Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

ObjectiveTo analyze the trend and influencing factors of low birth weight (LBW) among newborns in Chongming District of Shanghai from 2008 to 2022, so as to provide references for the development of intervention measures reducing the rate of LBW. MethodsBirth surveillance data of Chongming District of Shanghai from 2008 to 2022 were collected and organized, and the annual percentage change (APC) of LBW was calculated by using Joinpoint 5.0.2 software for trend change analysis. Logistic regression analysis was used to analyze the influencing factors of LBW. ResultsThe overall incidence of LBW was 3.71% in Chongming District, Shanghai from 2008 to 2022. Joinpoint trend analysis showed that the incidence of LBW in Chongming District had an upward trend (APC=5.49%, 95%CI: 3.31%‒7.72%, P<0.001).Multivariate logistic regression analysis showed that preterm birth, multiple births, female infants, birth defects, first pregnancy, primiparity, and a young father age (<20 years) were risk factors for LBW in Chongming District. Among the term infants, female infants, birth defects, and first pregnancy were risk factors for LBW (P<0.05). Female infants, birth defects, first pregnancy, primiparity, advanced maternal age (≥35 years), and a young father age (<20 years) were risk factors in singleton neonates. ConclusionThe incidence of LBW among newborns is on the rise in Chongming District of Shanghai. Therefore, high risk groups need to be identified, and prenatal check-ups and pregnancy care should be strengthened to reduce the risk of neonatal LBW.

Objective: To investigate the objective characteristics of tongue manifestation in different stages of damp-heat syndrome in diabetic kidney disease (DKD). Methods: A cross-sectional study enrolled 134 patients with DKD G3-5 stages who met the diagnostic criteria for damp-heat syndrome in DKD. The patients were treated at Dongzhimen Hospital, Beijing University of Chinese Medicine, from May 2023 to January 2024. The patients were divided into three groups: DKD G3, DKD G4, and DKD G5 stage, with 53, 33, and 48 patients in each group, respectively. Clinical general data (gender, age, and body mass index) and damp-heat syndrome scores were collected from the patients. The YZAI-02 traditional Chinese medicine (TCM) AI Tongue Image Acquisition Device was used to capture tongue images from these patients. The accompanying AI Open Platform for TCM Tongue Diagnosis of the device was used to analyze and extract tongue manifestation features, including objective data on tongue color, tongue quality, coating color, and coating texture. Clinical data and objective tongue manifestation characteristics were compared among patients with DKD G3-5 based on their DKD damp-heat syndrome status. Results: No statistically significant difference in gender or body mass index was observed among the three patient groups. The DKD G3 stage group had the highest age (P<0.05). The DKD G3 stage group had a lower score for symptoms of poor appetite and anorexia(P<0.05) than the DKD G5 group. No statistically significant difference was observed in damp-heat syndrome scores among the three groups. Compared with the DKD G5 stage group, the DKD G3 stage group showed a decreased proportion of pale color at the tip and edges of the tongue (P<0.05). The DKD G4 stage group exhibited an increased proportion of crimson at the root of the tongue, a decreased proportion of thick white tongue coating at the root, a decreased proportion of pale color at the tip and edges of the tongue, an increased hue value (indicating color tone) of the tongue color in the middle, an increased brightness value (indicating color lightness) of the tongue coating color in the middle, and an increased thickness of the tongue coating (P<0.05). No statistically significant difference was observed in other tongue color proportions, color chroma values, body characteristics, coating color proportions, coating color chroma values, and coating texture characteristics among the three groups. Conclusion Tongue features differ in different stages of DKD damp-heat syndrome in multiple dimensions, enabling the inference that during the DKD G5 stage, the degree of qi and blood deficiency in the kidneys, heart, lungs, liver, gallbladder, spleen, and stomach is prominent. Dampness is more likely to accumulate in the lower jiao, particularly in the kidneys, whereas heat evil in the spleen and stomach is the most severe. These insights provide novel ideas for the clinical treatment of DKD.

