ObjectiveChronic pain, a major global public health burden, is primarily driven by altered central pain processing, which conventional treatments rarely target directly. This systematic review and meta-analysis synthesized RCT evidence to quantify acupuncture’s modulatory effects on brain networks associated with altered central pain processing, validate its clinical efficacy/safety, and explore brain network-clinical outcome associations.MethodsComprehensive searches of English/Chinese databases (2016–2025) identified RCTs of acupuncture for chronic pain with neuroimaging. Two researchers independently performed study selection, data extraction, and bias assessment. Meta-analysis used RevMan 5.4; heterogeneity was evaluated via I2/Q test, with correlation analysis and GRADE evidence quality assessment.ResultsSeventeen high-quality RCTs comprising 750 patients, with osteoarticular pain and migraine as main subtypes, were included. Acupuncture significantly improved neuroimaging indicators in the anterior cingulate cortex (ACC) and insula (MD = 0.27, p < 0.00001), primary somatosensory cortex (S1) and thalamus (MD = 0.30, p < 0.00001), and default mode network (DMN) (MD = 0.29, p < 0.00001). Clinically, acupuncture reduced Visual Analogue Scale (VAS) scores (MD = -2.31, p < 0.00001) and increased pain relief rate (OR = 4.30, p < 0.00001), with only mild adverse events reported. Osteoarticular pain demonstrated more pronounced efficacy. No significant publication bias was detected. The GRADE assessment rated the evidence for pain relief rate as high.ConclusionAcupuncture exerts dual effects by alleviating clinical pain - exceeding the minimal clinically important difference (MCID) for VAS - and modulating brain networks implicated in altered central pain processing. It is a safe and valuable non-pharmacological intervention, with standardized protocols and subtype-specific application recommended. However, the evidence is constrained by a limited number of studies, heterogeneity in pain subtypes and neuroimaging modalities, and short follow-up durations. Larger RCTs and multimodal neuroimaging studies are needed for further validation.Systematic review registrationRegistered in PROSPERO (CRD420261290299); URL: https://www.crd.york.ac.uk/prospero/.

Background:Branched-chain amino acids (BCAAs), including isoleucine (Ile), leucine (Leu), and valine (Val), are substrates for synthesising nitrogenous compounds and signalling molecules involved in regulating immunity. To date, data on the role of BCAAs in autoimmune thyroiditis (AIT) are lacking; therefore, this study aimed to determine the causality using two-sample Mendelian randomisation (MR) and explored the role of BCAAs in the cGAS-STING-NLRP3 pathway in vitro. Methods:The causal relationship between BCAAs and the pathogenesis of AIT were identified using a two-sample MR study. The anti-inflammatory effects of BCAAs and their role in the cGAS-STING-NLRP3 pathway were investigated in lipopolysaccharide (LPS)- induced thyroid follicular cells (TFCs). Results:Our findings indicate that BCAAs are a pathogenic factor for AIT (IVW OR = 4.960; 95 % CI = (1.54,15.940); P = 0.007). Leu significantly exacerbated the inflammatory response of thyroid cells, as evidenced by the up-regulation of tumour necrosis factor-alpha (TNF-α) and interleukin (IL)-6 and down-regulation of TGF-β1; simultaneously aggravated cellular injury and oxidative stress; significantly increased the expression of Sestrin2/p-mTOR and cGAS/STING/NLRP3 in AIT cells. Furthermore, the expression of IL-18 and IL-1β was significantly increased. Conversely, Leu deprivation induced cell injury, decreased oxidative stress, and inhibited Sestrin2/p-mTOR and cGAS/STING/NLRP3 pathways. Conclusion:Our findings suggest a potential causal effect of genetically predicted Leu on AIT; Leu significantly exacerbated the inflammatory response and cellular damage in AIT cells. The mechanism by which Leu induces inflammation involves activating the promoted Sestrin2/mTOR and cGAS-STING-NLRP3 signalling pathways. Our study proposes a novel mechanism for the contributions of Leu in AIT and potential therapeutic strategies involving Leu deprivation in treating AIT.

