Application of Strain Selection Technology in Alcoholic Beverages: A Review.

The diversity of alcohol beverage microorganisms is of great significance for improving the brewing process and the quality of alcohol beverage products. During the process of making alcoholic beverages, a group of microorganisms, represented by yeast and lactic acid bacteria, conducts fermentation. These microorganisms have complex synergistic or competitive relationships, and the participation of different microorganisms has a major impact on the fermentation process and the flavor and aroma of the product. Strain selection is one of the key steps. Utilizing scientific breeding technology, the relationship between strains can be managed, the composition of the alcoholic beverage microbial community can be improved, and the quality and flavor of the alcoholic beverage products can be increased. Currently, research on the microbial diversity of alcohol beverages has received extensive attention. However, the selection technology for dominant bacteria in alcohol beverages has not yet been systematically summarized. To breed better-quality alcohol beverage strains and improve the quality and characteristics of wine, this paper introduces the microbial diversity characteristics of the world's three major brewing alcohols: beer, wine, and yellow wine, as well as the breeding technologies of related strains. The application of culture selection technology in the study of microbial diversity of brewed wine was reviewed and analyzed. The strain selection technology and alcohol beverage process should be combined to explore the potential application of a diverse array of alcohol beverage strains, thereby boosting the quality and flavor of the alcohol beverage and driving the sustainable development of the alcoholic beverage industry.

Small-Molecule Inhibitors of TIPE3 Protein Identified through Deep Learning Suppress Cancer Cell Growth In Vitro.

Tumor necrosis factor-α-induced protein 8-like 3 (TNFAIP8L3 or TIPE3) functions as a transfer protein for lipid second messengers. TIPE3 is highly upregulated in several human cancers and has been established to significantly promote tumor cell proliferation, migration, and invasion and inhibit the apoptosis of cancer cells. Thus, inhibiting the function of TIPE3 is expected to be an effective strategy against cancer. The advancement of artificial intelligence (AI)-driven drug development has recently invigorated research in anti-cancer drug development. In this work, we incorporated DFCNN, Autodock Vina docking, DeepBindBC, MD, and metadynamics to efficiently identify inhibitors of TIPE3 from a ZINC compound dataset. Six potential candidates were selected for further experimental study to validate their anti-tumor activity. Among these, three small-molecule compounds (K784-8160, E745-0011, and 7238-1516) showed significant anti-tumor activity in vitro, leading to reduced tumor cell viability, proliferation, and migration and enhanced apoptotic tumor cell death. Notably, E745-0011 and 7238-1516 exhibited selective cytotoxicity toward tumor cells with high TIPE3 expression while having little or no effect on normal human cells or tumor cells with low TIPE3 expression. A molecular docking analysis further supported their interactions with TIPE3, highlighting hydrophobic interactions and their shared interaction residues and offering insights for designing more effective inhibitors. Taken together, this work demonstrates the feasibility of incorporating deep learning and MD simulations in virtual drug screening and provides inhibitors with significant potential for anti-cancer drug development against TIPE3-.

The Diversity and Community Composition of Three Plants' Rhizosphere Fungi in Kaolin Mining Areas.

Mining activities in the kaolin mining area have led to the disruption of the ecological health of the mining area and nearby soils, but the effects on the fungal communities in the rhizosphere soils of the plants are not clear. Three common plants (Conyza bonariensis, Artemisia annua, and Dodonaea viscosa) in kaolin mining areas were selected and analyzed their rhizosphere soil fungal communities using ITS sequencing. The alpha diversity indices (Chao1, Shannon, Simpson, observed-species, pielou-e) of the fungal communities decreased to different extents in different plants compared to the non-kauri mining area. The ß-diversity (PCoA, NMDS) analysis showed that the rhizosphere soil fungal communities of the three plants in the kaolin mine area were significantly differentiated from those of the control plants grown in the non-kaolin mine area, and the extent of this differentiation varied among the plants. The analysis of fungal community composition showed that the dominant fungi in the rhizosphere fungi of C. bonariensis and A. annua changed, with an increase in the proportion of Mycosphaerella (genus) by about 20% in C. bonariensis and A. annua. An increase in the proportion of Didymella (genus) by 40% in D. viscosa was observed. At the same time, three plant rhizosphere soils were affected by kaolin mining activities with the appearance of new fungal genera Ochrocladosporium and Plenodomus. Predictive functional potential analysis of the samples revealed that a significant decrease in the potential of functions such as biosynthesis and glycolysis occurred in the rhizosphere fungal communities of kaolin-mined plants compared to non-kaolin-mined areas. The results show that heavy metals and plant species are the key factors influencing these changes, which suggests that selecting plants that can bring more abundant fungi can adapt to heavy metal contamination to restore soil ecology in the kaolin mining area.

