Applications of single­cell omics and spatial transcriptomics technologies in gastric cancer (Review).

Gastric cancer (GC) is a prominent contributor to global cancer-related mortalities, and a deeper understanding of its molecular characteristics and tumor heterogeneity is required. Single-cell omics and spatial transcriptomics (ST) technologies have revolutionized cancer research by enabling the exploration of cellular heterogeneity and molecular landscapes at the single-cell level. In the present review, an overview of the advancements in single-cell omics and ST technologies and their applications in GC research is provided. Firstly, multiple single-cell omics and ST methods are discussed, highlighting their ability to offer unique insights into gene expression, genetic alterations, epigenomic modifications, protein expression patterns and cellular location in tissues. Furthermore, a summary is provided of key findings from previous research on single-cell omics and ST methods used in GC, which have provided valuable insights into genetic alterations, tumor diagnosis and prognosis, tumor microenvironment analysis, and treatment response. In summary, the application of single-cell omics and ST technologies has revealed the levels of cellular heterogeneity and the molecular characteristics of GC, and holds promise for improving diagnostics, personalized treatments and patient outcomes in GC.

Abelmoschus manihot (L.) medik. seeds alleviate rheumatoid arthritis by modulating JAK2/STAT3 signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Abelmoschus manihot (L.) Medik. Seeds (AMS, སོ་མ་ར་ཛ།), a Tibetan classical herbal in China, are rich in flavonoids and phenolic glycosides compounds, such as quercetin and its derivatives. Moreover, it has been found to possess anti-rheumatoid arthritis (RA) effects. Nonetheless, its anti-RA mechanism is yet unknown. AIM OF THE STUDY: This research aimed to examine the active ingredients of AMS as well as potential pharmacological mechanisms in AMS on RA. MATERIALS AND METHODS: The ultra-performance liquid chromatography-electrospray ionization-tandem multistage mass spectrometry (UPLC-ESI-IT-MSn) technique was used to determine the primary chemical components of AMS that were responsible for the therapeutic effects on RA. In addition, 36 male Wistar rats weighing between 200 and 220 g were classified at random into six groups [normal control group, collagen-induced arthritis (CIA) group, methotrexate group (positive control, 1.05 mg/kg), AMS group (157.5 mg/kg, 315 mg/kg, 630 mg/kg)]. CIA rats were given AMS extract by intragastric administration for 28 days, and their ankles were photographed to observe the degree of swelling. Further, the arthritis score, paws swelling, and body weight changes of CIA rats were determined to observe whether AMS has any effect on RA, and synovial and cartilage tissue injuries were identified by histopathology. Besides, the levels of IL-10, TNF-α, IL-1ß, INF-γ, etc. in serum were estimated by ELISA. Western blot experiments were implemented to identify the expression levels of protein involved in the JAK2/STAT3 signaling pathway in the CIA rats' synovial tissues. Moreover, the mechanisms and targets of active ingredient therapy of AMS for RA were predicted using network pharmacology and then verified using molecular docking. RESULT: In the present study, 12 compounds were detected by UPLC-ESI-IT-MSn, such as quercetin and its derivative which could be potential active ingredients that contribute to the anti-RA properties of AMS. Our in vivo studies on CIA rats revealed that an AMS-H dose of 630 mg/kg significantly improved joint damage while decreasing the arthritic index and paw swelling. Furthermore, AMS inhibited the INF-γ, IL-6, IL-17, IL-1ß, and TNF-α, levels while upregulating the expression of anti-inflammatory cytokines IL-10 and IL-4 in serum. Besides, AMS inhibited the protein Bcl-2/Bax, STAT3, and JAK2 levels, and promoted the expression of Caspase3, SOCS1, and SOCS3 in the JAK2/STAT3 pathway. Additionally, the JAK/STAT signaling pathway was found to perform a remarkable function in the AMS therapy of RA as evidenced by enrichment in GO terms and KEGG pathways. Meanwhile, data from molecular docking experiments indicated that the core targets of PIK3CA, JAK2, and SRC bound stably to the active ingredients of mimuone, 4'-methoxy-bavachromanol, and quercetin. CONCLUSION: According to these findings, the AMS could improve joint inflammation in CIA rats, and its underlying mechanism could be linked to the regulation of the JAK2/STAT3 pathway. Therefore, AMS might become a promising agent for alleviating inflammation in RA patients.