Obstructive sleep apnea (OSA) is associated with metabolic disorders such as insulin resistance and liver fat accumulation. However, the specific mediating role of liver-related metabolic indicators in this association has not been fully studied. The purpose of this study was to investigate the relationship between Metabolic Score for Insulin Resistance (METS-IR) and OSA, focusing on the mediating effects of liver fat percentage (PLF) and hepatic steatosis index (HSI). Understanding these mechanisms may provide insights into targeted interventions for OSA. A total of 12,655 participants from the National Health and Nutrition Examination Survey (NHANES) were included in this analysis. Obstructive sleep apnea (OSA) was assessed using the NHANES questionnaire. Weighted multivariate logistic regression was employed to assess the relationship between METS-IR and OSA, with a mediation model constructed to explore the mediating roles of key liver and metabolic markers, including PLF, HSI, SII and OBS. Among 12,655 subjects, 31.04% had OSA. METS-IR was closely related to the increased risk of OSA, and the highest quartile group of METS-IR had a significantly increased risk of OSA (OR = 2.36, 95% CI 1.73-3.23). Mediating effect analysis showed that PLF and HSI mediated 6.95% and 17.87% of the effects, respectively, while systemic immunity-inflammation index (SII) and oxidative balance score (OBS) had no significant mediating effect. METS-IR is an important predictor of OSA risk, primarily mediated by hepatic lipid accumulation. Addressing insulin resistance and hepatic metabolic health is crucial for the effective management of OSA and provides valuable guidance for clinical risk assessment in susceptible populations.

Background: The association between the triglyceride glucose-body mass (TyG-BMI) index and cardiovascular disease (CVD) risk in postmenopausal women remains unclear. This study examines this association in Chinese menopausal women to develop targeted risk assessment tools. Methods: Data from the 2011 and 2020 China Health and Retirement Longitudinal Study (CHARLS) included menopausal women aged ≥45 years. Multivariable logistic regression models assessed the association between TyG-BMI and CVD. Restricted cubic spline (RCS) regression tested nonlinearity, and stratified analyses evaluated effect modification. Results: Among 2405 participants, 609 (25.32 %) developed CVD. Each interquartile TyG-BMI (49.10) increase raised CVD risk by 28 % (OR = 1.28; 95 % CI: 1.07–1.53). A linear dose-response relationship existed for CVD (P-trend <0.05; P-nonlinearity >0.05). Marital status modified the association (P-interaction = 0.035), with no significant interactions in other subgroups. For CVD prediction, TyG-BMI (AUC = 0.645) outperformed TyG (AUC = 0.622). Conclusions: Our study demonstrates a significant association between TyG-BMI and the risk of CVD in postmenopausal women, supporting its utility as a valuable biomarker for enhancing primary prevention and management strategies in this population.

Diabetic nephropathy (DN) remains a leading cause of end-stage renal disease despite guideline-based therapy. Acupuncture has been explored as an adjunct or alternative approach. We reviewed preclinical and clinical studies (2010–2025) on acupuncture for DN, summarizing mechanisms, intervention models (acupuncture alone; with Chinese medicine; with Western medicine; triple therapy), renal outcomes, and safety. Across animal and human data, acupuncture modulates immune–inflammatory and metabolic pathways—including HMGB1/NLRP3/NF-κB, SIRT1/AMPK/PGC-1α, eNOS–NO–cGMP, and autophagy (ULK1–Beclin-1–LC3)—enhances antioxidant defenses (SOD↑, MDA/8-OHdG↓), protects podocytes, and improves microcirculation. Clinically, it is associated with reductions in proteinuria (24-h UP, UACR/UAER), improvements in renal function (Scr, BUN, eGFR), and better metabolic control and symptoms. Combined regimens (with Chinese or Western medicines) tend to yield faster or broader benefits, with no serious adverse events reported in the included studies. Evidence quality is limited by small sample sizes, single-center designs, short follow-up, heterogeneous endpoints, and incomplete safety reporting. Acupuncture shows multi-target, complementary effects for DN and may be integrated with standard care. High-quality, multicenter randomized controlled trials with standardized endpoints (e.g., proteinuria, eGFR slope), robust safety monitoring, and embedded mechanistic assessments are warranted.

