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Background Forceps-assisted vaginal delivery is prone to perineal laceration and other complications. Episiotomy decisions are often experience-dependent, leading to excessive intervention. The Perineal Evaluation Form (PEF) provides an objective basis for episiotomy, but its clinical efficacy in forceps-assisted vaginal delivery has not been fully validated. Methods A single-center retrospective cohort study was conducted on 313 parturients who underwent forceps-assisted vaginal delivery at the Third Affiliated Hospital of Zhengzhou University from January 2017 to December 2024, divided into PEF group (n=194, PEF-guided elective episiotomy) and non-PEF group (n=119, clinician-experience-based episiotomy). Maternal and neonatal outcomes were compared, and multivariate binary logistic regression identified influencing factors of episiotomy. Results The PEF group had a significantly lower episiotomy rate, a shorter second stage of labor, less postpartum 24-hour blood loss, and a lower neonatal transfer rate (all P<0.05). No significant differences were found in severe perineal laceration, other maternal complications or short-term neonatal outcomes (all P>0.05). PEF-guided episiotomy, multiparity and epidural analgesia were protective factors; Class II/III fetal heart rate (FHR) monitoring, oxytocin use and gestational diabetes mellitus (GDM) were risk factors (all P<0.05). Conclusions PEF-guided elective episiotomy is safe and effective in forceps-assisted delivery, which reduces unnecessary clinical interventions without increasing the risk of severe maternal and neonatal complications. The identified influencing factors provide an evidence-based basis for precise episiotomy decision-making.

High stress and shape deviation during the glass forming process often led to low yield rates, posing a challenge in the production of high-precision smartwatch components. To address this issue, a numerical model was developed to simulate and analyze the forming behavior of 3D curved glass. The study focused on achieving a balance between energy consumption and key quality attributes, such as residual stress and shape accuracy. Results showed that forming pressure primarily affects shape deviation, while forming temperature plays a dominant role in energy usage and residual stress. Through orthogonal experiments, optimal parameters were identified: a forming temperature of 630 °C, pressure of 0.25 MPa, and cooling rate of 0.25 °C/s effectively minimize residual stress. Meanwhile, shape deviation is minimized at 630 °C, 0.30 MPa, and a cooling rate of 0.75 °C/s. Energy efficiency analysis indicated that low efficiency occurs at 610 °C with a 3 °C/s heating rate. Furthermore, NSGA-II multi-objective optimization validated the model’s accuracy, with prediction errors under 20%, offering valuable guidance for the precise fabrication of smartwatch glass.

With the increasing interest in the application of electrochromism to flexible and wearable electronics in recent years, flexible electrochromic devices (ECDs) that can function at extreme temperatures are required. However, the functionalities of flexible ECDs are severely hampered by the inadequate choice of electrolytes, which might ultimately result in performance fading during low‐ and high‐temperature operations. Here, we develop a deep eutectic solvent (DES)‐based gel electrolyte that can maintain its optical, electrical, and mechanical properties over a wide range of temperatures (−40 to 150°C), exhibiting an extremely high visible‐range transmittance over 90%, ion conductivity of 0.63 mS cm−1, and fracture strain exceeding 2000%. Owing to the excellent processability of the DES‐based electrolytes, provided by dynamic interactions such as the lithium and hydrogen bonding between the DES and polymer matrix, a directly written patterning in ECDs is realized for the first time. The fabricated ECDs exhibit an excellent electrochromic behavior superior to the behavior of the ECDs fabricated with traditional gel electrolytes. The introduction of such DES‐based electrolytes is expected to pave the way for a widespread application of electrochromic products. The gel electrolyte constructed with deep eutectic solvent (DES) and acrylate‐based copolymer enables a direct writing electrolyte layer for patterning in flexible electrochromic devices (ECDs), which can maintain its excellent optical transparency, electrical, and mechanical properties over a wide span of temperature ranging from −40 to 150°C.

