Search

To understand the dynamics of a living system, the analysis of particular and/or cellular dynamics has been performed based on shape-based center point detection. After collecting sequential time-lapse images of cellular dynamics, the trajectory of a moving object is determined from the set of center points of the cell analyzed from each image. The accuracy of trajectory is significant in understanding the stochastic nature of the dynamics of biological objects. In this study, to localize a cellular object in time-lapse images, three different localization methods, namely radial symmetry, circular Hough transform, and modified active contour, were considered. To analyze the accuracy of cellular dynamics, several statistical parameters such as mean square displacement and velocity autocorrelation function were employed, and localization error derived from these was reported for each localization method. In particular, through denoising using a Poisson noise filter, improved localization characteristics could be achieved. The modified active contour with denoising reduced localization error significantly, and thus allowed for accurate estimation of the statistical parameters of cellular dynamics.

BackgroundAssessing the complex and multifaceted symptoms of patients with acute psychiatric disorders proves to be significantly challenging for clinicians. Moreover, the staff in acute psychiatric wards face high work intensity and risk of burnout, yet research on the introduction of digital technologies in this field remains limited. The combination of continuous and objective wearable sensor data acquired from patients with deep learning techniques holds the potential to overcome the limitations of traditional psychiatric assessments and support clinical decision-making. ObjectiveThis study aimed to develop and validate wearable-based deep learning models to comprehensively predict patient symptoms across various acute psychiatric wards in South Korea. MethodsParticipants diagnosed with schizophrenia and mood disorders were recruited from 4 wards across 3 hospitals and prospectively observed using wrist-worn wearable devices during their admission period. Trained raters conducted periodic clinical assessments using the Brief Psychiatric Rating Scale, Hamilton Anxiety Rating Scale, Montgomery-Asberg Depression Rating Scale, and Young Mania Rating Scale. Wearable devices collected patients’ heart rate, accelerometer, and location data. Deep learning models were developed to predict psychiatric symptoms using 2 distinct approaches: single symptoms individually (Single) and multiple symptoms simultaneously via multitask learning (Multi). These models further addressed 2 problems: within-subject relative changes (Deterioration) and between-subject absolute severity (Score). Four configurations were consequently developed for each scale: Single-Deterioration, Single-Score, Multi-Deterioration, and Multi-Score. Data of participants recruited before May 1, 2024, underwent cross-validation, and the resulting fine-tuned models were then externally validated using data from the remaining participants. ResultsOf the 244 enrolled participants, 191 (78.3%; 3954 person-days) were included in the final analysis after applying the exclusion criteria. The demographic and clinical characteristics of participants, as well as the distribution of sensor data, showed considerable variations across wards and hospitals. Data of 139 participants were used for cross-validation, while data of 52 participants were used for external validation. The Single-Deterioration and Multi-Deterioration models achieved similar overall accuracy values of 0.75 in cross-validation and 0.73 in external validation. The Single-Score and Multi-Score models attained overall R² values of 0.78 and 0.83 in cross-validation and 0.66 and 0.74 in external validation, respectively, with the Multi-Score model demonstrating superior performance. ConclusionsDeep learning models based on wearable sensor data effectively classified symptom deterioration and predicted symptom severity in participants in acute psychiatric wards. Despite lower computational costs, Multi models demonstrated equivalent or superior performance than Single models, suggesting that multitask learning is a promising approach for comprehensive symptom prediction. However, significant variations were observed across wards, which presents a key challenge for developing clinical decision support systems in acute psychiatric wards. Future studies may benefit from recurring local validation or federated learning to address generalizability issues.

Abstract Entangled coherent states play pivotal roles in various fields such as quantum computation, quantum communication, and quantum sensing. We experimentally demonstrate the generation of entangled coherent states with the two-dimensional motion of a trapped ion system. Using Raman transitions with appropriate detunings, we simultaneously drive the red and blue sidebands of the two transverse axes of a single trapped ion and observe multi-periodic entanglement and disentanglement of its spin and two-dimensional motion. Then, by measuring the spin state, we herald entangled coherent states of the transverse motions of the trapped ion and observe the corresponding modulation in the parity of the phonon distribution of one of the harmonic oscillators. Lastly, we trap two ions in a linear chain and realize Mølmer–Sørensen gate using two-dimensional motion.

Site-specific integration has emerged as a promising strategy for streamlined and predictable Chinese hamster ovary (CHO) cell line development (CLD). However, the low specific productivity of the targeted integrants limits their practical application. In this study, we developed a hybrid CLD platform combining site-specific integration of a transgene and dihydrofolate reductase/methotrexate (DHFR/MTX)-mediated gene amplification to generate high-producing recombinant CHO cell lines. We used the CRISPR/Cas9-based recombinase-mediated cassette exchange landing pad platform to integrate the DHFR expression cassette and transgene landing pad into a CHO genomic hot spot, C12orf35 locus, of DHFR-knockout CHO-K1 host cell lines. When subjected to various MTX concentrations up to 1 μM, EGFP-expressing targeted integrants showed a 3.6-fold increase in EGFP expression in the presence of 200 nM MTX, accompanied by an increase in the DHFR and EGFP copy number. A single-step 200 nM MTX amplification increased the specific monoclonal antibody (mAb) productivity (qmAb) of recombinant mAb-producing targeted integrants by 2.8-folds, reaching a qmAb of 9.1–11.0 pg/cell/day. Fluorescence in situ hybridization analysis showed colocalization of DHFR and mAb sequences at the intended chromosomal locations without clear amplified arrays of signals. Most MTX-amplified targeted integrants sustained recombinant mAb production during long-term culture in the absence of MTX, supporting stable gene expression in the amplified cell lines. Our study provides a new CLD platform that increases the productivity of targeted integrants by amplifying the transgene copies.

