Evaluating the severity of depressive symptoms using upper body motion captured by RGB-depth sensors and machine learning in a clinical interview setting: A preliminary study.

BACKGROUND: Mood disorders have long been known to affect motor function. While methods to objectively assess such symptoms have been used in experiments, those same methods have not yet been applied in clinical practice because the methods are time-consuming, labor-intensive, or invasive. METHODS: We videotaped the upper body of each subject using a Red-Green-Blue-Depth (RGB-D) sensor during a clinical interview setting. We then examined the relationship between depressive symptoms and body motion by comparing the head motion of patients with major depressive disorders (MDD) and bipolar disorders (BD) to the motion of healthy controls (HC). Furthermore, we attempted to predict the severity of depressive symptoms by using machine learning. RESULTS: A total of 47 participants (HC, n = 16; MDD, n = 17; BD, n = 14) participated in the study, contributing to 144 data sets. It was found that patients with depression move significantly slower compared to HC in the 5th percentile and 50th percentile of motion speed. In addition, Hamilton Depression Rating Scale (HAMD)-17 scores correlated with 5th percentile, 50th percentile, and mean speed of motion. Moreover, using machine learning, the presence and/or severity of depressive symptoms based on HAMD-17 scores were distinguished by a kappa coefficient of 0.37 to 0.43. LIMITATIONS: Limitations include the small number of subjects, especially the number of severe cases and young people. CONCLUSIONS: The RGB-D sensor captured some differences in upper body motion between depressed patients and controls. If much larger samples are accumulated, machine learning may be useful in identifying objective measures for depression in the future.

Necessity for a Significant Maintenance Dosage Reduction of Voriconazole in Patients with Severe Liver Cirrhosis (Child-Pugh Class C).

Therapeutic drug monitoring for voriconazole, an antifungal agent, is essential for maximizing efficacy and preventing toxicity. The aim of this study was to elucidate the optimal maintenance dose of voriconazole in patients with severe liver cirrhosis (Child-Pugh class C) by reviewing the plasma trough concentrations obtained by therapeutic drug monitoring and daily doses of voriconazole. We retrospectively evaluated 6 patients with Child-Pugh class C cirrhosis who received oral voriconazole treatment and were liver transplant recipients or were awaiting liver transplantation. We compared their voriconazole trough concentrations and daily maintenance doses to those of patients who did not have liver cirrhosis (n=56). We found that plasma voriconazole trough concentrations in all patients with Child-Pugh class C were almost within therapeutic range, and the median plasma trough concentration at steady state was not significantly different from that of patients who did not have liver cirrhosis. In addition, the median daily maintenance dose of voriconazole was significantly lower (2.13 mg/kg/d) than that of the control patients (6.27 mg/kg/d), suggesting that trough voriconazole concentrations are elevated in Child-Pugh class C patients. Thus, we conclude that oral voriconazole maintenance doses in patients with Child-Pugh class C should be reduced to approximately one-third that of patients with normal liver function, with the follow-up dose adjusted by therapeutic drug monitoring.

Schedule-dependent cytotoxicity of Etoposide and cyclophosphamide in P-glycoprotein-expressing human leukemic K-562 cells.

Combination chemotherapy is often used to treat cancer. Many studies have shown schedule-dependent effects between anticancer drugs. Our previous studies showed that K-562 cells pretreated with non-cytotoxic concentrations of 4-hydroperoxycyclophosphamide (4-HPC), which is a preactivated analog of cyclophosphamide (CY), enhanced the cytotoxicity of etoposide (VP-16). The appearance of cellular resistance to anticancer drugs is a major problem in cancer chemotherapy. P-Glycoprotein (P-gp) plays an important role in drug resistance, and VP-16 is a substrate for this efflux pump. In the present study, we demonstrated schedule-dependent cytotoxicity of VP-16 and CY in P-gp-overexpressed K-562/P-gp cells. Cytotoxicity of VP-16 was enhanced in K-562/P-gp cells that were pretreated with a non-cytotoxic concentration of 4-HPC compared to that of cells not treated with 4-HPC. 4-HPC arrested the cell cycle at S phase. Cells in S phase are most sensitive to VP-16. The results suggest that cell cycle arrest by 4-HPC pretreatment may be responsible for the enhanced cytotoxicity of VP-16. The findings in this study should lead to improvements in clinical combination chemotherapy.

