Acid-assisted ultrasonic preparation of nitrogen-doped MXene quantum dots for the efficient fluorescence "off-on-off" detection of Zn(II) in water and oxalic acid in vegetables.

A novel fluorescence "off-on-off" probe was presented to detect Zn(II) and oxalic acid (OA) based on nitrogen-doped MXene quantum dots (N-MQDs), which were synthesized by an ultrasound approach at room temperature with nitric acid and ethylenediamine. These N-MQDs displayed small size (<10 nm), water dispersibility, and good photoluminescence. Furthermore, the N-MQDs showed an selective response towards Zn(II) through fluorescence enhancement, with a limit of detection (LOD) calculated as 0.127 µM in the linear range of 0-20 µM. Then, the fluorescence of N-MQDs/Zn(II) system could be selectively quenched after adding OA, with an effective response in the range from 0 to 20 µM (LOD: 0.883 µM). The fluorescence "turn-on" and "turn-off" properties of N-MQDs were resulted from the intramolecular charge transfer (ICT) of Zn(II) and the coordination between OA and Zn(II), respectively. This sensing platform was successfully applied for Zn(II) and OA detection in actual environmental and vegetable samples.

Fabrication of Self-Assembled BiFeO3/CeO2 Nanocatalytic Materials for Efficient Catalytic Dye Degradation.

The catalytic treatment of wastewater serves as an effective way to solve the problem of water pollution, in which non-homogeneous Fenton catalysts are widely used. However, the activity enhancement of non-homogeneous Fenton catalysts still remains a great challenge. Herein, self-assembled BiFeO3/CeO2 nanocatalytic materials with different molar ratios were successfully fabricated by a suspension blending method, following which the structure evolution was determined by various characterizations. The catalytic degradation of methylene blue (MB), rhodamine B (RhB), and saffron T (ST) were performed over the BiFeO3/CeO2 nanocatalytic materials. It was found that the 0.2BiFeO3:0.8CeO2 nanocatalytic materials exhibited an 80.8% degradation efficiency for RhB. The 0.6BiFeO3:0.4CeO2 nanocatalytic materials reached 81.1% and 48.7% for ST and MB, respectively. The BiFeO3/CeO2 nanocatalytic materials also showed a good stability during several cycles. The combination of CeO2 with BiFeO3 led to an enhanced activity for dye degradation, probably due to the electron transfer from ≡Fe2+ to ≡Ce4+. This study provides a new approach to dye degradation by using Fenton catalytic systems.

Associations of Dietary Inflammatory Potential with Esophageal Precancerous Lesions and Esophageal Squamous-Cell Cancer: A Cross-Sectional Study.

Chronic inflammation plays a central role in the progression from esophageal precancerous lesions (EPLs) to esophageal squamous-cell cancer (ESCC). However, few studies have investigated the relationship between the overall inflammatory potential of diets and EPLs and ESCC. We aimed to study the association between the Dietary Inflammatory Index (DII) and EPLs and ESCC. As part of the National Cohort of Esophageal Cancer (NCEC) in China, 3967 residents (1993 men and 1974 women) aged from 40 to 69 years living in Yanting County received free gastroscopy screenings from 2017 to 2019. Dietary intake during the past year was assessed at enrollment of the cohort before screening and DII scores were calculated based on 28 food parameters. EPLs (classified into mild, moderate, and severe dysplasia) and ESCC were histologically confirmed by biopsy. Multivariable logistic regression was used to examine the associations of DII scores with EPLs and ESCC. A total of 312 participants were diagnosed with EPLs (226 with mild dysplasia, 40 with moderate dysplasia, and 46 with severe dysplasia) and 72 were diagnosed with ESCC. A statistically significant positive association was observed between DII scores and overall EPLs (ORT3 vs. T1 = 1.45, 95%CI = 1.01-2.09); the association was similar but not statistically significant for mild dysplasia (ORone-unit-increment = 1.11, 95%CI = 0.95-1.34) and for moderate and severe dysplasia combined (ORone-unit-increment = 1.15, 95%CI = 0.87-1.51). The association with ESCC was similar in magnitude but not significant, likely due to the small number of cases. In this cross-sectional study of a population in China at high risk of ESCC, DII scores were positively associated with odds of EPLs and ESCC. Consumption of anti-inflammatory foods may be beneficial to prevent EPLs and ESCC.

