Objective:To explore the molecular mechanism of a case with RhD-phenotype.Methods:A proband with RhD-phenotype who attended the clinic of the First Affiliated Hospital of Zhengzhou University on January 29, 2024 was selected as the study subject. Peripheral blood samples were collected from the proband (8 mL) and her close relatives (father, mother and brother; 3 mL each) for Rh phenotyping and irregular antibodies testing with gel card and test tube methods. Direct agglutination reaction and absorption-elution test were used to detect the c antigen on the red blood cells of the proband. PCR-sequence specific primers (PCR-SSP) typing and gene sequencing were used to determine the RHCE gene of the proband and her relatives. The origin of the proband′s variant was traced by pedigree analysis. Three-dimensional structural models of the wild-type RhCE*cE protein and the RhD-phenotype protein were constructed to predict the alterations of the RhD-phenotype protein caused by the variant. The procedures of this study were approved by the Medical Ethics Committee of the First Affiliated Hospital of Zhengzhou University (Ethics No.: 2023-KY-0870-003). Results:The red blood cells of the proband did not agglutinate with anti-C, anti-c, anti-E, and anti-e. The result of the serum irregular antibody test was negative. The results of direct agglutination reaction and absorption-elution test of the proband were both negative. Her Rh blood group was identified as RhD-. The results of the Rh blood grouping of her close relatives were normal. PCR-SSP detection showed that the RHCE genotypes of the proband and her close relatives were cE/cE and Ce/cE, respectively. Gene sequencing analysis showed that the RHCE genotypes of the proband and her close relatives were RHCE* cE (c.365C>A)/ RHCE* cE (c.365C>A) and RHCE* Ce/ RHCE* cE (c.365C>A), respectively. Pedigree analysis revealed that the variants in the proband were inherited from her father and mother, respectively. Homology modeling of RhCE*cE protein showed that the RhD-type peptide chain with a significantly shortened C-terminal was encoded by only 121 amino acid resides, which was 296 amino acid resides shorter compared to the wild-type RhCE*cE peptide chain encoded by 417 amino acid residues. Conclusion:Above results revealed the molecular biological mechanism of a RhD-phenotype. The c. 365C>A variant in the RHCE gene has rendered the RHCE* cE alleles invalid, which ultimately led to the RhD-phenotype.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

OBJECTIVE: To explore the molecular mechanism of a case with RhD-- phenotype. METHODS: A proband with RhD-- phenotype who attended the clinic of the First Affiliated Hospital of Zhengzhou University on January 29, 2024 was selected as the study subject. Peripheral blood samples were collected from the proband (8 mL) and her close relatives (father, mother and brother; 3 mL each) for Rh phenotyping and irregular antibodies testing with gel card and test tube methods. Direct agglutination reaction and absorption-elution test were used to detect the c antigen on the red blood cells of the proband. PCR-sequence specific primers (PCR-SSP) typing and gene sequencing were used to determine the RHCE gene of the proband and her relatives. The origin of the proband's variant was traced by pedigree analysis. Three-dimensional structural models of the wild-type RhCE*cE protein and the RhD-- phenotype protein were constructed to predict the alterations of the RhD-- phenotype protein caused by the variant. The procedures of this study were approved by the Medical Ethics Committee of the First Affiliated Hospital of Zhengzhou University (Ethics No.: 2023-KY-0870-003). RESULTS: The red blood cells of the proband did not agglutinate with anti-C, anti-c, anti-E, and anti-e. The result of the serum irregular antibody test was negative. The results of direct agglutination reaction and absorption-elution test of the proband were both negative. Her Rh blood group was identified as RhD--. The results of the Rh blood grouping of her close relatives were normal. PCR-SSP detection showed that the RHCE genotypes of the proband and her close relatives were cE/cE and Ce/cE, respectively. Gene sequencing analysis showed that the RHCE genotypes of the proband and her close relatives were RHCE*cE (c.365C>A)/RHCE*cE (c.365C>A) and RHCE*Ce/RHCE*cE (c.365C>A), respectively. Pedigree analysis revealed that the variants in the proband were inherited from her father and mother, respectively. Homology modeling of RhCE*cE protein showed that the RhD-- type peptide chain with a significantly shortened C-terminal was encoded by only 121 amino acid resides, which was 296 amino acid resides shorter compared to the wild-type RhCE*cE peptide chain encoded by 417 amino acid residues. CONCLUSION Above results revealed the molecular biological mechanism of a RhD-- phenotype. The c.365C>A variant in the RHCE gene has rendered the RHCE*cE alleles invalid, which ultimately led to the RhD-- phenotype.
Humans ; Rh-Hr Blood-Group System/chemistry* ; Female ; Phenotype ; Male ; Alleles ; Pedigree ; Base Sequence ; Molecular Sequence Data ; Adult

