Diabetic nephropathy （DKD）， as a common microvascular complication of diabetes mellitus （DM）， is a major cause of end-stage renal disease （ESRD）. Its clinical manifestations include increased urinary protein excretion， thickening of the glomerular basement membrane， and renal tubulointerstitial fibrosis. The pathogenesis of DKD is complex and involves multiple factors， including disordered glucose metabolism， hemodynamic alterations， and oxidative stress. Although modern medical approaches can alleviate certain symptoms， they still have limitations such as insufficient therapeutic targeting and prominent adverse effects. The transforming growth factor-β/Smad （TGF-β/Smad） signaling pathway is not only a tissue fibrosis pathway that has attracted considerable attention in recent years， but also regulates multiple protein molecules， including the glomerular podocyte slit diaphragm protein Podocin， interleukin-1β （IL-1β）， and superoxide dismutase （SOD）， thereby participating in various pathological processes and ultimately mediating renal injury. Flavonoid compounds， owing to their sustained pharmacological effects， broad spectrum of action， and high safety profile， have become ideal candidates for targeted therapy research in DKD. Existing studies have shown that these compounds can exert inhibitory effects on renal fibrosis， alleviate inflammatory responses， protect podocytes， and reduce oxidative stress by regulating the interactions between the TGF-β/Smad signaling pathway and the aforementioned protein molecules， thereby maintaining renal structure and function， reducing proteinuria， and significantly improving DKD lesions. This review briefly outlines the composition and functions of the TGF-β/Smad signaling pathway， elucidates the mechanisms by which this pathway regulates DKD， and focuses on summarizing major studies from the past decade on flavonoid-based interventions in DKD through targeted inhibition of the TGF-β/Smad signaling pathway. Furthermore， it discusses the considerable therapeutic potential of flavonoids in the treatment of this disease， aiming to provide a scientific basis for future clinical prevention and treatment of DKD and to promote the development of targeted drugs.

OBJECTIVE To analyze the diagnosis of latent tuberculosis infection(LTBI)in hospitalized patients of a tertiary general hospital and investigate the current status of related comorbidities.METHODS The clinical data were collected from the 14 448 hospitalized patients who received tuberculin skin test(TST)or interferon-gamma release assay(IGRA)in China-Japan Friendship Hospital from Jan.1,2022 to Dec.31,2023,and the results were assessed.RESULTS The detection rate of LTBI was 23.62％(3413/14448)among the hospitalized patients who received the tests,and the rate of definite diagnosis was only 4.22％(144/3413).88.40％(3017/3413)of the hospitalized patients with LTBI had at least one type of comorbidity,and the top 5 comorbidities were in turn as follows:high blood pressure,hyperlipidemia,diabetes mellitus,malignant tumors and rheumatic immune disea-ses;the number of comorbidities was increased with the age(x2=291.199,P＜0.001).The rheumatic immune disease(73/144,50.69％)was the most common type of comorbidity among the hospitalized patients with definite diagnosis of LTBI,and less than half of the patients(66/144,45.83％)were treated in rheumatology and immu-nology department.CONCLUSION The two-way screening of LTBI and comorbidities is the core premise for the standardized management of LTBI.

Objective To explore the value of improved ResNet18 lightweight deep learning(DL)models for automatically detecting gouty arthritis(GA)based on ultrasonogram of the first metatarsophalangeal joint(MTP1).Methods A total of 2 401 ultrasonograms obtained from 260 patients with suspected gout who underwent MTP1 ultrasound examination were included and divided into training set(1 910 ultrasonograms from 209 cases)and test set(491 ultrasonograms from 51 cases)at the ratio of 4∶1.GA lesions on ultrasonograms were manually labeled.After preprocessing,ResNet18 lightweight network was used to construct DL models for identifying the ultrasonogram category was normal or abnormal(with any manifestation of GA).Five-fold cross-validation method was adopted to evaluate the efficacy of the DL models constructed with 2,3,4 or 6 residual blocks,i.e.model 1,2,3 and 4,respectively,and the computational cost and the amount of parameters of each model were recorded.The efficacy of the models were verified using test set,and the best DL model was screened.Results The computational cost of model 1,2,3 and 4 was 7 558.27,2 963.73,4 012.33 and 6 093.39 M,respectively,while the amount of parameters was 4.61,4.91,4.91 and 5.28 M,respectively.Model 2 had the least computational cost with parameters only slightly more than model 1.In test set,no significant difference of accuracy nor the area under the curve was found among 4 models(all P＞0.05).The sensitivity of model 2 was higher than that of model 3,while its specificity was lower only than that of model 3(both P＜0.05),hence model 2 was the best DL model.Conclusion Improved ResNet18 lightweight DL models could be used for automatically detecting GA based on ultrasonogram of MTP1,among which model 2 was the best one.