An Interpretable High-Accuracy Method for Rice Disease Detection Based on Multisource Data and Transfer Learning.

With the evolution of modern agriculture and precision farming, the efficient and accurate detection of crop diseases has emerged as a pivotal research focus. In this study, an interpretative high-precision rice disease detection method, integrating multisource data and transfer learning, is introduced. This approach harnesses diverse data types, including imagery, climatic conditions, and soil attributes, facilitating enriched information extraction and enhanced detection accuracy. The incorporation of transfer learning bestows the model with robust generalization capabilities, enabling rapid adaptation to varying agricultural environments. Moreover, the interpretability of the model ensures transparency in its decision-making processes, garnering trust for real-world applications. Experimental outcomes demonstrate superior performance of the proposed method on multiple datasets when juxtaposed against advanced deep learning models and traditional machine learning techniques. Collectively, this research offers a novel perspective and toolkit for agricultural disease detection, laying a solid foundation for the future advancement of agriculture.

SP-141 targets Trs85 to inhibit rice blast fungus infection and functions as a potential broad-spectrum antifungal.

Rice blast is a devastating disease worldwide, threatening rice production and food security. The blast fungus Magnaporthe oryzae invades the host via an appressorium specialized pressure-generating structure, which generates enormous turgor to penetrate host cuticles. However, due to the ongoing evolution of fungicide resistance, it is vitally essential to identify new targets and fungicides. Here, we showed that Trs85, a subunit of TRAPPIII complex, is essential for appressorium-mediated infection in M. oryzae. We explained how Trs85 regulates autophagy through Ypt1 (a small GTPase protein) in M. oryzae. We then identified a key conserved amphipathic α-helix within Trs85 associated with the pathogenicity of M. oryzae. Screening with the aid of the computer, we have identified a lead compound SP-141 that affects autophagy and Trs85-Ypt1 interaction. SP-141 demonstrates a substantial capacity to effectively inhibit the infection caused by the rice blast fungus, while also exhibiting a wide-ranging potential as an antifungal agent with broad-spectrum activity. Taken together, our data show that Trs85 is a potential new target and SP-141 has the potential for controlling rice blast. Our findings thus provide a novel strategy that may help humans fight against rice blast.

[Research on Digital Manufacturing Technology of Key Components of Artificial Knee Joint].

The surface of the artificial knee joint manufactured by 3D printing technology is rough. This study uses advanced multi-axis machining technology to study how to improve the manufacturing accuracy of the artificial knee joint surface, and uses five-axis machining CAM software to analyze the process of three-dimensional model of the artificial knee joint and to compile tool path, create a five-axis special post-processor, convert the tool path point file into the NC program for machine tool processing. In order to ensure the safety and efficiency of the processing procedure, a Mikron HEM-500U machine tool simulation platform was built in the VERICUT simulation system for simulation processing verification, and then the blank prototype obtained by 3D printing was processed in a five-axis machine tool to meet medical clinical use requirements.

Current and Future of "Turn-On" Based Small-Molecule Copper Probes for Cuproptosis.

