ObjectiveTo study the mechanism of compound Xishu granules （CXG） in inhibiting the proliferation of hepatocellular carcinoma cells by regulating ferroptosis. MethodsThe transplanted tumor model of human Huh7 was established with nude mice and the successfully modeled mice were randomized into model， Fufang Banmao （0.21 g·kg^-1）， low-dose （1.87 g·kg^-1） CXG， medium-dose （3.74 g·kg^-1） CXG， and high-dose （7.49 g·kg^-1） CXG groups. Mice were administrated with drinking water or CXG for 28 days， and the body weight and tumor volume were measured every 4 days. Hematoxylin-eosin staining was employed to observe the histopathological changes of tumors. The cell-counting kit-8 （CCK-8） was used to examine the survival rate of Huh7 cells treated with different concentrations （0， 31.25， 62.5， 125， 250， 500， 1 000 mg·L^-1） of CXG for 24 h and 48 h. CA-AM， DCFH-DA， and C11-BODIPY^581/591 fluorescent probes were used to determine the intracellular levels of ferrous ion （Fe²⁺）， reactive oxygen species （ROS）， and lipid peroxide （LPO）， respectively. The colorimetric method was employed to measure the levels of glutathione （GSH） and superoxide dismutase （SOD）. Western blot was employed to determine the protein levels of glutathione peroxidase 4 （GPX4）， transferrin receptor 1 （TFR1）， and ferritin heavy chain 1 （FTH1）， respectively. ResultsIn the animal experiment， compared with the model group， the drug treatment groups showed reductions in the tumor volume from day 12 （P<0.01）. After treatment， the Fufang Banmao and low-， medium-， and high-dose CXG groups had lower tumor volume， relative tumor volume， and tumor weight than the model group （P<0.05）， with tumor inhibition rates of 48.99%， 79.93%， 91.38%， and 97.36%， respectively. Moreover， the CXG groups had lower tumor volume and relative tumor volume （P<0.05 in all the three dose groups） and lower tumor weight （P<0.05 in medium-dose and high-dose groups） than the Fufang Banmao group. Compared with the model group， the drug treatment groups showed reduced number of tumor cells， necrotic foci with karyopyknosis， nuclear fragmentation， and nucleolysis， and the high-dose CXG group showed an increase in the proportion of interstitial fibroblasts. In the cell experiment， compared with the blank group， CXG reduced the survival rate of Huh7 cells in a dose-dependent manner after incubation for 24 h and 48 h （P<0.05）. Compared with the blank group， the RSL3 group and the low-， medium-， and high-dose CXG groups showed a decrease in the relative fluorescence intensity of CA-AM and increases in the fluorescence intensity of DCFH-DA and fluorescence ratio of C11-BODIPY^581/591， which indicated elevations in the levels of Fe²⁺ （P<0.01）， ROS （P<0.05）， and LPO （P<0.01）， respectively. Compared with the blank group， the RSL3 and low-， medium-， and high-dose CXG groups showed lowered levels of GSH and SOD （P<0.05）. In addition， the RSL3 group and the medium- and high-dose CXG groups showed down-regulated expression of GPX4 and FTH1 （P<0.05）， and the low- and high-dose CXG groups presented up-regulated expression of TFR1 （P<0.05）. ConclusionCXG suppresses the proliferation of hepatocellular carcinoma cells by inducing ferroptosis via downregulating the GSH-GPX4 signaling axis and increasing intracellular Fe²⁺and LPO levels.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

The accumulation of uremic toxins such as urea nitrogen, blood creatinine, and uric acid of patients with renal failure in vivo would lead to aggravated kidney damage. In this study, coated aldehyde oxy-starch (CAO) was used as an adsorbent to investigate its in vitro adsorption performance on renal failure indexes for urea, indoxyl sulfate (INS), monomethylamine (MMA), dimethylamine (DMA), uric acid (UA), and creatinine (Cr). The effects of variables such as pH, temperature, concentration, dosage, and time on the adsorption capacity of CAO were systematically investigated, employing analytical techniques of high-performance liquid chromatography (HPLC) and gas chromatography (GC). The results revealed that CAO exhibited a strong adsorption capacity for urea, INS, and MMA, alongside a moderate adsorption capacity for DMA, UA, and Cr. The adsorption kinetics and thermodynamic studies indicated that the adsorption of urea and UA by CAO were fitted in pseudo-first-order kinetics, and the adsorption isotherm aligned with the Freundlich adsorption model. The enthalpy change ΔH of urea in adsorption was in the range of 40 to 60 kJ·mol^-1, which demonstrated the presence of strong adsorption force due to the interactions of coordinating groups. The ΔH of UA was greater than 80 kJ·mol^-1, indicating the generation of chemical bonds during the adsorption. Both of them, Gibbs free energy ΔG was less than 0, within the range of -20 to 0 kJ·mol^-1, suggested that the adsorption of urea and UA by CAO occurred spontaneously as physical adsorption process. The adsorption entropy ΔS of urea and UA was > 0, which indicated an increase in entropy throughout the adsorption. The infrared spectroscopygram showed the formation of a chemical bond, specifically the imine bond, following the adsorption of urea by CAO, thereby indicating a chemical reaction during the adsorption. This study elucidates the adsorption mechanism of CAO on various indexes of renal failure, providing a scientific basis for its clinical usage.

