Identification of chronic non-atrophic gastritis and intestinal metaplasia stages in the Correa's cascade through machine learning analyses of SERS spectral signature of non-invasively-collected human gastric fluid samples.

The progression of gastric cancer involves a complex multi-stage process, with gastroscopy and biopsy being the standard procedures for diagnosing gastric diseases. This study introduces an innovative non-invasive approach to differentiate gastric disease stage using gastric fluid samples through machine-learning-assisted surface-enhanced Raman spectroscopy (SERS). This method effectively identifies different stages of gastric lesions. The XGBoost algorithm demonstrates the highest accuracy of 96.88% and 91.67%, respectively, in distinguishing chronic non-atrophic gastritis from intestinal metaplasia and different subtypes of gastritis (mild, moderate, and severe). Through blinded testing validation, the model can achieve more than 80% accuracy. These findings offer new possibilities for rapid, cost-effective, and minimally invasive diagnosis of gastric diseases.

Discovery of novel diaryl substituted isoquinolin-1(2H)-one derivatives as hypoxia-inducible factor-1 signaling inhibitors for the treatment of rheumatoid arthritis.

Since synovial hypoxic microenvironment significantly promotes the pathological progress of rheumatoid arthritis (RA), hypoxia-inducible factor 1 (HIF-1) has been emerged as a promising target for the development of novel therapeutic agents for RA treatment. In this study, we designed and synthesized a series of diaryl substituted isoquinolin-1(2H)-one derivatives as HIF-1 signaling inhibitors using scaffold-hopping strategy. By modifying the substituents on N-atom and 6-position of isoquinolin-1-one, we discovered compound 17q with the most potent activities against HIF-1 (IC50 = 0.55 µM) in a hypoxia-reactive element (HRE) luciferase reporter assay. Further pharmacological studies revealed that 17q concentration-dependently blocked hypoxia-induced HIF-1α protein accumulation, reduced inflammation response, inhibited cellular invasiveness and promoted VHL-dependent HIF-1α degradation in human RA synovial cell line. Moreover, 17q improved the pathological injury of ankle joints, decreased angiogenesis and attenuated inflammation response in the adjuvant-induced arthritis (AIA) rat model, indicating the promising therapeutic potential of compound 17q as an effective HIF-1 inhibitor for RA therapy.

Gestational supplementation of Bifidobacterium, Lactobacillus, and Streptococcus thermophilus attenuates hepatic steatosis in offspring mice through promoting fatty acid ß-oxidation.

Currently, Bifidobacterium, Lactobacillus, and Streptococcus thermophilus (BLS) are widely recognized as the crucially beneficial bacteria in the gut. Many preclinical and clinical studies have shown their protective effects against non-alcoholic fatty liver disease (NAFLD). However, whether gestational BLS supplementation could alleviate NAFLD in the offspring is still unknown. Kunming mice were given a high-fat diet (HFD) for 4 weeks before mating. They received BLS supplementation by gavage during pregnancy. After weaning, offspring mice were fed with a regular diet up to 5 weeks old. Gestational BLS supplementation significantly increased the abundance of Actinobacteriota, Bifidobacterium, and Faecalibaculum in the gut of dams exposed to HFD. In offspring mice exposed to maternal HFD, maternal BLS intake significantly decreased the ratio of Firmicutes to Bacteroidetes as well as the relative abundance of Prevotella and Streptococcus, but increased the relative abundance of Parabacteroides. In offspring mice, maternal BLS supplementation significantly decreased the hepatic triglyceride content and mitigated hepatic steatosis. Furthermore, maternal BLS supplementation increased the glutathione content and reduced malondialdehyde content in the liver. In addition, mRNA and protein expression levels of key rate-limiting enzymes in mitochondrial ß-oxidation (CPT1α, PPARα, and PGC1α) in the livers of offspring mice were significantly increased after gestational BLS supplementation. Thus, gestational BLS supplementation may ameliorate maternal HFD-induced steatosis and oxidative stress in the livers of offspring mice by modulating fatty acid ß-oxidation.

Lipid accumulation product is a valid predictor of hepatic steatosis and nonalcoholic fatty liver disease.

