Machine learning judged neutral facial expressions as key factors for a "good therapist" within the first five minutes: An experiment to simulate online video counselling.

Objective: Machine learning models were employed to discern patients' impressions from the therapists' facial expressions during a virtual online video counselling session. Methods: Eight therapists simulated an online video counselling session for the same patient. The facial emotions of the therapists were extracted from the session videos; we then utilized a random forest model to determine the therapist's impression as perceived by the patients. Results: The therapists' neutral facial expressions were important controlling factors for patients' impressions. A predictive model with three neutral facial features achieved an accuracy of 83% in identifying patients' impressions. Conclusions: Neutral facial expressions may contribute to patient impressions in an online video counselling environment with spatiotemporal disconnection. Innovation: Expression recognition techniques were applied innovatively to an online counselling setting where therapists' expressions are limited. Our findings have the potential to enhance psychiatric clinical practice using Information and Communication Technology.

Quantification of the Plasma Concentration of Vadadustat by High-Performance Liquid Chromatography with Ultraviolet Detection and Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry.

BACKGROUND: An inexpensive, simple, and accurate plasma concentration measurement system is needed to actively conduct pharmacokinetic and pharmacodynamic analyses of vadadustat, hypoxia-inducible factor-prolyl hydroxylase inhibitor, in clinical settings. In this study, the authors aimed to develop a method for measuring vadadustat in human plasma that could be applied for therapeutic drug monitoring using high-performance liquid chromatography with ultraviolet detection (HPLC-UV) in a clinical setting. METHODS: Plasma samples (100 µL) were pretreated with acetonitrile using butyl paraoxybenzoate as an internal standard. Chromatographic separation was performed on a SunShell PFP C18 column (2.6 µm, 4.6 mm × 150 mm). The mobile phase consisted of (A) 20 mM of phosphate buffer (pH 2.4) and (B) acetonitrile (60:40, v/v), delivered isocratically at a flow rate of 1 mL/min. The analytes were detected by UV absorbance at a wavelength of 220 nm, and the column temperature was 40°C. To evaluate the applicability of HPLC-UV in a clinical setting, blood samples were collected at 19 time points from 7 patients who had been taking vadadustat. RESULTS: The calibration curve was linear over the concentration range of 0.2-150 mcg/mL (R2 > 0.99). Intra-assay and interassay accuracy, precision, and stability met the Food and Drug Administration recommendations. The vadadustat plasma concentrations of patients analyzed using the current HPLC-UV method were almost equal to those measured using ultra-performance liquid chromatography-tandem mass spectrometry (mean difference: 0.13 mcg/mL). Large variability in the dose-adjusted plasma concentrations of vadadustat at 12 hours after administration was observed between patients (coefficient of variation = 57.6%). CONCLUSIONS: This HPLC-UV method is a simple, accurate quantification method for evaluating plasma concentrations in patients taking vadadustat in a clinical setting.

Pleuroparenchymal Fibroelastosis as a Late-Onset Pulmonary Toxicity after Treatment with Anticancer Chemotherapy for High-Risk Neuroblastoma.

Pleuroparenchymal fibroelastosis (PPFE) is a rare, progressive, restrictive lung disease characterized by hypercarbic respiratory failure. In pediatrics, it has been described in patients with a history of malignancy who have received a bone marrow transplant, chemotherapy, or radiotherapy. It is characterized by pleural thickening, fibrosis, subpleural elastosis, and intraalveolar collagen deposits. Survival is poor, and the only therapy is lung transplantation. Here, we report a patient who developed PPFE as a late-onset pulmonary toxicity after treatment with anticancer chemotherapy for high-risk neuroblastoma (NB).

Clinical effects of online cognitive behavioral group therapy for chronic pain patients and developing a therapeutic alliance: A pre-post pilot trial.