Background and objectivesMajor Depressive Disorder (MDD) is one of the most prevalent and debilitating health conditions worldwide. Previous studies have reported a link between metabolic dysregulation and MDD. However, evidence for a causal relationship between blood metabolites and MDD is lacking.MethodsUsing a two-sample bidirectional Mendelian randomization analysis (MR), we assessed the causal relationship between 1,400 serum metabolites and Major Depressive Disorder (MDD). The Inverse Variance Weighted method (IVW) was employed to estimate the causal association between exposures and outcomes. Additionally, MR-Egger regression, weighted median, simple mode, and weighted mode methods were used as supplementary approaches for a comprehensive appraisal of the causality between blood metabolites and MDD. Pleiotropy and heterogeneity tests were also conducted. Lastly, the relevant metabolites were subjected to metabolite function analysis, and a reverse MR was implemented to explore the potential influence of MDD on these metabolites.ResultsAfter rigorous screening, we identified 34 known metabolites, 13 unknown metabolites, and 18 metabolite ratios associated with Major Depressive Disorder (MDD). Among all metabolites, 33 were found to have positive associations, and 32 had negative associations. The top five metabolites that increased the risk of MDD were the Arachidonate (20:4n6) to linoleate (18:2n6) ratio, LysoPE(18:0/0:0), N-acetyl-beta-alanine levels, Arachidonate (20:4n6) to oleate to vaccenate (18:1) ratio, Glutaminylglutamine, and Threonine to pyruvate ratio. Conversely, the top five metabolites that decreased the risk of MDD were N6-Acetyl-L-lysine, Oleoyl-linoleoyl-glycerol (18:1 to 18:2) [2] to linoleoyl-arachidonoyl-glycerol (18:2 to 20:4) [2] ratio, Methionine to phosphate ratio, Pregnanediol 3-O-glucuronide, and 6-Oxopiperidine-2-carboxylic acid. Metabolite function enrichment was primarily concentrated in pathways such as Bile Acid Biosynthesis (FDR=0.177), Glutathione Metabolism (FDR=0.177), Threonine, and 2-Oxobutanoate Degradation (FDR=0.177). In addition, enrichment was noted in pathways like Valine, Leucine, and Isoleucine Biosynthesis (p=0.04), as well as Ascorbate and Aldarate Metabolism (p=0.04).DiscussionWithin a pool of 1,400 blood metabolites, we identified 34 known metabolites and 13 unknown metabolites, as well as 18 metabolite ratios associated with Major Depressive Disorder (MDD). Additionally, three functionally enriched groups and two metabolic pathways were selected. The integration of genomics and metabolomics has provided significant insights for the screening and prevention of MDD.

Background Obstructive sleep apnea (OSA) is associated with metabolic disorders such as insulin resistance and liver fat accumulation. However, the specific mediating role of liver-related metabolic indicators in this association has not been fully studied. The purpose of this study was to investigate the relationship between Metabolic Score for Insulin Resistance (METS-IR) and OSA, focusing on the mediating effects of liver fat percentage (PLF) and hepatic steatosis index (HSI). Understanding these mechanisms may provide insights into targeted interventions for OSA. Methods A total of 12,655 participants from the National Health and Nutrition Examination Survey (NHANES) were included in this analysis. Obstructive sleep apnea (OSA) was assessed using the NHANES questionnaire. Weighted multivariate logistic regression was employed to assess the relationship between METS-IR and OSA, with a mediation model constructed to explore the mediating roles of key liver and metabolic markers, including PLF, HSI, SII, and OBS. Results Among 12,655 subjects, 31.04% had OSA. METS-IR was closely related to the increased risk of OSA, and the highest quartile group of METS-IR had a significantly increased risk of OSA ( OR = 2.35, 95% CI : 1.72–3.21 ). Mediating effect analysis showed that PLF and HSI mediated 11.22% and 22.78% of the effects, respectively, while systemic immunity-inflammation index (SII) and oxidative balance score (OBS) had no significant mediating effect. Conclusions METS-IR is an important predictor of OSA risk, primarily mediated by hepatic lipid accumulation. Addressing insulin resistance and hepatic metabolic health is crucial for the effective management of OSA and provides valuable guidance for clinical risk assessment in susceptible populations.