Therapeutic Drug Monitoring of Oral Voriconazole in an Infant Less than Six Months of Age and Pharmacokinetics Changes Induced by Development of CYP2C19 in the Growth Process: A Novel Case Report.

Therapeutic drug monitoring (TDM) is recommended for voriconazole (VRCZ) to avoid adverse events and maximize antifungal efficacy. Currently, the appropriate dose for patients under the age of 2 years is unknown. Here, we report the case of a 1.5-month-old infant with inborn errors of immunity who was orally administered VRCZ. This patient's plasma concentration decreased significantly from 3.8 µg/mL (day 6) to 0.09 µg/mL (day 21), leading to repeated dose escalations to achieve the target concentration (1.38 µg/mL, day 58). The signal intensity ratio of VRCZ to its main metabolite, N-oxide VRCZ, in LC/MS/MS also decreased from 5.30 (day 6) to 0.57 (day 64). Consequently, we suspected that VRCZ metabolism may be enhanced during infant growth. To our knowledge, this is the first report of remarkable changes in VRCZ pharmacokinetics with metabolic activity enhanced by the growth process. In conclusion, we propose that frequent TDM helped to maintain adequate VRCZ plasma concentration in a infants less than 6 months of age.

Schedule-dependent cytotoxicity of etoposide (VP-16) and cyclophosphamide in leukemia cell line K-562.

In allogeneic bone marrow transplantation (allo-BMT) in patients with leukemia, the combination of VP-16 and cyclophosphamide (CY) is commonly used for the conditioning regimen. In the present study, we demonstrated schedule-dependent cytotoxicity of VP-16 and CY in K-562 cells. K-562 cells were pretreated with low concentrations (2.5 and 5 µg/mL) of 4-hydroperoxycyclophosphamide (40487S), which is a preactivated analog of CY. It was confirmed that these concentrations did not influence cell viability. Cells subsequently exposed to 0.5-100 µg/mL of VP-16 showed reduced the viability compared to that of control cells not treated with 40487S. In contrast, there was no change in the viability of K-562 cells pretreated with low concentrations (0.5 and 1 µg/mL) of VP-16. It was confirmed that these concentrations did not influence cell viability. Viability of subsequently exposed to 1-20 µg/mL was not different from that of control cells not treated with VP-16. VP-16 caused cell cycle arrest at G2/M phase. On the other hand, 40487S arrested the cell cycle at S phase. Thymidine-synchronized cells, VP-16 showed cell cycle specificity for cell killing from early-S to mid-S phase. On the other hand, 40487S showed cell cycle-independent cytotoxicity. Exposure of cells to VP-16 after 40487S induced a greater cytotoxic effect on K-562 cells. The findings may lead to improvements in clinical combination chemotherapy.

Development of medical device software for the screening and assessment of depression severity using data collected from a wristband-type wearable device: SWIFT study protocol.

Introduction: Few biomarkers can be used clinically to diagnose and assess the severity of depression. However, a decrease in activity and sleep efficiency can be observed in depressed patients, and recent technological developments have made it possible to measure these changes. In addition, physiological changes, such as heart rate variability, can be used to distinguish depressed patients from normal persons; these parameters can be used to improve diagnostic accuracy. The proposed research will explore and construct machine learning models capable of detecting depressive episodes and assessing their severity using data collected from wristband-type wearable devices. Methods and analysis: Patients with depressive symptoms and healthy subjects will wear a wristband-type wearable device for 7 days; data on triaxial acceleration, pulse rate, skin temperature, and ultraviolet light will be collected. On the seventh day of wearing, the severity of depressive episodes will be assessed using Structured Clinical Interview for DSM-5 (SCID-5), Hamilton Depression Rating Scale (HAMD), and other scales. Data for up to five 7-day periods of device wearing will be collected from each subject. Using wearable device data associated with clinical symptoms as supervisory data, we will explore and build a machine learning model capable of identifying the presence or absence of depressive episodes and predicting the HAMD scores for an unknown data set. Discussion: Our machine learning model could improve the clinical diagnosis and management of depression through the use of a wearable medical device. Clinical trial registration: [https://jrct.niph.go.jp/latest-detail/jRCT1031210478], identifier [jRCT1031210478].

