Targeting metabolism to enhance immunotherapy within tumor microenvironment.

Cancer metabolic reprogramming has been considered an emerging hallmark in tumorigenesis and the antitumor immune response. Like cancer cells, immune cells within the tumor microenvironment or premetastatic niche also undergo extensive metabolic reprogramming, which profoundly impacts anti-tumor immune responses. Numerous evidence has illuminated that immunosuppressive TME and the metabolites released by tumor cells, including lactic acid, Prostaglandin E2 (PGE2), fatty acids (FAs), cholesterol, D-2-Hydroxyglutaric acid (2-HG), adenosine (ADO), and kynurenine (KYN) can contribute to CD8+ T cell dysfunction. Dynamic alterations of these metabolites between tumor cells and immune cells can similarly initiate metabolic competition in the TME, leading to nutrient deprivation and subsequent microenvironmental acidosis, which impedes immune response. This review summarizes the new landscape beyond the classical metabolic pathways in tumor cells, highlighting the pivotal role of metabolic disturbance in the immunosuppressive microenvironment, especially how nutrient deprivation in TME leads to metabolic reprogramming of CD8+ T cells. Likewise, it emphasizes the current therapeutic targets or strategies related to tumor metabolism and immune response, providing therapeutic benefits for tumor immunotherapy and drug development in the future. Cancer metabolic reprogramming has been considered an emerging hallmark in tumorigenesis and the antitumor immune response. Dynamic alterations of metabolites between tumor cells and immune cells initiate metabolic competition in the TME, leading to nutrient deprivation and subsequent microenvironmental acidosis, which impedes immune response.

Bifidobacterium Relieved Fluoride-Induced Hepatic and Ileal Toxicity via Inflammatory Response and Bile Acid Transporters in Mice.

Fluoride is a pervasive environmental contaminant. Prolonged excessive fluoride intake can inflict severe damage on the liver and intestines. Previous 16S rDNA sequencing revealed a decrease in ileal Bifidobacterium abundance during fluoride-induced hepatointestinal injury. Hence, this work aimed to investigate the possible mitigating function of Bifidobacterium on hepatointestinal injury caused by fluoride. Thirty-six 6-week-old C57BL/6J mice (equally divided between males and females) were allotted randomly to three groups: Ctrl group (distilled water), NaF group, and NaF + Ba group (100 mg/L NaF distilled water). After 10 weeks, the mice were given 1 × 109 CFU/mL Bifidobacterium solution (0.2 mL/day) intragastrically in the NaF + Ba group for 8 weeks, and the mice in other groups were given the same amount of distilled water. Dental damage, bone fluoride content, blood routine, liver and intestinal microstructure and function, inflammatory factors, and regulatory cholic acid transporters were examined. Our results showed that fluoride increased glutamic-oxalacetic transaminase (GOT), glutamic-pyruvic transaminase (GPT) activities, and the levels of lipopolysaccharide (LPS), IL-1ß, IL-6, TNF-α, and IL-10 levels in serum, liver, and ileum. However, Bifidobacterium intervention alleviated fluoride-induced changes in the above indicators. In addition, Bifidobacterium reduced the mRNA expression levels of bile acid transporters ASBT, IBABP, OST-α, and OST-ß in the ileum. In summary, Bifidobacterium supplementation relieved fluoride-induced hepatic and ileal toxicity via an inflammatory response and bile acid transporters in the liver and ileum of mice.

Dbl family RhoGEFs in cancer: different roles and targeting strategies.

Small Ras homologous guanosine triphosphatase (Rho GTPase) family proteins are highly associated with tumorigenesis and development. As intrinsic exchange activity regulators of Rho GTPases, Rho guanine nucleotide exchange factors (RhoGEFs) have been demonstrated to be closely involved in tumor development and received increasing attention. They mainly contain two families: the diffuse B-cell lymphoma (Dbl) family and the dedicator of cytokinesis (Dock) family. More and more emphasis has been paid to the Dbl family members for their abnormally high expression in various cancers and their correlation to poor prognosis. In this review, the common and distinctive structures of Dbl family members are discussed, and their roles in cancer are summarized with a focus on Ect2, Tiam1/2, P-Rex1/2, Vav1/2/3, Trio, KALRN, and LARG. Significantly, the strategies targeting Dbl family RhoGEFs are highlighted as novel therapeutic opportunities for cancer.

