The first complete chloroplast genome of (Forssk.) Boiss. 1882 (Cymodoceaceae).

(Forssk.) Boiss. 1882 is a seagrass species.

Genome-wide association study of the loci and candidate genes associated with agronomic traits in Amomum villosum Lour.

Amomum villosum Lour. (A. villosum) is a valuable herbaceous plant that produces the famous traditional Chinese medicine Amori Fructus.

Stabilized, ROS-sensitive β-cyclodextrin-grafted hyaluronic supramolecular nanocontainers for CD44-targeted anticancer drug delivery.

Hyaluronic acid (HA)-based tumor microenvironment-responsive nanocontainers are attractive candidates for anticancer drug delivery due to HA's excellent biocompatibility, biodegradability, and CD44-targeting properties. Nevertheless, the consecutive synthesis of stabilized, stealthy, responsive HA-based multicomponent nanomedicines generally requires multi-step preparation and purification procedures, leading to batch-to-batch variation and scale-up difficulties. To develop a facile yet robust strategy for promoted translations, a silica monomer containing a cross-linkable diethoxysilyl unit was prepared to enable in situ crosslinking without any additives.

Comparison of the Measurement Properties of EQ-5D-5L and SF-6Dv2 in COVID-19 Patients in China.

Background And Objectives: There are limited studies comparing the health utility values of EQ-5D-5L and SF-6Dv2 within the same patient cohorts. The widespread transmission and recurring infections associated with Omicron variants amid the COVID-19 pandemic have resulted in substantial health detriments and increased utilisation of health care resources. This highlights the crucial need to assess the loss in quality-adjusted life years (QALYs).

Novel Circular RNA CircUBAP2 Drives Tumor Progression by Regulating the miR-143/TFAP2B Axis in Prostate Cancer.

Background: More and more investigations reveal that circular RNAs (circRNAs) are involved in cancer progression. CircRNA UBAP2 was closely related to prostate cancer. However, the biological function and specifical mechanism of circUBAP2 are still poorly discovered in prostate cancer (PCa).

Immunogenicity and Safety of One versus Two Doses of Quadrivalent Inactivated Influenza Vaccine (IIV4) in Vaccine-Unprimed Children and One Dose of IIV4 in Vaccine-Primed Children Aged 3-8 Years.

Two doses of the inactivated influenza vaccine (IIV) are generally recommended for children under 9 years old. This study assessed the necessity for a second dose of quadrivalent IIV (IIV4) in children aged 3-8 years. In this randomized, open-label, paralleled-controlled study, 400 children aged 3-8 years who were vaccine-unprimed were randomly assigned at a 1:1 ratio to receive a two-dose (Group 1) or one-dose (Group 2) regimen of IIV4, and 200 who were vaccine-primed received one dose of IIV4 (Group 3).

High-throughput manufacturing of epitaxial membranes from a single wafer by 2D materials-based layer transfer process.

Layer transfer techniques have been extensively explored for semiconductor device fabrication as a path to reduce costs and to form heterogeneously integrated devices. These techniques entail isolating epitaxial layers from an expensive donor wafer to form freestanding membranes. However, current layer transfer processes are still low-throughput and too expensive to be commercially suitable.

Temporal contexts for motion tracking in ultrasound sequences with information bottleneck.

Background: Recently, deep convolutional neural networks (CNNs) have been widely adopted for ultrasound sequence tracking and shown to perform satisfactorily. However, existing trackers ignore the rich temporal contexts that exists between consecutive frames, making it difficult for these trackers to perceive information about the motion of the target.

Purpose: In this paper, we propose a sophisticated method to fully utilize temporal contexts for ultrasound sequences tracking with information bottleneck.

A Soft Label Method for Medical Image Segmentation with Multirater Annotations.

In medical image analysis, collecting multiple annotations from different clinical raters is a typical practice to mitigate possible diagnostic errors. For such multirater labels' learning problems, in addition to majority voting, it is a common practice to use soft labels in the form of full-probability distributions obtained by averaging raters as ground truth to train the model, which benefits from uncertainty contained in soft labels. However, the potential information contained in soft labels is rarely studied, which may be the key to improving the performance of medical image segmentation with multirater annotations.

Advection-Dispersion Behavior for Simulation of H-3 and Pu-238 Transport in Undisturbed Argillaceous Shale of a Near-Surface Repository.

In this study, a column experiment was employed to evaluate the nuclide migration behavior in the surrounding rock medium of a near-surface disposal site in China and to investigate the advection-dispersion behavior of tritium (H-3) and plutonium-238 (Pu-238) in highly weathered argillaceous shale. A reasonable numerical model was selected to fit the experimental breakthrough curves (BTCs) and to obtain the relevant migration parameters. The results show the following: (1) the internal structure of the highly weathered argillaceous shale exhibited heterogeneity, and the nuclide migration BTC showed characteristics of a "curve peak moving forward" and a "tail curve trailing"; (2) compared with other models, the stream tube mode could better fit the BTCs and obtain the average dispersion coefficient <>, average distribution coefficient <>, and other parameters; (3) compared to the results of the batch experiment, the distribution coefficient obtained from the column experiment was smaller than that obtained from the batch experiment, which is speculated to be due to the influence of contact time and the contact area between the nuclide and the medium.

Dual-Modal Information Bottleneck Network for Seizure Detection.

In recent years, deep learning has shown very competitive performance in seizure detection. However, most of the currently used methods either convert electroencephalogram (EEG) signals into spectral images and employ 2D-CNNs, or split the one-dimensional (1D) features of EEG signals into many segments and employ 1D-CNNs. Moreover, these investigations are further constrained by the absence of consideration for temporal links between time series segments or spectrogram images.