Enhanced therapeutic effects of mesenchymal stem cell-derived extracellular vesicles within chitosan hydrogel in the treatment of diabetic foot ulcers.

Extracellular vesicles (EVs) derived from human umbilical cord mesenchymal stem cells (hUCMSCs) have emerged as promising candidates for cell-free therapy in various diseases, including chronic cutaneous wounds. However, the lack of standardized protocols for EVs' preparation and identification poses a significant challenge to their clinical application. Thus, the objective was to develop a safe and efficient method for the large-scale production of hUCMSC-derived EVs while establishing a comprehensive identification protocol encompassing morphology, particle size distribution, protein expression, and purity. This study observed that most of the EVs acquired through the protocol exhibited either a cup-shaped or round-shaped structure, with a median diameter of ~73.25 nm. The proportions of EVs positive for CD9, CD63, and CD81 were 37.5%, 38.6%, and 19.8%, respectively. To enhance their therapeutic potential in wound treatment, EVs were incorporated into chitosan hydrogel, forming chitosan hydrogel-EVs (CS-EVs). Furthermore, it was demonstrated that CS-EVs exhibited continuous release of EVs into the surrounding environment and, importantly, that the released EVs were internalized by human umbilical vein endothelial cells (HUVECs), resulting in significant enhancement of cell migration and angiogenesis. Additionally, in a rat model of diabetic foot ulcers, CS-EVs demonstrated a robust therapeutic effect in promoting wound healing. Following a 15-day treatment period, the group treated with CS-EVs demonstrated an impressive 93.3% wound closure ability, accompanied by a high degree of re-epithelialization. In contrast, the control group exhibited only a 71.5% reduction in wound size. In summary, this study offers solutions for the purification, characterization, and application of EVs in clinical wound treatment. These results not only offer fresh perspectives on the involvement of hUCMSC-derived EVs in wound healing but also introduce a non-invasive approach for applying EVs that holds practical significance in skin repair.

Gender Differences in Gut Microbiome Composition Between Schizophrenia Patients With Normal Body Weight and Central Obesity.

Background: Obesity is a common health problem among patients with schizophrenia, but the precise mechanisms are not fully understood. There has been much interest in the relationship between gut microbiome and development of obesity. Gender-dependent microbial alteration has been reported in previous studies. However, the gender factor in gut microbiome composition of schizophrenia patients has been less investigated. Our study aimed to identify differences in gut microbiota between schizophrenia patients with normal weight and central obesity and investigate the gender specific features. Method: Twenty participants (10 males, 10 females) with central obesity (CO) and 20 participants (10 males, 10 females) with normal weight (NW) were recruited from two rehabilitation wards in a psychiatric hospital in central Taiwan. Fecal samples from 40 participants were processed for microbiota analysis. The intestinal microbiota composition was analyzed using next-generation sequencing and QIIME software. Results: Significantly higher richness of gut microbiota at the class level (measured by the number of observed OTUs) was observed in female NW subjects than in female CO subjects (P = 0.033). Furthermore, female NW subjects showed higher alpha diversity at both phylum and class levels (measured by the Shannon, Simpson, and Inverse-Simpson indexes) compared with female CO subjects. Males showed no significant difference in alpha diversity between groups. Taxonomic analysis showed that female CO subjects had significantly lower abundance of Verrucomicrobia (P = 0.004) at the phylum level, reduced abundance of Akkermansia (P = 0.003) and elevated level of Prevotella (P = 0.038) and Roseburia (P = 0.005) at the genus level. Conclusions: The present results evidenced altered microbiome composition in schizophrenia patients with central obesity and further suggested the role of the gender factor in the process of gut dysbiosis.

A review for cell and particle tracking on microscopy images using algorithms and deep learning technologies.