Objective To observe the value of follicular thyroid imaging reporting and data system(F-TIRADS)for differentiating benign and malignant follicular thyroid lesions.Methods Totally 502 patients with follicular thyroid lesions were retrospectively enrolled,including 104 patients with single malignant lesion(malignant group,containing 77 follicular thyroid carcinomas[FTC]and 27 follicular variant of papillary thyroid carcinomas[FVPTC])and 398 patients with 416 benign lesions(benign group,containing 197 follicular thyroid adenomas[FTA]and 219 thyroid adenomatous hyperplasia).Ultrasonic features of lesions were recorded,and F-TIRADS scores were assigned by 1 junior and 1 senior ultrasound physicians.Taken histopathology results as gold standard,receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy for differentiating benign and malignant follicular thyroid lesions using F-TIRADS.Results Significant differences of composition,internal echo,boundary,calcification and trabecular structure of lesions were found between groups(all P＜0.001).Taken F-TIRADS score≥ 7 as the optimal cut-off value,the sensitivity,specificity,accuracy,positive predictive value and negative predictive value for differentiating benign and malignant follicular thyroid lesions by the junior physician was 76.92％,77.40％,77.31％,93.06％and 45.98％,while by the senior physician was 78.84％,81.25％,80.76％,93.89％and 51.25％,respectively.The efficacy of the latter was higher than of the former(AUC was 0.827 and 0.859,respectively,P＜0.05).Conclusion F-TIRADS could effectively identifying benign and malignant follicular thyroid lesions.

OBJECTIVE To analyze the diagnosis of latent tuberculosis infection(LTBI)in hospitalized patients of a tertiary general hospital and investigate the current status of related comorbidities.METHODS The clinical data were collected from the 14 448 hospitalized patients who received tuberculin skin test(TST)or interferon-gamma release assay(IGRA)in China-Japan Friendship Hospital from Jan.1,2022 to Dec.31,2023,and the results were assessed.RESULTS The detection rate of LTBI was 23.62％(3413/14448)among the hospitalized patients who received the tests,and the rate of definite diagnosis was only 4.22％(144/3413).88.40％(3017/3413)of the hospitalized patients with LTBI had at least one type of comorbidity,and the top 5 comorbidities were in turn as follows:high blood pressure,hyperlipidemia,diabetes mellitus,malignant tumors and rheumatic immune disea-ses;the number of comorbidities was increased with the age(x2=291.199,P＜0.001).The rheumatic immune disease(73/144,50.69％)was the most common type of comorbidity among the hospitalized patients with definite diagnosis of LTBI,and less than half of the patients(66/144,45.83％)were treated in rheumatology and immu-nology department.CONCLUSION The two-way screening of LTBI and comorbidities is the core premise for the standardized management of LTBI.

Objective To explore the value of improved ResNet18 lightweight deep learning(DL)models for automatically detecting gouty arthritis(GA)based on ultrasonogram of the first metatarsophalangeal joint(MTP1).Methods A total of 2 401 ultrasonograms obtained from 260 patients with suspected gout who underwent MTP1 ultrasound examination were included and divided into training set(1 910 ultrasonograms from 209 cases)and test set(491 ultrasonograms from 51 cases)at the ratio of 4∶1.GA lesions on ultrasonograms were manually labeled.After preprocessing,ResNet18 lightweight network was used to construct DL models for identifying the ultrasonogram category was normal or abnormal(with any manifestation of GA).Five-fold cross-validation method was adopted to evaluate the efficacy of the DL models constructed with 2,3,4 or 6 residual blocks,i.e.model 1,2,3 and 4,respectively,and the computational cost and the amount of parameters of each model were recorded.The efficacy of the models were verified using test set,and the best DL model was screened.Results The computational cost of model 1,2,3 and 4 was 7 558.27,2 963.73,4 012.33 and 6 093.39 M,respectively,while the amount of parameters was 4.61,4.91,4.91 and 5.28 M,respectively.Model 2 had the least computational cost with parameters only slightly more than model 1.In test set,no significant difference of accuracy nor the area under the curve was found among 4 models(all P＞0.05).The sensitivity of model 2 was higher than that of model 3,while its specificity was lower only than that of model 3(both P＜0.05),hence model 2 was the best DL model.Conclusion Improved ResNet18 lightweight DL models could be used for automatically detecting GA based on ultrasonogram of MTP1,among which model 2 was the best one.