Fluoride induces pyroptosis via IL-17A-mediated caspase-1/11-dependent pathways and Bifidobacterium intervention in testis.

Fluoride, a ubiquitous environmental pollutant, poses a significant public health threat. Our previous study revealed a correlation between fluoride-induced testicular pyroptosis and male reproductive dysfunction. However, the underlying mechanism remains unclear. Wild-type and interleukin 17A knockout mice were exposed to sodium fluoride (100 mg/L) in deionized drinking water for 18 weeks. Bifidobacterium intervention (1 × 109 CFU/mL, 0.2 mL/day, administered via gavage) commenced in the 10th week. Sperm quality, testicular morphology, key pyroptosis markers, spermatogenesis key genes, IL-17A signaling pathway, and pyroptosis pathway related genes were determined. The results showed that fluoride reduced sperm quality, damaged testicular morphology, affected spermatogenesis, elevated IL-17A levels, and induced testicular pyroptosis. Bifidobacterium intervention alleviated adverse reproductive outcomes. Fluoride-activated testicular pyroptosis through both typical and atypical pathways, with IL-17A involvement. Bifidobacterium supplementation attenuated pyroptosis by downregulating IL-17A, inhibiting NLRP3 and PYRIN-mediated caspase-1 and caspase-11 dependent pathways in testis, thereby alleviating fluoride-induced male reproductive damage. In summary, this study uncovers the mechanism underlying fluorine-induced testicular pyroptosis and illustrates the novel protecting feature of Bifidobacterium against fluoride-induced harm to male reproduction, along with its potential regulatory mechanism. These results provide fresh perspectives on treating male reproductive dysfunction resulting from fluoride or other environmental toxins.

Molecular-level transformations of biomass burning-derived water-soluble organic carbon during dark aqueous OH oxidation: Insights from absorption, fluorescence, high-performance size exclusion chromatography and high-resolution mass spectrometry analysis.

Biomass burning (BB) releases large amounts of water-soluble organic carbon (WSOC), which would undergo heterogenous oxidation processes that induce transformations in both molecular structures and compositions within BB WSOC. This study designed an aqueous oxidation initiated by OH radicals in the absence of light for WSOC extracted from smoke particles generated by burning of corn straw and fir wood. The BB WSOC was comprehensively characterized using a combination of UV-visible spectra, excitation-emission matrix fluorescence in conjunction with parallel factor analysis (EEM-PARAFAC), high-performance size exclusion chromatography (HPSEC), and high-resolution mass spectrometry (HRMS) analyses. Over the course of oxidation, both chromophores and fluorophores exhibited gradual decreases. Moreover, EEM-PARAFAC revealed a preferential degradation of larger-sized protein-like/phenol-like organic matters, accompanied by the accumulation and/or formation of humic-like substances in aged BB WSOC. HPSEC analysis showed notable changes in molecular weight (MW) distributions for both types of BB WSOC during oxidation. Specifically, high MW species (>1 kDa) displayed a tendency to form along with oxidation, possibly attributed to the formation of assemblies via intermolecular weak forces. After oxidation, evidence of CHO compound degradation and enrichment/formation of CHON compounds was observed for both types of BB WSOC. Remarkably, the resistant, degraded and produced molecules for BB WSOC were dominated by CHO (38-73 %) and lignin-like molecules (41-47 %), suggesting diverse responses to oxidation within these two groups. Furthermore, polyphenols experienced selective degradation, while CHON, aliphatic and poly-aromatic molecules tended to form during the oxidation process for both types of BB WSOC. In summary, this study provides a comprehensive understanding of the molecular-level transformations undergone by BB WSOC during dark aqueous OH oxidation. The findings significantly contribute to our insights into atmospheric evolution of BB WSOC, thereby playing a crucial role in accurately assessing their effects within climate models and informing policy decisions.