Time-lapse microscopy images generated by biological experiments have been widely used for observing target activities, such as the motion trajectories and survival states. Based on these observations, biologists can conclude experimental results or present new hypotheses for several biological applications, i.e. virus research or drug design. Many methods or tools have been proposed in the past to observe cell and particle activities, which are defined as single cell tracking and single particle tracking problems, by using algorithms and deep learning technologies. In this article, a review for these works is presented in order to summarize the past methods and research topics at first, then points out the problems raised by these works, and finally proposes future research directions. The contributions of this article will help researchers to understand past development trends and further propose innovative technologies.

The Chinese Mandarin Version of the Crisis Triage Rating Scale for Taiwanese with Mental Illness to Compulsory Hospitalization.

BACKGROUND: A controversial issue of the need to protect human rights and ensure public safety still remains a conflict in Taiwan. The purpose of this study was to translate the Crisis Triage Rating Scale to Chinese Mandarin (CMCTRS). METHOD: A cross-sectional design with convenient sampling was employed in this study. The CMCTRS was tested on 302 Taiwanese individuals with mental illness who were admitted to the emergency room (ER) of a psychiatric center. A higher score indicated a greater need for mandatory psychiatric admission. Psychiatrists rated the patients' status according to three scale criteria and six action plans of recommendations. RESULTS: Five specialists evaluated the content validity index to be 0.8. A total of 210 participants (69.5%) were deemed suitable for compulsory hospitalization or admission for observation in ER. The optimal cut-off score was 8, with a Youden Index of 1.46, a sensitivity of 0.748, and a specificity of 0.712 in deciding the need for hospitalization or observation. CONCLUSIONS: The CMCTRS exhibited an acceptable criterion validity with psychiatrists in a population of 302 patients at the ER of a psychiatric center. A cut-off point of 8 is recommended for determining hospitalization or a minimum 24 h stay at emergency for observation.

Genome-Wide Association Study of Lithium-Induced Dry Mouth in Bipolar I Disorder.

Dry mouth is a rather common unpleasant adverse drug reaction (ADR) to lithium treatment in bipolar disorders that often lead to poor adherence or early dropout. The aim of this study was to identify the genetic variants of dry mouth associated with lithium treatment in patients with bipolar I (BPI) disorder. In total, 1242 BPI patients who had ever received lithium treatment were identified by the Taiwan Bipolar Consortium for this study. The proportions of patients who experienced impaired drug compliance during lithium medication were comparable between those only with dry mouth and those with any other ADR (86% and 93%, respectively). Dry mouth appeared to be the most prevalent (47.3%) ADR induced by lithium treatment. From the study patients, 921 were included in a genome-wide association study (GWAS), and replication was conducted in the remaining 321 patients. The SNP rs10135918, located in the immunoglobulin heavy chain locus (IGH), showed the strongest associations in the GWAS (p = 2.12 × 10-37) and replication groups (p = 6.36 × 10-13) (dominant model) for dry mouth with a sensitivity of 84.9% in predicting dry mouth induced by lithium. Our results may be translated into clinical recommendation to help identify at-risk individuals for early identification and management of dry mouth, which will improve medication adherence.

An Automatic Bleeding-Rank System for Transurethral Resection of the Prostate Surgery Videos Using Machine Learning.

Benign prostatic hyperplasia (BPH) is the main cause of lower urinary tract symptoms (LUTS) in aging males. Transurethral resection of the prostate (TURP) surgery is performed by a cystoscope passing through the urethra and scraping off the prostrate piece by piece through a cutting loop. Although TURP is a minimally invasive procedure, bleeding is still the most common complication. Therefore, the evaluation, monitoring, and prevention of interop bleeding during TURP are very important issues. The main idea of this study is to rank bleeding levels during TURP surgery from videos. Generally, to judge bleeding level by human eyes from surgery videos is a difficult task, which requires sufficient experienced urologists. In this study, machine learning-based ranking algorithms are proposed to efficiently evaluate the ranking of blood levels. Based on the visual clarity of the surgical field, the four ranking of blood levels, including score 0: excellent; score 1: acceptable; score 2: slightly bad; and 3: bad, were identified by urologists who have sufficient experience in TURP surgery. The results of extensive experiments show that the revised accuracy can achieve 90, 89, 90, and 91%, respectively. Particularly, the results reveal that the proposed methods were capable of classifying the ranking of bleeding level accurately and efficiently reducing the burden of urologists.

