Objective: To evaluate the effect of bioactive peptides combined with probiotics on serum uric acid (SUA) in patients with hyperuricemia (HUA), so as to provide the evidence for prevention and treatment of HUA. Methods: The patients with HUA aged 18 to 65 years were selected and randomly divided into an intervention group and a control group. The patients in the intervention group received bioactive peptides combined with probiotics for 28 days at a dose of 3 g/d, while the patients in the control group received an equal dose of placebos. Demographic information, body mass index (BMI), blood pressure and blood lipid were collected through questionnaire surveys, physical examination and laboratory tests. SUA levels were detected before and after 14 days and 28 days of interventions. The differences of SUA levels between the two groups were compared using generalized estimation equation. Results: Totally 108 patients with HUA were recruited, including 54 patients in the intervention group and 53 patients in the control group (1 dropout). Before interventions, there were no statistically significant differences in gender, age, course of HUA, exercise duration, frequency of alcohol consumption, frequency of meat broth consumption, BMI, prevalence of hypertension and prevalence of dyslipidemia between the two groups (all P>0.05). After 14 days of interventions, the SUA levels of the patients in the intervention group decreased by 3.00 μmol/L, while those in the control group increased by 7.00 μmol/L. After 28 days of interventions, the SUA levels of the patients in the intervention group and the control group decreased by 26.00 μmol/L and 16.00 μmol/L, respectively. However, there was no statistically significant interaction between the intervention time and group (both P>0.05). Subgroup analysis showed that after 28 days of interventions, the decrease in SUA levels in the patients aged 55 years and older and without hypertension in the intervention group was greater than those in the control group (both P<0.05). Conclusions Bioactive peptides combined with probiotics showed no significant difference in reducing SUA levels in patients with HUA compared to the control group. The effect was more significant for patients aged 55 years and older and without hypertension.

OBJECTIVE: To investigate the clinical characteristics, treatment and prognosis of adult AML patients with NUP98::HOXA9 fusion gene. METHODS: From May 2017 to October 2023， among 2 113 AML patients who visited the Hematology Department of our hospital, patients with NUP98 rearrangements were screened. The clinical characteristics, chromosome karyotypes, immunophenotypes, gene mutations, treatment efficacy and prognosis of the patients with NUP98::HOXA9 positive were analyzed. RESULTS: Among the 2 113 AML patients, there were 18 cases with NUP98 rearrangement, including 14 NUP98::HOXA9 positive cases, with a detection rate of 0.66% (14/2 113). The median age of the NUP98::HOXA9 positive patients was 42.5 (23-64) years old. The most common chromosome karyotype was t(7; 11)(p15; p15). The immunophenotypes of all patients expressed CD13, CD33, CD117 and CD38, and most patients expressed CD34 and cMPO, while only a few expressed HLA-DR. Second-generation sequencing (NGS) was performed to detect genetic mutations associated with leukemia in all 14 patients, and the genes exhibiting a high frequency of mutation were WT1 (10/14), TET2 (7/14), and FLT3-ITD (6/14). Additionally, mutations were also observed in KRAS/NRAS, IDH1, and KIT. Of the 13 patients who received treatment, 9 achieved complete remission (CR), and all 3 patients who received azacytidine(AZA)+ venetoclax (VEN) regimen achieved CR after the first course of treatment. Within this cohort, 6 patients were classified as relapsed/refractory (6/13). 4 patients underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT), of which two achieved long-term survival. The median follow-up time was 12 (2.1-65.0) months, while the median overall survival (OS) and relapse-free survival (RFS) were recorded as 11.4 months and 9.6 months, respectively. CONCLUSION The most common type of NUP98 rearrangement in adults AML patients is NUP98::HOXA9 , which is often accompanied by somatic mutations in WT1, TET2, and FLT3-ITD. These patients are prone to relapse, have short survival time, and generally face poor prognoses. Hopefully, utilization of the AZA+VEN regimen is anticipated to enhance the rate of induced remission in the patients, and some patients may prolong their survival through allo-HSCT. However, more effective treatment methods are still needed to improve the overall prognosis of these patients.
Humans ; Adult ; Leukemia, Myeloid, Acute/genetics* ; Middle Aged ; Prognosis ; Nuclear Pore Complex Proteins/genetics* ; Oncogene Proteins, Fusion/genetics* ; Mutation ; Male ; Female ; Young Adult ; Homeodomain Proteins/genetics*

