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AbstractAim: The aim of this systematic review and meta-analysis was to identify, evaluate, and synthesize the evidence from studies that have investigated the treatment effect via telemedicine interventions on depressive symptoms, quality of life, and work and social functioning in patients with depression.Methods: Six electronic databases (MEDLINE [1916–2021], PubMED [1950–2021], PsycINFO [1971–2021], Scopus [2004–2021], Embase [1972–2021], and CINAHL [1937–2021]) were systematically searched in March 2021. Reference lists of identified articles were hand searched. Randomized controlled trials were included if they investigated the treatment effects via telemedicine interventions in patients who had a depression diagnosis. Quality assessment was evaluated using the critical appraisal checklists developed by the Joanna Briggs Institute.Results: Seventeen (17) trials (n = 2,394) met eligibility criteria and were included in the analysis. Eleven (11) randomized controlled trials shared common outcome measures, allowing meta-analysis. The results provided evidence that treatment via telemedicine interventions were beneficial for depressive symptoms (standardized mean difference= −0.44; 95% CI= −0.64 to −0.25; p

Abstract Background Neutropenia is a noteworthy side effect of clozapine, which might warrant this drugs’ discontinuance for safety. Studies have revealed that the risk of neutropenia increases with concurrent administration of valproate, but the evidence was limited. Conversely, lithium may have an ameliorating effect on clozapine-induced neutropenia. This study explored the effects of valproate and lithium on white blood cell counts in patients treated with clozapine. Methods We retrospectively investigated the electronic medical records from one tertiary psychiatric hospital in Taiwan and enrolled patients discharged between January 1, 2006, and December 31, 2017, with clozapine prescriptions. We scrutinized their demographic data, medications, and hematological results at discharge and during follow-up outpatient clinic visits over the subsequent 3 years. Patients were classified into four groups: clozapine only (CLO), clozapine and valproate (CLO + VAL), clozapine and lithium (CLO + Li), and clozapine, valproate, and lithium (CLO + VAL + Li). We also identified hematological events (neutropenia or leukocytosis) of these patients during outpatient follow-ups. Results Of the included 1084 patients, 55(5.1%) developed neutropenia. Concurrent valproate use (odds ratio [OR] = 3.49) and older age (p = .007) were identified as risk factors. Moreover, 453 (41.79%) patients developed leukocytosis. Younger age; male sex; and concurrent use of lithium (OR = 3.39, p

IntroductionThe effects of repetitive transcranial magnetic stimulation (rTMS) on the left dorsolateral prefrontal cortex (DLPFC) in patients with major depressive disorder (MDD) have been proved to have antidepressant effects. However, the absence of biomarkers to assess treatment response remains a challenge. This research aims to explore the relationship between frontal lobe activity, measured using near infrared spectroscopy (NIRS), and changes in symptoms among MDD patients following rTMS treatment.MethodsA total of 26 MDD patients underwent 20 sessions of 10 Hz rTMS targeting the left DLPFC. NIRS was used to measure frontal lobe activity during a verbal fluency test at baseline, after 10 rTMS sessions, and after 20 rTMS sessions. Responders were defined as individuals with more than a 50% reduction in symptoms based on the 21-item Hamilton Depression Rating Scale after 20 rTMS sessions.ResultsAmong the 14 responders, an increase in frontal lobe activity was significantly correlated with improvements in depressive symptoms following 10 (p = 0.0001) and 20 rTMS sessions (p = 0.007). Additionally, frontal lobe activity after 10 rTMS sessions was significantly associated with symptom improvement after 20 sessions (p = 0.001). These associations were not observed among non-responders.ConclusionThe findings from this study indicate distinct patterns of frontal lobe activity between responders and non-responders to rTMS treatment, suggesting that NIRS has the potential to serve as a biomarker for monitoring treatment response in MDD patients undergoing rTMS.

