Risk prediction models for postoperative pulmonary complications (PPCs) can assist healthcare professionals in assessing the likelihood of PPCs occurring after surgery, thereby supporting rapid decision-making. This study evaluated the merits, limitations, and challenges of these models, focusing on model types, construction methods, performance, and clinical applications. The findings indicate that current risk prediction models for PPCs following lung cancer surgery demonstrate a certain level of predictive effectiveness. However, there are notable deficiencies in study design, clinical implementation, and reporting transparency. Future research should prioritize large-scale, prospective, multi-center studies that utilize multiomics approaches to ensure robust data for accurate predictions, ultimately facilitating clinical translation, adoption, and promotion.

OBJECTIVE: To explore the association between acupuncture during controlled ovarian hyperstimulation (COH) and the live birth rate (LBR) using different propensity score methods. METHODS: In this retrospective cohort study, eligible women who underwent a COH were divided into acupuncture and non-acupuncture groups. The primary outcome was LBR, as determined by propensity score matching (PSM). LBR was defined as the delivery of one or more living infants that reached a gestational age over 28 weeks after embryo transfer. The propensity score model encompassed 16 confounding variables. To validate the results, sensitivity analyses were conducted using three additional propensity score methods: propensity score adjustment, inverse probability weighting (IPW), and IPW with a "doubly robust" estimator. RESULTS: The primary cohort encompassed 9751 patients (1830 [18.76%] in the acupuncture group and 7921 [81.23%] in the non-acupuncture group). Following 1:1 PSM, a higher LBR was found in the acupuncture cohort (41.4% [755/1824] vs 36.4% [664/1824], with an odds ratio of 1.23 [95% confidence interval, 1.08-1.41]). Three additional propensity score methods produced essentially similar results. The risk of serious adverse events did not significantly differ between the two groups. CONCLUSION This retrospective study revealed an association between acupuncture and an increased LBR among patients undergoing COH, and that acupuncture is a safe and valuable treatment option. Please cite this article as: Zheng XY, Jiang ZY, Li YT, Li CL, Zhu H, Yu Z, Yu SY, Yang LL, Tang SY, Lü XY, Liang FR, Yang J. Association between acupuncture and live birth rates after fresh embryo transfer: A cohort study based on different propensity score methods. J Integr Med. 2025; 23(5):528-536.
Humans ; Female ; Propensity Score ; Embryo Transfer ; Adult ; Acupuncture Therapy ; Retrospective Studies ; Pregnancy ; Live Birth ; Birth Rate ; Cohort Studies

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

OBJECTIVE: To reveal the effects and potential mechanisms by which synaptic vesicle glycoprotein 2A (SV2A) influences the distribution of amyloid precursor protein (APP) in the trans-Golgi network (TGN), endolysosomal system, and cell membranes and to reveal the effects of SV2A on APP amyloid degradation. METHODS: Colocalization analysis of APP with specific tagged proteins in the TGN, ensolysosomal system, and cell membrane was performed to explore the effects of SV2A on the intracellular transport of APP. APP, β-site amyloid precursor protein cleaving enzyme 1 (BACE1) expressions, and APP cleavage products levels were investigated to observe the effects of SV2A on APP amyloidogenic processing. RESULTS: APP localization was reduced in the TGN, early endosomes, late endosomes, and lysosomes, whereas it was increased in the recycling endosomes and cell membrane of SV2A-overexpressed neurons. Moreover, Arl5b (ADP-ribosylation factor 5b), a protein responsible for transporting APP from the TGN to early endosomes, was upregulated by SV2A. SV2A overexpression also decreased APP transport from the cell membrane to early endosomes by downregulating APP endocytosis. In addition, products of APP amyloid degradation, including sAPPβ, Aβ _1-42, and Aβ _1-40, were decreased in SV2A-overexpressed cells. CONCLUSION These results demonstrated that SV2A promotes APP transport from the TGN to early endosomes by upregulating Arl5b and promoting APP transport from early endosomes to recycling endosomes-cell membrane pathway, which slows APP amyloid degradation.
Amyloid beta-Protein Precursor/genetics* ; Membrane Glycoproteins/genetics* ; Animals ; Protein Transport ; Nerve Tissue Proteins/genetics* ; Humans ; Mice ; Endosomes/metabolism* ; trans-Golgi Network/metabolism*

