Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

Intervertebral disc degeneration (IVDD) is the predominant pathological contributor to chronic low back pain, a pervasive musculoskeletal condition affecting over 630 million people globally and imposing tremendous socioeconomic and public health burdens. The etiopathogenesis of IVDD is remarkably complex and multifactorial, involving intricate crosstalk among chronic inflammatory responses, extracellular matrix (ECM) catabolism, cellular senescence, aberrant programmed cell death (including apoptosis, pyroptosis, and ferroptosis), mitochondrial dysfunction, and oxidative damage. Compelling evidence indicates that the inflammatory microenvironment acts as a decisive driving force throughout the entire degenerative course of IVDD. Among the diverse inflammatory mediators, interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) serve as core pro-inflammatory cytokines that initiate and perpetuate the degenerative cascade. These two pivotal cytokines collectively activate an array of canonical intracellular signaling pathways, including nuclear factor-κB (NF-κB), mitogen-activated protein kinase (MAPK), nucleotide-binding domain leucine-rich repeat and pyrin domain-containing receptor 3 (NLRP3) inflammasome, and the phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) cascade. Such interconnected signaling networks trigger a self-reinforcing positive feedback loop, which exacerbates inflammatory reactions, disrupts the anabolic-catabolic homeostasis of the ECM, promotes oxidative stress and mitochondrial injury, induces multiple forms of disc cell death, and ultimately leads to progressive structural collapse and functional deterioration of the intervertebral disc. Conventional therapeutic strategies, dominated by nonsteroidal anti-inflammatory drugs and surgical interventions, are limited by systemic adverse reactions, suboptimal long-term efficacy, and the risk of adjacent segment degeneration. In contrast, traditional Chinese medicine (TCM) exhibits prominent advantages in the prevention and treatment of IVDD by virtue of its holistic regulation, syndrome differentiation, and multi-component, multi-target, multi-pathway pharmacological properties. This review systematically elucidates the molecular mechanisms by which inflammation-associated signaling pathways modulate disc cell fate and ECM metabolic homeostasis, and comprehensively summarizes the experimental progress over the past five years on TCM monomers and compound formulas for intervening in IVDD. Accumulating studies have confirmed that numerous natural active ingredients isolated from herbal medicines (ferulic acid, mangiferin, paeonol, astragaloside IV) and representative TCM compound prescriptions (Bushen Huoxue Formula, Shensuitongzhi Formula, Fuzi Decoction) exert synergistic protective effects by coordinately targeting core signaling hubs. These TCM agents demonstrate potent anti-inflammatory, antioxidant, anti-apoptotic, anti-pyroptotic, anti-ferroptotic, ECM-protective, and autophagy-regulating bioactivities, thereby effectively decelerating the pathological progression of IVDD. Despite remarkable progress, current investigations are still confronted by several critical limitations. Most studies are restricted to validating the regulatory effects of single TCM components on individual signaling pathways, leaving the systematic, dynamic, and synergistic mechanisms of TCM compound formulas within multi-pathway regulatory networks largely unexplored. Furthermore, clinical translation of TCM is severely hampered by the lack of efficient targeted drug delivery systems, unclear pharmacokinetic profiles, suboptimal local bioavailability, and incomplete long-term safety assessments. Therefore, future research should adopt an interdisciplinary paradigm integrating multi-omics technologies, artificial intelligence, organoid models, and organ-on-chip systems to systematically decipher the scientific basis of TCM against IVDD. Concurrently, the development of intelligent, site-specific delivery systems (hydrogels, nanoparticles, exosome-based carriers) is urgently needed to enhance the local accumulation and sustained release of TCM ingredients. By deepening mechanistic exploration and accelerating translational research, TCM is expected to evolve into safe, effective, and personalized precision therapeutic regimens for IVDD, offering novel and reliable solutions for the clinical management of chronic low back pain.