The project for objective measures using computational psychiatry technology (PROMPT): Rationale, design, and methodology.

INTRODUCTION: Depressive and neurocognitive disorders are debilitating conditions that account for the leading causes of years lived with disability worldwide. However, there are no biomarkers that are objective or easy-to-obtain in daily clinical practice, which leads to difficulties in assessing treatment response and developing new drugs. New technology allows quantification of features that clinicians perceive as reflective of disorder severity, such as facial expressions, phonic/speech information, body motion, daily activity, and sleep. METHODS: Major depressive disorder, bipolar disorder, and major and minor neurocognitive disorders as well as healthy controls are recruited for the study. A psychiatrist/psychologist conducts conversational 10-min interviews with participants ≤10 times within up to five years of follow-up. Interviews are recorded using RGB and infrared cameras, and an array microphone. As an option, participants are asked to wear wrist-band type devices during the observational period. Various software is used to process the raw video, voice, infrared, and wearable device data. A machine learning approach is used to predict the presence of symptoms, severity, and the improvement/deterioration of symptoms. DISCUSSION: The overall goal of this proposed study, the Project for Objective Measures Using Computational Psychiatry Technology (PROMPT), is to develop objective, noninvasive, and easy-to-use biomarkers for assessing the severity of depressive and neurocognitive disorders in the hopes of guiding decision-making in clinical settings as well as reducing the risk of clinical trial failure. Challenges may include the large variability of samples, which makes it difficult to extract the features that commonly reflect disorder severity. TRIAL REGISTRATION: UMIN000021396, University Hospital Medical Information Network (UMIN).

[Artificial Intelligence in Psychiatry].

Diagnosis of psychiatric disorders is based primarily on subjective symptoms, and neuroimaging or other biological examinations are used for excluding organic disorders. Advances in artificial intelligence technologies, such as machine learning, may enable us to utilize neuroimaging for individual diagnosis of psychiatric disorder or treatment response prediction. In addition, such technologies may elucidate the underlying pathophysiology of psychiatric disorders. In this article, we review studies that utilized machine learning on structural magnetic resonance imaging for depression.

[Possibility of Poor Outcomes after Treatment Using Teicoplanin at the Minimum Inhibitory Concentration of >2 µg/mL in Methicillin-resistant Staphylococcus aureus Bacteremia].

　Only minimal information exists regarding the treatment outcomes of patients suffering from methicillin-resistant Staphylococcus aureus (MRSA) bacteremia treated with teicoplanin (TEIC) when the TEIC minimum inhibitory concentration (MIC) is close to the upper limit of the "susceptibility range" according to the Clinical Laboratory Standards Institute (CLSI). We investigated the outcome of TEIC-treated patients in MRSA bacteremia, focusing on TEIC MIC against MRSA. A retrospective cohort study was conducted on patients with MRSA bacteremia. TEIC treatment failure was defined as any of the following: (1) all-cause 60-day mortality, (2) persistent bacteremia until the end of TEIC treatment, or (3) 30-day recurrence of MRSA bacteremia. Nineteen patients were enrolled, of whom 15 exhibited TEIC MICs ≤2 µg/mL and the remaining 4 exhibited >2 µg/mL. The rate of treatment failure and all-cause 60-day mortality in patients with MIC >2 µg/mL were significantly higher than those in patients with MIC ≤2 µg/mL [4 patients (100%) versus 4 patients (26.7%) (p=0.018) and 4 patients (100%) versus 2 patients (13.3%) (p=0.004), respectively]. Three of four patients (75%) with MIC >2 µg/mL had persistent bacteremia, which was quantitatively higher than in patients with MIC ≤2 µg/mL (1 of 7 patients, 14.3%). Our finding suggests that TEIC MIC >2 µg/mL may be related to poor treatment outcome in MRSA bacteremia, and that TEIC should not be used in this case.

