Objective: To conduct screening for rare blood types within important blood group systems for the Chinese population, such as Rh, Duffy, Kidd, P1Pk, Diego, and MNS, in the Guangzhou region, and to establish a corresponding rare blood type database and physical repository. Methods: The saline medium microplate method was used to screen blood donors with the ccDEE phenotype combined with either Jk(a-) or Jk(b-). The polybrene microplate method was employed to screen for donors with Fy(a-), s(-), Lu(b-), Di(b-), k(-), and p phenotypes. The urea lysis microplate method was applied to screen for the Jk(a-b-) phenotype. A high-resolution melting (HRM) curve method was established for screening some donors with the Di(b-) phenotype. Subsequently, expanded phenotyping of antigens in the Rh, Kidd, MNS, Duffy, P1Pk, Lewis, Kell, and Lutheran blood group systems was performed on identified rare blood type donors using monoclonal antibodies. The test results are entered into the Rare Blood Type Bank Management System of the Guangzhou Blood Center, enabling functions such as confirmation reminders and cryopreservation storage when the donor donates again. Red blood cells of rare blood types are processed into frozen red blood cells for long-term storage. Results: Among voluntary blood donors, 16 cases of the ccDEE combined with Jk(a-) phenotype were identified (0.221 7%, 16/7 216); 10 cases of the ccDEE combined with Jk(b-) phenotype (0.138 6%, 10/7 216); 78 cases of the Fy(a-) phenotype (0.169 5%, 78/46 012); 39 cases of the Lu(b-) phenotype (0.138 2%, 39/28 214); 31 cases of the s(-) phenotype (0.081 8%, 31/37 913); 22 cases of the Di(b-) phenotype (0.029 9%, 22/73 691); 30 cases of the Jk(a-b-) phenotype (0.010 1%, 30/298 250); and 1 case of the k(-) phenotype (0.001 3%, 1/77 382), which was further identified as KELnull phenotype (K0). No p phenotype donors were identified (0/88 528). A total of 228 units of frozen red blood cells were prepared. The screening results were compared and analyzed with rare blood type data from other regions. Conclusion: This study, through a combination of different screening methods, significantly improved the efficiency of rare blood type screening while remaining cost-effective. By conducting large-scale screening and performing data informatization processing, a database and physical repository of rare blood types in the Guangzhou region were successfully established. This provides a strong guarantee for the timely supply of blood to patients with difficult-to-match and rare blood types in the region, effectively enhances the level of transfusion safety in the region, and offers a practical paradigm for constructing a comprehensive blood transfusion support system.

OBJECTIVE To provide guidance for the individualized use of antiepileptic drugs （AEDs） in patients with epilepsy or bipolar affective disorder.METHODS Clinical data of patients with epilepsy or bipolar affective disorder who received AEDs treatment and underwent therapeutic drug monitoring （TDM） at Xi’an International Medical Center Hospital from January 2023 to December 2025 were retrospectively collected. The baseline information， characteristics of AEDs utilization， implementation status of TDM and laboratory parameters were summarized. Spearman correlation analysis， univariate analysis and multivariate linear regression analysis were performed to identify the independent influencing factors for blood concentrations of AEDs.RESULTS A total of 1 572 patients were enrolled， including 660 males and 912 females. The majority were aged ≥60 years （30.15%）； 71.76% of patients were on monotherapy with AEDs， with valproic acid being the most commonly prescribed （51.97%）； combination therapy was predominantly a two-drug regimen （26.21%）， while three-drug regimens were rare （2.04%）. A total of 2 901 blood samples for TDM were collected， with the highest number of samples for valproic acid and levetiracetam （1 987 and 684 samples， respectively）. TDM for all five drugs was primarily conducted once； among which， the blood concentrations attainment rates exceeded 50% for patients taking valproic acid and levetiracetam， while the median blood concentrations for patients taking lamotrigine， oxcarbazepine， and carbamazepine were all below the lower limit of the therapeutic reference range. Based on the results of Spearman correlation analysis， univariate analysis， and multivariate linear regression analysis， patient gender， platelet count （PLT）， alanine transaminase （ALT）， aspartate transaminase （AST）， and total bilirubin （TBil） were found to be independent factors influencing blood concentration of valproic acid （unstandardized coefficients were －6.770 7， －0.078 6， －0.099 4， 0.083 2， －0.578 9， P ＜0.05）， while age and creatinine （CRE） were found to be independent factors influencing blood concentration of levetiracetam （unstandardized coefficients were 0.108 7， 0.047 8， P ＜0.05）.CONCLUSIONS Female gender and elevated AST levels are risk factors for increased blood concentration of valproic acid， while elevated PLT， ALT and TBil levels are associated with decreased blood concentration of valproic acid. Patients of advanced age and those with renal insufficiency bear a relatively high risk of in vivo levetiracetam accumulation.

