This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

This paper introduces a real-world cohort research model for community-acquired pneumonia （CAP） based on the Jiangsu Traditional Chinese Medicine （TCM） Dominant Diseases Diagnosis and Treatment Data Platform. Firstly， data cleaning is performed by standardizing diagnosis， symptoms， treatment and imaging， intelligently extracting unstructured information， and cleaning and constructing a standardized database. Secondly， for cohort establishment， CAP patients across the province are screened in accordance with CAP diagnostic criteria to build a high-quality disease-specific cohort. Lastly， in terms of protocol design， the characteristics of TCM research and the CAP disease profile are considered to determine appropriate inclusion and exclusion criteria， estimate sample size， define interventions， outcomes and economic evaluations， providing a reference for real-world TCM research on CAP.

Objective: To explore the nonlinear dynamic effects of social capital, adverse childhood experiences (ACEs) and depressive symptoms on suicidal behavior among vocational high school students, so as to provide theoretical basis and practical references for formulating suicide prevention strategies. Methods: A convenience sampling method was employed to include 668 students from a vocational high school from Wuhan in March 2023. Social capital was used as the asymmetry variable, while ACEs and depressive symptoms were used as bifurcation variables, a cusp catastrophe model was constructed to analyze the nonlinear changes in suicidal behavior among vocational high school students, and its fit was compared with linear and Logistic regression models. Results: Among students in the health vocational high school in Wuhan, only suicidal ideation accounted for 8.5%, only suicide attempt for 18.6%, neither accounted for 31.9%, and both for 41.0%. Gender, left behind experience, family economic status, parental parenting styles, depressive symptoms, social capital, and ACEs were all related factors influencing suicidal behavior among vocational high school students ( χ 2/H=19.03, 13.33, 21.11, 46.70, 144.38, 24.61, 118.77, all P <0.05). Violin plots showed a bimodal distribution of suicidal behavior, indicating nonlinear variation characteristics. The cusp catastrophe model results showed that social capital was negatively correlated with suicidal behavior, but the relationship was bifurcated by ACEs ( α social capital = -0.006 , β ACEs =0.075) and depressive symptoms ( α social capital =-0.013, β depressive =0.028) (all P <0.05). When both ACEs and depressive symptoms coexisted, the impact of ACEs was stronger ( β ACEs =0.077, β depressive =0.014) (both P <0.05). The cusp catastrophe model fitted ( R 2=0.886, 0.881, 0.882) better than the linear ( R 2=0.258, 0.219, 0.258) and Logistic regression models ( R 2= 0.242, 0.211 , 0.176). Gender stratified analysis results showed that bifurcation effect of ACEs was stronger in males than in females( β boys =0.224, β girls =0.086); in females, both ACEs and depressive symptoms had a bifurcation effect, with the former showing a stronger effect ( β ACEs =0.062, β depressive =0.015) (all P <0.05). Conclusions Suicidal behavior among vocational high school students exhibits nonlinear characteristics. Improving social capital to reducing ACEs and depressive symptoms may contribute to decreasing adolescent suicidal behaviors.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTranscranial magneto-acoustic stimulation (TMAS) is an emerging non-invasive neuromodulation technique that may provide a novel non-pharmacological intervention strategy for Parkinson's disease (PD). PD is characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc), leading to motor impairments such as bradykinesia, tremor, and rigidity. Increasing evidence indicates that mitochondrial dysfunction and impaired mitochondrial quality control are central mechanisms underlying dopaminergic neuronal loss. In particular, abnormalities in mitophagy and mitochondrial fission-fusion balance contribute substantially to oxidative stress, energy metabolic failure, and neuronal injury. At present, most clinical treatments for PD mainly alleviate symptoms but do not effectively halt disease progression. Therefore, exploring new interventions targeting the core pathological mechanisms is of considerable significance. This study aims to investigate whether TMAS can improve neural damage and motor dysfunction in PD mice by regulating mitophagy and the fission/fusion dynamic balance, thereby providing theoretical and experimental support for its application in PD treatment. MethodsMale C57BL/6 mice were used in this study. A PD model was established by intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) for 7 consecutive days. After model induction, mice in the intervention group received TMAS once daily for 14 consecutive days, whereas the corresponding control group received sham stimulation. The stimulation target was positioned over the primary motor cortex (M1). Motor performance was evaluated using the pole test and the open-field test. To verify the activation effect of TMAS on the target cortical region, c-Fos immunohistochemistry was performed in the M1. To assess nigral dopaminergic neuronal injury, tyrosine hydroxylase (TH) immunohistochemistry was used to quantify TH-positive neurons in the SNc. Mitochondrial function was evaluated by measuring reactive oxygen species (ROS) levels and adenosine triphosphate (ATP) content in the SNc. Western blot was further performed to determine the expression of mitophagy-related proteins, including PINK1, Parkin, LC3-II, and p62, as well as mitochondrial dynamics-related proteins, including Drp1 and Opa1. ResultsTMAS significantly increased the number of c-Fos-positive cells in M1 (P<0.000 1), indicating effective activation of neurons in the targeted cortical region. Compared with the control group, MPTP-treated mice exhibited marked motor dysfunction, including a significant reduction in total distance traveled in the open-field test (P<0.000 1) and mean speed (P=0.000 1), as well as significant prolongation of turn time and total climbing time in the pole test (P<0.000 1). These behavioral impairments were accompanied by a substantial loss of TH-positive dopaminergic neurons in the SNc, whereas TMAS significantly increased TH-positive neuron survival (P<0.000 1). In parallel, MPTP induced a pronounced increase in ROS levels and a significant reduction in ATP content, indicating severe mitochondrial dysfunction and energy metabolism impairment (P<0.01). TMAS treatment significantly improved motor performance, as reflected by the reversal of MPTP-induced impairment in the open-field and pole tests, and significantly reduced ROS accumulation (P<0.01) while restoring ATP production (P<0.001). At the molecular level, MPTP markedly downregulated PINK1 and Parkin, decreased p62 expression, increased LC3-II accumulation, elevated Drp1 expression, and reduced Opa1 expression, whereas TMAS significantly reversed these abnormalities, suggesting restoration of mitophagy-related mitochondrial quality control and re-establishment of mitochondrial fission-fusion balance. Collectively, these findings indicate that TMAS ameliorates MPTP-induced neurotoxicity and restores mitochondrial homeostasis and energy metabolism. ConclusionTMAS effectively attenuates neural damage and improves motor dysfunction in MPTP-induced PD mice. Its neuroprotective effects are closely associated with multidimensional regulation of the mitochondrial quality control system, including restoration of PINK1/Parkin-mediated mitophagy and rebalancing of Drp1/Opa1-related mitochondrial dynamics. Rather than acting only as a symptomatic neuromodulatory intervention, TMAS may influence a key pathological axis of PD by improving mitochondrial homeostasis in SNc and protecting nigral dopaminergic neurons. These findings provide experimental evidence supporting TMAS as a promising non-invasive physical intervention for PD.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTranscranial magneto-acoustic stimulation (TMAS) is an emerging non-invasive neuromodulation technique that may provide a novel non-pharmacological intervention strategy for Parkinson's disease (PD). PD is characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNc), leading to motor impairments such as bradykinesia, tremor, and rigidity. Increasing evidence indicates that mitochondrial dysfunction and impaired mitochondrial quality control are central mechanisms underlying dopaminergic neuronal loss. In particular, abnormalities in mitophagy and mitochondrial fission-fusion balance contribute substantially to oxidative stress, energy metabolic failure, and neuronal injury. At present, most clinical treatments for PD mainly alleviate symptoms but do not effectively halt disease progression. Therefore, exploring new interventions targeting the core pathological mechanisms is of considerable significance. This study aims to investigate whether TMAS can improve neural damage and motor dysfunction in PD mice by regulating mitophagy and the fission/fusion dynamic balance, thereby providing theoretical and experimental support for its application in PD treatment. MethodsMale C57BL/6 mice were used in this study. A PD model was established by intraperitoneal injection of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) for 7 consecutive days. After model induction, mice in the intervention group received TMAS once daily for 14 consecutive days, whereas the corresponding control group received sham stimulation. The stimulation target was positioned over the primary motor cortex (M1). Motor performance was evaluated using the pole test and the open-field test. To verify the activation effect of TMAS on the target cortical region, c-Fos immunohistochemistry was performed in the M1. To assess nigral dopaminergic neuronal injury, tyrosine hydroxylase (TH) immunohistochemistry was used to quantify TH-positive neurons in the SNc. Mitochondrial function was evaluated by measuring reactive