Late life depression （LLD） has long been a challenge in clinical diagnosis and treatment due to its unique and complex nature in etiology， clinical features， assessment and diagnostic procedures， as well as treatment interventions. Centered on the core content of the Expert consensus on diagnosis and treatment of late life depression （2025 edition） and integrated with current clinical focuses， this article systematically interprets the consensus regarding its background， risk factors， feature identification and multidimensional assessment， diagnostic and differential principles， treatment strategies， as well as rehabilitation and recurrence prevention management of LLD. This article aims to deepen the understanding of the consensus， promote its application in clinical practice， and further elevate the level of standardized diagnosis and treatment of LLD in China. ［Funded by National Natural Science Foundation of China （number， 82171524）］

BackgroundSuicide among adolescents has become a serious public health issue， with suicidal ideation serving as a necessary precursor to suicide attempts and death. Previous research suggests that campus exclusion， depression， and psychological resilience are closely associated with the development of suicidal ideation in individuals. However， there is a lack of longitudinal research to deeply explore the relationship between each influencing factor and suicidal ideation. ObjectiveTo explore the impact of campus exclusion on suicidal ideation among adolescents， as well as the mediating role of depression and the moderating role of resilience， so as to provide references for formulating strategies for preventing and intervening in adolescent suicide. MethodsAUsing a longitudinal research design， in November 2023， 1 226 students from 21 classes （4 classes per grade in junior high school and 3 classes per grade in senior high school） from a junior high school and a senior high school in a certain area of Shandong Province were selected as the research subjects. The Ostracism Experience Scale for Adolescents （OES-A）， the Patients' Health Questionnaire Depression Scale-9 item （PHQ-9）， and the Resilience Scale for Chinese Adolescents （RSCA） were used for assessment. The PHQ-9 suicide ideation item was evaluated again three months after the baseline survey （the two suicide ideation evaluations were respectively denoted as T1 and T2 respectively. Spearman correlation analysis was used to examine the relationships among scale scores. Model 4 and model 59 in the SPSS macro program Process 4.2 were used to test the mediating effect of depression between school exclusion and suicide ideation， as well as the moderating effect of psychological resilience on the three paths. ResultsCorrelation analysis showed that OES-A score was positively correlated with PHQ-9 score and suicidal ideation item score （T2）， and PHQ-9 score was also positively correlated with suicidal ideation item score （T2） （r=0.361， 0.292， 0.508， P<0.01）. RSCA score was negatively correlated with OES-A， PHQ-9， and suicidal ideation （T2） scores （r=-0.500， -0.676， -0.459， P<0.01）. Campus exclusion positively predicted suicidal ideation （T2） and depression （β=0.081， 0.281， P<0.01）， while depression positively predicted suicidal ideation （T2） （β=0.108， P<0.01）. The mediation analysis revealed an effect size of 0.030 （95% CI： 0.019~0.043， P<0.01）， accounting for 37.35% of the total effect. Psychological resilience moderated the relationships between campus exclusion and depression， campus exclusion and suicidal ideation （T2）， and depression and suicidal ideation （T2） （β=-0.059， -0.049， -0.062， P<0.01）. ConclusionA moderated mediation model exists among campus exclusion， depression， resilience， and adolescent's suicidal ideation. Psychological resilience moderates the associations between campus exclusion， depression and suicidal ideation across all three paths. ［Funded by Beijing Municipal Health Commission Clinical Research Excellence Program， （number， BRWEP2024W072130101）；Beijing Municipal Hospital Management Center Summit Program， （number， DFL20221701）］