Ankylosing spondylitis (AS) stands as a persistent inflammatory ailment predominantly impacting the axial skeleton, with the immune system and inflammation intricately entwined in its pathogenesis. This study endeavors to elucidate gender-specific patterns in immune cell infiltration and diverse forms of cell demise within the AS milieu. The aim is to refine the diagnosis and treatment of gender-specific AS patients, thereby advancing patient outcomes. In the pursuit of our investigation, two datasets (GSE25101 and GSE73754) pertinent to ankylosing spondylitis (AS) were meticulously collected and normalized from the GEO database. Employing the CIBERSORT algorithm, we conducted a comprehensive analysis of immune cell infiltration across distinct demographic groups and genders. Subsequently, we discerned differentially expressed genes (DEGs) associated with various cell death modalities in AS patients and their healthy counterparts. Our focus extended specifically to ferroptosis-related DEGs (FRDEGs), cuproptosis-related DEGs (CRDEGs), anoikis-related DEGs (ARDEGs), autophagy-related DEGs (AURDEGs), and pyroptosis-related DEGs (PRDEGs). Further scrutiny involved discerning disparities in these DEGs between AS patients and healthy controls, as well as disparities between male and female patients. Leveraging machine learning (ML) methodologies, we formulated disease prediction models employing cell death-related DEGs (CDRDEGs) and identified biomarkers intertwined with cell death in AS. Relative to healthy controls, a myriad of differentially expressed genes (DEGs) linked to cell death surfaced in AS patients. Among AS patients, 82 FRDEGs, 29 CRDEGs, 54 AURDEGs, 21 ARDEGs, and 74 PRDEGs were identified. In male AS patients, these numbers were 78, 33, 55, 24, and 94, respectively. Female AS patients exhibited 66, 41, 40, 17, and 82 DEGs in the corresponding categories. Additionally, 36 FRDEGs, 14 CRDEGs, 19 AURDEGs, 10 ARDEGs, and 36 PRDEGs exhibited differential expression between male and female AS patients. Employing machine learning techniques, LASSO, RF, and SVM-RFE were employed to discern key DEGs related to cell death (CDRDDEGs). The six pivotal CDRDDEGs in AS patients, healthy controls, were identified as CLIC4, BIRC2, MATK, PKN2, SLC25A5, and EDEM1. For male AS patients, the three crucial CDRDDEGs were EDEM1, MAP3K11, and TRIM21, whereas for female AS patients, COX7B, PEX2, and RHEB took precedence. Furthermore, the trio of DDX3X, CAPNS1, and TMSB4Y emerged as the key CDRDDEGs distinguishing between male and female AS patients. In the realm of immune correlation, the immune infiltration abundance in female patients mirrored that of healthy controls. Notably, key genes exhibited a positive correlation with T-cell CD4 memory activation when comparing male and female patient samples. This study engenders a more profound comprehension of the molecular underpinnings governing immune cell infiltration and cell death in ankylosing spondylitis (AS). Furthermore, the discernment of gender-specific disparities among AS patients underscores the clinical significance of these findings. By identifying DEGs associated with diverse cell death modalities, this study proffers invaluable insights into potential clinical targets for AS patients, taking cognizance of gender-specific nuances. The identification of gender-specific biological targets lays the groundwork for the development of tailored diagnostic and therapeutic strategies, heralding a pivotal step toward personalized care for AS patients.

