Validating polyp and instrument segmentation methods in colonoscopy through Medico 2020 and MedAI 2021 Challenges.

Automatic analysis of colonoscopy images has been an active field of research motivated by the importance of early detection of precancerous polyps. However, detecting polyps during the live examination can be challenging due to various factors such as variation of skills and experience among the endoscopists, lack of attentiveness, and fatigue leading to a high polyp miss-rate. Therefore, there is a need for an automated system that can flag missed polyps during the examination and improve patient care. Deep learning has emerged as a promising solution to this challenge as it can assist endoscopists in detecting and classifying overlooked polyps and abnormalities in real time, improving the accuracy of diagnosis and enhancing treatment. In addition to the algorithm's accuracy, transparency and interpretability are crucial to explaining the whys and hows of the algorithm's prediction. Further, conclusions based on incorrect decisions may be fatal, especially in medicine. Despite these pitfalls, most algorithms are developed in private data, closed source, or proprietary software, and methods lack reproducibility. Therefore, to promote the development of efficient and transparent methods, we have organized the "Medico automatic polyp segmentation (Medico 2020)" and "MedAI: Transparency in Medical Image Segmentation (MedAI 2021)" competitions. The Medico 2020 challenge received submissions from 17 teams, while the MedAI 2021 challenge also gathered submissions from another 17 distinct teams in the following year. We present a comprehensive summary and analyze each contribution, highlight the strength of the best-performing methods, and discuss the possibility of clinical translations of such methods into the clinic. Our analysis revealed that the participants improved dice coefficient metrics from 0.8607 in 2020 to 0.8993 in 2021 despite adding diverse and challenging frames (containing irregular, smaller, sessile, or flat polyps), which are frequently missed during a routine clinical examination. For the instrument segmentation task, the best team obtained a mean Intersection over union metric of 0.9364. For the transparency task, a multi-disciplinary team, including expert gastroenterologists, accessed each submission and evaluated the team based on open-source practices, failure case analysis, ablation studies, usability and understandability of evaluations to gain a deeper understanding of the models' credibility for clinical deployment. The best team obtained a final transparency score of 21 out of 25. Through the comprehensive analysis of the challenge, we not only highlight the advancements in polyp and surgical instrument segmentation but also encourage subjective evaluation for building more transparent and understandable AI-based colonoscopy systems. Moreover, we discuss the need for multi-center and out-of-distribution testing to address the current limitations of the methods to reduce the cancer burden and improve patient care.

A single-cell transcriptomic landscape of cadmium-hindered brain development in mice.

The effects of neurotoxicant cadmium (Cd) exposure on brain development have not been well elucidated. To investigate this, we have herein subjected pregnant mice to low-dose Cd throughout gestation. Using single-cell RNA sequencing (scRNA-seq), we explored the cellular responses in the embryonic brain to Cd exposure, and identified 18 distinct cell subpopulations that exhibited varied responses to Cd. Typically, Cd exposure impeded the development and maturation of cells in the brain, especially progenitor cells such as neural progenitor cells (NPCs) and oligodendrocyte progenitor cells (OPCs). It also caused significant cell subpopulation shifts in almost all the types of cells in the brain. Additionally, Cd exposure reduced the dendritic sophistication of cortical neurons in the offspring. Importantly, these changes led to aberrant Ca2+ activity in the cortex and neural behavior changes in mature offspring. These data contribute to our understanding of the effects and mechanisms of Cd exposure on brain development and highlight the importance of controlling environmental neurotoxicant exposure at the population level.

CamoFormer: Masked Separable Attention for Camouflaged Object Detection.

How to identify and segment camouflaged objects from the background is challenging. Inspired by the multi-head self-attention in Transformers, we present a simple masked separable attention (MSA) for camouflaged object detection. We first separate the multi-head self-attention into three parts, which are responsible for distinguishing the camouflaged objects from the background using different mask strategies. Furthermore, we propose to capture high-resolution semantic representations progressively based on a simple top-down decoder with the proposed MSA to attain precise segmentation results. These structures plus a backbone encoder form a new model, dubbed CamoFormer. Extensive experiments show that CamoFormer achieves new state-of-the-art performance on three widely-used camouflaged object detection benchmarks. To better evaluate the performance of the proposed CamoFormer around the border regions, we propose to use two new metrics, i.e. BR-M and BR-F. There are on average  âˆ¼ 5% relative improvements over previous methods in terms of S-measure and weighted F-measure. Our code is available at https://github.com/HVision-NKU/CamoFormer.