OBJECTIVE To construct three-class （insufficient， normal， excessive） and two-class （insufficient， normal） models for predicting plasma concentration of valproic acid （VPA）， and compare the performance of these two models， with the aim of providing a reference for formulating clinical medication strategies. METHODS The clinical data of 480 patients who received VPA treatment and underwent blood concentration test at the Xi’an International Medical Center Hospital were collected from November 2022 to September 2024 （a total of 695 sets of data）. In this study， predictive models were constructed for target variables of three-class and two-class models. Feature ranking and selection were carried out using XGBoost scores. Twelve different machine learning algorithms were used for training and validation， and the performance of the models was evaluated using three indexes: accuracy， F1 score， and the area under the working characteristic curve of the subject （AUC）. RESULTS XGBoost feature importance scores revealed that in the three-class model， the importance ranking of kidney disease and electrolyte disorders was higher. However， in the two-class model， the importance ranking of these features significantly decreased， suggesting a close association with the excessive blood concentration of VPA. In the three-class model， Random Forest method performed best， with F1 score of 0.704 0 and AUC of 0.519 3 on the test set； while in the two-class model， CatBoost method performed optimally， with F1 score of 0.785 7 and AUC of 0.819 5 on the test set. CONCLUSIONS The constructed three-class model has the ability to predict excessive VPA blood concentration， but its prediction and model generalization abilities are poor； the constructed two-class model can only perform classification prediction for insufficient and normal blood concentration cases， but its model performance is stronger.

Objective: To analyze the temporal variation patterns of sickness absenteeism among primary and secondary school students in Shanghai, so as to explore models suitable for predicting peaks and intensity of absenteeism rates. Methods: The seasonal and trend decomposition using loess (STL) method was used to analyze the seasonal and long term trend changes in sickness absenteeism among primary and secondary school students from September 1 in 2010 to June 30 in 2018, in Shanghai. A hierarchical clustering method based on Dynamic Time Warping (DTW) was employed to classify absenteeism symptoms with similar temporal patterns. Based on historical data, the study constructed and evaluated different time series algorithms and machine learning models to optimize the accuracy of predicting the trend of sickness absenteeism. Results: During the research period, the average new absenteeism rate due to illness was 16.86 per 10 000 person day for every academic year, and the trend of sickness absenteeism exhibited both seasonality and a long term upward trend, reaching its highest point in the 2017 academic year (22.47 per 10 000 person day). The symptoms of absenteeism were divided into three categories: high incidence in winter and spring (respiratory symptoms, fever and general discomfort, etc.), high incidence in summer (eye symptoms, nosebleeds, etc.) and those without obvious seasonality (skin symptoms, accidental injuries, etc.).The constructed time series models effectively predicted the trend of absenteeism due to illness, although the accuracy of predicting peak intensity was relatively low. Among them, the multi layer perceptron (MLP) model performed the best, with an root mean squared error (RMSE) of 8.96 and an mean absolute error (MAE) of 4.37, reducing 36.51% and 39.02% compared to the baseline model. Conclusion Time series models and machine learning algorithms could effectively predict the trend of sickness absenteeism, and corresponding prevention and control measures can be taken for absenteeism caused by different symptoms during peak periods.