BackgroundAs a mental health issue, suicide is a growing global concern, with patients who have post-traumatic stress disorder (PTSD) being at particularly high risk. This study aimed to investigate whether the link between PTSD and suicidal ideation is mediated by trauma-related guilt.MethodsData were obtained from Wave 1, Time 1 (November 2016), and Time 2 (March 2017) of the National Survey for Stress and Health (NSSH) in Japan. The NSSH is an online longitudinal survey conducted on Japan’s national population aged 18 years and older. The cumulative response rate of the survey was 66.7% at Time 2. A total of 1,005 patients with PTSD were included for analyses. The severity of PTSD symptoms was assessed with PTSD DSM-5 Checklist, and the trauma-related guilt were assessed using the two subscales (hindsight-bias/responsibility and global guilt scale) of the trauma-related guilt inventory (TRGI). Suicidal ideation was evaluated using the suicidal ideation attributes scale (SIDAS). Pearson’s correlation was used to investigate the associations among PTSD symptoms, TRGI scores, and SIDAS scores. Causal mediation analysis was applied to evaluate the causal relationship between PTSD, trauma-related guilt, and suicidal ideation.ResultsPearson’s correlation did not show patients’ age, gender, and household income significantly associated with SIDAS scores. On the other hand, severities of PTSD symptoms (r = 0.361, p

Objective: This meta-analysis aimed to ascertain the efficacy of non-invasive brain stimulation (NIBS)—comprising repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS)—for depression in traumatic brain injury (TBI) patients. Methods: Comprehensive searches were conducted in PubMed, Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials up to 28 January 2023. Random-effects models assessed the treatment effects, and heterogeneity was evaluated through I2 statistics and funnel plot inspection. Results: From 10 trials (234 participants; 8 rTMS, 2 tDCS), NIBS was found significantly more effective than sham in alleviating depressive symptoms (SMD: 0.588, 95% CI: 0.264–0.912; p < 0.001). rTMS, specifically, showed higher efficacy (SMD: 0.707, 95% CI: 0.306–1.108; p = 0.001) compared to sham, whereas tDCS outcomes were inconclusive (SMD: 0.271, 95% CI: −0.230 to 0.771; p = 0.289). Meta-regression found no correlation with the number of sessions, treatment intensity, or total dose. Notably, while post-treatment effects were significant, they diminished 1–2 months post intervention. Adverse events associated with NIBS were minimal, with no severe outcomes like seizures and suicide reported. Conclusions: rTMS emerged as a potent short-term intervention for depression in TBI patients, while tDCS findings remained equivocal. The long-term efficacy of NIBS is yet to be established, warranting further studies. The low adverse event rate reaffirms NIBS’s potential safety.

ObjectiveSeveral prognostic models of suicide risk have been published; however, few have been implemented in Japan using longitudinal cohort data. The aim of this study was to identify suicide risk factors for suicidal ideation in the Japanese population and to develop a machine-learning model to predict suicide risk in Japan.Materials and MethodsData was obtained from Wave1 Time 1 (November 2016) and Time 2 (March 2017) of the National Survey for Stress and Health in Japan, were incorporated into a suicide risk prediction machine-learning model, trained using 65 items related to trauma and stress. The study included 3,090 and 2,163 survey respondents >18 years old at Time 1 and Time 2, respectively. The mean (standard deviation, SD) age was 44.9 (10.9) years at Time 1 and 46.0 (10.7) years at Time 2. We analyzed the participants with increased suicide risk at Time 2 survey. Model performance, including the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity, were also analyzed.ResultsThe model showed a good performance (AUC = 0.830, 95% confidence interval = 0.795–0.866). Overall, the model achieved an accuracy of 78.8%, sensitivity of 75.4%, specificity of 80.4%, positive predictive value of 63.4%, and negative predictive value of 87.9%. The most important risk factor for suicide risk was the participants' Suicidal Ideation Attributes Scale score, followed by the Sheehan Disability Scale score, Patient Health Questionnaire-9 scores, Cross-Cutting Symptom Measure (CCSM-suicidal ideation domain, Dissociation Experience Scale score, history of self-harm, Generalized Anxiety Disorder-7 score, Post-Traumatic Stress Disorder check list-5 score, CCSM-dissociation domain, and Impact of Event Scale-Revised scores at Time 1.ConclusionsThis prognostic study suggests the ability to identify patients at a high risk of suicide using an online survey method. In addition to confirming several well-known risk factors of suicide, new risk measures related to trauma and trauma-related experiences were also identified, which may help guide future clinical assessments and early intervention approaches.