Increasing evidence shows that abnormal copper (Cu) metabolism is highly related to many diseases, such as Alzheimer's disease, Wilson's disease, hematological malignancies and Menkes disease. Very recently, cuproptosis, a Cu-dependent, programmed cell death was firstly described by Tsvetkov et al. in 2022. Their findings may provide a new perspective for the treatment of related diseases. However, the concrete mechanisms of these diseases, especially cuproptosis, remain completely unclear, the reason of which may be a lack of reliable tools to conduct highly selective, sensitive and high-resolution imaging of Cu in complex life systems. So far, numerous small-molecular fluorescent probes have been designed and utilized to explore the Cu signal pathway. Among them, fluorescence turn-on probes greatly enhance the resolution and accuracy of imaging and may be a promising tool for research of investigation into cuproptosis. This review summarizes the probes developed in the past decade which have the potential to study cuproptosis, focusing on the design strategies, luminescence mechanism and biological-imaging applications. Besides, we put forward some ideas concerning the design of next-generation probes for cuproptosis, aiming to tackle the main problems in this new field. Furthermore, the prospect of cuproptosis in the treatment of corresponding diseases is also highlighted.

Large AI Models in Health Informatics: Applications, Challenges, and the Future.

Large AI models, or foundation models, are models recently emerging with massive scales both parameter-wise and data-wise, the magnitudes of which can reach beyond billions. Once pretrained, large AI models demonstrate impressive performance in various downstream tasks. A prime example is ChatGPT, whose capability has compelled people's imagination about the far-reaching influence that large AI models can have and their potential to transform different domains of our lives. In health informatics, the advent of large AI models has brought new paradigms for the design of methodologies. The scale of multi-modal data in the biomedical and health domain has been ever-expanding especially since the community embraced the era of deep learning, which provides the ground to develop, validate, and advance large AI models for breakthroughs in health-related areas. This article presents a comprehensive review of large AI models, from background to their applications. We identify seven key sectors in which large AI models are applicable and might have substantial influence, including 1) bioinformatics; 2) medical diagnosis; 3) medical imaging; 4) medical informatics; 5) medical education; 6) public health; and 7) medical robotics. We examine their challenges, followed by a critical discussion about potential future directions and pitfalls of large AI models in transforming the field of health informatics.

Prevalence of Malnutrition and the Value of Predicting Pancreatic Fistula in Patients with Laparoscopic Pancreatoduodenectomy.

Background: Pancreatoduodenectomy is a standard surgical procedure for periampullary tumors. With recent improvements in perioperative management, postoperative mortality has decreased significantly in recent years; however, postoperative pancreatic fistula (POPF) is still one of the most prevalent and dangerous complications. The purpose of this study was to analyze the prevalence of malnutrition and the value of predicting POPF in patients with laparoscopic pancreatoduodenectomy (LPD). Methods: We retrospectively analyzed the perioperative data of 747 patients undergoing LPD in the Department of Hepatobiliary and Pancreatic Surgery, The First Hospital of Jilin University, China. Simultaneously, we analyzed the prevalence rate of malnutrition with three different nutritional assessment scores and explored the independent risk variables for POPF to identify potential predictive value. Results: Malnutrition was observed in 20.1% of patients with the prognostic nutritional index (PNI), 85.0% of patients with the controlling nutritional status (CONUT) score, and 73.1% of patients with the NRI score. Univariate and multivariate analyses all showed that the risk factors for POPF were pancreatic texture, pancreatic duct diameter, abdominal infection, body mass index (BMI), nomogram-revised risk index (NRI), and PNI. The receiver operating characteristic curve indicated that the BMI/PNI ratio was capable of predicting the occurrence of clinical POPF following LPD, with an area under the curve of 0.708. Conclusions: Compared with no malnourished patients, malnutrition is associated with a higher risk of POPF among patients with LPD. In addition, the BMI/PNI ratio has some predictive value in the development of POPF following LPD.

Mechanical properties and wound healing potential of bacterial cellulose-xyloglucan-dextran hydrogels.