Objective To investigate the global burden of visceral leishmaniasis (VL) from 1990 to 2021 and predict the trends in the burden of VL from 2022 to 2035, so as to provide insights into global VL prevention and control. Methods The global age-standardized incidence, prevalence, mortality and disability-adjusted life years (DALYs) rates of VL and their 95% uncertainty intervals (UI) were captured from the Global Burden of Disease Study 2021 (GBD 2021) data resources. The trends in the global burden of VL were evaluated with average annual percent change (AAPC) and 95% confidence interval (CI) from 1990 to 2021, and gender-, age-, country-, geographical area- and socio-demographic index (SDI)-stratified burdens of VL were analyzed. The trends in the global burden of VL were projected with a Bayesian age-period-cohort (BAPC) model from 2022 to 2035, and the associations of age-standardized incidence, prevalence, mortality, and DALYs rates of VL with SDI levels were examined with a smoothing spline model. Results The global age-standardized incidence [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)], prevalence [AAPC = -0.06%, 95% CI: (-0.06%, -0.06%)], mortality [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)] and DALYs rates of VL [AAPC = -2.38%, 95% CI: (-2.44%, -2.33%)] all appeared a tendency towards a decline from 1990 to 2021, and the highest age-standardized incidence [2.55/10⁵, 95% UI: (1.49/10⁵, 4.07/10⁵)], prevalence [0.64/10⁵, 95% UI: (0.37/10⁵, 1.02/10⁵)], mortality [0.51/10⁵, 95% UI: (0, 1.80/10⁵)] and DALYs rates of VL [33.81/10⁵, 95% UI: (0.06/10⁵, 124.09/10⁵)] were seen in tropical Latin America in 2021. The global age-standardized incidence and prevalence of VL were both higher among men [0.57/10⁵, 95% UI: (0.45/10⁵, 0.72/10⁵); 0.14/10⁵, 95% UI: (0.11/10⁵, 0.18/10⁵)] than among women [0.27/10⁵, 95% UI: (0.21/10⁵, 0.33/10⁵); 0.06/10⁵, 95% UI: (0.05/10⁵, 0.08/10⁵)], and the highest mortality of VL was found among children under 5 years of age [0.24/10⁵, 95% UI: (0.08/10⁵, 0.66/10⁵)]. The age-standardized incidence (r = -0.483, P < 0.001), prevalence (r = -0.483, P < 0.001), mortality (r = -0.511, P < 0.001) and DALYs rates of VL (r = -0.514, P < 0.001) correlated negatively with SDI levels from 1990 to 2021. In addition, the global burden of VL was projected with the BAPC model to appear a tendency towards a decline from 2022 to 2035, and the age-standardized incidence, prevalence, mortality and DALYs rates were projected to be reduced to 0.11/10⁵, 0.03/10⁵, 0.02/10⁵ and 1.44/10⁵ in 2035, respectively. Conclusions Although the global burden of VL appeared an overall tendency towards a decline from 1990 to 2021, the burden of VL showed a tendency towards a rise in Central Asia and western sub-Saharan African areas. The age-standardized incidence and prevalence rates of VL were relatively higher among men, and the age-standardized mortality of VL was relatively higher among children under 5 years of age. The global burden of VL was projected to continue to decline from 2022 to 2035.

