Explore the vast range of titles available.

The recent breakthrough of single-cell RNA velocity methods brings attractive promises to reveal directed trajectory on cell differentiation, states transition and response to perturbations. However, the existing RNA velocity methods are often found to return erroneous results, partly due to model violation or lack of temporal regularization. Here, we present UniTVelo, a statistical framework of RNA velocity that models the dynamics of spliced and unspliced RNAs via flexible transcription activities. Uniquely, it also supports the inference of a unified latent time across the transcriptome. With ten datasets, we demonstrate that UniTVelo returns the expected trajectory in different biological systems, including hematopoietic differentiation and those even with weak kinetics or complex branches. RNA velocity can detect the differentiation directionality by modelling sparse unspliced RNAs, but suffers from high estimation errors. Here, the authors develop a computational method called UniTVelo to reinforce the velocity estimation by introducing a unified time and a top-down model design.

In recent years, the internalisation of education in China has led to an increase in the prevalence of a highly competitive, test-focused approach to learning. This has had a detrimental impact on the physical health and wellbeing of children and adolescents in China, resulting in a concerning lack of physical literacy among junior high school students. Accordingly, the objective of this study is to construct an evaluation index system for physical literacy in junior high school students with Chinese characteristics, quantify the relative importance of each domain, and provide a framework for students to assess and self-evaluate the sustainable development of their physical literacy. The indicator system was modelled on CAPL-2, and valid indicators were extracted from the literature. A pre-selected indicator system for physical literacy in junior high school students was constructed through three rounds of Delphi expert questionnaire surveys (48 questionnaires were distributed in total). A total of 16 experts participated in all three rounds of the surveys until a consensus was reached on the indicators, resulting in the establishment of a hierarchical analysis-based theoretical model. This was developed using the experts’ opinions and determined the items to be subdomains and weights. The AHP was employed to ascertain the relative importance of the subdomains and items within the assessment system. The index weight scores of the Chinese junior high school students’ physical literacy assessment index system are aligned with the core tenet of the physical literacy concept, comprising four primary indicators, eight secondary indicators, and 26 tertiary indicators. The weights of the physical literacy evaluation indexes for junior high school students in China were calculated using the AHP to establish a progressive hierarchical model and the consistency test. The primary indicators were found to be in the following order of importance: Physical Competence (29.82%) > Motivation and Confidence (29.64%) > Knowledge and Understanding (20.27%) = Daily Behavior (20.27%). The system is an effective means of evaluating the impact of physical activity and health promotion among junior high school students, and it effectively addresses the needs of this age group in these areas. It provides a comprehensive assessment of the effects of physical activity and health promotion among junior high school students, and it offers a scientific foundation for the development of precise and individualized physical activity and health promotion programs.

Recent lineage tracing based single-cell techniques (LT-scSeq), e.g., the Lineage And RNA RecoverY (LARRY) barcoding system, have enabled clonally resolved interpretation of differentiation trajectories. However, the heterogeneity of clone-specific kinetics remains understudied, both quantitatively and in terms of interpretability, thus limiting the power of barcoding systems to unravel how heterogeneous stem cell clones drive the overall cell population dynamics. Here, we present CLADES, a NeuralODE-based framework to faithfully estimate the clone and population-specific kinetics from both newly generated and publicly available LARRY LT-scSeq data. By incorporating a stochastic simulation algorithm (SSA) and differential expression gene (DEGs) analysis, CLADES yields the summary of cell division dynamics across differentiation time-courses and reconstructs the lineage tree of the progenitor cells in a quantitative way. Moreover, clone-level behaviors can be grouped into characteristic types by pooling individual clones into meta-clones for analyses at various resolutions. Finally, we show that meta-clone specific cellular behaviors identified by CLADES originate from hematopoietic stem and progenitor cells in distinct transcriptional states. In conclusion, we report a scalable approach to robustly quantify clone-specific differentiation kinetics of cellular populations for time-series systems with static barcoding designs. Recent studies have traced haematopoiesis at the clonal level but lack a way to extract dynamical information. Here, authors develop CLADES, a tool to estimate cellular kinetics and the number of divisions to produce mature cells for each clone, in human cord blood and adult mouse haematopoiesis.