Bacterial cellulose (BC) is a promising material for use as an artificial skin in wound healing application, however, its applications are limited due to its poor malleability. Incorporating non-cellulosic polysaccharides such as dextran and xyloglucan (XG) may enhance its respective wound healing and malleability. This study presents a novel in situ biopreparation method to produce BC-based hybrid hydrogels containing dextran (BC-D) and xyloglucan-dextran (BC-XG-D) with unique mechanical and rheological properties. Structural analysis revealed that dextran of different sizes (10 k, 70 k and 2 M of Mw) form micron-sized particles by loosely binding to cellulosic fibres. The addition of xyloglucan resulted acts as a lubricant in mechanical testing. The BC-XG-D hybrid hydrogels showed a reduced Young's modulus of 4 MPa and a higher maximum tensile strain of 53 % compared to native BC. Moreover, they displayed less plastic but more viscous behaviour under large shear strain deformation. The wound healing animal model experiments demonstrated that the BC-XG-D hybrid hydrogels promoted wound healing process and skin maturation. Overall, these findings contribute to the development of functional BC-based medical materials with desired mechanical and rheological properties that have the potential to accelerate wound healing.

Multi-scale statistical deformation based co-registration of prostate MRI and post-surgical whole mount histopathology.

BACKGROUND: Accurate delineations of regions of interest (ROIs) on multi-parametric magnetic resonance imaging (mpMRI) are crucial for development of automated, machine learning-based prostate cancer (PCa) detection and segmentation models. However, manual ROI delineations are labor-intensive and susceptible to inter-reader variability. Histopathology images from radical prostatectomy (RP) represent the "gold standard" in terms of the delineation of disease extents, for example, PCa, prostatitis, and benign prostatic hyperplasia (BPH). Co-registering digitized histopathology images onto pre-operative mpMRI enables automated mapping of the ground truth disease extents onto mpMRI, thus enabling the development of machine learning tools for PCa detection and risk stratification. Still, MRI-histopathology co-registration is challenging due to various artifacts and large deformation between in vivo MRI and ex vivo whole-mount histopathology images (WMHs). Furthermore, the artifacts on WMHs, such as tissue loss, may introduce unrealistic deformation during co-registration. PURPOSE: This study presents a new registration pipeline, MSERgSDM, a multi-scale feature-based registration (MSERg) with a statistical deformation (SDM) constraint, which aims to improve accuracy of MRI-histopathology co-registration. METHODS: In this study, we collected 85 pairs of MRI and WMHs from 48 patients across three cohorts. Cohort 1 (D1 ), comprised of a unique set of 3D printed mold data from six patients, facilitated the generation of ground truth deformations between ex vivo WMHs and in vivo MRI. The other two clinically acquired cohorts (D2 and D3 ) included 42 patients. Affine and nonrigid registrations were employed to minimize the deformation between ex vivo WMH and ex vivo T2-weighted MRI (T2WI) in D1 . Subsequently, ground truth deformation between in vivo T2WI and ex vivo WMH was approximated as the deformation between in vivo T2WI and ex vivo T2WI. In D2 and D3 , the prostate anatomical annotations, for example, tumor and urethra, were made by a pathologist and a radiologist in collaboration. These annotations included ROI boundary contours and landmark points. Before applying the registration, manual corrections were made for flipping and rotation of WMHs. MSERgSDM comprises two main components: (1) multi-scale representation construction, and (2) SDM construction. For the SDM construction, we collected N = 200 reasonable deformation fields generated using MSERg, verified through visual inspection. Three additional methods, including intensity-based registration, ProsRegNet, and MSERg, were also employed for comparison against MSERgSDM. RESULTS: Our results suggest that MSERgSDM performed comparably to the ground truth (p > 0.05). Additionally, MSERgSDM (ROI Dice ratio = 0.61, landmark distance = 3.26 mm) exhibited significant improvement over MSERg (ROI Dice ratio = 0.59, landmark distance = 3.69 mm) and ProsRegNet (ROI Dice ratio = 0.56, landmark distance = 4.00 mm) in local alignment. CONCLUSIONS: This study presents a novel registration method, MSERgSDM, for mapping ex vivo WMH onto in vivo prostate MRI. Our preliminary results demonstrate that MSERgSDM can serve as a valuable tool to map ground truth disease annotations from histopathology images onto MRI, thereby assisting in the development of machine learning models for PCa detection on MRI.