Background and Aims: Research suggests that various psychosocial factors influence chronic pain, with psychotherapies like cognitive behavioral therapy  proving effective. However, the limited availability and accessibility have prolonged suffering among patients with chronic pain. This challenge has led to a growing demand for accessible online interventions. We developed an online cognitive behavioral group therapy (CBGT) program, building upon our existing face-to-face CBGT program. We compared the scores obtained by patients during the treatment-as-usual (TAU) period with those collected at the beginning and at the end of the intervention. Methods: Patients with chronic pain (N = 22) agreed to participate in the online CBGT program, which was conducted once a week for 12 sessions. The sample size was decided based on the effect sizes of our past face-to-face CBGT. We assessed pain intensity [Visual Analogue Scale (VAS)], pain catastrophizing [pain catastrophizing scale (PCS)] and psychiatric assessment [Beck Depression Inventory-Second Edition (BDI)-II], State-Trait-Anxiety Inventory (STAI), and Short Form Health Survey (SF-36) at three points: entry, pretreatment, and posttreatment. We also evaluated the participants' therapeutic alliance with the treatment staff [short-form version of the Working Alliance Inventory (WAI-S)]. We utilized analyses of variance, Friedman test, paired t-tests, Wilcoxon signed-rank test, and Pearson correlation analysis for data evaluation. Results: Results indicated a significant posttreatment improvement in VAS, PCS, and BDI-II scores compared to the TAU period. Furthermore, posttreatment WAI-S scores increased significantly compared to pretreatment scores. Also, positive correlations were observed among pre- and posttreatment changes in WAI-S, pain intensity, and pain catastrophizing scores. Conclusion: There is a possibility that a therapeutic alliance can be established, and therapeutic effects achieved through an online CBGT intervention; however, additional research is required to substantiate this potential. We have registered this clinical trial in UMIN-CTR on 04/21/2021 with the number UMIN000043982.

Validation of a Behavioral Activation Model Including Self-Compassion: A Longitudinal Study at Three Time Points.

INTRODUCTION: Depression is highly prevalent among university students. While behavioral activation has been shown to be an effective psychotherapy for depression, there is a lack of research regarding the behavioral activation mechanism. Furthermore, although self-compassion seems to be a factor in promoting behavioral activation, no studies have attempted to validate a behavioral activation model that includes positive self-compassion. In addition, mechanistic studies have lacked consideration in longitudinal studies of behavioral activation. Thus, in this longitudinal study, we constructed and validated an exploratory model of behavioral activation. METHODS: A total of 300 undergraduate students completed online surveys in 2019, 2020, and 2021. We examined the longitudinal effects of five factors (value-based behavior, goal-oriented and scheduled activities, positive reinforcement, self-compassion, and depressive symptoms) using structural equation modeling based on maximum likelihood estimation using bootstrapping. RESULTS: The exploratory model was found to be valid and to have a good fit with the data. The results indicate that value-based behaviors increase the frequency of goal-oriented and scheduled activities, which in turn increases the frequency of positive reinforcement in everyday life. Additionally, when self-compassion, value-based behavior, goal-oriented and scheduled activities, and positive reinforcement are considered together, self-compassion may be indirectly related to activation via value-based behavior. CONCLUSION: From the perspective of preventing depressive symptoms, it is important to increase the frequency of value-based activities. Furthermore, adding self-compassion is effective in behavioral activation to increase value-based activities. However, to address the limitations of this study, future studies should investigate the relationship among behavioral characteristics during interventions.

Thought habits and processing modes among Japanese university students do not influence dynamic associations between rumination and negative affect.

The integrated model of rumination argues that two trait factors-negative thinking habits and processing modes-get people stuck in maladaptive rumination. There is little evidence showing whether these factors influence the daily dynamic associations between rumination and negative moods. To address this, in this study, we conducted an experience-sampling method on Japanese university students. We recruited 92 Japanese university students and assessed their daily rumination and negative affect (NA) eight times a day for seven days. We examined the effects of habits and processing modes on the dynamic associations between rumination and negative moods using dynamic structural equation modeling. We found that individuals were more likely to ruminate when they experienced NA. However, contrary to previous findings, this study's participants did not experience NA after engaging in rumination. Moreover, we did not detect any significant trait factor effect on these dynamic associations. Our findings imply that individuals are more likely to engage in rumination after experiencing NA, but the reverse association, particularly the autoregression of rumination, may not be maintained in natural daily life. Furthermore, negative thinking habits and processing modes may not influence the daily dynamic associations between rumination and NA among Japanese university students.