BACKGROUND:Neuroinflammation is involved in the advancement of depression. Du-moxibustion can treat depression. Here, we explored whether Du-moxibustion could alleviate neuroglia-associated neuro-inflammatory process in chronic unpredictable mild stress (CUMS) mice. METHODS:C57BL/6J mice were distributed into five groups. Except for the CON group, other four groups underwent CUMS for four consecutive weeks, and Du-moxibustion was given simultaneously after modeling. Behavioral tests were then carried out. Additionally, Western blot was conducted to measure the relative expression levels of high-mobility group box 1 (HMGB1), toll-like receptor 4 (TLR4), myeloid differentiation factor 88 (MyD88), and nuclear factor-kappa B (NF-κB). Immunofluorescence was employed to evaluate the positive cells of ionized calcium binding adapter molecule 1 (Iba-1) and glial fibrillary acidic protein (GFAP). Furthermore, interleukin-1 beta (IL-1β) and tumor necrosis factor-alpha (TNF-α) were analyzed using an ELISA assay. RESULTS:We found that CUMS induced depression-like behaviors, such as reduced sucrose preference ratio, decreased locomotor and exploratory activity, decreased the time in open arms and prolonged immobility. Furthermore, versus the CON group, the expression of HMGB1, TLR4, MyD88, NF-κB, positive cells of Iba-1, IL-1β and TNF-α were increased but positive cells of GFAP were decreased in CUMS group. However, the detrimental effects were ameliorated by treatment with CUMS+FLU and CUMS+DM. LIMITATIONS:A shortage of this study is that only CUMS model of depression were used, while other depression model were not included. CONCLUSIONS:Du-moxibustion alleviates depression-like behaviors in CUMS mice mainly by reducing neuroinflammation, which offers novel insights into the potential treatment of depression.

Abstract Background Depression and insomnia often co-occur and have a bidirectional relationship. This review utilized bibliometric and visualized analysis to explore current research hotspots and trends in this field to identify future clinical practice directions. Methods To identify papers on the comorbidity of depression and insomnia, the researchers utilized the Web of Science Core Collection (WoSCC). They employed tools such as CiteSpace, VOSviewer, and Scimago Graphica to visually analyze the knowledge network of authors, institutions, countries/regions, journals, cited authors, cited references, cited journals, and keywords in the field of depression comorbid with insomnia. Results A total of 697 papers were extracted from the Web of Science Core Collection (WoSCC) with Andrew D. Krystal being the most influential author in this area. The University of Pittsburgh and the United States emerged as the most prolific institution and country, respectively. The Journal of Affective Disorders was the most productive journal, with primary keywords including insomnia, depression, anxiety, disorder, and sleep. In terms of co-citation analysis, Morin, Cm led the field. The top-cited journal was Sleep, and the paper titled “Validation of the Insomnia Severity Index as an outcome measure for insomnia research” ranked first. Finally, “Psychiatry”was the most frequent study category. Conclusions This bibliometric analysis provides a comprehensive overview of current research on depression comorbid with insomnia and highlights key areas of focus, offering guidance for clinicians and researchers in selecting research directions.

BACKGROUND:Depression is linked to obesity. The body roundness index (BRI) provides a more accurate assessment of body and visceral fat levels than the body mass index or waist circumference. However, the association between BRI and depression is unclear. Therefore, we investigated this relationship using the National Health and Nutrition Examination Survey (NHANES) database. METHODS:In this population-based cross-sectional study, data from 18,654 adults aged ≥20 years from the NHANES 2011-2018 were analyzed. Covariates, including age, gender, race/ethnicity, education level, marital status, poverty-income ratio, alcohol status, smoking status, hypertension, diabetes mellitus, cardiovascular disease, energy intake, physical activity, total cholesterol, and triglycerides were adjusted in multivariable logistic regression models. In addition, smooth curve fitting, subgroup analysis, and interaction testing were conducted. RESULTS:After adjusting for covariates, BRI was positively correlated with depression. For each one-unit increase in BRI, the prevalence of depression increased by 8 % (odds ratio = 1.08, 95 % confidence interval = 1.05-1.10, P < 0.001). LIMITATIONS:As this was a cross-sectional study, we could not determine a causal relationship between BRI and depression. Patients with depression in this study were not clinically diagnosed with major depressive disorder. CONCLUSION:BRI levels were positively related to an increased prevalence of depression in American adults. BRI may serve as a simple anthropometric index to predict depression.

