Remodeling the immune microenvironment for gastric cancer therapy through antagonism of prostaglandin E2 receptor 4.

Gastric cancer is highly prevalent among digestive tract tumors. Due to the intricate nature of the gastric cancer immune microenvironment, there is currently no effective treatment available for advanced gastric cancer. However, there is promising potential for immunotherapy targeting the prostaglandin E2 receptor subtype 4 (EP4) in gastric cancer. In our previous study, we identified a novel small molecule EP4 receptor antagonist called YY001. Treatment with YY001 alone demonstrated a significant reduction in gastric cancer growth and inhibited tumor metastasis to the lungs in a mouse model. Furthermore, administration of YY001 stimulated a robust immune response within the tumor microenvironment, characterized by increased infiltration of antigen-presenting cells, T cells, and M1 macrophages. Additionally, our research revealed that YY001 exhibited remarkable synergistic effects when combined with the PD-1 antibody and the clinically targeted drug apatinib, rather than fluorouracil. These findings suggest that YY001 holds great promise as a potential therapeutic strategy for gastric cancer, whether used as a standalone treatment or in combination with other drugs.

CRISPR-M: Predicting sgRNA off-target effect using a multi-view deep learning network.

Using the CRISPR-Cas9 system to perform base substitutions at the target site is a typical technique for genome editing with the potential for applications in gene therapy and agricultural productivity. When the CRISPR-Cas9 system uses guide RNA to direct the Cas9 endonuclease to the target site, it may misdirect it to a potential off-target site, resulting in an unintended genome editing. Although several computational methods have been proposed to predict off-target effects, there is still room for improvement in the off-target effect prediction capability. In this paper, we present an effective approach called CRISPR-M with a new encoding scheme and a novel multi-view deep learning model to predict the sgRNA off-target effects for target sites containing indels and mismatches. CRISPR-M takes advantage of convolutional neural networks and bidirectional long short-term memory recurrent neural networks to construct a three-branch network towards multi-views. Compared with existing methods, CRISPR-M demonstrates significant performance advantages running on real-world datasets. Furthermore, experimental analysis of CRISPR-M under multiple metrics reveals its capability to extract features and validates its superiority on sgRNA off-target effect predictions.

High-power, electrically-driven continuous-wave 1.55-µm Si-based multi-quantum well lasers with a wide operating temperature range grown on wafer-scale InP-on-Si (100) heterogeneous substrate.

A reliable, efficient and electrically-pumped Si-based laser is considered as the main challenge to achieve the integration of all key building blocks with silicon photonics. Despite the impressive advances that have been made in developing 1.3-µm Si-based quantum dot (QD) lasers, extending the wavelength window to the widely used 1.55-µm telecommunication region remains difficult. In this study, we develop a novel photonic integration method of epitaxial growth of III-V on a wafer-scale InP-on-Si (100) (InPOS) heterogeneous substrate fabricated by the ion-cutting technique to realize integrated lasers on Si substrate. This ion-cutting plus epitaxial growth approach decouples the correlated root causes of many detrimental dislocations during heteroepitaxial growth, namely lattice and domain mismatches. Using this approach, we achieved state-of-the-art performance of the electrically-pumped, continuous-wave (CW) 1.55-µm Si-based laser with a room-temperature threshold current density of 0.65 kA/cm-2, and output power exceeding 155 mW per facet without facet coating in CW mode. CW lasing at 120 °C and pulsed lasing at over 130 °C were achieved. This generic approach is also applied to other material systems to provide better performance and more functionalities for photonics and microelectronics.

{Ru(C6 H6 )}-Decorating Heteropolymolybdate for Highly Activity Photocatalytic Oxidation of Benzyl Alcohol to Benzaldehyde.

