Predicting rapid decline in kidney function among type 2 diabetes patients: A machine learning approach.

Background: Diabetic kidney disease (DKD) is one of the typical complications of type 2 diabetes (T2D), with approximately 10 % of DKD patients experiencing a Rapid decline (RD) in kidney function. RD leads to an increased risk of poor outcomes such as the need for dialysis. Albuminuria is a known kidney damage biomarker for DKD, yet RD cases do not always show changes in albuminuria, and the exact mechanism of RD remains unclear.

Using One-Shot Prompting of Non-Fine-Tuned Commercial Artificial Intelligence to Assess Nutrients from Photographs of Japanese Meals.

Background: Diet interventions often have poor adherence due to burdensome food logging. Approaches using photographs assessed by artificial intelligence (AI) may make food logging easier, if they are adequately accurate.

Method: We used OpenAI's GPT-4o model with one-shot prompts and no fine-tuning to assess energy, fat, protein, carbohydrate, fiber, and salt through photographs of 22 meals, comparing assessments to weighed food records for each meal and to assessments of dieticians.

Validation of Sleep Measurements of an Actigraphy Watch: Instrument Validation Study.

Background: The iAide2 (Tokai) physical activity monitoring system includes diverse measurements and wireless features useful to researchers. The iAide2's sleep measurement capabilities have not been compared to validated sleep measurement standards in any published work.

Objective: We aimed to assess the iAide2's sleep duration and total sleep time (TST) measurement performance and perform calibration if needed.

Use of Upadacitinib to Treat a Severe Flare-Up of Rheumatoid Arthritis During Anti-PD-1 Immune Checkpoint Inhibitor Therapy for Stage IV Squamous Cell Carcinoma of the Lung.

Immune checkpoint inhibitor (ICI) therapy is becoming the standard of care for the treatment of advanced non-small-cell lung cancer. However, T-cell activation by ICIs frequently induces a flare-up of preexisting autoimmune diseases such as rheumatoid arthritis (RA). Janus kinase (JAK) inhibitors are increasingly used in the treatment of RA, but they could interfere with the efficacy of ICIs by inhibiting interferon signaling.

Efficacy of Save Medical Corporation (SMC)-01, a Smartphone App Designed to Support Type 2 Diabetes Self-Management Based on Established Guidelines: Randomized Controlled Trial.

Background: Lifestyle modifications are a key part of type 2 diabetes mellitus treatment. Many patients find long-term self-management difficult, and mobile apps could be a solution. In 2010, in the United States, a mobile app was approved as an official medical device.

A Comparative Study of Access Analysis Service Utilization on Japanese Medical Institutions' Websites with GDPR-Compliant Cases.

The browsing history of a medical institution's website can potentially reveal or identify information about the health condition of the website visitor through browser cookies and fingerprints. In Japan, although the Personal Information Protection Law was revised in April 2022, the use of access analysis services to collect browsing history on medical institution websites has not been investigated. Therefore, this study investigates the actual usage of access analysis services on Japanese medical institution websites and compares it with the current situation in France, which follows the General Data Protection Regulation.

HeXEHRS: FHIR-Based Cloud EHR Services to Support Healthcare in Depopulated Areas Driven by Digital Twin.

HeXEHRS is a FHIR-based cloud EHR service designed to support healthcare in depopulated areas, powered by digital twin technology. Its core functionalities encompass standard EHR tasks including data exchange for healthcare processes. In the first year of this national project, we present the design and define the functionalities of the system.

Enhancing Type 2 Diabetes Treatment Decisions With Interpretable Machine Learning Models for Predicting Hemoglobin A1c Changes: Machine Learning Model Development.

Background: Type 2 diabetes (T2D) is a significant global health challenge. Physicians need to assess whether future glycemic control will be poor on the current trajectory of usual care and usual-care treatment intensifications so that they can consider taking extra treatment measures to prevent poor outcomes. Predicting poor glycemic control from trends in hemoglobin A (HbA) levels is difficult due to the influence of seasonal fluctuations and other factors.

Dual-responsive near-infrared turn-on fluorescent probe for cancer stem cell-specific visualization.

Aldehyde dehydrogenase 1A1 (ALDH1A1) stands out as one of the most reliable intracellular biomarkers for stem cells because it is expressed in both cancer stem cells (CSCs) and normal somatic stem cells (NSCs). Although several turn-on fluorescent probes for ALDH1A1 have been developed to visualize CSCs in cancer cells, the discrimination of CSCs from NSCs is difficult. We here report an AND-type dual-responsive fluorescent probe, CHO_βgal, the near-infrared fluorescence of which can be turned on after responding to both ALDH1A1 and β-galactosidase.

Divergent effects of chronic continuous and intermittent social defeat stress on emotional behaviors: Impact on phosphorylated CREB and BDNF protein levels in the rat hippocampus.

Chronic psychosocial stress stands as a significant heterogeneous risk factor for psychiatric disorders. The brain's physiological response to such stress varies based on the frequency and intensity of stress episodes. However, whether stress episodes divergently could affect hippocampal cyclic AMP response element-binding protein (CREB)-brain-derived neurotrophic factor (BDNF) signaling remains unclear, a key regulator of psychiatric symptoms.

AIE-ESIPT Photoluminescent Probe Based on 3-(3-Hydroxypyridin-2-yl)isoquinolin-4-ol for the Detection of Intracellular Hydrogen Peroxide.

Excited-state intramolecular proton transfer (ESIPT) molecules, which feature large Stokes shifts to avoid self-absorption, play an essential role in photoluminescent bioimaging probes. Herein, we report the development of an ESIPT molecule 3-(3-hydroxypyridin-2-yl)isoquinolin-4-ol (PiQ). PiQ not only undergoes a distinct ESIPT process unlike the symmetrical 2,2'-bipyridyl-3,3'-diol but also exhibits aggregation-induced emission (AIE) characteristics.

