Objective: To identify the structure of the complementarity determining region (CDRs), the V(D)J rearrangement and somatic hypermutational characteristics of the heavy and light chains of a red blood cell blood group-specific monoclonal antibody. Methods: The hybridoma cell line secreting human IgM κ monoclonal anti-P antibody was used as the research object. Total RNA was extracted from cultured monoclonal cell line, and cDNA was obtained by reverse transcription PCR (RT-PCR) using random hexamers primers. It was then amplified and sequenced using primers specific for variable regions of the immunoglobulin heavy and light chains encoding the anti-P antibody. The sequences were aligned against the NCBI database using online Immunoglobulin BLAST (Ig-BLAST) tool. Results: The study determined the structure of the CDRs and framework regions (FRs) of the variable regions of human monoclonal anti-P immunoglobulin, as well as the characteristics of V(D)J rearrangement. Moreover, the closest VH, VD, and VJ germline alleles for the heavy chain and VL and VJ germline alleles for the light chain were also identified. The IgH gene rearrangment pattern of the monoclonal anti-P was IGHV6-1 * 01—IGHD5-18 02—IGHJ4 02 and IgL gene was IGκV1-12 01—IGκJ3 01. Nine base mutations occurred within the germline gene IGHV6-1 01 in variable region of heavy chain, whereas 5 base mutations were found in the germline gene IGκV1-12 01 in variable region of light chain, respectively. Conclusion: This study characterized the CDR structure in monoclonal antibody cell line targeting the high-frequency red blood cell P antigen, and provided a foundation for the construction of recombinant antibody expressing plasmids and transfomation of the immunoglobulin type.

Objective To analyze the clinical and therapeutic characteristics of Epstein-Barr virus (EBV)-negative posttransplant lymphoproliferative disease (PTLD) with diffuse large B-cell lymphoma (DLBCL) in the context of specific cases and literature. Methods A case of EBV-negative DLBCL (GCB type) after kidney transplantation is reported. The patient was a 45-year-old male who underwent living-related kidney transplantation in 2016 and has been receiving triple immunosuppressive therapy with tacrolimus, mycophenolate mofetil and methylprednisolone since then. In 2024, the patient presented with intermittent fever, night sweats and gastrointestinal symptoms. The diagnosis was confirmed by endoscopic pathology, immunohistochemical staining and positron emission tomography/computed tomography. The R-CDOP regimen (rituximab + cyclophosphamide + liposomal doxorubicin + vincristine + dexamethasone) was used for treatment. Results The patient was diagnosed with EBV-negative DLBCL (GCB type, Ann Arbor stage Ⅳ B). After 4 cycles of R-CDOP chemotherapy, the efficacy assessment was partial remission, and the transplant kidney function remained stable. Conclusions For EBV-negative PTLD after kidney transplantation, it is necessary to break through the "virus-dependent" diagnostic thinking. In clinical practice, the focus should be on protecting the transplant kidney, and individualized treatment plans should be developed for patients.

BACKGROUND:Although previous studies have reported associations between lipids and the risk of osteoporotic pathological fractures,the specific causal relationships between lipid level and osteoporotic pathological fractures remain unclear.OBJECTIVE:To elucidate the causal relationship between lipids and osteoporotic pathological fractures using a two-sample bidirectional Mendelian randomization analysis.METHODS:The data for 178 lipid metabolites were obtained from the IEU-GWAS database(developed by the MRC Integrative Epidemiology Unit at the University of Bristol,UK,which provides extensive summary data from genome-wide association studies),while osteoporotic pathological fracture data(from 173 619 European participants)were acquired from the FinnGen database(constructed by the Finnish national gene research program,focusing on investigating relationships between genomics and health/disease in the Finnish population).Osteoporotic pathological fracture data were used as the outcome variable,with lipids serving as exposures,for the bidirectional Mendelian randomization study to evaluate the causal effects of different lipids on osteoporotic pathological fractures.The UK Biobank database was employed as a validation set by switching the outcome variable to verify the findings horizontally.RESULTS AND CONCLUSION:(1)The inverse variance weighted analysis indicated that each unit increase in sterol ester(27∶1/20∶2)levels was associated with a 25.55％increase in the risk of osteoporotic pathological fractures(odds ratio=1.256,95％confidence interval:1.001-1.575,P=0.049),suggesting a significant positive correlation between elevated sterol ester levels and increased fracture risk.Reverse Mendelian randomization analysis revealed a significant negative association between osteoporotic pathological fractures and three types of phosphatidylcholine.Horizontal validation yielded consistent results,confirming sterol ester as a risk factor for osteoporotic pathological fractures.(2)The results indicate that sterol ester is a risk factor for osteoporotic pathological fractures,while phosphatidylcholine serves as a protective factor.These findings strengthen the evidence supporting the effect of lipids on the risk of osteoporotic pathological fractures.Although the GWAS data used in this study were derived from European populations,given the broad commonality of human genetics,the results provide valuable reference significance for improving osteoporosis in Chinese populations through lipid regulation.