2D-HPLC-MS Technology Combined with Molecular Network for the Identification of Components in Tibetan medicine Aconitum pendulum.

In this study, a comprehensive approach was employed, utilizing 2D-HPLC-MS technology in conjunction with the molecular network to unravel the intricate chemical composition of the Tibetan medicinal plant APB. Through the implementation of 2D-HPLC, enhanced separation of complex mixtures was achieved, enabling the isolation of individual compounds for subsequent analysis. The molecular network approach further aided in elucidating structural relationships among these compounds, contributing to the determination of potential bioactive molecules. This integrated strategy efficiently identified a wide array of chemical components present within the plant. The findings revealed a diverse spectrum of chemical constituents within APB, including alkaloids, among others. This research not only advances understanding of the phytochemical profile of this traditional Tibetan medicine but also provides valuable insights into its potential therapeutic properties. The integration of 2D-HPLC-MS and molecular network proves to be a powerful tool for systematically exploring and identifying complex chemical compositions in herbal medicines, paving the way for further research and development in the field of natural product discovery.

Field Collection and Laboratory Routine Identification of Rhodiola crenulata.

The identification of medicinal materials is the premise and guarantee of drug safety. The majority of scientific researchers are bound to favor the simple, fast, effective, and inexpensive identification process of herbals. Rhodiola crenulata is a traditional Tibetan medicine grown at high altitudes, mainly distributed in Tibet, Yunnan, and Sichuan regions of China. Rhodiola crenulate possesses multiple bioactivities, such as anti-inflammatory, anti-hypoxia, and antioxidant properties, and has great potential for development. With the increasing market demand and a rapid decrease in resource content, a large number of confused products of Rhodiola crenulata have been troubling people. Therefore, this protocol introduces a standard process for the identification of Rhodiola crenulata in the field combined with routine laboratory testing. The combination of habitat, microscopic features, and thin-layer chromatography will undoubtedly identify Rhodiola crenulata quickly, efficiently, and economically, contributing to the continuous development of Tibetan medicine and the quality control of medicinal materials.

Standardized Identification of Compound Structure in Tibetan Medicine Using Ion Trap Mass Spectrometry and Multiple-Stage Fragmentation Analysis.

Tibetan medicines are complex and contain numerous unknown compounds, making in-depth research on their molecular structures crucial. Liquid chromatography-electrospray ionization time-of-flight mass spectrometry (LC-ESI-TOF-MS) is commonly used to extract Tibetan medicine; however, many unpredictable unknown compounds remain after using the spectrum database. The present article developed a universal method for identifying components in Tibetan medicine using ion trap mass spectrometry (IT-MS). The method includes standardized and programmed protocols for sample preparation, MS setting, LC prerun, method establishment, MS acquisition, multiple-stage MS operation, and manual data analysis. Two representative compounds in the Tibetan medicine Abelmoschus manihot seeds were identified using multiple-stage fragmentation, with a detailed analysis of typical compound structures. In addition, the article discusses aspects such as ion mode selection, mobile phase adjustment, scanning range optimization, collision energy control, collision mode switchover, fragmentation factors, and limitations of the method. The developed standardized analysis method is universal and can be applied to unknown compounds in Tibetan medicine.

A Multi-Task Multi-Stage Transitional Training Framework for Neural Chat Translation.

Neural chat translation (NCT) aims to translate a cross-lingual chat between speakers of different languages. Existing context-aware NMT models cannot achieve satisfactory performances due to the following inherent problems: 1) limited resources of annotated bilingual dialogues; 2) the neglect of modelling conversational properties; 3) training discrepancy between different stages. To address these issues, in this paper, we propose a multi-task multi-stage transitional (MMT) training framework, where an NCT model is trained using the bilingual chat translation dataset and additional monolingual dialogues. We elaborately design two auxiliary tasks, namely utterance discrimination and speaker discrimination, to introduce the modelling of dialogue coherence and speaker characteristic into the NCT model. The training process consists of three stages: 1) sentence-level pre-training on large-scale parallel corpus; 2) intermediate training with auxiliary tasks using additional monolingual dialogues; 3) context-aware fine-tuning with gradual transition. Particularly, the second stage serves as an intermediate phase that alleviates the training discrepancy between the pre-training and fine-tuning stages. Moreover, to make the stage transition smoother, we train the NCT model using a gradual transition strategy, i.e., gradually transiting from using monolingual to bilingual dialogues. Extensive experiments on two language pairs demonstrate the effectiveness and superiority of our proposed training framework.