Missile-borne short-range infrared detection (SIRD) technology is commonly used in military ground target detection. In complex battlefield environments, achieving precise strike on ground target is a challenging task. However, real battlefield data is limited, and equivalent experiments are costly. Currently, there is a lack of comprehensive physical modeling and numerical simulation methods for SIRD. To this end, this study proposes a SIRD simulation framework incorporating full-link physical response, which is integrated through the radiative transfer layer, the sensor response layer, and the model-driven layer. In the radiative transfer layer, a coupled dynamic detection model is established to describe the external optical channel response of the SIRD system by combining the infrared radiation model and the geometric measurement model. In the sensor response layer, considering photoelectric conversion and signal processing, the internal signal response model of the SIRD system is established by a hybrid mode of parametric modeling and analog circuit analysis. In the model-driven layer, a co-simulation application based on a three-dimensional virtual environment is proposed to drive the full-link physical model, and a parallel ray tracing method is employed for real-time synchronous simulation. The proposed simulation framework can provide pixel-level signal output and is verified by the measured data. The evaluation results of the root mean square error (RMSE) and the Pearson correlation coefficient (PCC) show that the simulated data and the measured data achieve good consistency, and the evaluation results of the waveform eigenvalues indicate that the simulated signals exhibit low errors compared to the measured signals. The proposed simulation framework has the potential to acquire large sample datasets of SIRD under various complex battlefield environments and can provide an effective data source for SIRD application research.

This study employed experimental methods to systematically investigate the bending behavior of composite materials at high temperatures. The biaxial warp-knitted fabric (BWKC) and quadaxial warp-knitted fabric (QWKC) were selected as reinforcement and the mixture solution of epoxy resin and curing agent were selected as matrix. The composite specimen was fabricated by vacuum assisted resin film (VARI). Taking into influence of temperature on the bending behavior of composites for wind turbine blades, further investigations have been conducted to analyze the influence of temperature on the mechanical properties of composites. The quasi-bending behavior of BWKC and QWKC in 0°–90°directions at different service temperatures (20℃, 45℃ and 70℃) were analyzed at macro-scale and micro-scale. Results show that the bending strength and modulus were decreased with the increase of temperature. The ultimate normalized strength of BWKC and QWKC composites were decreased by 20.36–23.56%. The behavior such as the stress–strain curves were also obtained. The relationships between bending behavior and temperatures are also obtained by nonlinear fitting with the experimental data, which could be used to predict the bending properties at different temperatures.

In this paper, an ultrasonic target detection system based on Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) is proposed, which consists of the PMUTs based ultrasonic sensor and the sensor system. Two pieces of 3 × 3 PMUTs arrays with the resonant frequency of 115 kHz are used as transmitter and receiver of the PMUTs-based ultrasonic sensor. Then, the sensor system can calculate the target’s position through the signal received by the above receiver. The static and dynamic performance of the proposed prototype system are characterized on black, white, and transparent targets. The experiment results demonstrated that the proposed system can detect targets of different colors, transparencies, and motion states. In the static experiments, the static location errors of the proposed system in the range of 200 mm to 320 mm are 0.51 mm, 0.50 mm and 0.53 mm, whereas the errors of a commercial laser sensor are 2.89 mm, 0.62 mm, and N In the dynamic experiments, the experimental materials are the targets with thicknesses of 1 mm, 1.5 mm, 2 mm and 2.5 mm, respectively. The proposed system can detect the above targets with a maximum detection error of 4.00%. Meanwhile, the minimum resolution of the proposed system is about 0.5 mm. Finally, in the comprehensive experiments, the proposed system successfully guides a robotic manipulator to realize the detecting, grasping, and moving of a transparent target with 1 mm. This ultrasonic target detection system has demonstrated a cost-effective method to detect targets, especially transparent targets, which can be widely used in the detection and transfer of glass substrates in automated production lines.