[Evaluation of the Stability of Indomethacin Oral Spray in Two Different Formulation Conditions].

　Indomethacin (IM) oral spray is a hospital preparation that is used to reduce pain from oral mucositis induced by radiotherapy and chemotherapy. IM oral spray consists of IM (0.25%) dissolved in KH2PO4-NaOH buffer (Formulation A) or Formulation A containing xylitol (Xyl) and glycerin (Gly) (Formulation B). To clarify the stability of IM oral spray in two different formulation conditions, we evaluated the residual rates of IM in these formulations to determine the optimal storage temperature and shelf-life. IM oral spray was stored at freezer temperature (-20°C), refrigerator temperature (4°C) and room temperature (25°C) for up to 16 weeks after preparation. The residual rate of IM was determined by using HPLC. The residual rates of IM in Formulation A and Formulation B after storage for 16 weeks at freezer temperature were ≥95%. When stored at refrigerator temperature, the residual rate of IM in Formulation A was 96.1% after 12 weeks, and the residual rates of IM in Formulation B were 95.8% after 2 weeks, 90.1% after 4 weeks and 72.7% after 12 weeks. These results suggested that Formulation A is stable for at least 12 weeks when stored at 4°C. However, degradation of IM seemed to be accelerated in the formulation containing Xyl and Gly, suggesting that the expiration date should be shortened to 2 weeks at 4°C. In addition, both formulations were stable for at least 16 weeks in a freezer, indicating that long-term preservation is possible.

Pharmacokinetics and dose adjustment of etoposide administered in a medium-dose etoposide, cyclophosphamide and total body irradiation regimen before allogeneic hematopoietic stem cell transplantation.

BACKGROUND: We investigated the pharmacokinetics of etoposide (ETP) to reduce the inter-individual variations of ETP concentrations in patients with acute leukemia who underwent allogeneic hematopoietic stem cell transplantation. We also carried out an in vivo study using rats to verify the dose adjustment. METHODS: This study included 20 adult patients. ETP was administered intravenously at a dose of 15 mg/kg once daily for 2 days (total dose: 30 mg/kg) combined with standard conditioning of cyclophosphamide and total body irradiation. In an in vivo study using rats, ETP was administered intravenously at a dose of 15 mg/kg or an adjusted dose. The ETP plasma concentration was determined by using HPLC. The pharmacokinetic parameters were estimated by using a 1-compartment model. RESULTS: The peak concentration (Cmax) of ETP and the area under the plasma concentration-time curve (AUC) of ETP differed greatly among patients (range of Cmax, 51.8 - 116.5 µg/mL; range of AUC, 870 - 2015 µg · h/mL). A significant relationship was found between Cmax and AUC (R = 0.85, P < 0.05). Distribution volume (Vd) was suggested to be one of the factors of inter-individual variation in plasma concentration of ETP in patients (range of Vd, 0.13 - 0.27 L/kg), and correlated with Alb and body weight (R = 0.56, P < 0.05; R = 0.40, P < 0.05 respectively). We predicted Vd of rats by body weight of rats (with normal albumin levels and renal function), and the dose of ETP was adjusted using predicted Vd. In the dose adjustment group, the target plasma ETP concentration was achieved and the variation of plasma ETP concentration was decreased. CONCLUSION: The results suggested that inter-individual variation of plasma concentration of ETP could be reduced by predicting Vd. Prediction of Vd is effective for reducing individual variation of ETP concentration and might enable a good therapeutic effect to be achieved.