Due to the increasing number of individuals suffering from depression, there is much attention paid to the detection of depression. This review paper addresses the critical field of depression detection, examining innovative methods including serological tests, cerebrospinal fluid analysis, and imaging techniques. Serological markers like C-reactive protein and cytokines are highlighted for their potential in identifying inflammation associated with depression. The role of cerebrospinal fluid in providing direct brain markers is discussed, alongside the utility of imaging in visualizing brain metabolism linked to depressive symptoms. Though there is a large amount of evidence, more and further research is still needed, which ensures that these methods are more quantitative and precise enough so that we can put them into practice. The overview and understanding of these approaches are crucial to improving diagnostic precision, which is quite essential for developing effective treatment strategies and enhancing patient outcomes in the management of depression.

Abstract Background Studies examining whether diet sugar intake increases the risk of depression have produced inconsistent results. Therefore, we investigated this relationship, using the US’ National Health and Nutrition Examination Survey (NHANES) database. Methods This cross-sectional study included 18,439 adults (aged ≥ 20 years) from NHANES (2011–2018). Depressive symptoms were assessed using the nine-item version of the Patient Health Questionnaire (PHQ-9). Covariates, including age, sex, race/ethnicity, poverty-income ratio, education, marital status, hypertension, diabetes mellitus, cardiovascular disease, alcohol intake, smoking status, physical activity, and dietary energy intake, were adjusted in multivariate logistic regression models. Subgroup and threshold saturation effect analyses were performed. Results After adjusting for potential confounders, we found that a 100 g/day increase in dietary sugar intake correlated with a 28% higher prevalence of depression (odds ratio = 1.28, 95% confidence interval = 1.17–1.40, P < 0.001). Conclusion Dietary sugar intake is positively associated with depression in US adults.

As the second most common neurodegenerative disease globally, Parkinson's disease (PD) affects millions of people worldwide. In recent years, the scientific publications related to PD biomarker research have exploded, reflecting the growing interest in unraveling the complex pathophysiology of PD. In this study, we aim to use various bibliometric tools to identify key scientific concepts, detect emerging trends, and analyze the global trends and development of PD biomarker research.The research encompasses various stages of biomarker development, including exploration, identification, and multi-modal research. MOVEMENT DISORDERS emerged as the leading journal in terms of publications and citations. Key authors such as Mollenhauer and Salem were identified, while the University of Pennsylvania and USA stood out in collaboration and research output. NEUROSCIENCES emerged as the most important research direction. Key biomarker categories include α-synuclein-related markers, neurotransmitter-related markers, inflammation and immune system-related markers, oxidative stress and mitochondrial function-related markers, and brain imaging-related markers. Furthermore, future trends in PD biomarker research focus on exosomes and plasma biomarkers, miRNA, cerebrospinal fluid biomarkers, machine learning applications, and animal models of PD. These trends contribute to early diagnosis, disease progression monitoring, and understanding the pathological mechanisms of PD.

OBJECTIVES:The triglyceride glucose-body mass index (TyG-BMI) is a well-established surrogate marker for insulin resistance. While an association between insulin resistance and depression has been identified, that between TyG-BMI and depression remains unclear. Therefore, we used data from the National Health and Nutrition Examination Survey (NHANES) database to investigate this. STUDY DESIGN:This cross-sectional study included 9673 adults (aged ≥20 years) from the NHANES in the United States from 2011 to 2020. METHODS:Depressive symptoms were assessed using a nine-item version of the Patient Health Questionnaire. The covariates included age, sex, race/ethnicity, marital status, educational level, poverty-income ratio, smoking status, alcohol intake, diabetes status, cardiovascular disease, hypertension, physical activity, high-density lipoprotein, low-density lipoprotein, and total cholesterol. Multivariate logistic regression models, subgroup analyses, and threshold saturation effect analyses were conducted. RESULTS:After adjusting for age, sex, race/ethnicity, marital status, education level, poverty-income ratio, smoking status, drinking status, diabetes status, cardiovascular disease, hypertension, physical activity, total cholesterol, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol, the threshold saturation effect showed a TyG-BMI inflection point of 174.4. Below the inflection point, a 10-unit increase in TyG-BMI was associated with a 12 % lower prevalence of depression. Above the inflection point, each 10-unit increase in TyG-BMI was associated with a 4 % increase in prevalence of depression. CONCLUSIONS:TyG-BMI had a U-shaped relationship with prevalence of depression. There was a significant link between higher TyG-BMI levels and increased prevalence of depression. When the TyG-BMI value was below 174.4, any further increase in TyG-BMI was associated with a significantly lower prevalence of depression.