Corrigendum: Learning the heterogeneous representation of brain's structure from serial SEM images using a masked autoencoder.

[This corrects the article DOI: 10.3389/fninf.2023.1118419.].

Anti-Inflammatory Mechanism of Ligustrum Lucidum Ait Based on Network Pharmacology and Molecular Docking.

OBJECTIVE: To investigate possible targets of Ligustrum lucidum and its anti-inflammatory mechanism. Core targets were screened by the established networks of component target and potential protein interaction, accompanied by GO and KEGG analyses. The findings were confirmed using molecular docking. RESULTS: eight active components including Quercetin, luteolin, kaempferol and corresponding 163 potential targets, including CCL2, IL6, CXCL8, TNF, IL1B, were identified with a threshold of OB ≥ 30% and DL ≥ 0.18%. 1018 anti-inflammatory targets were acquired, with 101 common targets identified by mutual mapping. 172 nodes and 287 edges are readable in the "component target" visualization network graph. The KEGG analysis identified 20 significantly differentiated signaling pathways, including IL-17, toll-like receptor, TNF, HIF-1, lipid and atherosclerosis. CONCLUSION: Molecular docking has verified the binding sites and energies of the chemical components in Ligustrum lucidum with key anti-inflammatory proteins, providing a theoretical basis for its clinical use and development.

Organic Excitonic State Management by Surface Metallic Coupling of Inorganic Lanthanide Nanocrystals.

The ability to harness charges and spins for control of organic excitonic states is critical in developing high-performance organic luminophores and optoelectronic devices. Here we report a facile strategy to efficiently manipulate the electronic energy states of various organic phosphors by coupling them with inorganic lanthanide nanocrystals. We show that the metallic atoms exposed on the nanocrystal surface can introduce strong coupling effects to 9-(4-ethoxy-6-phenyl-1,3,5-triazin-2-yl)-9H-carbazole (OCzT) and some organic chromophores with carbazole functional groups when the organics are approaching the nanocrystals. This unconventional organic-inorganic hybridization enables a nearly 100 % conversion of the singlet excitation to fast charge transfer luminescence that does not exist in pristine organics, which broadens the utility of organic phosphors in hybrid systems.

Investigating the molecular weight distribution of atmospheric water-soluble brown carbon using high-performance size exclusion chromatography coupled with diode array and fluorescence detectors.

Atmospheric brown carbon (BrC) contain amounts of organic species, but their molecular weight (MW) distributions is still poorly understood. This study applied high-performance size exclusion chromatography (HPSEC) coupled with a diode array detector (DAD) and fluorescence detector (FLD) to characterize the MW distributions of typical chromophores and fluorophores within water-soluble BrC. The investigation focused on the spring season, encompassing both typical urban and rural aerosols. Our results showed that chromophores (at 254 and 365 nm), and humic-like and protein-like fluorophores identified by excitation-emission matrix parallel factor analysis (EEM-PARAFAC) within BrC were broadly distributed along the MW continuum (∼50-20,000 Da). This suggests that BrC mainly comprises complex chromophores and fluorophores with heterogeneous molecular sizes. High-MW (HMW, >1 kDa) species (66%-74%) dominated the chromophores at 254 and 365 nm. However, the latter chromophores were enriched with more HMW species. This result suggested that the HMW chromophores might contribute more to BrC absorption at longer wavelengths. The PARAFAC-derived fluorescent components also exhibited different MW distributions. Three humic-like substances (HULIS) were all dominated by HMW fractions (51%-74%), but protein-like fluorescent component (PLOM) enriched low-MW (LMW, <1 kDa) species (60%-66%). Furthermore, the molecular size (i.e., weight-averaged and number-averaged MW) and the ratios between HMW and LMW species decreased in the order highly-oxygenated HULIS > less-oxygenated HULIS > PLOM, indicating that the fluorophores with longer Em were generally related to larger MW. To our knowledge, this is the first report on the molecular size of individual fluorescent components within aerosol BrC. The results obtained here enhanced our knowledge of heterogeneous composition, complex physicochemical properties, and potential atmospheric fates of aerosol BrC.

