Accuracy of immediate anterior implantation using static and robotic computer-assisted implant surgery: A retrospective study.

OBJECTIVES: To investigate the accuracy of immediate anterior implantation using static computer-assisted implant surgery (s-CAIS) and robotic computer-assisted implant surgery (r-CAIS). MATERIALS AND METHODS: One hundred and six implants were immediately inserted in the anterior zone of 69 patients using a freehand technique, s-CAIS or r-CAIS. Postoperative cone-beam computed tomography scans were matched with preoperative plans to evaluate the deviations between the planned and placed implant positions. RESULTS: The global coronal deviations in the freehand, s-CAIS, and r-CAIS groups were 1.29 ± 0.52 mm, 1.01 ± 0.41 mm, and 0.62 ± 0.28 mm, respectively. Significant differences were observed in the r-CAIS group compared to both the s-CAIS group and the freehand group (p < 0.05). However, no significant differences were found between the s-CAIS group and the freehand group (p > 0.05). The global apical deviations in the freehand, s-CAIS and r-CAIS groups were 1.78 ± 0.59 mm, 1.24 ± 0.52 mm and 0.65 ± 0.27 mm, respectively, while the angular deviations in the freehand, s-CAIS and r-CAIS groups were 6.46 ± 2.21°, 2.94 ± 1.71° and 1.46 ± 0.57°, respectively. Significant differences were observed in both the global apical deviations and angular deviations among the three groups (p < 0.05). CONCLUSIONS: The accuracy of immediate anterior implantation with r-CAIS was better than that with s-CAIS. This difference is attributed to better control of the coronal, vertical and axial errors during r-CAIS. CLINICAL SIGNIFICANCE: This study provides significant evidence to support the use of r-CAIS as a potential alternative in immediate anterior implantation.

Mechanism of immune activation mediated by genomic instability and its implication in radiotherapy combined with immune checkpoint inhibitors.

Various genetic and epigenetic changes associated with genomic instability (GI), including DNA damage repair defects, chromosomal instability, and mitochondrial GI, contribute to development and progression of cancer. These alterations not only result in DNA leakage into the cytoplasm, either directly or through micronuclei, but also trigger downstream inflammatory signals, such as the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway. Apart from directly inducing DNA damage to eliminate cancer cells, radiotherapy (RT) exerts its antitumor effects through intracellular DNA damage sensing mechanisms, leading to the activation of downstream inflammatory signaling pathways. This not only enables local tumor control but also reshapes the immune microenvironment, triggering systemic immune responses. The combination of RT and immunotherapy has emerged as a promising approach to increase the probability of abscopal effects, where distant tumors respond to treatment due to the systemic immunomodulatory effects. This review emphasizes the importance of GI in cancer biology and elucidates the mechanisms by which RT induces GI remodeling of the immune microenvironment. By elucidating the mechanisms of GI and RT-induced immune responses, we aim to emphasize the crucial importance of this approach in modern oncology. Understanding the impact of GI on tumor biological behavior and therapeutic response, as well as the possibility of activating systemic anti-tumor immunity through RT, will pave the way for the development of new treatment strategies and improve prognosis for patients.

The Conservation Implications of the Gut Microbiome for Protecting the Critically Endangered Gray Snub-Nosed Monkey (Rhinopithecus brelichi).

The gut microbiota plays a crucial role in regulating energy metabolism, facilitating nutrient absorption, and supporting immune function, thereby assisting the host in adapting to seasonal dietary changes. Here, we compare the gut microbiome composition of wild gray snub-nosed monkeys during winter (from October to December) and spring (from January to March) to understand differences in seasonal nutrient intake patterns. Snub-nosed monkeys are foregut fermenters and consume difficult-to-digest carbohydrates and lichen. To examine the digestive adaptations of gray snub-nosed monkeys, we collected 14 fresh fecal samples for DNA analysis during the winter and spring. Based on 16S rRNA sequencing, metagenomic sequencing, and functional metagenomic analyses, we identified that Firmicutes, Actinobacteria, Verrucomicrobia, and Bacteroidetes constitute a keystone bacterial group in the gut microbiota during winter and spring and are responsible for degrading cellulose. Moreover, the transition in dietary composition from winter to spring was accompanied by changes in gut microbiota composition, demonstrating adaptive responses to varying food sources and availability. In winter, the bacterial species of the genera Streptococcus were found in higher abundance. At the functional level, these bacteria are involved in fructose and mannose metabolism and galactose metabolism c-related pathways, which facilitate the breakdown of glycogen, starch, and fiber found in fruits, seeds, and mature leaves. During spring, there was an increased abundance of bacteria species from the Prevotella and Lactobacillus genera, which aid the digestion of protein-rich buds. Combined, these findings reveal how the gut microbiota adjusts to fluctuations in energy balance and nutrient intake across different seasons in this critically endangered species. Moreover, we also identified Pseudomonas in two samples; the presence of potential pathogens within the gut could pose a risk to other troop members. Our findings highlight the necessity of a conservation plan that focuses on protecting vegetation and implementing measures to prevent disease transmission for this critically endangered species.