Tibetan medicine Qi-Sai-Er-Sang-Dang-Song Decoction inhibits TNF-α-induced rheumatoid arthritis in human fibroblast-like synoviocytes via regulating NOTCH1/NF-κB/NLRP3 pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Qi-Sai-Er-Sang-Dang-Song Decoction (QSD, ཆུ་སེར་སེང་ལྡེང་སུམ་ཐང་།), a Tibetan classical herbal formula, is commonly used in Tibetan hospital preparation for the treatment of rheumatoid arthritis (RA). Its efficacy is to relieve inflammation, dispel cold, remove dampness, and alleviate pain. However, its anti-RA mechanism is still unclear. AIM OF THE STUDY: This study aimed to investigate the effect of QSD on rheumatoid arthritis and explore its anti-inflammatory mechanism against human fibroblast-like synoviocytes (HFLSs) by regulating the notch family of receptors (NOTCH1)/Nuclear factor-κB (NF-κB)/nucleotide-binding (NLRP3) pathway. MATERIALS AND METHODS: We used ultra-performance liquid chromatography coupled with Q-TOF mass spectrometry (UPLC-Q-TOF-MS) to identify the chemical composition of QSD. Then, HFLSs were exposed to drug-containing serum. The effect of QSD drug-containing serum on HFLS viability was detected using the cell counting kit-8 (CCK-8) assay. Next, we explored the anti-inflammatory effect of QSD using enzyme-linked immunosorbent assay (ELISA) for inflammatory factors, such as interleukin-18 (IL-18), interleukin-1ß (IL-1ß), and interleukin-6 (IL-6). The expression of NOTCH-related proteins, a member of the NOTCH1, Cleaved NOTCH1, hairy and enhancer of split-1 (HES-1), NF-κB p65, NF-κB pp65, NLRP3, and delta-like 1 (DLL-1), was examined using western blotting. Furthermore, the relative mRNA expression levels of NOTCH1, NF-κB p65, NLRP3, DLL-1, and HES-1 were detected using real-time quantitative (RT-qPCR). To explore the mechanism underlying the anti-RA effect of QSD, we the used the NOTCH signaling pathway inhibitor LY411575 and transfection with a NOTCH1 siRNA. In addition, we employed immunofluorescence to determine the expression of HES-1 and NF-κB p65 in vitro. RESULT: Our results revealed that QSD ameliorated inflammation in HFLSs. Compared with the model group, the QSD drug-containing serum group had obviously down-regulated levels of IL-18, IL-1ß, and IL-6. Consistently, the CCK-8 results showed that the QSD drug-containing serum had no obvious toxicity towards HFLSs. Moreover, both LY411575 and siNOTCH1, QSD could reduce NOTCH1, NLRP3, and HES-1 protein expression levels, and LY411575 could significantly inhibit the expression levels of NF-κB p65, NF-κB pp65, and Cleaved NOTCH1 (p < 0.05). siNOTCH1 could also suppress the expression of DLL-1. The RT-qPCR results indicated that QSD could downregulate the relative mRNA expression levels of NOTCH1, NF-κB p65, NLRP3, DLL-1, and HES-1 in HFLSs (p < 0.05). In the immunofluorescence experiment, the fluorescence intensities of HES-1 and NF-κB p65 in HFLSs were found to decrease after exposure to QSD drug-containing serum (p < 0.05). Ultimately, 44 chemical components were detected in QSD using UPLC-Q-TOF-MS. CONCLUSION: This study reveals that the QSD can markedly ameliorate inflammation induced by TNF-α on HFLS. The effect of QSD on HFLS may be exerted by inhibition of the NOTCH1/NF-κB/NLRP3 signaling pathway.

In vitro and in vivo exploration of the anti-atopic dermatitis mechanism of action of Tibetan medicine Qi-Sai-Er-Sang-Dang-Song decoction.

