Unsupervised cryo-EM data clustering through adaptively constrained K-means algorithm

In single-particle cryo-electron microscopy (cryo-EM), K-means clustering algorithm is widely used in unsupervised 2D classification of projection images of biological macromolecules. 3D ab initio reconstruction requires accurate unsupervised classification in order to separate molecular projections of distinct orientations. Due to background noise in single-particle images and uncertainty of molecular orientations, traditional K-means clustering algorithm may classify images into wrong classes and produce classes with a large variation in membership. Overcoming these limitations requires further development on clustering algorithms for cryo-EM data analysis. We propose a novel unsupervised data clustering method building upon the traditional K-means algorithm. By introducing an adaptive constraint term in the objective function, our algorithm not only avoids a large variation in class sizes but also produces more accurate data clustering. Applications of this approach to both simulated and experimental cryo-EM data demonstrate that our algorithm is a significantly improved alterative to the traditional K-means algorithm in single-particle cryo-EM analysis.Comment: 35 pages, 14 figure

A Randomized Algorithm for Single-Source Shortest Path on Undirected Real-Weighted Graphs

In undirected graphs with real non-negative weights, we give a new randomized algorithm for the single-source shortest path (SSSP) problem with running time $O(m\sqrt{\log n \cdot \log\log n})$ in the comparison-addition model. This is the first algorithm to break the $O(m+n\log n)$ time bound for real-weighted sparse graphs by Dijkstra's algorithm with Fibonacci heaps. Previous undirected non-negative SSSP algorithms give time bound of $O(m\alpha(m,n)+\min\{n\log n, n\log\log r\})$ in comparison-addition model, where $\alpha$ is the inverse-Ackermann function and $r$ is the ratio of the maximum-to-minimum edge weight [Pettie & Ramachandran 2005], and linear time for integer edge weights in RAM model [Thorup 1999]. Note that there is a proposed complexity lower bound of $\Omega(m+\min\{n\log n, n\log\log r\})$ for hierarchy-based algorithms for undirected real-weighted SSSP [Pettie & Ramachandran 2005], but our algorithm does not obey the properties required for that lower bound. As a non-hierarchy-based approach, our algorithm shows great advantage with much simpler structure, and is much easier to implement.Comment: 17 page

PICNN: A Pathway towards Interpretable Convolutional Neural Networks

Convolutional Neural Networks (CNNs) have exhibited great performance in discriminative feature learning for complex visual tasks. Besides discrimination power, interpretability is another important yet under-explored property for CNNs. One difficulty in the CNN interpretability is that filters and image classes are entangled. In this paper, we introduce a novel pathway to alleviate the entanglement between filters and image classes. The proposed pathway groups the filters in a late conv-layer of CNN into class-specific clusters. Clusters and classes are in a one-to-one relationship. Specifically, we use the Bernoulli sampling to generate the filter-cluster assignment matrix from a learnable filter-class correspondence matrix. To enable end-to-end optimization, we develop a novel reparameterization trick for handling the non-differentiable Bernoulli sampling. We evaluate the effectiveness of our method on ten widely used network architectures (including nine CNNs and a ViT) and five benchmark datasets. Experimental results have demonstrated that our method PICNN (the combination of standard CNNs with our proposed pathway) exhibits greater interpretability than standard CNNs while achieving higher or comparable discrimination power

ChatGPT for Shaping the Future of Dentistry: The Potential of Multi-Modal Large Language Model

The ChatGPT, a lite and conversational variant of Generative Pretrained Transformer 4 (GPT-4) developed by OpenAI, is one of the milestone Large Language Models (LLMs) with billions of parameters. LLMs have stirred up much interest among researchers and practitioners in their impressive skills in natural language processing tasks, which profoundly impact various fields. This paper mainly discusses the future applications of LLMs in dentistry. We introduce two primary LLM deployment methods in dentistry, including automated dental diagnosis and cross-modal dental diagnosis, and examine their potential applications. Especially, equipped with a cross-modal encoder, a single LLM can manage multi-source data and conduct advanced natural language reasoning to perform complex clinical operations. We also present cases to demonstrate the potential of a fully automatic Multi-Modal LLM AI system for dentistry clinical application. While LLMs offer significant potential benefits, the challenges, such as data privacy, data quality, and model bias, need further study. Overall, LLMs have the potential to revolutionize dental diagnosis and treatment, which indicates a promising avenue for clinical application and research in dentistry

Current insights in the preclinical study of palatal wound healing and oronasal fistula after cleft palate repair