Aims: To evaluate and compare lipid accumulation product (LAP) with alanine aminotransferase (ALT), aspartate aminotransferase (AST), visceral adiposity index (VAI) and triglyceride-glucose index (TyG) as biomarkers for hepatic steatosis and nonalcoholic fatty liver disease (NAFLD). Methods: LAP, ALT, AST, VAI and TyG were measured in 52 biopsy-proven NAFLD patients and 21 control subjects. Additionally, LAP was also measured in 448 ultrasound-proven NAFLD patients and 1009 control subjects. Results: LAP was positively associated with hepatic steatosis and inflammation in biopsy-proven NAFLD. The risk of NAFLD was positively related to LAP and TyG, but LAP showed a better area under the receiver operating characteristic curve for hepatic steatosis and NAFLD. LAP also performed well in recognizing ultrasound-proven NAFLD. Conclusion: LAP is an ideal biomarker of hepatic steatosis and NAFLD.

TaiChiNet: Negative-Positive Cross-Attention Network for Breast Lesion Segmentation in Ultrasound Images.

Breast lesion segmentation in ultrasound images is essential for computer-aided breast-cancer diagnosis. To improve the segmentation performance, most approaches design sophisticated deep-learning models by mining the patterns of foreground lesions and normal backgrounds simultaneously or by unilaterally enhancing foreground lesions via various focal losses. However, the potential of normal backgrounds is underutilized, which could reduce false positives by compacting the feature representation of all normal backgrounds. From a novel viewpoint of bilateral enhancement, we propose a negative-positive cross-attention network to concentrate on normal backgrounds and foreground lesions, respectively. Derived from the complementing opposites of bipolarity in TaiChi, the network is denoted as TaiChiNet, which consists of the negative normal-background and positive foreground-lesion paths. To transmit the information across the two paths, a cross-attention module, a complementary MLP-head, and a complementary loss are built for deep-layer features, shallow-layer features, and mutual-learning supervision, separately. To the best of our knowledge, this is the first work to formulate breast lesion segmentation as a mutual supervision task from the foreground-lesion and normal-background views. Experimental results have demonstrated the effectiveness of TaiChiNet on two breast lesion segmentation datasets with a lightweight architecture. Furthermore, extensive experiments on the thyroid nodule segmentation and retinal optic cup/disc segmentation datasets indicate the application potential of TaiChiNet.

Elimination of methylmercury production potential in excessive sludge in wastewater treatment plants by sulfur addition.

Mercury ions (Hg(II)) in wastewater can accumulate and transform into the highly neurotoxic methylmercury (MeHg) in activated sludge. The release of MeHg can have severe environmental consequences, making the treatment of MeHg-contaminated sludge a pressing concern. In this study, we found that all the collected activated sludge samples, from different wastewater treatment plants in four cities, had the potential for Hg methylation. The Hg-methylating capacity reached a maximum level of 0.70-0.92 µg/g volatile suspended solids after 48 h of exposure to 5 µg/L Hg(II) and showed an average MeHg production rate of 4.8±0.5%. Accordingly, a sludge treatment method involving the addition of elemental sulfur (S0) for a short-term or long-term duration (3 or 180 days, respectively) was proposed. The results demonstrated that this treatment approach effectively mitigated and potentially eliminated MeHg formation by simultaneously reducing Hg bioavailability and Hg-methylating bioactivity. We found that bioavailable Hg(II) ions were converted to a secondary phase similar to insoluble HgS after S0 addition treatment, leading to a decrease in Hg bioavailability in sludge. The enhancement of Hg and extracellular polymeric substances (EPS) complexation via the increasing amount of thiol groups in EPS also reduced the Hg bioavailability after the long-term treatment. Furthermore, the long-term S0 addition significantly reduced the abundance of Hg-methylators with hgcA gene and promoted the growth of Hg-reducers with merA gene, which ensured the complete elimination of MeHg production potential of the excessive activated sludge. Our findings demonstrated that the proposed S0-addition sludge treatment is a promising and safe biotechnology for treating Hg-contaminated sludge. This approach has the potential to contribute significantly to the mitigation of MeHg pollution within environmental contexts.

Detection of Helicobacter pylori Infection in Human Gastric Fluid Through Surface-Enhanced Raman Spectroscopy Coupled With Machine Learning Algorithms.

