Integrated analysis of m6A regulator-mediated RNA methylation modification patterns and immune characteristics in Sjögren's syndrome.

The epigenetic modifier N6-methyladenosine (m6A), recognized as the most prevalent internal modification in messenger RNA (mRNA), has recently emerged as a pivotal player in immune regulation. Its dysregulation has been implicated in the pathogenesis of various autoimmune conditions. However, the implications of m6A modification within the immune microenvironment of Sjögren's syndrome (SS), a chronic autoimmune disorder characterized by exocrine gland dysfunction, remain unexplored. Herein, we leverage an integrative analysis combining public database resources and novel sequencing data to investigate the expression profiles of m6A regulatory genes in SS. Our cohort comprised 220 patients diagnosed with SS and 62 healthy individuals, enabling a comprehensive evaluation of peripheral blood at the transcriptomic level. We report a significant association between SS and altered expression of key m6A regulators, with these changes closely tied to the activation of CD4+ T cells. Employing a random forest (RF) algorithm, we identified crucial genes contributing to the disease phenotype, which facilitated the development of a robust diagnostic model via multivariate logistic regression analysis. Further, unsupervised clustering revealed two distinct m6A modification patterns, which were significantly associated with variations in immunocyte infiltration, immune response activity, and biological function enrichment in SS. Subsequently, we proceeded with a screening process aimed at identifying genes that were differentially expressed (DEGs) between the two groups distinguished by m6A modification. Leveraging these DEGs, we employed weight gene co-expression network analysis (WGCNA) to uncover sets of genes that exhibited strong co-variance and hub genes that were closely linked to m6A modification. Through rigorous analysis, we identified three critical m6A regulators - METTL3, ALKBH5, and YTHDF1 - alongside two m6A-related hub genes, COMMD8 and SRP9. These elements collectively underscore a complex but discernible pattern of m6A modification that appears to be integrally linked with SS's pathogenesis. Our findings not only illuminate the significant correlation between m6A modification and the immune microenvironment in SS but also lay the groundwork for a deeper understanding of m6A regulatory mechanisms. More importantly, the identification of these key regulators and hub genes opens new avenues for the diagnosis and treatment of SS, presenting potential targets for therapeutic intervention.

Effect of dietary supplementation Ampelopsis grossedentata extract on growth performance and muscle nutrition of Megalobrama hoffmanni by gut bacterial mediation.

Nowadays, Megalobrama hoffmanni is a typical cultured fish in south China due to its resource decline in the Pearl River. Meanwhile, since antibiotics had been banned internationally, Chinese medical herbal plant serving as alternative to antibiotics has been adopted in aquaculture. In the present study, to ensure the health growth of M. hoffmanni, extract of traditional medical herbal plant Ampelopsis grossedentata was dietary supplemented and a series experiments were performed, including growth performance determination, physiological/biochemical detection, nutrition analysis, histology analysis, and 16S rRNA amplicon sequencing. Growth performance enhancement was determined since the weight gain rate (WGR), specific growth rate (SGR), and condition factor (CF) of M. hoffmanni increased as feeding inclusion A. grossedentata extract. Interestingly, the total content of muscle fatty acids ascended via supplementing A. grossedentata extract at middle level, in which group the activities of superoxide dismutase (SOD) and catalase (CAT) significantly increased and thus retarded the lipid peroxidation process (manifesting as malondialdehyde (MDA) content rising). Additionally, immune response and inflammatory reaction was stimulated in low and high level A. grossedentata extract added groups, indicating a suitable dosage of A. grossedentata extract benefited in safety production. Moreover, gut microbiota community varied hugely as daily supplementation A. grossedentata extract and the keystone species were tightly related to lipid transformation, which ultimately led to fatty acids composition variation. Our results confirmed that dietary supplementation A. grossedentata extract at the middle level (0.5‰, w/w) is suitable for serving as feed additive in healthful aquaculture of M. hoffmanni.

microRNA-15a-5p suppresses hypoxia-induced tumor growth and chemoresistance in bladder cancer by binding to eIF5A2.