Impact of Vanadium-Titanium-Magnetite Mining Activities on Endophytic Bacterial Communities and Functions in the Root Systems of Local Plants.

This study utilized 16S rRNA high-throughput sequencing technology to analyze the community structure and function of endophytic bacteria within the roots of three plant species in the vanadium-titanium-magnetite (VTM) mining area. The findings indicated that mining activities of VTM led to a notable decrease in both the biodiversity and abundance of endophytic bacteria within the root systems of Eleusine indica and Carex (p < 0.05). Significant reductions were observed in the populations of Nocardioides, concurrently with substantial increments in the populations of Pseudomonas (p < 0.05), indicating that Pseudomonas has a strong adaptability to this environmental stress. In addition, ß diversity analysis revealed divergence in the endophytic bacterial communities within the roots of E. indica and Carex from the VTM mining area, which had diverged to adapt to the environmental stress caused by mining activity. Functional enrichment analysis revealed that VTM mining led to an increase in polymyxin resistance, nicotinate degradation I, and glucose degradation (oxidative) (p < 0.05). Interestingly, we found that VTM mining did not notably alter the endophytic bacterial communities or functions in the root systems of Dodonaea viscosa, indicating that this plant can adapt well to environmental stress. This study represents the primary investigation into the influence of VTM mining activities on endophytic bacterial communities and the functions of nearby plant roots, providing further insight into the impact of VTM mining activities on the ecological environment.

Intraspecific and interspecific variations in the synonymous codon usage in mitochondrial genomes of 8 pleurotus strains.

In this study, we investigated the codon bias of twelve mitochondrial core protein coding genes (PCGs) in eight Pleurotus strains, two of which are from the same species. The results revealed that the codons of all Pleurotus strains had a preference for ending in A/T. Furthermore, the correlation between codon base compositions and codon adaptation index (CAI), codon bias index (CBI) and frequency of optimal codons (FOP) indices was also detected, implying the influence of base composition on codon bias. The two P. ostreatus species were found to have differences in various base bias indicators. The average effective number of codons (ENC) of mitochondrial core PCGs of Pleurotus was found to be less than 35, indicating strong codon preference of mitochondrial core PCGs of Pleurotus. The neutrality plot analysis and PR2-Bias plot analysis further suggested that natural selection plays an important role in Pleurotus codon bias. Additionally, six to ten optimal codons (ΔRSCU > 0.08 and RSCU > 1) were identified in eight Pleurotus strains, with UGU and ACU being the most widely used optimal codons in Pleurotus. Finally, based on the combined mitochondrial sequence and RSCU value, the genetic relationship between different Pleurotus strains was deduced, showing large variations between them. This research has improved our understanding of synonymous codon usage characteristics and evolution of this important fungal group.

Adjusting Catalytic Activity of ß-Amyrin Synthase GgBAS by Utilizing the Plasticity Residues of an Active Site.

ß-Amyrin synthase (bAS) is a representative plant oxidosqualene cyclase (OSC), and previous studies have identified many functional residues and mutants that can alter its catalytic activity. However, the regulatory mechanism of the active site architecture for adjusting the catalytic activity remains unclear. In this study, we investigate the function of key residues and their regulatory effects on the catalytic activity of Glycyrrhiza glabra ß-amyrin synthase (GgbAS) through molecular dynamics simulations and site-directed mutagenesis experiments. We identified the plasticity residues located in two active site regions and explored the interactions between these residues and tetracyclic/pentacyclic intermediates. Based on computational and experimental results, we further categorize these plasticity residues into three types: effector, adjuster, and supporter residues, according to their functions in the catalytic process. This study provides valuable insights into the catalytic mechanism and active site plasticity of GgbAS, offering important references for the rational enzyme engineering of other OSC enzyme.

Discovery of novel bromodomain-containing protein 4 (BRD4-BD1) inhibitors combined with 3d-QSAR, molecular docking and molecular dynamics in silico.