ETHNOPHARMACOLOGICAL RELEVANCE: Tibetan medicine Qi-Sai-Er-Sang-Dang-Song Decoction(QSD, ཆུ་སེར་སེང་ལྡེང་སུམ་ཐང་།)is a traditional Tibetan medical formulation with demonstrated clinical benefits in atopic dermatitis (AD). However, its potential mechanism and molecular targets remain to be elucidated. AIM OF THE STUDY: This study aims to explore the activity and mechanism of QSD on AD in multiple dimensions by combining in vitro and in vivo experiments with network pharmacology. MATERIALS AND METHODS: The AD effect of QSD was investigated by evaluating the levels of nitric oxide (NO) and interleukin-6 (IL-6) in the lipopolysaccharide (LPS) stimulated RAW264.7 cells. AD-like skin lesions in female BALB/c mice were induced by 2,4-dinitrochlorobenzene (DNCB). QSD or dexamethasone (positive control) were gavagely administered daily for 15 consecutive days. The body weight and skin lesion severity were recorded throughout the study. Enzyme-linked immunosorbent assay (ELISA) and Western blot (WB) analysis were used to illuminate the molecular targets associated with the anti-AD effects of QSD. Meanwhile, the ingredients of QSD in the blood were revealed and analyzed by Ultra performance liquid chromatography tandem quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) method. Network pharmacology was used to predict the targets and mechanism of active ingredient therapy for AD. In addition, the network pharmacology outcomes were further verified by molecular docking. RESULT: After treatment with QSD, the levels of NO and IL-6 were decreased in the cell supernatant. Herein, QSD markedly decreased the eosinophil and mast cells infiltration in the dorsal skin of the 2,4-dinitrochlorobenzene. Moreover, QSD reconstructed the epidermal barrier by increasing the content of collagen fibers and changing the arrangement of DNCB-treated mice. QSD not only inhibited the levels of tumor necrosis factor-α (TNF-α) and interleukin-12 (IL-12) but also inhibited phosphorylation of p38, c-Jun N-terminal kinase (JNK), and extracellular signal-regulated kinase (ERK) proteins in the dorsal skin. Four active ingredients were identified through UPLC-Q-TOF/MS, including (-)-epicatechin, kaempferol-7-O-glucoside, cassiaside, and questin. After the network pharmacological analysis, six core targets of QSD closely related to AD were obtained, including TNF-α, IL-6, Caspase-3 (CASP3), Epidermal growth factor (EGFR), Peroxisome proliferator-activated receptor gamma (PPARG), and Neurotrophic Receptor Tyrosine Kinase 1 (NTRK1). Meanwhile, through Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, the Mitogen-activated protein kinase (MAPK) signaling pathway occupies an important position in the QSD treatment of AD. The molecular docking results showed that the six core targets are stable in binding to the four active ingredients as indicated by the molecular docking results. CONCLUSIONS: The anti-AD effect of QSD might be related to the reconstruction of the epidermal barrier and inhibition of inflammation, which regulated the MAPK pathway. Hence, it provided a promising idea for the study of Tibetan medicine prescriptions for the treatment of AD.

Blapsimidazolium A: A new imidazolium carboxylate derivative with anti-inflammatory activity from medicinal insect Blaps rynchopetera.

Blaps rynchopetera Fairmaire is a medicinal insect of Yi-nationality medicine used for a long time in Yunnan, China. In the present study, a new blapsimidazolium A (1), together with twelve known N-containing compounds (2-13), were isolated from this insect. The structures were elucidated by extensive spectroscopic analyses (1D and 2D NMR, HR-MS) and comparisons with the reported literature. Blapsimidazolium A was identified as racemic mixture by optical rotation and chiral analysis. Blapsimidazolium A (1) has a unique architecture containing an imidazolium carboxylate moiety. The results of molecular docking showed that blapsimidazolium A bound well to IL-1ß, IL-6 and iNOS. The racemates of (±)-blapsimidazolium A (1) exerted anti-inflammatory activity in LPS-stimulated THP-1 cells by significantly decreasing the production of the proinflammatory cytokines IL-1ß, IL-6 and iNOS. This is the first report describing the anti-inflammatory activity of this type imidazolium carboxylate derivative.

A Real-Time Global Inference Network for One-Stage Referring Expression Comprehension.