Microdissection of cancer-associated fibroblast infiltration subtypes unveils the secreted SERPINE2 contributing to immunosuppressive microenvironment and immuotherapeutic resistance in gastric cancer: A large-scale study integrating bulk and single-cell transcriptome profiling.

In the era of immunotherapy, the suboptimal response rate and the development of acquired resistance among the initial beneficiaries continue to present significant challenges across multiple malignancies, including gastric cancer (GC). Considering that the interactions of tumor stroma, especially the cancer-associated fibroblasts (CAFs), with immune and tumor cells, play indispensable roles in tumor progression, tumor microenvironment remodeling and therapeutic responsiveness, in-depth exploration on the roles of CAFs and pivotal mediators of their functions may provide novel clues to increase the effectiveness of current immunotherapeutic drugs and further achieve synergistic antitumor response. Herein, through the consensus clustering of canonical biomarkers, three GC subclasses with different abundance of CAFs were virtually microdissected in four integrated bulk cohorts encompassing 2148 GC patients from 11 independent datasets. An extensive immunogenomic analysis revealed that tumors with high CAFs infiltration were characterized with unfavorable outcomes, aggressive phenotypes, decreased tumor immunogenicity, high risk of immune evasion and thus immunotherapeutic resistance. By leveraging large-scale single-cell transcriptomic profiling, a series of CAF-secreted proteins were identified, among which the SERPINE2 was confirmed to be restrictively enriched in stromal fibroblasts of GC tissues and contribute to promoting a protumor milieu and fostering an immunosuppressive microenvironment via bioinformatics computations and tissue microarray analysis. Moreover, pan-cancer investigations generalized the immunological roles of SERPINE2, especially in pan-gastrointestinal malignancies, with multiple real-world immunotherapy cohorts further confirming its implications on predicting immunotherapeutic efficacy. In conclusion, these findings suggest that the CAF-derived SERPINE2 is a promising immune-oncology target with therapeutic implications to further synergize the immunotherapeutic combinations.

MC1R signaling through the cAMP-CREB/ATF-1 and ERK-NFκB pathways accelerates G1/S transition promoting breast cancer progression.

MC1R, a G-protein coupled receptor, triggers ultraviolet light-induced melanin synthesis and DNA repair in melanocytes and is implicated in the pathogenesis of melanoma. Although widely expressed in different tissue types, its function in non-cutaneous tissue is relatively unknown. Herein, we demonstrate that disruptive MC1R variants associated with melanomagenesis are less frequently found in patients with several cancers. Further exploration revealed that breast cancer tissue shows a significantly higher MC1R expression than normal breast tissue, and knocking down MC1R significantly reduced cell proliferation in vitro and in vivo. Mechanistically, MC1R signaling through the MC1R-cAMP-CREB/ATF-1 and MC1R-ERK-NFκB axes accelerated the G1-S transition in breast cancer cells. Our results revealed a new association between MC1R and breast cancer, which could be potentially targeted therapeutically. Moreover, our results suggest that MC1R-enhancing/activating therapies should be used cautiously, as they might be pro-tumorigenic in certain contexts.

Eco-friendly approach for enhancing the floatability of non-metallic components in waste printed circuit boards: Adding gutter oil during dry grinding.

