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Abstract TNF inhibitors have been used to treat autoimmune and autoinflammatory diseases. Here we report an unexpected mechanism underlying the therapeutic effects of TNF inhibitors in Behçet’s disease (BD), an autoimmune inflammatory disorder. Using serum metabolomics and peripheral immunocyte transcriptomics, we find that polymorphonuclear neutrophil (PMN) from patients with BD (BD-PMN) has dysregulated mevalonate pathway and subsequently increased farnesyl pyrophosphate (FPP) levels. Mechanistically, FPP induces TRPM2-calcium signaling for neutrophil extracellular trap (NET) and proinflammatory cytokine productions, leading to vascular endothelial inflammation and damage. TNF, but not IL-1β, IL-6, IL-18, or IFN-γ, upregulates TRPM2 expression on BD-PMN, while TNF inhibitors have opposite effects. Results from mice with PMN-specific FPP synthetase or TRPM2 deficiency show reduced experimental vasculitis. Meanwhile, analyses of public datasets correlate increased TRPM2 expressions with the clinical benefits of TNF inhibitors. Our results thus implicate FPP-TRPM2-TNF/NETs feedback loops for inflammation aggravation, and novel insights for TNF inhibitor therapies on BD.

Abstract Untargeted metabolomic analysis using mass spectrometry provides comprehensive metabolic profiling, but its medical application faces challenges of complex data processing, high inter-batch variability, and unidentified metabolites. Here, we present DeepMSProfiler, an explainable deep-learning-based method, enabling end-to-end analysis on raw metabolic signals with output of high accuracy and reliability. Using cross-hospital 859 human serum samples from lung adenocarcinoma, benign lung nodules, and healthy individuals, DeepMSProfiler successfully differentiates the metabolomic profiles of different groups (AUC 0.99) and detects early-stage lung adenocarcinoma (accuracy 0.961). Model flow and ablation experiments demonstrate that DeepMSProfiler overcomes inter-hospital variability and effects of unknown metabolites signals. Our ensemble strategy removes background-category phenomena in multi-classification deep-learning models, and the novel interpretability enables direct access to disease-related metabolite-protein networks. Further applying to lipid metabolomic data unveils correlations of important metabolites and proteins. Overall, DeepMSProfiler offers a straightforward and reliable method for disease diagnosis and mechanism discovery, enhancing its broad applicability.

Abstract Background Intestinal ischemia–reperfusion (I/R) injury is a severe vascular emergency. Previous research indicated the protective effects of Emodin on I/R injury. Our study aims to explore the effect of Emodin on intestinal I/R (II/R) injury and elucidate the underlying mechanisms. Methods C57BL/6 mice and Caco-2 cells were used for in vivo and in vitro studies. We established an animal model of II/R injury by temporarily occluding superior mesenteric artery. We constructed an oxygen–glucose deprivation/reoxygenation (OGD/R) cell model using a hypoxia-reoxygenation incubator. Different doses of Emodin were explored to determine the optimal therapeutic dose. Additionally, inhibitors targeting the protein kinase B (Akt) or Heme oxygenase-1 (HO-1) were administered to investigate their potential protective mechanisms. Results Our results demonstrated that in animal experiments, Emodin mitigated barrier disruption, minimized inflammation, reduced oxidative stress, and inhibited apoptosis. When Akt or HO-1 was inhibited, the protective effect of Emodin was eliminated. Inhibiting Akt also reduced the level of HO-1. In cell experiments, Emodin reduced inflammation and apoptosis in the OGD/R cell model. Additionally, when Akt or HO-1 was inhibited, the protective effect of Emodin was weakened. Conclusions Our findings suggest that Emodin may protect the intestine against II/R injury through the Akt/HO-1 signaling pathway.

Introduction: The tumor-associated microbiota plays a vital role in cancer development. Accumulating evidence shows that Fusobacterium nucleatum (Fn) participates in the progression of multiple tumor types. However, the underlying mechanisms remain unclear. Objectives: This study examined the expression of methyltransferase-like protein 3 (METTL3) during Fn infection and elucidated the function and pathway of Fn-induced m6A methylation in esophageal squamous cell carcinoma (ESCC). Methods: The abundance of Fn in patient tissues was determined by qPCR. Western blot, qRT-PCR, and immunohistochemistry were performed to measure METTL3 expression in cells and tissues. METTL3 function was evaluated in vitro by colony formation and cell migration assays. MeRIP-qPCR was performed to determine the relationship between METTL3 and c-Myc. In addition, the half-lives of genes that are downstream of METTL3 were determined with RNA stability assays. Results: Fn was enriched in hepatocellular carcinoma (HCC), breast cancer (BRCA), ESCC, and colorectal cancer (CRC) tumor tissues. METTL3 expression was positively associated with Fn abundance in ESCC tissues. Fn could survive and proliferation as well as increase METTL3 expression in ESCC, HCC, CRC, and BRCA cells. Moreover, METTL3 overexpression promoted ESCC cells proliferation, migration in vivo and in vitro. Mechanistically, Intracellular Fn infection increases METTL3 transcription. METTL3 promoted c-Myc mRNA methylation in the 3′-untranslated Region (3′-UTR) and enhanced its mRNA stability in a YTH N6-Methyladenosine RNA binding protein 1(YTHDF1)-dependent manner, which contributes to Fn induced ESCC proliferation and metastasis. Conclusions: This study indicates that intracellular Fn infection promotes ESCC development and metastasis, and eradicating Fn infection may be a promising strategy for treating ESCC.

Background With the gradual increase of infertility in the world, among which male sperm problems are the main factor for infertility, more and more couples are using computer-assisted sperm analysis (CASA) to assist in the analysis and treatment of infertility. Meanwhile, the rapid development of deep learning (DL) has led to strong results in image classification tasks. However, the classification of sperm images has not been well studied in current deep learning methods, and the sperm images are often affected by noise in practical CASA applications. The purpose of this article is to investigate the anti-noise robustness of deep learning classification methods applied on sperm images.Methods The SVIA dataset is a publicly available large-scale sperm dataset containing three subsets. In this work, we used subset-C, which provides more than 125,000 independent images of sperms and impurities, including 121,401 sperm images and 4,479 impurity images. To investigate the anti-noise robustness of deep learning classification methods applied on sperm images, we conducted a comprehensive comparative study of sperm images using many convolutional neural network (CNN) and visual transformer (VT) deep learning methods to find the deep learning model with the most stable anti-noise robustness.Results This study proved that VT had strong robustness for the classification of tiny object (sperm and impurity) image datasets under some types of conventional noise and some adversarial attacks. In particular, under the influence of Poisson noise, accuracy changed from 91.45% to 91.08%, impurity precison changed from 92.7% to 91.3%, impurity recall changed from 88.8% to 89.5%, and impurity F1-score changed 90.7% to 90.4%. Meanwhile, sperm precision changed from 90.9% to 90.5%, sperm recall changed from 92.5% to 93.8%, and sperm F1-score changed from 92.1% to 90.4%.Conclusion Sperm image classification may be strongly affected by noise in current deep learning methods; the robustness with regard to noise of VT methods based on global information is greater than that of CNN methods based on local information, indicating that the robustness with regard to noise is reflected mainly in global information.

