Objective: To analyze the etiological surveillance results of influenza-like illness (ILI) cases in Jiangsu Province, and investigate the distribution characteristics of different influenza virus types, so as to provide the evidence for improving influenza prevention and control measures. Methods: Influenza laboratory testing data for sentinel surveillance of ILI cases in Jiangsu Province from 2019 to 2024 were collected through the China Influenza Surveillance Information System. The positive detection rate of influenza virus was calculated, and descriptive analysis was performed to characterize the distribution of different influenza virus types. Using the farthest neighbor linkage method, influenza virus positive detection rates clustering was analyzed by year and week. Clusters were defined based on inter-cluster distance, and the intensity of the positive detection rate was visualized through color gradients in the clustering heatmap. Results: From 2019 to 2024, a total of 183 878 ILI specimens were collected in Jiangsu Province. Among them, 20 059 specimens tested positive for influenza virus, corresponding to an overall positive detection rate of 10.91%, and an average annual positive detection rate of 10.89%. The primary circulating influenza virus types were influenza A H3N2 subtype, accounting for 40.92%, followed by influenza B Victoria linage at 34.00%, and influenza A H1N1 subtype at 24.80%. Influenza B Yamagata linage was not detected throughout the five-year period. Influenza A H3N2 subtype predominated during two distinct periods: from January to March 2019, and from June 2022 to December 2023. Influenz B Victoria linage was the dominant type from April 2019 to May 2022 and again from January to April 2024. Influenza A H1N1 subtype emerged as the primary type from May to December 2024. Year-based clustering analysis grouped the annual positive detection rates from 2019 to 2024 into three clusters. The closest cluster distance was observed between 2019 and 2024. The highest annual positive detection rate occurred in 2023. Both influenza A H3N2 and H1N1 subtype each formed a single cluster, with their peak positive detection rates also recorded in 2023. Influenza B Victoria lineage was separated into two clusters, with its highest positive detection rate occurring in 2020. Week-based clustering analysis revealed that influenza virus detection was concentrated in weeks 47 to 52 and weeks 1 to 15. More specifically, the positive detection rates for influenza A H3N2 subtype peaked during weeks 30 to 34 and weeks 42 to 52; for influenza A H1N1 subtype, during weeks 9 to 15 and weeks 51 to 52; and for influenza B Victoria lineage, during weeks 1 to 11 and weeks 50 to 52. Conclusions From 2019 to 2024, the average annual positive detection rate of influenza virus in Jiangsu Province remained relatively low. Influenza activity characterized by the alternating circulation of influenza A H1N1 subtype, influenza A H3N2 subtype, and influenza B Victoria linage. It is necessary to maintain the surveillance sensitivity for the influenza B Yamagata lineage.

Objective Objective To analyze the potential spatial factors affecting the genetic differentiation of Oncomelania hupensis robertsoni in Yunnan Province. Methods A total of 13 administrative villages were selected from schistosomiasis-endemic areas of Yunnan Province as O. hupensis snail sampling sites. At least 200 snails were collected in each site, and the spatial variable data of each site were recorded, including longitude, latitude and altitude. Thirty active and Schistosoma japonicum uninfected O. hupensis snails were selected from each sampling site by means of the crawling method and the cercarial shedding method. Genomic DNA was extracted from O. hupensis snails. Following PCR amplification, purification of PCR amplification products and sequencing, the gene sequences of O. hupensis snail samples were spliced and edited using the DNAstar software and the NCBI database to yield the complete mitochondrial sequences of O. hupensis snails at each sampling site, and the mitochondrial genetic distance matrix of O. hupensis robertsoni was calculated at each sampling site. The geographical coordinates of each sampling site were marked using the software ArcGIS 10.2, and the straight-line geographical distance between each sampling site was calculated. The altitude difference, longitude difference and latitude difference between each sampling site were calculated using the Excel software, and the correlation between the mitochondrial genetic distance matrix of O. hupensis robertsoni and each spatial variable matrix was examined by using the Mantel test at 13 sampling sites in Yunnan Province. Results Among the 13 O. hupensis snail sampling sites in Yunnan Province, the largest mitochondrial genetic distance of O. hupensis robertsoni snail populations was seen between Anding Village, Nanjian Yi Autonomous County and Caizhuang Village, Midu County (26.244 2), and the largest geographical distance was seen between Dongyuan Village, Gucheng District and Cangling Village, Chuxiong County (272.64 km). The highest altitude difference was seen between Anding Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1 086.10 m), and the largest longitude difference was found between Qiandian Village, Eryuan County and Cangling Village, Chuxiong County (1.86°), while the largest latitude difference was measured between Leqiu Village, Nanjian Yi Autonomous County and Dongyuan Village, Gucheng District (1.81°). In addition, the mitochondrial genetic distance of O. hupensis robertsoni snail populations was positively correlated with altitude at 13 snail sampling sites in Yunnan Province (r = 0.542 8, P < 0.001), and showed no significant correlations with geographical distance (r = 0.093 4, P > 0.05), longitude (r = −0.199 5, P > 0.05) or latitude (r = 0.205 7, P > 0.05). Conclusion Altitude may be a potential spatial factor affecting the genetic differentiation of O. hupensis robertsoni in Yunnan Province.