Objective:To explore the molecular mechanism of a case with RhD-phenotype.Methods:A proband with RhD-phenotype who attended the clinic of the First Affiliated Hospital of Zhengzhou University on January 29, 2024 was selected as the study subject. Peripheral blood samples were collected from the proband (8 mL) and her close relatives (father, mother and brother; 3 mL each) for Rh phenotyping and irregular antibodies testing with gel card and test tube methods. Direct agglutination reaction and absorption-elution test were used to detect the c antigen on the red blood cells of the proband. PCR-sequence specific primers (PCR-SSP) typing and gene sequencing were used to determine the RHCE gene of the proband and her relatives. The origin of the proband′s variant was traced by pedigree analysis. Three-dimensional structural models of the wild-type RhCE*cE protein and the RhD-phenotype protein were constructed to predict the alterations of the RhD-phenotype protein caused by the variant. The procedures of this study were approved by the Medical Ethics Committee of the First Affiliated Hospital of Zhengzhou University (Ethics No.: 2023-KY-0870-003). Results:The red blood cells of the proband did not agglutinate with anti-C, anti-c, anti-E, and anti-e. The result of the serum irregular antibody test was negative. The results of direct agglutination reaction and absorption-elution test of the proband were both negative. Her Rh blood group was identified as RhD-. The results of the Rh blood grouping of her close relatives were normal. PCR-SSP detection showed that the RHCE genotypes of the proband and her close relatives were cE/cE and Ce/cE, respectively. Gene sequencing analysis showed that the RHCE genotypes of the proband and her close relatives were RHCE* cE (c.365C>A)/ RHCE* cE (c.365C>A) and RHCE* Ce/ RHCE* cE (c.365C>A), respectively. Pedigree analysis revealed that the variants in the proband were inherited from her father and mother, respectively. Homology modeling of RhCE*cE protein showed that the RhD-type peptide chain with a significantly shortened C-terminal was encoded by only 121 amino acid resides, which was 296 amino acid resides shorter compared to the wild-type RhCE*cE peptide chain encoded by 417 amino acid residues. Conclusion:Above results revealed the molecular biological mechanism of a RhD-phenotype. The c. 365C>A variant in the RHCE gene has rendered the RHCE* cE alleles invalid, which ultimately led to the RhD-phenotype.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

Objective: To construct a nonsuicidal selfinjury (NSSI) risk prediction model for middle school students using different machine learning algorithms and evaluate the models effectiveness, so as to provide guidance for the prevention and control of NSSI in campus. Methods: In March 2023, a total of 3 372 middle and high school students from schools in Nanchang, Fuzhou and Shangrao cities in Jiangxi Province were selected by combining stratified random cluster sampling and convenient sampling methods. Questionnaire surveys were conducted using various instruments including general information questionnaire, Selfesteem Scale, Ottawa Selfinjury Scale, Social Support Assessment Scale, Chinese Version of the Olweus Bullying Questionnaire, Event Attribution Style Scale, Adolescent Resilience Scale, and Adolescent Life Events Scale. Data were divided into training set (n=2 361) and test set (n=1 011) at a ratio of 7∶3, and variables were selected based on univariate and LASSO regression results. Four machine learning algorithms including namely random forest, support vector machine, Logistic regression and XGBoost, were used to construct NSSI risk prediction models, and the models performance was evaluated and compared using metrics including area under curve (AUC), sensitivity, specificity, positive predictive value, negative predictive value and F1 score. Results: The detection rate of NSSI among middle school students was 34.4%. Univariate analysis showed that there were statistically significant differences in NSSI detection rates among middle school students of different grades, genders, registered residence locations, whether they were class cadres and four types of bullying (physical, verbal, relational bullying and cyberbullying) (χ2=27.17, 15.81, 11.54, 4.63；68.22, 140.63, 77.81, 13.95, P<0.05). NSSI was included as the dependent variable in the LASSO regression model for variable screening, and the results regression identified 10 predictive variables including grade level, selfesteem, subjective support, support utilization, verbal bullying, emotional control, interpersonal relationships, punishment, loss of relatives and property, and health and adaptation issues. The AUC values of random forest, support vector machine, Logistic regression, and XGBoost algorithms were 0.76, 0.76, 0.76 and 0.77, respectively, with no statistically significant differences between pairwise comparisons (Z=-0.59-0.82, P>0.05). Sensitivity values were 0.62, 0.61, 0.62 and 0.61, respectively. Specificity values were 0.74, 0.78, 0.78 and 0.78, respectively. Positive predictive values were 0.56, 0.59, 0.60 and 0.59, respectively. Negative predictive values were 0.79, 0.79, 0.80 and 0.79, respectively. F1 scores were 0.59, 0.60, 0.61 and 0.60, respectively. Conclusions All four nonsuicidal selfinjury risk prediction models perform well, with the Logistic regression model slightly outperforming the others. Schools and parents should pay attention to the predictive factors corresponding to NSSI, so as to reduce the occurrence of NSSI among middle school students.