Abstract Monocarboxylate transporter 1 (MCT1) exhibits essential roles in cellular metabolism and energy supply. Although MCT1 is highly expressed in activated B cells, it is not clear how MCT1-governed monocarboxylates transportation is functionally coupled to antibody production during the glucose metabolism. Here, we report that B cell-lineage deficiency of MCT1 significantly influences the class-switch recombination (CSR), rendering impaired IgG antibody responses in Mct1 f/f Mb1 Cre mice after immunization. Metabolic flux reveals that glucose metabolism is significantly reprogrammed from glycolysis to oxidative phosphorylation in Mct1-deficient B cells upon activation. Consistently, activation-induced cytidine deaminase (AID), is severely suppressed in Mct1-deficient B cells due to the decreased level of pyruvate metabolite. Mechanistically, MCT1 is required to maintain the optimal concentration of pyruvate to secure the sufficient acetylation of H3K27 for the elevated transcription of AID in activated B cells. Clinically, we found that MCT1 expression levels are significantly upregulated in systemic lupus erythematosus patients, and Mct1 deficiency can alleviate the symptoms of bm12-induced murine lupus model. Collectively, these results demonstrate that MCT1-mediated pyruvate metabolism is required for IgG antibody CSR through an epigenetic dependent AID transcription, revealing MCT1 as a potential target for vaccine development and SLE disease treatment.

Abstract Purpose The purpose of this study was to understand and analyze the risk factors of peripherally inserted central catheter (PICC)-related venous thrombosis in adult patients with cancer. Methods This observational cohort study included adult patients with cancer who underwent color Doppler ultrasound at the Xiangya Hospital of Central South University, Hunan Provincial Maternal and Child Healthcare Hospital, and Xiangya Changde Hospital, Hunan Province, from January 1, 2017 to December 31, 2021. Univariate and multivariate logistic regression analyses were performed to determine the risk factors of PICC-related venous thrombosis. Results After risk adjustment, multivariate logistic regression analysis revealed statistically significant associations between PICC-related venous thrombosis and age > 65 years old (OR: 1.791, CI: 1.343–2.389), male sex (OR: 1.398, CI: 1.057–1.849), white blood cell count > 9.5 × 109 /L (OR: 1.422, CI: 1.041–1.942), APTT < 25 s (OR: 2.006, CI: 1.431–2.811), gastrointestinal tumor (OR: 2.191, CI: 1.406–3.414), infection (OR:7.619, CI: 5.783–10.037), the use of cisplatin (OR: 2.374, CI: 1.714–3.214), vincristine (OR: 2.329, CI: 1.447–3.749), the use of polyurethane (OR: 2.449, CI: 1.863–3.219) and open-ended catheters (OR:1.660, CI: 1.131–2.439), keeping time of the catheter (days) (OR: 1.003, CI: 1.001–1.005) were associated with PICC-related venous thrombosis. Conclusion We identified that the presence of age > 65 years old, male sex, white blood cell count > 9.5 × 109 /L, APTT < 25 s, gastrointestinal tumor, infection, the use of cisplatin and vincristine, the use of polyurethane, open-ended catheters and keeping time of the catheter (days), were associated with PICC-related venous thrombosis.

With the global objectives of achieving a “carbon peak” and “carbon neutrality” along with the implementation of carbon reduction policies, China’s industrial structure has undergone significant adjustments, resulting in constraints on high-energy consumption and high-emission industries while promoting the rapid growth of green industries. Consequently, these changes have led to an increasingly complex power system structure and presented new challenges for electricity demand forecasting. To address this issue, this study proposes a 24-step multivariate time series short-term load forecasting algorithm model based on KNN data imputation and BiTCN bidirectional temporal convolutional networks combined with BiGRU bidirectional gated recurrent units and attention mechanism. The Kepler adaptive optimization algorithm (KOA) is employed for hyperparameter optimization to effectively enhance prediction accuracy. Furthermore, using real load data from a wind farm in Xinjiang as an example, this paper predicts the electricity load from 1 January to 30 December in 2019. Experimental results demonstrate that our comprehensive short-term load forecasting model exhibits lower prediction errors and superior performance compared to traditional methods, thus holding great value for practical applications.

Abstract Objective To identify the risk factors for moderate and severe contrast media extravasation and provide effective guidance to reduce the degree of extravasation injuries. Methods We observed 224 adult patients who underwent contrast media extravasation at Xiangya Hospital of Central South University, Hunan Provincial Maternal and Child Healthcare Hospital, and Xiangya Changde Hospital, Hunan Province between January 1, 2018 and December 31, 2022. Risk factors for moderate extravasation injuries were evaluated using univariate and multivariate logistic regression. Results Among 224 patients, 0 (0%) had severe, 18 (8.0%) had moderate, and 206 (92.0%) had mild contrast media extravasation injury. Multivariate logistic regression analysis revealed malignant tumors (odds ratio [OR] = 6.992, 95% confidence interval [CI]: 1.674–29.208), Iohexol (OR = 9.343, 95% CI 1.280–68.214), large-volume (> 50 mL) extravasation (OR = 5.773, 95% CI 1.350‒24.695), and injection site (back of the hand) (OR = 13.491, 95% CI 3.056–59.560) as independent risk factors for moderate injury. Conclusion Risk factors for moderate contrast media extravasation injury are malignant tumors, iohexol, large-volume (> 50 mL) extravasation, and back-of-the-hand injection. Analysis of these risk factors can help reduce the degree of injury after extravasation. Clinical relevance statement High-risk patients with extravasation support should choose the appropriate contrast media type, avoiding back-of-the-hand injections. We recommend that patients with cancer be implanted with a high-pressure resistant central venous catheter and receive effective measures to timely detect and reduce extravasation.

Abstract Currently, the influence of the tumor microbiome on the effectiveness of immunotherapy remains largely unknown. Intratumoural Fusobacterium nucleatum (Fn) functions as an oncogenic bacterium and can promote tumor progression in esophageal squamous cell carcinoma (ESCC). Our previous study revealed that Fn is a facultative intracellular bacterium and that its virulence factor Fn-Dps facilitates the intracellular survival of Fn. In this study, we find that Fn DNA is enriched in the nonresponder (NR) group among ESCC patients receiving PD-1 inhibitor and that the serum antibody level of Fn is significantly higher in the NR group than in the responder (R) group. In addition, Fn infection has an opposite impact on the efficacy of αPD-L1 treatment in animals. Mechanistically, we confirm that Fn can inhibit the proliferation and cytokine secretion of T cells and that Fn-Dps binds to the PD-L1 gene promoter activating transcription factor-3 (ATF3) to transcriptionally upregulate PD-L1 expression. Our results suggest that it may be an important therapeutic strategy to eradicate intratumoral Fn infection before initiating ESCC immunotherapies.