Learning the heterogeneous representation of brain's structure from serial SEM images using a masked autoencoder.

Introduction: The exorbitant cost of accurately annotating the large-scale serial scanning electron microscope (SEM) images as the ground truth for training has always been a great challenge for brain map reconstruction by deep learning methods in neural connectome studies. The representation ability of the model is strongly correlated with the number of such high-quality labels. Recently, the masked autoencoder (MAE) has been shown to effectively pre-train Vision Transformers (ViT) to improve their representational capabilities. Methods: In this paper, we investigated a self-pre-training paradigm for serial SEM images with MAE to implement downstream segmentation tasks. We randomly masked voxels in three-dimensional brain image patches and trained an autoencoder to reconstruct the neuronal structures. Results and discussion: We tested different pre-training and fine-tuning configurations on three different serial SEM datasets of mouse brains, including two public ones, SNEMI3D and MitoEM-R, and one acquired in our lab. A series of masking ratios were examined and the optimal ratio for pre-training efficiency was spotted for 3D segmentation. The MAE pre-training strategy significantly outperformed the supervised learning from scratch. Our work shows that the general framework of can be a unified approach for effective learning of the representation of heterogeneous neural structural features in serial SEM images to greatly facilitate brain connectome reconstruction.

Trends and characteristics of COVID-19 and cardiovascular disease related studies.

Introduction: The new coronavirus has caused a pandemic that has infected hundreds of millions of people around the world since its outbreak. But the cardiovascular damage caused by the new coronavirus is unknown. We have analyzed the current global scenario and the general pattern of growth. After summarizing the known relationship between cardiovascular diseases and new coronary pneumonia, relevant articles are analyzed through bibliometrics and visualization. Methods: Following our pre-designed search strategy, we selected publications on COVID-19 and cardiovascular disease in the Web of Science database. In our relevant bibliometric visualization analysis, a total of 7,028 related articles in the WOS core database up to 20th October 2022 were summarized, and the most prolific authors, the most prolific countries, and the journals and institutions that published the most articles were summarized and quantitatively analyzed. Results: SARS-CoV-2 is more infectious than SARS-CoV-1 and has significant involvement in the cardiovascular system in addition to pulmonary manifestations, with a difference of 10.16% (20.26%/10.10%) in the incidence of cardiovascular diseases. The number of cases increases in winter and decreases slightly in summer with temperature changes, but the increase in cases tends to break out of seasonality across the region as mutant strains emerge. The co-occurrence analysis found that with the progress of the epidemic, the research keywords gradually shifted from ACE2 and inflammation to the treatment of myocarditis and complications, indicating that the research on the new crown epidemic has entered the stage of prevention and treatment of complications. Conclusion: When combined with the current global pandemic trend, how to improve prognosis and reduce human body damage could become a research focus. At the same time, timely detection, prevention, and discovery of new mutant strains have also become key tasks in the fight against the epidemic, and full preparations have been made to prevent the spread of the next wave of mutant strains, and still need to continue to pay attention to the differential performance of the variant "omicron."

Improving the Neural Segmentation of Blurry Serial SEM Images by Blind Deblurring.

Serial scanning electron microscopy (sSEM) has recently been developed to reconstruct complex largescale neural connectomes, through learning-based instance segmentation. However, blurry images are inevitable amid prolonged automated data acquisition due to imprecision in autofocusing and autostigmation, which impose a great challenge to accurate segmentation of the massive sSEM image data. Recently, learning-based methods, such as adversarial learning and supervised learning, have been proven to be effective for blind EM image deblurring. However, in practice, these methods suffer from the limited training dataset and the underrepresentation of high-resolution decoded features. Here, we propose a semisupervised learning guided progressive decoding network (SGPN) to exploit unlabeled blurry images for training and progressively enrich high-resolution feature representation. The proposed method outperforms the latest deblurring models on real SEM images with much less ground truth input. The improvement of the PSNR and SSIM is 1.04 dB and 0.086, respectively. We then trained segmentation models with deblurred datasets and demonstrated significant improvement in segmentation accuracy. The A-rand (Bogovic et al. 2013) decreased by 0.119 and 0.026, respectively, for 2D and 3D segmentation.