oxygen species (ROS) levels and adenosine triphosphate (ATP) content in the SNc. Western blot was further performed to determine the expression of mitophagy-related proteins, including PINK1, Parkin, LC3-II, and p62, as well as mitochondrial dynamics-related proteins, including Drp1 and Opa1. ResultsTMAS significantly increased the number of c-Fos-positive cells in M1 (P<0.000 1), indicating effective activation of neurons in the targeted cortical region. Compared with the control group, MPTP-treated mice exhibited marked motor dysfunction, including a significant reduction in total distance traveled in the open-field test (P<0.000 1) and mean speed (P=0.000 1), as well as significant prolongation of turn time and total climbing time in the pole test (P<0.000 1). These behavioral impairments were accompanied by a substantial loss of TH-positive dopaminergic neurons in the SNc, whereas TMAS significantly increased TH-positive neuron survival (P<0.000 1). In parallel, MPTP induced a pronounced increase in ROS levels and a significant reduction in ATP content, indicating severe mitochondrial dysfunction and energy metabolism impairment (P<0.01). TMAS treatment significantly improved motor performance, as reflected by the reversal of MPTP-induced impairment in the open-field and pole tests, and significantly reduced ROS accumulation (P<0.01) while restoring ATP production (P<0.001). At the molecular level, MPTP markedly downregulated PINK1 and Parkin, decreased p62 expression, increased LC3-II accumulation, elevated Drp1 expression, and reduced Opa1 expression, whereas TMAS significantly reversed these abnormalities, suggesting restoration of mitophagy-related mitochondrial quality control and re-establishment of mitochondrial fission-fusion balance. Collectively, these findings indicate that TMAS ameliorates MPTP-induced neurotoxicity and restores mitochondrial homeostasis and energy metabolism. ConclusionTMAS effectively attenuates neural damage and improves motor dysfunction in MPTP-induced PD mice. Its neuroprotective effects are closely associated with multidimensional regulation of the mitochondrial quality control system, including restoration of PINK1/Parkin-mediated mitophagy and rebalancing of Drp1/Opa1-related mitochondrial dynamics. Rather than acting only as a symptomatic neuromodulatory intervention, TMAS may influence a key pathological axis of PD by improving mitochondrial homeostasis in SNc and protecting nigral dopaminergic neurons. These findings provide experimental evidence supporting TMAS as a promising non-invasive physical intervention for PD.

Objective: To investigate the incidence and influencing factors of new onset suicidal behaviors among junior and senior high school students, so as to provide evidence for early warning and intervention. Methods: Using a cluster sampling method, baseline data were collected from September to November 2023 among 2 379 adolescents selected from 2 junior high schools, 2 general senior high schools and 2 vocational senior high schools in Wuhan, Hubei Province, with follow up carried out from September to November 2024. Data were collected using the School Adaptation Scale, the Essential Resilience Scale, the Personal Social Support Scale, the Adverse Childhood Experiences Questionnaire, the Adolescent Life Events Scale, the Pittsburgh Sleep Quality Index, the Center for Epidemiologic Studies Depression Scale, and the Columbia-Suicide Severity Rating Scale. Multivariate Logistic regression analysis was used to identify factors influencing new onset suicidal behavior among junior and senior high school students. Results: Among junior and senior high school students without suicide risk at baseline, 53.55% remained stable risk free during follow up, while 13.28% developed new suicidal behavior during follow up, of which suicidal ideation, suicide plan and suicide attempts accounted for 11.69%, 8.83% and 6.52%, respectively. Multivariate Logistic regression revealed that increased depressive symptoms at follow up elevated the risk of overall new onset suicidal behaviors ( OR =4.14), ideation ( OR = 4.59), plans ( OR =4.24), and attempts ( OR =4.09); poor sleep quality also increased the risk of overall new onset suicidal behaviors ( OR =2.23), plans ( OR =2.03), and attempts ( OR =2.65) (all P <0.05). Non boarding junior and senior high school students had lower risks of overall new onset suicidal behaviors and ideation ( OR=0.70 and 0.49, respectively); secondary school students with academic performance ranking in the top 20%-30% of their class had a lower risk of new onset ideation ( OR =0.27); and those whose place of origin was outside the city had a lower risk of new onset plans ( OR =0.49) (all P <0.05). Conclusions New onset suicidal behaviors among junior and senior high school students exhibit dynamic and stage specific differences. Depressive symptoms serve as a common core risk factor across all stages, whereas sleep quality, academic performance, boarding status, and place of origin exert differential influences at distinct stages.