BackgroundFamily functioning is one of the factors influencing non-suicidal self-injury （NSSI） behaviors in adolescents with depressive disorders. Previous studies have treated family functioning as a unitary construct， which may obscure the differential impacts of specific dimensions on NSSI behaviors. ObjectiveTo explore the relationships between various dimensions of family functioning and NSSI behaviors in adolescents with depressive disorders， aiming to provide precise targets for family-based interventions for adolescents with depressive disorders who exhibit NSSI behaviors. MethodsIn this cross-sectional study， 217 adolescent patients who were treated at the outpatient or inpatient department of The First Psychiatric Hospital of Harbin from January to July 2025 and met the diagnostic criteria for depressive disorders as stipulated in the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5） were included as the research subjects. Assessments included a self-designed questionnaire， the Hamilton Depression Scale-17 item （HAMD-17）， and the Family Assessment Device （FAD）. Univariate Logistic regression analysis was employed to investigate the association between each dimension of family functioning and the NSSI behaviors， and multivariate Logistic regression was used to test the independent effect of each dimension of family functioning on the NSSI behaviors. ResultsA total of 204 cases （94.01%） of adolescent patients with depressive disorders completed the valid questionnaire survey. Among them， 134 cases （65.69%） exhibited NSSI behaviors （NSSI group）， and 70 cases （34.31%） did not exhibit NSSI behaviors （non-NSSI group）. Compared with the non-NSSI group， the NSSI group had a higher HAMD-17 score ［（20.97±7.50） vs. （17.79±6.95）， t=8.705， P=0.004］， a higher FAD total score ［（155.68±21.84） vs. （148.87±22.72）， t=4.348， P=0.038］， and a higher problem-solving dimension score ［（2.54±0.49） vs. （2.34±0.51）， t=7.399， P=0.007］. All the differences were statistically significant. The results of the Logistic regression analysis showed that the FAD total score （OR=1.014， 95% CI： 1.001–1.028， P=0.041） and the problem-solving dimension score （OR=2.241， 95% CI： 1.228–4.090， P=0.009） were both risk factors for NSSI behaviors. After adjusting for gender， age， residence， educational level， monthly family income， and whether being an only child， the correlation between the FAD total score and NSSI behaviors was not statistically significant （OR=1.010， 95% CI： 0.995–1.025， P=0.185）， while the correlation between the FAD problem-solving dimension score and NSSI behaviors remained statistically significant （OR=2.000， 95% CI： 1.028–3.889， P=0.041）. ConclusionImpaired problem-solving capacity within family functioning may constitute a risk factor for NSSI behaviors in adolescents with depressive disorders. ［Funded by Research Project of Heilongjiang Provincial Health Commission （number， 20240303090148， 20230303090154）］

BackgroundAdolescents with depressive disorder often engage in non-suicidal self-injury （NSSI） behaviors， which severely impacts their physical and mental health. Impulsivity and emotional regulation are key factors influencing NSSI behaviors. However， research on the mechanisms through which impulsivity and emotional regulation affect NSSI behaviors in adolescent depressive disorder patients with NSSI remains insufficient， limiting the development of effective intervention strategies. ObjectiveTo explore the differences in impulsivity and emotion regulation abilities between adolescent patients with depressive disorder accompanied by and without NSSI behaviors， and to analyze the association between NSSI behaviors and impulsivity and emotion regulation abilities in adolescent patients with depressive disorder accompanied by NSSI behaviors. MethodsA total of 184 adolescents hospitalized in the child and adolescent psychiatry department of Wuxi Mental Health Center from October 2023 to August 2024， who met the diagnostic criteria for depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders， fifth edition （DSM-5）， were consecutively enrolled as study subjects. Based on the diagnostic criteria for NSSI in DSM-5， patients were divided into NSSI group （n=108） and non-NSSI group （n=76）. The Barratt Impulsiveness Scale-11 （BIS-11）， the Emotion Regulation Questionnaire （ERQ）， the Adolescent Self-Harm Questionnaire， and the Positive and Negative Suicide Ideation （PANSI） were used for assessment. Spearman correlation analysis was employed to explore the correlation between the scores of the Adolescent Self-Harm Questionnaire and the scores of BIS-11 and ERQ in the NSSI group. Multiple regression analysis was conducted to examine the effects of impulsivity and emotion regulation on NSSI behaviors in the NSSI group. ResultsCompared to the non-NSSI group， the NSSI group showed significantly higher scores in BIS-11 non-planned impulsivity （Z=-4.181， P<0.05）， action impulsivity （t=4.944， P<0.05）， cognitive impulsivity （Z=-3.392， P<0.05）， and total score （t=4.763， P<0.05）， and lower scores in the cognitive reappraisal of ERQ （t=-4.094， P<0.05） and total score （Z=-2.299， P<0.05）， and higher scores in the expression inhibition of ERQ （Z=-3.019， P<0.05）. The correlation analysis results showed that the score of the adolescent self-harm questionnaire in the NSSI group was positively correlated with the behavioral impulsivity factor score in the BIS-11 （r=0.434， P<0.05）. Multiple regression analysis indicated that action impulsivity factor was a significant correlate of self-injury behaviors in the NSSI group （B=0.855， P<0.05）， explaining 22.30% of the total variance. ConclusionAdolescent patients with depressive disorder accompanied by NSSI behaviors exhibit higher levels of impulsivity and poorer emotional regulation abilities. Action impulsivity may play a significant role in the mechanism of NSSI behaviors. ［Funded by Wuxi Municipal Health Commission Research Project （number， Q202320）］