Whispers of the polycystic ovary syndrome theater: Directing role of long noncoding RNAs.

Polycystic Ovary Syndrome (PCOS) is a multifaceted endocrine disorder that implicates a spectrum of clinical manifestations, including hormonal imbalance, metabolic dysfunction, and even compromised ovarian granulosa cell (GC) activity. The underlying molecular mechanisms of PCOS remain elusive, presenting a significant barrier to effective diagnosis and treatment. This review delves into the emerging role of long non-coding RNAs (lncRNAs) in the pathophysiology of PCOS, articulating their intricate interactions with mRNAs, microRNAs, and other epigenetic regulators that collectively influence the hormonal and metabolic milieu of PCOS. We examine the dynamic regulatory networks orchestrated by lncRNAs that impact GC function, steroidogenesis, insulin resistance, and inflammatory pathways. By integrating findings from recent studies, we illuminate the potential of lncRNAs as biomarkers for PCOS and highlight their contribution to the disorder, offering a detailed perspective on the lncRNA-mediated modulation of gene expression and pathogenic pathways. Understanding targeted lncRNA interactions with PCOS proposes novel avenues for therapeutic intervention to ameliorate the reproductive and metabolic disturbances characteristic of the syndrome.

Design, synthesis, and biological evaluation of naphthalene imidazo[1,2-b]pyridazine hybrid derivatives as VEGFR selective inhibitors.

The vascular endothelial growth factor receptor (VEGFR) is a receptor tyrosine kinase that is regarded as an emerging target for abnormal angiogenesis diseases. In this study, novel naphthalene imidazo[1,2-b]pyridazine hybrids as VEGFR selective inhibitors were designed and synthesized using a scaffold hopping strategy based on ponatinib, a multitarget kinase inhibitor. Among the evaluated compounds, derivative 9k (WS-011) demonstrated the most potent inhibitory potency against VEGFR-2 (IC50 = 8.4 nM) and displayed superior VEGFR selectivity over a panel of 70 kinases compared with ponatinib. Furthermore, 9k possessed good cytotoxic effects on various cancer cell lines, especially the colon cancer HT-29 cells, with an acceptable oral bioavailability. Moreover, 9k significantly inhibited the migration and invasion of human umbilical vein endothelial cells (HUVEC) cells and induced apoptosis through the upregulation of apoptotic proteins in HT-29 cells. 9k also effectively suppressed the activation of VEGFR-2 signaling pathways, which in turn inhibited the growth of HT-29 cells and the tube formation of HUVECs in vitro. All of the findings revealed that 9k could be considered a promising antiangiogenesis lead that merits further investigation.

Risk Factors for 30-Day Mortality of Community-Acquired Bloodstream Infection Patients in Changsha City, Hunan Province, China.

Purpose: To analyze the factors affecting patients' prognoses based on the community acquired-bloodstream infection patient data from 2017 to 2021. Patients and Methods: The data of 940 patients were retrieved, having at least one positive bilateral blood culture within 48 hours of hospitalization, and grouped into survivor and non-survivor groups. The clinical characteristics, laboratory results, causative pathogen and other indicators were collected and compared, and risk factors were identified by applying Cox proportional hazard regression model to the data. Results: Community acquired-bloodstream infection is most commonly caused by Escherichia coli, Klebsiella species and Staphylococcus hominis. Among the total of 940 selected patients, 52 (5.5%) died during hospitalization. The demographic parameters like age and gender, clinical protocols like maintenance hemodialysis, glucocorticoid use during hospitalization, catheter placement, procaicitonin, total protein, albumin, creatinine, uric acid contents and Sequential Organ Failure Assessment scores were significantly different between the survivor and non-survivor groups. The survival analysis results revealed that age (HR=1.02, 95% CI: 1.00-1.05, P=0.002), glucocorticoid use during hospitalization (HR=3.69, 95% CI: 1.62-8.37, P=0.021) and Sequential Organ Failure Assessment score (HR=1.10, 95% CI: 1.03-1.18, P=0.004) might be the risk factors affecting 30-day mortality in patients with community acquired-bloodstream infection. Conclusion: The identified risk factors may help guide clinical treatment protocol for patients with community acquired-bloodstream infection, providing more effective treatment strategy selection with improved clinical outcomes.