In various malignant tumors (including bladder cancer) poor prognosis is associated with hypoxia and therapeutic resistance. Evidence indicates that in bladder cancer, microRNAs (miRNAs) have vital functions in acquired drug resistance. However, the involvement of miRNAs in hypoxia-mediated bladder cancer doxorubicin (Dox) resistance is unknown. Herein, we showed that hypoxia and Dox treatment downregulated miR-15a-5p expression. Using UM-UC-3 and J82 bladder cancer cell lines and in vivo mouse models of bladder cancer, we confirmed that miR-15a-5p arrests tumor cell growth and Dox resistance in vitro and in vivo. Furthermore, we determined the interaction between miR-15a-5p and eukaryotic translation initiation factor 5A-2 (eIF5A2) using dual luciferase reporters and quantitative real-time reverse transcription polymerase chain reaction assays. We also showed that a miR-15a-5p agomir repressed EIF5A2 expression in bladder cancer cells, thereby inhibiting the epithelial-mesenchymal transition (EMT) induced by Dox or hypoxia. Moreover, ectopic expression of miR-15a-5p abrogated eIF5A2-mediated Dox resistance in bladder cancer cells. Collectively, these data indicated that hypoxia promotes tumor growth and chemoresistance through the HIF-1α/miR-15a-5p/eIFTA2/EMT pathway. This new finding not only has implications for improving our understanding of the Dox resistance process during bladder cancer progression but also indicates that the miR-15a-5p agomir is a promising tool to prevent Dox resistance in patients with bladder cancer.

MoDAFold: a strategy for predicting the structure of missense mutant protein based on AlphaFold2 and molecular dynamics.

Protein structure prediction is a longstanding issue crucial for identifying new drug targets and providing a mechanistic understanding of protein functions. To enhance the progress in this field, a spectrum of computational methodologies has been cultivated. AlphaFold2 has exhibited exceptional precision in predicting wild-type protein structures, with performance exceeding that of other methods. However, predicting the structures of missense mutant proteins using AlphaFold2 remains challenging due to the intricate and substantial structural alterations caused by minor sequence variations in the mutant proteins. Molecular dynamics (MD) has been validated for precisely capturing changes in amino acid interactions attributed to protein mutations. Therefore, for the first time, a strategy entitled 'MoDAFold' was proposed to improve the accuracy and reliability of missense mutant protein structure prediction by combining AlphaFold2 with MD. Multiple case studies have confirmed the superior performance of MoDAFold compared to other methods, particularly AlphaFold2.

The impact of clinical and laboratory parameters on clinical pregnancy and live birth rates in fresh cycles: a retrospective study of 9608 high-quality cleavage-stage embryos.

BACKGROUND: Evidence from the Istanbul consensus workshop suggests correlations between morphological parameters and embryo developments. 8-cell embryos are the best blastomere stage on day 3. No good quality evidence exists to support high-quality embryonic selection following blastulation and clinical outcomes. This study aimed to investigate the factors that affect blastocyst formation, blastocyst quality, and clinical outcomes of high-quality cleavage-stage embryos in fresh cycles. METHODS: This study was a retrospective analysis of 9608 high-quality cleavage-stage embryos from 2987 couples between January 2017 to June 2021, namely 1520 embryos categorized as "812" (8-cell, grade 2, mild fragmentation), 2961 as "821" (8-cell, grade 2, mild asymmetry), 896 as "711" (7-cell, grade 1), and 517 as "911" (9-cell, grade 1) compared with 3714 embryos categorized as "811" (8-cell, grade 1). The primary outcomes were clinical pregnancy rate (CPR) and live birth rate (LBR). Blastulation rate (BR), available late blastocyst rate (ABR) and high-quality late blastocyst rate (HBR) were secondary outcome measures. RESULTS: BR, ABR, and HBR had significant differences among the five groups (P < 0.001), while CPR and LBR were also significantly different in cleavage-stage fresh transfer (P < 0.01). The multivariable multilevel logistic regression analysis revealed a significant association between cell number, cell size, blastocyst development and clinical outcomes. For 7 to 9-cell highest-quality embryo, mild fragmentation and more blastomeres were more conducive to blastocyst formation and clinical outcomes. While cleavage-stage embryos developed into blastocysts, the negative impact of their initial morphology on clinical outcomes would be erased. CONCLUSIONS: Our study firstly evaluated blastocyst development and clinical outcomes of high-quality cleavage-stage embryos in fresh cycles, with rankings of 811, 812, 911, 821, and 711. We found the initial morphological characteristics of the high-quality cleavage-stage embryos did not adversely impact clinical outcomes, even as they progressed to the blastocyst stage.