An unclassical structure of {Ru(C6 H6 )}-based polyoxometalate, Cs6 H4 [Te2 Mo12 O46 {Ru(C6 H6 )}] ⋅ 16.5H2 O (1), has been successfully constructed from {Te2 Mo12 O46 }-type heteropolymolybdate and {Ru(C6 H6 )} group, which structure type was discovered for the first time. Compound 1 not only possesses strong light-harvesting ability, but also exhibits high carrier separation efficiency and lower charge transfer resistance. Under visible light irradiation, compound 1 displayed excellent catalytic activity and circularity in the conversion of benzyl alcohol to benzaldehyde (yield=94 %; turnover number=500; turnover frequency=20.8 h-1 ). Finally, the electron paramagnetic resonance measurement and energy level matching analysis provide theoretical basis for the derivation of the reaction mechanism.

Recent insight into the role of macrophage in alcohol-associated liver disease: a mini-review.

Alcohol-associated liver disease (ALD) is a condition that develops due to prolonged and excessive alcohol consumption. It encompasses various stages of liver damage, including fatty liver, alcoholic hepatitis, and cirrhosis. Immune cells, particularly macrophages, of various types play a significant role in the onset and progression of the disease. Macrophages observed in the liver exhibit diverse differentiation forms, and perform a range of functions. Beyond M1 and M2 macrophages, human macrophages can polarize into distinct phenotypes in response to various stimuli. Recent advancements have improved our understanding of macrophage diversity and their role in the progression of ALD. This mini-review provides a concise overview of the latest findings on the role and differentiation of macrophages in ALD. Additionally, it discusses potential therapeutic targets associated with macrophages and explores potential therapeutic strategies.

HiBrowser: an interactive and dynamic browser for synchronous Hi-C data visualization.

With the development of chromosome conformation capture technology, the genome-wide investigation of higher-order chromatin structure by using high-throughput chromatin conformation capture (Hi-C) technology is emerging as an important component for understanding the mechanism of gene regulation. Considering genetic and epigenetic differences are typically used to explore the pathological reasons on the chromosome and gene level, visualizing multi-omics data and performing an intuitive analysis by using an interactive browser become a powerful and welcomed way. In this paper, we develop an effective sequence and chromatin interaction data display browser called HiBrowser for visualizing and analyzing Hi-C data and their associated genetic and epigenetic annotations. The advantages of HiBrowser are flexible multi-omics navigation, novel multidimensional synchronization comparisons and dynamic interaction system. In particular, HiBrowser first provides an out of the box web service and allows flexible and dynamic reconstruction of custom annotation tracks on demand during running. In order to conveniently and intuitively analyze the similarities and differences among multiple samples, such as visual comparisons of normal and tumor tissue samples, and pan genomes of multiple (consanguineous) species, HiBrowser develops a clone mode to synchronously display the genome coordinate positions or the same regions of multiple samples on the same page of visualization. HiBrowser also supports a pluralistic and precise search on correlation data of distal cis-regulatory elements and navigation to any region on Hi-C heatmap of interest according to the searching results. HiBrowser is a no-build tool, and could be easily deployed in local server. The source code is available at https://github.com/lyotvincent/HiBrowser.

Estimating the Distribution and Convergence of County-level Healthcare Resources Allocative Efficiency in China Based on DEA and Spatial Panel Model.

Although China's 2009 New Healthcare Reform aimed to correct the imbalance in the spatial allocation of healthcare resources with a focus on the county level, its impact on county-level allocative efficiency evolution and convergence remains unclear. This paper for the first time performs a spatial analysis to explore the distribution, evolution, and convergence of the allocative efficiency of healthcare resources with county-level data. This paper uses the sample data of 158 countries in Henan Province, China, to evaluate the evolution and convergence of the allocative efficiency of healthcare resources. Based on the estimated Data Envelopment Analysis (DEA) allocative efficiency, analysis of variance (ANOVA), and spatial descriptive analysis, we explore the county heterogeneity and efficiency evolution; a spatial panel model is then utilized to test the county-level convergence of the allocative efficiency of healthcare resources. Although the number of efficient counties has not increased, the number of inefficient individuals keeps decreasing, and the allocative efficiency of municipal districts is lower than that of nonmunicipal counties. There exists a positive spatial correlation of allocative efficiency in Henan Province, and significant and robust convergence results can be found at the county level after China's 2009 reform. This study reveals a diversified picture of China's county-level spatial evolution of allocative efficiency in healthcare resources, showing a more balanced spatial distribution of allocative efficiency since the triggering of China's 2009 reform. However, long-term investment incentives and a targeted allocation of healthcare resources are still needed to promote further efficiency convergence and increase the number of counties with efficiency.