BackgroundThe violent aggressive behaviors of patients with schizophrenia usually have the characteristics of suddenness， unpredictability， high severity， and great difficulty in prevention. Early identification and accurate assessment of their risk of violent aggression have significant clinical significance. ObjectiveTo construct a predictive model for the violence risk in hospitalized patients with schizophrenia， to identify the key factors influencing the occurrence of violent behavior in these patients， so as to provide references for clinical precise quantitative assessment and early intervention. MethodsA total of 200 patients with schizophrenia who were hospitalized at Taiyuan Psychiatric Hospital from March 2022 to September 2024 and met the diagnostic criteria of the International Classification of Diseases， eleventh edition （ICD-11） were collected to form the modeling cohort. They were randomly divided into a training set （n=140） and a test set （n=60） at a ratio of 7∶3. Based on the least absolute shrinkage and selection operator （LASSO） regression algorithm， the feature variables were screened and dimension-reduced. The support vector machine （SVM） from machine learning was selected for model training and prediction. The discrimination efficacy of the model was evaluated by the area under the receiver operating characteristic （ROC） curve （AUC）， accuracy， precision， sensitivity， specificity， F1 value， and Brier value. ResultsLASSO regression screening identified 16 feature variables. Pearson correlation analysis revealed a positive correlation between prior violent behavior frequency and clinical psychiatric symptom scores （r=0.580， P<0.01）， a positive correlation between hospitalization compliance and current disease status （r=0.550， P=0.003）， and a positive correlation between educational level and family per capita monthly income （r=0.367， P<0.01）. The SVM model achieved an AUC of 0.853， accuracy of 0.800， precision of 0.810， sensitivity of 0.895， specificity of 0.636， F1 value of 0.850， and Brier value of 0.168. ConclusionThe SVM model has a relatively high level of applicability and overall predictive performance in the assessment of violent risk in schizophrenia patients， which is helpful for the early identification of violent risks in such patients. ［Funded by Specialized Research Project for Enhancing the Competence of Health Professionals in Taiyuan City （number， Y2023006）］

BackgroundLow medication compliance among patients with severe mental disorders increases the disease burden on both the patients' families and the society. Medication adherence is influenced by numerous factors. Traditional methods such as Logistic regression struggle to quantify the importance of these factors. By introducing Extreme Gradient Boosting （XGBoost） combined with Shapley Additive Explanations （SHAP）， enables the quantification of the relative contribution weights of each factor， providing support for identifying the core influencing factors. ObjectiveTo explore the influencing factors of medication adherence among patients with severe mental disorders in Zhuhai， aiming to provide references for optimizing patient management strategies. MethodsExtract the data of patients with severe mental disorders who were registered on the mental health system platform in Zhuhai City from January 1， 2023 to March 31， 2025. A total of 9 329 patients were finally included for analysis. Influencing factors were screened using univariate analysis and multivariate logistic regression analysis， and an XGBoost model combined with the SHAP algorithm was constructed to quantify the importance of each influencing factor. ResultsAmong 9 329 patients， 8 446 demonstrated medication adherence， yielding an adherence rate of 90.53%. Multivariable analysis identified several risk factors significantly associated with medication non-adherence， being unmarried （OR=1.237， 95% CI： 1.019–1.502） or divorced （OR=1.389， 95% CI： 1.038–1.832）， a diagnosis of mental retardation with psychiatric disorders （OR=3.025， 95% CI： 2.402–3.796） or paranoid psychosis （OR=5.117， 95% CI： 3.086–8.299）， a disease duration of 2–4 years （OR=1.355， 95% CI： 1.085–1.696）， 4–6 years （OR=2.143， 95% CI： 1.671–2.747）， or >6 years （OR=1.681， 95% CI： 1.365–2.079）， lack of guardian subsidies （OR=1.412， 95% CI： 1.099–1.801）， absence of a disability certificate （OR=1.900， 95% CI： 1.588–2.282）， not being enrolled in care and support groups （OR=1.384， 95% CI： 1.183–1.617） or community services （OR=1.313， 95% CI： 1.042–1.645）， and not cohabiting with a guardian （OR=1.257， 95% CI： 1.048–1.501）. Conversely， the enrollment in special outpatient disease programs （OR=0.716， 95% CI： 0.609–0.842） and a family history of mental illness （OR=0.713， 95% CI： 0.503–0.982） were identified as protective factors. The XGBoost model exhibited robust predictive performance， with a sensitivity of 0.433， specificity of 0.944， accuracy of 0.891， Area Under the Curve （AUC） of 0.837， and F1 value of 0.449. Feature importance ranking indicated that the top three factors were disease duration， diagnosis， and the acquisition of disability certificates. ConclusionPolicy-based support （acquisition of disability certificates， special outpatient disease enrollment） and clinical disease characteristics （disease duration， diagnosis type） are key factors affecting medication adherence among patients with severe mental disorders in Zhuhai City. ［Funded by Zhuhai Medical Research Project （number， 2220009000281）］

BackgroundPatients with chronic schizophrenia often suffer from cognitive impairment. Traditional cognitive rehabilitation training has problems such as a single form and poor compliance， making it urgent to develop new cognitive intervention methods. ObjectiveTo explore the intervention effect of smartphone games on the cognitive function of patients with chronic schizophrenia， and to analyze the differences in cognitive function improvement between patients of different genders， in order to provide references for the cognitive function intervention of these patients. MethodsThis study was a prospective cohort study. A total of 30 patients who were hospitalized in the Psychiatry Department of Chaohu Hospital Affiliated to Anhui Medical University from March to October 2021， met the diagnostic criteria for schizophrenia as defined in the International Classification of Diseases， tenth edition （ICD-10）， and had a disease duration of above 5 years， were selected as the research subjects. All patients received smartphone game intervention for 12 weeks， 5 times a week， each session lasting 1 hour， in addition to conventional antipsychotic drug treatment. At the baseline and at 3， 6， 9， and 12 weeks of the intervention， the cognitive function was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status （RBANS）， the Positive and Negative Syndrome Scale （PANSS） was used to assess mental symptoms， and the Problematic Mobile Gaming Questionnaire （PMGQ） was used to assess addiction symptoms. ResultsA total of 26 patients （86.67%） completed the study， including 13 females and 13 males. The time effects， group effects， and interaction effect between time and group for the immediate memory factor score of RBANS in the female group and the male group were all statistically significant （F=36.682， 5.712， 3.090， P<0.05 or 0.01）， and the time effects and group effects for the verbal and delayed memory factors as well as the total score in both groups were also statistically significant （F=3.841， 6.149， 15.372， P<0.05 or 0.01）. The time effects and group effects of the total score of PANSS in both groups had no statistical significance （F=2.041， 0.623， P>0.05 for both）， and the interaction effect between time and group was statistically significant （F=5.728， P<0.01）. The time effects， group effects， and interaction effect of the total score of PMGQ in both groups were all without statistical significance （F=2.672， 0.166， 0.642， P>0.05 for both）. ConclusionSmartphone game intervention may help improve the cognitive function of patients with chronic schizophrenia （especially immediate memory， verbal function， and delayed memory）， and the benefits are greater for female patients. The smartphone game intervention did not induce game addiction， but no significant improvement in psychotic symptoms was observed. ［Funded by Excellent Young Talents Support Program of Anhui Provincial Department of Education （number， gxyqZD2022022）； www.chictr.org.cn number， ChiCTR2100044113］