Background: and Purpose This study aimed to investigate the association between residual inflammatory risk (RIR) and vulnerable plaques using high-resolution magnetic resonance imaging (HRMRI) in symptomatic intracranial atherosclerotic stenosis (ICAS). Methods: This retrospective study included 70%–99% symptomatic ICAS patients hospitalized from January 2016 to December 2022. Patients were classified into four groups based on high-sensitivity C-reactive protein (hs-CRP) and low-density lipoprotein cholesterol (LDL-C): residual cholesterol inflammatory risk (RCIR, hs-CRP ≥3 mg/L and LDL-C ≥2.6 mmol/L), RIR (hs-CRP ≥3 mg/L and LDL-C <2.6 mmol/L), residual cholesterol risk (RCR, hs-CRP <3 mg/L and LDL-C ≥2.6 mmol/L), and no residual risk (NRR, hs-CRP <3 mg/L and LDL-C <2.6 mmol/L). Vulnerable plaque features on HRMRI included positive remodeling, diffuse distribution, intraplaque hemorrhage, and strong enhancement. Results: Among 336 included patients, 21, 60, 58, and 197 were assigned to the RCIR, RIR, RCR, and NRR groups, respectively. Patients with RCIR (adjusted odds ratio [aOR], 3.606; 95% confidence interval [CI], 1.346–9.662; P=0.011) and RIR (aOR, 3.361; 95% CI, 1.774–6.368, P<0.001) had higher risks of strong enhancement than those with NRR. Additionally, patients with RCIR (aOR, 2.965; 95% CI, 1.060–8.297; P=0.038) were more likely to have intraplaque hemorrhage compared with those with NRR. In the sensitivity analysis, RCR (aOR, 2.595; 95% CI, 1.201–5.608; P=0.015) exhibited an additional correlation with an increased risk of intraplaque hemorrhage. Conclusion In patients with symptomatic ICAS, RIR is associated with a higher risk of intraplaque hemorrhage and strong enhancement, indicating an increased vulnerability to atherosclerotic plaques.

Purpose: Diagnosing sarcopenia necessitates the measurement of skeletal muscle mass. However, guidelines lack a standardized imaging modality with thresholds validated among Asians. This systematic review compared ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and bioelectrical impedance analysis (BIA)/body composition monitoring in the detection of sarcopenia within Asian populations. Methods: PubMed and Embase were systematically searched for studies analyzing ultrasonography, CT, MRI, and BIA in diagnosing sarcopenia among Asians. Study quality was assessed using the Newcastle-Ottawa scale. Results: Pooled findings from 21,598 patients across 25 studies were examined. In receiver operating characteristic analysis, ultrasound displayed a pooled mean area under the curve (AUC) of 0.767 (95% confidence interval [CI], 0.709–0.806), with mean sensitivity of 81.1% (95% CI, 0.744–0.846) and specificity of 73.1% (95% CI, 0.648–0.774), for detecting sarcopenia in Asian populations. CT exhibited an AUC of 0.720 (sensitivity, 54.0%; specificity, 92.0%). MRI demonstrated an AUC of 0.839 (sensitivity, 67.0%; specificity, 66.0%). BIA displayed an AUC of 0.905 (95% CI, 0.842–0.968), 80.7% sensitivity (95% CI, 0.129–0.679), and 82.4% specificity (95% CI, 0.191–0.633). Conclusion Various modalities aid in diagnosing sarcopenia, and selection should be individualized. Although only BIA and dual-energy x-ray absorptiometry are recommended by the Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People, ultrasound imaging may hold diagnostic value for sarcopenia in the Asian population. In certain groups, diagnostic use of CT and MRI is warranted. Future research can standardize and validate modality-specific thresholds and protocols within Asian populations.