Bromine-containing domain protein 4 (BRD4) plays a crucial role in regulating transcription and genome stability. Selective inhibitors of BRD4-BD1 can specifically target specific bromine domains to affect cell proliferation, apoptosis, and differentiation. In this work, 43 selective benzoazepinone BRD4-BD1 inhibitors were studied using molecular simulations and three-dimensional quantitative conformation relationships (3D-QSAR). A reliable 3D-QSAR model was established based on COMFA (Q2 = 0.532, R2 = 0.981) and COMSIA (S + E + H (Q2 = 0.536, R2 = 0.979) two different analysis methods. Through 3D-QSAR model prediction and quantum chemical analysis, 15 small molecules with stronger inhibitory activity than the template compounds were constructed, and 5 new compounds with higher predictive activity and binding affinity were screened by molecular docking and ADMET methods. According to the molecular dynamics simulation, the key residues that can interact with BRD4-BD1 protein and molecular docking results are consistent, including ASN140, MET132, GLN85, MET105, ASN135 and TYR97. From the MD trajectory, we calculated and analyzed RMSD, RMSF, free binding energy, FECM, DCCM and PCA, the loop region formed by amino acids VAL45∼PRO62 showed α-helix, ß-folding and clustering towards the active center with the extension of simulation time. Further optimization of the structure of active candidate compounds A6, A11, A14, and A15 will provide the necessary theoretical basis for the synthesis and activity evaluation of novel BRD4-BD1 inhibitors.Communicated by Ramaswamy H. Sarma.

Polysaccharide from Boletus aereus ameliorates DSS-induced colitis in mice by regulating the MANF/MUC2 signaling and gut microbiota.

Inflammatory bowel diseases (IBD) are chronic inflammatory conditions characterized by disruptions in the colonic mucus barrier and gut microbiota. In this study, a novel soluble polysaccharide obtained from Boletus aereus (BAP) through water extraction was examined for its structure. The protective effects of BAP on colitis were investigated using a DSS-induced mice model. BAP was found to promote the expression of intestinal mucosal and tight junction proteins, restore the compromised mucus barrier, and suppress the activation of inflammatory signaling. Moreover, BAP reshape the gut microbiota and had a positive impact on the composition of the gut microbiota by reducing inflammation-related microbes. Additionally, BAP decreased cytokine levels through the MANF-BATF2 signaling pathway. Correlation analysis revealed that MANF was negatively correlated with the DAI and the level of cytokines. Furthermore, the depletion of gut microbiota using antibiotic partially inhabited the effect of BAP on the activation of MANF and Muc2, indicating the role of gut microbiota in its protective effect against colitis. In conclusion, BAP had an obvious activation on MANF under gut inflammation. This provides new insights into the prospective use of BAP as a functional food to enhance intestinal health.

Structural changes of rice starch-anthocyanins complexes (V-type) and its impact on gut microbiotas and potential metabolic pathways during in vitro fermentation.

This study explored the differences in the in vitro fermentation properties of rice starch (RS) and rice starch-anthocyanins complexes (RS-A). Structural characterization suggested that RS and RS-A complexes showed a V-type crystalline structure. The degree of order (DO) and degree of double helix (DD) values of RS and RS-A complexes were enhanced after fermentation. Moreover, the RS-A complexes could improve the relative abundance of Bacteroidetes, Ruminococcaceae, and up-regulate gut microbiota diversity to maintain gut homeostasis. Relative abundance of potential metabolic pathways, such as energy metabolism, digestion system, and carbohydrate degradation overexpressed in the presence of RS-A complexes. The results demonstrated that the RS-A complexes had slower fermentation rates contributing to the transport of the formed short-chain fatty acid (SCFA) to the end of the colon and that the crystallinity might be a factor influencing the utilization of the starch matrix by the gut microbiota for SCFA formation.

Accelerated Selective Li+ Transports Assisted by Microcrack-Free Anionic Network Polymer Membranes for Long Cyclable Lithium Metal Batteries.

Rechargeable Li metal batteries have the potential to meet the demands of high-energy density batteries for electric vehicles and grid-energy storage system applications. Achieving this goal, however, requires resolving not only safety concerns and a shortened battery cycle life arising from a combination of undesirable lithium dendrite and solid-electrolyte interphase formations. Here, a series of microcrack-free anionic network polymer membranes formed by a facile one-step click reaction are reported, displaying a high cation conductivity of 3.1 × 10-5 S cm-1 at high temperature, a wide electrochemical stability window up to 5 V, a remarkable resistance to dendrite growth, and outstanding non-flammability. These enhanced properties are attributed to the presence of tethered borate anions in microcrack-free membranes, which benefits the acceleration of selective Li+ cations transport as well as suppression of dendrite growth. Ultimately, the microcrack-free anionic network polymer membranes render Li metal batteries a safe and long-cyclable energy storage device at high temperatures with a capacity retention of 92.7% and an average coulombic efficiency of 99.867% at 450 cycles.