Implantable and wearable bioelectronic systems can enable tailored therapies for the effective management of long-term diseases, thus minimising the risk of associated complications. In this context, glucose fuel cells hold great promise as in- or on-body energy harvesters for ultra-low-power bioelectronics and as self-powered glucose sensors. We report here the generation of gold nanostructures through a gold electrodeposition method in a soft template for the abiotic electrocatalysis of glucose in glucose fuel cells. Two different types of soft template were used: a lipid cubic phase-based soft template composed of Phytantriol and Brij®-56, and an emulsion-based soft template composed of hexane and sodium dodecyl sulphate (SDS). The resulting gold structures were first characterised by SAXS, SEM and TEM to elucidate their structure, and then their electrocatalytic activity towards glucose was compared in both a three-electrode set-up and in a fuel cell set-up. The Phytantriol/Brij®-56 template led to a nanofeather-like Au structure, while the hexane/SDS template led to a nanocoral-like Au structure. These templated electrodes exhibited similar electrochemical active surface areas (0.446 cm2 with a roughness factor (RF) of 14.2 for Phytantriol/Brij®-56 templated nanostructures and 0.421 cm2 with an RF of 13.4 for hexane/SDS templated nanostructures), and a sensitivity towards glucose of over 7 μA mM−1 cm−2. When tested as the anode of an abiotic glucose fuel cell (in a phosphate-buffered solution with a glucose concentration of 6 mM), a maximum power density of 7 μW cm−2 was reached; however the current density in the case of the fuel cell with the Phytantriol/Brij®-56 templated anode was approximately two times higher, reaching the value of 70 μA cm−2. Overall, this study demonstrates two simple, cost-effective and efficient strategies to manipulate the morphology of gold nanostructures, and thus their catalytic property, paving the way for the successful manufacturing of functional abiotic glucose fuel cells.

Abstract Background Immune checkpoint inhibitor (ICI) therapy has been used in various tumors. The biomarkers predictive of a response to ICI treatment remain unclear, and additional and combined biomarkers are urgently needed. Secreted factors related to the tumor microenvironment (TME) have been evaluated to identify novel noninvasive predictive biomarkers. Methods We analyzed 85 patients undergoing ICI therapy as the primary cohort. The associations between ICI response and all biomarkers were evaluated. A prediction model and a nomogram were developed and validated based on the above factors. Results Seventy-seven patients were enrolled in the validation cohort. In the primary cohort, the baseline serum levels of H3Cit, IL-8 and CRP were significantly higher in nonresponder patients. A model based on these three factors was developed, and the “risk score” of an ICI response was calculated with the formula: “risk score” = 3.4591×H3Cit + 2.5808×IL8 + 2.0045 ×CRP– 11.3844. The cutoff point of the “risk score” was 0.528, and patients with a “risk score” lower than 0.528 were more likely to benefit from ICI treatment (AUC: 0.937, 95% CI: 0.886–0.988, with sensitivity 80.60%, specificity 91.40%). The AUC was 0.719 (95% CI: 0.600-0.837, P = 0.001), with a sensitivity of 70.00% and specificity of 65.20% in the validation cohort. Conclusions A model incorporating H3Cit, IL-8 and CRP has an excellent prediction ability for ICI response; thus, patients with a lower “risk score” selectively benefit from ICI treatment, which may have significant clinical implications for the early detection of an ICI response.

The complex bridge-track interaction between kilometer-span bridges and continuous Welded Rail (CWR) brings great challenges to CWR designing. Taking a suspension bridge with laying CWR as a case, the mechanical properties of CWR on the bridge are analyzed to reveal the sensitive areas of the track, and the design method of CWR and track structures on the beam ends are proposed. The results show that the unidirectional Rail Expansion Joints(REJ) need to be installed on the beam end of the kilometer-span bridge to reduce rail longitudinal force. Due to the bridge characteristics, there is no CWR fixed area on the kilometer-span bridge, and rail longitudinal force on the main span caused by bending loads needs to be concerned. The deformation of track on the beam end is complex, which is the weak area on the kilometer bridge, the large relative displacement between the stock rail of REJ and the main beam can cause poor stability of ballast bed on beam end, small resistance fasteners need to be laid on the sides of stock rail on the main beam to increase the stability of ballast and fasteners on the beam end. To improve the driving safety and comfort of beam end, the Sleeper-Supporting Apparatus (SSA) should be specially designed to ensure the uniform transition of track on beam ends. Temperature and wind loads have a significant impact on track regularity on the kilometer span bridge, the dynamic response of trains and bridges under those loads needs to be attended to.

BackgroundWith the rapid advancement of the One Health approach, the transmission of human infectious diseases is generally related to environmental and animal health. Coronavirus disease (COVID-19) has been largely impacted by environmental factors regionally and globally and has significantly disrupted human society, especially in low-income regions that border many countries. However, few research studies have explored the impact of environmental factors on disease transmission in these regions.MethodsWe used the Xinjiang Uygur Autonomous Region as the study area to investigate the impact of environmental factors on COVID-19 variation using a dynamic disease model. Given the special control and prevention strategies against COVID-19 in Xinjiang, the focus was on social and environmental factors, including population mobility, quarantine rates, and return rates. The model performance was evaluated using the statistical metrics of correlation coefficient (CC), normalized absolute error (NAE), root mean square error (RMSE), and distance between the simulation and observation (DISO) indices. Scenario analyses of COVID-19 in Xinjiang encompassed three aspects: different population mobilities, quarantine rates, and return rates.ResultsThe results suggest that the established dynamic disease model can accurately simulate and predict COVID-19 variations with high accuracy. This model had a CC value of 0.96 and a DISO value of less than 0.35. According to the scenario analysis results, population mobilities have a large impact on COVID-19 variations, with quarantine rates having a stronger impact than return rates.ConclusionThese results provide scientific insight into the control and prevention of COVID-19 in Xinjiang, considering the influence of social and environmental factors on COVID-19 variation. The control and prevention strategies for COVID-19 examined in this study may also be useful for the control of other infectious diseases, especially in low-income regions that are bordered by many countries.

ABSTRACTOur purpose is to investigate the relationship between the microbiota of patients' tongue coating microbiota and the severity of COVID-19, and to identify the severity of COVID-19 patients' condition as early as possible. The participants were categorized into three groups: healthy controls (Con group) consisting of 37 individuals, patients with mild to moderate symptoms (M group) comprising 49 individuals, and patients with severe and critical symptoms (S-C group) consisting of 44 individuals. We collected oral swabs from all participants and performed 16S rRNA gene sequencing to analyze the microbiome. The α and β diversity differences were assessed respectively. Additionally, we employed the Linear Discriminant Analysis Effect Size (LEfSe) analysis to evaluate taxonomic differences among the three groups. Our findings revealed a significantly higher richness of tongue coating microbiota in both the S-C group and M group compared to the Con group. When compared with Con group, decreased Prevotella, Neisseria, Fusobacterium and Alloprevotella, and over-expressed Streptococcus and Rothia in M and S-C group were identified. LEfSe analysis indicated a greater abundance of Pseudomonas, Acinetbacter, Lactobacillus, Corynebacterium, Rothia in S-C group. Our study suggests a potential association between tongue coating microbiome and the severity of COVID-19 patients.