Effectiveness of DialBetesPlus, a self-management support system for diabetic kidney disease: Randomized controlled trial.

We evaluated the effectiveness of a mobile health (mHealth) intervention for diabetic kidney disease patients by conducting a 12-month randomized controlled trial among 126 type 2 diabetes mellitus patients with moderately increased albuminuria (urinary albumin-to-creatinine ratio (UACR): 30-299 mg/g creatinine) recruited from eight clinical sites in Japan. Using a Theory of Planned Behavior (TPB) behavior change theory framework, the intervention provides patients detailed information in order to improve patient control over exercise and dietary behaviors. In addition to standard care, the intervention group received DialBetesPlus, a self-management support system allowing patients to monitor exercise, blood glucose, diet, blood pressure, and body weight via a smartphone application.

Sleep rebound leads to marked recovery of prolonged sleep deprivation-induced adversities in the stress response and hippocampal neuroplasticity of male rats.

Background: Sleep disturbances are not only frequent symptoms, but also risk factors for major depressive disorder. We previously reported that depressed patients who experienced "Hypersomnia" showed a higher and more rapid response rate under paroxetine treatment, but the underlying mechanism remains unclear. The present study was conducted to clarify the beneficial effects of sleep rebound through an experimental "Hypersomnia" rat model on glucocorticoid and hippocampal neuroplasticity associated with antidepressive potency.

Light-controllable cell-membrane disturbance for intracellular delivery.

Highly polar and charged molecules, such as oligonucleotides, face significant barriers in crossing the cell membrane to access the cytoplasm. To address this problem, we developed a light-triggered twistable tetraphenylethene (TPE) derivative, TPE-C-N, to facilitate the intracellular delivery of charged molecules through an endocytosis-independent pathway. The central double bond of TPE in TPE-C-N is planar in the ground state but becomes twisted in the excited state.

Efficacy of StepAdd, a Personalized mHealth Intervention Based on Social Cognitive Theory to Increase Physical Activity Among Patients With Type 2 Diabetes Mellitus: Protocol for a Randomized Controlled Trial.

Background: Increasing physical activity improves glycemic control in patients with type 2 diabetes (T2D). Mobile health (mHealth) interventions have been proven to increase exercise, but engagement often fades with time. As the use of health behavior theory in mHealth design can increase effectiveness, we developed StepAdd, an mHealth intervention based on the constructs of social cognitive theory (SCT).

Chirality-Induced Selectivity of Phonon Angular Momenta in Chiral Quartz Crystals.

A generation, propagation, and transfer of phonon angular momenta are examined on thermal transport in chiral insulative and diamagnetic crystals of α-quartz. We found that thermally driven phonons carry chirality-dependent angular momenta in the quartz crystals and they could be extracted from the quartz as a spin signal. Namely, chirality-induced selectivity of phonon angular momenta is realized in the chiral quartz.

Designing Medication-Related Profiles for Japanese ePrescriptions with HL7 FHIR.

HL7 FHIR is the standard for healthcare information exchange. In November 2022, our medication subgroup developed 8 profiles and 23 extensions for medication procedures in Japan, as part of the JP Core Implementation Guide 1.1.

Graph Representation Learning-Based Fixed-Length Clinical Feature Vector Generation from Heterogeneous Medical Records.

Transformation of patient data extracted from a database into fixed-length numerical vectors requires expertise in topical medical knowledge as well as data manipulation-thus, manual feature design is labor-intensive. In this study, we propose a machine learning-based method to for this purpose applicable to electronic medical data recorded during hospitalization, which utilizes unsupervised feature extraction based on graph embedding. Unsupervised learning is performed on a heterogeneous graph using Graph2Vec, and the inclusion of clinically useful data in the obtained embedding representation is evaluated by predicting readmission within 30 days of discharge based on it.

Effect of Step Count Measurement on Glycemic Control: Secondary Analysis of a Randomized Controlled Trial.

Although walking has proven efficacy for glycemic control, patients struggle to meet daily step goals. This secondary analysis investigated the effect of step count measurement rate on glycemic control. Patients with type 2 diabetes from eight hospitals in Japan participated in a 12-month randomized controlled trial.

Providing Practical Knowledge and Skills to Handle Real-World Data? Lessons Learned from Med RWD Program.

Both lectures and hands-on education are essential for the development of human resources that can use real-world data (RWD). The University of Tokyo has launched a new hybrid-style RWD educational program entitled "Medical Real World Data Utilization Human Resource Development Project" from FY2019 onwards. We present an overview of the overall picture of the project, including the development process of the educational program and the challenges associated with it.

A reductively convertible nickel phthalocyanine precursor as a biological thiol-responsive turn-on photoacoustic contrast agent.

A nickel phthalocyanine precursor bearing poly(ethylene glycol) as a turn-on contrast agent for photoacoustic imaging was prepared. The water-soluble polymeric chains were smoothly eliminated through thiol-mediated reductive aromatization in cancer cells, enabling the detection of endogenous biological thiols and .

Clinical Feature Vector Generation using Unsupervised Graph Representation Learning from Heterogeneous Medical Records.

The diversity of patient information recorded on electronic medical records generally, presents a challenge for converting it into fixed-length vectors that align with clinical characteristics. To address this issue, this study aimed to utilize an unsupervised graph representation learning method to transform the unstructured inpatient information from electronic medical records into a fixed-length vector. Infograph, one of the unsupervised graph representation learning algorithms was applied to the graphed inpatient information, resulting in embedded vectors of fixed length.