3D Printing of a Vascularized Mini-Liver Based on the Size-Dependent Functional Enhancements of Cell Spheroids for Rescue of Liver Failure.

The emerging stem cell-derived hepatocyte-like cells (HLCs) are the alternative cell sources of hepatocytes for treatment of highly lethal acute liver failure (ALF). However, the hostile local environment and the immature cell differentiation may compromise their therapeutic efficacy. To this end, human adipose-derived mesenchymal stromal/stem cells (hASCs) are engineered into different-sized multicellular spheroids and co-cultured with 3D coaxially and hexagonally patterned human umbilical vein endothelial cells (HUVECs) in a liver lobule-like manner to enhance their hepatic differentiation efficiency. It is found that small-sized hASC spheroids, with a diameter of ≈50 µm, show superior pro-angiogenic effects and hepatic differentiation compared to the other counterparts. The size-dependent functional enhancements are mediated by the Wnt signaling pathway. Meanwhile, co-culture of hASCs with HUVECs, at a HUVECs/hASCs seeding density ratio of 2:1, distinctly promotes hepatic differentiation and vascularization both in vitro and in vivo, especially when endothelial cells are patterned into hollow hexagons. After subcutaneous implantation, the mini-liver, consisting of HLC spheroids and 3D-printed interconnected vasculatures, can effectively improve liver regeneration in two ALF animal models through amelioration of local oxidative stress and inflammation, reduction of liver necrosis, as well as increase of cell proliferation, thereby showing great promise for clinical translation.

Engineering novel scaffolds for specific HDAC11 inhibitors against metabolic diseases exploiting deep learning, virtual screening, and molecular dynamics simulations.

The prevalence of metabolic diseases is increasing at a frightening rate year by year. The burgeoning development of deep learning enables drug design to be more efficient, selective, and structurally novel. The critical relevance of Histone deacetylase 11 (HDAC11) to the pathogenesis of several metabolic diseases makes it a promising drug target for curbing metabolic disorders. The present study aims to design new specific HDAC11 inhibitors for the treatment of metabolic diseases. Deep learning was performed to learn the properties of existing HDAC11 inhibitors and yield a novel compound library containing 23,122 molecules. Subsequently, the compound library was screened by ADMET properties, Lipinski & Veber rules, traditional machine classification models, and molecular docking, and 10 compounds were screened as candidate HDAC11 inhibitors. The stability of the 10 new molecules was further evaluated by deploying RMSD, RMSF, MM/GBSA, free energy landscape mapping, and PCA analysis in molecular dynamics simulations. As a result, ten compounds, Cpd_17556, Cpd_2184, Cpd_8907, Cpd_7771, Cpd_14959, Cpd_7108, Cpd_12383, Cpd_13153, Cpd_14500and Cpd_21811, were characterized as good HDAC11 inhibitors and are expected to be promising drug candidates for metabolic disorders, and further in vitro, in vivo and clinical trials to demonstrate in the future.

An investigation of the effects of meteorological factors on the incidence of tuberculosis.

To explore the influence of meteorological factors on the incidence of tuberculosis (TB) in Yingjisha County, Kashgar Region, Xinjiang, and to provide a scientific basis for the prevention and control of TB. The Spearman correlation analysis and distribution lag nonlinear model analysis were conducted on the number of daily reported cases of TB from 2016 to 2023 to study the association effect of various meteorological factors and the daily incidence number of TB in Yingjisha County. A total of 13,288 TB cases were reported from January 2016 to June 2023, and June to October is the peak period of annual TB incidence. Spearman correlation analysis revealed that average daily temperature (AT) and average daily wind speed (WS) were positively correlated with TB incidence (rAT = 0.110, rWS = 0.090); and average daily relative humidity (RH) and TB incidence was negatively correlated (rRH = - 0.093). When AT was - 15 °C, the RR reached a maximum of 2.20 (95% CI: 0.77-6.29) at a lag of 21 days. When RH was 92%, the RR reached a maximum of 1.05 (95% CI: 0.92-1.19) at a lag of 6 days. When WS was 5.2 m/s, the RR reached a maximum of 1.30 (95% CI: 0.78-2.16) at a lag of 16 days. There is a non-linearity and a certain lag between meteorological factors and the occurrence and prevalence of TB in the population, which is mainly manifested in the fact that the risk of incidence of TB decreases with the increase of the daily AT, has a hazardous effect within a certain range of humidity as the average daily RH rises, and gradually increases with the increase of the average daily WS. Local residents are advised to pay attention to climate change so as to take appropriate preventive measures, especially women and middle and old age group should pay close attention to climate change and add more clothes in time, minimise travelling in hazy weather and windy and sandy weather, maintain good nutrition, adequate sleep and moderate exercise in daily life to enhance their immunity, wash hands frequently and ventilate the air, and try to avoid staying in humid and confined spaces in order to reduce the risk of latent TB patients developing the disease.