Tailored lipid nanoparticles (LNPs)-mediated small interfering RNA (siRNA) nanomedicines show promise in treating liver disease, such as acute liver injury (ALI) and non-alcoholic steatohepatitis (NASH). However, constructing LNPs that address biosafety concerns, ensure efficient delivery, and target specific hepatic subcellular fractions has been challenging. To evade above obstacles, we develop three novel self-degradable "gemini-like" ionizable lipids (SS-MA, SS-DC, SS-MH) by incorporating disulfide bonds and modifying the length of ester bond and tertiary amino head. Our findings reveal that the disulfide-bond-bridged LNPs exhibit reduction-responsive drug release, improving both biosafety and siRNA delivery efficiency. Furthermore, the distance of ester bond and tertiary amino head significantly influences the LNPs' pK _a, thereby affecting endosomal escape, hemolytic efficiency, absorption capacity of ApoE, uptake efficiency of hepatocytes and liver accumulation. We also develop the modified-mannose LNPs (M-LNP) to target liver macrophages specifically. The optimized M-MH_LNP@TNFα exhibits potential in preventing ALI by decreasing tumor necrosis factor α (TNFα) levels in the macrophages, while MH_LNP@DGAT2 could treat NASH by selectively degrading diacylglycerol O-acyltransferase 2 (DGAT2) in the hepatocytes. Our findings provide new insights into developing novel highly effective and low-toxic "gemini-like" ionizable lipids for constructing LNPs, potentially achieving more effective treatment for hepatic diseases.

OBJECTIVE: Several epidemiological observational studies have related particulate matter (PM) exposure to Inflammatory bowel disease (IBD), but many confounding factors make it difficult to draw causal links from observational studies. The objective of this study was to explore the causal association between PM _2.5 exposure, its absorbance, and IBD. METHODS: We assessed the association of PM _2.5 and PM _2.5 absorbance with the two primary forms of IBD (Crohn's disease [CD] and ulcerative colitis [UC]) using Mendelian randomization (MR) to explore the causal relationship. We conducted two-sample MR analyses with aggregated data from the UK Biobank genome-wide association study. Single-nucleotide polymorphisms linked with PM _2.5 concentrations or their absorbance were used as instrumental variables (IVs). We used inverse variance weighting (IVW) as the primary analytical approach and four other standard methods as supplementary analyses for quality control. RESULTS: The results of MR demonstrated that PM _2.5 had an adverse influence on UC risk (odds ratio [ OR] = 1.010; 95% confidence interval [ CI] = 1.001-1.019, P = 0.020). Meanwhile, the results of IVW showed that PM _2.5 absorbance was also causally associated with UC ( OR = 1.012; 95% CI = 1.004-1.019, P = 0.002). We observed no causal relationship between PM _2.5, PM _2.5 absorbance, and CD. The results of sensitivity analysis indicated the absence of heterogeneity or pleiotropy, ensuring the reliability of MR results. CONCLUSION Based on two-sample MR analyses, there are potential positive causal relationships between PM _2.5, PM _2.5 absorbance, and UC.
Humans ; Mendelian Randomization Analysis ; Particulate Matter/analysis* ; Polymorphism, Single Nucleotide ; Inflammatory Bowel Diseases/genetics* ; Air Pollutants/analysis* ; Crohn Disease/genetics* ; Colitis, Ulcerative/genetics* ; Genome-Wide Association Study ; Risk Factors ; Environmental Exposure

Nodal marginal zone B-cell lymphoma(NMZL),the least common subtype of marginal zone lymphoma,represents a low-grade malignancy arising from the marginal zone of lymph node follicles,composed of small B-cells with an inert non-Hodgkin lymphoma nature.It accounts for 1.5% to 1.8% of all non-Hodgkin lymphomas and 10% of all marginal zone lymphomas.The low incidence and lack of typical clinical and pathological features pose a challenge to the diagnosis and clinical management of NMZL.In this article,we reported the diagnosis and treatment of a case of NMZL located in the parapharyngeal space of the left neck and reviewed the relevant literature from both domestic and international sources.We summarized the clinical manifestations,histopathological features,immunohistochemical characteristics,imaging features,diagnosis and treatment modalities,and prognosis of NMZL.
Humans ; Lymphoma, B-Cell, Marginal Zone/pathology* ; Lymph Nodes/pathology* ; Neck/pathology* ; Male

Nano/microplastics(NMPs),due to their environmental persistence and resistance to degradation,have emerged as a major contributor to global pollution.NMPs are capable of adsorbing various hazardous chemicals and heavy metals,thereby posing threats to aquatic ecosystem health,which may ultimately cause potential risks to human health.Conventional analytical methods suffered from limited resolution,insufficient chemical information,or destruction of sample,invalidating these assays for on-site detection of NMPs.Surface-enhanced Raman scattering(SERS)offers distinct advantages such as high sensitivity,superior specificity,rich fingerprint information,and non-destructive analysis,thus facilitating the on-site analysis of NMPs in complex matrices.This review summarized recent advances in SERS substrates for detection of NMPs,discussed the construction and applications of SERS-based multimodal detection strategies,and introduced the research progress of SERS detection of NMPs in food safety,environmental pollution,and bioanalysis.Moreover,the main challenges and future directions of SERS-based NMP detection were outlined.