Construction of a fecal immune-related protein-based biomarker panel for colorectal cancer diagnosis: a multicenter study.

Purpose: To explore fecal immune-related proteins that can be used for colorectal cancer (CRC) diagnosis. Patients and methods: Three independent cohorts were used in present study. In the discovery cohort, which included 14 CRC patients and 6 healthy controls (HCs), label-free proteomics was applied to identify immune-related proteins in stool that could be used for CRC diagnosis. Exploring potential links between gut microbes and immune-related proteins by 16S rRNA sequencing. The abundance of fecal immune-associated proteins was verified by ELISA in two independent validation cohorts and a biomarker panel was constructed that could be used for CRC diagnosis. The validation cohort I included 192 CRC patients and 151 HCs from 6 different hospitals. The validation cohort II included 141 CRC patients, 82 colorectal adenoma (CRA) patients, and 87 HCs from another hospital. Finally, the expression of biomarkers in cancer tissues was verified by immunohistochemistry (IHC). Results: In the discovery study, 436 plausible fecal proteins were identified. And among 67 differential fecal proteins (|log2 fold change| > 1, P< 0.01) that could be used for CRC diagnosis, 16 immune-related proteins with diagnostic value were identified. The 16S rRNA sequencing results showed a positive correlation between immune-related proteins and the abundance of oncogenic bacteria. In the validation cohort I, a biomarker panel consisting of five fecal immune-related proteins (CAT, LTF, MMP9, RBP4, and SERPINA3) was constructed based on the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. The biomarker panel was found to be superior to hemoglobin in the diagnosis of CRC in both validation cohort I and validation cohort II. The IHC result showed that protein expression levels of these five immune-related proteins were significantly higher in CRC tissue than in normal colorectal tissue. Conclusion: A novel biomarker panel consisting of fecal immune-related proteins can be used for the diagnosis of CRC.

The universality of eAREs in animal feces suggesting that eAREs function possibly in horizontal gene transfer.

Objectives: This study aimed to pinpoint the universality of extracellular antimicrobial resistance elements (eAREs) and compare the contents of eAREs with those of intracellular AREs (iAREs) in animal feces, thus laying a foundation for the further analysis of the horizontal transfer of antimicrobial resistance genes (ARGs) in the animal guts. Materials and Methods: Extracellular DNAs were isolated from the fecal samples of Pavo cristatus (n = 18), Ursus thibetanus (n = 2), two breeds of broilers (n = 21 and 11, respectively), and from the contents of rabbit intestines (n = 5). eAREs were detected by PCR technology. iAREs in P. cristatus and broiler feces were also detected and compared with the corresponding eAREs. In addition, some gene cassettes of class 1 integrons were sequenced and analyzed. Results: The results showed that eAREs exist in animal feces and intestinal contents. In this study, different eAREs were detected from animal feces and intestinal contents, and tetA, tetB, sul1, sul2, class 1 integron, and IncFIB presented the highest detection rates. The detection rates of certain eAREs were significantly higher than those of parallel iAREs. The integral cassettes with intact structures were found in eAREs, and the cassettes carried ARGs. Conclusions: The presented study here sheds light on the presence of eAREs in animal feces or guts, and eAREs may play an important role in the horizontal gene transfer of ARGs.

LPAD: using network construction and label propagation to detect topologically associating domains from Hi-C data.

With the development of chromosome conformation capture technique, the study of spatial conformation of a genome based on Hi-C technique has made a quantum leap. Previous studies reveal that genomes are folded into hierarchy of three-dimensional (3D) structures associated with topologically associating domains (TADs), and detecting TAD boundaries is of great significance in the chromosome-level analysis of 3D genome architecture. In this paper, we propose a novel TAD identification method, LPAD, which first extracts node correlations from global interactions of chromosomes based on the random walk with restart and then builds an undirected graph from Hi-C contact matrix. Next, LPAD designs a label propagation-based approach to discover communities and generates TADs. Experimental results verify the effectiveness and quality of TAD detections compared with existing methods. Furthermore, experimental evaluation of chromatin immunoprecipitation sequencing data shows that LPAD performs high enrichment of histone modifications remarkably nearby the TAD boundaries, and these results demonstrate LPAD's advantages on TAD identification accuracy.