AnnoPRO: a strategy for protein function annotation based on multi-scale protein representation and a hybrid deep learning of dual-path encoding.

Protein function annotation has been one of the longstanding issues in biological sciences, and various computational methods have been developed. However, the existing methods suffer from a serious long-tail problem, with a large number of GO families containing few annotated proteins. Herein, an innovative strategy named AnnoPRO was therefore constructed by enabling sequence-based multi-scale protein representation, dual-path protein encoding using pre-training, and function annotation by long short-term memory-based decoding. A variety of case studies based on different benchmarks were conducted, which confirmed the superior performance of AnnoPRO among available methods. Source code and models have been made freely available at: https://github.com/idrblab/AnnoPRO and https://zenodo.org/records/10012272.

Lysine acetyltransferase 6A maintains CD4+ T cell response via epigenetic reprogramming of glucose metabolism in autoimmunity.

Augmented CD4+ T cell response in autoimmunity is characterized by extensive metabolic reprogramming. However, the epigenetic molecule that drives the metabolic adaptation of CD4+ T cells remains largely unknown. Here, we show that lysine acetyltransferase 6A (KAT6A), an epigenetic modulator that is clinically associated with autoimmunity, orchestrates the metabolic reprogramming of glucose in CD4+ T cells. KAT6A is required for the proliferation and differentiation of proinflammatory CD4+ T cell subsets in vitro, and mice with KAT6A-deficient CD4+ T cells are less susceptible to experimental autoimmune encephalomyelitis and colitis. Mechanistically, KAT6A orchestrates the abundance of histone acetylation at the chromatin where several glycolytic genes are located, thus affecting glucose metabolic reprogramming and subsequent CD4+ T cell responses. Treatment with KAT6A small-molecule inhibitors in mouse models shows high therapeutic value for targeting KAT6A in autoimmunity. Our study provides novel insights into the epigenetic programming of immunometabolism and suggests potential therapeutic targets for patients with autoimmunity.

Effect of Fermented Artemisia argyi on Egg Quality, Nutrition, and Flavor by Gut Bacterial Mediation.

To improve the palatability of Artemisia argyi, fermented A. argyi (AAF) were prepared by Lactobacillus plantarum and Saccharomyces cerevisiae, which were used in the hen industry subsequently. Six hundred hens were randomly divided into three groups: control (A), dietary supplementation AAF at a low level (B), and dietary supplementation AAF at a high level (C). After feeding for four months, egg production, egg quality, egg nutrition, egg flavor, plasma biochemical parameters, intestinal histology, and microbiome of the gut contents were analyzed among the three tested groups. Interestingly, 5-6 percentage points elevation in the laying rates were observed in the AAF-supplemented groups in comparison to the control, accompanied with a 5 g increase in daily feed consumption. Since no alteration in egg/body weights was detected, laying performance enhancement was the main effect of dietary supplementation AAF. Meanwhile, the compositions of the egg amino acids and fatty acids changed as the feed inclusion AAF changed, e.g., His and linoleic acid decreased almost 0.1 and 0.5 g/100 g, respectively, while oleic acid increased almost 0.4 g/100 g. In addition, although no significant difference was detected (p > 0.05), the ß-diversity of the gut microbiota decreased as the diet addition of AAF decreased, and probiotics (Faecalibacterium, Prevotellaceae, Intestinimonas, and Lachnospiraceae) were the dominant keystone species under AAF treatments. These probiotics were well associated with the egg nutrition component variations based on the correlation analysis, as the Sankey plot showed. Furthermore, the results of headspace-gas chromatography-ion mobility spectrometry manifested that the egg volatile components varied (e.g., the contents of acetone, 4-methyl-3-penten-2-one, 1-hydroxy-2-propanone, ethyl acetate, ethyl octanoate, ethanol, and 2-butanol in the B and C groups were higher than in the A group) and separated clearly as daily supplementation AAF, indicating AAF hugely contributed to the egg flavor variation. Due to no significant differences noticed between the B and C groups, dietary supplementation AAF at a relative low level was enough to serve as a feed attractant in the hen industry for real feeding.