Insecticidal potential and risk assessment of diamide pesticides against Spodoptera frugiperda in maize crops.

The effectiveness, tolerance, and safety of pesticides must be established before their scientific or rational. This study evaluates the field control efficacy of broflanilide, tetraniliprole, and chlorantraniliprole in combating Spodoptera frugiperda in maize crops, as well as the resistance of S. frugiperda to these three diamide pesticides after exposure. By assessing field control efficiency, toxicity, effects on development and reproduction, and detoxification enzyme activity of these diamide pesticides on S. frugiperda, highlights broflanilide's significant insecticidal potential. A highly sensitive and efficient method using QuEChERS/HPLCMS/MS was developed to simultaneously detect residues of these three pesticides on maize. Initial concentrations of broflanilide, tetraniliprole, and chlorantraniliprole ranged from 2.13 to 4.02 mg/kg, with their respective half-lives varying between 1.23 and 1.51 days. Following foliar application, by the time of harvest, the terminal residue concentrations of these pesticides were all under 0.01 mg/kg. Chronic dietary intake risk assessments and cumulative chronic dietary exposure for three pesticides indicated that the general population's terminal residue concentration was within acceptable limits. Not only does this research provide valuable insights into field control efficiency, insecticidal effects, resistance, residues, and risk assessment results of broflanilide, tetraniliprole, and chlorantraniliprole on maize, but additionally, it also paves the way for setting suitable Maximum Residue Limits (MRLs) values based on pre-harvest interval values, rational dosage, and application frequency.

Synthesis of Fully Substituted Difluoromethylpyrazoles by Cyclization of Difluoroacetohydrazonoyl Bromides with 2-Acylacetonitriles or Malononitrile.

A concise and efficient method for the construction of fully substituted difluoromethylpyrazoles is achieved by a cyclization reaction between difluoroacetohydrazonoyl bromides and 2-acylacetonitrile or malononitrile. The method features advantages such as mild reaction conditions, broad substrate scope, good product yields, and high regioselectivity.

Whole genome sequencing and genomic characteristics analysis of carbapenem-resistant Acinetobacter baumannii clinical isolates in two hospitals in China.

Nosocomial outbreaks caused by carbapenem-resistant Acinetobacter baumannii (CRAB) strains are rapidly emerging worldwide and are cause for concern. Herein, we aimed to describe the genomic characteristics of CRAB strains isolated from two hospitals in China in 2023. The A. baumannii isolates were mainly collected from the ICU and isolated from the sputum (71.43%, 15/21), followed by urine (14.29%, 3/21). Twenty-one A. baumannii strains possessed a multidrug-resistant (MDR) profile, and whole-genome sequencing showed that they all carried blaOXA-23. Based on the Pasteur multilocus sequence typing (MLST) scheme, all strains were typed into a sequence type 2 (ST2). Based on the Oxford MLST scheme, six strains belonged to ST540, three of which were ST208, and four strains were assigned to ST784. Kaptive showed most of the strains (38.10%, 8/21) contained KL93. As for the lipoolygosaccharide (OC locus) type, OCL1c and OCL1d were identified, accounting for 33.33% (7/21) and 66.67% (14/21), respectively. Based on the BacWGSTdb server, we found that the strains belonging to ST540 and ST784 were all collected from China. However, the ST938 strains were isolated from Malaysia and Thailand. Comparative genomics analysis showed that the AB10 strain had a closed relationship with SXAB10-SXAB13 strains, suggesting the transmission happened in these two hospitals and other hospital in China. In addition, the 4300STDY7045869 strain, which was collected from Thailand, possessed near genetic relationship with our isolates in this study, suggesting the possible spread among various countries. Additionally, 3-237 single nucleotide polymorphisms were observed among these strains. In conclusion, this study conducted a genome-based study for A. baumannii strains collected from two hospitals in China and revealed their epidemiological and molecular features. Clone spreading occurred in these two hospitals. Hence, there is an urgent need for increased surveillance in hospitals and other clinical settings to prevent and control CRAB spreading.