Purpose: Coronavirus disease 2019 (COVID-19) infection may affect serum hormones levels and male sexual function. This study aims to provide evidence for the causal relationship between COVID-19 infection, serum testosterone levels and the risk of erectile dysfunction (ED) using a two-sample Mendelian randomization (MR) approach. Materials and Methods: Summary-level data for serum testosterone levels (199,569 samples and 12,321,875 single nucleotide polymorphisms [SNPs]) were obtained from Rebecca’s study, while data for ED (6,175 cases and 217,630 controls) were sourced from Bovijn’s study. Genetic variations linked to COVID-19 were used as instrumental variables (IVs) in meta-analyses of genome-wide association studies (GWASs) involving 6,406 cases and 902,088 controls from the COVID-19 Host Genetics Initiative.The inverse-variance weighted (IVW) method was primarily employed to evaluate the potential associations between COVID-19 infection, serum testosterone levels, and the risk of ED. The weighted mode, weighted-median and simple-median method were employed to evaluate the sensitivity. Heterogeneity and pleiotropic outlier were assessed using Cochran’s Q test and MREgger regression. Results: The MR analysis demonstrated that COVID-19 infection was associated with reduced serum testosterone levels (odds ratio [OR] 0.966, 95% confidence interval [CI] 0.938–0.993, p=0.016) and an increased risk of ED (OR 1.205, 95% CI 1.063–1.367, p=0.004) when using IVW methods. Sensitivity analyses utilizing various IV sets and MR approach remained consistent. Conclusions COVID-19 infection is associated with a decrease in serum testosterone levels and an increased risk of ED. Male patients recovering from COVID-19 need to pay special attention to their sex hormone levels and sexual health.

Objective:To analyze the prospective associations between liver biomarkers and mortality among Chinese middle-aged and elderly populations and to evaluate the mortality risk predictive value.Methods:A total of 22 758 participants from the 3 rd resurvey of the China Kadoorie Biobank were included. Cox proportional hazard models were used to analyze the prospective associations of 5 liver biomarkers with mortality. These liver biomarkers included two liver imaging biomarkers (liver fat attenuation parameter, liver stiffness measurement) and three serum liver enzyme biomarkers [gamma-glutamyl transferase (GGT), ALT, and AST]. Restricted cubic spline was used to assess the nonlinear associations between biomarkers and mortality. The area used the receiver operating characteristic curve (AUC) to evaluate the predictive ability of the models after incorporating liver biomarkers into traditional prediction models for mortality. Results:The mean age of the participants was (65.2±9.1) years, with a median follow-up of 1.5 years, during which 307 deaths occurred. Compared to individuals without hepatic steatosis, those with severe hepatic steatosis had a 79% higher risk of mortality, with a HR of 1.79 (95% CI: 1.06-3.03). Compared to individuals without hepatic fibrosis, those with advanced fibrosis and cirrhosis had higher mortality risks of 48% and 91%, respectively (both P<0.05). For each standard deviation increase in GGT, the mortality risk increased by 10% ( HR=1.10, 95% CI: 1.05-1.15), with the positive association plateauing at higher GGT levels. AST exhibited a U-shaped association with mortality risk. The AUC of the prediction model adding liver biomarkers into traditional prediction factors was 0.718 (95% CI: 0.679-0.757), with an increase of 0.030 ( P<0.001) compared with the traditional model. Conclusions:Severe hepatic steatosis, higher levels of hepatic fibrosis, and elevated GGT levels are significantly associated with higher mortality risk. AST shows a U-shaped nonlinear association with mortality risk. Incorporating liver biomarkers into traditional risk prediction models enhance the ability to predict mortality.

Objective:To investigate the prospective associations between plasma metabolites and the risks of all-cause and cause-specific mortality among Chinese adults.Methods:This study analyzed plasma metabolomics data from 2 183 healthy adults in the China Kadoorie Biobank (CKB), measured using targeted mass spectrometry. Cox proportional hazards regression models were used to examine the associations between 630 metabolites and the risk of all-cause mortality. Cause-specific hazard regression models evaluated the associations between metabolites and cardiovascular disease (CVD) risks, cancer, and other-cause mortality. Stepwise regression was used to identify key metabolites independently associated with all-cause mortality, and the area under the receiver operating characteristic curve (AUC) was calculated to assess the improvement in predictive performance when these metabolites were added to traditional risk prediction models.Results:The mean age of the participants was (53.2±9.8) years, 65.1% of whom were female. During a median follow-up of 14.5 years, 231 deaths occurred. A total of 44 metabolites were significantly associated with the risk of all-cause mortality [false discovery rate (FDR)-adjusted P<0.05], primarily including triglycerides, ceramides, and amino acids. Additionally, 29 and 15 metabolites were found to be associated with cancer and other-cause mortality, respectively, but no metabolites were significantly associated with CVD mortality after FDR corrections. Adding 14 metabolites independently associated with all-cause mortality into the traditional prediction model significantly improved its predictive performance. Specifically, incorporating metabolites into the traditional model, which already included laboratory biomarkers, increased the AUC to 0.798 (95% CI: 0.755-0.843), an improvement of 0.088 compared to the traditional model ( P<0.001). Conclusions:Multiple metabolites are significantly associated with mortality risk and can substantially improve the accuracy of mortality risk prediction models. These findings provide new insights into the physiological mechanisms of aging and offer valuable clues for personalized health risk assessment.