Diabetic nephropathy(DN)is a serious complication of diabetes mellitus and a leading cause of end-stage renal diseases.In DN patients,key pathological mechanisms include proteinuria,glomerulo-sclerosis,and fibrosis,largely driven by poor glycemic control and oxidative stress caused by prolonged hyperglycemia.This stress damages renal podocytes and triggers inflammatory mesenchymal infiltration of renal tubular cells,exacerbating the progression of proteinuria and fibrosis.Human umbilical cord-de-rived mesenchymal stem cells(hUC-MSCs)offer promising potential for treating DN due to their strong anti-oxidative properties.In this study,we developed a DN mouse model and treated the mouse via tail vein injections of hUC-MSCs(1×106 cells/mouse).The results indicated that hUC-MSCs significantly lowered fasting blood glucose levels(22.5±3.0 vs 14.7±1.1,P＜0.01)and improved glucose toler-ance,as shown by intraperitoneal glucose tolerance test(IPGTT)results(P＜0.05).Additionally,the renal function improved in hUC-MSCs-treated mice,with marked reductions in oxidative stress markers,including blood urea nitrogen(BUN),urinary creatinine(Ucr),urinary protein(PRO),superoxide dismutase(SOD),and malondialdehyde(MDA)(P＜0.05).Histological analyses through hematoxy-lin-eosin(H&E),Periodic Acid-Schiff(PAS),and Sirius red staining demonstrated alleviation of glo-merular mesangial hyperplasia,glomerular hypertrophy,and tubular inflammation.Furthermore,hUC-MSCs treatment downregulated the expression of oxidative stress-related proteins,such as NADPH oxi-dase 4(NOX4)and thioredoxin-interacting protein(TXNIP),and reduced reactive oxygen species(ROS)production(P＜0.05).Meanwhile,human renal cortical proximal tubule epithelial cells(HK-2 cells)were selected for validation in vitro experiments using high glucose treatment followed by super-natants of hUC-MSCs(MSC-CM),and Western blotting showed that the expression of both NOX4 and TXNIP was inhibited(P＜0.05)and ROS expression was reduced.In conclusion,hUC-MSC treatment effectively lowered blood glucose levels and improved renal function in DN mice,likely through the sup-pression of NOX4 expression and TXNIP-mediated oxidative stress.

Objective:To develop habitat radiomics models to predict early treatment responses to the hepatic arterial infusion chemotherapy (HAIC) combined with targeted therapy or immunotherapy in advanced hepatocellular carcinoma (HCC) patients, and to guide clinical diagnosis and treatment.Methods:From October 2021 to Decemeber 2023, at Army Characteristic Medical Center of PLA (Chongqing Daping Hospital) and the First Affiliated Hospital of Chongqing Medical University, 94 patients with advanced HCC who received HAIC combined with targeted therapy or immunotherapy were retrospectively enrolled. According to the treatment results, the patients were divided into response group and non-response group. Univariate and multivariate logistic regression were performed to analyze the clinical data of the patients. Based on contrast-enhanced CT images, tumor habitats were delineated and habitat features were extracted with k-means clustering, and the imaging features of arterial and venous phases were also extracted. The least absolute shrinkage and selection operator (LASSO) was used for dimensionality reduction. Feature selection was performed using LASSO to reduce dimensions, and then the selected features were further refined through stepwise logistic regression analysis.Binary logistic regression models were conducted to develop the habitat radiomics model, arterial phase radiomics model (APRM), venous phase radiomics model (VPRM), clinical data model, as well as the combination of radiomics model and clinical data model to predict early treatment (after 2 treatment cycles) response. Receiver operating characteristic curves (ROC) were plotted, and model performance was evaluated by the area under the curve (AUC), calibration curves, and decision curve. The models were validated through Bootstrap methods (1 000 times). DeLong test was used to compare