Machine Learning Algorithms to Predict Mortality of Neonates on Mechanical Intubation for Respiratory Failure.

BACKGROUND: Early identification of critically ill neonates with poor outcomes can optimize therapeutic strategies. We aimed to examine whether machine learning (ML) methods can improve mortality prediction for neonatal intensive care unit (NICU) patients on intubation for respiratory failure. METHODS: A total of 1734 neonates with respiratory failure were randomly divided into training (70%, n = 1214) and test (30%, n = 520) sets. The primary outcome was the probability of NICU mortality. The areas under the receiver operating characteristic curves (AUCs) of several ML algorithms were compared with those of the conventional neonatal illness severity scoring systems including the NTISS and SNAPPE-II. RESULTS: For NICU mortality, the random forest (RF) model showed the highest AUC (0.939 (0.921-0.958)) for the prediction of neonates with respiratory failure, and the bagged classification and regression tree model demonstrated the next best results (0.915 (0.891-0.939)). The AUCs of both models were significantly better than the traditional NTISS (0.836 (0.800-0.871)) and SNAPPE-II scores (0.805 (0.766-0.843)). The superior performances were confirmed by higher accuracy and F1 score and better calibration, and the superior and net benefit was confirmed by decision curve analysis. In addition, Shapley additive explanation (SHAP) values were utilized to explain the RF prediction model. CONCLUSIONS: Machine learning algorithms increase the accuracy and predictive ability for mortality of neonates with respiratory failure compared with conventional neonatal illness severity scores. The RF model is suitable for clinical use in the NICU, and clinicians can gain insights and have better communication with families in advance.

Machine Learning Approaches to Predict In-Hospital Mortality among Neonates with Clinically Suspected Sepsis in the Neonatal Intensive Care Unit.

BACKGROUND: preterm and critically ill neonates often experience clinically suspected sepsis during their prolonged hospitalization in the neonatal intensive care unit (NICU), which can be the initial sign of final adverse outcomes. Therefore, we aimed to utilize machine learning approaches to predict neonatal in-hospital mortality through data-driven learning. METHODS: a total of 1095 neonates who experienced clinically suspected sepsis in a tertiary-level NICU in Taiwan between August 2017 and July 2020 were enrolled. Clinically suspected sepsis was defined based on clinical features and laboratory criteria and the administration of empiric antibiotics by clinicians. The variables used for analysis included patient demographics, clinical features, laboratory data, and medications. The machine learning methods used included deep neural network (DNN), k-nearest neighbors, support vector machine, random forest, and extreme gradient boost. The performance of these models was evaluated using the area under the receiver operating characteristic curve (AUC). RESULTS: the final in-hospital mortality of this cohort was 8.2% (90 neonates died). A total of 765 (69.8%) and 330 (30.2%) patients were randomly assigned to the training and test sets, respectively. Regarding the efficacy of the single model that most accurately predicted the outcome, DNN exhibited the greatest AUC (0.923, 95% confidence interval [CI] 0.953-0.893) and the best accuracy (95.64%, 95% CI 96.76-94.52%), Cohen's kappa coefficient value (0.74, 95% CI 0.79-0.69) and Matthews correlation coefficient value (0.75, 95% CI 0.80-0.70). The top three most influential variables in the DNN importance matrix plot were the requirement of ventilator support at the onset of suspected sepsis, the feeding conditions, and intravascular volume expansion. The model performance was indistinguishable between the training and test sets. CONCLUSIONS: the DNN model was successfully established to predict in-hospital mortality in neonates with clinically suspected sepsis, and the machine learning algorithm is applicable for clinicians to gain insights and have better communication with families in advance.

