OBJECTIVE To construct and evaluate nomogram prediction model for refractory chemotherapy-induced nausea and vomiting （CINV）. METHODS The data of malignant tumor patients who received chemotherapy at the Third People’s Hospital of Zhengzhou from January 2017 to December 2023 were collected. These patients were categorized into the occurrence group and the non-occurrence group according to the occurrence of refractory CINV. Multivariate Logistic regression analysis was employed to screen predictive factors for refractory CINV and constructing a nomogram prediction model. Model performance was assessed via receiver operating characteristic curve analysis. Model calibration was evaluated using Bootstrap resampling. Decision curve analysis （DCA） was used to determine the clinical net benefit of three strategies under different risk thresholds. Clinical impact curves were utilized to assess the clinical value of the model at different risk thresholds. Shapley additive explanations （SHAP） analysis was performed to evaluate individual factor contributions to the predictive model. RESULTS A total of 388 patients were included， with 219 experiencing refractory CINV. Multivariate Logistic regression identified 11 predictive factors for refractory CINV， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， etc. The model’s area under the curve was 0.80 [95% confidence interval （0.76， 0.84）]， with a mean error of 0.036. DCA demonstrated the prediction model had higher clinical net benefit when the risk threshold was between 0.05 and 0.85. SHAP analysis revealed the top three predictive factors as gastrointestinal disease history （0.924）， chemotherapy- induced emetic risk classification （0.866）， and electrolyte levels （0.581）. CONCLUSIONS Eleven factors， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， are identified as predictors of refractory CINV. The model based on these factors has good predictive ability， which can be used to predict the risk of refractory CINV.

The Ebola virus (EBOV), a member of the Filoviridae family, is a highly pathogenic agent responsible for severe hemorrhagic fever in humans. Understanding the molecular mechanisms governing its replication is critical for developing effective antiviral strategies. VP35-TurboID immunosuppression coupled with quantitative mass spectrometry identified Septin9, the host GTP-binding protein which played a role in cytoskeletal regulation, as a novel interactor of VP35. Western blotting and Far-Western blotting confirmed the direct interaction and demonstrated that the C-terminal region of VP35 was the critical binding domain. Functionally, EBOV replication as well as the formation of viral inclusion bodies (VIBs) was demonstrated to be significantly suppressed by Septin9 knockdown and depletion, as shown by the EBOV minigenome (EBOV MG) and the transcription- and replication-competent virus-like particles (trVLPs) system. This study reveals that VP35 engages in a specific interaction with the GTP-binding protein Septin9, thereby impeding EBOV replication through the disruption of inclusion bodies. The overarching objective of this study is to significantly enhance our understanding about the pathogenic mechanism of EBOV and offer a robust theoretical foundation and solid empirical support for the formulation of innovative therapeutic strategies against EBOV.
Virus Replication/physiology* ; Septins/physiology* ; Humans ; Ebolavirus/physiology* ; Inclusion Bodies, Viral/metabolism* ; Viral Regulatory and Accessory Proteins/metabolism* ; Hemorrhagic Fever, Ebola/virology*

Objective To explore the relationship between serum chitosinase 3-like protein 1(CHI3L1)and Syndecan-1(SDC1)levels and bone metabolism in elderly patients with type 2 diabetes mellitus and their predictive efficacy on osteoporosis.Methods A total of 412 elderly patients with type 2 diabetes admitted to this hospital from May 2019 to May 2023 were included in this study,and were divided into normal bone mass group(n=151),reduced bone mass group(n=138)and osteoporosis group(n=123)according to the iffer-ences in bone mineral density.Serum CHI3L1 and SDC1 levels were detected by enzyme-linked immunosor-bent assay,and serum levels of type 1 collagen cross-linked carboxyl terminal peptide(CTX),25-hydroxyvita-min D[25-(OH)D],osteocalcin(OC),and type 1 procollagen N-terminal propeptide(P1NP)were deter-mined by automatic chemiluminescence immunoassay.Pearson correlation analysis was used to investigate the relationship between serum CHI3L1,SDC1 and bone metabolism in elderly patients with type 2 diabetes.Re-ceiver operating characteristic(ROC)curve was drawn to evaluate the predictive value of serum CHI3L1 and SDC1 on osteoporosis in elderly patients with type 2 diabetes.Multivariate Logistic regression analysis was used to investigate the influencing factors of osteoporosis in elderly patients with type 2 diabetes.Results There were significant differences in diabetes course,fasting blood glucose,HbA1c and HDL-C a-mong normal bone mass group,decreased bone mass group and osteoporosis group(P＜0.05).The levels of serum CHI3L1,25-(OH)D,P1NP and osteocalcin in osteoporosis group were lower than those in osteopenia group,and those in osteopenia group were lower than those in normal bone mass group,the differences were statistically significant(P＜0.05).Serum SDC1 and CTX levels in osteoporosis group were higher than those in osteopenia group,and those in osteopenia group were higher than those in normal bone mass group,the differences were statistically significant(P＜0.05).Serum CHI3L1 was positively correlated with 25-(OH)D,P1NP and OC(P＜0.05),and negatively correlated with CTX(P＜0.05).Serum SDC1 was negatively correlated with 25-(OH)D,P1NP,OC(P＜0.05),and positively correlated with CTX(P＜0.05).The area under the curve(AUC)of serum CHI3L1,SDC1 and their combination predicted osteoporosis in elderly pa-tients with type 2 diabetes were 0.851,0.772 and 0.904,respectively.Multivariate Logistic regression analysis showed that long duration of diabetes,increased HbA1c,high expression of OC,CHI3L1＞4.16 ng/mL,SDC1≥50.94 ng/mL were all influential factors for osteoporosis in elderly patients with type 2 diabetes(P＜0.05).Conclusion Low expression of CHI3L1 and high expression of SDC1 in serum are associated with ab-normal bone metabolism in elderly patients with type 2 diabetes.These two indexes are expected to be used as biological markers to predict osteoporosis in elderly patients with type 2 diabetes.