A task-specific encoding algorithm for RNAs and RNA-associated interactions based on convolutional autoencoder.

RNAs play essential roles in diverse physiological and pathological processes by interacting with other molecules (RNA/protein/compound), and various computational methods are available for identifying these interactions. However, the encoding features provided by existing methods are limited and the existing tools does not offer an effective way to integrate the interacting partners. In this study, a task-specific encoding algorithm for RNAs and RNA-associated interactions was therefore developed. This new algorithm was unique in (a) realizing comprehensive RNA feature encoding by introducing a great many of novel features and (b) enabling task-specific integration of interacting partners using convolutional autoencoder-directed feature embedding. Compared with existing methods/tools, this novel algorithm demonstrated superior performances in diverse benchmark testing studies. This algorithm together with its source code could be readily accessed by all user at: https://idrblab.org/corain/ and https://github.com/idrblab/corain/.

Nanomaterial-based biosensors for the detection of foodborne bacteria: a review.

Ensuring food safety is a critical concern for the development and well-being of humanity, as foodborne illnesses caused by foodborne bacteria have increasingly become a major public health concern worldwide. Traditional food safety monitoring systems are expensive and time-consuming, relying heavily on specialized equipment and operations. Therefore, there is an urgent need to develop low-cost, user-friendly and highly sensitive biosensors for detecting foodborne bacteria. In recent years, the combination of nanomaterials with optical biosensors has provided a prospective future platform for the detection of foodborne bacteria. By harnessing the unique properties of nanomaterials, such as their high surface area-to-volume ratio and exceptional sensitivity, in tandem with the precision of optical biosensing techniques, a new prospect has opened up for the rapid and accurate identification of potential bacterial contaminants in food. This review focuses on recent advances and new trends of nanomaterial-based biosensors for the detection of foodborne pathogens, which mainly include noble metal nanoparticles (NMPs), metal organic frameworks (MOFs), graphene nanomaterials, quantum dot (QD) nanomaterials, upconversion fluorescent nanomaterials (UCNPs) and carbon dots (CDs). Additionally, we summarized the research progress of color indicators, nanozymes, natural enzyme vectors and fluorescent dye biosensors, focusing on the advantages and disadvantages of nanomaterial-based biosensors and their development prospects. This review provides an outlook on future technological directions and potential applications to help identify the most promising areas of development in this field.

Lactate-induced mtDNA Accumulation Activates cGAS-STING Signaling and the Inflammatory Response in Sjögren's Syndrome.

Acinar epithelial cell atrophy in secretory glands is a hallmark of primary Sjögren's syndrome (pSS), the cause of which is far from elucidated. We examined the role of acinar atrophy by focusing on the metabolism of glandular epithelial cells and mitochondria in the pSS environment. After confirming the presence of a high-lactate environment in the labial glands of human pSS patients, we used the A253 cell line and NOD/Ltj mice as models to investigate the metabolic changes in salivary gland epithelial cells in a high-lactate environment in vitro and in vivo. We found that epithelial cells produced high levels of IL-6, IL-8, IFN-α, IFN-ß and TNF-α and exhibited significant NF-κB and type I IFN-related pathway activation. The results confirmed that lactate damaged mitochondrial DNA (mtDNA) and led to its leakage, which subsequently activated the cGAS-STING pathway. Inflammatory cytokine production and pathway activation were inhibited in vivo and in vitro by the lactate scavenger sodium dichloroacetate (DCA). Our study provides new insights into the etiology and treatment of pSS from the perspective of cell metabolism.