AUC values.Results:The results of cluster analysis identified 3 characteristic habitats in HCC imaging: low-, medium-, and high-enhancement tumor habitats. The proportion of high-enhancement habitats was higher than that in the non-response group. A predictive model was established based on the proportions of these 3 habitats. Based on the proportion of low-, medium-, and high-enhancement habitats within the tumor, a habitat radiomics model was constructed. After LASSO selection and logistic regression analysis, 3 arterial phase and 3 venous phase radiomic features were selected to build the APRM and VPRM, respectively. Logistic regression analysis identified the following factors for the clinical data model: comorbidities ( OR=0.275, P=0.031), maximum tumor diameter ( OR=1.149, P=0.019), red blood cell count ( OR=0.463, P=0.022), alpha fetoprotein >400 μg/L ( OR=3.452, P=0.017), and tyrosine kinase inhibitor therapy ( OR=3.072, P=0.048). Among the single predictive model′s comparison, the AUC of habitat radiomics model was 0.860 (95% confidence interval(95% CI): 0.789 to 0.932), while those of the APRM、VPRM and clinical data model were 0.850 (95% CI: 0.773 to 0.926), 0.855 (95% CI: 0.782 to 0.928), and 0.774 (95% CI: 0.681 to 0.867), respectively, and there were no statistically significant among these models (all P>0.05). Among the combination models, the AUC of the habitat rediomic-clinical data combination model was 0.881 (95% CI: 0.814 to 0.947); the AUC of arterial phase rediomic-clinical data combination model was 0.897 (95% CI: 0.833 to 0.961); and the AUC of venous phase rediomic-clinical data combination model was 0.888 (95% CI: 0.826 to 0.951), but there were no statistically significant among the 3 models (all P>0.05). The calibration curve showed that the habitat rediomic-clinical data combination model had the most accurate predictive probability. Internal validation showed that the AUC of habitat rediomic-clinical data combination model was 0.848 (95% CI: 0.772 to 0.922), and the predictive performance was better than that of the clinical-data model (0.733 (95% CI: 0.670 to 0.863)). Conclusion:The habitat radiomics model based on enhanced CT can effectively predict early treatment responses to the HAIC combined with targeted therapy or immunotherapy in advanced HCC patients, which provides theoretical basis for individualized treatment in advanced HCC.

Objective:To investigate the effects of prognostic nutritional index (PNI) on the readmission rate, complication rate, mortality rate and survival of patients with liver cirrhosis.Methods:From January 1, 2020 to December 31, 2022, 395 hospitalized patients with liver cirrhosis at Tianmen Hospital Affiliated to Wuhan University of Science and Technology were retrospectively enrolled. The clinical data were collected from the patients at their first hospitalization (baseline period) and re-hospitalization during follow-up period. The 18-month follow-up was divided into 4 periods, including the first period (from the 0th to the 3rd month), the second one was from the 4th to the 6th month, the third one was from the 7th to the 12th month, and the fourth one was from the 13th to the 18th month of follow-up. The prognostic value of PNI for patients with liver cirrhosis was evaluated through the receiver operating characteristic curve (ROC) of the baseline PNI. The 395 patients were divided into the low PNI group and the high PNI group based on the optimal cut-off value of PNI on the ROC. Patients readmitted during each follow-up period were divided into the PNI improvement group (PNI at follow-up -PNI at baseline>0) and the PNI non-improvement group (PNI at follow-up-PNI at baseline ≤0). Independent sample t-test, one-way analysis of variance (ANOVA), Mann-Whitney U test, chi-square test or Fisher′s exact test were used for statistical analysis. Survival curves depicting the relationship between PNI and overall survival rate of patients with liver cirrhosis were constructed using the Kaplan-Meier method. Results:The ROC analysis