Acute kidney injury (AKI) affects 40-50% of septic patients, with limited prevention options. This study investigates the relationship between early ampicillin administration and severe AKI in septic patients. A retrospective cohort study using the MIMIC-IV database (2008-2019) was conducted. The primary outcome was severe AKI, and secondary outcomes included continuous renal replacement therapy, in-hospital death, and any-stage AKI. Propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) were used to adjust for confounders. Multivariate regression explored the association between ampicillin and severe AKI incidence, and subgroup analyses were performed. A total of 17,676 septic patients were included, with 915 matched pairs after PSM. Ampicillin administration was associated with a reduced risk of severe AKI (OR = 0.78; 95% CI 0.68-0.90) in multivariable logistic regression, PSM (OR = 0.74; 95% CI 0.61-0.92), and IPTW (OR = 0.77; 95% CI 0.74-0.81). Incidence of acute kidney disease was lower in the ampicillin group (OR = 0.77; 95% CI 0.61-0.97). Mortality rates at 30 and 90 days were also lower (HR = 0.69; 95% CI 0.55-0.86 and OR = 0.67; 95% CI 0.55-0.82). The protective effect was more pronounced in female and older patients. Early ampicillin administration within 48 h of ICU admission is associated with reduced severe AKI and improved short-term renal outcomes in septic patients. Further studies are needed to confirm these findings.

Objectives Observational studies indicated a controversial relationship between periodontitis (PD) and Sjogren’s syndrome (SS). To overcome restrictions in conventional observational studies, we conducted a two-sample Mendelian randomization (MR) analysis to assess the potential bidirectional relationship between PD and SS. Methods We utilized the largest available genome-wide association study (GWAS) of European ancestry on both PD (17,353 cases-28,210 controls) and SS (2495 cases-365,533 controls) for MR genetic instrument selection. The random-effect inverse-variance weighted (IVW) method complemented by Causal Analysis Using Summary Effect (CAUSE), weighted median, weighted mode, simple mode, MR-Egger regression, and MR-pleiotropy residual sum and outlier (MR-PRESSO) was used for MR analysis. Subsequent pleiotropy and heterogeneity tests were conducted. Results IVW analysis exhibited neither an effect of PD on SS (OR = 0.939, 95%CI = 0.525–1.677, P  = 0.8304) nor that of SS on PD (OR = 1.007, 95%CI = 0.977–1.038, P  = 0.6440). The other five complementary methods further recognized the null association with an effect size close to one. No significant pleiotropy was detected in the relationship between PD and SS ( P  > 0.05). Heterogeneity existed in the effect of PD on SS but not vice versa. Conclusions No genetic causality between PD and SS or vice versa was supported by our results under MR assumptions and limitations. The study results provided new insights into the relationship between periodontal status and sjogren’s syndrome, highlighting the need for a more prudent medical intervention.

Seagrass beds are among the most productive and ecologically valuable coastal ecosystems. However, temperate nearshore seagrass beds exposed to urban stressors remain understudied. From 2020 to 2024, this study investigated seagrass communities, environmental factors, and benthic macrofauna in Qingdao’s coastal bays (Qingdao Bay, Huiquan Bay and Tangdao Bay) using field sampling and remote sensing. Redundancy analysis (RDA), Spearman correlation, and PERMANOVA were applied to clarify the ecological response relationships among these components. Results revealed significant spatiotemporal variations: Qingdao Bay experienced severe degradation with an 88% decline in belowground biomass. Huiquan Bay showed shoot height increases but ecological instability, while Tangdao Bay maintained relatively stable conditions. Mollusks dominated Qingdao Bay (67.4%), whereas annelids were prevalent in Huiquan Bay (51.8%) and Tangdao Bay (69.6%). Tangdao Bay supported the most complex and stable benthic communities. Water depth acted as a stressor to seagrass growth, while the role of dissolved oxygen and salinity was complex, exhibiting context-dependent relationships with seagrass parameters. Dissolved inorganic nitrogen and reactive phosphate were shared positive drivers for both seagrasses and macrofauna. This study conclusively links specific environmental drivers to seagrass ecosystem dynamics, delivering essential insights for effective ecological management and restoration strategies.

In recent years, metal nanomaterials and nanoproducts have been developed intensively, and they are now widely applied across various sectors, including energy, aerospace, agriculture, industry, and biomedicine. However, nanomaterials have been identified as potentially toxic, with the toxicity of metal nanoparticles posing significant risks to both human health and the environment. Therefore, the toxicological risk assessment of metal nanomaterials is essential to identify and mitigate potential adverse effects. This review provides a comprehensive analysis of the safety and sustainability of metallic nanoparticles (such as Au NPs, Ag NPs, etc.) in key domains such as medicine, energy, and environmental protection. Using a dual-perspective analysis approach, it highlights the unique advantages of machine learning in data processing, predictive modeling, and optimization. At the same time, it underscores the importance of traditional methods, particularly their ability to offer greater interpretability and more intuitive results in specific contexts. Finally, a comparative analysis of traditional methods and machine learning techniques for detecting the toxicity of metal nanomaterials is presented, emphasizing the key challenges that need to be addressed in future research.