Discrimination rancidity degree of infant formula rice flour based on Headspace Solid-Phase Microextraction combined with Gas Chromatography-Mass Spectrometry as an alternative to sensory evaluation.

To mitigating the serious threat of harmful volatile substances to the health of infants, an alternative method of odor evaluation were proposed based on Headspace solid-phase microextraction (HS-SPME) combined with Gas Chromatography-Mass Spectrometry (GC-MS) to discriminate the degree of rancidity of infant formula rice flour (IFRF). Inspectors can simply calculate the rancidity degree of infant formula rice flour according to the regression equation based on the concentration of rancidity markers. The results showed that the joint application of OPLS-DA, molecular sensory experiments, and unsaturated fatty acids (UFAs) degradation experiments could successfully recognize the rancidity markers without collinearity in multiple linear regression analysis. The rancidity markers curve fitting was helpful for the establishment of multivariate regression model of rancidity grading. The model had an accuracy of more than 92.90% by the verification of odor evaluation. The application of the model to investigate the market IFRF samples showed that about 3% of the samples collected in the experiment were unsuitable for infant feeding. Therefore, the established model was considered to be a robust and less workload method to replace the olfactory evaluation method for discriminating the rancidity degree of IFRF.

A Transformer-Based Ensemble Framework for the Prediction of Protein-Protein Interaction Sites.

The identification of protein-protein interaction (PPI) sites is essential in the research of protein function and the discovery of new drugs. So far, a variety of computational tools based on machine learning have been developed to accelerate the identification of PPI sites. However, existing methods suffer from the low predictive accuracy or the limited scope of application. Specifically, some methods learned only global or local sequential features, leading to low predictive accuracy, while others achieved improved performance by extracting residue interactions from structures but were limited in their application scope for the serious dependence on precise structure information. There is an urgent need to develop a method that integrates comprehensive information to realize proteome-wide accurate profiling of PPI sites. Herein, a novel ensemble framework for PPI sites prediction, EnsemPPIS, was therefore proposed based on transformer and gated convolutional networks. EnsemPPIS can effectively capture not only global and local patterns but also residue interactions. Specifically, EnsemPPIS was unique in (a) extracting residue interactions from protein sequences with transformer and (b) further integrating global and local sequential features with the ensemble learning strategy. Compared with various existing methods, EnsemPPIS exhibited either superior performance or broader applicability on multiple PPI sites prediction tasks. Moreover, pattern analysis based on the interpretability of EnsemPPIS demonstrated that EnsemPPIS was fully capable of learning residue interactions within the local structure of PPI sites using only sequence information. The web server of EnsemPPIS is freely available at http://idrblab.org/ensemppis.

Metagenomic next-generation sequencing for the diagnosis of oral and maxillofacial space infections.

Background/purpose: Metagenomic next-generation sequencing (mNGS) has been widely used for the detection of pathogens causing infectious diseases. This study aimed to evaluate the potential ability of mNGS to detect pathogens causing oral and maxillofacial space infection (OMSI) and compare the results with those of the traditional diagnostic microbial culture method. Materials and methods: We retrospectively reviewed the data of 218 patients diagnosed with OMSI who underwent microbial culture and mNGS at the Department of Oral Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, from July 2020 to January 2022. Results: The positivity rate of mNGS (216 cases) was significantly higher than that of microbial culture (123 cases). The most frequently detected bacteria were different between these two detection methods. Streptococcus constellatus (16.05%, 35), Streptococcus anginosus (15.69%, 34) and Klebsiella pneumoniae (6.88%, 15) were the most commonly isolated bacteria by culture. However, Peptostreptococcus stomatis (61.47%, 134), Parvimonas micra (68.35%, 149) and Streptococcus constellatus (57.34%, 125) were the most commonly detected bacteria by mNGS. mNGS also has advantages in diagnosing viral infections. The optimal numbers of diagnostic reads were 1162 and 588 for the diagnosis of Streptococcus anginosus and Streptococcus constellatus infections, respectively. Read numbers were significantly correlated with C-reactive protein (CRP), procalcitonin (PCT), and blood glucose levels and neutrophil percentage (NEUT%). Conclusion: For pathogens causing OMSI, mNGS had a higher rate of microbial pathogen detection and remarkable advantages in identifying coinfections involving viruses and fungi. The read numbers for mNGS are important for diagnostic accuracy and disease severity evaluation.

