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The plant-derived toxin ricin is classified as a type 2 ribosome-inactivating protein (RIP) and currently lacks effective clinical antidotes. The toxicity of ricin is mainly due to its ricin toxin A chain (RTA), which has become an important target for drug development. Previous studies have identified two essential binding pockets in the active site of RTA, but most existing inhibitors only target one of these pockets. In this study, we used computer-aided virtual screening to identify a compound called RSMI-29, which potentially interacts with both active pockets of RTA. We found that RSMI-29 can directly bind to RTA and effectively attenuate protein synthesis inhibition and rRNA depurination induced by RTA or ricin, thereby inhibiting their cytotoxic effects on cells in vitro. Moreover, RSMI-29 significantly reduced ricin-mediated damage to the liver, spleen, intestine, and lungs in mice, demonstrating its detoxification effect against ricin in vivo. RSMI-29 also exhibited excellent drug-like properties, featuring a typical structural moiety of known sulfonamides and barbiturates. These findings suggest that RSMI-29 is a novel small-molecule inhibitor that specifically targets ricin toxin A chain, providing a potential therapeutic option for ricin intoxication.

Chinese medical Named Entity Recognition (NER) is a task of Natural Language Processing (NLP), which aims to extract key information from Chinese medical texts. Recently, Transformer becomes the mainstream approach for NLP due to its powerful capability for global feature extraction. However, entities usually appear in the form of subsequences in NER, therefore the local features are not negligible, and the uncertainty of Chinese word segmentation increases the difficulty of this task. In this paper, we propose a network structure that combines global feature extraction and multi-local feature extraction to enhance the performance of Chinese medical NER. Based on the global feature extracted by the Transformer, Bi-LSTM is used to extract the multi-local features, and a context integration mechanism is used to enhance local features by integrating both forward and backward global contexts in each cell. This allows for a more comprehensive representation of individual cells. And a feature fusion method based on attention mechanism is proposed, which allows the decoder to better focus on the more important information for predicting the current character. During the global feature extraction, the flat-lattice structure is introduced to generate all the potential results of Chinese word segmentation. And the span-based relative positional encoding integrates direction and distance perception, which overcomes the shortcoming of Transformer’s inability to capture sequential characteristics. Finally, a CRF with conditional constraints is used as the decoder of the model. Experimental results on two benchmark datasets show the effectiveness of our model, and the method significantly outperforms the state-of-the-art methods in the medical NER task, achieving $F1$ value of 93.64% on CCKS2017 and 85.01% on CCKS2019.

Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) is one of the most prominent housekeeping proteins and is widely used as an internal control in some semi-quantitative assays. In addition to glycolysis, GAPDH is involved in several cancer-related biological processes and has been reported to be commonly dysregulated in multiple cancer types. Therefore, its role in the physiological process of cancer needs to be urgently elucidated. Pan-cancer analysis indicated that GAPDH is ubiquitously highly expressed in most cancer types, and that patients with a high GAPDH expression of in tumor tissues have a poor prognosis. The concordance of GAPDH expression in tumors with the infiltration of immune cells and immune checkpoints implies a certain association between GAPDH and the tumor microenvironment as well as tumor development. Gene Set Enrichment Analysis revealed that GAPDH may contribute to multiple important cancer-related pathways and biological processes. Multi-omics analysis and in vitro cell experiments revealed that GAPDH overexpression is regulated by DNA copy number amplification and promoter methylation modification. Importantly, a transcription factor, forkhead box M1 (FOXM1), which is capable of regulating GAPDH expression, was also identified and was confirmed to be an oncogene and ubiquitously highly expressed in multiple cancer types. Semi-quantitative chromatin immunoprecipitation, quantitative PCR, and dual-luciferase assays showed that FOXM1 mainly binds to the promoter region of GAPDH in two cancer cell lines. The present findings revealed the implication of GAPDH in tumor development, thus bringing attention to this important molecule and casting doubts on its role as an internal reference gene in cancer studies.