Abstract Differential diagnosis of pulmonary nodules detected by computed tomography (CT) remains a challenge in clinical practice. Here, we characterize the global metabolomes of 480 serum samples including healthy controls, benign pulmonary nodules, and stage I lung adenocarcinoma. The adenocarcinoma demonstrates a distinct metabolomic signature, whereas benign nodules and healthy controls share major similarities in metabolomic profiles. A panel of 27 metabolites is identified in the discovery cohort (n = 306) to distinguish between benign and malignant nodules. The discriminant model achieves an AUC of 0.915 and 0.945 in the internal validation (n = 104) and external validation cohort (n = 111), respectively. Pathway analysis reveals elevation in glycolytic metabolites associated with decreased tryptophan in serum of lung adenocarcinoma vs benign nodules and healthy controls, and demonstrates that uptake of tryptophan promotes glycolysis in lung cancer cells. Our study highlights the value of the serum metabolite biomarkers in risk assessment of pulmonary nodules detected by CT screening.

Top-coal structure detection is an important basis for realizing effective mining in fully mechanized cave faces. However, the top-coal structure is very complex and often contains multi-layer gangues, which seriously influence the level of effective mining. For these reasons, this paper proposes a novel multi-frequency ground-penetrating radar (GPR) data-fusing method through a joint sliding window and wavelet transform weighting method to accurately detect the top-coal structure. It possesses the advantages of both high resolution and great detection depth, and it can also integrate multi-frequency GPR data into one composite profile to interpret the internal structure information of top coal in detail. The detection procedure is implemented following several steps: First of all, the multi-frequency GPR data are preprocessed and aligned through a band-pass filter and a zero offset elimination method to establish their spatial correspondences. Secondly, the proposed method is used to determine the time-varying weight values of each frequency GPR signal according to the wavelet energy proportion within the sliding window; also, the edge detection algorithm is introduced to improve the fusion efficiency of the wavelet transform so as to realize the effective fusion of the multi-frequency GPR data. Thirdly, a reflection intensity model of multi-frequency GPR signals traveling in the top-coal is established by using the stratified identification method, and then, the detailed top-coal structure can be inversely interpreted. Finally, the quantitative evaluation criteria, information entropy (IE), space–frequency (SF) and Laplacian gradient (LG), are used to evaluate the multi-frequency GPR data fusion’s effectiveness in laboratory and field environments. The experimental results show that, compared with the genetic, time-varying and wavelet transform fusion method, the fusion performance of the presented method possesses higher values in the IE, SF and LG evaluation criteria, and it also has both the merits of high resolution and great detection depth.

[This corrects the article DOI: 10.1371/journal.pbio.3001134.].

Abstract Supramolecular assembly can be used to fabricate complex functional materials by organizing simple building blocks. However, it is difficult to control the hierarchical assembly across multiple length scales. The correlation of a supramolecular gel network and a pre‐gelling aggregate will help to understand how a molecular‐level assembly is translated into a higher order. Here, a functional dipeptide 2NapFF is used that can assemble in different micellar structures at high pH by varying the counterion. Replacing the counterions with a divalent calcium salt results in a cross‐linked gel network, or an interesting analog “gel noodles.” The physical properties of the gel noodles can be varied by choosing specific micellar assemblies as the pre‐gel. The mechanical rigidity of the gel networks is compared by nanoindentation and tensile testing, and the pattern to the structures of the micelles observed by small‐angle X‐ray scattering is correlated. The supramolecular assembly can be fine‐tuned by using different micelles as the pre‐gel without affecting the inherent gel‐state properties.

Abstract Climate change and human activities have profoundly changed the evolutionary processes and developmental trends of the hydrology and geomorphology of rivers and lakes. Such changes have affected the evolution of bars and channels at the intersections of rivers and lakes and the utilization of water depth resources in waterways, which, in turn, have affected the sustainable development of waterways, such as the “Golden Waterway” of the Yangtze River. Considering the confluence of Dongting Lake and the Yangtze River as the present study area, we analyzed the effect of the hydrology of Dongting Lake and the evolution of bars and channels in the Jingjiang reach of the Yangtze River on the depth of the waterways. Our results indicated that from before the operation of the Three Gorges Project (1960–2002) to after its operation (2003–2021), the flow and sediment volume of the three inlets of Dongting Lake demonstrated a continuous decreasing trend. Furthermore, the relative increase in the runoff of the Jingjiang reach increased channel erosion. Channel erosion at the river–lake confluence from 2003 to 2021 created favorable conditions for increasing the dimensions of the waterways. The total length of the river–lake confluence that did not meet the requirements for safe navigation [4.5 × 200 m (water depth × width)] was 12.6 km, accounting for 68.35% of the total length of the Jingjiang reach with obstructed navigation. We observed that a decrease in the low‐water level and “steep slope and rapid flow” were the major factors hindering the navigation of the reach (from Zhicheng to Dabujie) affected by the Songzikou diversion of Dongting Lake. This was mostly reflected by the width of the 4.5 m waterway being less than 200 m. A declining water level, shrinking sandbanks and tidal flats, and alternating branches that destabilize the low‐water route were the major factors hindering navigation in the reach (from Taipingkou) affected by the Taipingkou diversion of Dongting Lake. Consequently, alternative waterways were implemented during low‐water periods with the water depth decreasing below 4.5 m. The obvious collapse of sandbanks and tidal flats and their erosion and migration were the major factors hindering navigation of the Ouchikou diversion of Dongting Lake. In addition, the scattered submerged shoals in the navigation channel restricted the width of the 4.5 m channel to less than 200 m. The reach affected by the Dongting Lake confluence (from Xiongjiazhou–Chenglingji reach) was subject to the erosion and silting of bends and the jacking effect of lake outflow, causing shoals with a water depth of less than 4.5 m in the channel. However, the jacking effect slowed the current, thereby assisting in improving channel conditions.

Abstract All organisms living in complex environments have evolved effective mechanisms of dynamic responses to extracellular stimuli. The immune system activates when damaged or injured cells release damage‐associated molecular patterns (DAMPs). In addition to well‐characterized DAMPs such as high‐mobility group box 1 and adenosine triphosphate, studies on new classes of DAMPs have emerged. Here, we review recent reports of a new class of isoprenoid‐derived DAMPs, including farnesyl pyrophosphate and geranylgeranyl pyrophosphate, both of which are pivotal metabolic intermediates of the mevalonate pathway. We also explore the roles of old and new DAMPs in autoimmune diseases that result from dysregulated inflammation. The findings highlight that understanding the functional mechanisms of DAMPs is important to enrich the DAMP family and decipher their immunoregulatory mechanisms to provide new therapeutics for the prevention and treatment of autoimmune diseases.

Abstract Aims To examine the effectiveness of D‐dimer values to be used as an independent diagnostic marker for excluding peripherally inserted central catheter‐associated upper extremity deep vein thrombosis and superficial vein thrombosis. Design This was a retrospective case–cohort study. Methods Records were reviewed for 281 patients who underwent peripherally inserted central catheter insertion between 1 October 2017 and 1 October 2019. According to the modified Wells score after peripherally inserted central catheter insertion, the patients who had low vein thrombosis risk underwent a D‐dimer test and colour Doppler ultrasound. Results Among 281 patients, 180 patients (64%, 95% CI: 58.2%–69.4%) had negative D‐dimer results and 39 of 180 patients had vein thrombosis despite having a negative D‐dimer result, resulting in a failure rate of 21.7% (95% CI: 16.3%–28.3%). The negative predictive value of peripherally inserted central catheter‐associated vein thrombosis in the cancer group (80.0%, 95% CI: 73.2%–85.4%) was higher than that of the non‐cancer group (60.0%, 95% CI: 35.7%–80.2%). The negative predictive value of peripherally inserted central catheter‐associated deep venous thrombosis (84.9%, 95% CI: 78.7%–89.6%) was lower than that of the PICC‐associated superficial venous thrombosis (91.0%, 95% CI: 85.4%–94.6%). Conclusion The D‐dimer levels maybe should not be used as a diagnostic index to rule out peripherally inserted central catheter‐associated upper extremity vein thrombosis.