Novel Role for miR-1290 in Host Species Specificity of Influenza A Virus.

The role of microRNA (miRNA) in influenza A virus (IAV) host species specificity is not well understood as yet. Here, we show that a host miRNA, miR-1290, is induced through the extracellular signal-regulated kinase (ERK) pathway upon IAV infection and is associated with increased viral titers in human cells and ferret animal models. miR-1290 was observed to target and reduce expression of the host vimentin gene. Vimentin binds with the PB2 subunit of influenza A virus ribonucleoprotein (vRNP), and knockdown of vimentin expression significantly increased vRNP nuclear retention and viral polymerase activity. Interestingly, miR-1290 was not detected in either chicken cells or mouse animal models, and the 3' UTR of the chicken vimentin gene contains no binding site for miR-1290. These findings point to a host species-specific mechanism by which IAV upregulates miR-1290 to disrupt vimentin expression and retain vRNP in the nucleus, thereby enhancing viral polymerase activity and viral replication.

Long-term Use of Clozapine is Protective for Bone Density in Patients with Schizophrenia.

Low bone mineral density (BMD) prevails among patients with schizophrenia. Antipsychotics use plays an important role in BMD. Previous cross-section study suggests that clozapine treatment may benefit BMD of women with schizophrenia. However, the effect of long-term clozapine therapy on BMD remains unknown. This prospective study compared clozapine and non-clozapine antipsychotics in long-term effects on BMD among both men and women with schizophrenia. Patients with schizophrenia and age-matched healthy individuals were enrolled from two centers. All patients, including clozapine receivers and non-clozapine antipsychotics recipients, kept clinically stable with unchanged antipsychotics and doses for at least 6 months at enrollment and during the follow-up period. BMD was examined by dual-energy X-ray absorptiometer upon enrollment and at 1- or 3-year follow-up. Thorough clinical and laboratory variables were measured too. The mean BMD of patients receiving clozapine was higher than that of the non-clozapine patients at both enrollment and follow-up. Overall, the patients in the clozapine group gained BMD, while those in the non-clozapine group lost BMD after 1-3 years (p = 0.015). There was no significant difference of BMD change between clozapine-treated patients and healthy controls. Factors associated with BMD change in the clozapine group included calcium level (B = -0.607, p = 0.021) and T3 level (B = -0.077, p = 0.007). This longitudinal study suggests that long-term clozapine treatment may protect BMD compared to prolactin-raising and non-clozapine prolactin-sparing antipsychotics among patients with schizophrenia. Future prospective studies are warranted to testify whether switching from non-clozapine antipsychotics to clozapine can rescue BMD.

Change in 1-year hospitalization of overall and older patients with major depressive disorder after second-generation antipsychotics augmentation treatment.

BACKGROUND: Studies on second-generation antipsychotics (SGA) augmentation treatment for older adults with major depressive disorder (MDD) remain limited. We aimed to investigate the effectiveness of SGA augmentation for overall and older patients with MDD inpatient history by assessing the change in 1-year hospitalization before and after SGA augmentation using the latest National Health Insurance Research Database (NHIRD) in Taiwan. METHODS: The samples were MDD patients (ICD-9 CM code: 296.2 and 296.3) who had psychiatric inpatient history. A total of 2602 MDD patients including 430 elderly subjects (age ≥ 60 years) who received SGA augmentation for 8 weeks between January 1998 and December 2012 were included in this 1-year mirror-image study. Outcome measures included number and length of psychiatric and all-cause hospitalizations. RESULTS: After 8-week continuous SGA augmentation in the study subjects, the total number and days of psychiatric hospitalizations among overall patients reduced by 33.57% (p < .0001) and 18.24% (p < .0001), respectively; the total number and days of psychiatric hospitalizations among older patients (age ≥ 60) reduced by 44.52% (p < .0001) and 27.95% (p < .0001), respectively. Similarly, the total number and days of all-cause hospitalizations were significantly reduced. LIMITATIONS: MDD patients without inpatient history were not included due to data limitation; hence, the results may not be generalized to all patients. CONCLUSIONS: The results support that SGA may be effective in reducing psychiatric and all-cause hospitalization among overall and elderly MDD patients. More studies focusing on the safety of SGA among older MDD patients is warranted.