Objective To explore a deep learning-based automatic bone age estimation model for elbow joint X-ray images of Chinese Han adolescents and children and evaluate its performance.Methods A total of 943(517 males and 426 females)elbow joint frontal view X-ray images of Chinese Han ado-lescents and children aged 6.00 to<16.00 years were collected from East,South,Central and North-west China.Three experimental schemes were adopted for bone age estimation.Scheme 1:Directly in-put preprocessed images into the regression model;Scheme 2:Train a segmentation network using"key elbow joint bone annotations"as labels,then input segmented images into the regression model;Scheme 3:Train a segmentation network using"full elbow joint bone annotations"as labels,then in-put segmented images into the regression model.For segmentation,the optimal model was selected from U-Net,UNet++and TransUNet.For regression,VGG16,VGG19,InceptionV2,InceptionV3,ResNet34,ResNet50,ResNet101 and DenseNet121 models were selected for bone age estimation.The dataset was randomly split into 80%(754 samples)for training and validation for model fitting and hyperparameter tuning,and 20%(189 samples)as an internal test set to test the performance of the trained model.An additional 104 elbow joint X-ray images from the same demographic and age group were col-lected and used as an external test set.Model performance was evaluated by comparing the mean ab-solute error(MAE),root mean square error(RMSE),accuracies within±0.7 years(P±0.7 years)and±1.0 years(P±1.0 years)between the estimated age and the actual age,and by drawing radar charts,scat-ter plots,and heatmaps.Results When segmented with Scheme 3,the UNet++model achieved good segmentation performance with a segmentation loss of 0.000 4 and an accuracy of 93.8%at a learning rate of 0.000 1.In the internal test set,the DenseNet121 model with Scheme 3 yielded the best results with MAE,P±0.7 years and P±1.0 years being 0.83 years,70.03%,and 84.30%,respectively.In the external test set,the DenseNet121 model with Scheme 3 also performed best,with an average MAE of 0.89 years and an average RMSE of 1.00 years.Conclusion When performing automatic bone age estima-tion using elbow joint X-ray images in Chinese Han adolescents and children,it is recommended to use the UNet++model for segmentation.The DenseNet121 model with Scheme 3 achieves optimal per-formance.Using segmentation networks,especially that trained with annotation areas encompassing the full elbow joint including the distal humerus,proximal radius,and proximal ulna,can improve the ac-curacy of bone age estimation based on elbow joint X-ray images.

Objective To explore a deep learning network model suitable for bone age estimation using shoulder joint X-ray images in Chinese Han adolescents.Methods A retrospective collection of 1 286 shoulder joint X-ray images of Chinese Han adolescents aged 12.0 to<18.0 years(708 males and 578 females)was conducted.Using random sampling,approximately 80%of the samples(1 032 cases)were selected as the training and validation sets for model learning,selection and optimization,and the other 20%samples(254 cases)were used as the test set to evaluate the model's generalization ability.The original single-channel shoulder joint X-ray images and dual-channel inputs combining original images with segmentation labels(manually annotated shoulder joint regions multiplied pixel-by-pixel with original images,followed by segmentation via the U-Net++network to retain only key shoulder joint region information)were respectively input into four network models,namely VGG16,ResNet18,ResNet50 and DenseNet121 for bone age estimation.Additionally,manual bone age estimation was con-ducted on the test set data,and the results were compared with the four network models.The mean absolute error(MAE),root mean square error(RMSE),coefficient of determination(R2),and Pear-son correlation coefficient(PCC)were used as main evaluation indicators.Results In the test set,the bone age estimation results of the four models with dual-channel input of shoulder joint X-ray images outperformed those with single-channel input in all four evaluation indicators.Among them,DenseNet121 with dual-channel input achieved best results with MAE of 0.54 years,RMSE of 0.82 years,R2 of 0.76,and PCC(r)of 0.88.Manual estimation yielded an MAE of 0.82 years,ranking second only to dual-channel DenseNet121.Conclusion The DenseNet121 model with dual-channel input combined with original images and segmentation labels is superior to manual evaluation results,and can effectively estimate the bone age of Chinese Han adolescents.