BACKGROUND:Although previous studies have reported associations between lipids and the risk of osteoporotic pathological fractures,the specific causal relationships between lipid level and osteoporotic pathological fractures remain unclear.OBJECTIVE:To elucidate the causal relationship between lipids and osteoporotic pathological fractures using a two-sample bidirectional Mendelian randomization analysis.METHODS:The data for 178 lipid metabolites were obtained from the IEU-GWAS database(developed by the MRC Integrative Epidemiology Unit at the University of Bristol,UK,which provides extensive summary data from genome-wide association studies),while osteoporotic pathological fracture data(from 173 619 European participants)were acquired from the FinnGen database(constructed by the Finnish national gene research program,focusing on investigating relationships between genomics and health/disease in the Finnish population).Osteoporotic pathological fracture data were used as the outcome variable,with lipids serving as exposures,for the bidirectional Mendelian randomization study to evaluate the causal effects of different lipids on osteoporotic pathological fractures.The UK Biobank database was employed as a validation set by switching the outcome variable to verify the findings horizontally.RESULTS AND CONCLUSION:(1)The inverse variance weighted analysis indicated that each unit increase in sterol ester(27∶1/20∶2)levels was associated with a 25.55％increase in the risk of osteoporotic pathological fractures(odds ratio=1.256,95％confidence interval:1.001-1.575,P=0.049),suggesting a significant positive correlation between elevated sterol ester levels and increased fracture risk.Reverse Mendelian randomization analysis revealed a significant negative association between osteoporotic pathological fractures and three types of phosphatidylcholine.Horizontal validation yielded consistent results,confirming sterol ester as a risk factor for osteoporotic pathological fractures.(2)The results indicate that sterol ester is a risk factor for osteoporotic pathological fractures,while phosphatidylcholine serves as a protective factor.These findings strengthen the evidence supporting the effect of lipids on the risk of osteoporotic pathological fractures.Although the GWAS data used in this study were derived from European populations,given the broad commonality of human genetics,the results provide valuable reference significance for improving osteoporosis in Chinese populations through lipid regulation.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