MGUPGMA: A Fast UPGMA Algorithm With Multiple Graphics Processing Units Using NCCL.

A phylogenetic tree is a visual diagram of the relationship between a set of biological species. The scientists usually use it to analyze many characteristics of the species. The distance-matrix methods, such as Unweighted Pair Group Method with Arithmetic Mean and Neighbor Joining, construct a phylogenetic tree by calculating pairwise genetic distances between taxa. These methods have the computational performance issue. Although several new methods with high-performance hardware and frameworks have been proposed, the issue still exists. In this work, a novel parallel Unweighted Pair Group Method with Arithmetic Mean approach on multiple Graphics Processing Units is proposed to construct a phylogenetic tree from extremely large set of sequences. The experimental results present that the proposed approach on a DGX-1 server with 8 NVIDIA P100 graphic cards achieves approximately 3-fold to 7-fold speedup over the implementation of Unweighted Pair Group Method with Arithmetic Mean on a modern CPU and a single GPU, respectively.

Embedded-Based Graphics Processing Unit Cluster Platform for Multiple Sequence Alignments.

High-end graphics processing units (GPUs), such as NVIDIA Tesla/Fermi/Kepler series cards with thousands of cores per chip, are widely applied to high-performance computing fields in a decade. These desktop GPU cards should be installed in personal computers/servers with desktop CPUs, and the cost and power consumption of constructing a GPU cluster platform are very high. In recent years, NVIDIA releases an embedded board, called Jetson Tegra K1 (TK1), which contains 4 ARM Cortex-A15 CPUs and 192 Compute Unified Device Architecture cores (belong to Kepler GPUs). Jetson Tegra K1 has several advantages, such as the low cost, low power consumption, and high applicability, and it has been applied into several specific applications. In our previous work, a bioinformatics platform with a single TK1 (STK platform) was constructed, and this previous work is also used to prove that the Web and mobile services can be implemented in the STK platform with a good cost-performance ratio by comparing a STK platform with the desktop CPU and GPU. In this work, an embedded-based GPU cluster platform will be constructed with multiple TK1s (MTK platform). Complex system installation and setup are necessary procedures at first. Then, 2 job assignment modes are designed for the MTK platform to provide services for users. Finally, ClustalW v2.0.11 and ClustalWtk will be ported to the MTK platform. The experimental results showed that the speedup ratios achieved 5.5 and 4.8 times for ClustalW v2.0.11 and ClustalWtk, respectively, by comparing 6 TK1s with a single TK1. The MTK platform is proven to be useful for multiple sequence alignments.

Corrigendum: Intestinal microbiome in children with severe and complicated acute viral gastroenteritis.

This corrects the article DOI: 10.1038/srep46130.

Intestinal microbiome in children with severe and complicated acute viral gastroenteritis.

The aim of the present study was to evaluate the microbiota of children with severe or complicated acute viral gastroenteritis (AGE). To that end, next-generation sequencing (NGS) technology was used to sequence the 16S ribosomal RNA (16S rRNA) gene in 20 hospitalized pediatric patients with severe or complicated AGE and a further 20 otherwise healthy children; the fecal microbiome was then assessed. Comparative metagenomics data were analyzed by a Wilcoxon rank-sum test and hierarchical clustering analysis of bacterial reads. The statistical analyses showed a significantly decreased Shannon diversity index (entropy score) of the intestinal microbiota in patients with severe AGE compared with normal controls (P = 0.017) and patients with mild-to-moderate AGE (P = 0.011). The intestinal microbiota score of the 5 patients with rotavirus AGE was significantly lower than that of those with norovirus infection (P = 0.048). Greater richness in Campylobacteraceae (P = 0.0003), Neisseriaceae (P = 0.0115), Methylobacteriaceae (P = 0.0004), Sphingomonadaceae (P = 0.0221), and Enterobacteriaceae (P = 0.0451) was found in patients with complicated AGE compared with normal controls. The data suggest a significant reduction in intestinal microbial diversity in patients with severe AGE, particularly those with rotavirus infection.

