-protein hydrogels and serves as a reference for the creation of multifunctional protein-based hydrogels.