Objective To evaluate the efficacy and safety of 450nm semiconductor blue laser vaporization prostatectomy in high-risk benign prostatic hyperplasia (BPH) patients without discontinuing anticoagulant drugs, so as to provide a safe and effectiveminimally invasive treatment option for such patients. Methods A total of 40 high-risk BPH patients who underwent 450nm semiconductor blue laser vaporization prostatectomy in our hospital during Sep. 2023 and Dec. 2024 were selected as the research subjects. The patients were divided into two groups: the oral medication group took oral anticoagulants during the perioperative period, while the discontinuation group discontinued anticoagulants, with 20 cases in either group. The perioperative indicators and changes including international prostate symptom score (IPSS), quality of life score (QoL), maximum urinary flow rate (Qmax) and post-void residual (PVR) were compared between the two groups.Results There were no statistically significant differences between the oral medication group and discontinuation group in operation time [(28.83±15.52)min vs. (26.43±14.02)min], postoperative catheter indwelling time [(3.04±0.89) d vs. (3.23±1.01) d], bladder irrigation time [(27.36±7.54) h vs. (25.46±7.10) h], and decrease in hemoglobin [(8.08±1.82)g/L vs. (7.56±1.68)g/L] (all P＞0.05). Three month after surgery, Qmax in both groups was higher, while IPSS, QoL and PVR were significantly lower (P＜0.05), but there were no statistically significant differences between the two groups (P＞0.05). No serious complications such as urinary incontinence or massive hemorrhage occurred.Conclusion 450nm semiconductor blue laser vaporization prostatectomy for high-risk BPH patients is characterized by high vaporization efficiency and good hemostatic effects. It can significantly improve the clinical symptoms with high safety, especially for high-risk patients who cannot discontinue anticoagulants.

Objective: To analyze the change trends in the body shape indicators and proportions of students in Harbin from 2010 to 2024, and to investigate ergonomic compatibility of functional dimensions of school desks and chairs with current student shape indicators, so as to provide a reference for revising furniture standards of desks and chairs. Methods: Between September and November of both 2010 and 2024, a combination of convenience sampling and stratified cluster random sampling was conducted across three districts in Harbin, yielding samples of 6 590 and 6 252 students, respectively. Anthropometric shape indicators cluding height, sitting height, crus length, and thigh length-and their proportional changes were compared over the 15-year period. The 2024 data were compared with current standard functional dimensions of school furniture. The statistical analysis incorporated t-test and Mann-Whitney U- test. Results: From 2010 to 2024, average height increased by 1.8 cm for boys and 1.5 cm for girls; sitting height increased by 1.5 cm for both genders; crus length increased by 0.3 cm for boys and 0.4 cm for girls; and thigh length increased by 0.5 cm for both genders. The ratios of sitting height to height, and sitting height to leg length increased by less than 0.1 . The difference between desk chair height and 1/3 sitting height ranged from 0.4-0.8 cm. Among students matched with size 0 desks and chairs, 22.0% had a desk to chair height difference less than 0, indicating that the desk to chair height difference might be insufficient for taller students. The differences between seat height and fibular height ranged from -1.4 to 1.1 cm; and the differences between seat depth and buttock popliteal length ranged from -9.8 to 3.4 cm. Among obese students, the differences between seat width and 1/2 hip circumference ranged from -20.5 to -8.7 cm, while it ranged from -12.2 to -3.8 cm among non obese students. Conclusion Current furniture standards basically satisfy hygienic requirements; however, in the case of exceptionally tall and obese students, ergonomic accommodations such as adaptive seating allocation or personalized adjustments are recommended to meet hygienic requirements.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