Abstract Rationale Lung cancer is the most prevalent form of cancer and has a high mortality rate, making it a global public health concern. The N6-methyladenosine (m6A) modification is a highly dynamic and reversible process that is involved in a variety of essential biological processes. Using in vitro, in vivo, and multi-omics bioinformatics, the present study aims to determine the function and regulatory mechanisms of the long non-coding (lnc)RNA zinc ribbon domain-containing 1-antisense 1 (ZNRD1-AS1). Methods The RNAs that were bound to the m6A ‘reader’ were identified using YTH domain-containing 2 (YTHDC2) RNA immunoprecipitation (RIP)-sequencing. Utilizing methylated RIP PCR/quantitative PCR, pull-down, and RNA stability assays, m6A modification and ZNRD1-AS1 regulation were analyzed. Using bioinformatics, the expression levels and clinical significance of ZNRD1-AS1 in lung cancer were evaluated. Using fluorescent in situ hybridization and quantitative PCR assays, the subcellular location of ZNRD1-AS1 was determined. Using cell migration, proliferation, and angiogenesis assays, the biological function of ZNRD1-AS1 in lung cancer was determined. In addition, the tumor suppressor effect of ZNRD1-AS1 in vivo was validated using a xenograft animal model. Through bioinformatics analysis and in vitro assays, the downstream microRNAs (miRs) and competing endogenous RNAs were also predicted and validated. Results This study provided evidence that m6A modification mediates YTHDC2-mediated downregulation of ZNRD1-AS1 in lung cancer and cigarette smoke-exposed cells. Low levels of ZNRD1-AS1 expression were linked to adverse clinicopathological characteristics, immune infiltration, and prognosis. ZNRD1-AS1 overexpression was shown to suppress lung cancer cell proliferation, migration, and angiogenesis in vitro and in vivo, and to reduce tumor growth in nude mice. ZNRD1-AS1 expression was shown to be controlled by treatment of cells with either the methylation inhibitor 3-Deazaadenosine or the demethylation inhibitor Meclofenamic. Furthermore, the miR-942/tensin 1 (TNS1) axis was demonstrated to be the downstream regulatory signaling pathway of ZNRD1-AS1. Conclusions ZNRD1-AS1 serves an important function and has clinical relevance in lung cancer. In addition, the findings suggested that m6A modification could mediate the regulation of the ZNRD1-AS1/miR-942/TNS1 axis via the m6A reader YTHDC2. Graphical Abstract

Mode overlapping promotes the capability in manipulating optical absorption. Based on such a mechanism, an all-dielectric metasurface has the capability of perfectly absorbing incident optical energy without the assistance of a mirror. Here, an array of thin germanium waveguide-like units is designed as a special absorber possessing some advantages by overlapping two localized resonant modes. Such a thin absorber can realize strong absorption even though the germanium material is of low loss at the O band. It is found that the absorption capability is about three times stronger than that of an unpatterned germanium film with the same thickness, and wideband strong absorption is obtained at the same time. The structure is continuous so that it can conduct carriers in photodetection. The suggested method would be heuristic in the photodetection area.

Absorbers such as photonic crystals, metasurfaces, and nanowires have been demonstrated to have important applications in solar cells, detectors, etc. The application of thin-layer-based absorbers to photodetectors is beneficial to simultaneously improve responsivity and 3 dB bandwidth. In this work, we propose a high-contrast-gratings-like absorber to achieve ultra-high absorption based on a thin Germanium layer. High absorption approximately 95% at wavelength 1310 nm is reached for TE-polarized incidence due to the interference of two guided modes, which is 4 times compared to the planar film with the same thickness. The high absorption of the absorber is also experimentally demonstrated. This work shows a new method for enhanced absorption with thin Germanium layer, indicating a promising prospect for high-efficiency photodetection.