ObjectiveWe aimed to investigate the efficacy and tolerability of cranial electrotherapy stimulation (CES) for patients with anxiety symptoms.MethodWe searched the Pubmed, Cochrane Central Register of Controlled Trials (CENTRAL), Embase and Medline for randomized control trials (RCTs) from the time of inception until November 15, 2021, following Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Data were pooled using a random-effects model. The primary outcomes were the mean change scores for anxiety symptoms. The secondary outcomes were the mean change scores for depressive symptoms.ResultsEleven RCTs were eligible (n = 794, mean age: 41.4, mean population of female: 64.8%). CES significantly reduced the anxiety symptoms compared to the control group [k = 11, n = 692, Hedge's g = −0.625, 95% confidence intervals (CIs) = −0.952 to −0.298, P < 0.001] with moderate effect size. The subgroup analysis showed that CES reduced both primary and secondary anxiety (primary anxiety, k =3, n = 288, Hedges' g = −1.218, 95% CIs = −1.418 to −0.968, P = 0.007; secondary anxiety, k = 8, n = 504, Hedges' g = −0.334, 95% CIs = −0.570 to −0.098, P = 0.006). After performing between group analysis, we found CES has significant better efficacy for patients with primary anxiety than those with secondary anxiety (P < 0.001). For secondary outcome, CES significantly reduced depressive symptoms in patients with anxiety disorders (k = 8, n = 552, Hedges' g = −0.648, 95% CIs = −1.062 to −0.234, P = 0.002). No severe side effects were reported and the most commonly reported adverse events were ear discomfort and ear pain.ConclusionWe found CES is effective in reducing anxiety symptoms with moderate effect size in patients with both primary and secondary anxiety. Furthermore, CES was well-tolerated and acceptable.Systematic Review Registration: PROSPERO, https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021267916.

ObjectiveThis study aimed to investigate the efficacy of repetitive transcranial magnetic stimulation (rTMS) in treating suicidal ideation in patients with mental illness.MethodWe followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Major electronic databases were systematically searched from the time of their inception until July 22, 2021. The primary outcome was the mean change in the scores for suicidal ideation. The secondary outcome was the mean change in depression severity.ResultsTen randomized controlled trials were eligible with 415 participants in the active treatment group (mean age = 53.78 years; mean proportion of women = 54.5%) and 387 participants in the control group (mean age = 55.52 years; mean proportion of women = 51.78%). rTMS significantly reduced suicidal ideation (k = 10, n = 802, Hedges' g = −0.390, 95% confidence interval [CI] = −0.193 to −0.588, p

Matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) has been used to identify microorganisms and predict antibiotic resistance. The preprocessing method for the MS spectrum is key to extracting critical information from complicated MS spectral data. Different preprocessing methods yield different data, and the optimal approach is unclear. In this study, we adopted an ensemble of multiple preprocessing methods––FlexAnalysis, MALDIquant, and continuous wavelet transform-based methods––to detect peaks and build machine learning classifiers, including logistic regressions, naïve Bayes classifiers, random forests, and a support vector machine. The aim was to identify antibiotic resistance in Acinetobacter baumannii, Acinetobacter nosocomialis, Enterococcus faecium, and Group B Streptococci (GBS) based on MALDI-TOF MS spectra collected from two branches of a referral tertiary medical center. The ensemble method was compared with the individual methods. Random forest models built with the data preprocessed by the ensemble method outperformed individual preprocessing methods and achieved the highest accuracy, with values of 84.37% (A. baumannii), 90.96% (A. nosocomialis), 78.54% (E. faecium), and 70.12% (GBS) on independent testing datasets. Through feature selection, important peaks related to antibiotic resistance could be detected from integrated information. The prediction model can provide an opinion for clinicians. The discriminative peaks enabling better prediction performance can provide a reference for further investigation of the resistance mechanism.