Referring expression comprehension (REC) is an emerging research topic in computer vision, which refers to the detection of a target region in an image given a test description. Most existing REC methods follow a multistage pipeline, which is computationally expensive and greatly limits the applications of REC. In this article, we propose a one-stage model toward real-time REC, termed real-time global inference network (RealGIN). RealGIN addresses the issues of expression diversity and complexity of REC with two innovative designs: adaptive feature selection (AFS) and Global Attentive ReAsoNing (GARAN). Expression diversity concerns varying expression content, which includes information such as colors, attributes, locations, and fine-grained categories. To address this issue, AFS adaptively fuses features of different semantic levels to tackle the changes in expression content. In contrast, expression complexity concerns the complex relational conditions in expressions that are used to identify the referent. To this end, GARAN uses the textual feature as a pivot to collect expression-aware visual information from all regions and then diffuses this information back to each region, which provides sufficient context for modeling the relational conditions in expressions. On five benchmark datasets, i.e., RefCOCO, RefCOCO+, RefCOCOg, ReferIT, and Flickr30k, the proposed RealGIN outperforms most existing methods and achieves very competitive performances against the most advanced one, i.e., MAttNet. More importantly, under the same hardware, RealGIN can boost the processing speed by 10-20 times over the existing methods.

A comprehensive review of Shengdeng in Tibetan medicine: textual research, herbal and botanical distribution, traditional uses, phytochemistry, and pharmacology.

"Shengdeng", a group of Tibetan medicines with diverse biological origins, has long been utilized in Tibet for the treatment of rheumatoid arthritis. It showcases remarkable efficacy in alleviating rheumatism, reducing swelling, and relieving pain. This study aimed to clarify the plant species used as "Shengdeng" and summarize their botanical distribution, traditional uses, phytochemistry, and pharmacology to promote its utilization and development. "Shengdeng" is derived from a remarkable collection of 14 plant species belonging to six distinct families. Extensive phytochemical investigations have led to the identification of 355 chemical constituents within "Shengdeng". Pharmacological studies conducted on "Shengdeng" have revealed a wide range of beneficial properties, including antioxidant, anticancer, antimicrobial, antiviral, antiparasitic, anti-inflammatory, and anti-arthritic activities. Notably, flavonoids and triterpenoids emerge as the predominant groups among these constituents, contributing to the therapeutic potential and diverse applications of "Shengdeng". The present review provides a concise summary of the recent advancements in textual research concerning the herbal and botanical distribution, traditional uses, phytochemistry, and pharmacological activities of "Shengdeng". It is crucial to note that future research on "Shengdeng" should prioritize the analysis of its active ingredients and the establishment of rigorous quality standards. These aspects are essential for ensuring consistency, efficacy, and safety in its clinical application.

Chalcone Derivatives From Abelmoschus manihot Seeds Restrain NLRP3 Inflammasome Assembly by Inhibiting ASC Oligomerization.

Three chalcone derivatives, abelmanihotols A-C (1-3), and nine known compounds were isolated from A. manihot seeds, and their structures were determined using HRESIMS and NMR spectroscopic analysis. Compound 1 exhibited the most potent inhibitory effect (IC50 = 4.79 ± 0.72 µM) against lipopolysaccharide (LPS)-induced NO release in THP-1 cells, and significantly inhibited interleukin 1ß (IL-1ß) secretion, which is stimulated by LPS plus nigericin (IC50 = 11.86 ± 1.20 µM), ATP or MSU, in THP-1 cells. A preliminary mechanism of action study indicated that compound 1 blocked the formation of nucleotide oligomerization domain-like receptor protein-3 (NLRP3) inflammasome formation by suppressing apoptosis-associated speck-like protein oligomerization, thereby attenuating caspase-1 activation and IL-1ß release. These results reveal that compound 1 is not only a potent and efficacious NLRP3 inflammasome inhibitor but also a promising drug for the treatment of NLRP3-related diseases.

Apoptosis Induction, a Sharp Edge of Berberine to Exert Anti-Cancer Effects, Focus on Breast, Lung, and Liver Cancer.

Cancer is the leading cause of death and one of the greatest barriers to increased life expectancy worldwide. Currently, chemotherapy with synthetic drugs remains one of the predominant ways for cancer treatment, which may lead to drug resistance and normal organ damage. Increasing researches have suggested that apoptosis, a type of programmed cell death, is a promising way for cancer therapy. Furthermore, natural products are important sources for finding new drugs with high availability, low cost and low toxicity. As a well-known isoquinoline alkaloid, accumulating evidence has revealed that berberine (BBR) exerts potential pro-apoptotic effects on multiple cancers, including breast, lung, liver, gastric, colorectal, pancreatic, and ovarian cancers. The related potential signal pathways are AMP-activated protein kinase, mitogen-activated protein kinase, and protein kinase B pathways. In this review, we provide a timely and comprehensive summary of the detailed molecular mechanisms of BBR in treating three types of cancer (breast, lung and liver cancer) by inducing apoptosis. Furthermore, we also discuss the existing challenges and strategies to improve BBR's bioavailability. Hopefully, this review provides valuable information for the comprehension of BBR in treating three types of cancer and highlight the pro-apoptotic effects of BBR, which would be beneficial for the further development of this natural compound as an effective clinical drug for treating cancers.