Background: B lymphocytes (B cells) are essential in humoral response, and their activation is an important first step for the production of antibodies. However, aberrant B-cell activation is common in the development and progression of autoimmune diseases including systemic lupus erythematosus (SLE), which is characterized by the generation of superfluous autoantibodies. SLE exhibits clinical manifestation such as excessive inflammation and tissue damage. This review aims to summarize the recent emerging studies on aberrant B-cell activation and the associated concurrent therapeutic targets in SLE. Summary: Aberrant B-cell activation is closely associated with the pathogenesis of SLE. Among a variety of mechanisms, dysregulations of B-cell receptor (BCR), toll-like receptor (TLR), and B-cell activating factor receptor (BAFF-R) pathways are the common and dominating factors involved in aberrant B-cell activation. These aberrant signaling transductions play diverse and integrated roles in the development and the pathogenesis of SLE. Therapies targeting aberrant B-cell activation have shown promising efficacy in achieving the clinical alleviation of SLE, suggesting the discovery of new drug targets from these aberrant signaling pathways is imminent. Here, an integrated survey or review of published high-throughput sequencing database covering RNAs of B cells from SLE versus criteria-matched healthy controls highlights that reported signaling molecules in BCR pathway (VAV2, PLC-γ2), TLR pathway (TLR9, P105, IRF7, TAB1), and BAFF-R pathway (SDF-1α) are attitudinally upregulated in SLE patients. This review thus suggests the concurrent and future therapeutic targets and potential biomarkers in both basic and clinical studies of SLE. Key Messages: This review focuses on core B-cell signaling pathways, discussing the progress in the role of aberrant B-cell activation during the pathogenesis of SLE. This review also highlights the signaling molecules from published studies and database for the possible prevention and treatment targets serving the future clinical treatments of SLE.

Abstract Purpose The angiogenesis is among the primary factors that affect tumor recurrence and distant organ metastasis in colorectal cancer (CRC). N6-methyladenosine (m6A) modification is one of the most common chemical modifications in eukaryotic mRNA, especially at the post-transcriptional level. Methyltransferase-like 3 (METTL3) promoting angiogenesis in a variety of tumors has been reported. However, the mechanism of how METTL3 dual-regulates the stability of long non-coding RNAs (lncRNAs) and vascular-related factor RNAs to affect angiogenesis in CRC is unclear. Methods 64 paired CRC and adjacent normal tissues were collected. In vitro, quantitative real-time polymerase chain reaction (qRT-PCR), immunohistochemistry (IHC), actinomycin assay, methylated RNA immunoprecipitation (MeRIP) experiment,3-(4,5)-dimethylthiahiazo(-z-y1)-3,5-di-phenytetrazoliumromide (MTT) and colony formation assay were performed. The functions were also studied in zebrafish model animals in vivo. Results We found that the vascular endothelial growth factor A(VEGFA), METTL3 and LINC00662 RNAs were highly expressed in CRC, and that METTL3 was significantly positively correlated with LINC00662 and VEGFA. The protein expression levels of CD31, CD34, VEGFA, m6A and METTL3 were all significantly increased in the CRC tissues. The angiogenesis experiments both in vivo and in vitro found that METTL3 and LINC00662 promoted angiogenesis in CRC. The actinomycin assay indicated that METTL3 maintained the stability of LINC00662 and VEGFA RNAs. In addition, the MeRIP experiment confirmed that the LINC00662 and VEGFA RNAs had METTL3-enriched sites. Conclusion These findings suggest that METTL3 and LINC00662 may both serve as diagnostic and prognostic predictive biomarkers for CRC and potential targets for anti-vascular therapy.

Event coreference resolution is the task of clustering event mentions that refer to the same entity or situation in text and performing operations like linking, information completion, and validation. Existing methods model this task as a text similarity problem, focusing solely on semantic information, neglecting key features like event trigger words and subject. In this paper, we introduce the event coreference resolution based on context prediction (ECR-CP) as an alternative to traditional methods. ECR-CP treats the task as sentence-level relationship prediction, examining if two event descriptions can create a continuous sentence-level connection to identify coreference. We enhance ECR-CP with a fusion coding model (ECR-CP+) to incorporate event-specific structure and semantics. The model identifies key text information such as trigger words, argument roles, event types, and tenses via an event extraction module, integrating them into the encoding process as auxiliary features. Extensive experiments on the benchmark CCKS 2021 dataset demonstrate that ECR-CP and ECR-CP+ outperform existing methods in terms of precision, recall, and F1 Score, indicating their superior performance.

Summary: Inflammatory bowel diseases (IBDs) contribute to the tumorigenesis of colorectal cancer (CRC). Here, we describe a step-by-step protocol for the construction of colitis-associated CRC murine model by sequential utilization of azoxymethane and dextran sulfate sodium. We also detail steps to determine the degree of murine intestinal inflammation and to generate colorectum Swiss roll for further histopathological analyses. This is a convenient and reproducible protocol for colitis-associated CRC murine model by the induction of general chemical reagents.For complete details on the use and execution of this protocol, please refer to Yang et al. (2022).1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Background Colorectal adenomas (CRAs) are precancerous lesions of the large intestine presenting as colorectal polyps. At present, the conventional treatment methods for CRA mainly include high-frequency electrocoagulation and electroexcision, biopsy forceps polypectomy, cauterization by laser and microwave, and other endoscopic interventions. The principal advantages conferred by these treatment strategies include less trauma, quick postoperative recovery, and simplicity to perform. However, the higher recurrence rates and insignificant improvement of postoperative symptoms after endoscopic surgery are considerable drawbacks to this approach. Besides, there is currently no effective pharmacotherapy to prevent the recurrence of CRA. Jianpi Lishi Jiedu (JLJ) granules are a form of traditional Chinese medicine (TCM) used to manage postoperative patients with CRA, which has shown a certain degree of efficacy in clinical practice. However, its effectiveness and safety profile have not been convincingly evaluated. The purpose of this study is to evaluate the clinical efficacy and safety profile of JLJ granules in the management of postoperative patients with CRA and to observe the recurrence rate of adenoma in these patients. Methods A randomized, double-blind, and placebo-controlled clinical trial is performed in this study. A total of 80 postoperative patients with CRA will be randomly classified into the Jianpi Lishi Jiedu granules group or the placebo control group. Patients in both groups shall receive 3 months of intervention, after which medical follow-up and safety evaluation will be performed for all of the patients. The primary outcome is the recurrence rate of adenomas within 12 months. The secondary outcomes are the cardinal TCM symptom scores, minor TCM symptom scores, Bristol Stool Scale, efficacy of TCM symptoms, safety indicators, and blinding assessment. Discussion In this study, the impact on the recurrence of adenomas and the efficacy and safety of JLJ granules in terms of improving the clinical symptoms of postoperative patients with CRA will be evaluated. Trial registration Trial registration Chinese Clinical Trial Registry ChiCTR 2100044297. Registered on March 16, 2021