CalibNet: Dual-Branch Cross-Modal Calibration for RGB-D Salient Instance Segmentation.

In this study, we propose a novel approach for RGB-D salient instance segmentation using a dual-branch cross-modal feature calibration architecture called CalibNet. Our method simultaneously calibrates depth and RGB features in the kernel and mask branches to generate instance-aware kernels and mask features. CalibNet consists of three simple modules, a dynamic interactive kernel (DIK) and a weight-sharing fusion (WSF), which work together to generate effective instance-aware kernels and integrate cross-modal features. To improve the quality of depth features, we incorporate a depth similarity assessment (DSA) module prior to DIK and WSF. In addition, we further contribute a new DSIS dataset, which contains 1,940 images with elaborate instance-level annotations. Extensive experiments on three challenging benchmarks show that CalibNet yields a promising result, i.e., 58.0% AP with 320×480 input size on the COME15K-E test set, which significantly surpasses the alternative frameworks. Our code and dataset will be publicly available at: https://github.com/PJLallen/CalibNet.

SIRT5-Mediated Desuccinylation of RAB7A Protects Against Cadmium-Induced Alzheimer's Disease-Like Pathology by Restoring Autophagic Flux.

Cadmium (Cd) is a neurotoxic contaminant that induces cognitive decline similar to that observed in Alzheimer's disease (AD). Autophagic flux dysfunction is attributed to the pathogenesis of AD, and this study aimed to investigate the effect of autophagy on environmental Cd-induced AD progression and the underlying mechanism. Here, Cd exposure inhibited autophagosome-lysosome fusion and impaired lysosomal function, leading to defects in autophagic clearance and then to APP accumulation and nerve cell death. Proteomic analysis coupled with Ingenuity Pathway Analysis (IPA) identified SIRT5 as an essential molecular target in Cd-impaired autophagic flux. Mechanistically, Cd exposure hampered the expression of SIRT5, thus increasing the succinylation of RAB7A at lysine 31 and inhibiting RAB7A activity, which contributed to autophagic flux blockade. Importantly, SIRT5 overexpression led to the restoration of autophagic flux blockade, the alleviation of Aß deposition and memory deficits, and the desuccinylation of RAB7A in Cd-exposed FAD4T mice. Additionally, SIRT5 levels decrease mainly in neurons but not in other cell clusters in the brains of AD patients according to single-nucleus RNA sequencing data from the public dataset GSE188545. This study reveals that SIRT5-catalysed RAB7A desuccinylation is an essential adaptive mechanism for the amelioration of Cd-induced autophagic flux blockade and AD-like pathogenesis.

Discovery of novel natural-product-derived mutant isocitrate dehydrogenases 1 inhibitors: Structure-based virtual screening, biological evaluation and structure-activity relationship study.

Mutations in IDH1 are commonly observed across various cancers, causing the conversion of α-KG to 2-HG. Elevated levels of 2-HG disrupt histone and DNA demethylation processes, promoting tumor development. Consequently, there is substantial interest in developing small molecule inhibitors targeting the mutant enzymes. Herein, we report a structure-based high-throughput virtual screening strategy using a natural products library, followed by hit-to-lead optimization. Through this process, we discover a potent compound, named 11s, which exhibited significant inhibition to IDH1 R132H and IDH1 R132C with IC50 values of 124.4 and 95.7 nM, respectively. Furthermore, 11s effectively reduced 2-HG formation, with EC50 values of 182 nM in U87 R132H cell, and 84 nM in HT-1080 cell. In addition, 11s significantly reduced U87 R132H and HT-1080 cell proliferation with GC50 values of 3.48 and 1.38 µM, respectively. PK-PD experiments further confirmed that compound 11s significantly decreased 2-HG formation in an HT-1080 xenograft mouse model, resulting in notable suppression of tumor growth without apparent loss in body weight.

A prognostic nomogram to predict the cancer-specific survival of patients with initially diagnosed metastatic gastric cancer: a validation study in a Chinese cohort.

