Towards expert-level autonomous carotid ultrasonography with large-scale learning-based robotic system.

Carotid ultrasound requires skilled operators due to small vessel dimensions and high anatomical variability, exacerbating sonographer shortages and diagnostic inconsistencies. Prior automation attempts, including rule-based approaches with manual heuristics and reinforcement learning trained in simulated environments, demonstrate limited generalizability and fail to complete real-world clinical workflows. Here, we present UltraBot, a fully learning-based autonomous carotid ultrasound robot, achieving human-expert-level performance through four innovations: (1) A unified imitation learning framework for acquiring anatomical knowledge and scanning operational skills; (2) A large-scale expert demonstration dataset (247,000 samples, 100 × scale-up), enabling embodied foundation models with strong generalization; (3) A comprehensive scanning protocol ensuring full anatomical coverage for biometric measurement and plaque screening; (4) The clinical-oriented validation showing over 90% success rates, expert-level accuracy, up to 5.

Microwave-Assisted Synthesis of Heterocycles via Rhodium(III)-Catalyzed C-H Activation: Norbornadiene as an Acetylene Equivalent.

General procedures for the rhodium-catalyzed annulation of aryl/heteroaryl -pivaloyl hydroxamic acids and norbornadiene have been developed. Employing norbornadiene as an acetylene equivalent enables utilization of diverse heterocyclic substrates for this transformation which fail to react or undergo competitive Lossen rearrangement under previously reported conditions. Microwave heating significantly reduces reaction times compared to conventional protocols and allows a one-step process to be realized.

Chinese Immigrant Caregivers: Understanding Their Unmet Needs and the Co-Design of an mHealth App.

Background: Immigrant caregivers support the aging population, yet their own needs are often neglected. Mobile technology-facilitated interventions can promote caregiver health by providing easy access to self-care materials.

Objective: This study employed a design thinking framework to examine Chinese immigrant caregivers' (CICs) unmet self-care needs and co-design an app for promoting self-care with CICs.

Association between residential environment and emotional wellbeing among older adults in China: the mediating effect of health lifestyle.

Introduction: The association between the residential environment and emotional wellbeing (EWB) in older adults has received extensive attention from gerontologists, especially during the COVID-19 pandemic; however, the mediating mechanism of how residential environment affects emotional wellbeing has not been fully explored. This study examined the effects of the residential environment on EWB and the mediating role of health lifestyle.

Methods: This study analyzed the survey data of 493 rural and 515 urban older adults from 2021 Chinese General Social Survey.

Construction and Verification of Predictive Model for Influencing Factors of Quality of Life in Patients with Type 2 Diabetic Nephropathy: A Hospital-Based Retrospective Study.

Objective: The influencing factors of quality of life (QOL) in patients with type 2 diabetic nephropathy (T2DN) were explored, a practical risk prediction model was constructed and independent verification was conducted.

Methods: The clinical data of 273 patients with T2DN in Tai'an Maternal and Child Health Care Center from February 2021 to February 2023 were used for retrospective analysis, and the patients were divided into modelling group (n = 173) and validation group (n = 100). According to 36-item short form health survey (SF-36) scores, the research subjects in the modelling group were divided further into poor group (n = 78) and good group (n = 95).

Glance and Focus Networks for Dynamic Visual Recognition.

Spatial redundancy widely exists in visual recognition tasks, i.e., discriminative features in an image or video frame usually correspond to only a subset of pixels, while the remaining regions are irrelevant to the task at hand.

Spatially Adaptive Feature Refinement for Efficient Inference.

Spatial redundancy commonly exists in the learned representations of convolutional neural networks (CNNs), leading to unnecessary computation on high-resolution features. In this paper, we propose a novel Spatially Adaptive feature Refinement (SAR) approach to reduce such superfluous computation. It performs efficient inference by adaptively fusing information from two branches: one conducts standard convolution on input features at a lower spatial resolution, and the other one selectively refines a set of regions at the original resolution.