Gastric cancer has become a global health issue, severely disrupting daily life. Early detection in gastric cancer patients and immediate treatment contribute significantly to the protection of human health. However, routine gastric cancer examinations carry the risk of complications and are time-consuming. We proposed a framework to predict gastric cancer non-invasively and conveniently. A total of 703 tongue images were acquired using a bespoke tongue image capture instrument, then a dataset containing subjects with and without gastric cancer was created. As the images acquired by this instrument contain non-tongue areas, the Deeplabv3+ network was applied for tongue segmentation to reduce the interference in feature extraction. Nine tongue features were extracted, relationships between tongue features and gastric cancer were explored by using statistical methods and deep learning, finally a prediction framework for gastric cancer was designed. The experimental results showed that the proposed framework had a strong detection ability, with an accuracy of 93.6%. The gastric cancer prediction framework created by combining statistical methods and deep learning proposes a scheme for exploring the relationships between gastric cancer and tongue features. This framework contributes to the effective early diagnosis of patients with gastric cancer.

Fano resonance, which is based on a plasmonic metasurface, has many potential applications in various fields, such as biochemical sensors, slow light effect, and integrated optical circuits. In this study, a rectangular-like nanotetramer metasurface structure composed of four round-head nanorods was designed. The transmission spectrum, surface charge, and electrical field distributions of the proposed structure were simulated using the finite element method. A double Fano resonance profile was observed in the transmission spectrum. One of the Fano resonances was caused by the symmetry breaking and plasmon hybridization between the horizontal double rods, whereas the other resonance was due to the plasmonic modes’ hybridization among four nanorods. These resonances could be independently tuned because of different formation mechanisms. The number of Fano resonances could be adjusted by changing the coupling distance between the horizontal and vertical rods. The results contributed to designing the highly sensitive sensors based on the plasmonic metasurface.

A plasmonic refractive index sensor based on surface plasmon polaritons (SPPs) that consist of metal–insulator–metal (MIM) waveguides and a whistle-shaped cavity is proposed. The transmission properties were simulated numerically by using the finite element method. The Fano resonance phenomenon can be observed in their transmission spectra, which is due to the coupling of SPPs between the transmission along the clockwise and anticlockwise directions. The refractive index-sensing properties based on the Fano resonance were investigated by changing the refractive index of the insulator of the MIM waveguide. Modulation of the structural parameters on the Fano resonance and the optics transmission properties of the coupled structure of two MIM waveguides with a whistle-shaped cavity were designed and evaluated. The results of this study will help in the design of new photonic devices and micro-sensors with high sensitivity, and can serve as a guide for future application of this structure.

Tongue diagnosis is an important part of the diagnostic process in traditional Chinese medicine (TCM). It primarily relies on the expertise and experience of TCM practitioners in identifying tongue features, which are subjective and unstable. We proposed a tongue feature classification framework based on convolutional neural networks to reduce the differences in diagnoses among TCM practitioners. Initially, we used our self-designed instrument to capture 482 tongue photos and created 11 data sets based on different features. Then, the tongue segmentation task was completed using an upgraded facial landmark detection method and UNET. Finally, we used ResNet34 as the backbone to extract features from the tongue photos and classify them. Experimental results show that our framework has excellent results with an overall accuracy of over 86 percent and is particularly sensitive to the corresponding feature regions, and thus it could assist TCM practitioners in making more accurate diagnoses.

We analyze the property of the grating modes given by the modal method in a periodic array of parallel square rods. It is shown that the grating modes can be classified as the non-coupling mode originating from the interaction between optical waves and dielectric and the coupling mode from the inter-rod interaction. The non-coupling mode, therefore, can be excited in any case, in comparison with the coupling mode denoting a geometrical resonance of a rod array and sensitive to any change of structure. The coupling and non-coupling modes determine the optical properties of the array together. The study for a low-permittivity dielectric rod array shows that when the high reflectance is achieved, the coupling mode is excited to provide the transmission component to cancel out that from the non-coupling modes. Our results could provide the basis for understanding and optimizing optical devices based on rod arrays. [ABSTRACT FROM AUTHOR]