Relationship between Value-Based Behaviors and Scheduled Activities of University Students before and during the COVID-19 Pandemic: A Longitudinal Cross-Lagged Model.

University students are in a phase during which they have various experiences typical in the academic environment and face situations that require adaptability and influence value formation. In the abnormal situation of the COVID-19 pandemic, university students' life rhythms, academic, interpersonal, and financial situations have changed drastically. In those situational cues, the value-based behavior of university students may have changed. Values provide purpose and direction for each action. Furthermore, values are situational goals that lead to specific real-time behavior. Therefore, this study aimed to examine whether there is a two-way influencing relationship between value-based behavior and scheduled activities of university students at two points in time (before the COVID-19 pandemic and during the COVID-19 pandemic). 417 university students answered a questionnaire at Times 1 and 2 (with a 1-year interval). We examined the relationship between value-based behavior and scheduled activities using a longitudinal cross-lagged model analysis. The findings of this study indicate that promoting value-based behaviors is positively associated with the frequency of value-based behaviors and scheduled activities even during anomalies such as the COVID-19 pandemic. Even in anomalous situations such as the COVID-19 pandemic, increasing value-based behaviors such as behavioral activation can improve the lives of university students. Future intervention studies should show whether behavioral activation is effective in decreasing depressive symptoms among university students even in abnormal situations such as the COVID-19 pandemic.

Association between sodium-glucose cotransporter 2 inhibitors and pancreatic cancer in the Japanese working-age population.

OBJECTIVE: Pancreatic cancer-related mortality is increasing worldwide, and prevention methods and effective novel therapies are required. In pancreatic cancer, sodium-glucose cotransporters (SGLT) are involved in glucose uptake. This study aimed to clarify the association between SGLT2 inhibitors and pancreatic cancer development. MATERIALS AND METHODS: A nested case-control study was conducted using the JMDC administrative claims database (January 2005 to June 2020). Patients newly diagnosed with type 2 diabetes mellitus (T2DM) were included, and cases were defined as patients who developed pancreatic cancer. Patients with outcomes were randomly matched to a maximum of 20 controls according to age (± 5 years), sex, and calendar date (month and year) of the first T2DM diagnosis through risk set sampling. RESULTS: Of the 181,107 T2DM patients, 363 cases and 7,043 controls were selected with 14 and 457 patients prescribed SGLT2 inhibitors, respectively. Cumulative administration of SGLT2 inhibitors for > 180 days was significantly inversely associated with the development of pancreatic cancer (adjusted odds ratio: 0.58, 95% confidence interval: 0.31 - 0.99). CONCLUSION: SGLT2 inhibitors may reduce the risk of developing pancreatic cancer in T2DM patients. The number of patients over 65 years of age was small in this study due to the nature of the data source. Further studies with larger sample sizes including older patients are needed.

Subcortical volumetric alterations in four major psychiatric disorders: a mega-analysis study of 5604 subjects and a volumetric data-driven approach for classification.