This study investigated the prevalence of hepatitis E virus(HEV)in rodents within the Inner Mongolia Autonomous Region.In 2024,liver,spleen,kidney,and lung tissue samples were collected from rodents in 11 leagues and cities across the Inner Mongolia Autonomous Region,including Hohhot,Baotou,Hulunbuir,Xing'an League,Tongliao,Chifeng,Xilin Gol League,Ulan-qab,Ordos,Bayannur,and Wuhai.Nested PCR(RT-PCR)was used to detect the conserved regions of the HEV open reading frame 1(ORF1)gene.The RT-PCR-positive products were sequenced,and phylogenetic and homology analysis of the obtained sequences was performed.A total of 816 rodents were captured in this investigation,including 319 Rattus norvegicus(39.09%,319/816),206 Musmusculus(25.25%,206/816),and 140 Mongolian gerbils(17.16%,140/816).The HEV infection rate among rodents in the In-ner Mongolia region was 3.68%(30/816).Sequencing of the RT-PCR-positive results and analysis of the nucleotide sequences yielded 30 HEV-positive rodent samples.Phylogenetic analysis identified these sequences as belonging to the HEV-C1 genotype.The prevalence of HEV was observed in brown rats(Rattus norvegicus)in five leagues and cities within the Inner Mongolia region,includ-ing Xing'an League,Chifeng City,Hulunbuir City,Xilin Gol League,and Tongliao City,with infection rates of 16.67%,10.00%,5.98%,3.30%,and 2.50%,respectively.Brown rats,a species of house rats,frequently inhabit areas near human residences and have close interactions with humans and livestock.Studies have shown that multiple subtypes of HEV can cause zoonotic infections.Therefore,strengthening the monitoring of pathogens carried by rodents in residential environments and optimizing the prevention and control of rodent-borne diseases will be essential.Timely dissemination of relevant infectious disease knowledge to local communities will also be crucial,to decrease the risk of human infection.

This study investigated the prevalence of hepatitis E virus(HEV)in rodents within the Inner Mongolia Autonomous Region.In 2024,liver,spleen,kidney,and lung tissue samples were collected from rodents in 11 leagues and cities across the Inner Mongolia Autonomous Region,including Hohhot,Baotou,Hulunbuir,Xing'an League,Tongliao,Chifeng,Xilin Gol League,Ulan-qab,Ordos,Bayannur,and Wuhai.Nested PCR(RT-PCR)was used to detect the conserved regions of the HEV open reading frame 1(ORF1)gene.The RT-PCR-positive products were sequenced,and phylogenetic and homology analysis of the obtained sequences was performed.A total of 816 rodents were captured in this investigation,including 319 Rattus norvegicus(39.09%,319/816),206 Musmusculus(25.25%,206/816),and 140 Mongolian gerbils(17.16%,140/816).The HEV infection rate among rodents in the In-ner Mongolia region was 3.68%(30/816).Sequencing of the RT-PCR-positive results and analysis of the nucleotide sequences yielded 30 HEV-positive rodent samples.Phylogenetic analysis identified these sequences as belonging to the HEV-C1 genotype.The prevalence of HEV was observed in brown rats(Rattus norvegicus)in five leagues and cities within the Inner Mongolia region,includ-ing Xing'an League,Chifeng City,Hulunbuir City,Xilin Gol League,and Tongliao City,with infection rates of 16.67%,10.00%,5.98%,3.30%,and 2.50%,respectively.Brown rats,a species of house rats,frequently inhabit areas near human residences and have close interactions with humans and livestock.Studies have shown that multiple subtypes of HEV can cause zoonotic infections.Therefore,strengthening the monitoring of pathogens carried by rodents in residential environments and optimizing the prevention and control of rodent-borne diseases will be essential.Timely dissemination of relevant infectious disease knowledge to local communities will also be crucial,to decrease the risk of human infection.

Objective To observe the value of follicular thyroid imaging reporting and data system(F-TIRADS)for differentiating benign and malignant follicular thyroid lesions.Methods Totally 502 patients with follicular thyroid lesions were retrospectively enrolled,including 104 patients with single malignant lesion(malignant group,containing 77 follicular thyroid carcinomas[FTC]and 27 follicular variant of papillary thyroid carcinomas[FVPTC])and 398 patients with 416 benign lesions(benign group,containing 197 follicular thyroid adenomas[FTA]and 219 thyroid adenomatous hyperplasia).Ultrasonic features of lesions were recorded,and F-TIRADS scores were assigned by 1 junior and 1 senior ultrasound physicians.Taken histopathology results as gold standard,receiver operating characteristic curve was drawn,the area under the curve(AUC)was calculated to evaluate the efficacy for differentiating benign and malignant follicular thyroid lesions using F-TIRADS.Results Significant differences of composition,internal echo,boundary,calcification and trabecular structure of lesions were found between groups(all P＜0.001).Taken F-TIRADS score≥ 7 as the optimal cut-off value,the sensitivity,specificity,accuracy,positive predictive value and negative predictive value for differentiating benign and malignant follicular thyroid lesions by the junior physician was 76.92％,77.40％,77.31％,93.06％and 45.98％,while by the senior physician was 78.84％,81.25％,80.76％,93.89％and 51.25％,respectively.The efficacy of the latter was higher than of the former(AUC was 0.827 and 0.859,respectively,P＜0.05).Conclusion F-TIRADS could effectively identifying benign and malignant follicular thyroid lesions.