indicated that the optimal cut-off value of PNI at baseline was 32.65, with an area under the curve of 0.639 (95% confidence interval: 0.541 to 0.738, P=0.011), with a sensitivity of 0.567 and a specificity of 0.701. There were 269 cases in the high PNI group and 126 cases in the low PNI group. The readmission rate, complication rate and mortality rate in the low PNI group were all higher than those in the high PNI group at the first and fourth follow-up periods (32.5% (41/126) vs. 22.3% (60/269), 31.7% (40/126) vs. 20.4% (55/269), 6.3% (8/126) vs. 1.1% (3/269), 25.0% (29/116) vs. 16.2% (42/260), 25.0% (29/116) vs. 15.4% (40/260), 6.0% (7/116) vs. 1.5% (4/260)), and the differences were statistically significant ( χ2=4.72, 6.00, 6.86, 4.10, 4.95, and 4.24; P=0.030, 0.014, 0.009, 0.043, 0.026, and 0.040). The mortality rates of the PNI improvement group at the first and fourth follow-up periods were both lower than those of the PNI non-improvement group (4.3% (2/47) vs. 16.7% (9/54), 0 (0/24) vs. 23.4% (11/47)), and the differences were statistically significant ( χ2=3.99, Fisher′s exact test; P=0.046 and 0.012). There were no statistically significant difference in the incidence of complications between the PNI improvement group and the PNI non-improvement group at each follow-up period (all P>0.05). The Kaplan-Meier survival curve demonstrated that the average survival time of the high PNI group was longer than that of the low PNI group (17.54 months (95% confidence interval: 17.26 to 17.83 months) vs. 16.74 months (95% confidence interval: 16.96 to 17.52 months), and the difference was statistically significant ( χ2=9.18, P<0.001). The survival rate of the high PNI group at the 18th month of follow-up period was higher than that of the low PNI group (95.2% (256/269) vs. 86.5% (109/126), and the difference was statistically significant ( χ2=9.17, P=0.002). Conclusions:PNI has certain predictive efficacy for the survival period of patients with liver cirrhosis. Low-level PNI may increase the readmission rate, complication rate, and mortality of patients with liver cirrhosis, and shorten the survival period, indicating poor prognosis.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To investigate the efficacy of volar anatomical locking plates combined with dorsal mini-plates in treating com-plex distal radius fractures.Methods:We retrospectively included patients with complex distal radius fractures who had been treated with volar locking plates and dorsal mini-plates at Chongqing General Hospital from January 2019 to June 2023.The quality of articu-lar surface fragment reduction was assessed through image analysis.Follow-up data included the Mayo wrist score,Disabilities of the Arm,Shoulder,and Hand Questionnaire(DASH)score,wrist range of motion,time to fracture healing,and complications.Results:Twenty-eight patients[19 males,9 females;mean age,(45.4±11.9)years]were included,with a mean follow-up of 1(4.9±3.6)months.Their injury mechanisms included falls from height(11 cases),traffic accidents(9 cases),and simple falls(8 cases).After op-eration,the volar tilt was(5.1±4.9)°,and the ulnar inclination was(19.8±2.8)°;at the final follow-up,the angles were(5.2±4.8)° and(19.3±2.5)°,respectively,neither showing any significant change(P>0.05).At the final follow-up,all fractures healed,with a mean healing time of 3.6 months.At 1 year after operation,the wrist extension was(50.7±6.3)°;the wrist flexion was(49.4±6.1)°;the DASH score was 15.0±6.3;the Mayo wrist scores were excellent or good in 24 cases;the grip strength of the affected side averaged 84.4%of that of the contralateral side.No implant loosening occurred.Two cases of superficial wound infection and one case of exten-sor tendon irritation were reported.Conclusion:Locked volar plat-ing combined with dorsal mini-plating provides stable fixation for comminuted articular surface fragments in complex distal radius fractures,enabling early functional rehabilitation with favorable wrist recovery and low rates of dorsal tendon irritation.