Differential diagnosis is sometimes difficult in practical psychiatric settings, in terms of using the current diagnostic system based on presenting symptoms and signs. The creation of a novel diagnostic system using objective biomarkers is expected to take place. Neuroimaging studies and others reported that subcortical brain structures are the hubs for various psycho-behavioral functions, while there are so far no neuroimaging data-driven clinical criteria overcoming limitations of the current diagnostic system, which would reflect cognitive/social functioning. Prior to the main analysis, we conducted a large-scale multisite study of subcortical volumetric and lateralization alterations in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder using T1-weighted images of 5604 subjects (3078 controls and 2526 patients). We demonstrated larger lateral ventricles volume in schizophrenia, bipolar disorder, and major depressive disorder, smaller hippocampus volume in schizophrenia and bipolar disorder, and schizophrenia-specific smaller amygdala, thalamus, and accumbens volumes and larger caudate, putamen, and pallidum volumes. In addition, we observed a leftward alteration of lateralization for pallidum volume specifically in schizophrenia. Moreover, as our main objective, we clustered the 5,604 subjects based on subcortical volumes, and explored whether data-driven clustering results can explain cognitive/social functioning in the subcohorts. We showed a four-biotype classification, namely extremely (Brain Biotype [BB] 1) and moderately smaller limbic regions (BB2), larger basal ganglia (BB3), and normal volumes (BB4), being associated with cognitive/social functioning. Specifically, BB1 and BB2-3 were associated with severe and mild cognitive/social impairment, respectively, while BB4 was characterized by normal cognitive/social functioning. Our results may lead to the future creation of novel biological data-driven psychiatric diagnostic criteria, which may be expected to be useful for prediction or therapeutic selection.

Cerebral cortical structural alteration patterns across four major psychiatric disorders in 5549 individuals.

According to the operational diagnostic criteria, psychiatric disorders such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and autism spectrum disorder (ASD) are classified based on symptoms. While its cluster of symptoms defines each of these psychiatric disorders, there is also an overlap in symptoms between the disorders. We hypothesized that there are also similarities and differences in cortical structural neuroimaging features among these psychiatric disorders. T1-weighted magnetic resonance imaging scans were performed for 5,549 subjects recruited from 14 sites. Effect sizes were determined using a linear regression model within each protocol, and these effect sizes were meta-analyzed. The similarity of the differences in cortical thickness and surface area of each disorder group was calculated using cosine similarity, which was calculated from the effect sizes of each cortical regions. The thinnest cortex was found in SZ, followed by BD and MDD. The cosine similarity values between disorders were 0.943 for SZ and BD, 0.959 for SZ and MDD, and 0.943 for BD and MDD, which indicated that a common pattern of cortical thickness alterations was found among SZ, BD, and MDD. Additionally, a generally smaller cortical surface area was found in SZ and MDD than in BD, and the effect was larger in SZ. The cosine similarity values between disorders were 0.945 for SZ and MDD, 0.867 for SZ and ASD, and 0.811 for MDD and ASD, which indicated a common pattern of cortical surface area alterations among SZ, MDD, and ASD. Patterns of alterations in cortical thickness and surface area were revealed in the four major psychiatric disorders. To our knowledge, this is the first report of a cross-disorder analysis conducted on four major psychiatric disorders. Cross-disorder brain imaging research can help to advance our understanding of the pathogenesis of psychiatric disorders and common symptoms.

Association between statin use and open-angle glaucoma: a nested case-control study using the Japanese claims database.

The association between statins and open-angle glaucoma (OAG) remains controversial. This study investigated the relationship between statins and OAG in Japanese patients with dyslipidemia using the Japanese administrative claims database. A nested case-control study using two models was conducted using the JMDC claims database (01/2005-01/2020). The onset of OAG: index date was defined as the diagnosis of glaucoma, prescription of anti-glaucoma drugs, or surgery of glaucoma. For each case, a maximum of 10 age-, sex-, and calendar year/month-matched controls were randomly selected by risk-set sampling with replacement. The number of statin prescriptions during the exposure assessment period, which was identified as the 12-month (model 1) or 24-month (model 2) periods prior to the index date, was used as an indicator for statin exposure. Adjusted odds ratios (aORs) and 95% confidence interval (CI) were estimated using conditional logistic regression analyses. We identified 375,373 patients with newly diagnosed dyslipidemia. Of these, 6180 cases and 61,792 controls (model 1) and 4153 cases and 41,522 controls (model 2) were selected. Statin use was not identified as a significant risk factor for OAG (model 1: aOR 0.98, 95% CI 0.93-1.03, model 2: aOR 0.97, 95% CI 0.91-1.04). Compared with nonexposure, short-term exposure (< 2 years) to statins was not related to an increased risk of OAG in the Japanese working-age population with dyslipidemia.