Glaesserella parasuis (G. parasuis) causes serious inflammation and meningitis in piglets. Quercetin has anti-inflammatory and anti-bacterial activities; however, whether quercetin can alleviate brain inflammation and provide protective effects during G. parasuis infection has not been studied. Here, we established a mouse model of G. parasuis infection in vivo and in vitro to investigate transcriptome changes in the mouse cerebrum and determine the protective effects of quercetin on brain inflammation and blood–brain barrier (BBB) integrity during G. parasuis infection. The results showed that G. parasuis induced brain inflammation, destroyed BBB integrity, and suppressed PI3K/Akt/Erk signaling-pathway activation in mice. Quercetin decreased the expression of inflammatory cytokines (Il-18, Il-6, Il-8, and Tnf-α) and BBB-permeability marker genes (Mmp9, Vegf, Ang-2, and Et-1), increased the expression of angiogenetic genes (Sema4D and PlexinB1), reduced G. parasuis-induced tight junction disruption, and reactivated G. parasuis-induced suppression of the PI3K/Akt/Erk signaling pathway in vitro. Thus, we concluded that quercetin may protect BBB integrity via the PI3K/Akt/Erk signaling pathway during G. parasuis infection. This was the first attempt to explore the protective effects of quercetin on brain inflammation and BBB integrity in a G. parasuis-infected mouse model. Our findings indicated that quercetin is a promising natural agent for the prevention and treatment of G. parasuis infection.

Glomerular hyperfiltration (GHF) has been widely recognized as a potential risk factor. However, current evidence regarding both its precise definition and clinical prognostic value remains inconclusive. We systematically searched PubMed, Embase, and the Cochrane Library, as well as reference lists of relevant articles. Cohort studies examining the association between eGFR-defined GHF and clinical outcomes were included, and meta-analyses were conducted using a random-effects model. Cross-sectional studies and data from the National Health and Nutrition Examination Survey (NHANES) were used to estimate and compare the 95th percentile of eGFR in healthy populations in China and the United States. The 95th percentile eGFR values among healthy individuals ranged from 94.7 to 146.7 mL/min/1.73 m . A total of 17 studies, including 11,563,332 participants, were included in the systematic review. GHF was significantly associated with an increased risk of all-cause mortality (HR, 1.30; 95% CI, 1.18-1.42) and incident albuminuria (HR, 1.43; 95% CI, 1.05-1.93) but was not significantly associated with cardiovascular disease. In addition, individual studies suggested potential associations between GHF and rapid eGFR decline, the incident dementia, and the incident non-alcoholic fatty liver disease. Although eGFR is subject to measurement biases in non-CKD populations, extremely high values may still indicate underlying risks not captured by routine monitoring. This study provides reference values for the 95th percentile of eGFR in the general Chinese and American populations and underscores the need to validate individualized definitions of GHF. Given the limited and heterogeneous evidence base, these findings should be interpreted cautiously, and further prospective studies are needed to clarify the clinical significance of GHF. INPLASY 202540039.

The heating system is an essential component of the glass molding process. It is responsible for heating the glass to an appropriate temperature, allowing it to soften and be easily molded. However, the energy consumption of the heating system becomes particularly significant in large-scale production. This study utilized G-11 glass for the simulation analysis and developed a finite element model for the thermal conduction of a 3D ultra-thin glass molding system, as well as a thermal bending model for smartwatches. Using finite element software, the heat transfer between the mold and the glass was modeled, and the temperature distribution and thermal stress under various processing conditions were predicted. The findings of the simulation, when subjected to a numerical analysis, showed that heating rate techniques significantly affect energy consumption. This study devised a total of four heating strategies. Upon comparison, optimizing with heating strategy 4, which applies an initial heating rate of 35 mJ/(mm2·s) during the initial phase (0 to 60 s) and subsequently escalates to 45 mJ/(mm2·s) during the second phase (60 to 160 s), resulted in a reduction of 4.396% in the system’s thermal output and a notable decrease of 7.875% in the heating duration, respectively. Furthermore, a single-factor research method was employed to study the forming process parameters. By comparing the numerical simulation results, it was found that within the temperature range of 615–625 °C, a molding pressure of 25–35 MPa, a heating rate of 1.5–2.5 °C/s, a cooling rate of 0.5–1 °C/s, and a pulse pressure of 45–55 Hz, the influence on residual stress and shape deviation in the glass was minimal. The relative error range was within the 20% acceptable limit, according to the experimental validation, which offered crucial direction and ideas for process development.