ObjectiveTo understand the infection characteristics and drug resistance of carbapenem-resistant Serratia marcescens (CRSM) in a general hospital in Shanghai, and to provide a theoretical basis for clinical anti-infective treatment and prevention of drug-resistant bacteria. MethodsClinical data on cases with CRSM infections detected in clinical specimens at a gradeⅢ level A general hospital in Shanghai from June 2022 to June 2024 were retrospectively collected, and their clinical distributions, factors of hospital-acquired infections, prognosis, and drug-resistant situation were analyzed simultaneously. ResultsA total of 38 cases with CRSM were detected from June 2022 to June 2024, and the number of CRSM strains accounted for 25.00% (38/152) of the number of SM strains. The 38 CRSM infection samples were all derived from sputum. CRSM were distributed in 9 clinical departments, and the top 3 departments having the highest percentages of CRSM among SM strains, were intensive care unit (ICU) (78.79%, 26/33), gastrointestinal surgery department (57.14%, 4/7), and thyroid hernia surgery department (50.00%, 1/2). Among the 38 patients with CRSM infections, 8 cases were identified as hospital-acquired infection, resulting in a hospital-acquired infection rate of 21.05. The mortality rate of the 38 cases of CRSM infected patients within 30 days after detection of CRSM was 23.68% (9/38). The results of multivariate logistic regression analysis showed that sequential organ failure assessment (SOFA) score ≥6.5 points (OR=15.33, P<0.001), septic shock (OR=4.85, P=0.032), and suffering from neoplastic diseases (OR=0.12, P=0.018) were the related factors for death within 30 days after the detection of CRSM in patients with CRSM infection. The results of drug sensitivity test showed that the 38 cases of CRSM exhibited 100.00% (38/38) sensitivity to trimethoprim/sulfamethoxazole, tigecycline, or ceftazidime/avibactam; demonstrated high resistance toβ-lactams except for ceftazidime (18.42%, 7/38), the latter of which was one of the third-generation of cephalosporins; showed elevated resistance to fluoroquinolones [levofloxacin (89.47%, 35/38), ciprofloxacin (94.74%, 36/38)]; maintained good tetracycline sensitivity [doxycycline (97.37%, 37/38), minocycline (76.32%, 29/38)]; and displayed high susceptibility to the aminoglycoside gentamicin (94.74%, 36/38) and elevated resistance to tobramycin (86.84%, 34/38). The detection rate of serine carbapenemase in the 38 strains of CRSM was 100.00%, while all strains tested negative for metallo-β-lactamases. ConclusionFrom June 2022 to June 2024, the detection rate of CRSM in a gradeⅢ level A general hospital in Shanghai was relatively high, especially in the ICU. CRSM has a high resistance rate to commonly used antibacterial drugs such as the first and second-generation cephalosporins, quinolones, and polypeptide antibacterial drugs. Therefore the dynamics of drug-resistant bacteria should be tracked in a timely manner to guide the rational clinical application of antibacterial drugs.

Objective To investigate the correlation between immune cells and the occurrence of cardiovascular disease(CVD)in patients with human immunodeficiency virus/acquired immunodeficiency syndrome(HIV/AIDS),and to construct a risk prediction model.Methods A total of 280 HIV/AIDS patients treated from June 2024 to August 2025 were selected as the research subjects and divided into a training set(n=200)and a test set(n=80)at a ratio of 5:2.The patients in the training set were subdivided into a CVD subgroup(n=60)and a non-CVD subgroup(n=140)according to whether they developed CVD.The baseline characteristics and immune cells of the two groups were compared,and the longitudinal trajectory changes of immune cells in the CVD subgroup and the non-CVD subgroup were analyzed.LASSO regression analysis was used to screen the independent influencing factors of CVD,multivariate Logistic regression analysis was used to screen the independent risk factors for the occurrence of CVD,and a risk prediction nomogram model was constructed.The area under the receiver operating characteristic(ROC)curve(AUC),Hosmer-Lem show test,calibration curve,and decision curve were used to compare the risk prediction nomogram model with the general cardiovascular risk assessment model,to evaluate its discrimination,goodness-of-fit,and clinical utility.Results There were significant differences in the baseline characteristics and immune cells between the two groups(P<0.05).The longitudinal trajectory plots revealed that the CD4+count,CD8+count,and CD4+/CD8+level in the CVD group exhibited substantial fluctuations,while the trajectories of these parameters in the non-CVD group remained relatively stable.After LASSO regression analysis screened out 11 non-zero coefficient variables,multivariate logistic regression analysis showed that age,hypertension,total cholesterol,smoking,high-sensitivity C-reactive protein,CD4+count at the time of HIV diagnosis,CD8+count at the time of HIV diagnosis,and globulin were all independent influencing factors for the occurrence of CVD in HIV/AIDS patients(P<0.05).The AUC of the risk prediction nomogram model was 0.960 in the training set and 0.914 in the test set,indicating good discrimination of the model.The Hosmer-Lem show test and calibration curve showed good accuracy and consistency of the model,and the decision curve showed a high net benefit value,indicating good clinical utility.Conclusion The CVD risk in HIV/AIDS patients is jointly affected by immune dysfunction and traditional metabolic factors.The risk prediction nomogram model constructed significantly improves the accuracy of risk prediction of CVD and can provide a basis for early identification of high-risk patients and the formulation of individualized intervention strategies.