Purpose: Diagnosing sarcopenia necessitates the measurement of skeletal muscle mass. However, guidelines lack a standardized imaging modality with thresholds validated among Asians. This systematic review compared ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and bioelectrical impedance analysis (BIA)/body composition monitoring in the detection of sarcopenia within Asian populations. Methods: PubMed and Embase were systematically searched for studies analyzing ultrasonography, CT, MRI, and BIA in diagnosing sarcopenia among Asians. Study quality was assessed using the Newcastle-Ottawa scale. Results: Pooled findings from 21,598 patients across 25 studies were examined. In receiver operating characteristic analysis, ultrasound displayed a pooled mean area under the curve (AUC) of 0.767 (95% confidence interval [CI], 0.709–0.806), with mean sensitivity of 81.1% (95% CI, 0.744–0.846) and specificity of 73.1% (95% CI, 0.648–0.774), for detecting sarcopenia in Asian populations. CT exhibited an AUC of 0.720 (sensitivity, 54.0%; specificity, 92.0%). MRI demonstrated an AUC of 0.839 (sensitivity, 67.0%; specificity, 66.0%). BIA displayed an AUC of 0.905 (95% CI, 0.842–0.968), 80.7% sensitivity (95% CI, 0.129–0.679), and 82.4% specificity (95% CI, 0.191–0.633). Conclusion Various modalities aid in diagnosing sarcopenia, and selection should be individualized. Although only BIA and dual-energy x-ray absorptiometry are recommended by the Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People, ultrasound imaging may hold diagnostic value for sarcopenia in the Asian population. In certain groups, diagnostic use of CT and MRI is warranted. Future research can standardize and validate modality-specific thresholds and protocols within Asian populations.

Purpose: Diagnosing sarcopenia necessitates the measurement of skeletal muscle mass. However, guidelines lack a standardized imaging modality with thresholds validated among Asians. This systematic review compared ultrasonography, computed tomography (CT), magnetic resonance imaging (MRI), and bioelectrical impedance analysis (BIA)/body composition monitoring in the detection of sarcopenia within Asian populations. Methods: PubMed and Embase were systematically searched for studies analyzing ultrasonography, CT, MRI, and BIA in diagnosing sarcopenia among Asians. Study quality was assessed using the Newcastle-Ottawa scale. Results: Pooled findings from 21,598 patients across 25 studies were examined. In receiver operating characteristic analysis, ultrasound displayed a pooled mean area under the curve (AUC) of 0.767 (95% confidence interval [CI], 0.709–0.806), with mean sensitivity of 81.1% (95% CI, 0.744–0.846) and specificity of 73.1% (95% CI, 0.648–0.774), for detecting sarcopenia in Asian populations. CT exhibited an AUC of 0.720 (sensitivity, 54.0%; specificity, 92.0%). MRI demonstrated an AUC of 0.839 (sensitivity, 67.0%; specificity, 66.0%). BIA displayed an AUC of 0.905 (95% CI, 0.842–0.968), 80.7% sensitivity (95% CI, 0.129–0.679), and 82.4% specificity (95% CI, 0.191–0.633). Conclusion Various modalities aid in diagnosing sarcopenia, and selection should be individualized. Although only BIA and dual-energy x-ray absorptiometry are recommended by the Asian Working Group for Sarcopenia and the European Working Group on Sarcopenia in Older People, ultrasound imaging may hold diagnostic value for sarcopenia in the Asian population. In certain groups, diagnostic use of CT and MRI is warranted. Future research can standardize and validate modality-specific thresholds and protocols within Asian populations.