ObjectiveTo evaluate the efficacy of Shuanghua drink in treating primary dysmenorrhea in the rat model and explore its mechanism of action. MethodsAn oxytocin-induced writhing mouse model was established to evaluate the analgesic effect of Shuanghua drink. Forty-eight non-pregnant female institute of cancer research （ICR） mice were randomly divided into six groups， including a blank group， a model group， an ibuprofen group （85.00 mg·kg^-1）， a low-dose group of Shuanghua drink （7.14 mL·kg^-1）， a medium-dose group of Shuanghua drink （14.28 mL·kg^-1）， and a high-dose group of Shuanghua drink （28.57 mL·kg^-1）. Each group consisted of eight mice. All treatment groups received daily intragastric administration at corresponding doses for 10 consecutive days. One hour after the final administration， 2 U of oxytocin was intraperitoneally injected per mouse. The writhing latency and number of writhing within 20 minutes were recorded. A primary dysmenorrhea rat model was established by using estradiol benzoate and oxytocin to evaluate the inhibitory effect of Shuanghua drink on the contraction of uterine smooth muscle. Forty-eight non-pregnant female Sprague-Dawley （SD） rats were divided into six groups， including a blank group， a model group， an ibuprofen group （51.00 mg·kg^-1）， a low-dose group of Shuanghua drink （4.28 mL·kg^-1）， a medium-dose group of Shuanghua drink （8.57 mL·kg^-1）， and a high-dose group of Shuanghua drink （17.10 mL·kg^-1）. Each group consisted of eight rats. Rats received subcutaneous injections of estradiol benzoate for 10 consecutive days to enhance uterine sensitivity. On the eleventh day， oxytocin （2 U/rat） was intraperitoneally administered to induce abnormal uterine contractions for establishing the primary dysmenorrhea model. All treatment groups received daily intragastric administration from the second day of modeling for 10 days. The effects of Shuanghua drink were evaluated by using parameters including uterine motility and the variation rate of uterine motility. The mechanism of action was investigated in rats with primary dysmenorrhea. The content of prostaglandin F_2α （PGF_2α）， prostaglandin E₂ （PGE₂）， thromboxane B₂ （TXB₂）， prostacyclin metabolite （6-keto-PGF_1α）， and β-endorphin （β-EP） in uterine tissue of rats was detected by using enzyme-linked immunosorbent assay （ELISA）. The changes in the content of nitric oxide （NO） and inducible nitric oxide synthase （iNOS） were analyzed via colorimetric assay. Western blot was performed to determine the content of phosphorylated inhibitor of kappa B kinase beta （p-IKKβ）/IKKβ， phosphorylated inhibitor of kappa B alpha （p-IκBα）， IκBα， phosphorylated p65 （p-p65）， p65， and cyclooxygenase-2 （COX-2） proteins in uterine tissue of rats. ResultsIn the oxytocin-induced writhing mouse model， the model group exhibited significantly shortened writhing latency and increased writhing frequency compared to the control group （P<0.01）. Both the ibuprofen group and the high-dose group of Shuanghua drink displayed prolonged writhing latency （P<0.05）， while the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink exhibited reduced writhing frequency （P<0.01）. In the primary dysmenorrhea rat model， the uterine motility and its variation rate in the model group were significantly higher than those in the blank group （P<0.01）. These parameters were markedly suppressed by ibuprofen and Shuanghua drink at all tested doses （P<0.01）. For the mechanism of action， the model group showed significantly increased PGF_2α/PGE₂， TXB₂/6-keto-PGF_1α， NO， and iNOS in uterine tissue （P<0.05， P<0.01） and significantly decreased β-EP （P<0.01）. These parameters were significantly attenuated in the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink. The PGF_2α/PGE₂ （P<0.01）， TXB₂/6-keto-PGF_1α （P<0.01）， NO （medium-dose group P<0.05）， and iNOS （P<0.01） were reduced， and the β-EP （medium-dose group P<0.05） was up-regulated. Compared to the model group， the ibuprofen group and medium-dose group of Shuanghua drink showed significantly increased content of β-EP in the serum of rats （P<0.05）. Compared to the blank group， the model group showed significantly elevated expressions of COX-2， p-IKKβ/IKKβ， p-IκBα/IκBα， and p-p65/p65 proteins （P<0.01） and significantly reduced anti-inflammatory protein IκBα （P<0.05）. Compared to the model group， the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink showed significantly reduced expressions of COX-2 （P<0.01）， p-IKKβ/IKKβ （P<0.01）， p-IκBα/IκBα （P<0.05， P<0.01）， and p-p65/p65（P<0.01） and up-regulated expression of IκBα protein （P<0.05， P<0.01）. ConclusionShuanghua drink effectively alleviates primary dysmenorrhea through analgesia and suppression of abnormal contractions of uterine smooth muscle. Its mechanism may be mediated by reduced levels of PGF_2α/PGE₂， TXB₂/6-keto-PGF_1α， iNOS， and NO， elevated β-EP level， and inhibited COX-2/NF-κB signaling pathway.