Objective:To investigate the distribution of CGG repeat numbers in the FMR1 gene among reproductive-age women in China, providing data reference for carrier screening and genetic counseling of Fragile X syndrome. Methods:This cross-sectional study recruited 16 610 reproductive-age women from 12 medical institutions between July 2022 and October 2023. Peripheral venous blood samples (3 mL) were collected, and genomic DNA was extracted. The number of CGG repeats in the FMR1 gene was determined using the triplet-primed polymerase chain reaction (TP-PCR) combined with capillary electrophoresis technology. Statistical analyses were performed to assess the prevalence and distribution of CGG repeat expansions. Results:Among 16 610 women of childbearing age, 5 684 (34.220%) women had the same number of CGG repeats in the two alleles of FMR1 gene, and 10 926 (65.780%) women had different numbers of repeats in the two alleles. Among the 33 220 FMR1 alleles in 16 610 women of reproductive age, the most common CGG repeat numbers were 29 [48.645% (16 160/33 220)] and 30 [26.276% (8 729/33 220)], while the most frequent CGG genotype was CGG 29/29 [24.726% (4 107/16 610)]. The CGG repeat numbers of FMR1 gene were normal in 16 498 women (99.326%). Among the 112 women (0.674%) with CGG repeat abnormities, 96 (0.578%) women were classified as intermediate carriers, 15 (0.090%) as premutation carriers, and 1 (0.006%) as a full mutation carrier, whose CGG genotype was (36, >200). Conclusion:In the general reproductive-age female population in China, the normal CGG repeat numbers of the FMR1 gene account for 99.326%, while the intermediate carrier rate is 0.578%, and the combined carrier rate of the premutation and full mutation types is 0.096%.

Objective To investigate the effects of three types of twin-block(TB)appliances on the stress and displacement of anterior teeth,periodontal ligaments,and alveolar bone.Methods A three-dimensional(3D)finite element model was constructed,including maxillofacial bones,articular discs,teeth,and periodontal ligaments.Three types of twin-block appliances were designed:classic twin-block(classic-TB),twin-block with acrylic capping(capping-TB),and clear twin-block aligner(CTBA).All appliances had an inclination angle of 70°,and a masticatory force of 200 N was applied to their inclined planes.The finite element method was used to analyze the stress distribution and displacement differences of anterior teeth.Results All three types of TB appliances induced lingual tilting of maxillary anterior teeth and labial tilting of mandibular anterior teeth.The CTBA group showed the greatest lingual displacement and stress of maxillary anterior teeth,with a maximum stress of 30.6 MPa,while the mandibular anterior teeth in this group exhibited the smallest labial displacement(approximately 0.02 mm)and stress.Additionally,the CTBA group had the lowest compressive stress in mandibular anterior teeth,periodontal ligaments,and alveolar bone,whereas the classic-TB group had the highest.Conclusions In the treatment of Angle Class Ⅱ malocclusion,classic-TB(with or without acrylic capping)causes labial inclination of mandibular anterior teeth.Compared with classic-TB,CTBA effectively reduces the compressive stress and displacement of mandibular anterior teeth,potentially minimizing adverse periodontal risks.However,attention should be paid to the lingual displacement of maxillary anterior teeth.

Patients with severe periodontal disease often involve multidisciplinary therapy.This paper reports a case of adult patients with severe periodontitis who was treated by orthodontics,restoration,and periodontics.The space between upper central incisors was closed,aesthetics and periodontal conditions were significantly improved.

Objective:To investigate gut microbiota differences between individuals with and without colorectal adenoma(CRA)and to identify gut microbes associated with CRA.Methods:This cross-sectional study analyzed the gut microbiota of 100 patients with CRA and 68 individuals without CRA(aged 40-75 years)who underwent colonoscopies between March 2021 and March 2022 at Tianjin Nankai Hospital.Fecal samples were sequenced for the V3-V4 region of the bacterial 16S rRNA gene using the Illumina NovaSeq platform.Results:Compared to the non-CRA group,the CRA group exhibited reduced relative abundances of identified and unidentified Lachnospiraceae,with increased Faecalibacterium and Streptococcus.In the non-CRA group,the relative abundances of Coprococcus,unidentified Clostridiaceae,and Clostridium were higher.LEfSe analysis revealed significant enrichment of Gammaproteobacteria,Proteobacteria,Enterobacteriales,and Faecalibacterium in the CRA group,while the non-CRA group was enriched for Moraxellaceae,Acinetobacter,and Anaerostipes.Conclusions:These findings suggest a discernible disparity in the gut microbiota structure between CRA patients and individuals without adenoma.The enrichment of potential pathogenic taxa,such as Faecalibacterium and Streptococcus,in the CRA group suggests a possible association with adenoma development.