Identification and developmental profiling of microRNAs in the acoel worm .

The acoel worm has recently emerged as a model organism for studying whole-body regeneration and embryonic development. Previous studies suggest that post-transcriptional mechanisms likely play important roles in whole-body regeneration. Here, we establish a resource for studying microRNA-mediated gene regulation, a major aspect of post-transcriptional control in animals.

A binary 2D perovskite passivation for efficient and stable perovskite/silicon tandem solar cells.

To achieve high power conversion efficiency in perovskite/silicon tandem solar cells, it is necessary to develop a promising wide-bandgap perovskite absorber and processing techniques in relevance. To date, the performance of devices based on wide-bandgap perovskite is still limited mainly by carrier recombination at their electron extraction interface. Here, we demonstrate assembling a binary two-dimensional perovskite by both alternating-cation-interlayer phase and Ruddlesden-Popper phase to passivate perovskite/C interface.

Nuclei engineering for even halide distribution in stable perovskite/silicon tandem solar cells.

Wide-bandgap (WBG) absorbers in tandem configurations suffer from poor crystallinity and weak texture, which leads to severe mixed halide-cation ion migration and phase segregation during practical operation. We control WBG film growth insensitive to compositions by nucleating the 3C phase before any formation of bromine-rich aggregates and 2H phases. The resultant WBG absorbers show improved crystallinity and strong texture with suppressed nonradiative recombination and enhanced resistance to various aging stresses.

Comprehensive review of deep learning in orthopaedics: Applications, challenges, trustworthiness, and fusion.

Deep learning (DL) in orthopaedics has gained significant attention in recent years. Previous studies have shown that DL can be applied to a wide variety of orthopaedic tasks, including fracture detection, bone tumour diagnosis, implant recognition, and evaluation of osteoarthritis severity. The utilisation of DL is expected to increase, owing to its ability to present accurate diagnoses more efficiently than traditional methods in many scenarios.

Modeling neurodevelopmental disorder-associated human mutations in Argonaute .

MicroRNAs (miRNA) associate with Argonaute (AGO) proteins and repress gene expression by base pairing to sequences in the 3' untranslated regions of target genes. De novo coding variants in the human AGO genes and cause neurodevelopmental disorders (NDD) with intellectual disability, referred to as Argonaute syndromes. Most of the altered amino acids are conserved between the miRNA-associated AGO in and , suggesting that the human mutations could disrupt conserved functions in miRNA biogenesis or activity.

A deep learning approach to remove contrast from contrast-enhanced CT for proton dose calculation.

Purpose: Non-Contrast Enhanced CT (NCECT) is normally required for proton dose calculation while Contrast Enhanced CT (CECT) is often scanned for tumor and organ delineation. Possible tissue motion between these two CTs raises dosimetry uncertainties, especially for moving tumors in the thorax and abdomen. Here we report a deep-learning approach to generate NCECT directly from CECT.

Modeling neurodevelopmental disorder-associated mutations in Argonaute .

MicroRNAs (miRNA) are endogenous non-coding RNAs important for post-transcriptional regulation of gene expression. miRNAs associate with Argonaute proteins to bind to the 3' UTR of target genes and confer target repression. Recently, multiple coding variants in the human Argonaute gene ( ) have been reported to cause a neurodevelopmental disorder (NDD) with intellectual disability (ID).

Contour interpolation by deep learning approach.

Purpose: Contour interpolation is an important tool for expediting manual segmentation of anatomical structures. The process allows users to manually contour on discontinuous slices and then automatically fill in the gaps, therefore saving time and efforts. The most used conventional shape-based interpolation (SBI) algorithm, which operates on shape information, often performs suboptimally near the superior and inferior borders of organs and for the gastrointestinal structures.

Critical contribution of 3' non-seed base pairing to the in vivo function of the evolutionarily conserved let-7a microRNA.

Base pairing of the seed region (g2-g8) is essential for microRNA targeting; however, the in vivo function of the 3' non-seed region (g9-g22) is less well understood. Here, we report a systematic investigation of the in vivo roles of 3' non-seed nucleotides in microRNA let-7a, whose entire g9-g22 region is conserved among bilaterians. We find that the 3' non-seed sequence functionally distinguishes let-7a from its family paralogs.

Digital tongue image analyses for health assessment.

Traditional Chinese Medicine (TCM), as an effective alternative medicine, utilizes tongue diagnosis as a major method to assess the patient's health status by examining the tongue's color, shape, and texture. Tongue images can also give the pre-disease indications without any significant disease symptoms, which provides a basis for preventive medicine and lifestyle adjustment. However, traditional tongue diagnosis has limitations, as the process may be subjective and inconsistent.

Analgesic Effects of Epidural Labor Analgesia at Different Periods and Its Effects on Maternal and Infant Outcomes and MiRNA-146b Level.

This paper aimed to analyze the analgesic effects of continuous epidural labor analgesia (ELA) at different periods and its effects on postpartum depression, maternal and infant outcomes, and maternal blood pressure. Giving birth in our hospital from September 2017 to August 2019, 119 primiparas with spontaneous delivery were enrolled and divided into an observation group (65 cases) and a control group (54 cases). Patients in the observation group received epidural block analgesia in advance, whereas those in the control group received epidural block analgesia routinely.