Diagnostic methods for Helicobacter pylori infection include, but are not limited to, urea breath test, serum antibody test, fecal antigen test, and rapid urease test. However, these methods suffer drawbacks such as low accuracy, high false-positive rate, complex operations, invasiveness, etc. Therefore, there is a need to develop simple, rapid, and noninvasive detection methods for H. pylori diagnosis. In this study, we propose a novel technique for accurately detecting H. pylori infection through machine learning analysis of surface-enhanced Raman scattering (SERS) spectra of gastric fluid samples that were noninvasively collected from human stomachs via the string test. One hundred participants were recruited to collect gastric fluid samples noninvasively. Therefore, 12,000 SERS spectra (n = 120 spectra/participant) were generated for building machine learning models evaluated by standard metrics in model performance assessment. According to the results, the Light Gradient Boosting Machine algorithm exhibited the best prediction capacity and time efficiency (accuracy = 99.54% and time = 2.61 seconds). Moreover, the Light Gradient Boosting Machine model was blindly tested on 2,000 SERS spectra collected from 100 participants with unknown H. pylori infection status, achieving a prediction accuracy of 82.15% compared with qPCR results. This novel technique is simple and rapid in diagnosing H. pylori infection, potentially complementing current H. pylori diagnostic methods.

Deterministic full-scenario analysis for maximum credible earthquake hazards.

Great earthquakes are one of the major threats to modern society due to their great destructive power and unpredictability. The maximum credible earthquake (MCE) for a specific fault, i.e., the largest magnitude earthquake that may occur there, has numerous potential scenarios with different source processes, making the future seismic hazard highly uncertain. We propose a full-scenario analysis method to evaluate the MCE hazards with deterministic broadband simulations of numerous scenarios. The full-scenario analysis is achieved by considering all uncertainties of potential future earthquakes with sufficient scenarios. Here we show an application of this method in the seismic hazard analysis for the Xiluodu dam in China by simulating 22,000,000 MCE scenarios in 0-10 Hz. The proposed method can provide arbitrary intensity measures, ground-motion time series, and spatial ground-motion fields for all hazard levels, which enables more realistic and accurate MCE hazard evaluations, and thus has great application potential in earthquake engineering.

Pyrolyzed sediment accelerates electron transfer and regulates rhodamine B biodegradation.

Electron transfer efficiency is a key factor that determined the removal of environmental pollution through biodegradation. Electron shuttles exogenously addition is one of the measures to improve the electron transfer efficiency. In this study, the sediment was pyrolyzed at different temperature to investigate its properties of mediating electron transfer and removing of rhodamine B (RhB) in microbial electrochemical systems (MESs). Sediments pyrolyzed at 300 °C (PS300) and 600 °C (PS600) have promoted electron transfer which led to 16 % enhancement of power generation while the result is reversed at 900 °C (PS900). Although power output of PS300 and PS600 are similar, the removal efficiency of RhB is not consistent, which may be caused by the biofilm structure difference. Microbial community analysis revealed that the abundance of EAB and toxicity-degrading bacteria (TDB) in PS600 was 6 % higher than that in PS300. The differentiation of microbial community also affected the metabolic pathway, the amino synthesis and tricarboxylic acid cycle were primarily upregulated with PS600 addition, which enhanced the intracellular metabolism. However, a more active cellular anabolism occurred with PS300, which may have been triggered by RhB toxicity. This study showed that pyrolytic sediment exhibits an excellent ability to mediate electron transport and promote pollutant removal at 600 °C, which provides a techno-economically feasible scenario for the utilization of low-carbon-containing solid wastes.

GREnet: Gradually REcurrent Network With Curriculum Learning for 2-D Medical Image Segmentation.