Although oral probiotics can improve breast microecology and alleviate the inflammatory response, there are no data regarding cases with existing abscesses. We aimed to investigate the effect of Lactobacillus fermentum CECT5716 during needle aspiration in patients with lactational breast abscesses. Patients (aged 20–41 years) with lactational single-cavity breast abscesses (diameter 3–6 cm) from 12 hospitals were randomly assigned to the experimental (n = 51) and control groups (n = 50). Outcome measures included the abscess cure rate on treatment day-5, delactation rate, relieving pain rate, and number of needle aspirations until day-28. The experimental group’s 5-day cure rate (43.1%) was significantly higher ( p  < 0.05). Breastfeeding continuation on day-5 did not differ significantly (experimental group: 88.2%, control group: 96.0%, p  = 0.269). In the experimental and control groups, 19.6% and 14.0% of patients experienced moderate to severe pain on day-5, respectively, with no statistically significant differences ( p  = 0.451). Four patients in each group developed diarrhea, with adverse reaction rates of 7.84% and 8.0%, respectively. No adverse reactions were reported in the infants. L. fermentum can shorten the healing time in patients with lactational breast abscesses. Trial registration This study was registered in the Chinese Clinical Trial Registry ( http://www.chictr.org.cn ), registration number: ChiCTR2000032682, registration date: 6/May/ 2020; first entry date: 11/May/2020.

High-energy-density lithium (Li)–air cells have been considered a promising energy-storage system, but the liquid electrolyte-related safety and side-reaction problems seriously hinder their development. To address these above issues, solid-state Li–air batteries have been widely developed. However, many commonly-used solid electrolytes generally face huge interface impedance in Li–air cells and also show poor stability towards ambient air/Li electrodes. Herein, we fabricate a differentiating surface-regulated ceramic-based composite electrolyte (DSCCE) by constructing disparately LiI-containing polymethyl methacrylate (PMMA) coating and Poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) layer on both sides of Li1.5Al0.5Ge1.5(PO4)3 (LAGP). The cathode-friendly LiI/PMMA layer displays excellent stability towards superoxide intermediates and also greatly reduces the decomposition voltage of discharge products in Li–air system. Additionally, the anode-friendly PVDF-HFP coating shows low-resistance properties towards anodes. Moreover, Li dendrite/passivation derived from liquid electrolyte-induced side reactions and air/I-attacking can be obviously suppressed by the uniform and compact composite framework. As a result, the DSCCE-based Li–air batteries possess high capacity/low voltage polarization (11,836 mA h g−1/1.45 V under 500 mA g−1), good rate performance (capacity ratio under 1000 mA g−1/250 mA g−1 is 68.2%) and long-term stable cell operation (∼300 cycles at 750 mA g−1 with 750 mAh g−1) in ambient air. The differentiatingly surface-regulated ceramic-based composite electrolyte (DSCCE) is constructed and applied in Li–air batteries. Because of the antioxidative PMMA-based layer with LiI redox mediator catalyst, anode-friendly PVDF-HFP-based coating and compact/stable ceramic frameworks, the corresponding cells shows the excellent cycling life under ambient air. [Display omitted] •Differentiating surface-regulated ceramic-based composite electrolyte (DSCCE) is constructed.•LiI/PMMA-based and PVDF-HFP-based layers of DSCCE match well with air-cathode and anode, respectively.•DSCCE effectively improve electrochemical performances of Li–air battery.

Photodynamic therapy (PDT), a promising treatment modality, employs photosensitizers to generate cytotoxic reactive oxygen species (ROS) within localized tumor regions. This technique involves administering a photosensitizer followed by light activation in the presence of oxygen (O 2 ), resulting in cytotoxic ROS production. PDT’s spatiotemporal selectivity, minimally invasive nature, and compatibility with other treatment modalities make it a compelling therapeutic approach. However, hypoxic tumor microenvironment (TME) poses a significant challenge to conventional PDT. To overcome this hurdle, various strategies have been devised, including in-situ O 2 generation, targeted O 2 delivery, tumor vasculature normalization, modulation of mitochondrial respiration, and photocatalytic O 2 generation. This review aims to provide a comprehensive overview of recent developments in designing tumor-oxygenated nanomaterials to enhance PDT efficacy. Furthermore, we delineate ongoing challenges and propose strategies to improve PDT’s clinical impact in cancer treatment.