Endometriosis is a common chronic gynecological condition characterized by the presence of endometrial tissue outside the uterine cavity, leading to chronic inflammation, pelvic nodules and masses, pelvic pain, and infertility. Acupuncture has been shown to improve pain associated with endometriosis by modulating abnormal levels of prostaglandins, β-endorphins, dynorphins, electrolytes, and substance P. This review aims to evaluate the clinical efficacy of acupuncture in treating endometriosis, specifically focusing on its efficacy in relieving pain associated with endometriosis. A comprehensive search was conducted in eight databases (PubMed, EMBASE, Cochrane, Web of Science, China National Knowledge Infrastructure (CNKI), the China Biology Medicine (CBM), Wanfang, and Weipu database) to identify randomized controlled trials (RCTs) published from database inception to December 16, 2022, which investigated the use of acupuncture for endometriosis-related pain. Two researchers independently screened articles, extracted data, and assessed methodological quality using the Cochrane Collaboration’s risk of bias tool. Meta-analysis was performed using Stata statistical software. A total of 1991 articles were identified, and ultimately, 14 studies involving 793 patients (387 in the acupuncture group and 359 in the control group) were included. The control interventions in the included studies included placebo, traditional Chinese medicine (TCM), and Western medicine treatments. Meta-analysis results showed that compared to the control group, acupuncture treatment for pain associated with endometriosis demonstrated significant reductions in pain severity [SMD = − 1.10, 95

Abstract Post-stroke depression (PSD) is a common neuropsychiatric consequence of stroke that can negatively impact cognitive function, somatic function recovery, and patient survival. This paper utilized bibliometric and visualized analysis to explore current research hotspots and trends in this field to identify future clinical practice directions. Researchers utilized the Web of Science Core Collection (WoSCC) to extract papers on PSD and employed tools such as CiteSpace, VOSviewer, and Scimago Graphica to visually analyze the knowledge network of authors, institutions, countries/regions, journals, cited authors, cited references, cited journals, and keywords. A total of 850 papers were extracted from WoSCC, with Robinson, RG being identified as the most influential author in this area. The most prolific institution was Wenzhou Medical University, and China emerged as the leading country in producing research on PSD. Journal of Affective Disorders was found to be the most productive journal, with the primary keywords including poststroke depression, stroke, depression, and symptom. Co-citation analysis identified Robinson, RG as the leading researcher in PSD. The top-cited journal was Stroke, and the paper titled “Poststroke Depression: A Review” was ranked the most cited. Finally, “Neurosciences & Neurology” emerged as the most frequent study category. This study provided valuable information on the hotspot and frontier in PSD research, including potential partners and institutions, as well as reference points for future research topics and development directions.

Background: Depression, a prevalent mental disorder, has shown an increasing trend in recent years, imposing a significant burden on health and society. Adequate sleep has been proven to reduce the incidence of depression. This study seeks to explore how Weekend Catch-up Sleep (WCS) is connected with the prevalence of depression in the American population. Methods: The National Health and Nutrition Examination Survey (NHANES) provides representative data for the U.S. population. We utilized data from the 2017-2018 and 2019-2020 cycles. Depression was operationally defined as a PHQ-9 score exceeding 10. WCS duration was categorized into five groups: no change in sleep duration (=0 h), decreased sleep duration (<0), short catch-up sleep duration (>0 h, <1 h), moderate catch-up sleep duration (>1 h, <2 h), and long catch-up sleep duration (>= 2 h). Results: Among the 8039 individuals, the distribution of WCS duration was as follows: no change (WCS = 0 h) in 2999 individuals (37.3 %), decreased sleep (WCS < 0 h) in 1199 individuals (14.9 %), short catch-up sleep (0 h < WCS < 1 h) in 1602 individuals (19.9 %), moderate catch-up sleep (1 h < WCS < 2 h) in 479 individuals (6.0 %), and long catch-up sleep (WCS >= 2 h) in 1760 individuals (21.9 %). Acting by adjustment for all covariates in a multiple regression analysis, we discovered that persons with 1 to 2 h of weekend catch-up sleep had a substantially low prevalence of depression concerning those with WCS = 0 (OR 0.22, 95 % CI 0.08-0.59, P = 0.007). Conclusion: The prevalence of depression in individuals engaging in weekend catch-up sleep for 1 to 2 h is lower than those who do not catch up on weekends. This discovery on the treatment and prevention of depression provides a new perspective. However, further prospective research and clinical trials are needed for a comprehensive investigation.