[Effects of dezocine on cardiac myocytes injury induced by hypoxia and reoxygenation in rats and its mechanism].

To investigate the mechanisms of dezocine on regulating H9C2 oxidative stress and apoptosis of rat cardiac myocytes induced by hypoxia-reoxygenation(H/R) by regulating the expressions of microRNA-7a- 5p(miR-7a-5p)/ubiquitin E3 ligase tripartite motif 10(TRIM10). H9C2 cells were divided into control group (cultured normally), H/R group (treated with hypoxia for 3 h and then reoxygenation for 4 h), different doses of dezocine intervention group (H9c2 cells were pretreated with dezocine at the concentrations of 10, 10 and 10 mmol/L for 24 h, and then treated with H/R), H/R+miR-7a-5p group (H9C2 cells were transfected with miR-7a-5p mimics and then treated with H/R), H/R+miR-NC group (H9C2 cells were transfected with miR-NC and then treated with H/R), H/R+Dezocine+anti-miR-7a-5p group (H9c2 cells transfected with anti-miR-7a-5p were pretreated with 10 mmol/L dezocine for 24 h, and then treated with H/R), H/R+dezocine+ anti-miR-NC Group (H9c2 cells transfected with anti-miR-NC were pretreated with 10 mmol/L dezocine for 24 h, and then treated with H/R). Each group of cells was set with 3 replicate wells, and the experiment was repeated 3 times.

Deepening into the suitability of using pre-trained models of ImageNet against a lightweight convolutional neural network in medical imaging: an experimental study.

Transfer learning (TL) has been widely utilized to address the lack of training data for deep learning models. Specifically, one of the most popular uses of TL has been for the pre-trained models of the ImageNet dataset. Nevertheless, although these pre-trained models have shown an effective performance in several domains of application, those models may not offer significant benefits in all instances when dealing with medical imaging scenarios.

N,O-codoped carbon spheres with uniform mesoporous entangled CoO nanoparticles as a highly efficient electrocatalyst for oxygen reduction in a Zn-air battery.

Highly efficient electrochemical catalysts for oxygen reduction reactions (ORRs) are urgently needed for various energy conversion and storage devices to overcome sluggish ORR kinetics. Here, N,O-codoped carbon spheres with uniform mesopores and a high specific surface area were used as supports for decorating CoO nanoparticles via a facile immersion route. In addition to the benefit of ions and gas mass transfer, the abundant mesopores present in the three-dimensional (3D) carbon spheres also confine and isolate the CoO nanoparticles growing in it, which help to provide rich CoO active sites.

Novel Transfer Learning Approach for Medical Imaging with Limited Labeled Data.

Deep learning requires a large amount of data to perform well. However, the field of medical image analysis suffers from a lack of sufficient data for training deep learning models. Moreover, medical images require manual labeling, usually provided by human annotators coming from various backgrounds.

Auto3DCryoMap: an automated particle alignment approach for 3D cryo-EM density map reconstruction.

Background: Cryo-EM data generated by electron tomography (ET) contains images for individual protein particles in different orientations and tilted angles. Individual cryo-EM particles can be aligned to reconstruct a 3D density map of a protein structure. However, low contrast and high noise in particle images make it challenging to build 3D density maps at intermediate to high resolution (1-3 Å).

DeepCryoPicker: fully automated deep neural network for single protein particle picking in cryo-EM.

Background: Cryo-electron microscopy (Cryo-EM) is widely used in the determination of the three-dimensional (3D) structures of macromolecules. Particle picking from 2D micrographs remains a challenging early step in the Cryo-EM pipeline due to the diversity of particle shapes and the extremely low signal-to-noise ratio of micrographs. Because of these issues, significant human intervention is often required to generate a high-quality set of particles for input to the downstream structure determination steps.

Effect of Trimetazidine on Diabetic Patients with Coronary Heart Diseases: A Meta-Analysis of Randomized, Controlled Trials.

Objective To explore the therapeutic effects of trimetazidine (TMZ) on diabetic patients with coronary heart diseases.Methods We conducted a comprehensive electronic search of PubMed, EMBASE, and Cochrane databases between the inception dates of databases and May 2019 (last search conducted on 30 May 2019) to identify randomized controlled trials. The evaluation method recommended by Cochrane Collaboration for bias risk assessment was employed for quality assessment.

REDN: A Recursive Encoder-Decoder Network for Edge Detection.

In this paper, we introduce REDN: A Recursive Encoder-Decoder Network with Skip-Connections for edge detection in natural images. The proposed network is a novel integration of a Recursive Neural Network with an Encoder-Decoder architecture. The recursive network enables iterative refinement of the edges using a single network model.

The effects of dietary reduced mineral elements and coated cysteamine supplementation on bacterial diversity in the ileum of finishing pigs.

This study was conducted to investigate the effects of different levels of dietary partial MEs and coated cysteamine (CC) supplementation on gut microbiota in finishing pigs. Results showed that whittling down dietary partial MEs (Cu, Fe, Zn, Mn) by 20% and 40% had little effect on the microbial diversity, community structure, and bacterial relative abundance in the ileum of finishing pigs. Supplementation with 1,600 mg/kg CC also had no obvious effect on the microbial diversity, community structure, and bacterial relative abundance in the finishing pig ileum when fed diets with a normal MEs level.