Medical image segmentation is a vital stage in medical image analysis. Numerous deep-learning methods are booming to improve the performance of 2-D medical image segmentation, owing to the fast growth of the convolutional neural network. Generally, the manually defined ground truth is utilized directly to supervise models in the training phase. However, direct supervision of the ground truth often results in ambiguity and distractors as complex challenges appear simultaneously. To alleviate this issue, we propose a gradually recurrent network with curriculum learning, which is supervised by gradual information of the ground truth. The whole model is composed of two independent networks. One is the segmentation network denoted as GREnet, which formulates 2-D medical image segmentation as a temporal task supervised by pixel-level gradual curricula in the training phase. The other is a curriculum-mining network. To a certain degree, the curriculum-mining network provides curricula with an increasing difficulty in the ground truth of the training set by progressively uncovering hard-to-segmentation pixels via a data-driven manner. Given that segmentation is a pixel-level dense-prediction challenge, to the best of our knowledge, this is the first work to function 2-D medical image segmentation as a temporal task with pixel-level curriculum learning. In GREnet, the naive UNet is adopted as the backbone, while ConvLSTM is used to establish the temporal link between gradual curricula. In the curriculum-mining network, UNet ++ supplemented by transformer is designed to deliver curricula through the outputs of the modified UNet ++ at different layers. Experimental results have demonstrated the effectiveness of GREnet on seven datasets, i.e., three lesion segmentation datasets in dermoscopic images, an optic disc and cup segmentation dataset and a blood vessel segmentation dataset in retinal images, a breast lesion segmentation dataset in ultrasound images, and a lung segmentation dataset in computed tomography (CT).

Treatment and remediation of metal-contaminated water and groundwater in mining areas by biological sulfidogenic processes: A review.

Heavy metal pollution in the mining areas leads to serious environmental problems. The biological sulfidogenic process (BSP) mediated by sulfidogenic bacteria has been considered an attractive technology for the treatment and remediation of metal-contaminated water and groundwater. Notwithstanding, BSP driven by different sulfidogenic bacteria could affect the efficiency and cost-effectiveness of the treatment performance in practical applications, such as the microbial intolerance of pH and metal ions, the formation of toxic byproducts, and the consumption of organic electron donors. Sulfur-reducing bacteria (S0RB)-driven BSP has been demonstrated to be a promising alternative to the commonly used sulfate-reducing bacteria (SRB)-driven BSP for treating metal-contaminated wastewater and groundwater, due to the cost-saving in chemical addition, the high efficiency in sulfide production and metal removal efficiency. Although the S0RB-driven BSP has been developed and applied for decades, the present review works mainly focus on the developments in SRB-driven BSP for the treatment and remediation of metal-contaminated wastewater and groundwater. Accordingly, a comprehensive review for metal-contaminated wastewater treatment and groundwater remediation should be provided with the incorporation of the SRB- and S0RB-driven BSP. To identify the bottlenecks and to improve BSP performance, this paper reviews sulfidogenic bacteria presenting in metal-contaminated water and groundwater; highlight the critical factors for the metabolism of sulfidogenic bacteria during BSP; the ecological roles of sulfidogenic bacteria and the mechanisms of metal removal by sulfidogenic bacteria; and the application of the present sulfidogenic systems and their drawbacks. Accordingly, the research knowledge gaps, current process limitations, and future prospects were provided for improving the performance of BSP in the treatment and remediation of metal-contaminated wastewater and groundwater in mining areas.

Spatial distribution, environmental risks, and sources of potentially toxic elements in soils from a typical abandoned antimony smelting site.

The rapid development of the smelting industry increases the release of antimony (Sb) into the soil environment, which threatens human health and ecosystems. A total of 87 samples were collected from an abandoned Sb smelting site to evaluate pollution characteristics and environmental risks of the potentially toxic elements (PTEs). The contents of As, Cu, Ni, Pb, Sb, and Zn in the fresh soils determined by P-XRF were 131, 120, 60, 145, 240, and 154 mg/kg, respectively, whilst following drying, grinding, and sieving pretreatments, the corresponding contents increased to 367, 179, 145, 295, 479, and 276 mg/kg, respectively. There was a significant correlation between the data obtained by P-XRF and ICP-OES in the treated samples, which showed the application feasibility of P-XRF. The average contents of Sb and As were 440.6 and 411.6 mg/kg, respectively, which exceeded the control values of the development land in GB 36600-2018. The ecological risk levels of the six PTEs decreased in the following order: As > Sb > Pb > Zn > Ni > Cu. Non-carcinogenic risk revealed that As, Pb, and Sb posed health risks for children, whilst for carcinogenic risk, the risk values for As and Ni were higher than the limit values for both children and adults. Anthropogenic sources accounted for more than 70.0% of As, Pb, and Sb concentrations in soils, indicating a significant influence on PTEs accumulation. The findings provide a basis for quick determination of the contamination characteristics and risk control of PTEs at Sb smelting sites.