BACKGROUND: Few studies have been designed to predict the survival of Chinese patients initially diagnosed with metastatic gastric cancer (mGC). Therefore, the objective of this study was to construct and validate a new nomogram model to predict cancer-specific survival (CSS) in Chinese patients. METHODS: We collected 328 patients with mGC from Northern Jiangsu People's Hospital as the training cohort and 60 patients from Xinyuan County People's Hospital as the external validation cohort. Multivariate Cox regression was used to identify risk factors, and a nomogram was created to predict CSS. The predictive performance of the nomogram was evaluated using the consistency index (C-index), the calibration curve, and the decision curve analysis (DCA) in the training cohort and the validation cohort. RESULTS: Multivariate Cox regression identified differentiation grade (P < 0.001), T-stage (P < 0.05), N-stage (P < 0.001), surgery (P < 0.05), and chemotherapy (P < 0.001) as independent predictors of CSS. Nomogram of chemotherapy regimens and cycles was also designed by us for the prediction of mGC. Thus, these factors are integrated into the nomogram model: the C-index value was 0.72 (95% CI 0.70-0.85) for the nomogram model and 0.82 (95% CI 0.79-0.89) and 0.73 (95% CI 0.70-0.86) for the internal and external validation cohorts, respectively. Calibration curves and DCA also demonstrated adequate fit and ideal net benefit in prediction and clinical applications. CONCLUSIONS: We established a practical nomogram to predict CSS in Chinese patients initially diagnosed with mGC. Nomograms can be used to individualize survival predictions and guide clinicians in making therapeutic decisions.

The BEL1-like homeodomain protein OsBLH4 regulates rice plant height, grain number, and heading date by repressing the expression of OsGA2ox1.

Gibberellins (GAs) play crucial roles in regulating plant architecture and grain yield of crops. In rice, the inactivation of endogenous bioactive GAs and their precursors by GA 2-oxidases (GA2oxs) regulates stem elongation and reproductive development. However, the regulatory mechanisms of GA2ox gene expression, especially in rice reproductive organs, are unknown. The BEL1-like homeodomain protein OsBLH4, a negative regulatory factor for the rice OsGA2ox1 gene, was identified in this study. Loss of OsBLH4 function results in decreased bioactive GA levels and pleiotropic phenotypes, including reduced plant height, decreased grain number per panicle, and delayed heading date, as also observed in OsGA2ox1-overexpressing plants. Consistent with the mutant phenotype, OsBLH4 was predominantly expressed in shoots and young spikelets; its encoded protein was exclusively localized in the nucleus. Molecular analysis demonstrated that OsBLH4 directly bound to the promoter region of OsGA2ox1 to repress its expression. Genetic assays revealed that OsBLH4 acts upstream of OsGA2ox1 to control rice plant height, grain number, and heading date. Taken together, these results indicate a crucial role for OsBLH4 in regulating rice plant architecture and yield potential via regulation of bioactive GA levels, and provide a potential strategy for genetic improvements of rice.

Effect of Boron Content in LiOH Solutions on the Corrosion Behavior of Zr-Sn-Nb Alloy.

In pressurized water reactors, LiOH may be concentrated in some areas, leading to the accelerated corrosion of fuel claddings. Injecting boric acid into primary coolants can mitigate the accelerated corrosion effect of LiOH on Zircaloys, but the effects of boron content on the corrosion behavior of the Zr-Sn-Nb alloy are still unknown. This work focused on the corrosion and hydrogen absorption behavior at 360 °C/18.6 MPa in 100 mg/kg LiOH solutions with 0 mg/kg, 50 mg/kg, and 200 mg/kg boron contents for up to 510 days, aiming to study the effect of boron content on corrosion resistance in LiOH solutions. Corrosion kinetics, microstructures of oxide films, hydrogen absorption concentrations and hydride morphology were obtained after the test. The results show that injecting boron in LiOH solutions can significantly reduce the corrosion weight gain, hydrogen concentration, and hydrogen length of Zr-Sn-Nb alloys, that is, improving corrosion resistance effectively. During the oxidation of the Zr-Sn-Nb alloy, B3+ and Li+ incorporate in oxide films. The incorporation of Li+ may lead to the generation of oxygen vacancies, which can carry oxygen from the solutions to O/M interface, accelerating corrosion. The incorporation of B3+ in oxide films will slow down the oxidation of Zr-Sn-Nb alloys by reducing the oxygen vacancies caused by Li+ aggregation.