BackgroundPatients with depressive episode and schizophrenia have a high risk of suicide. The sleep electroencephalogram power spectral density characteristics of patients with depressive episode accompanied by suicidal behavior and those with schizophrenia may be different， but there is currently a lack of direct comparative studies on these two groups of patients. ObjectiveTo compare the sleep electroencephalogram power spectral density between depressive episode and schizophrenic patients with suicidal behavior， in order to provide references for exploring predictive indicators of suicidal behavior. MethodsFrom June 2018 to December 2020， 20 patients with depressive episode and 20 patients with schizophrenia who had committed suicide within the past month and were treated at the outpatient department of Shenzhen Kangning Hospital were selected. All of them met the diagnostic criteria for depressive episode or schizophrenia as defined in the International Classification of Diseases， tenth edition （ICD-10）. Using a random sampling method， 20 volunteers with matching gender and age to the patient groups were selected from the Cuiping community in Shenzhen as the control group. The subjective sleep of the patients was evaluated using the Insomnia Severity Index （ISI）， the Dysfunctional Belief and Attitude about Sleep （DBAS）， the Disturbing Dreams and Nightmare Severity Index （DDNSI）， and the Epworth Somnolence Scale （ESS）. The objective sleep of the patients was assessed using polysomnography. The sleep electroencephalogram was filtered and the power spectral density of the brain wave was analyzed and processed for all the subjects. The subjective and objective sleep conditions of the two patient groups were compared， and the sleep electroencephalogram power spectral density of the patient groups and the control group were also compared. ResultsA comparison of subjective and objective sleep conditions between patients with depressive episode accompanied by suicidal behavior and patients with schizophrenia accompanied by suicidal behavior showed no statistically significant differences （P>0.05）. Comparisons of sleep electroencephalogram power spectral density in the W stage （average power of α wave， total power of δ wave， average power of δ wave， average power of θ wave）， N1 stage （average power of β wave， total power of α wave， total power of δ wave）， N2 stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave）， N3 stage （average power of α wave， average power of δ wave）， and R stage （total power of α wave， average power of α wave， total power of δ wave， average power of δ wave） between patients with depressive episode accompanied by suicidal behavior， patients with schizophrenia accompanied by suicidal behavior， and the control group showed statistically significant differences （P<0.05 or 0.01）. The total power of δ wave in the W stage and the average power of β wave and δ wave in the N1 stage were higher in two patient groups were higher than those of the control group. The total power of α wave and the average power of α wave in the N2 stage were lower than those of the control group， while the average power of δ wave was higher than that of the control group. The average power of α wave in the N3 stage of both patient groups were lower than that of the control group， while the average power of δ wave was higher than that of the control group. The total power and average power of α wave in the R stage were lower than those of the control group， while the total power and average power of δ wave were higher than those of the control group. All the differences were statistically significant. Patients with depressive episode accompanied by suicidal behavior had higher average powers of α wave， δ wave， and θ wave in the W stage compared with the control group， while the total power of α wave in the N1 stage was lower in the former group. All these differences were statistically significant （P<0.05）. ConclusionThe depressive episode patients accompanied by suicidal behavior have highly overlapping sleep electroencephalogram abnormal patterns with those of schizophrenia patients， mainly manifested as a general decrease in α wave power （N2， N3， R stage） and a general increase in δ wave power （W， N1， N2， N3， R stage） as well as β wave power in N1 stage. At the same time， patients with depressive episode accompanied by suicidal behavior also show specific changes， including an increase in the average power of α and θ waves during the wakefulness period （W stage）， and a decrease in the total power of α wave in N1 stage. ［Funded by Guangdong Province High-level Clinical Key Specialty （with supporting funds from Shenzhen City） （number， SZGSP013）； Shenzhen Key Medical Discipline （number， SZXK041）； Shenzhen Clinical Medicine Research Center Project （number， 20210617155253001）］