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Although clinical evidence suggests that nonalcoholic fatty liver disease is an established major risk factor for heart failure, it remains unexplored whether sleep disorder-caused hepatic damage contributes to the development of cardiovascular disease (CVD). Here, our findings revealed that sleep fragmentation (SF) displayed notable hepatic detrimental phenotypes, including steatosis and oxidative damage, along with significant abnormalities in cardiac structure and function. All these pathological changes persisted even after sleep recovery for 2 consecutive weeks or more, displaying memory properties. Mechanistically, persistent higher expression of nicotinamide adenine dinucleotide phosphate oxidase 4 (NOX4) in the liver was the key initiator of SF-accelerated damage phenotypes. SF epigenetically controlled the acetylation of histone H3 lysine 27 (H3K27ac) enrichment at the Nox4 promoter and markedly increased Nox4 expression in liver even after sleep recovery. Moreover, fine coordination of the circadian clock and hepatic damage was strictly controlled by BMAL1-dependent Sirtuin 1 (Sirt1) transcription after circadian misalignment. Accordingly, genetic manipulation of liver-specific Nox4 or Sirt1, along with pharmacological intervention targeting NOX4 (GLX351322) or SIRT1 (Resveratrol), could effectively erase the epigenetic modification of Nox4 by reducing the H3K27ac level and ameliorate the progression of liver pathology, thereby counteracting SF-evoked sustained CVD. Collectively, our findings may pave the way for strategies to mitigate myocardial injury from persistent hepatic detrimental memory in diabetic patients.

Acupuncture is an ancient treatment method used in traditional Chinese medicine and has been popularized worldwide. Over the past decade, there has been an increase in the amount of acupuncture research, mostly comprised of randomized controlled trials (RCTs) that aimed to answer the question on the efficacy of acupuncture. However, poor methodology and low replicability in these acupuncture RCTs have resulted in uncertainty about the efficacy of acupuncture. In this review, current advancements and challenges in acupuncture RCTs, regarding the methodological aspects of randomization, blinding, sham acupuncture and quality of reporting, were discussed. While there have been advancements in various aspects, current acupuncture RCTs still face pressing issues such as inadequate randomization and blinding, unviable sham acupuncture controls, and poor reporting quality. Given these limitations, this review seeks to identify the methodological problems that are responsible for these problems and to suggest solutions that could help to overcome them so as to improve the quality of future studies evaluating the efficacy of acupuncture. Please cite this article as: Seetoh WS, Lim RQR, Xu RB, Sun MX, Zhang P, Wang MN. Advancements and challenges of acupuncture randomized controlled trials. J Integr Med. 2025; 23(4): 333-343.
Acupuncture Therapy ; Humans ; Randomized Controlled Trials as Topic/methods* ; Research Design

Background: Gestational diabetes mellitus (GDM) is a metabolic disorder posing significant risks to maternal and infant health, with a lack of effective early screening markers. Therefore, identifying early screening biomarkers for GDM with higher sensitivity and specificity is urgently needed. Methods: High-throughput sequencing was employed to screen for key circular RNAs (circRNAs), which were then evaluated using reverse transcription quantitative polymerase chain reaction. Logistic regression analysis was conducted to examine the relationship between clinical characteristics, circRNA expression, and adverse pregnancy outcomes. The diagnostic accuracy of circRNAs for early and mid-pregnancy GDM was assessed using receiver operating characteristic curves. Pearson correlation analysis was utilized to explore the relationship between circRNA levels and oral glucose tolerance test results. A predictive model for early GDM was established using logistic regression. Results: Significant alterations in circRNA expression profiles were detected in GDM patients, with hsa_circ_0031560 and hsa_ circ_0000793 notably upregulated during the first and second trimesters. These circRNAs were associated with adverse pregnancy outcomes and effectively differentiated GDM patients, with second trimester cohorts achieving an area under the curve (AUC) of 0.836. In first trimester cohorts, these circRNAs identified potential GDM patients with AUCs of 0.832 and 0.765, respectively. The early GDM prediction model achieved an AUC of 0.904, validated in two independent cohorts. Conclusion Hsa_circ_0031560, hsa_circ_0000793, and the developed model serve as biomarkers for early prediction or midterm diagnosis of GDM, offering clinical tools for early GDM screening.