Elucidating the material basis and potential mechanisms of Ershiwuwei Lvxue Pill acting on rheumatoid arthritis by UPLC-Q-TOF/MS and network pharmacology.

Ershiwuwei Lvxue Pill (ELP, མགྲིན་མཚལ་ཉེར་ལྔ།), a traditional Tibetan medicine preparation, has been used hundreds of years for the clinical treatment of rheumatoid arthritis (RA) in the highland region of Tibet, China. Nevertheless, its chemical composition and therapeutic mechanism are unclear. This study aimed to uncover the potentially effective components of ELP and the pharmacological mechanisms against RA by combing UPLC-Q-TOF/MS and network pharmacology. In this study, 96 compounds of ELP were identified or tentatively characterized based on UPLC-Q-TOF/MS analysis. Then, a total of 22 potential bioactive compounds were screened by TCMSP with oral bioavailability and drug-likeness. Preliminarily, 10 crucial targets may be associated with RA through protein-protein interaction network analysis. The functional enrichment analysis indicated that ELP exerted anti-RA effects probably by synergistically regulating many biological pathways, such as PI3K-Akt, Cytokine-cytokine receptor interaction, JAK-STAT, MAPK, TNF, and Toll-like receptor signaling pathway. In addition, good molecular docking scores were highlighted between five promising bioactive compounds (ellagic acid, quercetin, kaempferol, galangin, coptisine) and five core targets (PTGS2, STAT3, VEGFA, MAPK3, TNF). Overall, ELP can exert its anti-RA activity via multicomponent, multitarget, and multichannel mechanisms of action. However, further studies are needed to validate the biological processes and effect pathways of ELP.

Plenty is Plague: Fine-Grained Learning for Visual Question Answering.

Visual Question Answering (VQA) has attracted extensive research focus recently. Along with the ever-increasing data scale and model complexity, the enormous training cost has become an emerging challenge for VQA. In this article, we show such a massive training cost is indeed plague. In contrast, a fine-grained design of the learning paradigm can be extremely beneficial in terms of both training efficiency and model accuracy. In particular, we argue that there exist two essential and unexplored issues in the existing VQA training paradigm that randomly samples data in each epoch, namely, the "difficulty diversity" and the "label redundancy". Concretely, "difficulty diversity" refers to the varying difficulty levels of different question types, while "label redundancy" refers to the redundant and noisy labels contained in individual question type. To tackle these two issues, in this article we propose a fine-grained VQA learning paradigm with an actor-critic based learning agent, termed FG-A1C. Instead of using all training data from scratch, FG-A1C includes a learning agent that adaptively and intelligently schedules the most difficult question types in each training epoch. Subsequently, two curriculum learning based schemes are further designed to identify the most useful data to be learned within each inidividual question type. We conduct extensive experiments on the VQA2.0 and VQA-CP v2 datasets, which demonstrate the significant benefits of our approach. For instance, on VQA-CP v2, with less than 75 percent of the training data, our learning paradigms can help the model achieves better performance than using the whole dataset. Meanwhile, we also shows the effectivenesss of our method in guiding data labeling. Finally, the proposed paradigm can be seamlessly integrated with any cutting-edge VQA models, without modifying their structures.