ObjectiveTo evaluate the efficacy of Shuanghua drink in treating primary dysmenorrhea in the rat model and explore its mechanism of action. MethodsAn oxytocin-induced writhing mouse model was established to evaluate the analgesic effect of Shuanghua drink. Forty-eight non-pregnant female institute of cancer research （ICR） mice were randomly divided into six groups， including a blank group， a model group， an ibuprofen group （85.00 mg·kg^-1）， a low-dose group of Shuanghua drink （7.14 mL·kg^-1）， a medium-dose group of Shuanghua drink （14.28 mL·kg^-1）， and a high-dose group of Shuanghua drink （28.57 mL·kg^-1）. Each group consisted of eight mice. All treatment groups received daily intragastric administration at corresponding doses for 10 consecutive days. One hour after the final administration， 2 U of oxytocin was intraperitoneally injected per mouse. The writhing latency and number of writhing within 20 minutes were recorded. A primary dysmenorrhea rat model was established by using estradiol benzoate and oxytocin to evaluate the inhibitory effect of Shuanghua drink on the contraction of uterine smooth muscle. Forty-eight non-pregnant female Sprague-Dawley （SD） rats were divided into six groups， including a blank group， a model group， an ibuprofen group （51.00 mg·kg^-1）， a low-dose group of Shuanghua drink （4.28 mL·kg^-1）， a medium-dose group of Shuanghua drink （8.57 mL·kg^-1）， and a high-dose group of Shuanghua drink （17.10 mL·kg^-1）. Each group consisted of eight rats. Rats received subcutaneous injections of estradiol benzoate for 10 consecutive days to enhance uterine sensitivity. On the eleventh day， oxytocin （2 U/rat） was intraperitoneally administered to induce abnormal uterine contractions for establishing the primary dysmenorrhea model. All treatment groups received daily intragastric administration from the second day of modeling for 10 days. The effects of Shuanghua drink were evaluated by using parameters including uterine motility and the variation rate of uterine motility. The mechanism of action was investigated in rats with primary dysmenorrhea. The content of prostaglandin F_2α （PGF_2α）， prostaglandin E₂ （PGE₂）， thromboxane B₂ （TXB₂）， prostacyclin metabolite （6-keto-PGF_1α）， and β-endorphin （β-EP） in uterine tissue of rats was detected by using enzyme-linked immunosorbent assay （ELISA）. The changes in the content of nitric oxide （NO） and inducible nitric oxide synthase （iNOS） were analyzed via colorimetric assay. Western blot was performed to determine the content of phosphorylated inhibitor of kappa B kinase beta （p-IKKβ）/IKKβ， phosphorylated inhibitor of kappa B alpha （p-IκBα）， IκBα， phosphorylated p65 （p-p65）， p65， and cyclooxygenase-2 （COX-2） proteins in uterine tissue of rats. ResultsIn the oxytocin-induced writhing mouse model， the model group exhibited significantly shortened writhing latency and increased writhing frequency compared to the control group （P<0.01）. Both the ibuprofen group and the high-dose group of Shuanghua drink displayed prolonged writhing latency （P<0.05）， while the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink exhibited reduced writhing frequency （P<0.01）. In the primary dysmenorrhea rat model， the uterine motility and its variation rate in the model group were significantly higher than those in the blank group （P<0.01）. These parameters were markedly suppressed by ibuprofen and Shuanghua drink at all tested doses （P<0.01）. For the mechanism of action， the model group showed significantly increased PGF_2α/PGE₂， TXB₂/6-keto-PGF_1α， NO， and iNOS in uterine tissue （P<0.05， P<0.01） and significantly decreased β-EP （P<0.01）. These parameters were significantly attenuated in the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink. The PGF_2α/PGE₂ （P<0.01）， TXB₂/6-keto-PGF_1α （P<0.01）， NO （medium-dose group P<0.05）， and iNOS （P<0.01） were reduced， and the β-EP （medium-dose group P<0.05） was up-regulated. Compared to the model group， the ibuprofen group and medium-dose group of Shuanghua drink showed significantly increased content of β-EP in the serum of rats （P<0.05）. Compared to the blank group， the model group showed significantly elevated expressions of COX-2， p-IKKβ/IKKβ， p-IκBα/IκBα， and p-p65/p65 proteins （P<0.01） and significantly reduced anti-inflammatory protein IκBα （P<0.05）. Compared to the model group， the ibuprofen group and the low-dose， medium-dose， and high-dose groups of Shuanghua drink showed significantly reduced expressions of COX-2 （P<0.01）， p-IKKβ/IKKβ （P<0.01）， p-IκBα/IκBα （P<0.05， P<0.01）， and p-p65/p65（P<0.01） and up-regulated expression of IκBα protein （P<0.05， P<0.01）. ConclusionShuanghua drink effectively alleviates primary dysmenorrhea through analgesia and suppression of abnormal contractions of uterine smooth muscle. Its mechanism may be mediated by reduced levels of PGF_2α/PGE₂， TXB₂/6-keto-PGF_1α， iNOS， and NO， elevated β-EP level， and inhibited COX-2/NF-κB signaling pathway.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.