Insight into the evolution characteristics on molecular weight of compost dissolved organic matters using high-performance size exclusion chromatography combined with a two-dimensional correlation analysis.

The information on molecular weight (MW) characteristics of DOM and relevant evolution behaviors during composting are limited. In this study, DOM extracted from co-composting of chicken manure and rice husks were comprehensively analyzed by using high-performance size exclusion chromatography (HPSEC) combined with a two-dimensional correlation spectroscopy (2D COS) to explore the evolution characteristics of MW of compost DOM. The HPSEC detected at UV of 254 nm and at fluorescence (FL) Ex/Em wavelengths (315/410, 270/455 nm) all showed a gradual increase in both weight-average and number-average MW for DOM, suggesting that the large MW fractions were continuously generated and polymerized during composting. The 2D COS applied on HPSEC-UV and -FL further identified the key active MW chromophoric (i.e., 0.5, 7.2. 9.5, 26.3, 30.7, and 83.9 kDa) and fluorophoric (i.e., 0.55 and 3.5 kDa) molecules that mainly participated in the transformation processes of compost DOM. Moreover, these active MW species were preferentially formed by the order of small to large molecules. A hetero-2D COS analysis disclosed the change sequence in the order of 0.5 and 7.2 kDa chromophores → 3.5 kDa fluorophores, and the 0.55 and 3.5 kDa fluorophores → 26.3 and 83.9 kDa chromophores.

Smart data collection for CryoEM.

This report provides an overview of the discussions, presentations, and consensus thinking from the Workshop on Smart Data Collection for CryoEM held at the New York Structural Biology Center on April 6-7, 2022. The goal of the workshop was to address next generation data collection strategies that integrate machine learning and real-time processing into the workflow to reduce or eliminate the need for operator intervention.

A method of regulating the wind field to reduce safety hazards of gas and dust in fully mechanized heading face based on dynamic data.

Accumulation of gas and dust in excavation work is a safety risk that remains to be solved. A substantial amount of gas and dust accumulate in fully mechanized heading face outlets, and the press-in tube jet cannot be adjusted dynamically based on the actual physical conditions. To solve the problem, a dynamic data-driven method for optimising gas and dust distribution by regulating the wind field is proposed. This method is based on the immune genetic algorithm and uses dynamic data as the incremental data with the historical data from the mine regulation rules to obtain the optimal incremental regulation rules (IRRs) for the wind field. The experiment was performed in Ningtiaota coal mine, Yulin city, northern Shaanxi, China. The observed wind velocity and gas concentrations were within the specification range when regulated by IRRs. The dust concentrations at the position of the driver and the average concentrations on the return air side decreased by 64.6 % and 56.5 %, respectively, when the outlet was 5 m from the head-on. When the distance of the outlet from the head-on was 10 m, the dust concentrations at the position of the driver and the average concentrations on the return air side dropped by 42.9 % and 68.6 %, respectively. The results from this study provide measures that would improve safety and efficiency during excavation of fully mechanized heading faces.

Comprehensive metabolomic characterization of the hippocampus in a ketamine mouse model of schizophrenia.