Differential evolution based dual adversarial camouflage: Fooling human eyes and object detectors.

Deep neural network-based object detectors are vulnerable to adversarial examples. Among existing works to fool object detectors, the camouflage-based method is more often adopted due to its adaptation to multi-view scenarios and non-planar objects. However, most of them can still be easily observed by human eyes, which limits their application in the real world. To fool human eyes and object detectors simultaneously, we propose a differential evolution based dual adversarial camouflage method. Specifically, we try to obtain the camouflage texture by the two-stage training, which can be wrapped over the surface of the object. In the first stage, we optimize the global texture to minimize the discrepancy between the rendered object and the scene background, making human eyes difficult to distinguish. In the second stage, we design three loss functions to optimize the local texture, which is selected from the global texture, making object detectors ineffective. In addition, we introduce the differential evolution algorithm to search for the near-optimal areas of the object to attack, improving the adversarial performance under certain attack area limitations. Experimental results show that our proposed method can obtain a good trade-off between fooling human eyes and object detectors under multiple specific scenes and objects.

Genome-Wide Identification and Evolutionary Analysis of Gossypium YTH Domain-Containing RNA-Binding Protein Family and the Role of GhYTH8 in Response to Drought Stress.

YTH domain-containing proteins are one kind of RNA-binding protein involved in post-transcriptional regulation and play multiple roles in regulating the growth, development, and abiotic stress responses of plants. However, the YTH domain-containing RNA-binding protein family has not been previously studied in cotton. In this study, a total of 10, 11, 22, and 21 YTH genes were identified in Gossypium arboreum, Gossypium raimondii, Gossypium barbadense, and Gossypium hirsutum, respectively. These Gossypium YTH genes were categorized into three subgroups by phylogenetic analysis. The chromosomal distribution, synteny analysis, structures of Gossypium YTH genes, and the motifs of YTH proteins were analyzed. Furthermore, the cis-element of GhYTH genes promoter, miRNA targets of GhYTH genes, and subcellular localization of GhYTH8 and GhYTH16 were characterized. Expression patterns of GhYTH genes in different tissues, organs, and in response to different stresses were also analyzed. Moreover, functional verifications revealed that silencing GhYTH8 attenuated the drought tolerance in the upland cotton TM-1 line. These findings provide useful clues for the functional and evolutionary analysis of YTH genes in cotton.

Genome-wide identification of KNOX transcription factors in cotton and the role of GhKNOX4-A and GhKNOX22-D in response to salt and drought stress.

Cotton is one of the most important economic and fiber crops in the world. KNOX is one class of universal transcription factors, which plays important roles in plant growth and development as well as response to different stresses. Although there are many researches on KNOXs in other plant species, there are few reports on cotton. In this study, we systematically and comprehensively identified all KNOX genes in upland cotton and its two ancestral species; we also studied their functions by employing RNA-seq analysis and virus-induced gene silence (VIGS). A total of 89 KNOX genes were identified from three cotton species. Among them, 44 were from upland cotton, 22 and 23 were found in its ancestral species G. raimondii and G. arboreum, respectively. Plant polyploidization and domestication play a selective force driving KNOX gene evolution. Phylogenetic analysis displayed that KNOX genes were evolved into three Classes. The intron length and exon number differed in each Class. Transcriptome data showed that KNOX genes of Class II were widely expressed in multiple tissues, including fiber. The majority of KNOX genes were induced by different abiotic stresses. Additionally, we found multiple cis-elements related to stress in the promoter region of KNOX genes. VIGS silence of GhKNOX4-A and GhKNOX22-D genes showed significant growth and development effect in cotton seedlings under salt and drought treatments. Both GhKNOX4-A and GhKNOX22-D regulated plant tolerance; silencing both genes induced oxidative stresses, evidenced by reduced SOD activity and induced leave cell death, and also enhanced stomatal open and water loss. Thus, GhKNOX4-A and GhKNOX22-D may contribute to drought response by regulating stomata opening and oxidative stresses.