To enable the large-area manufacture of solution-processed organic electronics, direct photocrosslinking processes has emerged as a promising technology solution. Here, the authors report an efficient universal crosslinking agent for micropatterning of stacked multi-layered organic electronics.

An active vibration-isolation system (AVIS) utilizes a geophone sensor, a type of velocity sensor, to control microvibration. The structure of the sensor is modeled by mass, damper, and spring. The mathematical model of the geophone sensor is a second-order model with a resonant frequency. However, at low-band frequencies, the response characteristic is nonlinear and phase delay occurs. Compared with the ideal velocity signals of the system, the velocity signals measured from the geophone sensor were distorted in low-band frequencies. Consequently, this measurement issue in feedback control loops can affect the stability and performance of the AVIS. This paper proposes design rules for a state-variable filter (SVF) that can compensate for the nonlinearity of the geophone sensors in low-band frequencies and evaluates vibration attenuation performance of the AVIS by applying the proposed SVF. To evaluate the effectiveness of the filter in compensating for the nonlinear response of the geophone sensor, we compared Bode plots generated through simulation and experimental results obtained using a dynamic signal analyzer. The experimental results demonstrated that the proposed SVF effectively reduces the resonance peak of the geophone sensor and expands the frequency bands that maintain a constant magnitude in range of 0.8–10 Hz. By applying the geophone sensor with SVF to AVIS, the microvibration attenuation improved to − 18.4 dB near 4.5 Hz. [ABSTRACT FROM AUTHOR]

Research Summary: Limited liability enables corporate parents to avoid financial responsibility of their subsidiaries. However, courts can disregard separate legal personality, "pierce the corporate veil," and impose the debts of a subsidiary on its parent—an exception referred to as "enterprise liability." We argue that in countries with weak enterprise liability, groups can better compartmentalize risks by incorporating more of their units as legally independent subsidiaries. Weaker enterprise liability may also induce headquarters to delegate more decision‐making authority to their subsidiaries, invest more, and expand faster, although failure rates could rise. Using data from 16 countries across the Americas, Asia, and Europe, we provide evidence supporting these predictions. This paper highlights two channels—risk compartmentalization and subsidiary autonomy—through which limited liability laws affect organizational outcomes. Managerial Summary: Limited liability is a key attribute of the corporate form. However, when the owner of a corporation is another corporation (as in corporate groups), a key justification for limited liability—to protect small, passive investors from unlimited losses—is severely weakened. We examine how variation in parent limited liability protections for subsidiaries across countries affect firm boundaries, internal organization, and performance. In countries with strong limited liability protections, groups partition their assets more finely into legally independent subsidiaries and grant their subsidiaries more autonomy. They also invest more and grow faster, although they experience higher rates of significant revenue declines. Our findings suggest that limited liability laws play a central role in shaping organizational structure and performance. [ABSTRACT FROM AUTHOR]

Mild hypothermia has been widely used to enhance transgene expression and improve the cellular productivity of mammalian cells. This study investigated mild hypothermia-responsive exogenous promoters in human embryonic kidney 293 (HEK293) cells using site-specific integration of various promoter sequences, including CMV, EF1α, SV40, and TK promoters, into the well-known genomic safe harbor site, AAVS1. EGFP expression driven by the CMV promoter increased up to 1.5-fold at 32 °C versus 37 °C under stable expression, while others showed no hypothermic response. Integration of short CMV variants revealed that the CMV-enhancer region is responsible for the positive hypothermic response. CMV-enhancer-specific transcription factors (TFs) were then predicted through in silico analysis and RNA-sequencing analysis, resulting in the selection of one TF, NKX3-1. At 37 °C, overexpression of NKX3-1 in recombinant HEK293 cells expressing EGFP through the CMV promoter (CMV-EGFP) increased EGFP expression up to 1.6-fold, compared with that in CMV-EGFP, the expression level of which was comparable to that of CMV-EGFP at 32 °C. Taken together, this work demonstrates promoter-dependent hypothermia responses in HEK293 cells and emphasizes interactions between endogenous TFs and promoter sequences.

Conventional louver fins have an inherent problem of condensate drainage. In this study, a newly developed louver fin is introduced. The louver fin has downstream a drainage channel. The dry and the wet surface heat transfer and pressure drop characteristics of the new sample were investigated, and the results were compared with those of the conventional sample. Compared to the conventional sample, superior wet surface heat transfer and pressure drop characteristics were obtained. The j factors of the new sample were 40% larger, and the f factors were 9% smaller. In addition, the wet j and f factors were not much different from the dry ones, which imply that excellent condensate drainage is possible for the new fin. Under dry condition, however, poor heat transfer and pressure drop characteristics were obtained. The j factors of the conventional sample were 81% larger, and the f factors were 14% smaller. Allocation of the fin surface to flat (not enhanced) drainage channel for the new fin may be responsible. Under wet condition, j/f1/3 of the new sample was 45% larger than that of the conventional sample. Under dry condition, however, j/f1/3 of the conventional sample was 91% larger.