Fusobacterium nucleatum (Fn) is a critical colorectal cancer (CRC)-associated bacterium. DNA hunger/stationary phase protective proteins (Dps) are bacterial ferritins that protect DNA from oxidative stress. However, little is known about the regulatory roles of Fn-Dps towards host cellular functions. Here, we identified Fn-Dps from the culture supernatant of Fn by mass spectrometry, and prepared the recombinant of Fn-Dps protein. We show a novel virulence protein of Fn, Fn-Dps, which lyses and disrupts erythrocytes by the competition for iron acquisition. Also, Fn-Dps facilitates intracellular survival of Fn in macrophages by upregulating the expression of the chemokine CCL2/CCL7. In addition, Fn-Dps can elicit a strong humoral immune response, and mucosal immunization with Fn-Dps conferred protection against Fn in the intestinal tract. Moreover, a high level of anti-Fn-Dps antibody was prevalent in populations, and elevated anti-Fn-Dps antibody levels were observed in CRC patients. Furthermore, Fn-Dps promotes the migration of CRC cells via the CCL2/CCL7-induced epithelial-mesenchymal transition (EMT) and promotes CRC metastasis in vivo.

IntroductionGastric cancer is the fifth most common cancer in the world. At the same time, it is also the fourth most deadly cancer. Early detection of cancer exists as a guide for the treatment of gastric cancer. Nowadays, computer technology has advanced rapidly to assist physicians in the diagnosis of pathological pictures of gastric cancer. Ensemble learning is a way to improve the accuracy of algorithms, and finding multiple learning models with complementarity types is the basis of ensemble learning. Therefore, this paper compares the performance of multiple algorithms in anticipation of applying ensemble learning to a practical gastric cancer classification problem.MethodsThe complementarity of sub-size pathology image classifiers when machine performance is insufficient is explored in this experimental platform. We choose seven classical machine learning classifiers and four deep learning classifiers for classification experiments on the GasHisSDB database. Among them, classical machine learning algorithms extract five different image virtual features to match multiple classifier algorithms. For deep learning, we choose three convolutional neural network classifiers. In addition, we also choose a novel Transformer-based classifier.ResultsThe experimental platform, in which a large number of classical machine learning and deep learning methods are performed, demonstrates that there are differences in the performance of different classifiers on GasHisSDB. Classical machine learning models exist for classifiers that classify Abnormal categories very well, while classifiers that excel in classifying Normal categories also exist. Deep learning models also exist with multiple models that can be complementarity.DiscussionSuitable classifiers are selected for ensemble learning, when machine performance is insufficient. This experimental platform demonstrates that multiple classifiers are indeed complementarity and can improve the efficiency of ensemble learning. This can better assist doctors in diagnosis, improve the detection of gastric cancer, and increase the cure rate.

IntroductionUnderstanding the physiological responses to warming temperatures is critical for evaluating the vulnerabilities of animals to climate warming. The physiological responses are increasingly affected by gut microbiota. However, the interactions between physiological responses and the gut microbiota of sympatric animals from various microhabitats in the face of climate change remain largely unknown.MethodsTo evaluate the effects of warming temperatures on animals from different microhabitats, we compared locomotor performance, metabolic rate, growth, survival, and gut microbiota of two sympatric ectothermic species (Eremias argus and Takydromus amurensis) from open and semi-closed microhabitats under present and moderate warming climate conditions, respectively.Results and discussionWe found that locomotor performance and growth rates of snout-vent length (SVL) were enhanced in both lizard species by warming climate. Interestingly, warming temperatures enhanced resting metabolic rates (RMR) in the open-habitat lizard, E. argus, but depressed them in the semi-closed habitat lizard, T. amurensis. Reversely, the metabolism-related gut microbiota was not affected by warming in E. argus, whereas it was significantly enhanced by warming in T. amurensis, indicating a plausible compensatory effect of the gut microbiota on the metabolic regulation of T. amurensis. Furthermore, warming likely improved immunity in both lizard species by significantly reducing pathogenic bacteria while increasing probiotics. This study found that high-latitude sympatric lizards from both open and semi-closed habitats were beneficial to warming temperatures by physiological modification and regulation of the gut microbiota and highlighted the importance of integrating the physiology and gut microbiota in evaluating the vulnerability of animals to climate warming.

Childhood Guillain–Barré syndrome (GBS) is a rare neurological disease. Early diagnosis followed by precise treatment can reduce mortality. In this study, we collected two transcriptome data between GBS and controls from the publicly available databases (GEO dataset). We identified two distinct down-regulated genes (PTGDS and AR) in GBS by transcriptome analysis (n = 20). Based on the two distinct down-regulated genes in the GBS group, a two-gene diagnostic signature was developed. Moreover, gene expression analysis for the two-gene was performed on a patient with GBS before and after Supportive Care. RT–PCR results show that the expression of PTGDS increased after the patient was given supportive care. Therefore, PTGDS might be considered as a potential target for therapeutic target in GBS.

In parallel with the rapid rise in breast cancer incidence, there is also a noticeable rise in the number of patients who experience persistent negative body image cognition after breast cancer surgery. This study aimed to explore the differences in illness perception, social support, and body image cognition among breast cancer patients with different surgical methods, and the correlation, regression, and mediation among the three variables. The Brief Illness Perception Questionnaire (BIPQ), the Social Support Rating Scale (SSRS) and the Body Image Cognition after Breast Cancer Questionnaire (BIBCQ) were used to evaluate breast cancer patients’ illness perception, social support and body image cognition. Data analyses were performed by descriptive statistics, independent samples t-test, analysis of variance (ANOVA), Pearson correlation, and linear regression. The mediation was explored by the PROCESS V3.3. The study found that breast cancer patients undergoing radical mastectomy (RM) and modified radical mastectomy (MRM) demonstrated more negative illness perception, body image cognition, and lower social support compared with the patients receiving nipple-sparing mastectomy (NSM; p

Abstract Background The purpose of this study is to elucidate the association between peripherally inserted central venous catheter (PICC) in upper extremities and lower extremity deep venous thrombosis (LEDVT) by observing the changes in D-dimer. Methods This was a retrospective cohort study with 3452 patients (104 inserted with PICCs and 3348 without PICC) enrolled at the neurology department from April 1, 2017 to April 1, 2020. The patients underwent color Doppler ultrasound (CDU) and D-dimer examinations. LEDVT-related factors and D-dimer value were analyzed before and after PICC insertion. The predictive value of D-dimer for LEDVT was also evaluated. Results Univariate logistic regression analysis showed that PICC insertion increased the risk of LEDVT by 9 times and promoted the increase of D-dimer by 5 times. After risk adjustment, multivariate logistic regression analysis showed that PICC insertion increased the risk of LEDVT by 4 times and tripled the risk of D-dimer increase. The concentration of D-dimer was significantly increased after PICC insertion. D-dimer was unsuitable for excluding venous thrombosis in patients inserted with PICCs. Conclusions PICC insertion increases the level of D-dimer and the risk of LEDVT. The risks of venous thrombosis need to be assessed in patients inserted with PICCs to ensure the expected clinical outcomes.