Objective:To analyze the changes in the phylogenetic and antigenic characteristics of the hemagglutinin (HA) gene of influenza virus A(H3N2) [A(H3N2)] during the 2022-2024 influenza seasons in Beijing.Methods:The data of influenza-like cases and A(H3N2) strains from 17 network laboratories and their corresponding sentinel hospitals were collected during the 2022-2024 influenza seasons. The HA genes were amplified and sequenced after extracting nucleic acids of the chosen virus strains. BioEdit, the nucleotide and amino acid sequence identity were conducted, and the maximum likelihood method in MEGA 5.0 software was used to construct the phylogenetic tree of HA genes. Web Logo displayed the amino acid mutation, and the N-glycosylation sites of HA online were analyzed using the NetNGlyc1.0 Server online. The Datamonkey platform was utilized to analyze the positive selection pressure sites of the HA protein.Results:The 2022-2024 influenza season includes 2022-2023 and 2023-2024. During the influenza seasons of 2022-2024, the positive rates of A(H3N2) nucleic acid were 10.35% (2 127/20 543) and 10.47% (4 386/41 876), respectively. In the 2022-2023 influenza season, there were two peaks in the A(H3N2). The comparison of HA genes between all A(H3N2) strains studied with the 2022-2024 vaccine strain (A/Darwin/9/2021) revealed that all of the strains studied have the two amino acid mutations involving 186 and 225 receptor binding sites. There were 31 amino acid substitutions in the 2022-2023 influenza season, of which 18 variant sites involved antigenic determinants. There were 35 amino acid mutations during the 2023-2024 influenza season, of which 14 were related to antigenic determinants. There were changes in the genetic evolutionary subclades of A(H3N2) strains in two influenza seasons: from 2022 to 2023, three evolutionary subclades were co-prevalent together, with the 3C.2a1b.2a.2a.3a.1 accounting for 76.67% (23/30), the 3C.2a1b.2a.1a accounting for 20.00% (6/30), the 3C.2a1b.2a.2a.1 accounting for 3.33% (1/30); from 2023 to 2024, two subclades were prevalent, with 3C.2a1b.2a.2a.3a.1 accounting for 95.12% (39/41) and 3C.2a1b.2a.2a.1 accounting for 4.88% (2/41). The glycosylation site changes of the HA protein of A(H3N2) have been enhanced from 2023 to 2024. The 145 amino acid position of the HA protein of the A(H3N2) was the positive selection site for stress selection site analysis.Conclusions:The evolutionary subclades of the HA gene of A(H3N2) in Beijing showed changes from 2022 to 2024, and the glycosylation site polymorphism of the HA protein of A(H3N2) significantly increased from 2023 to 2024. Continuous monitoring of HA mutations in the A(H3N2) is crucial, providing a basis for developing influenza prevention and control strategies, as well as new strategic support for screening influenza vaccine components, vaccine design, and discovery of drug targets.

Objective To explore the clinical efficacy of Xingqi Tongjiang tablets in treating postprandial distress syndrome(PDS)of liver-stomach disharmony syndrome and its impact on electrogastrogram indicators.Methods A total of 300 patients with PDS were prospectively selected and randomly divided into the control group(treated with mosapride citrate+placebo of Xingqi Tongjiang tablets,n=151)and the observation group(treated with mosapride citrate+Xingqi Tongjiang tablets,n=149)according to the random number table method.The levels of traditional Chinese medicine(TCM)syndrome scores,clinical efficacy,electrogastrography indicators,negative emotion scores,quality of life scores and adverse reactions were compared between the two groups.Results After treatment,the TCM syndrome scores of both groups decreased,and the scores of the observation group were lower than those of the control group(P＜0.05).The total effective rate of the observation group was higher than that of the control group(P＜0.05).After treatment,the percentages of normal gastric slow waves(NGSW)in the overall stomach and gastric antrum before and after meals of both groups increased,and the proportion of slow waves(SR)decreased.Moreover,the increased NGSW and the decreased SR in the observation group were more significant(P＜0.05).The scores of the Hamilton Anxiety Scale(HAMA)and the Hamilton Depression Scale(HAMD)decreased after treatment in both groups,and the scores of the observation group were lower(P＜0.05).The scores of the Nepean Dyspepsia Quality of Life Index(NDLQI)increased after treatment in both groups,and the scores of the observation group were higher(P＜0.05).There were no significant differences in adverse reactions between the two groups.Conclusion Xingqi Tongjiang tablets can effectively improve the electrogastrogram indicators of patients with postprandial distress syndrome of liver-stomach disharmony syndrome,and enhance clinical efficacy.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.