DupScan: predicting and visualizing vertebrate genome duplication database.

Duplicated genes prevail in vertebrates and are important in the acquisition of new genes and novelties. Whole genome duplication (WGD) is one of the sources of duplicated genes. It can provide raw materials for natural selection by increasing the flexibility and complexity of the genome. WGDs are the driving force for the evolution of vertebrates and contribute greatly to their species diversity, especially in fish species with complicated WGD patterns. Here, we constructed the DupScan database (https://dupscan.sysumeg.com/) by integrating 106 chromosomal-level genomes, which can analyze and visualize synteny at both the gene and genome scales, visualize the Ka, Ks, and 4DTV values, and browse genomes. DupScan was used to perform functional adaptation for the intricate WGD investigation based on synteny matching. DupScan supports the analysis of five WGD rounds (R): VGD2 (vertebrate genome duplication 2), Ars3R (Acipenser-ruthenus-specific 3R), Pss3R (Polyodon-spathula-specific 3R), Ts3R (teleost-specific duplication 3R), Ss4R (salmonid-specific 4R), and Cs4R (carp-specific 4R). DupScan serves as one-stop analysis platform for synteny and WGD research in which users can analyze and predict synteny and WGD patterns across 106 species of whole genome sequences. This further aided us in elucidating genome evolutionary patterns across over 60,000 vertebrate species with synteny and WGD events.

High-speed compact folded Michelson interferometer modulator.

We propose and experimentally demonstrate a novel compact folded Michelson interferometer (FMI) modulator with high modulation efficiency. By folding the 0.5 mm-long phase shift arms, the length of the modulation area of the FMI modulator is only 0.25 mm. Meanwhile, the traveling wave electrode (TWE) is also shorter, which decreases the propagation loss of the RF signal and contributes to a small footprint. The Vπ-L of the present device is as low as 0.87 V·cm at -8 V bias voltage. The minimum optical insertion loss is 3.7 dB, and the static extinction ratio (ER) is over 25 dB. The measured 3-dB electro-optical (EO) bandwidth is 17.3 GHz at a -6 V bias. The OOK eye diagram up to 40 Gb/s is demonstrated under 2 V driver voltage.

Pyroptosis and respiratory diseases: A review of current knowledge.

Pyroptosis is a relatively newly discovered programmed cell death accompanied by an inflammatory response. In the classical view, pyroptosis is mediated by caspases-1,-4,-5,-11 and executed by GSDMD, however, recently it was demonstrated that caspase-3 and-8 also participate in the process of pyroptosis, by cleaving GSDMD/E and GSDMD respectively. Different from autophagy and apoptosis, many pores are formed on the cell membrane during pyroptosis, which makes the cell membrane lose its integrity, eventually leading to the release of cytokines interleukin(IL)-1ß and IL-18. When the body is infected with pathogens or exposed to some stimulations, pyroptosis could play an immune defense role. It is found that pyroptosis exists widely in infectious and inflammatory respiratory diseases such as acute lung injury, bronchial dysplasia, chronic obstructive pulmonary disease, and asthma. Excessive pyroptosis may accompany airway inflammation, tissue injury, and airway damage, and induce an inflammatory reaction, leading to more serious damage and poor prognosis of respiratory diseases. This review summarizes the relationship between pyroptosis and related respiratory diseases.

Systematic Infection of Chlamydia Pneumoniae.