HECT, UBA and WWE domain containing 1 represses cholesterol efflux during CD4+ T cell activation in Sjögren's syndrome.

Introduction: Sjögren's syndrome (SS) is a chronic autoimmune disorder characterized by exocrine gland dysfunction, leading to loss of salivary function. Histological analysis of salivary glands from SS patients reveals a high infiltration of immune cells, particularly activated CD4+ T cells. Thus, interventions targeting abnormal activation of CD4+ T cells may provide promising therapeutic strategies for SS. Here, we demonstrate that Hect, uba, and wwe domain containing 1 (HUWE1), a member of the eukaryotic Hect E3 ubiquitin ligase family, plays a critical role in CD4+ T-cell activation and SS pathophysiology. Methods: In the context of HUWE1 inhibition, we investigated the impact of the HUWE1 inhibitor BI8626 and sh-Huwe1 on CD4+ T cells in mice, focusing on the assessment of activation levels, proliferation capacity, and cholesterol abundance. Furthermore, we examined the therapeutic potential of BI8626 in NOD/ShiLtj mice and evaluated its efficacy as a treatment strategy. Results: Inhibition of HUWE1 reduces ABCA1 ubiquitination and promotes cholesterol efflux, decreasing intracellular cholesterol and reducing the expression of phosphorylated ZAP-70, CD25, and other activation markers, culminating in the suppressed proliferation of CD4+ T cells. Moreover, pharmacological inhibition of HUWE1 significantly reduces CD4+ T-cell infiltration in the submandibular glands and improves salivary flow rate in NOD/ShiLtj mice. Conclusion: These findings suggest that HUWE1 may regulate CD4+ T-cell activation and SS development by modulating ABCA1-mediated cholesterol efflux and presents a promising target for SS treatment.

Endocrine profiles and cycle characteristics of infertile 17α-hydroxylase/17,20-lyase Deficiency Patients undergoing assisted Reproduction Treatment: a retrospective cohort study.

BACKGROUND: 17α-hydroxylase/17,20-lyase deficiency (17-OHD) is a rare form of congenital adrenal hyperplasia caused by CYP17A1 gene variants. Female patients with 17-OHD demonstrate a broad clinical spectrum, including oligomenorrhea or amenorrhea and infertility, often as the sole manifestation. However, no spontaneous pregnancies in affected women have been reported. OBJECTIVE: This retrospective cohort study aimed to explore the endocrine characteristics and assisted reproductive technique (ART) performance in women with 17-OHD. METHODS: Five women were referred for primary infertility in a university-affiliated hospital over an eight-year period. The endocrine profiles and cycle characteristics during a total of nine cycles of ovarian stimulation and eight cycles of frozen-thawed embryo transfer (FET) were described in details. RESULTS: Three cases had homozygous variants and two cases had compound heterozygous variants, including one novel missense variant (p.Leu433Ser) in the CYP17A1 gene. Despite dual-suppression of progesterone (P) production by glucocorticoid and gonadotropin releasing hormone agonist, gradually increased P level, relatively low estradiol concentrations and thin endometrium were observed, negating fresh embryo transfer. During FET cycles, appropriate treatment resulted in low serum P levels and adequate endometrial thickness, leading to four live births. CONCLUSIONS: Our findings demonstrate that continuous elevation of serum P during follicular growth impairs endometrial receptivity, the likely cause of female infertility in 17-OHD. Therefore, female infertility caused by 17-OHD is suggested as an indication for freeze-all strategy, with promising reproductive prognoses following segmented ovarian stimulation and FET treatment.

Molecular mechanisms and therapeutic potential of icariin in the treatment of Alzheimer's disease.