The dysfunction of qi, blood, and fluid underlies the pathology of diabetes mellitus. The symptoms, signs, and physical and chemical indexes of diabetes mellitus patients reflect the duration, degree, primary and secondary pathological state of the abnormal metabolism of qi, blood, and fluid. It is necessary to construct a three-dimensional syndrome differentiation system of diabetes mellitus based on spatial and temporal dimensions. According to the four stages of depression, heat, deficiency, and damage, the location of the disease can be locked into qi, ying, and blood levels. The process reflects the pathological trend of the abnormal metabolism of qi, blood, and fluid: qi depression (prodromal stage: asymptomatic metabolic disorder/early stage of qi level) → qi heat (initial stage: index stage/late stage of qi level) → deficiency of both qi and yin (middle stage: symptom stage of three more and one less/stage of ying level) → damage of zang-fu viscera and meridians (late stage: complication stage/stage of blood level). According to the time process, the treatment principles are proposed as follows: during the early stage of qi level, treatment should focus on strengthening the spleen to regulate qi flow, to prevent the accumulation of glucose; during the late stage of qi level, treatment should focus on clearing heat and resolving turbidity, to remove the stagnated heat caused by glucose; during the stage of ying level, treatment should focus on benefiting qi and nourishing yin, to improve the symptoms about deficiency of both qi and yin; during the stage of blood level, treatment should focus on promoting blood circulation and removing blood stasis, to remove the complication. According to the etiology and pathogenesis of diabetes mellitus, the sequential treatment strategy is thus proposed, which is strengthening the spleen to regulate qi flow, clearing heat and resolving turbidity, benefiting qi and nourishing yin, and promoting blood circulation and removing blood stasis. The compound prescriptions such as Houpo Sanwu Decoction, Baihu Jia Renshen Decoction, Danggui Liuhuang Decoction, and Taohong Siwu Decoction are used with modification in the stage-based treatment.

The occurrence of diabetes mellitus （DM） is closely related to insulin resistance and islet β cell dysfunction. Modern studies have found that macrophages are widely present in the liver，fat，skeletal muscle，islets， and other tissues and organs. Macrophage M1/M2 polarization plays an important role in the occurrence and development of diabetes mellitus and its related complications by intervening in inflammatory response，improving insulin resistance，and promoting tissue repair. Most of the traditional Chinese medicines that regulate the activation and polarization of macrophages are Qi-replenishing and Yin-nourishing，heat-clearing， and detoxicating medicinal，which are consistent with the etiology and pathogenesis of diabetes and its related complications. Therefore，by summarizing the mechanisms between macrophage activation，polarization， and insulin resistance in various tissues，this paper reviewed traditional Chinese medicine and its effective components and compounds in improving diabetes mellitus and its related complications through multi-channel regulation of macrophage polarization and regulation of M1/M2 ratio，providing references for the future treatment of DM and its related complications with traditional Chinese medicine.

Objective: To determine 17 types of phthalic acid esters (PAEs) in drinking water using solid-phase extraction coupled with gas chromatography-mass spectrometry (GC-MS) in multiple reaction monitoring (MRM) mode. Methods: One litre of commercially available bottled water was purified using an HLB solid-phase extraction column, and was eluted with ethyl acetate, dichloromethane and average methanol. Seventeen types of PAEs were detected using a triple quadrupole gas chromatography-mass spectrometer in MRM mode. By optimizing the temperature programming and adjusting the mass spectrometry collision energy, collection efficiency was improved and matrix interference was reduced. The precision and accuracy of this method were assessed by determining the standard curves, detection limits, quantification limits, relative standard deviations (RSD) and average spiked recovery rates for the 17 types of PAEs. Results: The 17 types of PAEs showed good linear relationships between mass concentration and chromatographic peak areas in the range of 0.02 to 1.0 mg/L, with correlation coefficients all greater than 0.999 1. The detection limits ranged from 0.002 9 to 0.009 7 mg/kg, the quantification limits ranged from 0.008 7 to 0.029 1 mg/kg, the RSD ranged from 0.8% to 3.0%, and the average spiked recovery rates ranged from 88.8% to 111.8%. Conclusion Solid-phase extraction coupled with MRM of GC-MS can better determine low concentrations of PAEs in drinking water.