BackgroundChronic insomnia disorder has become a significant public health issue， and it may be associated with dyslipidemia. Previous studies on dyslipidemia in patients with chronic insomnia disorder have mainly focused on exploring the relationship between subjective short sleep duration and dyslipidemia， while there have been limited studies on the relationship between objective short sleep duration and dyslipidemia. ObjectiveTo explore the relationship between objective short sleep duration and dyslipidemia in patients with chronic insomnia disorder， in order to provide references for the prevention and intervention of dyslipidemia in this population. MethodsA total of 103 patients who were hospitalized at The Third Hospital of Mianyang from August 2022 to November 2023 and met the diagnostic criteria for chronic insomnia disorder as defined in the International Classification of Sleep Disorder， third edition （ICSD-3） were retrospectively collected. The objective sleep duration of the patients was obtained through polysomnography. The patients were divided into two groups based on their objective sleep duration： the group with objective sleep duration ≥ 7 hours （n=71） and the group with objective sleep duration < 7 hours （n=32）. Binary Logistic regression analysis was used to explore the impact of objective sleep duration < 7 hours on dyslipidemia. ResultsAmong 103 patients with chronic insomnia disorder， 59 cases （57.28%） were identified with dyslipidemia. The comparison of dyslipidemia conditions between the group with objective sleep duration ≥ 7 hours and the group with objective sleep duration < 7 hours showed a statistically significant difference （χ²=5.956， P<0.05）. Compared with the group with objective sleep duration ≥7 hours， the group with objective sleep duration < 7 hours exhibited significantly lower high-density lipoprotein cholesterol levels， and reduced sleep efficiency （t=-2.003， -5.482， P<0.05 or 0.01）. Binary Logistic regression analysis results showed that the risk of abnormal blood lipids in patients with chronic insomnia disorder with objective sleep duration < 7 hours was 3.128 times higher than that of patients with objective sleep duration ≥ 7 hours （OR=3.128， 95% CI： 1.139–8.588）. ConclusionObjective short sleep duration may be a risk factor for dyslipidemia in patients with chronic insomnia disorder.

BackgroundAnxiety disorder is a common mental disorder， with its prevalence showing a continuous upward trend， significantly affecting the quality of life and social function of patients. Due to the lack of objective and reliable biomarkers in clinical practice， the early identification and treatment of anxiety disorder have been somewhat limited. Plasma proteins have the potential to serve as biomarkers for mental diseases， however， the causal relationship between them and anxiety disorder remains unclear. ObjectiveTo identify the plasma proteins that have a causal relationship with anxiety disorders， and to elucidate the associated biological pathways， in order to provide references for the search for biomarkers of anxiety disorders and the exploration of potential therapeutic targets. MethodsBased on the protein quantitative trait locus （pQTL） data of 4 907 plasma proteins covering 35 559 Icelandic individuals from the deCODE database， and the genome-wide association studies （GWAS） data of 50 486 patients with anxiety disorders and 330 460 healthy controls， the inverse-variance weighted （IVW） method was used as the main analysis method， supplemented by MR-Egger method， weighted median method， simple model method， and weighted model method for bidirectional Mendelian randomization analysis. Enrichment analysis of gene ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathways was conducted for the related proteins. Sensitivity analysis was performed using Cochran's Q test， MR-Egger intercept test， MR-PRESSO test， and leave-one-out analysis to evaluate the robustness of the results. ResultsA total of 10 plasma proteins were identified as significantly associated with anxiety disorders. Among these， SPATA9 （OR=0.856， 95% CI： 0.784–0.934， P<0.01） and PDE5A （OR=0.911， 95% CI： 0.864–0.961， P<0.01） were identified as protective factors， while CRYGD （OR=1.209， 95% CI： 1.095–1.334， P<0.01）， BTN3A3 （OR=1.045， 95% CI： 1.018–1.073， P<0.01）， SERPINB13 （OR=1.102， 95% CI： 1.040–1.168， P<0.01）， ERBB4 （OR=1.283， 95% CI： 1.109–1.484， P<0.01）， LSAMP （OR=1.096， 95% CI： 1.037–1.158， P<0.01）， ICOSLG （OR=1.283， 95% CI： 1.104–1.490， P<0.01）， DNAJB11 （OR=1.172， 95% CI： 1.076–1.277， P<0.01）， and TREML1 （OR=1.115， 95% CI： 1.054–1.179， P<0.01） were identified as risk factors. The sensitivity analysis showed that the results were robust， with no heterogeneity （Cochran's Q test P>0.05） or pleiotropy （MR-Egger intercept test P>0.05）. Enrichment analysis indicated that these plasma proteins were enriched in biological processes such as T-cell signal transduction， lymphocyte proliferation， cell membrane structure and synaptic function， as well as the intestinal immune network that produces IgA and the ErbB signaling pathway. ConclusionThis study identified 10 plasma proteins associated with anxiety disorders. The functions of these plasma proteins involve multiple biological processes such as neural development and immune regulation.