OBJECTIVE: To evaluate the safety and effectiveness of robot-assisted percutaneous coronary intervention (R-PCI) compared to traditional manual percutaneous coronary intervention (M-PCI). METHODS: This prospective, multicenter, randomized controlled, non-inferior clinical trial enrolled patients with coronary heart disease who met the inclusion criteria and had indications for elective percutaneous coronary intervention. Participants were randomly assigned to either the R-PCI group or the M-PCI group. Primary endpoints were clinical and technical success rates. Clinical success was defined as visually estimated residual post-percutaneous coronary intervention stenosis < 30% with no 30-day major adverse cardiac events. Technical success in the R-PCI group was defined as successful completion of percutaneous coronary intervention using the ETcath200 robot-assisted system, without conversion to M-PCI in the event of a guidewire or balloon/stent catheter that was unable to cross the vessel or was poorly supported by the catheter. Secondary endpoints included total procedure time, percutaneous coronary intervention procedure time, fluoroscopy time, contrast volume, operator radiation exposure, air kerma, and dose-area product. RESULTS: The trial enrolled 152 patients (R-PCI: 73 patients, M-PCI: 79 patients). Lesions were predominantly B2/C type (73.6%). Both groups achieved 100% clinical success rate. No major adverse cardiac events occurred during the 30-day follow-up. The R-PCI group had a technical success rate of 100%. The R-PCI group had longer total procedure and fluoroscopy times, but lower operator radiation exposure. The percutaneous coronary intervention procedure time, contrast volume, air kerma, and dose-area product were similar between the two groups. CONCLUSIONS For certain complex lesions, performing percutaneous coronary intervention using the ETcath200 robot-assisted system is safe and effective and does not result in conversion to M-PCI.

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

Intestinal fibrosis is a significant clinical challenge in inflammatory bowel diseases, but no effective anti-fibrotic therapy is currently available. Glucagon receptor (GCGR) and glucagon-like peptide 1 receptor (GLP1R) are both peptide hormone receptors involved in energy metabolism of epithelial cells. However, their role in intestinal fibrosis and the underlying mechanisms remain largely unexplored. Herein GCGR and GLP1R were found to be reduced in the stenotic ileum of patients with Crohn's disease as well as in the fibrotic colon of mice with chronic colitis. The downregulation of GCGR and GLP1R led to the accumulation of the metabolic byproduct lactate, resulting in histone H3K9 lactylation and exacerbated intestinal fibrosis through epithelial-to-mesenchymal transition (EMT). Dual activating GCGR and GLP1R by peptide 1907B reduced the H3K9 lactylation in epithelial cells and ameliorated intestinal fibrosis in vivo. We uncovered the role of GCGR/GLP1R in regulating EMT involved in intestinal fibrosis via histone lactylation. Simultaneously activating GCGR/GLP1R with the novel dual agonist peptide 1907B holds promise as a treatment strategy for alleviating intestinal fibrosis.

HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.

OBJECTIVES: To analyze bone mass distribution and the factors affecting bone mass in a general Chinese Han cohort undergoing physical examinations at our center. METHODS: We retrospectively collected the data of bone mineral density (BMD) measurements from 30 599 healthy Han Chinese adults (age≥20 years) who underwent dual-energy X-ray absorptiometry scans at our hospital from July, 2013 to July, 2023. Basic parameters including height, body weight, and gender were recorded, and descriptive statistics and correlation analyses were performed using R software. RESULTS: In this cohort, the male individuals had a mean peak BMD of 1.00±0.12 g/cm² in the lumbar vertebrae, 0.94±0.14 g/cm² in the femoral neck, and 0.99±0.13 g/cm² in the total hip, significantly higher than the values in the female individuals [0.99±0.12 g/cm² in the lumbar vertebrae (P=0.022), 0.79±0.11 g/cm² in the femoral neck (P<0.001), and 0.88±0.11 g/cm² in the total hip (P<0.001)]. In the overall cohort, the BMD values of the lumbar spine and femur decreased with age after reaching their peak levels. There was a positive correlation between BMD value and body mass index (BMI) in both male and female individuals. The 2013-2014 period recorded the lowest BMD values in the lumbar, hip, and femoral neck, which tended to increase steadily in the following years (2015-2023). CONCLUSIONS Our data suggest that the BMD values vary among different populations, and future multi-center studies using more accurate BMD detection technology are warranted to capture the variation patterns of BMD with demographic characteristics of specific populations.
Humans ; Bone Density ; Absorptiometry, Photon ; Male ; Female ; Retrospective Studies ; Osteoporosis/diagnostic imaging* ; Adult ; Middle Aged ; Lumbar Vertebrae/diagnostic imaging* ; China/epidemiology* ; Femur Neck/diagnostic imaging* ; Aged ; Beijing/epidemiology* ; Young Adult