Ketamine is a noncompetitive antagonist of N-methyl-D-aspartate receptors (NMDARs). We have shown that ketamine can induce cognitive impairments and schizophrenia-like symptoms in mice. However, the detailed metabolic profile changes in the progression of ketamine-induced schizophrenia-like symptoms are still not fully elucidated. In this study, an ultra-performance liquid chromatography-Q-Exactive hybrid quadrupole-Orbitrap mass spectrometry-based untargeted hippocampus high-throughput metabolomics method was first performed to screen for potential biomarkers in a schizophrenia-like state in a chronically administered ketamine-induced mouse model. Our results identified that the amino acid and energy metabolism pathways were significantly affected in mouse models of ketamine-induced schizophrenia. The detailed amino acid profiles were subsequently quantified in the hippocampus. The results showed that ketamine dramatically decreased the Lys, Gly, and Ser levels while significantly increasing the Gln level and relative Glu-to-GABA ratio. Our study suggested that Gln, Gly and Ser metabolism disturbances might be involved in ketamine-induced schizophrenia-like phenotypes. This research offers a fresh viewpoint for creating new neuroleptic medications and contributes to understanding the mechanisms underlying ketamine-induced schizophrenia.

Modulation of autophagy as a therapeutic strategy for Toxoplasma gondii infection.

Toxoplasma gondii infection is a severe health threat that endangers billions of people worldwide. T. gondii utilizes the host cell membrane to form a parasitophorous vacuole (PV), thereby fully isolating itself from the host cell cytoplasm and making intracellular clearance difficult. PV can be targeted and destroyed by autophagy. Autophagic targeting results in T. gondii killing via the fusion of autophagosomes and lysosomes. However, T. gondii has developed many strategies to suppress autophagic targeting. Accordingly, the interplay between host cell autophagy and T. gondii is an emerging area with important practical implications. By promoting the canonical autophagy pathway or attenuating the suppression of autophagic targeting, autophagy can be effectively utilized in the development of novel therapeutic strategies against T gondii. Here, we have illustrated the complex interplay between host cell mediated autophagy and T. gondii. Different strategies to promote autophagy in order to target the parasite have been elucidated. Besides, we have analyzed some potential new drug molecules from the DrugBank database using bioinformatics tools, which can modulate autophagy. Various challenges and opportunities focusing autophagy mediated T. gondii clearance have been discussed, which will provide new insights for the development of novel drugs against the parasite.

Engineering carbon nanosheets with hexagonal ordered conical macropores as high-performance sodium-ion battery anodes.

As one of the most promising candidates for sodium-ion battery anodes, hard carbons suffer from inferior rate performance owing to limited ion transfer rate and sluggish electrochemical kinetics. In this work, novel carbon nanosheets (CNS) with hexagonal ordered conical macropores are prepared. The CNS has a very thin thickness of approximately 370 nm, and the conical pores are penetrated through the whole nanosheet, forming well-connected ion transport freeway. In addition, the carbon microcrystal structure and interlayer spacing can be well tailored by adjusting the carbonization temperature, thereby controlling the sodium storage behavior of carbon electrodes. These structural merits endow CNS with accelerated ion transfer, minimized ion diffusion distance and fast electrochemical kinetics. Consequently, the CNS presents superior electrochemical performance. It delivers a high reversible capacity of 298 mAh g-1 at 0.1 A g-1; and after repeated charge/discharge for 500 times at 1 A g-1, its capacity remains 195 mA h g-1, with no rapid capacity loss. More importantly, CNS exhibits outstanding rate capability. Even under a very high current density of 2 A g-1, it still displays a large capacity of 210 mAh g-1, higher than most of state-of-the-art carbon anodes.

Self-Assembly Vertical Graphene-Based MoO3 Nanosheets for High Performance Supercapacitors.

Supercapacitors have been extensively studied due to their advantages of fast-charging and discharging, high-power density, long-cycling life, low cost, etc. Exploring novel nanomaterial schemes for high-performance electrode materials is of great significance. Herein, a strategy to combine vertical graphene (VG) with MoO3 nanosheets to form a composite VG/MoO3 nanostructure is proposed. VGs as transition layers supply rich active sites for the growth of MoO3 nanosheets with increasing specific surface areas. The VG transition layer further improves the electric contact and adhesion of the MoO3 electrode, simultaneously stabilizing its volume and crystal structure during repeated redox reactions. Thus, the prepared VG/MoO3 nanosheets have been demonstrated to exhibit excellent electrochemical properties, such as high reversible capacitance, better cycling performance, and high-rate capability.