Influenza A infection results in γδ T cell influx and production of IL-17 in the lungs. Here, the authors show that this effect is primed by CD1-restricted ligands that are released by infected cells and presented by B1a cells in the lungs.

Abstract Background This study aimed to establish and validate a novel clinical model to differentiate between benign and malignant solitary pulmonary nodules (SPNs). Methods Records from 295 patients with SPNs in Sun Yat-sen University Cancer Center were retrospectively reviewed. The novel prediction model was established using LASSO logistic regression analysis by integrating clinical features, radiologic characteristics and laboratory test data, the calibration of model was analyzed using the Hosmer-Lemeshow test (HL test). Subsequently, the model was compared with PKUPH, Shanghai and Mayo models using receiver-operating characteristics curve (ROC), decision curve analysis (DCA), net reclassification improvement index (NRI), and integrated discrimination improvement index (IDI) with the same data. Other 101 SPNs patients in Henan Tumor Hospital were used for external validation cohort. Results A total of 11 variables were screened out and then aggregated to generate new prediction model. The model showed good calibration with the HL test (P = 0.964). The AUC for our model was 0.768, which was higher than other three reported models. DCA also showed our model was superior to the other three reported models. In our model, sensitivity = 78.84%, specificity = 61.32%. Compared with the PKUPH, Shanghai and Mayo models, the NRI of our model increased by 0.177, 0.127, and 0.396 respectively, and the IDI changed − 0.019, -0.076, and 0.112, respectively. Furthermore, the model was significant positive correlation with PKUPH, Shanghai and Mayo models. Conclusions The novel model in our study had a high clinical value in diagnose of MSPNs.

Abstract Background MicroRNAs (miRNAs) show considerable promise as therapeutic agents to improve tumor treatment, as they have been revealed as crucial modulators in tumor progression. However, our understanding of their roles in gastric carcinoma (GC) metastasis is limited. Here, we aimed to identify novel miRNAs involved in GC metastasis and explored their regulatory mechanisms and therapeutic significance in GC. Methods The microRNA expression profiles of GC tumors at different stages and at different metastasis statuses were compared respectively using the stomach adenocarcinoma (STAD) miRNASeq dataset in TCGA. Using the above method, miR-4521 was picked out for further study. miR-4521 expression in GC tissues was examined by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and in situ hybridization (ISH). Highly and lowly invasive cell sublines were established using a repetitive transwell assay. Gain-of-function and loss-of-function analyses were performed to investigate the functions of miR-4521 and its upstream and downstream regulatory mechanisms in vitro and in vivo. Moreover, we investigated the therapeutic role of miR-4521 in a mouse xenograft model. Results In this study, we found that miR-4521 expression was downregulated in GC tissues compared with adjacent normal tissues and that its downregulation was positively correlated with advanced clinical stage, metastasis status and poor patient prognosis. Functional experiments revealed that miR-4521 inhibited GC cell invasion and metastasis in vitro and in vivo. Further studies showed that hypoxia repressed miR-4521 expression via inducing ETS1 and miR-4521 mitigated hypoxia-mediated metastasis, while miR-4521 inactivated the AKT/GSK3β/Snai1 pathway by targeting IGF2 and FOXM1, thereby inhibiting the epithelial-mesenchymal transition (EMT) process and metastasis. In addition, we demonstrated that therapeutic delivery of synthetic miR-4521 suppressed gastric carcinoma progression in vivo. Conclusions Our results suggest an important role for miR-4521 in regulating GC metastasis and hypoxic response of tumor cells as well as the therapeutic significance of this miRNA in GC.

Background Effective means for early diagnosis are imperative to reduce death rate of non-small cell lung cancer (NSCLC) patients. We aimed to find out high-performance serologic markers to distinguish early-stage NSCLC patients from benign pulmonary nodule patients and healthy controls (HC). Cystatin-SN (CST1) is an active cysteine protease inhibitor of the CST superfamily, involving in the processes of inflammation and tumorigenesis. This is the first exploration of the diagnostic and prognostic values of serum CST1 in NSCLC. Methods We analyzed the transcriptome data from The Cancer Genome Atlas and the Gene Expression Omnibus database, screened biomarkers for NSCLC, and verified the candidate markers via the ONCOMINE database. Then, we performed ELISA, western blotting, and immunohistochemistry analysis to detect the expression levels of CST1 in NSCLC cell lines, tumor tissues, and serum samples of clinical cohorts. Results We identified 3 up-regulated secreted protein-encoding genes, validated the expression levels of CST1 in NSCLC tumor tissues and cell lines, and found that serum CST1 levels of NSCLC (4289 ± 2405 pg/mL) were significantly higher than those of PBN patients (1558 ± 441 pg/mL, P < .0001) and healthy controls (1529 ± 416 pg/mL, P < .0001). The AUC of the combination of CST1, Cytokeratin 19 fragment (Cyfra21-1), and Carcinoembryonic antigen (CEA) for distinguishing early-stage NSCLC from PBN/HC was as high as .914/0.925. Furthermore, our results suggested that the NSCLC patient with low serum CST1 level had a better survival rate. Conclusions Serum CST1 may serve as a novel diagnostic marker for differentiating early-stage NSCLC from PBN and HC, and could be used as a prognosis predictor in NSCLC patients.

Summary: With the rapid emergence and spread of SARS-CoV-2 variants, development of vaccines with broad and potent protectivity has become a global priority. Here, we designed a lipid nanoparticle-encapsulated, nucleoside-unmodified mRNA (mRNA-LNP) vaccine encoding the trimerized receptor-binding domain (RBD trimer) and showed its robust capability in inducing broad and protective immune responses against wild-type and major variants of concern (VOCs) in the mouse model of SARS-CoV-2 infection. The protectivity was correlated with RBD-specific B cell responses especially the long-lived plasma B cells in bone marrow, strong ability in triggering BCR clustering, and downstream signaling. Monoclonal antibodies isolated from vaccinated animals demonstrated broad and potent neutralizing activity against VOCs tested. Structure analysis of one representative antibody identified a novel epitope with a high degree of conservation among different variants. Collectively, these results demonstrate that the RBD trimer mRNA vaccine serves as a promising vaccine candidate against SARS-CoV-2 variants and beyond.