Objective: The association between posttraumatic stress disorder (PTSD) and suicidal ideation (SI) is well-known. However, a few studies have investigated the associations between PTSD symptom clusters based on the fifth edition of the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) and changes in suicide risk longitudinally.Methods: We adopted a longitudinal study design using data from the National Survey for Stress and Health of 3,090 of the Japanese population. The first and second surveys were conducted on November 2016 and March 2017, respectively. The suicidal ideation attributes scale was applied to assess the severity of suicidal ideation at baseline and the follow-up period. A multivariate linear regression model was conducted to examine the associations between the 4- or 7-factor model of PTSD symptom clusters at baseline and longitudinal changes in SI.Results: Overall, 3,090 subjects were analyzed (mean age, 44.9 ± 10.9 years; 48.8% female) at Baseline, and 2,163 completed the second survey. In the 4-factor model, we found that the severity of negative alternations in cognition and mood were significantly associated with increased SI after 4 months. In the 7-factor model, we found that the severity of anhedonia and externalizing behavior at baseline was significantly associated with increased SI during the follow-up period.Conclusions: We found that the seven-factor model of DSM-5 PTSD symptoms may provide greater specificity in predicting longitudinal SI change in the general population. Closely monitoring specific PTSD core symptoms may be more effective in mitigating key clinical and functional outcomes.

BackgroundClostridioides difficile is the leading cause of nosocomial infectious diarrhea. Toll-like receptors (TLRs) are the major components of innate immunity that sense pathogens. The relationship between TLRs and C. difficile infection (CDI) was analyzed in clinical patients and a mouse model.Materials and MethodsA prospective investigation was conducted in medical wards of Tainan Hospital, Ministry of Health and Welfare, Tainan, Taiwan, from January 2011 to January 2013. Adult patients were followed up for the development of CDI. Single nucleotide polymorphisms (SNPs) of TLR2 and TLR4 were analyzed to assess the relationship between genetic polymorphisms and the development of CDI. A mouse model of CDI was used to investigate the pathogenic role of TLRs in CDI, TLR2 and TLR4 knockout (Tlr2-/- and Tlr4-/-) mice.ResultsIn the prospective study, 556 patients were enrolled, and 6.5% (36) of patients, accounting for 3.59 episodes per 1000 patient-days, developed CDI. Of 539 patients with available blood samples, the TLR2 rs3804099 polymorphism was more often noted in those with CDI than in those without CDI (64.5% vs. 46.1%; P = 0.046) but was not significant in multivariate analysis. Because the TLR2 rs3804099 polymorphism was moderately associated with CDI, the role of TLR2 and TLR4 was further evaluated in a mouse model. Both Tlr2-/- and Tlr4-/- mice showed more severe CDI disease than wild-type mice in terms of body weight change and fecal content five days after oral challenge with C. difficile. Furthermore, Tlr2-/- mice suffered from more severe disease than Tlr4-/- mice, as evidenced by stool consistency, cecum weight, and survival rate.ConclusionThe TLR2 rs3804099 polymorphism is marginally associated with the development of CDI, and the pathogenic role of TLR2 is further supported by a mouse model.

Backgrounds: Reduced brain cortical activity over the frontotemporal regions measured by near infrared spectroscopy (NIRS) has been reported in patients with first-episode schizophrenia (FES). This study aimed to differentiate between patients with FES and healthy controls (HCs) on basis of the frontotemporal activity measured by NIRS with a support vector machine (SVM) and deep neural network (DNN) classifier. In addition, we compared the accuracy of performance of SVM and DNN.Methods: In total, 33 FES patients and 34 HCs were recruited. Their brain cortical activities were measured using NIRS while performing letter and category versions of verbal fluency tests (VFTs). The integral and centroid values of brain cortical activity in the bilateral frontotemporal regions during the VFTs were selected as features in SVM and DNN classifier.Results: Compared to HCs, FES patients displayed reduced brain cortical activity over the bilateral frontotemporal regions during both types of VFTs. Regarding the classifier performance, SVM reached an accuracy of 68.6%, sensitivity of 70.1%, and specificity of 64.6%, while DNN reached an accuracy of 79.7%, sensitivity of 88.8%, and specificity of 74.9% in the classification of FES patients and HCs.Conclusions: Compared to findings of previous structural neuroimaging studies, we found that using DNN to measure the NIRS signals during the VFTs to differentiate between FES patients and HCs could achieve a higher accuracy, indicating that NIRS can be used as a potential marker to classify FES patients from HCs. Future additional independent datasets are needed to confirm the validity of our model.