A comprehensive review on the photocatalytic inactivation of Microcystis aeruginosa: Performance, development, and mechanisms.

Harmful algae blooms (HABs), caused by severe eutrophication and extreme weather, have spread all over the world, posing adverse effects on eco-environment and human health. Microcystis aeruginosa is the dominant harmful cyanobacterial species when HABs occur, and the toxic metabolites produced by it, microcystins, are even fatal to humans. Photocatalytic technology has received wide attention from researchers for its clean and energy-efficient features, while the basic mechanisms and modification methods of photocatalysts have also been widely reported. In recent years, photocatalytic technology has shown great promise in the inhibition of HABs. In this article, we systematically reviewed the progress in photocatalytic performance and algae removal efficiency, discuss the damage mechanisms of photocatalysts for algae removal, including physical damage and various oxidative stresses, and also explore the degradation rates and possible pathways of microcystins. It can be concluded that during the photocatalytic process, the cytoarchitectural integrity of algae cells was damaged, a variety of important protein and enzyme systems were disrupted, and the antioxidant systems collapsed due to the continuous attack of ROS, which adversely affected the normal physiological activities and growth, resulting in the inactivation of algae cells. Moreover, photocatalysts have a degrading effect on microcystins, thus reducing the adverse effects of HAB. Finally, a brief summary of future research priorities regarding the photocatalytic degradation of algae cells is presented. This study helps to enhance the understanding of the destruction mechanism of Microcystis aeruginosa during the photocatalytic process, and provides a reference for the photodegradation of HAB in water bodies.

Cross-kingdom synthetic microbiota supports tomato suppression of Fusarium wilt disease.

The role of rhizosphere microbiota in the resistance of tomato plant against soil-borne Fusarium wilt disease (FWD) remains unclear. Here, we showed that the FWD incidence was significantly negatively correlated with the diversity of both rhizosphere bacterial and fungal communities. Using the microbiological culturomic approach, we selected 205 unique strains to construct different synthetic communities (SynComs), which were inoculated into germ-free tomato seedlings, and their roles in suppressing FWD were monitored using omics approach. Cross-kingdom (fungi and bacteria) SynComs were most effective in suppressing FWD than those of Fungal or Bacterial SynComs alone. This effect was underpinned by a combination of molecular mechanisms related to plant immunity and microbial interactions contributed by the bacterial and fungal communities. This study provides new insight into the dynamics of microbiota in pathogen suppression and host immunity interactions. Also, the formulation and manipulation of SynComs for functional complementation constitute a beneficial strategy in controlling soil-borne disease.

Mesoscale Modeling Study on Mechanical Deterioration of Alkali-Aggregate Reaction-Affected Concrete.

The alkali-aggregate reaction (AAR) is a harmful chemical reaction that reduces the mechanical properties and weakens the durability of concrete. Different types of activated aggregates may result in various AAR modes, which affect the mechanical deterioration of concrete. In this paper, the aggregate expansion model and the gel pocket model are considered to represent the two well-recognized AAR modes. The mesoscale particle model of concrete was presented to model the AAR expansion process and the splitting tensile behavior of AAR-affected concrete. The numerical results show that different AAR modes have a great influence on the development of AAR in terms of expansion and microcracks and the deterioration of concrete specimens. The AAR mode of the gel pocket model causes slight expansion, but generates microcracks in the concrete at the early stage of AAR. This means there is difficulty in achieving early warning and timely maintenance of AAR-affected concrete structures based on the monitoring expansion. Compared with the aggregate expansion model, more severe cracking can be observed, and a greater loss of tensile strength is achieved at the same AAR expansion in the gel pocket model. AAR modes determine the subsequent reaction process and deterioration, and thus, it is necessary to develop effective detection methods and standards for large concrete projects according to different reactive aggregates.

Pollution simulation and remediation strategy of a zinc smelting site based on multi-source information.