Anti-inflammatory activity of Boletus aereus polysaccharides: Involvement of digestion and gut microbiota fermentation.

Boletus aereus, an edible mushroom, has gained popularity as a medicinal and functional food. This study aimed to investigate the digestive characteristics of B. aereus polysaccharide (BAP) and its effects on gut microbiota. In vitro digestion results indicated partial degradation of BAP. Furthermore, the digested BAP displayed significantly enhanced antioxidant ability. The 16S rRNA sequencing data revealed that BAP positively influenced the abundance of Phascolarctobacterium, Prevotella, and Bifidobacterium in the gut microbiota. Additionally, BAP promoted the production of short-chain fatty acids (SCFAs). Metabolites of BAP utilized by the gut microbiota effectively reduced the concentration of TNF-α, IL-1ß, and NO in an LPS-stimulated RAW 264.7 cell inflammation model. Mantel tests demonstrated a strong correlation among fermentation indicators, gut microbiome composition, SCFAs, and inflammatory cytokines. Overall, this research revealed the underlying digestive and fermentation mechanisms of BAP and provided new insights into the usage of edible mushroom polysaccharides in functional food.

Decoding Biomechanical Cues Based on DNA Sensors.

Biological systems perceive and respond to mechanical forces, generating mechanical cues to regulate life processes. Analyzing biomechanical forces has profound significance for understanding biological functions. Therefore, a series of molecular mechanical techniques have been developed, mainly including single-molecule force spectroscopy, traction force microscopy, and molecular tension sensor systems, which provide indispensable tools for advancing the field of mechanobiology. DNA molecules with a programmable structure and well-defined mechanical characteristics have attached much attention to molecular tension sensors as sensing elements, and are designed for the study of biomechanical forces to present biomechanical information with high sensitivity and resolution. In this work, a comprehensive overview of molecular mechanical technology is presented, with a particular focus on molecular tension sensor systems, specifically those based on DNA. Finally, the future development and challenges of DNA-based molecular tension sensor systems are looked upon.

CloudBrain-MRS: An intelligent cloud computing platform for in vivo magnetic resonance spectroscopy preprocessing, quantification, and analysis.

Magnetic resonance spectroscopy (MRS) is an important clinical imaging method for diagnosis of diseases. MRS spectrum is used to observe the signal intensity of metabolites or further infer their concentrations. Although the magnetic resonance vendors commonly provide basic functions of spectrum plots and metabolite quantification, the spread of clinical research of MRS is still limited due to the lack of easy-to-use processing software or platform. To address this issue, we have developed CloudBrain-MRS, a cloud-based online platform that provides powerful hardware and advanced algorithms. The platform can be accessed simply through a web browser, without the need of any program installation on the user side. CloudBrain-MRS also integrates the classic LCModel and advanced artificial intelligence algorithms and supports batch preprocessing, quantification, and analysis of MRS data from different vendors. Additionally, the platform offers useful functions: (1) Automatically statistical analysis to find biomarkers for diseases; (2) Consistency verification between the classic and artificial intelligence quantification algorithms; (3) Colorful three-dimensional visualization for easy observation of individual metabolite spectrum. Last, data of both healthy subjects and patients with mild cognitive impairment are used to demonstrate the functions of the platform. To the best of our knowledge, this is the first cloud computing platform for in vivo MRS with artificial intelligence processing. We have shared our cloud platform at MRSHub, providing at least two years of free access and service. If you are interested, please visit https://mrshub.org/software_all/#CloudBrain-MRS or https://csrc.xmu.edu.cn/CloudBrain.html.

Full hardware implementation of neuromorphic visual system based on multimodal optoelectronic resistive memory arrays for versatile image processing.