BACKGROUND: Icariin (ICA) is the main active component of Epimedium, a traditional Chinese medicine (TCM), known to enhance cognitive function in Alzheimer's disease (AD). This study aims to investigate and summarize the mechanisms through which ICA treats AD. METHODS: The PubMed and CNKI databases were utilized to review the advancements in ICA's role in AD prevention and treatment by analyzing literature published between January 2005 and April 2023. To further illustrate ICA's impact on AD development, tables, and images are included to summarize the relationships between various mechanisms. RESULTS: The study reveals that ICA ameliorates cognitive deficits in AD model mice by modulating Aß via multiple pathways, including BACE-1, NO/cGMP, Wnt/Ca2+, and PI3K/Akt signaling. ICA exhibits neuroprotective properties by inhibiting neuronal apoptosis through the suppression of ER stress in AD mice, potentially linked to NF-κB, MAPK, ERK, and PERK/Eif2α signaling pathways. Moreover, ICA may safeguard neurons by attenuating mitochondrial oxidative stress injury. ICA can also enhance learning, memory, and cognition by improving synaptic structure via regulation of the PSD-95 protein. Furthermore, ICA can mitigate neuroinflammation by inactivating microglial activity through the upregulation of PPARγ, TAK1/IKK/NF-κB, and JNK/p38 MAPK signaling pathways. CONCLUSION: This study indicates that ICA possesses multiple beneficial effects in AD treatment. Through the integration of pharmacological and molecular biological research, ICA may emerge as a promising candidate to expedite the advancement of TCM in the clinical management of AD.

The predictive value of laboratory tests in oro-maxillofacial infection of different severity.

OBJECTIVE: We aimed to investigate the value of individual laboratory tests and combinations of tests for predicting disease severity. METHODS: We retrospectively reviewed 62 patients with space infections in the oral and maxillofacial head and neck regions. Patients were divided into three groups according to severity. Laboratory tests associated with disease severity were identified. RESULTS: As the severity of infection increased, leukocytes, neutrophils, C-reactive protein (CRP), procalcitonin (PCT), soluble interleukin receptor (sILR) 2, IL6, and creatinine (CR) increased. In the ROC analysis of group 1 (moderate infection) versus group 2 (severe infection), the area under the curve (AUC) values for leukocytes (AUC = 0.724), neutrophils (AUC = 0.714), PCT (AUC = 0.762) and a combination of the 3 tests (AUC = 0.768) suggested a strong predictive value. Furthermore, in the ROC analysis of group 2 (severe infection) versus group 3 (extremely severe infection), the AUC values for CRP (AUC = 0.84), PCT (AUC = 0.799), sIL2R (AUC = 0.937), IL6 (AUC = 0.863) and a combination of the four tests (AUC = 0.943) suggested a strong predictive value. CONCLUSIONS: Leukocytes, neutrophils, and PCT were associated with multispace infection and high severity. CRP, PCT, sIL2R, and/or IL6 were associated with extremely severe infections occurring in the oral and maxillofacial head and neck regions.

SoCube: an innovative end-to-end doublet detection algorithm for analyzing scRNA-seq data.

Doublets formed during single-cell RNA sequencing (scRNA-seq) severely affect downstream studies, such as differentially expressed gene analysis and cell trajectory inference, and limit the cellular throughput of scRNA-seq. Several doublet detection algorithms are currently available, but their generalization performance could be further improved due to the lack of effective feature-embedding strategies with suitable model architectures. Therefore, SoCube, a novel deep learning algorithm, was developed to precisely detect doublets in various types of scRNA-seq data. SoCube (i) proposed a novel 3D composite feature-embedding strategy that embedded latent gene information and (ii) constructed a multikernel, multichannel CNN-ensembled architecture in conjunction with the feature-embedding strategy. With its excellent performance on benchmark evaluation and several downstream tasks, it is expected to be a powerful algorithm to detect and remove doublets in scRNA-seq data. SoCube is freely provided as an end-to-end tool on the Python official package site PyPi (https://pypi.org/project/socube/) and open-source on GitHub (https://github.com/idrblab/socube/).