Comparative evaluating laser ionization and iKnife coupled with rapid evaporative ionization mass spectrometry and machine learning for geographical authentication of Larimichthys crocea.

Larimichthys crocea (LYC) holds significant economic value as a marine fish species. However, inaccuracies in labeling its origin can adversely affect consumer interests. Herein, a laser assisted rapid evaporative ionization mass spectrometry (LA-REIMS) and machine learning (ML) was developed for geographical authentication. When compared to iKnife, the LA demonstrated to be superior owing to reduced thermal damage to sample tissue, enhanced automation, and ease of use. Analysis of LYC from six distinct geographical origins across China revealed a total of 798 ions, which were then subjected to six classifiers to establish ML models. Following hyperparameter optimization and feature engineering, the Chi2(15%)-KNN model exhibited the highest training and testing accuracy, achieving 98.4 ± 0.9% and 98.5 ± 1.4%, respectively. This LA-REIMS/ML methodology offers a rapid, accurate, and intelligent solution for tracing the origin of LYC, thereby providing valuable technical support for the establishment of traceability systems in the aquatic product industry.

Adaptive Zone Learning for Weakly Supervised Object Localization.

Weakly supervised object localization (WSOL) stands as a pivotal endeavor within the realm of computer vision, entailing the location of objects utilizing merely image-level labels. Contemporary approaches in WSOL have leveraged FPMs, yielding commendable outcomes. However, these existing FPM-based techniques are predominantly confined to rudimentary strategies of either augmenting the foreground or diminishing the background presence. We argue for the exploration and exploitation of the intricate interplay between the object's foreground and its background to achieve efficient object localization. In this manuscript, we introduce an innovative framework, termed adaptive zone learning (AZL), which operates on a coarse-to-fine basis to refine FPMs through a triad of adaptive zone mechanisms. First, an adversarial learning mechanism (ALM) is employed, orchestrating an interplay between the foreground and background regions. This mechanism accentuates coarse-grained object regions in a mutually adversarial manner. Subsequently, an oriented learning mechanism (OLM) is unveiled, which harnesses local insights from both foreground and background in a fine-grained manner. This mechanism is instrumental in delineating object regions with greater granularity, thereby generating better FPMs. Furthermore, we propose a reinforced learning mechanism (RLM) as the compensatory mechanism for adversarial design, by which the undesirable foreground maps are refined again. Extensive experiments on CUB-200-2011 and ILSVRC datasets demonstrate that AZL achieves significant and consistent performance improvements over other state-of-the-art WSOL methods.

Structural basis for recruitment of peptidoglycan endopeptidase MepS by lipoprotein NlpI.

Peptidoglycan (PG) sacculi surround the cytoplasmic membrane, maintaining cell integrity by withstanding internal turgor pressure. During cell growth, PG endopeptidases cleave the crosslinks of the fully closed sacculi, allowing for the incorporation of new glycan strands and expansion of the peptidoglycan mesh. Outer-membrane-anchored NlpI associates with hydrolases and synthases near PG synthesis complexes, facilitating spatially close PG hydrolysis. Here, we present the structure of adaptor NlpI in complex with the endopeptidase MepS, revealing atomic details of how NlpI recruits multiple MepS molecules and subsequently influences PG expansion. NlpI binding elicits a disorder-to-order transition in the intrinsically disordered N-terminal of MepS, concomitantly promoting the dimerization of monomeric MepS. This results in the alignment of two asymmetric MepS dimers respectively located on the two opposite sides of the dimerization interface of NlpI, thus enhancing MepS activity in PG hydrolysis. Notably, the protein level of MepS is primarily modulated by the tail-specific protease Prc, which is known to interact with NlpI. The structure of the Prc-NlpI-MepS complex demonstrates that NlpI brings together MepS and Prc, leading to the efficient MepS degradation by Prc. Collectively, our results provide structural insights into the NlpI-enabled avidity effect of cellular endopeptidases and NlpI-directed MepS degradation by Prc.