Waste printed circuit boards (WPCBs) are an attractive secondary resource that is challenging to dispose of due to its complexity. Reverse flotation is an effective method to remove non-metallic particles (NMPs) to obtain metals from WPCBs. Nevertheless, the removal of NMPs is usually inadequate in the present flotation practice. Thus, to provide a clean approach to improve the removal efficiency of NMPs, the method of adding gutter oil during dry grinding process was adopted to enhance the hydrophobic sites on the surface of NMPs to improve the floatability. The surface morphology of NMPs was analyzed by SEM, the results show that the rough morphology inhibited the adhesion of bubbles, while water occupied the cracks and pores, making it challenging for collector adsorption, which result in unstable particle-bubble adhesion. The results of FTIR indicate that both NMPs and gutter oil have -CH3, -CH2, -C = O, -C-O functional groups, which promotes the adsorption of gutter oil on the surface of NMPs. The contact angle (CA) results show that the adsorption of gutter oil on the particle surface is conducive to the formation of enhanced CA. Furthermore, the flotation enhancement effect was verified by flotation kinetic experiments. The accumulated floats yield of NMPs conditioned by gutter oil during grinding is increased from 67.05% (NMPs without conditioning) to 95.02%, and the resin recovery is increased by 31.10%. It is demonstrated that dry grinding with gutter oil can strengthen the floatability of NMPs, which provides a potential approach to increase the flotation efficiency of WPCBs.

Silanol-Engineered Nonclassical Growth of Zeolite Nanosheets from Oriented Attachment of Amorphous Protozeolite Nanoparticles.

Zeolite nonclassical growth via particle attachment has been proposed for two decades, yet the attachment mechanism and kinetic regulation remain elusive. Here, nonclassical growth of an MFI-type zeolite has been achieved by using amorphous protozeolite (PZ) nanoparticles containing encapsulated TPA+ templates and abundant silanols (Si-OH) as sole precursors under hydrothermal conditions. The silanol characteristics of the precursor were studied by two-dimensional (2D) solid-state nuclear magnetic resonance (NMR) correlation spectroscopy, which were proven to play critical roles in determining precursor attachment behavior and crystal growth orientation. Under mechanical ball-milling or tablet-pressing process, pressure drove the fusion of spherical PZ into platelet-like integrated PZ (IPZ) coupled with transformations of external silanols from evenly distributed to curvature-dependent distributed and internal silanols from isolated to spatially proximate. Compared to isolated silanols, the spatially proximate silanols possessed a stronger correlation with TPA+, benefiting the formation of Si-O-Si bonds via silanol condensation. Subsequently, driven by minimization of surface energy, particle attachment of the platelet-like IPZ precursor preferentially occurred at high-curvature surfaces with high-density silanols, leading to anisotropic rates of nonclassical growth and thus the formation of high-aspect-ratio MFI-type zeolite nanosheets. Advanced electron microscopy provided direct evidence of attachment of amorphous IPZ precursors to crystalline intermediate surfaces along the c-axis direction with the formation of amorphous-crystalline interfaces, followed by interface elimination and structural evolution to a single-crystalline phase. Our findings not only unravel the zeolite nonclassical growth mechanism but also reveal the critical role of silanol chemistry in kinetic regulation, which is of great importance for pursuing a tailored zeolite synthesis.

Polyethylenimine-protected green-emission copper nanoclusters as highly effective fluorescent and colorimetric nanoprobe for selective cobalt ions and temperature sensing.

Excessive uptake of Co2+ is harmful to one's physical health and should not be ignored. Herein, a polyethylenimine (PEI) protected hydrophilic copper nanoclusters (PEI-CuNCs) with strong green fluorescence emission around 510 nm was apace synthesized employing a one-pot method without hyperthermia. Interestingly, the as-prepared water-soluble PEI-CuNCs can be specifically quenched by Co2+ at pH 6.0, with a wide detection range (0-500 µM) and a sensitive detection limit of 14.9 nM, which was lower than the maximum level in the body. Besides, the colorimetric detection of Co2+ could be additionally realized based upon the typical yellow color of PEI-CuNCs changed to baby-pink color of the PEI-Co2+ complex. Furthermore, the PEI-CuNCs was employed in fabrication portable test strip for visual detection of Co2+ by capturing the change in fluorescence color, which can be ascribed to the coordination interaction between Co2+ and amine groups in PEI, and also the aggregated quenching of large PEI-CuNCs-Co2+ particles formation. Moreover, the PEI-CuNCs displayed excellent reversible thermo-responsive within a temperature range of 20-65 °C. It is worth mentioning that the PEI-CuNCs exhibited low bio-toxicity and excellent cell permeability when selectively detecting Co2+ in living cells by fluorescence microscopy imaging. Armed with these engaging properties, the sensing system paved a new avenue for the effective development of a convenient fluorescence colorimetry sensor for general assessment of potential risks and specific assessment of human security.