Emerging studies have focused on ways to treat cancers by modulating T cell activation. However, whether B cell receptor signaling in the tumor microenvironment (TME) can be harnessed for immunotherapy is unclear. Here, we report that an Asia-specific variant of human IgG1 containing a Gly396 to Arg396 substitution (hIgG1-G396R) conferred improved survival of patients with colorectal cancer (CRC). Mice with knockin of the murine functional homolog mIgG2c-G400R recapitulated the alleviated tumorigenesis and progression in murine colon carcinoma models. Immune profiling of the TME revealed broad mobilizations of IgG1+ plasma cells, CD8+ T cells, CD103+ DCs, and active tertiary lymphoid structure formation, suggesting an effective antitumor microenvironment in hIgG1-G396R CRC patients. Mechanistically, this variant potentiated tumor-associated antigen–specific (TAA-specific) plasma cell differentiation and thus antibody production. These elevated TAA-specific IgG2c antibodies in turn efficiently boosted the antibody-dependent tumor cell phagocytosis and TAA presentation to effector CD8+ T cells. Notably, adoptive transfer of TAA-specific class-switched memory B cells harboring this variant exhibited therapeutic efficacy in murine tumor models, indicating their clinical potential. All these results prompted a prospective investigation of hIgG1-G396R in patients with CRC as a biomarker for clinical prognosis and demonstrated that manipulating the functionality of IgG1+ memory B cells in tumors could improve immunotherapy outcomes.

Persistent Scatterer SAR Interferometry (PSInSAR) is known as one of the most effective technique for monitoring and analyzing ground deformation. It is a key step that how to identify Persistent Scatterers (PS) effectively and automatically from time-series SAR images. In the past research, one pixel will be classified to "PS" set or "no-PS" set clearly by one or more threshold rules for PS features. However, it is easy to fall into the 'either this or that' logical paradox in some cases because the covered objects in study area usually possess ambiguous boundary for interested characteristics. In this paper, a fuzzy PS concept is present and a fuzzy identification method is designed based on fuzzy set theory by taking the fuzzy characteristics of the pixels into account. Two groups of real data tests indicate that the new method can not only recognize more effective and reliable PS, but also can obtain the better quality results of selected PS, which can be used to evaluate the result of deformation and further improve the PSInSAR technology.

Accurate positioning of the shearer remains a challenge for automation of the longwall coal mining process. In this paper, the popular Ultra-wideband (UWB) positioning system that has attracted considerable attention is adopted to obtain the target node location. Unfortunately, localization accuracy is still unsatisfactory and unreliable in mixed line of sight (LOS) and non-line of sight (NLOS) scenarios. To ameliorate localization accuracy of UWB for complicate underground environment where the positioning scenarios suffered from frequently switching among LOS, NLOS, and mixed LOS-NLOS condition, the novel positioning algorithm GMM-IMM-EKF was proposed. Gaussian mixed model (GMM) was employed to re-estimate the measurement distance, and two parallel variational Bayesian adaptive Kalman filters (VBAKFs) under the structure of interacting multiple model (IMM) was utilized to smoothen the result of GMM to eliminate the LOS and NLOS errors, respectively. Then, the position of the target node was determined by exploiting extended Kalman filter (EKF) based on the outcome of IMM-VBAKF. The proposed approach was assessed by exploiting UWB P440 modules. Comparative experimental verification demonstrated that GMM-IMM-EKF strategy outperformed other positioning approaches, which can effectively reduce the adverse effect of NLOS errors and achieve higher positioning accuracy in underground environment with LOS/NLOS/LOS-NLOS transition conditions.

Human activities and climate change have profoundly changed the hydrological and geomorphological evolutionary processes and trends of rivers and lakes, which, in turn, has affected the utilization of their waterway depth. This study chose the Dongting Lake–Jingjiang confluence of the Changjiang River (Yangtze Rvier), since the operation of the Three Gorges Project, the split ratio of water and the sediment distribution of the three outlets of Dongting Lake—that is, Songzikou, Taipigkou, and Ouchikou—have continued to decrease. Along with the decreasing flow of Dongting Lake, the relative increase in the runoff of the Jingjiang reach and the increase in riverbed erosion intensity have increased the relative height difference between Jingjiang and Dongting Lake, intensifying the reduction of the split ratio of water and the sediment distribution of the three outlets. The riverbed erosion of the Jingjiang reach has created a promising foundation for an increase in the waterway dimensions. However, the length of the reach not meeting the requirements of 4.5× 200 m (water depth × width) is 18.4 km, of which the length in the river-lake confluence is 12.6 km, accounting for 68.35% of the total length of obstructed navigation. Furthermore, at the reach (Zhicheng–Dabujie reach) affected by the first outlet (Songzikou), a 4.5-m flume has been formed, but its width is less than 200 m. Moreover, the “steep slope and rapid current” phenomenon is clear, and it affects the safety of ships. At the reach (Taipingkou reach) affected by the second outlet, the shrinkage of the bottomland, and the intersecting braided river channels make the low-flow routes unstable, the water depth being less than 4.5 m. At the reach (Tianxingzhou–Ouchikou reach) affected by the third outlet, the shoreline of the reach has collapsed and retreated significantly. Additionally, beach erosion and the downstream movement of cut banks have caused the downstream waterway width at the reach to be reduced to less than 200 m or formed shoals with a water depth of less than 4.5 m. Owing to the jacking effect of the lake’s outflow backwater, the flow rate of the reach (Xiongjiazhou–Chenglingji reach) affected by the confluence of Dongting Lake decreased, creating a shoal with a water depth of less than 4.5 m in the navigation waterway. The results of this study have guiding significance for understanding the changes of channel conditions and the improvement of channel scale in the intersection area of rivers and lakes.

The appearance and magnitude of the immune response and the related factors correlated with SARS-CoV-2 vaccination need to be defined. Here, we enrolled a prospective cohort of 52 participants who received two doses of inactivated vaccines (BBIBP-CorV). Their serial plasma samples (n = 260) over 2 months were collected at five timepoints. We measured antibody responses (NAb, S-IgG and S-IgM) and routine blood parameter. NAb seroconversion occurred in 90.7% of vaccinated individuals and four typical NAb kinetic curves were observed. All of the participants who seroconverted after the first dose were females and had relatively high prevaccine estradiol levels. Moreover, those without seroconversion tended to have lower lymphocyte counts and higher serum SAA levels than those who experienced seroconversion. The NAb titers in young vaccine recipients had a significantly higher peak than those in elderly recipients. S-IgG and S-IgM dynamics were accompanied by similar trends in NAb. Here, we gained insight into the dynamic changes in NAbs and preliminarily explored the prevaccine blood parameters related to the kinetic subclasses, providing a reference for vaccination strategies.

Cell death is a vital event in life. Infections and injuries cause lytic cell death, which gives rise to danger signals that can further induce cell death, inflammation, and tissue damage. The mevalonate (MVA) pathway is an essential, highly conserved and dynamic metabolic pathway. Here, we discover that farnesyl pyrophosphate (FPP), a metabolic intermediate of the MVA pathway, functions as a newly identified danger signal to trigger acute cell death leading to neuron loss in stroke. Harboring both a hydrophobic 15-carbon isoprenyl chain and a heavily charged pyrophosphate head, FPP leads to acute cell death independent of its downstream metabolic pathways. Mechanistically, extracellular calcium influx and the cation channel transient receptor potential melastatin 2 (TRPM2) exhibit essential roles in FPP-induced cell death. FPP activates TRPM2 opening for ion influx. Furthermore, in terms of a mouse model constructing by middle cerebral artery occlusion (MCAO), FPP accumulates in the brain, which indicates the function of the FPP and TRPM2 danger signal axis in ischemic injury. Overall, our data have revealed a novel function of the MVA pathway intermediate metabolite FPP as a danger signal via transient receptor potential cation channels.