Objective The aim of the study is to analyze the incidence patterns and epidemiological characteristics of parasitic and vector-borne diseases in the Minhang and Jinshan districts of Shanghai, and provide evidence-based information for optimizing prevention and control measures. Methods We collected information from epidemic reports and epidemiological investigation forms for cases of parasitic and vector-borne diseases from 2005 to 2024 in Shanghai's Minhang and Jinshan districts. Descriptive epidemiological method were adopted to conduct a comparative analysis of incidence trends, epidemic characteristics, and infection sources. Results A total of 229 cases in 7 categories were reported between 2005 and 2024, with an average annual incidence rate of 0.36/100 000. The average annual incidence rate in Minhang District was significantly higher than that in Jinshan District. The most prevalent diseases were malaria and dengue fever, followed by Japanese encephalitis. Monthly case reports were available, predominantly from June to October, with a peak in July-August. A statistically significant difference was observed between the two districts in case distribution during June-October (P＜0.001), whereas no significant difference was found for July-August (P=0.331). The majority of cases were young men (111/229,48.47%), aged 20-39 years. Migrant workers/farmers constituted the largest occupational group (55/229, 24.02%). Registered residents of other provinces and cities (147/229,64.19%), and the main source of infection was overseas importation (112/229,48.91%). There were no statistically significant differences in gender and household-registration composition between the two districts (P＞0.05). Significant differences existed in age, occupation, and source of infection (P＜0.05). The imported diseases were malaria and dengue fever, with Africa and Southeast Asia being the primary source locations. Malaria was the predominant disease imported from other provinces and cities, with cases having been imported from abroad since 2012. Local infections were mainly Japanese encephalitis, followed by malaria (with the last local case reported in 2010). Cases between 2005 and 2009 were predominantly imported from other provinces and cities. The proportion of cases imported from abroad increased sharply after 2010, particularly in Minhang District. Local infections sometimes arise in Jinshan District, with Japanese encephalitis serving as the primary type. Conclusions Incidence rates of parasitic and vector-borne diseases in Minhang and Jinshan districts have generally remained low. To further reduce this disease burden, it will be necessary to strengthen joint measures for prevention and control, eliminate the environmental risk factors of vector organisms, enhance monitoring and precise control of the environment and inbound personnel to prevent the occurrence and transmission of parasitic and vector-borne diseases.

Urolithiasis represents a prevalent clinical challenge marked by high recurrence rates and morbidity，with existing preventive strategies struggling to effectively curb its epidemic trajectory，thereby posing a significant threat to public health. The etiology of this condition is intricate，involving a complex network of interactions spanning classical supersaturation-crystallization theory，Randall’s plaque theory，and multifactorial elements such as cellular injury，inflammatory responses，metabolic derangements，the gut-kidney axis，immune dysregulation，and genetic predisposition. However，the critical mechanisms initiating stone formation and the early pathophysiological processes remain incompletely elucidated，constituting the core impasse in current preventive strategies. This review systematically synthesizes classical theories and cutting-edge advancements in urolithiasis etiology research，emphasizing the urgent need to integrate emerging technologies，including high-dimensional omics，advanced imaging modalities，and artificial intelligence，to dissect pivotal pathological nodes in early stone formation. Such interdisciplinary efforts are essential to overcome cognitive bottlenecks and ultimately achieve personalized，precision-based prevention strategies.