Monotropein Induced Apoptosis and Suppressed Cell Cycle Progression in Colorectal Cancer Cells.

OBJECTIVE: To determine whether monotropein has an anticancer effect and explore its potential mechanisms against colorectal cancer (CRC) through network pharmacology and molecular docking combined with experimental verification. METHODS: Network pharmacology and molecular docking were used to predict potential targets of monotropein against CRC. Cell counting kit assay, plate monoclonal assay and microscopic observation were used to investigate the antiproliferative effects of monotropein on CRC cells HCT116, HT29 and LoVo. Flow cytometry and scratch assay were used to analyze apoptosis and cell cycle, as well as cell migration, respectively in HCT116, HT29, and LoVo cells. Western blotting was used to detect the expression of proteins related to apoptosis, cell cycle, and cell migration, and the expression of proteins key to the Akt pathway. RESULTS: The Gene Ontology and Reactome enrichment analyses indicated that the anticancer potential of monotropein against CRC might be involved in multiple cancer-related signaling pathways. Among these pathways, RAC-beta serine/threonine-protein kinase (Akt1, Akt2), cyclin-dependent kinase 6 (CDK6), matrix metalloproteinase-9 (MMP9), epidermal growth factor receptor (EGFR), cell division control protein 42 homolog (CDC42) were shown as the potential anticancer targets of monotropein against CRC. Molecular docking suggested that monotropein may interact with the 6 targets (Akt1, Akt2, CDK6, MMP9, EGFR, CDC42). Subsequently, cell activity of HCT116, HT29 and LoVo cell lines were significantly suppressed by monotropein (P<0.05). Furthermore, our research revealed that monotropein induced cell apoptosis by inhibiting Bcl-2 and increasing Bax, induced G1-S cycle arrest in colorectal cancer by decreasing the expressions of CyclinD1, CDK4 and CDK6, inhibited cell migration by suppressing the expressions of CDC42 and MMP9 (P<0.05), and might play an anticancer role through Akt signaling pathway. CONCLUSION: Monotropein exerts its antitumor effects primarily by arresting the cell cycle, causing cell apoptosis, and inhibiting cell migration. This indicates a high potential for developing novel medication for treating CRC.

DNA damage repair profiling of esophageal squamous cell carcinoma uncovers clinically relevant molecular subtypes with distinct prognoses and therapeutic vulnerabilities.