A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multi-Modal.

Knowledge graph reasoning (KGR), aiming to deduce new facts from existing facts based on mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research direction. It has been proven to significantly benefit the usage of KGs in many AI applications, such as question answering, recommendation systems, and etc. According to the graph types, existing KGR models can be roughly divided into three categories, i.e., static models, temporal models, and multi-modal models. Early works in this domain mainly focus on static KGR, and recent works try to leverage the temporal and multi-modal information, which are more practical and closer to real-world. However, no survey papers and open-source repositories comprehensively summarize and discuss models in this important direction. To fill the gap, we conduct a first survey for knowledge graph reasoning tracing from static to temporal and then to multi-modal KGs. Concretely, the models are reviewed based on bi-level taxonomy, i.e., top-level (graph types) and base-level (techniques and scenarios). Besides, the performances, as well as datasets, are summarized and presented. Moreover, we point out the challenges and potential opportunities to enlighten the readers. The corresponding open-source repository is shared on GitHub https://github.com/LIANGKE23/Awesome-Knowledge-Graph-Reasoning.

Natural Language Processing-Powered Real-Time Monitoring Solution for Vaccine Sentiments and Hesitancy on Social Media: System Development and Validation.

BACKGROUND: Vaccines serve as a crucial public health tool, although vaccine hesitancy continues to pose a significant threat to full vaccine uptake and, consequently, community health. Understanding and tracking vaccine hesitancy is essential for effective public health interventions; however, traditional survey methods present various limitations. OBJECTIVE: This study aimed to create a real-time, natural language processing (NLP)-based tool to assess vaccine sentiment and hesitancy across 3 prominent social media platforms. METHODS: We mined and curated discussions in English from Twitter (subsequently rebranded as X), Reddit, and YouTube social media platforms posted between January 1, 2011, and October 31, 2021, concerning human papillomavirus; measles, mumps, and rubella; and unspecified vaccines. We tested multiple NLP algorithms to classify vaccine sentiment into positive, neutral, or negative and to classify vaccine hesitancy using the World Health Organization's (WHO) 3Cs (confidence, complacency, and convenience) hesitancy model, conceptualizing an online dashboard to illustrate and contextualize trends. RESULTS: We compiled over 86 million discussions. Our top-performing NLP models displayed accuracies ranging from 0.51 to 0.78 for sentiment classification and from 0.69 to 0.91 for hesitancy classification. Explorative analysis on our platform highlighted variations in online activity about vaccine sentiment and hesitancy, suggesting unique patterns for different vaccines. CONCLUSIONS: Our innovative system performs real-time analysis of sentiment and hesitancy on 3 vaccine topics across major social networks, providing crucial trend insights to assist campaigns aimed at enhancing vaccine uptake and public health.

Environmental fate and safety analysis of methoxyfenozide application to control litchi and longan pests.

Litchi and longan pests significantly affect crop yield and quality. Chemical prevention and control are very effective for production; therefore, it is crucial to study fate assessment and appropriate field efficacy before pesticide application on crops to appropriately assess the health and ecological risks linked with these agents. This study conducted Good Agricultural Practice (GAP) field trials and laboratory experiments to elucidate the dissipation, terminal residues, and efficacy of methoxyfenozide on litchi and longan in six locations throughout China. To detect methoxyfenozide residues on litchi and longan, a QuEChERS/UPLC-MS/MS-based method was designed. The initial methoxyfenozide levels in litchi and longan ranged from 2.21-2.86 to 0.83-0.95 mg kg-1 and indicated half-lives of 5.1-5.3 and 5.3-5.7 days, respectively. After 7 days of foliage treatment, the concentrations of terminal methoxyfenozide residue were 0.78-2.61 and 0.02-1.01 mg kg-1, which were less than the established maximum residue limit for methoxyfenozide in litchi and longan. The chronic (acceptable daily intake = 0.0055-0.0331%) dietary intake risk analysis for methoxyfenozide in longan and litchi indicated acceptable concentrations of terminal residue for the general population. Methoxyfenozide in litchi and longan was readily degraded in first-order kinetics models, the degradation rate on longan was higher than that on litchi, and their dietary risks were negligible to consumers. Two hundred forty grams per liter of methoxyfenozide suspension concentrate (SC) represents a highly efficacious insecticidal dose to control litchi and longan pests and indicates a significant application potential as it is rapidly degraded and linked with reduced post-treatment residue levels.