BackgroundAnkylosing spondylitis (AS) is a rheumatic and autoimmune disease associated with a chronic inflammatory response, mainly characterized by pain, stiffness, or limited mobility of the spine and sacroiliac joints. Severe symptoms can lead to joint deformity, destruction, and even lifelong disability, causing a serious burden on families and society as a whole. A large number of clinical studies have been published on AS over the past 20 years. This study aimed to summarize the current research status and global trends relating to AS clinical trials through a bibliometric analysis.MethodsThe Web of Science Core Collection database was searched for publications related to AS clinical trials published between January 2003 and June 2023. Bibliometric analysis and web visualization were performed using CiteSpace, VOSviewer, and a bibliometric online analysis platform (https://bibliometric.com), which included the number of publications, citations, countries, institutions, journals, authors, references, and keywords.Results1,212 articles published in 201 journals from 65 countries were included in this study. The number of publications related to AS clinical trials is increasing annually. The United States and the Free University of Berlin, the countries and institutions, respectively, that have published the most articles on AS, have made outstanding contributions to this field. The author with the most published papers and co-citations over the period covered by the study was Desiree Van Der Heijde. The journal with the most published and cited articles was Annals of the Rheumatic Diseases. The keywords: “double-blind,” “rheumatoid arthritis,” “efficacy,” “placebo-controlled trial,” “infliximab,” “etanercept,” “psoriatic arthritis” and “therapy” represent the current research hotspots regarding AS.DiscussionThis is the first study to perform a bibliometric analysis and visualization of AS clinical trial publications, providing a reliable research focus and direction for clinicians. Future studies in the field of AS clinical trials should focus on placebo-controlled trials of targeted therapeutic drugs.

Background Prediabetes and diabetes are associated with obesity, and the body roundness index (BRI) is a new obesity index that more accurately reflects body fat and visceral fat levels. The relationships between BRI and prediabetes and diabetes are currently unknown, and we aimed to investigate the relationships between BRI and the prevalence of prediabetes and diabetes. Methods A cross-sectional study was conducted using data from the 2005–2020 NHANES, which included a total of 46,447 participants. We used restricted cubic spline (RCS) analysis, logistic regression analysis, and subgroup analysis to assess the associations of BRI with prediabetes and diabetes. We assessed the ability of the BRI and body mass index (BMI) to identify prediabetes and diabetes patients via receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) analysis and compared the results via the Delong test. Results Of the 46,447 participants aged 18 years and older included in the study, 15808 had prediabetes and diabetes. According to the fully adjusted models, a positive association was observed between BRI and the prevalence of prediabetes and diabetes (OR = 1.17, 95% CI: 1.14–1.20; P < 0.0001). Compared with those in the lowest quartile, individuals in the highest quartile of BRI had a 125% increased risk of prediabetes and diabetes (OR = 2.20, 95% CI: 1.88–2.57; P < 0.0001). The associations between BRI and prediabetes and diabetes persisted in the subgroup analyses. ROC analysis revealed that the BRI (AUC = 0.695) was a stronger predictor of prediabetes and diabetes than BMI was (AUC = 0.651). Conclusions An elevated BRI is associated with an increased prevalence of prediabetes and diabetes in the U.S. population, and the BRI is a stronger predictor of prediabetes and diabetes than BMI is. Maintaining an appropriate BRI is recommended to reduce the incidence of prediabetes and diabetes.