BACKGROUND: DNA damage repair (DDR) is a critical process that maintains genomic integrity and plays essential roles at both the cellular and organismic levels. Here, we aimed to characterize the DDR profiling of esophageal squamous cell carcinoma (ESCC), investigate the prognostic value of DDR-related features, and explore their potential for guiding personalized treatment strategies. METHODS: We analyzed bulk and single-cell transcriptomics data from 377 ESCC cases from our institution and other publicly available cohorts to identify major DDR subtypes. The heterogeneity in cellular and functional properties, tumor microenvironment (TME) characteristics, and prognostic significance of these DDR subtypes were investigated using immunogenomic analysis and in vitro experiments. Additionally, we experimentally validated a combinatorial immunotherapy strategy using syngeneic mouse models of ESCC. FINDINGS: DDR alteration profiling enabled us to identify two distinct DDR subtypes, DDRactive and DDRsilent, which exhibited independent prognostic values in locoregional ESCC but not in metastatic ESCC. The DDRsilent subtype was characterized by an inflamed but immune-suppressed microenvironment with relatively high immune cell infiltration, abnormal immune checkpoint expression, T-cell exhaustion, and enrichment of cancer-related pathways. Moreover, DDR subtyping indicates that BRCA1 and HFM1 are robust and independent prognostic factors in locoregional ESCC. Finally, we proposed and verified that the concomitant triggering of GITR or blockade of BTLA with PD-1 blockade or cisplatin chemotherapy represents effective combination strategies for high-risk locoregional ESCC tumors. INTERPRETATION: Our discovery of DDR-based molecular subtypes will enhance our understanding of tumor heterogeneity and have significant clinical implications for the therapeutic and management strategies of locoregional ESCC. FUNDING: This study was supported by the National Key R&D Program of China (2021YFC2501000, 2022YFC3401003), National Natural Science Foundation of China (82172882), the Beijing Natural Science Foundation (7212085), the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-018, 2021-I2M-1-067), the Fundamental Research Funds for the Central Universities (3332021091), and the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences (2019PT310027).

Molecular characterization of a novel mitochondrial NOD-like receptor X1 in chicken that negatively regulates IFN-ß expression via STING.

NOD-like receptor X1 (NLRX1) is known for its unique mitochondrial localization and plays a negative role in innate immunity. The initial characterization and function of chicken NLRX1 remain unclear. Here, chicken mitochondrial-targeted NLRX1 (chNLRX1) protein was identified. It had relatively conserved domains, a unique N-terminal "X" mitochondrial-targeting domain (MT) and 2 highly conserved motifs at positions 510-520 and 412-421. Furthermore, chNLRX1 had a unique 53aa N-terminus-MT consistent with its localization to mitochondria. Additionally, chNLRX1 was observed to reduce the DNA sensing adaptor stimulator of interferon genes (STING)-induced IFN-ß by attenuating the STING-TANK-binding kinase 1 (TBK1) interaction, which is a requisite for the STING-TBK1-IFN-ß signaling pathway. These results suggested that chNLRX1 negatively regulated type-I interferon production via STING in host innate immunity.

A bibliometric and visual analysis of research trends and hotspots of myocardial apoptosis: A review.

BACKGROUND: Recent studies have found that cardiomyocyte apoptosis is closely associated with the pathophysiological development of various cardiovascular diseases, for example chronic heart failure and myocardial infarction. At present, there are many researches in this field, such as pharmacological research, traditional Chinese medicine intervention research and pathway research. However, the relevant research is fragmented, with few comprehensive analysis and systematic combing. METHODS: The relevant literature on cardiomyocyte apoptosis was downloaded from the Web of Science Core Collection (WoSCC) and PubMed databases. Citespace 6.1.R2 software Microsoft Excel 2019 and VOSviewer1.6.18.0 were used for bibliometric and visual analysis of publication volume, countries, institutions, journals, authors, keywords. RESULTS: Since 1996, there are 1881 research articles and reviews related to cardiomyocyte apoptosis published by 10,313 researchers from 1648 institutions in 58 countries or regions were included. The number of annual publications showed an upward trend, especially in recent years. Countries participating in this research area include China, the United States, and Japan. Capital Medical University, Harbin Medical University are the key research institution, and other institutions also have substantial contribution on the project as to cardiomyocyte apoptosis. The journal EUR REV MED PHARMACO has a large number of publications, whereas CIRCULATION has the highest number of co-citations. Keywords analysis showed that apoptosis, expression and oxidative stress had higher frequencies, leading to 8 clusters. CONCLUSIONS: Cardiomyocyte apoptosis is a hot research field in recent years. Through visualization and bibliometric analysis, it is found that this field focus on hotspots like clinical manifestations including heart failure or myocardial infarction, and microscopic mechanisms such as oxidative stress and inflammation.