Antigout effects and mechanisms of total flavonoids from prunus tomentosa.

BACKGROUND: In recent years, hyperuricemia and acute gouty arthritis have become increasingly common, posing a serious threat to public health. Current treatments primarily involve Western medicines with associated toxic side effects. OBJECTIVE: This study aims to investigate the therapeutic effects of total flavones from Prunus tomentosa (PTTF) on a rat model of gout and explore the mechanism of PTTF's anti-gout action through the TLR4/NF-κB signaling pathway. METHODS: We measured serum uric acid (UA), creatinine (Cr), blood urea nitrogen (BUN), tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1ß), and interleukin-6 (IL-6) levels using an enzyme-linked immunosorbent assay (ELISA). Histopathological changes were observed using HE staining, and the expression levels of relevant proteins were detected through Western blotting. RESULTS: After PTTF treatment, all indicators improved significantly. PTTF reduced blood levels of UA, Cr, BUN, IL-1ß, IL-6, and TNF-α, and decreased ankle swelling. CONCLUSIONS: PTTF may have a therapeutic effect on animal models of hyperuricemia and acute gouty arthritis by reducing serum UA levels, improving ankle swelling, and inhibiting inflammation. The primary mechanism involves the regulation of the TLR4/NF-κB signaling pathway to alleviate inflammation. Further research is needed to explore deeper mechanisms.

Apigenin suppresses epithelial-mesenchymal transition in high glucose-induced retinal pigment epithelial cell by inhibiting CBP/p300-mediated histone acetylation.

Epithelial mesenchymal transition (EMT) is a critical process implicated in the pathogenesis of retinal fibrosis and the exacerbation of diabetic retinopathy (DR) within retinal pigment epithelium (RPE) cells. Apigenin (AP), a potential dietary supplement for managing diabetes and its associated complications, has demonstrated inhibitory effects on EMT in various diseases. However, the specific impact and underlying mechanisms of AP on EMT in RPE cells remain poorly understood. In this study, we have successfully validated the inhibitory effects of AP on high glucose-induced EMT in ARPE-19 cells and diabetic db/db mice. Notably, our findings have identified CBP/p300 as a potential therapeutic target for EMT in RPE cells and have further substantiated that AP effectively downregulates the expression of EMT-related genes by attenuating the activity of CBP/p300, consequently reducing histone acetylation alterations within the promoter region of these genes. Taken together, our results provide novel evidence supporting the inhibitory effect of AP on EMT in RPE cells, and highlight the potential of specifically targeting CBP/p300 as a strategy for inhibiting retinal fibrosis in the context of DR.

Laponite-activated AIE supramolecular assembly with modulating multicolor luminescence for logic digital encryption and perfluorinated pollutant detection.

Recently, the non-covalently activated supramolecular scaffold method has become a prominent research area in the field of intelligent materials. Here, the inorganic clay (LP) promoted the AIE properties of 4,4',4″,4‴-(ethene-1,1,2,2-tetrayltetrakis(benzene-4,1-diyl))tetrakis(1-ethylpyridin-1-ium) (P-TPE), showing an astonishing 42-fold enhancement of the emission intensity of the yellow-green luminescence and a 34-fold increase of the quantum yield via organic-inorganic supramolecular strategy as well as the efficient light-harvesting properties (energy transfer efficiency up to 33 %) after doping with the dye receptor Rhodamine B. Furthermore, the full-color spectral regulation, including white light, was achieved by adjusting the ratio of the donor to the acceptor component and co-assembling with the carbon dots (CD). Interestingly, this TPE-based non-covalently activated full-color supramolecular light-harvesting system (LHS) could be achieved not only in aqueous media but also in the hydrogel and the solid state. More importantly, this panchromatic tunable supramolecular LHS exhibited the multi-mode and quadruple digital logic encryption property as well as the specific detection ability towards the perfluorobutyric acid and the perfluorobutanesulfonic acid, which are harmful to human health in drinking water. This result develops a simple, convenient and effective approach for the intelligent anti-counterfeiting and the pollutant sensing.