Tibetan medicine Ershiwuwei Lvxue Pill attenuates collagen-induced arthritis via inhibition of JAK2/STAT3 signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Ershiwuwei Lvxue Pill (ELP, མགྲིན་མཚལ་ཉེར་ལྔ།), a traditional Tibetan medicine preparation, has been used hundreds of years for the clinical treatment of rheumatoid arthritis (RA) in the highland region of Tibet, China. However, the underlying mechanism of its therapeutic effect remains unclear. AIM OF THE STUDY: The present study aimed to investigate the potential pharmacological mechanisms of anti-arthritic effect of ELP. MATERIALS AND METHODS: The main chemical constituents of ELP were analyzed by ultra-performance liquid chromatography quadrupole-time-flight mass spectrometry (UPLC-Q-TOF-MS). Forty-eight male Wistar rats (220 ± 20 g) were randomly divided into six groups: normal group, collagen-induced arthritis (CIA) group, methotrexate group (1.05 mg/kg), ELP groups (115, 230 and 460 mg/kg). CIA rat models were assigned to evaluate the anti-RA activity of ELP by determining the paws swelling, arthritis score, organ coefficients of spleen and thymus, and histopathological analysis of knee joints of synovial tissues. The levels of TNF-α, IL-10, IL-6 and IL-17 in serum were measured by ELISA. In addition, mRNA and protein expression levels associated with JAK2/STAT3 signaling pathway in synovial tissues of CIA rats were detected by qRT-PCR, immunohistochemistry and Western blot analyses. RESULTS: Fourteen main chemical constituents of ELP were quantitatively determined by UPLC-Q-TOF-MS analysis. Treatment with ELP reduced the paw swelling, arthritis score and organ coefficients of spleen and thymus. Histopathological examination revealed the protective effects of ELP on CIA rats with knee joint injury. The levels of serum pro-inflammatory cytokines (TNF-α, IL-6 and IL-17) were markedly reduced while the anti-inflammatory cytokine IL-10 was significantly increased with the treatment of ELP. Further investigations showed ELP down-regulated the mRNA and protein expression levels of Bcl-2, whereas up-regulated Bax, SOCS1 and SOCS3. Meanwhile, the ratios of p-JAK2/JAK2 and p-STAT3/STAT3 proteins from synovial tissues were dramatically decreased with the treatment of ELP, whereas no changes of the mRNA and protein expression levels of JAK2 and STAT3 were observed. CONCLUSION: These results indicated that ELP reduced the severity of arthritis and joint swelling, suggesting an antirheumatic effect on CIA rats. The possible mechanism is related to inhibiting inflammatory response and inducing apoptosis in synovial tissues by regulating JAK2/STAT3 signaling pathway. However, further in vivo and in vitro investigations are still needed to clarify the underlying mechanism of ELP in treating RA.

Exploring Discriminative Word-Level Domain Contexts for Multi-Domain Neural Machine Translation.

Owing to its practical significance, multi-domain Neural Machine Translation (NMT) has attracted much attention recently. Recent studies mainly focus on constructing a unified NMT model with mixed-domain training corpora to switch translation between different domains. In these models, the words in the same sentence are not well distinguished, while intuitively, they are related to the sentence domain to varying degrees and thus should exert different effects on the multi-domain NMT model. In this article, we are committed to distinguishing and exploiting different word-level domain contexts for multi-domain NMT. For this purpose, we adopt multi-task learning to jointly model NMT and monolingual attention-based domain classification tasks, improving the NMT model in two ways: 1) One domain classifier and one adversarial domain classifier are introduced to conduct domain classifications of input sentences. During this process, two generated gating vectors are used to produce domain-specific and domain-shared annotations for decoder; 2) We equip decoder with an attentional domain classifier. Then, the derived attentional weights are utilized to refine the model training via word-level cost weighting, so that the impacts of target words can be discriminated by their relevance to sentence domain. Experimental results on several multi-domain translations demonstrate the effectiveness of our model.

Four new polyynes from Codonopsis pilosula collected in Yunnan province, China.

Choushenpilosulynes D-G (1-4): four new polyynes were isolated from the roots of Codonopsis pilosula (Campanulaceae) cultivated in Yunnan province, China. Their structures were identified by spectroscopic methods. Bioactive evaluation showed that choushenpilosulynes E (2) and F (3) demonstrated potent inhibitory effect on lipid formation induced by 100 µM oleic acid stimulation. In addition, choushenpilosulyne F (3) uncovered inhibitory activity against the expression of human 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) and squalene monooxygenase (SQLE) gene transcript in HepG2 cells.