The efficacy mechanism of the alcoholic extract of Gnaphalium affine was investigated by observing its influence on oxidative stress and intestinal flora in rats modeled for chronic obstructive pulmonary disease(COPD). UPLC-MS was used to evaluate the quality of the alcoholic extract of G. affine, and 72 rats were randomly divided into six groups, with COPD models established in five groups by cigarette smoke combined with airway drip lipopolysaccharide, and the rats were given the positive drug of Danlong Oral Solution, as well as low-, medium-, and high-doses alcoholic extract of G. affine, respectively. After two weeks of continuous gastric gavage, the body weights and general morphology observations were performed; HE staining and Masson staining were used to verify the effects of the alcoholic extract of G. affine on alveolar inflammation and collagen deposition area in COPD rats; the oxidative stress indexes CAT and GSH in serum and SOD and MDA in lung tissue of the rats were measured, and the mRNA expression of HO-1, Nrf2, and NQO1 were determined by qRT-PCR. The protein expressions of HO-1, Nrf2, and NQO1 were determined by the Western blot method, and the mechanism by which the alcoholic extract of G. affine affected oxidative stress in COPD rats was explored. Finally, the influence of G. affine on the changes in intestinal flora caused by COPD was studied by 16S rRNA sequencing. The results showed that a total of 121 chemical components were identified by UPLC-MS, including 70 positive and 51 negative ion modes. In animal experiments, it was found that the alcoholic extracts of G. affine were able to reduce the percentage of collagen deposition, affect the oxidative stress indexes such as CAT, GSH, SOD, MDA, as well as the mRNA and protein expression of Nrf2, HO-1, and NQO1. The 16S rRNA sequencing results showed an increase in the level of Lactobacillales and a decrease in the level of Desulfovibrio and Desulfovibrionales, suggesting that the alcoholic extracts of G. affine could reverse the changes in intestinal flora caused by COPD. In conclusion, the alcoholic extracts of G. affine may exert anti-COPD effects by affecting the oxidative stress pathway and modulating the changes in intestinal flora.
Animals ; Oxidative Stress/drug effects* ; Pulmonary Disease, Chronic Obstructive/genetics* ; Rats ; Male ; Gastrointestinal Microbiome/drug effects* ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/administration & dosage* ; NF-E2-Related Factor 2/metabolism* ; Humans ; Lung/metabolism*

Osteoporotic fractures(OPF) refer to the fractures caused by minor violence in the state of osteoporosis, seriously threatening the life and health of elderly patients. Drug and surgical therapies have limitations such as single targets, diverse adverse reactions, and poor prognosis. Kidney-tonifying traditional Chinese medicine(TCM) has good potential in the treatment of OPF. TCM can promote the healing of OPF by promoting angiogenesis in the early stage of bone healing, promoting osteogenic differentiation of bone marrow mesenchymal stem cells in the stage of bone repair, maintaining the balance of osteogenic and osteoclastic system in the stage of bone remodeling, and regulating the oxidative stress responses throughout the process of OPF healing. TCM can alleviate the pathological state of osteoporosis and promote fracture healing in OPF patients via multiple pathways and targets, demonstrating the advantages and potential of biphasic regulation.
Humans ; Drugs, Chinese Herbal/therapeutic use* ; Osteoporotic Fractures/metabolism* ; Animals ; Fracture Healing/drug effects* ; Medicine, Chinese Traditional ; Kidney/metabolism* ; Osteogenesis/drug effects*

This study primarily aimed to investigate the prevalence of human papillomavirus (HPV) and other common pathogens of sexually transmitted infections (STIs) in spermatozoa of infertile men and their effects on semen parameters. These pathogens included Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae, Pseudomonas aeruginosa , and Staphylococcus aureus . A total of 1951 men of infertile couples were recruited between 23 March 2023, and 17 May 2023, at the Department of Reproductive Medicine of The First People's Hospital of Yunnan Province (Kunming, China). Multiplex polymerase chain reaction and capillary electrophoresis were used for HPV genotyping. Polymerase chain reaction and electrophoresis were also used to detect the presence of other STIs. The overall prevalence of HPV infection was 12.4%. The top five prevalent HPV subtypes were types 56, 52, 43, 16, and 53 among those tested positive for HPV. Other common infections with high prevalence rates were Ureaplasma urealyticum (28.3%), Ureaplasma parvum (20.4%), and Enterococcus faecalis (9.5%). The prevalence rates of HPV coinfection with Ureaplasma urealyticum, Ureaplasma parvum, Chlamydia trachomatis, Mycoplasma genitalium , herpes simplex virus 2, Neisseria gonorrhoeae, Enterococcus faecalis, Streptococcus agalactiae , and Staphylococcus aureus were 24.8%, 25.4%, 10.6%, 6.4%, 2.4%, 7.9%, 5.9%, 0.9%, and 1.3%, respectively. The semen volume and total sperm count were greatly decreased by HPV infection alone. Coinfection with HPV and Ureaplasma urealyticum significantly reduced sperm motility and viability. Our study shows that coinfection with STIs is highly prevalent in the semen of infertile men and that coinfection with pathogens can seriously affect semen parameters, emphasizing the necessity of semen screening for STIs.
Humans ; Male ; Infertility, Male/epidemiology* ; Coinfection/microbiology* ; Papillomavirus Infections/virology* ; Adult ; Sexually Transmitted Diseases/complications* ; China/epidemiology* ; Staphylococcus aureus/isolation & purification* ; Chlamydia trachomatis/isolation & purification* ; Prevalence ; Mycoplasma genitalium/isolation & purification* ; Ureaplasma urealyticum/isolation & purification* ; Neisseria gonorrhoeae/isolation & purification* ; Enterococcus faecalis/isolation & purification* ; Streptococcus agalactiae/isolation & purification* ; Herpesvirus 2, Human/genetics* ; Pseudomonas aeruginosa/isolation & purification* ; Semen/virology* ; Sperm Motility ; Spermatozoa/microbiology* ; Human Papillomavirus Viruses