BACKGROUND:Dementia is characterized by prolonged progressive disability. Therefore, predicting mortality is difficult. An accurate prediction tool may be useful to ensure that end-of-life patients with dementia receive timely palliative care. PURPOSE:This study aims to establish a survival prediction model for elderly patients with dementia in Taiwan. METHODS:Data from the 2001 to 2010 National Health Insurance Research Database in Taiwan were used to identify 37,289 patients with dementia aged ≥65 years for inclusion in this retrospective longitudinal study. Moreover, this study examined the mortality indicators for dementia among demographic characteristics, chronic physical comorbidities, and medical procedures. A Cox proportional hazards model with time-dependent covariates was used to estimate mortality risk, and risk score functions were formulated using a point system to establish a survival prediction model. The prediction model was then tested using the area under the receiver operating characteristic curve. RESULTS:Thirteen mortality risk factors were identified: age, sex, stroke, chronic renal failure, liver cirrhosis, cancer, pressure injury, and retrospectively retrieved factors occurring in the 6 months before death, including nasogastric tube placement, supplemental oxygen supply, ≥2 hospitalization, receiving ≥1 emergency services, ≥2 occurrences of cardiopulmonary resuscitation, and receiving ≥2 endotracheal intubations. The area under the receiver operating characteristic curves for this prediction model for mortality at 6 and 12 months were 0.726 and 0.733, respectively. CONCLUSIONS:The survival prediction model demonstrated moderate accuracy for predicting mortality at 6 and 12 months before death in elderly patients with dementia. This tool may be valuable for helping health care providers and family caregivers to make end-of-life care decisions.

The allergic rhinitis (AR) is common in children. Symptoms of AR may result in daytime inattention, irritability, and hyperactivity, which are similar to symptoms of ADHD. The goal of this study was to examine the associations between AR and ADHD. The study subjects included 469 patients who received psychiatric care for ADHD in 2005 and the general population (n = 220,599). Distributions of age, gender, and living areas as well as AR in the general population and in the ADHD group were examined by x -tests. Multivariate logistic regression models were used to analyze the risk factors associated with AR. The prevalence of AR in ADHD group and the general population was 28.4% and 15.2%, respectively, which was significantly higher in ADHD group than the general population (p

Previous research has suggested a link between antidepressants use and the development of cerebrovascular events, but there has never been any study investigating the risk of stroke in obsessive-compulsive disorder (OCD) patients treated with a selective serotonin reuptake inhibitor (SSRI).A retrospective observational cohort study was conducted using data from the National Health Insurance Database of Taiwan between the year of 2001 and 2009. A total of 527 OCD patients with 412 subjects in the SSRI use group and 115 in the non SSRI use group were included. Multivariable Cox proportional-hazards models were used to explore the associations between SSRI use and the occurrence of stroke, controlling for age, gender, concomitant medications, and comorbid medical illnesses.A total of nineteen OCD patients were diagnosed with new onset of stroke during the follow-up period including six cases in the SSRI group and thirteen in the non SSRI use group. SSRI use was demonstrated to be associated with a decreased risk of stroke (hazard ratio [HR] = 0.30; 95% confidence interval [CI] = 0.10-0.86, P = 0.02). The increase in age-related risk of strokes was 2.55 per decade (HR = 2.55; 95% CI = 1.74-3.75, P

Repetitive transcranial magnetic stimulation (rTMS) and intermittent theta-burst stimulation (iTBS) are evidenced-based treatments for patients with major depressive disorder (MDD) who fail to respond to standard first-line therapies. However, although various TMS protocols have been proven to be clinically effective, the response rate varies across clinical applications due to the heterogeneity of real-world psychiatric comorbidities, such as generalized anxiety disorder, posttraumatic stress disorder, panic disorder, or substance use disorder, which are often observed in patients with MDD. Therefore, individualized treatment approaches are important to increase treatment response by assigning a given patient to the most optimal TMS treatment protocol based on his or her individual profile. This literature review summarizes different rTMS or TBS protocols that have been applied in researches investigating MDD patients with certain psychiatric comorbidities and discusses biomarkers that may be used to predict rTMS treatment response. Furthermore, we highlight the need for the validation of neuroimaging and electrophysiological biomarkers associated with rTMS treatment responses. Finally, we discuss on which directions future efforts should focus for developing the personalization of the treatment of depression with rTMS or iTBS. [ABSTRACT FROM AUTHOR]