BACKGROUND: Chlamydia pneumoniae (Cpn) is one of the most common respiratory pathogens in children and adults. It is characterized as an obligate intracellular parasite. Peripheral blood monocytes (PBMC), lymphocytes, and macrophages are involved in spreading chlamydia infection to extrapulmonary organs indicating that Cpn infection can cause systematic symptoms in vivo via blood transmission. METHODS: This review summarizes the mechanisms of Cpn infection in host cells, the immune response of the body, and the relationship between Cpn infection and some chronic diseases. RESULTS: Cpn participation in extrapulmonary chronic diseases has been proven owing to the presence of Cpn DNA in AS plaque, nerve tissues, and synovium tissues of the joints. CONCLUSIONS: Cpn infection is related to the development of chronic diseases such as atherosclerosis, Alzheimer's Disease (AD), and reactive arthritis through in vivo and in vitro experiments.

Genome-Wide Identification of Cotton (Gossypium spp.) Trehalose-6-Phosphate Phosphatase (TPP) Gene Family Members and the Role of GhTPP22 in the Response to Drought Stress.

Trehalose-6-phosphate phosphatase (TPP) is a key enzyme involved in trehalose synthesis in higher plants. Previous studies have shown that TPP family genes increase yields without affecting plant growth under drought conditions, but their functions in cotton have not been reported. In this study, 17, 12, 26 and 24 TPP family genes were identified in Gossypium arboreum, Gossypium raimondii, Gossypium barbadense and Gossypium hirsutum, respectively. The 79 TPP family genes were divided into three subgroups by phylogenetic analysis. Virus-induced gene silencing (VIGS) of GhTPP22 produced TRV::GhTPP22 plants that were more sensitive to drought stress than the control plants, and the relative expression of GhTPP22 was decreased, as shown by qRT-PCR. Moreover, we analysed the gene structure, targeted small RNAs, and gene expression patterns of TPP family members and the physicochemical properties of their encoded proteins. Overall, members of the TPP gene family in cotton were systematically identified, and the function of GhTPP22 under drought stress conditions was preliminarily verified. These findings provide new information for improving drought resistance for cotton breeding in the future.

Genome-Wide Identification of Cotton (Gossypium spp.) Glycerol-3-Phosphate Dehydrogenase (GPDH) Family Members and the Role of GhGPDH5 in Response to Drought Stress.

Glycerol-3-phosphate dehydrogenase (GPDH) is a key enzyme in plant glycerol synthesis and metabolism, and plays an important role in plant resistance to abiotic stress. Here, we identified 6, 7, 14 and 14 GPDH genes derived from Gossypium arboreum, Gossypium raimondii, Gossypium barbadense and Gossypium hirsutum, respectively. Phylogenetic analysis assigned these genes into three classes, and most of the genes within the family were expanded by whole-genome duplication (WGD) and segmental duplications. Moreover, determination of the nonsynonymous substitution rate/synonymous substitution rate (Ka/Ks) ratio showed that the GPDH had an evolutionary preference for purifying selection. Transcriptome data revealed that GPDH genes were more active in the early stages of fiber development. Additionally, numerous stress-related cis-elements were identified in the potential promoter region. Then, a protein-protein-interaction (PPI) network of GPDH5 in G. hirsutum was constructed. In addition, we predicted 30 underlying miRNAs in G. hirsutum. Functional validation results indicated that silencing GhGPDH5 diminished drought tolerance in the upland cotton TM-1 line. In summary, this study provides a fundamental understanding of the GPDH gene family in cotton, GhGPDH5 exerts a positive effect during drought stress and is potentially involved in stomatal closure movements.

Effective Identification of Bacterial Genomes From Short and Long Read Sequencing Data.

With the development of sequencing technology, microbiological genome sequencing analysis has attracted extensive attention. For inexperienced users without sufficient bioinformatics skills, making sense of sequencing data for microbial identification, especially for bacterial identification, through reads analysis is still challenging. In order to address the challenge of effectively analyzing genomic information, in this paper, we develop an effective approach and automatic bioinformatics pipeline called PBGI for bacterial genome identification, performing automatedly and customized bioinformatics analysis using short-reads or long-reads sequencing data produced by multiple platforms such as Illumina, PacBio and Oxford Nanopore. An evaluation of the proposed approach on the practical data set is presented, showing that PBGI provides a user-friendly way to perform bacterial identification through short or long reads analysis, and could provide accurate analyzing results. The source code of the PBGI is freely available at https://github.com/lyotvincent/PBGI.