[Utilization of Big Data with a Focus on Administrative Claims Database].

With the development of information technology, patient information is stored as electronic data, and huge amounts of such data are collected every day. Such a collection compiled over the course of clinical practice is called real-world data and is expected to be used for evaluating drug efficacy and safety. Real-world data such as health insurance association-based administrative claims databases, pharmacy-based dispensing databases, and spontaneous reporting system databases are mainly used in pharmaceutical research. Among them, claims databases are used for various observational studies such as studies on nationwide prescription trends, pharmacovigilance studies, and studies on rare diseases due to their large sample size. Although the nature of omics data is different from that of real-world data, it has become accessible on cloud platforms and are being used to broaden the scope of research in recent years. In this paper, we introduce a method for generating and further testing hypotheses through integrated analysis of real-world data and omics data, with a focus on administrative claims databases.

An intervention to promote concrete thinking style in young adults: Effects on depressive symptoms and its protective factors.

BACKGROUND AND OBJECTIVES: Individuals with low concreteness-experiential thought (CET) tend to have exacerbated depressive symptoms. Interventions aimed at increasing CET have been shown to influence depressive symptoms. The present study examined the effects of increasing CET on depressive symptoms and its protective factors. METHODS: A two-armed experimental intervention was conducted with 86 healthy university students in Japan. They were randomly allocated to the intervention and waitlist groups. Participants in the intervention group engaged in an unguided and web-based (UW) intervention to increase CET (UW-CET). This intervention included a one-off session, to explain the rationale behind increasing CET via a psychoeducation video, and a five-session training on CET over a week. We assessed depressive symptoms, thought styles, and protective factors, such as mindfulness and goal striving, both pre- and-post-assessment and at the one-month follow-up. RESULTS: Participants in the intervention group had marginally increased CET in the follow-up assessments; however, participants in the waitlist group did not. Furthermore, participants in the intervention showed marginally increased mindfulness tendencies and strivings toward their personal goals, but their depressive symptoms were not affected. LIMITATIONS: The present study did not include any active control conditions. Additionally, the sample consisted of only healthy university students. CONCLUSIONS: The findings suggest that the UW-CET can marginally increase adaptive thinking, such as CET, and promote positive psychological aspects in healthy young adults; however, the effect is small. The findings may also help expand clinical implementations to prevent depression in young adults.

Resting-state functional connectivity disruption between the left and right pallidum as a biomarker for subthreshold depression.

Although the identification of late adolescents with subthreshold depression (StD) may provide a basis for developing effective interventions that could lead to a reduction in the prevalence of StD and prevent the development of major depressive disorder, knowledge about the neural basis of StD remains limited. The purpose of this study was to develop a generalizable classifier for StD and to shed light on the underlying neural mechanisms of StD in late adolescents. Resting-state functional magnetic resonance imaging data of 91 individuals (30 StD subjects, 61 healthy controls) were included to build an StD classifier, and eight functional connections were selected by using the combination of two machine learning algorithms. We applied this biomarker to an independent cohort (n = 43) and confirmed that it showed generalization performance (area under the curve = 0.84/0.75 for the training/test datasets). Moreover, the most important functional connection was between the left and right pallidum, which may be related to clinically important dysfunctions in subjects with StD such as anhedonia and hyposensitivity to rewards. Investigation of whether modulation of the identified functional connections can be an effective treatment for StD may be an important topic of future research.

Distinctive alterations in the mesocorticolimbic circuits in various psychiatric disorders.