The hydroxyl value and conjugated linoleic acid content of dehydrated castor oils are two important indicators that reflect its properties.Thus,monitoring the two indicators can better realize the industrial production of high-quality dehydrated castor oils.However,traditional chemical measurement methods have many disadvantages in determination of the two indictors,including large reagent consumption,long determination time,and cannot achieve rapid monitoring.Fourier transform infrared spectrometry(FTIR)is a new and non-destructive detection method that is low-cost and can achieve rapid detection.In this work,FTIR technique was employed to collect spectral information of dehydrated castor oils and analyze the relationship between FTIR spectral information and hydroxyl value and conjugated linoleic acid content,and a rapid detection method for detecting the property indicators of dehydrated castor oils was thus established.FTIR scanning was performed on dehydrated castor oils with a hydroxyl value of 21.9-161.4 mg KOH/g and a conjugated linoleic acid content of less than 37.5%.Among different preprocessing methods,orthogonal scatter correction(OSC)could improve the prediction accuracy of the resulting model,by which the optimal modeling data segments for hydroxyl value and conjugated linoleic acid content were 3200-3800 cm-1 and 800-1200 cm-1,respectively,and the optimal modeling method was partial least squares(PLS).The coefficients of determination of the optimal models for hydroxyl value and conjugated linoleic acid content were all above 0.99.

Objective To construct a competency evaluation model for forensic practitioners,providing a reference for their training and assessment.Methods Based on the iceberg and onion models of com-petency,and with reference to Spencer's Competency Dictionary,literature research was conducted and focus group interviews were employed to preliminarily construct core indices and measurement items for evaluating the competency of forensic practitioners.The Delphi method was applied for two rounds of expert consultation to further refine the competency evaluation index system.The analytic hierarchy process(AHP)was used to calculate the weights of the indices.Results A competency evaluation model for forensic practitioners was constructed,consisting of 7 core indices,encompassing forensic skills,identification service capabilities,and the ability to apply relevant legal knowledge and 49 mea-surement items.The weights of the core indices and measurement items were determined.Conclusion The constructed competency evaluation model for forensic practitioners is scientifically sound and inno-vative,and has unique characteristics of forensic medicine compared with other medical models.

Objective:To explore the impact of plant and animal dietary behaviors on type 2 diabetes mellitus (T2DM) in older adults aged ≥65 in 18 longevity areas of China.Methods:The subjects were 5 223 older adults over 65 years old from the Healthy Ageing and Biomarkers Cohort Study (HABCS) in 18 longevity areas in China. Through a questionnaire survey and physical examination, information about their demographic characteristics, lifestyles, daily activities, self-health status, current diseases, and fasting venous blood were collected. Food Frequency and Questionnaire (FFQ) was used to collect data on food intake frequency. Based on the prior method, the plant-based diet index (PDI) and animal-based diet index (ADI) of 5 223 older adults were calculated. Subjects were divided into three groups (low-level group: PDI<39 or ADI<31, middle-level group: 39≤PDI≤42 or 31≤ADI≤34, high-level group: PDI>42 or ADI>34) by tertiles of PDI and ADI. Multivariate logistic regression was used to analyze the association between PDI and ADI and the risk of T2DM.Results:The average age of 5 223 subjects was (84.8±11.5) years, with the median ( Q1, Q3) of PDI about 41(38, 43) and the median ( Q1, Q3) of ADI about 33 (30, 35). The prevalence rate of T2DM was 16.41% (857/5 223). After adjusting for covariates, multivariate logistic regression showed that PDI was negatively associated with T2DM. Compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 0.83 (0.69-0.99). ADI was positively associated with T2DM, and compared with the low-level group, the OR (95% CI) for T2DM in the high-level group was 1.28 (1.06-1.55). For every one-point increase in PDI and ADI, the risk of T2DM decreased by 2% and increased by 3%, respectively, with the OR (95% CI) of 0.98 (0.96-1.00) and 1.03 (1.01-1.06), respectively. Conclusion:In Chinese older adults ≥65 years in 18 longevity areas, higher adherence to the plant-based behavior may be negatively associated with the risk of T2DM, while higher adherence to the animal-based behavior may be positively associated with the risk of T2DM.