Objective To systematically evaluate the accuracy of computer navigation technique in the positioning of bone tunnel location of anterior cruciate ligament reconstruction(ACLR) and its effect on post-operative functional recovery.Methods The controlled trials of computer navigation-assisted ACLR in the da-tabases of Cochrane Library,PubMed,Embase,CNKI,Wanfang and VIP Database were retrieved.The retriev-al time limit was from the establishment of the database to August 2023.According to the inclusion and exclu-sion criteria,the NoteExpress V3.0 software was used to screen the literatures,the Cochrane risk bias assess-ment tool was used to evaluate the quality of the included literatures,and the RevMan5.4 software was used for conducting the meta analysis.Results A total of 10 trials involving 705 patients were included,including 354 cases in the navigation group and 351 cases in the conventional group.The meta analysis results showed that compared with the conventional group,the location positioning of bone tunnel in the navigation group was significantly improved[in femoral side (MD=5.59,95％CI:1.21-9.97,P=0.01) and tibial side (MD=1.32,95％CI:0.20-2.43,P=0.02).However there were no statistically significant differences in the IKDC scores (MD=1.76,95％CI:-0.17 to 3.70,P=0.07),Lysholm scores (MD=0.49,95％CI:-0.16 to 1.14,P=0.14),Tegner scores (MD=-0.08,95％CI:-0.35 to 0.20,P=0.58),KT-1000 anterior shift dis-tance (MD=0.01,95％CI:-0.49 to 0.52,P=0.96),the positive rate of Lachman test (RD=-0.01,95％CI:-0.09 to 0.07,P=0.75) and the positive rate of axial shift test (RD=-0.09,95％CI:-0.22 to 0.04,P=0.20).Conclusion The computer navigation technology is conducive to elevate the accuracy of tibial and femoral tunnel positioning in ACLR,but could not improve the postoperative functional recovery of the pa-tients.

Objective:To evaluate the feasibility of using MRI-only simulation images for dose calculation of both photon and proton radiotherapy for nasopharyngeal carcinoma cases.Methods:T 1-weighted MRI images and CT images of 100 patients with nasopharyngeal carcinoma treated with radiotherapy in Cancer Hospital of Chinese Academy of Medical Sciences from January 2020 to December 2021 were retrospectively analyzed. MRI images were converted to generate pseudo-CT images by using deep learning network models. The training set, validation set and test set included 70 cases, 10 cases and 20 cases, respectively. Convolutional neural network (CNN) and cycle-consistent generative adversarial neural network (CycleGAN) were exploited. Quantitative assessment of image quality was conducted by using mean absolute error (MAE) and structural similarity (SSIM), etc. Dose assessment was performed by using 3D-gamma pass rate and dose-volume histogram (DVH). The quality of pseudo-CT images generated was statistically analyzed by Wilcoxon signed-rank test. Results:The MAE of the CNN and CycleGAN was (91.99±19.98) HU and (108.30±20.54) HU, and the SSIM was 0.97±0.01 and 0.96±0.01, respectively. In terms of dosimetry, the accuracy of pseudo-CT for photon dose calculation was higher than that of the proton plan. For CNN, the gamma pass rate (3 mm/3%) of the photon radiotherapy plan was 99.90%±0.13%. For CycleGAN, the value was 99.87%±0.34%. The gamma pass rates of proton radiotherapy plans were 98.65%±0.64% (CNN, 3 mm/3%) and 97.69%±0.86% (CycleGAN, 3 mm/3%). For DVH, the dose calculation accuracy in the photon plan of pseudo-CT was better than that of the proton plan.Conclusions:The deep learning-based model generated accurate pseudo-CT images from MR images. Most dosimetric differences were within clinically acceptable criteria for photon and proton radiotherapy, demonstrating the feasibility of an MRI-only workflow for radiotherapy of nasopharyngeal cancer. However, compared with the raw CT images, the error of the CT value in the nasal cavity of the pseudo-CT images was relatively large and special attention should be paid during clinical application.

