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We commend Cao et al. for their systematic review demonstrating the efficacy of intra-articular mesenchymal stem cell (MSC) therapy in alleviating pain and improving function in patients with non-surgical knee osteoarthritis (OA). However, we reanalyzed their subgroup analyses to evaluate the methodological implications of statistical model selection (fixed-effect vs. random-effect models) on result reliability. In dose-stratified analyses, Cao et al. applied fixed-effect models to low-dose (I 2  = 0%) and high-dose (I 2  = 80%) MSC subgroups. Upon reanalysis using random-effect models, the high-dose group showed no statistically significant differences in Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) total scores compared to the control group at 6 months [MD = 8.75; 95% CI (−2.10, 19.61); P = 0.11] or 12 months [MD = 12.68; 95% CI (−4.96, 30.32); P = 0.16], contrasting with Cao et al.’s original findings. The low-dose subgroup, with no heterogeneity, yielded identical results across both models. Similarly, in cell-source stratification (adipose-derived MSCs [ADMSCs] vs. bone marrow-derived MSCs [BM-MSCs]), reanalysis of ADMSCs using random-effect models demonstrated significant 6-month WOMAC improvement [MD = 9.32; 95% CI (3.73, 14.92); P = 0.001] but non-significant 12-month differences [MD = 12.90; 95% CI (−1.76, 27.55); P = 0.08], diverging from Cao et al.’s conclusions. BM-MSCs results remained consistent due to negligible heterogeneity (I 2  = 0%). These findings underscore that fixed-effect models artificially narrow confidence intervals in heterogeneous populations, overestimating clinical significance. Our results align with Cochrane guidelines, emphasizing that random-effect models better accommodate inter-study diversity, yielding conservative and clinically generalizable estimates. This critique reinforces the necessity of transparent statistical model selection in meta-analyses, particularly when subgroup heterogeneity may influence therapeutic interpretations.

The recent article by Wen et al., published in PLOS ONE, titled “ Effects of neuraxial anesthesia in sitting and lateral positions on maternal hemodynamics in cesarean section: A systematic review and meta-analysis ,” caught my attention. In their study, the authors observed the effects of neuraxial anesthesia in sitting and lateral positions on maternal hemodynamics during cesarean section. Given the anatomical differences between the left and right sides of the body, which could result in differences in maternal hemodynamics and vasopressor requirements during neuraxial anesthesia for cesarean delivery, I was intrigued by the idea of further dividing the lateral position data from Wen et al.'s study into three subgroups: “left lateral position,” “right lateral position,” and “not mentioned” (where the included original study did not mention the lateral position) for a subgroup analysis. It seems to be more rigorous, the subgroup analysis revealed that the usage rate of ephedrine support was 1.42 times higher for parturients in the right lateral position compared to those in the sitting position. This finding supports our recommendation to distinguish between left and right lateral decubitus positioning in neuraxial anesthesia for cesarean delivery. But in contrast, no significant difference was observed between the sitting and lateral positions in terms of the number of parturients requiring ephedrine in Wen et al.'s. Given the limited research on the right-lateral position and its hemodynamic effects, further studies are needed to explore its clinical applications. Future research should also focus on conducting larger trials with greater sample sizes to evaluate the long-term neonatal outcomes associated with varying maternal positions. Additionally, researchers should conduct subgroup analyses that separate the left- and right-lateral positions to provide clearer guidance for anesthesiologists.

The cultural landscape in traditional settlements is an important historical and cultural resource created by human beings in the process of historical evolution, and is an important resource for the development of traditional settlement tourism. This paper selected 21 representative traditional settlements for research using online comments from tourists as data and content analytical methods including high-frequency vocabulary, semantic networks and emotional attitudes to explore the public perspective on the connotations of cultural landscape features in traditional settlements. There are four major findings, showing first that the cultural landscape of traditional settlements contains three core elements. Second, the semantic network relationships of the core elements show a significant central–edge tendency; and third, the emotional perception of cultural landscapes in traditional settlements is generally positive, and there is no significant difference emotionally between each core element. Last, the public’s perception of the cultural connotations of the landscape is seriously insufficient. Based on the research results, planning suggestions and countermeasures for the conservation and utilization of cultural landscapes in traditional settlements are proposed.

Composed of obesity and lipid parameters, the cardiometabolic index (CMI) has emerged as a novel diagnostic tool. Originally developed for diabetes diagnosis, its application has expanded to identifying patients with cardiovascular diseases, such as atherosclerosis and hypertension. However, the relationship between CMI and non-alcoholic fatty liver disease (NAFLD) and liver fibrosis in the US population remains unclear. This cross-sectional study analyzed data from the National Health and Nutrition Examination Survey (NHANES) spanning 2017–2020, involving 2996 participants aged 20 years or older. Vibration controlled transient elastography using a FibroScan® system (model 502, V2 Touch) with controlled attenuation parameter measurements identified NAFLD at a threshold of ≥ 274 dB/m, while liver stiffness measurement (LSM) results (median, ≥ 8.2 kPa) indicated fibrosis. A multifactorial logistic regression model explored the relationship between CMI and NAFLD and fibrosis. The effectiveness of CMI in detecting NAFLD and liver fibrosis was assessed through receiver operating characteristic curve analysis. Controlling for potential confounders, CMI showed a significant positive association with NAFLD (adjusted OR = 1.44, 95% CI 1.44–1.45) and liver fibrosis (adjusted OR = 1.84, 95% CI 1.84–1.85). The Areas Under the Curve for predicting NAFLD and fibrosis were 0.762 (95% CI 0.745 ~ 0.779) and 0.664(95% CI 0.633 ~ 0.696), respectively, with optimal cut-off values of 0.462 and 0.527. There is a positive correlation between CMI and NAFLD and fibrosis, which is a suitable and simple predictor of NAFLD and fibrosis.

