Improving Depression Severity Prediction from Passive Sensing: Symptom-Profiling Approach

Depression is a significant mental health issue that profoundly impacts people's lives. Diagnosing depression often involves interviews with mental health professionals and surveys, which can become cumbersome when administered continuously. Digital phenotyping offers an innovative approach for detecting and monitoring depression without requiring active user involvement. This study contributes to the detection of depression severity and depressive symptoms using mobile devices. Our proposed approach aims to distinguish between different patterns of depression and improve prediction accuracy. We conducted an experiment involving 381 participants over a period of at least three months, during which we collected comprehensive passive sensor data and Patient Health Questionnaire (PHQ-9) self-reports. To enhance the accuracy of predicting depression severity levels (classified as none/mild, moderate, or severe), we introduce a novel approach called symptom profiling. The symptom profile vector represents nine depressive symptoms and indicates both the probability of each symptom being present and its significance for an individual. We evaluated the effectiveness of the symptom-profiling method by comparing the F1 score achieved using sensor data features as inputs to machine learning models with the F1 score obtained using the symptom profile vectors as inputs. Our findings demonstrate that symptom profiling improves the F1 score by up to 0.09, with an average improvement of 0.05, resulting in a depression severity prediction with an F1 score as high as 0.86.

G-Quadruplex-Filtered Selective Ion-to-Ion Current Amplification for Non-Invasive Ion Monitoring in Real Time

Living cells efflux intracellular ions for maintaining cellular life, so intravital measurements of specific ion signals are of significant importance for studying cellular functions and pharmacokinetics. In this work, de novo synthesis of artificial K+ -selective membrane and its integration with polyelectrolyte hydrogel-based open-junction ionic diode (OJID) is demonstrated, achieving a real-time K+ -selective ion-to-ion current amplification in complex bioenvironments. By mimicking biological K+ channels and nerve impulse transmitters, in-line K+ -binding G-quartets are introduced across freestanding lipid bilayers by G-specific hexylation of monolithic G-quadruplex, and the pre-filtered K+ flow is directly converted to amplified ionic currents by the OJID with a fast response time at 100 ms intervals. By the synergistic combination of charge repulsion, sieving, and ion recognition, the synthetic membrane allows K+ transport exclusively without water leakage; it is 250× and 17× more permeable toward K+ than monovalent anion, Cl- , and polyatomic cation, N-methyl-d-glucamine+ , respectively. The molecular recognition-mediated ion channeling provides a 500% larger signal for K+ as compared to Li+ (0.6× smaller than K+ ) despite the same valence. Using the miniaturized device, non-invasive, direct, and real-time K+ efflux monitoring from living cell spheroids is achieved with minimal crosstalk, specifically in identifying osmotic shock-induced necrosis and drug-antidote dynamics.

Enhancing the Plasma-Resistance Properties of Li2O-Al2O3-SiO2 Glasses for the Semiconductor Etch Process via Alkaline Earth Oxide Incorporation

To develop plasma-resistant glass materials suitable for semiconductor etching processes, we introduced alkaline earth oxides (ROs) into a Li₂O-Al₂O₃-SiO₂ (LAS) glass. Analysis of glass properties with respect to the additives revealed that among the analyzed materials, the LAS material in which Li₂O was partially replaced by MgO (MLAS) exhibited the most favorable characteristics, including a low dielectric constant (6.3) and thermal expansion coefficient (2.302 × 10^-6/°C). The high performance of MLAS is attributed to the high ionic field strength of Mg²⁺ ions, which restricts the movement of Li⁺ ions under the influence of electric fields and thermal vibrations at elevated temperatures. When exposed to CF₄/O₂/Ar plasma, the etching speed of RO-doped glasses decreased compared with that of quartz and LAS glass, primarily owing to the generation of a high-sublimation-point fluoride layer on the surface. Herein, MLAS demonstrated the slowest etching speed, indicating exceptional plasma resistance. X-ray photoelectron spectroscopy analysis conducted immediately after plasma etching revealed that the oxidation-to-fluorination ratio of Li was the lowest for MLAS. This observation suggests that the presence of Mg²⁺ ions in the plasma discharge inhibits the migration of Li⁺ ions toward the surface, thereby contributing to the excellent plasma resistance of MLAS.