BACKGROUND: Asthma symptoms can interrupt daily activities, disturb sleep, and increase the risk of a child having an attention deficit or irritability, which also are symptoms of attention-deficit/hyperactivity disorder (ADHD). Previous studies have shown conflicting results regarding the association between ADHD and asthma. This study investigates the possible correlation between asthma and ADHD. METHODS: We retrieved data on 221,068 pediatric patients from Taiwan's National Health Insurance Research Database in 2005, and calculated the prevalence and risk factors of allergic diseases among ADHD patients. RESULTS: The prevalence of asthma in the ADHD group, compared with the control group, was 4.3 fold higher in the age 12 to 17 subgroup (95% Cl, 1.71 to 10.6), 1.5-fold higher in males (95% Cl, 1.05 to 2.03), and 1.6-fold higher for children living in urban areas (95% Cl, 1.12 to 2.28). Multivariate logistic regression models showed the odds ratio of asthma for children with ADHD was 1.43 (95% Cl, 1.05 to 1.95) as compared with children without ADHD. CONCLUSIONS: Pediatric ADHD was associated positively with asthma, but the underlying mechanisms require further clarification. [ABSTRACT FROM AUTHOR]

Background. Clostridium difficile is currently the leading cause of infectious diarrhea in hospitalized patients. In addition to the infection due to toxigenic C. difficile in the gastrointestinal tract of susceptible hosts, other predisposing factors for C. difficile infection (CDI) are identified, including advanced age, a prolonged hospital stay, and use of acidsuppressive drugs. Of note, exposure to gastric acid-reducing agents, such as H2 blockers and proton pump inhibitors (PPIs), remains a controversial risk factor, and has been associated with CDI in some studies but not in others. A mouse model of antibiotic-associated clostridial colitis was established to examine the role of PPIs for CDI. Materials and Methods. Amouse model of antibiotic-associated clostridial colitis was set up. NF-κB reportermice were used to address the in vivo spatial and temporal inflammatory patterns of C. difficile-associated colitis. Serum levels of lipopolysaccharide and dextran-FITC were measured to reflect the barrier permeability of affected intestines. Results. Mice with CDI that were exposed to PPI exhibited greater losses of stool consistency and body and cecal weights than those that were not exposed to PPI. Further, more neutrophilic infiltrations, epithelial damage, and inflammatory cytokine expression were noted in colon specimens of the mice with PPI exposure. More-evident inflammatory responses were detected by in vivo imaging of NF-κB reporter mice with CDI that were exposed to PPI. Gut barrier permeability was increased to a greater extent, as reflected by higher serum levels of lipopolysaccharide and dextran-FITC in mice with CDI that were exposed to PPI. Conclusions. Our mouse model demonstrates that PPI exposure increases the severity of intestinal inflammation in mice with C. difficile-associated colitis. [ABSTRACT FROM AUTHOR]

T cells can express multiple inhibitory receptors. Upon induction of T cell exhaustion in response to a persistent antigen, prominently in the anti-tumor immune response, many are expressed simultaneously. Key inhibitory receptors are CTLA-4, PD-1, LAG3, TIM3, and TIGIT, as investigated here. These receptors are important as central therapeutic targets in cancer immunotherapy. Inhibitory receptors are not constitutively expressed on the cell surface, but substantial fractions reside in intracellular vesicular structures. It remains unresolved to which extent the subcellular localization of different inhibitory receptors is distinct. Using quantitative imaging of subcellular distributions and plasma membrane insertion as complemented by proximity proteomics and biochemical analysis of the association of the inhibitory receptors with trafficking adaptors, the subcellular distributions of the five inhibitory receptors were discrete. The distribution of CTLA-4 was most distinct, with preferential association with lysosomal-derived vesicles and the sorting nexin 1/2/5/6 transport machinery. With a lack of evidence for the existence of specific vesicle subtypes to explain divergent inhibitory receptor distributions, we suggest that such distributions are driven by divergent trafficking through an overlapping joint set of vesicular structures. This extensive characterization of the subcellular localization of five inhibitory receptors in relation to each other lays the foundation for the molecular investigation of their trafficking and its therapeutic exploitation.