AIM: Increasing evidence suggests that psychiatric disorders are linked to alterations in the mesocorticolimbic dopamine-related circuits. However, the common and disease-specific alterations remain to be examined in schizophrenia (SCZ), major depressive disorder (MDD), and autism spectrum disorder (ASD). Thus, this study aimed to examine common and disease-specific features related to mesocorticolimbic circuits. METHODS: This study included 555 participants from four institutes with five scanners: 140 individuals with SCZ (45.0% female), 127 individuals with MDD (44.9%), 119 individuals with ASD (15.1%), and 169 healthy controls (HC) (34.9%). All participants underwent resting-state functional magnetic resonance imaging. A parametric empirical Bayes approach was adopted to compare estimated effective connectivity among groups. Intrinsic effective connectivity focusing on the mesocorticolimbic dopamine-related circuits including the ventral tegmental area (VTA), shell and core parts of the nucleus accumbens (NAc), and medial prefrontal cortex (mPFC) were examined using a dynamic causal modeling analysis across these psychiatric disorders. RESULTS: The excitatory shell-to-core connectivity was greater in all patients than in the HC group. The inhibitory shell-to-VTA and shell-to-mPFC connectivities were greater in the ASD group than in the HC, MDD, and SCZ groups. Furthermore, the VTA-to-core and VTA-to-shell connectivities were excitatory in the ASD group, while those connections were inhibitory in the HC, MDD, and SCZ groups. CONCLUSION: Impaired signaling in the mesocorticolimbic dopamine-related circuits could be an underlying neuropathogenesis of various psychiatric disorders. These findings will improve the understanding of unique neural alternations of each disorder and will facilitate identification of effective therapeutic targets.

Aberrant Large-Scale Network Interactions Across Psychiatric Disorders Revealed by Large-Sample Multi-Site Resting-State Functional Magnetic Resonance Imaging Datasets.

BACKGROUND AND HYPOTHESIS: Dynamics of the distributed sets of functionally synchronized brain regions, known as large-scale networks, are essential for the emotional state and cognitive processes. However, few studies were performed to elucidate the aberrant dynamics across the large-scale networks across multiple psychiatric disorders. In this paper, we aimed to investigate dynamic aspects of the aberrancy of the causal connections among the large-scale networks of the multiple psychiatric disorders. STUDY DESIGN: We applied dynamic causal modeling (DCM) to the large-sample multi-site dataset with 739 participants from 4 imaging sites including 4 different groups, healthy controls, schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BD), to compare the causal relationships among the large-scale networks, including visual network, somatomotor network (SMN), dorsal attention network (DAN), salience network (SAN), limbic network (LIN), frontoparietal network, and default mode network. STUDY RESULTS: DCM showed that the decreased self-inhibitory connection of LIN was the common aberrant connection pattern across psychiatry disorders. Furthermore, increased causal connections from LIN to multiple networks, aberrant self-inhibitory connections of DAN and SMN, and increased self-inhibitory connection of SAN were disorder-specific patterns for SCZ, MDD, and BD, respectively. CONCLUSIONS: DCM revealed that LIN was the core abnormal network common to psychiatric disorders. Furthermore, DCM showed disorder-specific abnormal patterns of causal connections across the 7 networks. Our findings suggested that aberrant dynamics among the large-scale networks could be a key biomarker for these transdiagnostic psychiatric disorders.

Association between hemorrhage and direct oral anticoagulants in combination with verapamil: Analysis of Japanese Adverse Drug Event Report database and electronic medical record data.