In-sensor and near-sensor computing are becoming the next-generation computing paradigm for high-density and low-power sensory processing. To fulfil a high-density and efficient neuromorphic visual system with fully hierarchical emulation of the retina and visual cortex, emerging multimodal neuromorphic devices for multi-stage processing and a fully hardware-implemented system with versatile image processing functions are still lacking and highly desirable. Here we demonstrate an emerging multimodal-multifunctional resistive random-access memory (RRAM) device array based on modified silk fibroin protein (MSFP), exhibiting both optoelectronic RRAM (ORRAM) mode featured by unique negative and positive photoconductance memory and electrical RRAM (ERRAM) mode featured by analogue resistive switching. A full hardware implementation of the artificial visual system with versatile image processing functions is realised for the first time, including ORRAM mode array for the in-sensor image pre-processing (contrast enhancement, background denoising, feature extraction) and ERRAM mode array for near-sensor high-level image recognition, which hugely improves the integration density, and simply the circuit design and the fabrication and integration complexity.

Structural optimization of pyrrolopyrimidine BTK inhibitors based on molecular simulation.

CONTEXT: BTK is a critical regulator involved in the proliferation, differentiation, and apoptosis of B cells. BTK inhibitors can effectively alleviate various diseases such as tumors, leukemia, and asthma. During this study, a range of novel BTK inhibitors were designed using 3D-QSAR, molecular docking, and molecular dynamics (MD) simulation. METHODS: We selected 41 pyrrolopyrimidine derivatives as BTK inhibitors to structure a 3D-QSAR model. Comparative molecular field analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA) were adopted to research the connection between the pharmacological activities and chemical structures of the compounds. The CoMFA model (q2 = 0.519, R2 = 0.971), CoMSIA model (q2 = 0.512, R2 = 0.990), and external validation demonstrated excellent predictive performance and reliability of the 3D-QSAR model. We designed eight novel molecules with higher inhibitory activities according to the three-dimensional equipotential fields and explored the interactions between the compounds and BTK by molecular docking, which showed that the novel molecules had higher binding affinities with BTK than the template molecule 18. Then, the results of molecular docking were further verified by MD simulation, which showed that amino acid residues such as Leu528, Val416, and Met477 played vital parts in the interaction, and the binding free energy analysis showed that the novel molecules had higher stability with BTK. Finally, the ADME/T properties were predicted for all of the novel compounds, and the results showed that the majority of them had favorable pharmacokinetic properties. Therefore, this study provides strong support for the development of novel BTK inhibitors.

Analysis of spatial characteristics and geographic weighted regression of tuberculosis prevalence in Kashgar, China.

Number of cases of tuberculosis (TB) was higher than that of the national level in Kashgar, China. This study aimed to analyze the spatial and temporal distribution of TB and the relationship between TB and social factors, which can provide a reference for the prevention and control of TB. We applied spatial autocorrelation analysis to study the distribution of tuberculosis in Kashgar. We used a geographically weighted regression (GWR) model to analyze the relationship between TB and social factors. A total of 100,330 cases of TB in Kashgar from 2016 to 2021 were analyzed. The number of TB cases in Kashgar was higher in the east, lower in the west, and most elevated in the center. The highest cumulative number of cases was found in Shache county. Global Moran's I ranged from -0.212 to -0.549, and local spatial autocorrelation analysis identified four clusters. According to our analysis, the incidence of tuberculosis was negatively correlated among the regions of Kashgar, and the related causes need to be analyzed in depth in future studies. Per capita gross domestic product (GDP), number of medical institutions per capita, and total population influenced the incidence of tuberculosis in Kashgar. Based on our findings, we suggest some effective measures to reduce the risk of TB infection, such as improving the living standard, developing the regional economy, and distributing health resources rationally.

Monocytes in Tumorigenesis and Tumor Immunotherapy.

Monocytes are highly plastic innate immune cells that display significant heterogeneity during homeostasis, inflammation, and tumorigenesis. Tumor-induced systemic and local microenvironmental changes influence the phenotype, differentiation, and distribution of monocytes. Meanwhile, monocytes and their related cell subsets perform an important regulatory role in the development of many cancers by affecting tumor growth or metastasis. Thanks to recent advances in single-cell technologies, the nature of monocyte heterogeneity and subset-specific functions have become increasingly clear, making it possible to systematically analyze subset-specific roles of monocytes in tumorigenesis. In this review, we discuss recent discoveries related to monocytes and tumorigenesis, and new strategies for tumor biomarker identification and anti-tumor immunotherapy.