Adjunctive sarcosine plus benzoate improved cognitive function in chronic schizophrenia patients with constant clinical symptoms: A randomised, double-blind, placebo-controlled trial.

Objectives Hypofunction of NMDA receptor is implicated in the pathophysiology, particularly cognitive impairment, of schizophrenia. Sarcosine, a glycine transporter I (GlyT-1) inhibitor, and sodium benzoate, a d-amino acid oxidase (DAAO) inhibitor, can both enhance NMDA receptor-mediated neurotransmission. We proposed simultaneously inhibiting DAAO and GlyT-1 may be more effective than inhibition of either in improving the cognitive and global functioning of schizophrenia patients. Methods This study compared add-on sarcosine (2 g/day) plus benzoate (1 g/day) vs. sarcosine (2 g/day) for the clinical symptoms, as well as the cognitive and global functioning, of chronic schizophrenia patients in a 12-week, double-blind, randomised, placebo-controlled trial. Participants were measured with the Positive and Negative Syndrome Scale and the Global Assessment of Functioning Scale every 3 weeks. Seven cognitive domains, recommended by the Measurement and Treatment Research to Improve Cognition in Schizophrenia Committee, were measured at weeks 0 and 12. Results Adjunctive sarcosine plus benzoate, but not sarcosine alone, improved the cognitive and global functioning of patients with schizophrenia, even when their clinical symptoms had not improved. Conclusions This finding suggests N-methyl-d-aspartate receptor-enhancement therapy can improve the cognitive function of patients with schizophrenia, further indicating this pro-cognitive effect can be primary without improvement in clinical symptoms.

Efficacy and safety of ticagrelor versus clopidogrel in acute coronary syndrome in Taiwan: A multicenter retrospective pilot study.

BACKGROUND: The efficacy and safety of ticagrelor compared with clopidogrel in acute coronary syndrome has not previously been evaluated in an Eastern Asian population, which is recognized to have a different response to P2Y12 antagonists compared with the Caucasian population in real-life situations. METHODS: A multicenter retrospective pilot study was performed to evaluate 928 consecutive patients with acute coronary syndrome, receiving aspirin and one P2Y12 antagonist (324 ticagrelor or 604 clopidogrel). Using propensity score matching, 448 patients were selected and divided into two equal groups. Kaplan-Meier analysis was used to study patient survival and event-free status using the log-rank test. Independent covariates were identified using univariate in a multivariate Cox proportional hazard model. RESULTS: In the overall cohort, significant differences were observed for certain variables between the two groups. During the mean 164.3 (±116.4)-day follow-up in the overall cohort, ticagrelor treatment had no significant effect on the primary efficacy endpoint (myocardial infarction, stroke, or vascular death); however, in the matched cohort, ticagrelor showed a lower incidence of primary endpoint (hazard ratio: 0.56; 95% confidence interval: 0.30-1.04; p = 0.07) and stroke (hazard ratio: 0.15; 95% confidence interval: 0.02-1.24; p = 0.08) with marginal statistical significance, and a similar bleeding rate. The protective effect of ticagrelor treatment was consistent for all subgroups. More patients treated with ticagrelor experienced dyspnea (21.0% vs. 11.6%, p = 0.007), and P2Y12 antagonist treatment was consequently discontinued. CONCLUSION: Ticagrelor treatment could provide a marginally favorable effect at the expense of an increased risk of dyspnea in real-life situations. This pilot study provides a scientific basis to call for a larger, suitably powered Phase 4 prospective or observational study in this ethnic population.