OBJECTIVE: The aim of this study was to investigate the risk of hemorrhage in concomitant therapy with direct oral anticoagulants (DOACs) and class IV antiarrhythmic drugs. MATERIALS AND METHODS: First, disproportionality analysis (DPA) was performed using the Japanese Adverse Drug Event Report (JADER) database to investigate the risk of hemorrhage with DOACs. Second, a cohort study was performed using electronic medical record data to confirm the results of the JADER analysis. RESULTS: In the JADER analysis, hemorrhage was significantly associated with treatment with edoxaban and verapamil (reporting odds ratio = 1.66; 95% confidence interval (CI) = 1.04 - 2.67). The cohort study revealed that hemorrhage incidence significantly differed between the verapamil-treated group and the bepridil-treated group, with a higher risk for hemorrhage in the verapamil group (log-rank test: p < 0.001). The multivariate Cox proportional hazards model also showed that the verapamil and DOAC combination was significantly associated with hemorrhage events compared with the bepridil and DOAC combination (hazard ratio (HR): 2.87, 95% CI: 1.17 - 7.07, p = 0.022). Furthermore, creatinine clearance (Ccr) ≥ 50 mL/min was significantly associated with hemorrhage events (HR: 2.72, 95% CI: 1.03 - 7.18, p = 0.043), and verapamil was significantly associated with hemorrhage in patients with Ccr ≥ 50 mL/min (HR: 3.58, 95% CI: 1.36 - 9.39, p = 0.010) but not in patients with Ccr < 50 mL/min. CONCLUSION: Verapamil increases the risk of hemorrhage in patients on DOACs. Dose adjustment of DOACs based on renal function may prevent hemorrhage when verapamil is concomitantly administered.

Verification of the brain network marker of major depressive disorder: Test-retest reliability and anterograde generalization performance for newly acquired data.

BACKGROUND: Recently, we developed a generalizable brain network marker for the diagnosis of major depressive disorder (MDD) across multiple imaging sites using resting-state functional magnetic resonance imaging. Here, we applied this brain network marker to newly acquired data to verify its test-retest reliability and anterograde generalization performance for new patients. METHODS: We tested the sensitivity and specificity of our brain network marker of MDD using data acquired from 43 new patients with MDD as well as new data from 33 healthy controls (HCs) who participated in our previous study. To examine the test-retest reliability of our brain network marker, we evaluated the intraclass correlation coefficients (ICCs) between the brain network marker-based classifier's output (probability of MDD) in two sets of HC data obtained at an interval of approximately 1 year. RESULTS: Test-retest correlation between the two sets of the classifier's output (probability of MDD) from HCs exhibited moderate reliability with an ICC of 0.45 (95 % confidence interval,0.13-0.68). The classifier distinguished patients with MDD and HCs with an accuracy of 69.7 % (sensitivity, 72.1 %; specificity, 66.7 %). LIMITATIONS: The data of patients with MDD in this study were cross-sectional, and the clinical significance of the marker, such as whether it is a state or trait marker of MDD and its association with treatment responsiveness, remains unclear. CONCLUSIONS: The results of this study reaffirmed the test-retest reliability and generalization performance of our brain network marker for the diagnosis of MDD.

Impact of solute carrier transporter gene polymorphisms on serum creatinine concentrations in healthy volunteers.

In this study, we investigated the impact of single nucleotide polymorphisms in solute carrier (SLC) transporters, that is, SLC22A7 c.1586 + 206A > G, SLC22A2 c.808G > T, SLC22A3 c.1233G > A, SLC47A1 c.922-158G > A, and SLC47A2 c.-130G > A, on serum creatinine (SCr) concentrations. This cross-sectional study included residents who participated as volunteers in a health promotion study. Lifestyle data, blood chemical analysis data, and SLC gene polymorphism information were collected from each participant. Univariate analyses were carried out to determine differences between groups and correlations in SCr. Stepwise multiple regression analysis was performed to confirm the independence of factors that were significantly different in the univariate analyses. In multiple regression analyses, muscle mass, serum cystatin C concentrations, body fat percentage, serum albumin concentrations, and SLC47A2 c.-130G/G had the highest contribution to SCr concentrations, in that order (standardized regression coefficients = .505, .332, -.234, .123, and .084, respectively). The final model explained 72.2% of the variability in SCr concentrations. The SLC47A2 c.-130G > A polymorphism may affect creatinine dynamics in the proximal tubules. Further studies are needed to determine the effects of SLC transporter gene polymorphisms on SCr concentrations in patients with various diseases in real-world clinical settings.