A preliminary study on calcifying nanoparticles in dental plaque: Isolation, characterization, and potential mineralization mechanism.

OBJECTIVES: Calcifying nanoparticles (CNPs), referred to as nanobacteria (NB), are recognized to be associated with ectopic calcification. This study aims to isolate and culture CNPs from the dental plaque of patients with periodontal disease and investigate their possible role in unravelling the aetiology of periodontal disease. MATERIAL AND METHODS: Supragingival and subgingival plaques were sampled from 30 periodontitis patients for CNPs isolation and culture. Alkaline phosphatase (ALP) content changes were tracked over time. Positive samples underwent thorough morphological identification via hematoxylin and eosin (HE) staining, Alizarin red S (ARS), and transmission electron microscopy (TEM). The chemical composition of CNPs analysis involved calcium (Ca) and phosphorus (P) content determination, Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). RESULTS: The subgingival plaque dental group exhibited a higher CNPs isolation rate at 36.67% (11/30) compared to the supragingival dental plaque group at 66.67% (20/30). ALP activity varied among the positive, negative and control groups. Morphological observation characterized the CNPs as round, oval, and ellipsoid particles with Ca deposits. Chemical analysis revealed the Ca/P ratio was 0.6753. Hydroxyl, methyl, carbonate, phosphate, hydrogen phosphate, and dihydrogen phosphate were detected by FTIR; the main chemical components detected by XRD were hydroxyapatite and tricalcium phosphate. CONCLUSION: CNPs were found in periodontitis-related dental plaque and exhibited the potential to develop calcified structures resembling dental calculus. However, the potential involvement of ALP in CNPs formation requires deeper exploration, as does the precise nature of its role and the interrelation with periodontitis demand a further comprehensive investigation.

Dissipation and Safety Analysis of Dimethomorph Application in Lychee by High-Performance Liquid Chromatography-Tandem Mass Spectrometry with QuEChERS.

This study presents a method for analyzing dimethomorph residues in lychee using QuEChERS extraction and HPLC-MS/MS. The validation parameters for this method, which include accuracy, precision, linearity, and recovery, indicate that it meets standard validation requirements. Following first-order kinetics, the dissipation dynamic of dimethomorph in lychee was determined to range from 6.4 to 9.2 days. Analysis of terminal residues revealed that residues in whole lychee were substantially greater than those in the pulp, indicating that dimethomorph residues are predominantly concentrated in the peel. When applied twice and thrice at two dosage levels with pre-harvest intervals (PHIs) of 5, 7, and 10 days, the terminal residues in whole lychee ranged from 0.092 to 1.99 mg/kg. The terminal residues of the pulp ranged from 0.01 to 0.18 mg/kg, with the residue ratio of whole lychee to pulp consistently exceeding one. The risk quotient (RQ) for dimethomorph, even at the recommended dosage, was less than one, indicating that the potential for damage was negligible. This study contributes to the establishment of maximum residue limits (MRLs) in China by providing essential information on the safe application of dimethomorph in lychee orchards.

Uncovering the burden of hidradenitis suppurativa misdiagnosis and underdiagnosis: a machine learning approach.

Hidradenitis suppurativa (HS) is a chronic inflammatory follicular skin condition that is associated with significant psychosocial and economic burden and a diminished quality of life and work productivity. Accurate diagnosis of HS is challenging due to its unknown etiology, which can lead to underdiagnosis or misdiagnosis that results in increased patient and healthcare system burden. We applied machine learning (ML) to a medical and pharmacy claims database using data from 2000 through 2018 to develop a novel model to better understand HS underdiagnosis on a healthcare system level. The primary results demonstrated that high-performing models for predicting HS diagnosis can be constructed using claims data, with an area under the curve (AUC) of 81%-82% observed among the top-performing models. The results of the models developed in this study could be input into the development of an impact of inaction model that determines the cost implications of HS diagnosis and treatment delay to the healthcare system.