RISK OF NEW ONSET TYPE II DM IN MDD PATIENTS RECEIVING SECOND-GENERATION ANTIPSYCHOTICS TREATMENT: A NATIONWIDE COHORT STUDY.

BACKGROUND: Second-generation antipsychotics (SGA) augmentation treatment has showed better efficacy in patients with major depressive disorder (MDD). However, the association between SGA and diabetes mellitus (DM) in MDD patients deserves further investigation. The study aimed to examine the risk of new onset type II DM in MDD patients receiving SGA treatment. METHODS: From the Psychiatric Inpatient Medical Claim Dataset, MDD patients treated with SGA continuously for more than 8 weeks were analyzed in a 1:1 propensity score matched pair sample to 1,049 patients that had never been treated with SGA. Patients were followed up to 5 years based on ICD-9 CM codes indicating incident type II DM. Cumulative incidences of type II DM were calculated and the Cox proportional hazards model with competing risk was applied to determine the risk factors for type II DM onset. RESULTS: Cumulative incidences of new-onset type II DM between the two groups were similar. Use of SGA showed no significant increase in risk for new-onset type II DM (hazard ratio [HR] = 0.898; 95% confidence interval [CI], 0.605-1.334; P-value = 0.596). Increased risk for type II DM was shown to be associated with aging (per year) (HR = 1.039; 95% CI, 1.026-1.053; P-value < 0.001) and history of hyperlipidemia (HR = 2.323; 95% CI, 1.469-3.675; P-value < 0.001). CONCLUSIONS: This study indicated that there is no significant difference in the risk of developing type II DM between MDD patients with and without SGA exposure. More studies focused on the benefit-risk assessment of SGA treatment in patients with MDD are warranted.

Decreased mRNA expression for the two subunits of system xc(-), SLC3A2 and SLC7A11, in WBC in patients with schizophrenia: Evidence in support of the hypo-glutamatergic hypothesis of schizophrenia.

BACKGROUND: The cystine/glutamate antiporter system xc(-), playing a critical role in the regulation of glutamate release, might be implicated in the pathogenesis of schizophrenia. This study examined whether peripheral expressions of the system xc(-) subunits are characteristic of schizophrenia. METHODS: Expression of system xc(-) genes including SLC3A2 and SLC7A11 in peripheral WBCs of patients with schizophrenia and healthy individuals were measured using quantitative PCR. Both psychotropic-free and medicated patients with schizophrenia were recruited. RESULTS: A total of 96 schizophrenia patients (48 medicated and 48 drug-free) and 96 healthy individuals were enrolled. The mRNA expression levels using the 2(-ΔΔC)T Method of both SLC3A2 and SLC7A11 in WBCs of schizophrenia patients were markedly lower than that of healthy individuals (0.22 and 0.48, respectively, the mRNA expression level of normal controls was normalized to 1). There was no significant difference between medicated and drug-free patients in the mRNA expressions of both SLC3A2 and SLC7A11. The Receiver Operating Characteristics (ROC) analysis of SLC3A2 mRNA levels using ΔΔCT values for drug-free schizophrenia patients vs. healthy controls determined an optimal cutoff value, 0.801, with high sensitivity (1.000) and modest specificity (0.694) (area under curve of ROC = 0.794). CONCLUSION: This is the first study indicating that the peripheral mRNA expression levels of SLC7A11 and SLC3A2 may be lower in patients with schizophrenia than healthy individuals. The finding supports the hypo-glutamatergic neurotransmission hypothesis in schizophrenia. Whether mRNA expression of system xc(-) subunits genes, particularly SLC3A2, could serve as a potential biomarker of schizophrenia needs further studies.