Detecting Coal Pulverizing System Anomaly Using a Gated Recurrent Unit and Clustering.

The coal pulverizing system is an important auxiliary system in thermal power generation systems. The working condition of a coal pulverizing system may directly affect the safety and economy of power generation. Prognostics and health management is an effective approach to ensure the reliability of coal pulverizing systems.

Noninvasive prenatal paternity testing by maternal plasma DNA sequencing in twin pregnancies.

SNPs, combined with massively parallel sequencing technology, have proven applicability in noninvasive prenatal paternity testing (NIPPT) for singleton pregnancies in our previous research, using circulating cell-free DNA in maternal plasma. However, the feasibility of NIPPT in twin pregnancies has remained uncertain. As a pilot study, we developed a practical method to noninvasively determine the paternity of twin pregnancies by maternal plasma DNA sequencing based on a massively parallel sequencing platform.

An Advanced Model to Precisely Estimate the Cell-Free Fetal DNA Concentration in Maternal Plasma.

Background: With the speedy development of sequencing technologies, noninvasive prenatal testing (NIPT) has been widely applied in clinical practice for testing for fetal aneuploidy. The cell-free fetal DNA (cffDNA) concentration in maternal plasma is the most critical parameter for this technology because it affects the accuracy of NIPT-based sequencing for fetal trisomies 21, 18 and 13. Several approaches have been developed to calculate the cffDNA fraction of the total cell-free DNA in the maternal plasma.

Noninvasive Prenatal Paternity Testing (NIPAT) through Maternal Plasma DNA Sequencing: A Pilot Study.

Short tandem repeats (STRs) and single nucleotide polymorphisms (SNPs) have been already used to perform noninvasive prenatal paternity testing from maternal plasma DNA. The frequently used technologies were PCR followed by capillary electrophoresis and SNP typing array, respectively. Here, we developed a noninvasive prenatal paternity testing (NIPAT) based on SNP typing with maternal plasma DNA sequencing.

Performance comparison between rapid sequencing platforms for ultra-low coverage sequencing strategy.

Ultra-low coverage sequencing (ULCS) is one of the most promising strategies for sequencing based clinical application. These clinical applications, especially prenatal diagnosis, have a strict requirement of turn-around-time; therefore, the application of ULCS is restricted by current high throughput sequencing platforms. Recently, the emergence of rapid sequencing platforms, such as MiSeq and Ion Proton, brings ULCS strategy into a new era.

PSCC: sensitive and reliable population-scale copy number variation detection method based on low coverage sequencing.

Background: Copy number variations (CNVs) represent an important type of genetic variation that deeply impact phenotypic polymorphisms and human diseases. The advent of high-throughput sequencing technologies provides an opportunity to revolutionize the discovery of CNVs and to explore their relationship with diseases. However, most of the existing methods depend on sequencing depth and show instability with low sequence coverage.

Noninvasive prenatal detection for pathogenic CNVs: the application in α-thalassemia.

Background: The discovery of cell free fetal DNA (cff-DNA) in maternal plasma has brought new insight for noninvasive prenatal diagnosis. Combining with the rapidly developed massively parallel sequencing technology, noninvasive prenatal detection of chromosome aneuploidy and single base variation has been successfully validated. However, few studies discussed the possibility of noninvasive pathogenic CNVs detection.

Effective noninvasive zygosity determination by maternal plasma target region sequencing.

Background: Currently very few noninvasive molecular genetic approaches are available to determine zygosity for twin pregnancies in clinical laboratories. This study aimed to develop a novel method to determine zygosity by using maternal plasma target region sequencing.

Methods: We constructed a statistic model to calculate the possibility of each zygosity type using likelihood ratios ( Li ) and empirical dynamic thresholds targeting at 4,524 single nucleotide polymorphisms (SNPs) loci on 22 autosomes.