Objective:To explore the impact of rehabilitation exercise intervention mode based on cardiac function classification on clinical effect and quality of life(QOL)in patients with chronic heart failure(CHF).Methods:A total of 160 CHF patients who visited our hospital from Dec 2021 to Jan 2023 were selected,and 154 cases were fi-nally enrolled.According to the random number table method,patients were divided into study group and control group with 77 cases in each group.Control group received routine nursing program,while the study group received rehabilitation exercise intervention based on cardiac function classification on the basis of control group,both groups were intervened for three months.Clinical total effective rate,and cardiopulmonary function,serum oxidative stress indicators and MLHFQ score before and after intervention were compared between two groups.Results:Total effective rates of study subgroups of class Ⅱ and Ⅲ were significantly higher than those of control group(class Ⅱ:100.00％vs.83.78％;class Ⅲ:97.37％vs.80.00％)(P＜0.05 both).Compared with control subgroup of classⅢ after intervention,there were significant rise in peak VO2[(16.98±2.03)ml·min-1·kg-1 vs.(18.61±2.41)ml·min-1·kg-1],LVEF[(41.73±4.53)％vs.(48.03±5.22)％]and 6MWD[(351.34±61.00)m vs.(391.53±64.42)m](P＜0.01 all);and significant reductions in LVEDd[(57.55±3.91)mm vs.(53.18±3.07)mm],LVESd[(35.90±2.91)mm vs.(30.50±2.67)mm],levels of LPO[(6.00±0.99)mg/L vs.(3.95±0.61)mg/L],MPO[(3.83±0.58)mg/L vs.(2.03±0.28)mg/L],and MLHFQ total score[(57.05±4.57)points vs.(45.29±3.94)points]in study subgroup of class Ⅲ(P=0.001 all).Compared with control subgroup of class Ⅱ after intervention,there were significant rise in peak VO2,LVEF and 6MWD,and significant reductions in LVEDd,LVESd,levels of LPO,MPO and MLHFQ score in study subgroup of class Ⅱ,P＜0.05 or＜0.01.There was no significant difference in the incidence rate of adverse events during follow-up between two groups(3.90％vs.6.49％,P=0.717).Conclusion:Rehabilitation exercise intervention based on cardiac function classifi-cation can significantly improve cardiopulmonary function,inhibit oxidative stress response in vivo and improve quality of life in CHF patients,which is worthy of promotion and application in clinical practice.

Objective To analyze the predictive value of fecal form for the quality of bowel preparation in patients scheduled for colonoscopy,identify risk factors for bowel preparation failure,and develop and validate a risk prediction model.Methods This was a prospective cohort study using convenience sampling.Patients scheduled for colonoscopy in the Digestive Department of a tertiary A hospital in Jiangsu Province from June to December 2022 were included in the modeling cohort.General information sheet and the Bristol Stool Form Scale(BSFS)were used for data collection.Patients were categorized into a successful bowel preparation group and a bowel preparation failure group based on the quality of bowel preparation.The optimal cutoff value for BSFS was determined using the best cutoff value method.Logistic regression analysis was employed to identify risk factors for bowel preparation failure,and a nomogram risk prediction model was constructed.Patients undergoing colonoscopy in the same hospital from January to February 2023 were served as the validation cohort.Results The modeling cohort included 569 patients,and the validation cohort included 212 patients,with bowel preparation failure rates of 19.0％and 19.8％,respectively.The risk prediction model formula derived from logistic regression analysis was P=-2.209+0.619 × hospitalized patients+0.635 × age≥65 years-0.710 × previous colonoscopy history+2.031 × BSFS type 1～2.The area under the receiver operating characteristic curve for the model was 0.751,with a sensitivity of 54.6％,a specificity of 85.9％,and the optimal cutoff value was 0.225,corresponding to a risk score of 80 for bowel preparation failure.The Hosmer-Lemeshow test showed x2=4.429,P=0.351.External validation demonstrated an area under the receiver operating characteristic curve of 0.775,indicating good model fit and high predictive value.Conclusion The incidence of bowel preparation failure in colonoscopy patients is relatively high.Patients aged 65 years,hospitalized patients,those with no history of colonoscopy,and those with BSFS type 1～2 are more likely to experience bowel preparation failure.The risk prediction model developed in this study has good predictive performance and can provide a basis for clinical nurses to quickly assess the risk of bowel preparation failure in patients.