Neurotoxicity of Combined Exposure to the Heavy Metals (Pb and As) in Zebrafish (Danio rerio).

Lead (Pb) and arsenic (As) are commonly occurring heavy metals in the environment and produce detrimental impacts on the central nervous system. Although they have both been indicated to exhibit neurotoxic properties, it is not known if they have joint effects, and their mechanisms of action are likewise unknown. In this study, zebrafish were exposed to different concentrations of Pb (40 µg/L, 4 mg/L), As (32 µg/L, 3.2 mg/L) and their combinations (40 µg/L + 32 µg/L, 4 mg/L + 3.2 mg/L) for 30 days. The histopathological analyses showed significant brain damage characterized by glial scar formation and ventricular enlargement in all exposed groups. In addition, either Pb or As staining inhibited the swimming speed of zebrafish, which was enhanced by their high concentrations in a mixture. To elucidate the underlying mechanisms, we examined changes in acetylcholinesterase (AChE) activity, neurotransmitter (dopamine, 5-hydroxytryptamine) levels, HPI axis-related hormone (cortisol and epinephrine) contents and neurodevelopment-related gene expression in zebrafish brain. The observations suggest that combined exposure to Pb and As can cause abnormalities in swimming behavior and ultimately exacerbate neurotoxicity in zebrafish by interfering with the cholinergic system, dopamine and 5-hydroxytryptamine signaling, HPI axis function as well as neuronal development. This study provides an important theoretical basis for the mixed exposure of heavy metals and their toxicity to aquatic organisms.

Radiofrequency radiation reshapes tumor immune microenvironment into antitumor phenotype in pulmonary metastatic melanoma by inducing active transformation of tumor-infiltrating CD8+ T and NK cells.

Immunosuppression by the tumor microenvironment is a pivotal factor contributing to tumor progression and immunotherapy resistance. Priming the tumor immune microenvironment (TIME) has emerged as a promising strategy for improving the efficacy of cancer immunotherapy. In this study we investigated the effects of noninvasive radiofrequency radiation (RFR) exposure on tumor progression and TIME phenotype, as well as the antitumor potential of PD-1 blockage in a model of pulmonary metastatic melanoma (PMM). Mouse model of PMM was established by tail vein injection of B16F10 cells. From day 3 after injection, the mice were exposed to RFR at an average specific absorption rate of 9.7 W/kg for 1 h per day for 14 days. After RFR exposure, lung tissues were harvested and RNAs were extracted for transcriptome sequencing; PMM-infiltrating immune cells were isolated for single-cell RNA-seq analysis. We showed that RFR exposure significantly impeded PMM progression accompanied by remodeled TIME of PMM via altering the proportion and transcription profile of tumor-infiltrating immune cells. RFR exposure increased the activation and cytotoxicity signatures of tumor-infiltrating CD8+ T cells, particularly in the early activation subset with upregulated genes associated with T cell cytotoxicity. The PD-1 checkpoint pathway was upregulated by RFR exposure in CD8+ T cells. RFR exposure also augmented NK cell subsets with increased cytotoxic characteristics in PMM. RFR exposure enhanced the effector function of tumor-infiltrating CD8+ T cells and NK cells, evidenced by increased expression of cytotoxic molecules. RFR-induced inhibition of PMM growth was mediated by RFR-activated CD8+ T cells and NK cells. We conclude that noninvasive RFR exposure induces antitumor remodeling of the TIME, leading to inhibition of tumor progression, which provides a promising novel strategy for TIME priming and potential combination with cancer immunotherapy.

Latent Semantic Consensus for Deterministic Geometric Model Fitting.

Estimating reliable geometric model parameters from the data with severe outliers is a fundamental and important task in computer vision. This paper attempts to sample high-quality subsets and select model instances to estimate parameters in the multi-structural data. To address this, we propose an effective method called Latent Semantic Consensus (LSC). The principle of LSC is to preserve the latent semantic consensus in both data points and model hypotheses. Specifically, LSC formulates the model fitting problem into two latent semantic spaces based on data points and model hypotheses, respectively. Then, LSC explores the distributions of points in the two latent semantic spaces, to remove outliers, generate high-quality model hypotheses, and effectively estimate model instances. Finally, LSC is able to provide consistent and reliable solutions within only a few milliseconds for general multi-structural model fitting, due to its deterministic fitting nature and efficiency. Compared with several state-of-the-art model fitting methods, our LSC achieves significant superiority for the performance of both accuracy and speed on synthetic data and real images.