Abstract Studies have demonstrated that miRNA-378 is expressed in various malignant tumors. In the present study, we aimed to explore the expression of serum miRNA-378 and its clinical significance in renal cell carcinoma (RCC) patients. A total of 75 RCC patients, 63 renal cysts (RC) patients and 75 healthy controls were selected. The miRNA-378 level in RCC and RC groups was significantly higher than in healthy control group, with RCC group having the highest level. The miRNA-378 levels were significantly decreased within the same group after surgery. When compared with healthy controls, RC group had higher levels but not significantly (p > 0.05) while levels in RCC group were significantly higher (p < 0.05). miRNA-378 expression was correlated with clinical stage and differentiation degree, but not correlated with patient's age, gender, surgical strategy and tumor diameter. The AUC of miRNA-378 was 0.896, 95% confidence interval was 0.847 to 0.945, and AUC hypothesis testing was statistically significant (p < 0.001, RCC vs healthy control). miRNA-378 shows potential in the diagnosis and prediction of postoperative curative effect of renal cell carcinoma, but further studies with lager samples are needed.

Introduction: Acute myocardial infarction (AMI) accounts for the majority of deaths caused by coronary artery disease (CAD). Early warning of AMI, especially for patients with stable coronary artery disease (sCAD), is urgently needed. Our previous study showed that alterations in the gut microbiota were correlated with CAD severity., Objectives: Herein, we tried to discover accurate and convenient biomarkers for AMI by combination of gut microbiota and fecal/blood/urinary metabolomics., Methods: We recruited 190 volunteers including 93 sCAD patients, 49 AMI patients, and 48 subjects with normal coronary artery (NCA), and measured their blood biochemical parameters, 16S rRNA-based gut microbiota and NMR-based fecal/blood/urinary metabolites. We further selected 20 subjects from each group and analyzed their gut microbiota by whole-metagenome shotgun sequencing., Results: Multi-omic analyses revealed that AMI patients exhibited specific changes in gut microbiota and serum/urinary/fecal metabolites as compared to subjects with sCAD or NCA. Fourteen bacterial genera and 30 metabolites (11 in feces, 10 in blood, 9 in urine) were closely related to AMI phenotypes and could accurately distinguish AMI patients from sCAD patients. Some species belonging to Alistipes, Streptococcus, Ruminococcus, Lactobacillus and Faecalibacterium were effective to distinguish AMI from sCAD and their predictive ability was confirmed in an independent cohort of CAD patients. We further selected nine indicators including 4 bacterial genera, 3 fecal and 2 urinary metabolites as a noninvasive biomarker set which can distinguish AMI from sCAD with an AUC of 0.932., Conclusion: Combination of gut microbiota and fecal/urinary metabolites provided a set of potential useful and noninvasive predictive biomarker for AMI from sCAD., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Production and hosting by Elsevier B.V.)

Background: Thrombophilia is a group of disorders that result in a blood hypercoagulable state and induce thrombosis, which was found widely existed in recurrent pregnancy loss (RPL). More and more research about thrombophilia has been conducted but the association between thrombophilia and RPL remains uncertain. Thus, it's necessary to combine relevant literature to find the research hotspots and analyze the internal link between different study points, and then predict the development trend in RPL with thrombophilia., Methods: Relevant articles between 1970 and 2022 were obtained from the Web of Science (WoS) database. Software VOSviewer and CiteSpace were used to perform the analysis and conduct visualization of scientific productivity and emerging trends., Results: Seven hundred twenty-five articles published in recent 30 years by 3205 authors from 1139 organizations and 68 countries were analyzed. 37authors, 38 countries, and 53 organizations published papers ≥5. The United States was the most productive country and Univ Amsterdam was the most productive institution. Journal thrombosis and haemostasis had the most total citations. In keyword and clusters, factor-v-Leiden, inherited thrombophilia, activated protein-c, low-dose aspirin, molecular-weigh heparin, polymorphism had high-frequency focus on its etiology, diagnostics, and therapeutics. The strongest keyword bursts showed the research hotspots changed over time., Conclusions: There could be differences in the clinical relevance of different type of thrombophilia, as well as single and multiple thrombophilic factors. Anticoagulation and immunotherapy are currently the main treatment options. More clinical trials and basic research are expected and we should attach more attention to the whole management of in-vitro fertilization in the future., (© 2022. The Author(s).)