Ethyl acetate extract of Tibetan medicine Rhamnella gilgitica ameliorated type II collagen-induced arthritis in rats via regulating JAK-STAT signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Rhamnella gilgitica Mansf. et Melch. (སེང་ལྡེང་།, RG) is a traditional Tibetan medicinal plant that is currently grown throughout Tibet. According to the theory of Tibetan medicine, RG is efficient for removing rheumatism, reducing swelling, and relieving pain. Hence, it has been used for the treatment of rheumatoid arthritis (RA) in Tibet for many years. However, there are no previous reports on the anti-RA activities of ethyl acetate extract of RG (RGEA). AIM OF THE STUDY: This study aimed to explore the anti-RA effect and mechanism of RGEA on collagen-induced arthritis (CIA) in rats. MATERIALS AND METHODS: The CIA model was established in male Wister rats by intradermal injection of bovine type II collagen and Complete Freund's Adjuvant at the base of the tail and left sole, respectively. The rats were orally administered with RGEA (9.71, 19.43, or 38.85 mg/kg) for 23 days. The body weight, swelling volume, arthritis index score, thymus and spleen indices, and pathological changes were observed to evaluate the effect of RGEA on RA. Furthermore, the inflammatory cytokines in serum, such as interleukin1 beta (IL-1ß), tumor necrosis factor alpha (TNF-α), interleukin6 (IL-6), interleukin17 (IL-17), interferon-γ (INF-γ), interleukin4 (IL-4), and interleukin10 (IL-10) were measured by enzyme linked immunosorbent assay (ELISA) to explore the anti-inflammatory effects of RGEA. The terminal deoxynucleotidyl transferase dUTP nick-end labelling (TUNEL) staining was used to examine apoptosis. Finally, the protein and gene expression of B-cell lymphoma-2-associated X (Bax), B-cell lymphoma 2 (Bcl-2), Caspase3, janus-activated kinase 2 (JAK2), signal transducer and activator of transcription 3 (STAT3), suppressor of cytokine signaling1 (SOCS1), and 3 (SOCS3) in synovial tissue were detected using immunohistochemistry and real-time quantitative polymerase chain reaction (RT-qPCR). RESULTS: After the treatment with RGEA, the body weight of rats was restored, both the arthritis index and paw swelling were suppressed, and spleen and thymus indices were decreased. RGEA reduced the inflammatory cells and synovial hyperplasia in the synovial tissue of the knee joint, and suppressed bone erosion. Meanwhile, RGEA decreased the levels of IL-1ß, IL-6, IL-17, TNF-α, and INF-γ, while increased the levels of IL-4 and IL-10. TUNEL fluorescence apoptosis results confirmed that RGEA obviously promoted the apoptosis of synovial cells. Further studies showed that RGEA inhibited the proteins and mRNAs expression of JAK2 and STAT3 as well as increased the proteins and mRNAs expression of SOCS1 and SOCS3. In addition, RGEA upregulated the expression of Bax and Caspase3, and downregulated the expression of Bcl-2. CONCLUSION: The anti-RA effectof RGEA might be related to the promotion of apoptosis and inhibition of inflammation, which regulated the JAK-STAT pathway.

Network Pharmacology Integrated Molecular Docking Reveals the Mechanism of Anisodamine Hydrobromide Injection against Novel Coronavirus Pneumonia.

BACKGROUND: The Coronavirus Disease 2019 (COVID-19) outbreak in Wuhan, China, was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Anisodamine hydrobromide injection (AHI), the main ingredient of which is anisodamine, is a listed drug for improving microcirculation in China. Anisodamine can improve the condition of patients with COVID-19. MATERIALS AND METHODS: Protein-protein interactions obtained from the String databases were used to construct the protein interaction network (PIN) of AHI using Cytoscape. The crucial targets of AHI PIN were screened by calculating three topological parameters. Gene ontology and pathway enrichment analyses were performed. The intersection between the AHI component proteins and angiotensin-converting enzyme 2 (ACE2) coexpression proteins was analyzed. We further investigated our predictions of crucial targets by performing molecular docking studies with anisodamine. RESULTS: The PIN of AHI, including 172 nodes and 1454 interactions, was constructed. A total of 54 crucial targets were obtained based on topological feature calculations. The results of Gene Ontology showed that AHI could regulate cell death, cytokine-mediated signaling pathways, and immune system processes. KEGG disease pathways were mainly enriched in viral infections, cancer, and immune system diseases. Between AHI targets and ACE2 coexpression proteins, 26 common proteins were obtained. The results of molecular docking showed that anisodamine bound well to all the crucial targets. CONCLUSION: The network pharmacological strategy integrated molecular docking to explore the mechanism of action of AHI against COVID-19. It provides protein targets associated with COVID-19 that may be further tested as therapeutic targets of anisodamine.