Long-term cadmium exposure induces epithelial-mesenchymal transition in breast cancer cells by activating CYP1B1-mediated glutamine metabolic reprogramming in BT474 cells and MMTV-Erbb2 mice.

Cadmium (Cd) exposure is known to enhance breast cancer (BC) progression. Cd promotes epithelial-mesenchymal transition (EMT) in BC cells, facilitating BC cell aggressiveness and invasion, but the underlying molecular mechanisms are unclear. Hence, transgenic MMTV-Erbb2 mice (6 weeks) were orally administered Cd (3.6 mg/L, approximately equal to 19.64 µΜ) for 23 weeks, and BC cells (BT474 cells) were exposed to Cd (0, 0.1, 1 or 10 µΜ) for 72 h to investigate the effect of Cd exposure on EMT in BC cells. Chronic Cd exposure dramatically expedited tumor metastasis to multiple organs; decreased E-cadherin density; and increased Vimentin, N-cadherin, ZEB1, and Twist density in the tumor tissues of MMTV-Erbb2 mice. Notably, transcriptomic analysis of BC tumors revealed cytochrome P450 1B1 (CYP1B1) as a key factor that regulates EMT progression in Cd-treated MMTV-Erbb2 mice. Moreover, Cd increased CYP1B1 expression in MMTV-Erbb2 mouse BC tumors and in BT474 cells, and CYP1B1 inhibition decreased Cd-induced BC cell malignancy and EMT in BT474 cells. Importantly, the promotion of EMT by CYP1B1 in Cd-treated BC cells was presumably controlled by glutamine metabolism. This study offers novel perspectives into the effect of environmental Cd exposure on driving BC progression and metastasis, and this study provides important guidance for comprehensively assessing the ecological and health risks of Cd.

Near-Infrared Absorbing Para-Azaquinodimethane Conjugated Polymers Synthesized via the Transition-Metal-Free Route toward Efficient Photothermal Conversion.

Conjugated polymers with strong absorption in the second near-infrared (NIR-II) window have multiple applications. However, the development of new type of NIR-II conjugated polymers via facile and green methods remains challenging. Herein, this work reports a mild and convenient transition-metal-free method to synthesize near-infrared absorbing quinoidal conjugated polymers containing para-azaquinodimethane (AQM) moieties. The AQM quinoidal conjugated polymers with unique molecular structures and tunable optoelectronic properties can be synthesized by combining the Knoevenagel polycondensation of aromatic dialdehyde monomers with commercially available 1,4-diacetyl-2,5-piperazinedione and the following alkylation reaction. The resultant polymer PQ-DPP shows remarkable NIR-II absorption with a narrow band gap of about 1.08 eV. PQ-DPP nanoparticles exhibit high photothermal conversion efficiency of up to 48% under 1064 nm laser irradiation (1 W cm-2) endowing this polymer with potential in bio-related applications.

Segment anything model for medical images?

The Segment Anything Model (SAM) is the first foundation model for general image segmentation. It has achieved impressive results on various natural image segmentation tasks. However, medical image segmentation (MIS) is more challenging because of the complex modalities, fine anatomical structures, uncertain and complex object boundaries, and wide-range object scales. To fully validate SAM's performance on medical data, we collected and sorted 53 open-source datasets and built a large medical segmentation dataset with 18 modalities, 84 objects, 125 object-modality paired targets, 1050K 2D images, and 6033K masks. We comprehensively analyzed different models and strategies on the so-called COSMOS 1050K dataset. Our findings mainly include the following: (1) SAM showed remarkable performance in some specific objects but was unstable, imperfect, or even totally failed in other situations. (2) SAM with the large ViT-H showed better overall performance than that with the small ViT-B. (3) SAM performed better with manual hints, especially box, than the Everything mode. (4) SAM could help human annotation with high labeling quality and less time. (5) SAM was sensitive to the randomness in the center point and tight box prompts, and may suffer from a serious performance drop. (6) SAM performed better than interactive methods with one or a few points, but will be outpaced as the number of points increases. (7) SAM's performance correlated to different factors, including boundary complexity, intensity differences, etc. (8) Finetuning the SAM on specific medical tasks could improve its average DICE performance by 4.39% and 6.68% for ViT-B and ViT-H, respectively. Codes and models are available at: https://github.com/yuhoo0302/Segment-Anything-Model-for-Medical-Images. We hope that this comprehensive report can help researchers explore the potential of SAM applications in MIS, and guide how to appropriately use and develop SAM.