Contaminated sites pose a significant risk to human health and the regional environment. A comprehensive study was dedicated to improving the understanding of the contamination condition of a smelting site by integrating multi-source information through 3D visualization techniques. The results showed that 3D visualization reveals excellent potential for application in the environmental studies to finely depict contamination in soils and establish relationships with geological features, hydrological conditions, and sources of contamination. The contamination plume model revealed that the soil environment at the site was seriously threatened by toxic metals, and dominated by multi-metal contamination, with contamination soil volume ranked as Cd > As > Pb> Zn > Hg. The stratigraphic model revealed the heterogeneous geological conditions of the site and identified the mixed fill layer as the primary remediation soil layer. The permeability model revealed that soil permeability significantly influenced contamination dispersion and contributed to delineate the contamination boundary accurately. The ecological hazard model targeted the high ecological hazard area and determined the high hazard contribution of Cd and Hg in the site soil. The outcomes can be directly applied to actual site remediation and provide a reference for the contaminated sites evaluation and restoration in the future.

Role of sulfur biogeochemical cycle in mercury methylation in estuarine sediments: A review.

Estuaries are sinks for mercury, in which the most toxic mercury form, neurotoxic methylmercury (MeHg), is produced by mercury methylators and accumulates in estuarine sediments. In the same area, the microbial sulfur cycle is triggered by sulfate-reducing bacteria (SRB), which is considered as the main mercury methylator. In this review, we analyzed the sulfur and mercury speciation in sediments from 70 estuaries globally. Abundant mercury and sulfur species were found in the global estuarine sediments. Up to 727 µg THg/g dw and 880 ng MeHg/g dw were found in estuarine sediments, showing the serious risk of mercury to aquatic ecological systems. Significant correlations between sulfur and MeHg concentrations were discovered. Especially, the porewater sulfate concentration positively correlated to MeHg production. The sulfur cycle affects MeHg formation via activating mercury methylator activities and limiting mercury bioavailability, leading to promote or inhibit MeHg formation at different sulfur speciation concentrations. These results suggest that sulfur biogeochemical cycle plays an important role in mercury methylation in estuarine sediments, and the effect of the sulfur cycle on mercury methylation deserves to be further explored in future research.

Applying fulvic acid for sediment metals remediation: Mechanism, factors, and prospect.

Fulvic acid (FA) has been shown to play a decisive role in controlling the environmental geochemical behavior of metals. As a green and natural microbial metabolite, FA is widely used in environmental remediation because of its good adsorption complexation and redox ability. This paper introduces the reaction mechanism and properties of FA with metals, and reviews the progress of research on the remediation of metal pollutant by FA through physicochemical remediation and bioremediation. FA can control the biotoxicity and migration ability of some metals, such as Pb, Cr, Hg, Cd, and As, through adsorption complexation and redox reactions. The concentration, molecular weight, and source are the main factors that determine the remediation ability of FA. In addition, the ambient pH, temperature, metal ion concentrations, and competing components in sediment environments have significant effects on the extent and rate of a reaction between metals and FA during the remediation process. Finally, we summarize the challenges that this promising environmental remediation tool may face. The research directions of FA in the field of metals ecological remediation are also prospected. This review can provide new ideas and directions for the research of remediation of metals contaminants in sediments.

High-efficiency genome editing of an extreme thermophile Thermus thermophilus using endogenous type I and type III CRISPR-Cas systems.

Thermus thermophilus is an attractive species in the bioindustry due to its valuable natural products, abundant thermophilic enzymes, and promising fermentation capacities. However, efficient and versatile genome editing tools are not available for this species. In this study, we developed an efficient genome editing tool for T. thermophilus HB27 based on its endogenous type I-B, I-C, and III-A/B CRISPR-Cas systems. First, we systematically characterized the DNA interference capabilities of the different types of the native CRISPR-Cas systems in T. thermophilus HB27. We found that genomic manipulations such as gene deletion, mutation, and in situ tagging could be easily implemented by a series of genome-editing plasmids carrying an artificial self-targeting mini-CRISPR and a donor DNA responsible for the recombinant recovery. We also compared the genome editing efficiency of different CRISPR-Cas systems and the editing plasmids with donor DNAs of different lengths. Additionally, we developed a reporter gene system for T. thermophilus based on a heat-stable ß-galactosidase gene TTP0042, and constructed an engineered strain with a high production capacity of superoxide dismutases by genome modification.