Objective:To summarize the clinical features, laboratory findings, treatment and prognosis of children confirmed as Mycoplasma pneumoniae-induced rash and mucositis (MIRM) in children. Methods:This retrospective study concluded 6 children diagnosed as MIRM in Department of Gastroenterology and Infectious Diseases, Shanghai Children′s Hospital, School of Medicine, Shanghai Jiao Tong University from August 2023 to April 2024. This paper described the characteristics of MIRM and analyzed the therapeutic strategy and prognosis.Results:A total of 6 children were diagnosed as MIRM including 2 boys and 4 girls with an age of onset was 6.4 (3.1, 7.5) years. Among the 6 patients, 4 patients had oral mucosal involvement among whom 2 showed crusting of the lips. Four patients had ocular involvement manifesting as conjunctival congestion and increased secretion. All patients presented with skin lesions, manifesting as target-shaped damage in 4 cases, herpes herpetiformis in 1 case and purpura-like rash in 1 case. Serological tests for Mycoplasma pneumoniae IgM and Mycoplasma pneumoniae nucleic acid test were positive in all 6 cases. Two cases received intravenous immunogloblin infusion combined with methylprednisolone, monotherapy of methylprednisolone in 4 cases. The course of glucocorticoids was 1-7 weeks, and the initial dose was 2-4 mg/(kg·d), which was gradually reduced according to the rash. The children were followed up for 3 to 9 months, no case suffered from long term ocular or cutaneous complications or recurrence of rash. All cases had good prognosis. Conclusions:Children diagnosed as MIRM present with mild symptoms and usually have good prognosis with early identification and appropriate intervention. Individualized therapy should be applied based on the severity of skin involvement.

Objective:To address large-scale nonlinear programming challenges in optimizing prognosis-guided intensity-modulated radiation therapy (IMRT) plans, to propose gradient-enhanced random contrastive interaction particle swarm optimization (GradRCIPSO). This gradient-enhanced swarm intelligence algorithm aims to enable global optimization of prognostic treatment plans in clinically efficient scenarios.Methods:The core concept of GradRCIPSO lied in achieving rapid global convergence by allowing particles to learn both swarm interaction and gradient information. Specifically, the interaction information was obtained from elite individuals in the swarm, enabling the particles to efficiently search the entire solution space, whereas the gradient information represents the direction of the steepest descent, enabling the particles to quickly explore the current neighborhood. To assess the effectiveness of the methodology, the IMRT plans for 10 cases of non-small cell lung cancer (NSCLC) were selected in this study. They were compared with the GradRCIPSO-generated prognosis-guided IMRT plans. Moreover, the interior-point method, sequential quadratic programming, active set, gradient descent method, and random contrastive interaction particle swarm optimization (RCIPSO) were employed as optimization engines and compared with GradRCIPSO in terms of optimization efficiency and accuracy.Results:GradRCIPSO successfully generated clinically viable prognosis-guided IMRT plans with comparable dosimetric statistics to original plans, while significantly reducing predicted total radiotherapy risk from 1.22(0.84, 1.51) to 0.93(0.80, 1.29) ( z=2.81, P<0.01). It demonstrated superior accuracy over the above four gradient-based method ( z=2.80-2.81, P<0.01) and achieved threefold acceleration versus RCIPSO while maintaining equivalent solution quality( P>0.05). Conclusions:The proposed GradRCIPSO demonstrates high feasibility and performance in optimizing prognosis-guided IMRT plans, laying the technical foundation for the broad clinical application of prognosis-guided IMRT plans for lung cancer.