Poor palatal wound healing after cleft palate repair could lead to unfavorable prognosis such as oronasal fistula (ONF), which might affect the patient’s velopharyngeal function as well as their quality of life. Thus, restoring poor palatal wound healing for avoiding the occurrence of ONF should be considered the key to postoperative care after cleft palate repair. This review provided current insights in the preclinical study of poor palatal wound healing after cleft palate repair. This review comprehensively introduced the animal model establishment for palatal wound healing and related ONF, including the models by mice, rats, piglets, and dogs, and then demonstrated the aspects for investigating poor palatal wound healing and related treatments, including possible signaling pathways that could be involved in the formation of poor palatal wound healing, the related microbiota changes because of the deformity of palatal structure, and the studies for potential therapeutic strategies for palatal wound healing and ONF. The purpose of this review was to show the state of the art in preclinical studies about palatal wound healing after cleft palate repair and to show the promising aspects for better management of palatal wound healing

Engineering Colloidal Metal-Semiconductor Nanorods Hybrid Nanostructures for Photocatalysis

Comprehensive Summary Emerging engineering strategies of colloidal metal-semiconductor nanorod hybrid nanostructures spanning from type, size, dimension, and location of both metal nanoparticles and semiconductors, co-catalyst, band gap structure, surface ligand to hole scavenger are elaborated symmetrically to rationalize the design of this type of intriguing materials for efficient photocatalytic applications. This article is protected by copyright. All rights reserved

Dietary Supplementation With Chinese Herbal Residues or Their Fermented Products Modifies the Colonic Microbiota, Bacterial Metabolites, and Expression of Genes Related to Colon Barrier Function in Weaned Piglets

To explore the feasibility of dietary Chinese herbal residue (CHR) supplementation in swine production with the objective of valorization, we examined the effects of dietary supplementation with CHR or fermented CHR products on the colonic ecosystem (i.e., microbiota composition, luminal bacterial metabolites, and expression of genes related to the intestinal barrier function in weaned piglets). We randomly assigned 120 piglets to one of four dietary treatment groups: a blank control group, CHR group (dose of supplement 4 kg/t), fermented CHR group (dose of supplement 4 kg/t), and a positive control group (supplemented with 0.04 kg/t virginiamycin, 0.2 kg/t colistin, and 3000 mg/kg zinc 0.04 kg/t virginiamycin, 0.2 kg/t colistin, and 3000 mg/kg zinc oxide). Our results indicate that dietary supplementation with CHR increased (P < 0.05) the mRNA level corresponding to E-cadherin compared with that observed in the other three groups, increased (P < 0.05) the mRNA level corresponding to zonula occludens-1, and decreased (P < 0.05) the quantity of Bifidobacterium spp. When compared with the blank control group. Dietary supplementation with fermented CHR decreased (P < 0.05) the concentration of indole when compared to the positive control group; increased (P < 0.05) the concentrations of short-chain fatty acids compared with the values measured in the CHR group, as well as the mRNA levels corresponding to interleukin 1 alpha, interleukin 2, and tumor necrosis factor alpha. However, supplementation with fermented CHR decreased (P < 0.05) interleukin 12 levels when compared with the blank control group. Collectively, these findings suggest that dietary supplementation with CHR or fermented CHR modifies the gut environment of weaned piglets

Nonepitaxial Gold-Tipped ZnSe Hybrid Nanorods for Efficient Photocatalytic Hydrogen Production

For the first time, colloidal gold (Au)–ZnSe hybrid nanorods (NRs) with controlled size and location of Au domains are synthesized and used for hydrogen production by photocatalytic water splitting. Au tips are found to grow on the apices of ZnSe NRs nonepitaxially to form an interface with no preference of orientation between Au(111) and ZnSe(001). Density functional theory calculations reveal that the Au tips on ZnSe hybrid NRs gain enhanced adsorption of H compared to pristine Au, which favors the hydrogen evolution reaction. Photocatalytic tests reveal that the Au tips on ZnSe NRs effectively enhance the photocatalytic performance in hydrogen generation, in which the single Au-tipped ZnSe hybrid NRs show the highest photocatalytic hydrogen production rate of 437.8 µmol h−1 g−1 in comparison with a rate of 51.5 µmol h−1 g−1 for pristine ZnSe NRs. An apparent quantum efficiency of 1.3% for hydrogen evolution reaction for single Au-tipped ZnSe hybrid NRs is obtained, showing the potential application of this type of cadmium (Cd)-free metal–semiconductor hybrid nanoparticles (NPs) in solar hydrogen production. This work opens an avenue toward Cd-free hybrid NP-based photocatalysis for clean fuel production.W.C. and X.L. contributed equally to this work. This work was supported by the Australian Research Council (ARC) Discovery Early Career Researcher Award (DECRA) (DE 160100589) and discovery project (DP 170104264). Y.L. acknowledges support from the NSFC (grant no. 11674131). W.C. acknowledges the scholarship from the China Scholarship Council