Identification of potentially high drug-like VEGFR2/c-Met dual-target type II kinase inhibitors with symmetric skeletons based on structural screening.

Vascular endothelial growth factor receptor 2 (VEGFR2) and c-Mesenchymal epithelial transition factor (c-Met) are tyrosine kinase receptors associated with the occurrence of malignant tumors. Studies have shown that inhibition of VEGFR2 promotes a feedback increase in c-Met, a mechanism linked to the emergence of resistance to VEGFR2 inhibitors. Therefore, treatment targeting both VEGFR2 and c-Met will have better application prospects. In this study, hierarchical virtual screening was performed on ZINC15, Molport and Mcule-ULTIMATE databases to identify potential VEGFR2/c-Met dual inhibitors. Firstly, the best pharmacophore model for each target was used to cross-screen the three databases, and the compounds that could match the two pharmacophore models were then retained based on the Fit Value of the respective crystal ligands. Compounds ZINC, MOL, and MLB named after their database sources were retained by binding pattern analysis and docking assessment. ADMET predictions indicated that ZINC had significantly higher oral bioavailability compared to the approved drug cabozantinib. This is likely due to ZINC's unique symmetrical backbone with less structure complexity, which may reduce the occurrence of adverse effects. Molecular dynamics simulations and binding free energy analysis showed that all three hit compounds were able to stably bind at the active site, but only ZINC could form high occupancy of hydrogen bonds with both VEGFR2 and c-Met, and also only ZINC had a higher binding free energy than crystal ligands, suggesting that ZINC was the most likely potential VEGFR2/c-Met dual-target inhibitor. This finding provides a promising starting point for the development of VEGFR2/c-Met dual-target inhibitors.Communicated by Ramaswamy H. Sarma.

The effect of epigallocatechin gallate on laying performance, egg quality, immune status, antioxidant capacity, and hepatic metabolome of laying ducks reared in high temperature condition.

Epigallocatechin gallate (EGCG) is a main component in green tea extract, which possesses multiple bioactivities. The present research studied the effects of EGCG on the laying performance, egg quality, immune status, antioxidant capacity, and hepatic metabolome of Linwu laying ducks reared under high temperature. A total of 180 42-w-old healthy Linwu laying ducks were allocated into control or EGCG-treated groups. Each treatment had 6 replicates with 15 ducks in each replicate. Diets for the two groups were basal diets supplemented with 0 or 300 mg/kg EGCG, respectively. All ducks were raised in the high temperature condition (35 ± 2 °C for 6 h from 10:00 to 16:00, and 28 ± 2 °C for the other 18 h from 16:00 to 10:00 the next day) for 21 days. Results showed that EGCG increased the egg production rate (p = 0.014) and enhanced the immunocompetence by improving serum levels of immunoglobulin A (p = 0.008) and immunoglobulin G (p = 0.006). EGCG also fortified the antioxidant capacity by activating superoxide dismutase (p = 0.012), catalase (p = 0.009), and glutathione peroxidase (p = 0.021), and increasing the level of heat-shock protein 70 (p = 0.003) in laying ducks' liver. At the same time, hepatic metabolomics result suggested that EGCG increased the concentration of several key metabolites, such as spermidine (p = 0.031), tetramethylenediamine (p = 0.009), hyoscyamine (p = 0.026), ß-nicotinamide adenine dinucleotide phosphate (p = 0.038), and pantothenic acid (p = 0.010), which were involved in the metabolic pathways of glutathione metabolism, arginine and proline metabolism, ß-alanine metabolism, and tropane, piperidine, and pyridine alkaloid biosynthesis. In conclusion, 300 mg/kg dietary EGCG showed protection effects on the laying ducks reared in high temperature by improving the immune and antioxidant capacities, which contributed to the increase of laying performance of ducks. The potential mechanism could be that EGCG modulate the synthesis of key metabolites and associated metabolic pathways.