OBJECTIVES: To study the risk factors for hypoxemia in children with severe Mycoplasma pneumoniae pneumonia (SMPP). METHODS: A retrospective collection of clinical data from children diagnosed with SMPP at the Third Affiliated Hospital of Zhengzhou University from June to December 2023 was conducted. The patients were categorized into hypoxemia and non-hypoxemia groups. Logistic regression analysis was used to assess the risk factors for hypoxemia, and receiver operating characteristic (ROC) curve analysis was employed to analyze the diagnostic performance of various indicators. RESULTS: A total of 113 children with SMPP were included. Univariate logistic regression analysis showed that ferritin, aspartate aminotransferase, creatinine, creatine kinase isoenzyme, lactate dehydrogenase, alpha-hydroxybutyrate dehydrogenase, immunoglobulin G, complement C3, complement C4, age, extrapulmonary complications, and a chest computed tomography (CT) scan showing a bronchiolitis pattern were significant factors for hypoxemia in children with SMPP (P<0.05). Multivariate logistic regression analysis revealed that elevated ferritin levels, presence of extrapulmonary complications, and a bronchiolitis pattern on lung CT were independent risk factors for hypoxemia in these patients (P<0.05). The ROC curve analysis indicated that the combination of these three indicators for predicting hypoxemia had a sensitivity of 71.9%, a specificity of 95.1%, and an area under the curve of 0.888 (95%CI: 0.809-0.968). CONCLUSIONS In children with SMPP, when there are elevated ferritin levels, a bronchiolitis pattern on chest CT, and the presence of extrapulmonary complications, there should be a high level of vigilance for the potential development of hypoxemia.
Humans ; Pneumonia, Mycoplasma/complications* ; Male ; Female ; Risk Factors ; Child, Preschool ; Hypoxia/etiology* ; Retrospective Studies ; Child ; Logistic Models ; Infant ; ROC Curve ; Adolescent

OBJECTIVES: To explore the relationship between white matter injury (WMI) and cerebral perfusion in preterm infants using arterial spin labeling (ASL). METHODS: A total of 293 preterm infants (gestational age <34 weeks) hospitalized at the Third Affiliated Hospital of Zhengzhou University between June 2022 and June 2024 were included. After achieving clinical stability, the infants underwent brain magnetic resonance imaging (MRI) and ASL. Based on MRI findings, infants were classified into WMI (n=66) and non-WMI (n=227) groups. Cerebral perfusion parameters were compared between groups, and the association between WMI and perfusion alterations was evaluated. RESULTS: The WMI group showed a higher incidence of mild intraventricular hemorrhage (IVH) than the non-WMI group (P<0.05). Significantly lower cerebral perfusion was observed in the WMI group across bilateral frontal, temporal, parietal, and occipital lobes, as well as the basal ganglia and thalamus (P<0.05). After adjusting for gestational age, corrected gestational age at ASL scan, and mild IVH, WMI remained significantly associated with reduced regional perfusion (P<0.05). CONCLUSIONS WMI in preterm infants correlates with localized cerebral hypoperfusion. ASL-detected perfusion abnormalities may provide novel insights into WMI pathogenesis.
Humans ; White Matter/blood supply* ; Infant, Newborn ; Spin Labels ; Infant, Premature ; Female ; Male ; Cerebrovascular Circulation ; Magnetic Resonance Imaging