Ji-Ni-De-Xie ameliorates type 2 diabetes mellitus by modulating the bile acids metabolism and FXR/FGF15 signaling pathway

Introduction: Ji-Ni-De-Xie (JNDX) is a traditional herbal preparation in China. It is widely used to treat type 2 diabetes mellitus (T2DM) in traditional Tibetan medicine system. However, its antidiabetic mechanisms have not been elucidated. The aim of this study is to elucidate the underlying mechanism of JNDX on bile acids (BAs) metabolism and FXR/FGF15 signaling pathway in T2DM rats.Methods: High-performance liquid chromatography-triple quadrupole mass spectrometry (HPLC-QQQ-MS) and UPLC-Q-Exactive Orbitrap MS technology were used to identify the constituents in JNDX. High-fat diet (HFD) combined with streptozotocin (45 mg∙kg−1) (STZ) was used to establish a T2DM rat model, and the levels of fasting blood-glucose (FBG), glycosylated serum protein (GSP), homeostasis model assessment of insulin resistance (HOMA-IR), LPS, TNF-α, IL-1β, IL-6, TG, TC, LDL-C, HDL-C, and insulin sensitivity index (ISI) were measured to evaluate the anti-diabetic activity of JNDX. In addition, metagenomic analysis was performed to detect changes in gut microbiota. The metabolic profile of BAs was analyzed by HPLC-QQQ-MS. Moreover, the protein and mRNA expressions of FXR and FGF15 in the colon and the protein expressions of FGF15 and CYP7A1 in the liver of T2DM rats were measured by western blot and RT-qPCR.Results: A total of 12 constituents were identified by HPLC-QQQ-MS in JNDX. Furthermore, 45 chemical components in serum were identified from JNDX via UPLC-Q-Exactive Orbitrap MS technology, including 22 prototype components and 23 metabolites. Using a T2DM rat model, we found that JNDX (0.083, 0.165 and 0.33 g/kg) reduced the levels of FBG, GSP, HOMA-IR, LPS, TNF-α, IL-1β, IL-6, TG, TC, and LDL-C, and increased ISI and HDL-C levels in T2DM rats. Metagenomic results demonstrated that JNDX treatment effectively improved gut microbiota dysbiosis, including altering some bacteria (e.g., Streptococcus and Bacteroides) associated with BAs metabolism. Additionally, JNDX improved BAs disorder in T2DM rats, especially significantly increasing cholic acid (CA) levels and decreasing ursodeoxycholic acid (UDCA) levels. Moreover, the protein and mRNA expressions of FXR and FGF15 of T2DM rats were significantly increased, while the expression of CYP7A1 protein in the liver was markedly inhibited by JNDX.Discussion: JNDX can effectively improve insulin resistance, hyperglycemia, hyperlipidemia, and inflammation in T2DM rats. The mechanism is related to its regulation of BAs metabolism and activation of FXR/FGF15 signaling pathway

Genotypic and Environmental Effects on the Volatile Chemotype of Valeriana jatamansi Jones

Valeriana jatamansi Jones is an aromatic medicinal herb and important alternative to V. officinalis, which is utilized for medicinal purposes in China and India and also as spices in India. Bioactive ingredients of V. jatamansi vary in different regions. However, no information is currently available on influence of genotype and environmental factors in the volatile compounds, especially when germplasms and planting locations need to be selected. Based on the results of SNP and volatile constituents from GC-MS analysis, this study found various genotypes and chemotypes of V. jatamansi for wild plants from seven regions in China and common-garden samples; correlations between genotype and chemotype were revealed for the plants. Two distinct populations (PX, FY) were distinguishable from five others (GJ, YL, SY, DD, DY) according to their genotypes and volatile profiles, the consistency of which was observed showing that genotype could significantly influence chemotype. Wild populations and common-garden samples were also separated in their volatile profiles, demonstrating that environmental factors strongly affected their chemotypes. Compounds contributing to the discrimination were identified as discriminatory compounds. This investigation has explored and provided essential information concerning the correlation between genotype and chemotype as well as environmental factors and chemotype of V. jatamansi in some regions of China. Feasible plantation and conservation strategies of V. jatamansi could be further explored based on these results