Objective To establish a novel rat model of chronic skeletal muscle composite injury in the lumbar region,to explore its mechanism and treatment method in depth.Methods Twenty-eight SD rats were randomly divided into control group(n = 10),Hitting injury model(HIM)group(n = 9),Composite damage model(CDM)group(n = 9)(vertical blow combined with forced prolonged sitting).Open field test,HE staining and PCR sequencing were performed 3 days after modeling.Results The open field distance of rats in HIM group was significantly shorter than that in the CDM group,and both groups had shorter distances than the control group.HE staining showed multiple muscle fiber breaks,significant widening of muscle gaps,uneven distribution of muscle nuclei,and visible congestion in the model group of simple blow injury;In the CDM group,muscle fibers were ruptured,the muscle gaps were slightly widened,and inflammatory cell infiltration was observed between the muscles,especially around the muscle fiber breakage,with muscle fiber nuclei gathering.A volcano plot of the sequencing result suggested significant differences in the Pf4 gene.GO analysis of muscle tissue in model group rats showed upregulation of oxygen binding and carrier activity pathways.Conclusions This study attempted to establish a composite skeletal muscle injury model to study the pathological changes of chronic skeletal muscle injury in the low back pain and evaluate the efficacy of treatment method.It has practical application value in animal experiments for chronic non-specific low back pain.

Objective:To investigate the correlations between perfused lung volumes, visual scores (using perfusion SPECT/CT) and right-heart catheter (RHC) hemodynamic parameters in patients with chronic thromboembolic pulmonary hypertension (CTEPH).Methods:A total of 51 consecutive CTEPH patients (17 males, 34 females, age (59±12) years) in the First Affiliated Hospital of Guangzhou Medical University between March 2015 and July 2019 were retrospectively analyzed. All patients underwent lung perfusion SPECT/CT imaging and RHC examinations. Perfused lung volumes were determined using threshold-based (15%-85%) segmentation. Visual semiquantitative scoring in each lung segment was performed using Begic method. RHC hemodynamic parameters including pulmonary artery systolic pressure (PASP), pulmonary arterial diastolic pressure (PADP), mean pulmonary artery pressure (mPAP), pulmonary arteriolar wedge pressure (PAWP), pulmonary vessel resistance (PVR), cardiac output (CO), cardiac index (CI) were recorded. Spearman correlation analysis was used to evaluate the correlations between perfused lung volumes, visual scores and hemodynamic parameters.Results:There were significant correlations between perfused lung volumes (30%-70% threshold) and mPAP ( rs values: from -0.414 to -0.302, all P<0.05). Among them, perfused lung volumes under the threshold of 40% and 45% were moderately correlated with mPAP ( rs values: -0.414, -0.412, both P<0.05). Perfused lung volume (40% threshold) was moderately negatively correlated with PASP, PADP ( rs values: -0.402, -0.440, both P<0.05), and slightly negatively correlated with PVR ( rs=-0.352, P<0.05). Visual scores were slightly positively correlated with the PADP ( rs=0.311, P<0.05), while there was no correlation between visual scores and other RHC hemodynamic parameters ( rs values: from -0.201 to 0.275, all P>0.05). Conclusion:Perfused lung volumes based on threshold-based segmentation in lung perfusion SPECT/CT imaging can accurately reflect hemodynamic status and may provide useful information for severity assessment of CTEPH.