The platelet/high-density lipoprotein ratio (PHR) has been identified as a significant indicator of inflammation and a hypercoagulable state, demonstrating a strong link with the severity of nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome (MetS). However, its correlation with hyperuricemia has not yet been documented. This study utilized a cross-sectional design, analyzing data collected from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2016 in the United States. The platelet/high-density lipoprotein ratio (PHR) was determined by dividing the number of platelets (PLT) by the level of high-density lipoprotein cholesterol (HDL-C). We employed multivariable logistic regression analyses, generalized additive models, and subgroup analyses to investigate the correlation between PHR and hyperuricemia. The study revealed a hyperuricemia prevalence of 18.56%. Analysis indicated a significant positive correlation between PHR and the risk of hyperuricemia (OR 1.11, 95% CI 1.08, 1.14). This correlation remained consistent across different subgroups including age, ethnicity, gender, and body mass index (BMI). Smooth curve fitting demonstrated a saturation effect between PHR and the risk of hyperuricemia. PHR is positively correlated with hyperuricemia and may serve as a novel biomarker for predicting the onset of this condition. Additionally, targeted interventions to improve PHR might help reduce the incidence of hyperuricemia.

This study presents comprehensive numerical and experimental investigation into the optimal design of rock bolts in single-lining tunnel support for expressway tunnels. Focusing on key design parameters, including anchorage length, bolt diameter, spacing, surrounding rock grade, and bolt type, the research explores their influence on tunnel stability. The study employs finite element simulations to analyze the distribution of axial force ( P u ), surrounding rock stress ( s u ), and displacement ( d u ). Experimental testing under varying conditions is used to validate the numerical results. The findings reveal that an anchorage length of approximately 2.5 m, a bolt diameter of 28 mm, and an anchorage spacing of 1.0 m offer the best performance for grade III rock conditions. Moreover, self-drilling hollow grouting bolts (SHGB) outperform expansion shell bolts (ESB) in terms of axial force capacity and deformation control. The study concludes by providing practical recommendations for the design of rock bolts in single-lining expressway tunnels, aiming to enhance both safety and cost-effectiveness in tunnel construction.

The primary goal of protein science is to understand how proteins function, which requires understanding the functional dynamics responsible for transitions between different functional structures of a protein. A central concept is the exact reaction coordinates that can determine the value of committor for any protein configuration, which provide the optimal description of functional dynamics. Despite intensive efforts, identifying the exact reaction coordinates (RCs) in complex molecules remains a formidable challenge. Using the recently developed generalized work functional, we report the discovery of the exact RCs for an important functional process—the flap opening of HIV-1 protease. Our results show that this process has six RCs, each one is a linear combination of ~240 backbone dihedrals, providing the precise definition of collectivity and cooperativity in the functional dynamics of a protein. Applying bias potentials along each RC can accelerate flap opening by 10³ to 10⁴ folds. The success in identifying the RCs of a protein with 198 residues represents a significant progress beyond that of the alanine dipeptide, currently the only other complex molecule for which the exact RCs for its conformational changes are known. Our results suggest that the generalized work functional (GWF) might be the fundamental operator of mechanics that controls protein dynamics.

Asymptomatic or symptomatic infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can be followed by reinfection. The protection conferred by prior infection among coronavirus disease 2019 (COVID-19) patients is unclear. We assessed the incidence of SARS-CoV-2 reinfection and the protection effect of previous infection against reinfection. We searched PubMed, EMBASE, Cochrane, Scopus, Web of Science, and ClinicalTrials.gov for publications up until the end date of May 1, 2021. The reinfection rate of recovered patients and the protection against reinfection were analyzed using meta-analysis. Overall, 19 studies of 1096 reinfection patients were included. The pooled reinfection rate was 0.65% (95% confidence interval [CI] 0.39-0.98%). The symptomatic reinfection rate was a bit lower (0.37% [95% CI 0.11-0.78%], I2 = 99%). The reinfection rate was much higher in high-risk populations (1.59% [95% CI 0.30-3.88%], I2 = 90%). The protection against reinfection and symptomatic reinfection was similar (87.02% [95% CI 83.22-89.96%] and 87.17% [95% CI 83.09-90.26%], respectively). The rate of reinfection with SARS-CoV-2 is relatively low. The protection against SARS-CoV-2 after natural infection is comparable to that estimated for vaccine efficacy. These data may help guide public health measures and vaccination strategies in response to the COVID-19 pandemic. High-quality clinical studies are needed to establish the relevant risk factors in recovered patients.