One-Step Multi-View Clustering With Diverse Representation.

Multi-View clustering has attracted broad attention due to its capacity to utilize consistent and complementary information among views. Although tremendous progress has been made recently, most existing methods undergo high complexity, preventing them from being applied to large-scale tasks. Multi-View clustering via matrix factorization is a representative to address this issue. However, most of them map the data matrices into a fixed dimension, limiting the model's expressiveness. Moreover, a range of methods suffers from a two-step process, i.e., multimodal learning and the subsequent k -means, inevitably causing a suboptimal clustering result. In light of this, we propose a one-step multi-view clustering with diverse representation (OMVCDR) method, which incorporates multi-view learning and k -means into a unified framework. Specifically, we first project original data matrices into various latent spaces to attain comprehensive information and auto-weight them in a self-supervised manner. Then, we directly use the information matrices under diverse dimensions to obtain consensus discrete clustering labels. The unified work of representation learning and clustering boosts the quality of the final results. Furthermore, we develop an efficient optimization algorithm with proven convergence to solve the resultant problem. Comprehensive experiments on various datasets demonstrate the promising clustering performance of our proposed method. The code is publicly available at https://github.com/wanxinhang/OMVCDR.

Traditional herbal medicine: Therapeutic potential in acute gouty arthritis.

ETHNOPHARMACOLOGICAL RELEVANCE: Acute gouty arthritis (AGA) is characterized by a rapid inflammatory reaction caused by the build-up of monosodium urate (MSU) crystals in the tissues surrounding the joints. This condition often associated with hyperuricemia (HUA), is distinguished by its symptoms of intense pain, active inflammation, and swelling of the joints. Traditional approaches in AGA management often fall short of desired outcomes in clinical settings. However, recent ethnopharmacological investigations have been focusing on the potential of Traditional Herbal Medicine (THM) in various forms, exploring their therapeutic impact and targets in AGA treatment. AIM OF THE REVIEW: This review briefly summarizes the current potential pharmacological mechanisms of THMs - including active ingredients, extracts, and prescriptions -in the treatment of AGA, and discusses the relevant potential mechanisms and molecular targets in depth. The objective of this study is to offer extensive information and a reference point for the exploration of targeted AGA treatment using THMs. MATERIALS AND METHODS: This review obtained scientific publications focused on in vitro and in vivo studies of anti-AGA THMs conducted between 2013 and 2023. The literature was collected from various journals and electronic databases, including PubMed, Elsevier, ScienceDirect, Web of Science, and Google Scholar. The retrieval and analysis of relevant articles were guided by keywords such as "acute gouty arthritis and Chinese herbal medicine," "acute gouty arthritis herbal prescription," "acute gouty arthritis and immune cells," "acute gouty arthritis and inflammation," "acute gouty arthritis and NOD-like receptor thermoprotein domain associated protein 3 (NLRP3)," "acute gouty arthritis and miRNA," and "acute gouty arthritis and oxidative stress." RESULTS: We found that AGA has a large number of therapeutic targets, highlighting the effectiveness the potential of THMs in AGA treatment through in vitro and in vivo studies. THMs and their active ingredients can mitigate AGA symptoms through a variety of therapeutic targets, such as influencing macrophage polarization, neutrophils, T cells, natural killer (NK) cells, and addressing factors like inflammation, NLRP3 inflammasome, signaling pathways, oxidative stress, and miRNA multi-target interactions. The anti-AGA properties of THMs, including their active components and prescriptions, were systematically summarized and categorized based on their respective therapeutic targets. CONCLUSION: phenolic, flavonoid, terpenoid and alkaloid compounds in THMs are considered the key ingredients to improve AGA. THMs and their active ingredients achieve enhanced efficacy through interactions with multiple targets, of which NLRP3 is a main therapeutic target. Nonetheless, given the intricate composition of traditional Chinese medicine (TCM), additional research is required to unravel the underlying mechanisms and molecular targets through which THMs alleviate AGA.