Synergistic regulation at physiological, transcriptional and metabolic levels in tomato plants subjected to a combination of salt and heat stress.

With global warming and climate change, abiotic stresses often simultaneously occur. Combined salt and heat stress was a common phenomenon that was severe, particularly in arid/semi-arid lands. We aimed to reveal the systematic responsive mechanisms of tomato genotypes with different salt/heat susceptibilities to combined salt and heat stress. Morphological and physiological responses of salt-tolerant/sensitive and heat-tolerant/sensitive tomatoes at control, heat, salt and combined stress were investigated. Based on leaf Fv /Fm and H2 O2 content, samples from tolerant genotype at the four treatments for 36 h were taken for transcriptomics and metabolomics. We found that plant height, dry weight and net photosynthetic rate decreased while leaf Na+ concentration increased in all four genotypes under salt and combined stress than control. Changes in physiological indicators such as photosynthetic parameters and defence enzyme activities in tomato under combined stress were regulated by the expression of relevant genes and the accumulation of key metabolites. We screened five key pathways in tomato responding to a combination of salt and heat stress, such as oxidative phosphorylation (map00190). Synergistic regulation at morphological, physiological, transcriptional and metabolic levels in tomato plants was induced by combined stress. Heat stress was considered as a dominant stressor for tomato plants under the current combined stress. The oxidative phosphorylation pathway played a key role in tomato in response to combined stress, where tapped key genes (e.g. alternative oxidase, Aox1a) need further functional analysis. Our study will provide a valuable resource important for studying stress combination and improving tomato tolerance.

Phase Change Thermal Storage Materials for Interdisciplinary Applications.

Functional phase change materials (PCMs) capable of reversibly storing and releasing tremendous thermal energy during the isothermal phase change process have recently received tremendous attention in interdisciplinary applications. The smart integration of PCMs with functional supporting materials enables multiple cutting-edge interdisciplinary applications, including optical, electrical, magnetic, acoustic, medical, mechanical, and catalytic disciplines etc. Herein, we systematically discuss thermal storage mechanism, thermal transfer mechanism, and energy conversion mechanism, and summarize the state-of-the-art advances in interdisciplinary applications of PCMs. In particular, the applications of PCMs in acoustic, mechanical, and catalytic disciplines are still in their infancy. Simultaneously, in-depth insights into the correlations between microscopic structures and thermophysical properties of composite PCMs are revealed. Finally, current challenges and future prospects are also highlighted according to the up-to-date interdisciplinary applications of PCMs. This review aims to arouse broad research interest in the interdisciplinary community and provide constructive references for exploring next generation advanced multifunctional PCMs for interdisciplinary applications, thereby facilitating their major breakthroughs in both fundamental researches and commercial applications.

HDAC inhibitor regulates the tumor immune microenvironment via pyroptosis in triple negative breast cancer.

Pyroptosis, an inflammatory form of cell death, promotes the release of immunogenic substances and stimulates immune cell recruitment, a process, which could turn cold tumors into hot ones. Thus, instigating pyroptosis in triple-negative breast cancer (TNBC) serves as a viable method for restoring antitumor immunity. We analyzed the effects of Histone Deacetylase Inhibitors (HDACi) on TNBC cells using the Cell Counting Kit-8 and colony formation assay. Apoptosis and lactate dehydrogenase (LDH) release assays were utilized to determine the form of cell death. The pyroptotic executor was validated by quantitative real-time polymerase chain reaction and western blot. Transcriptome was analyzed to investigate pyroptosis-inducing mechanisms. A subcutaneously transplanted tumor model was generated in BALB/c mice to evaluate infiltration of immune cells. HDACi significantly diminished cell proliferation, and pyroptotic "balloon"-like cells became apparent. HDACi led to an intra and extracellular material exchange, signified by the release of LDH and the uptake of propidium iodide. Among the gasdermin family, TNBC cells expressed maximum quantities of GSDME, and expression of GSDMA, GSDMB, and GSDME were augmented post HDACi treatment. Pyroptosis was instigated via the activation of the caspase 3-GSDME pathway with the potential mechanisms being cell cycle arrest and altered intracellular REDOX balance due to aberrant glutathione metabolism. In vivo experiments demonstrated that HDACi can activate pyroptosis, limit tumor growth, and escalate CD8+ lymphocyte and CD11b+ cell infiltration along with an increased presence of granzyme B in tumors. HDACi can instigate pyroptosis in TNBC, promoting infiltration of immune cells and consequently intensifying the efficacy of anticancer immunity.

Learning protein subcellular localization multi-view patterns from heterogeneous data of imaging, sequence and networks.

Location proteomics seeks to provide automated high-resolution descriptions of protein location patterns within cells. Many efforts have been undertaken in location proteomics over the past decades, thereby producing plenty of automated predictors for protein subcellular localization. However, most of these predictors are trained solely from high-throughput microscopic images or protein amino acid sequences alone. Unifying heterogeneous protein data sources has yet to be exploited. In this paper, we present a pipeline called sequence, image, network-based protein subcellular locator (SIN-Locator) that constructs a multi-view description of proteins by integrating multiple data types including images of protein expression in cells or tissues, amino acid sequences and protein-protein interaction networks, to classify the patterns of protein subcellular locations. Proteins were encoded by both handcrafted features and deep learning features, and multiple combining methods were implemented. Our experimental results indicated that optimal integrations can considerately enhance the classification accuracy, and the utility of SIN-Locator has been demonstrated through applying to new released proteins in the human protein atlas. Furthermore, we also investigate the contribution of different data sources and influence of partial absence of data. This work is anticipated to provide clues for reconciliation and combination of multi-source data for protein location analysis.

The multimodal imaging features and outcomes of multifocal choroiditis/punctate inner choroidopathy lesion with multiple evanescent white dot syndrome-like features: a retrospective study.

BACKGROUND: Multiple evanescent white dot syndrome (MEWDS)-like features is a rare condition triggered by a macular disease or iatrogenic injury, exhibiting MEWDS changes in the fundus. This study aims to describe the multimodal imaging features and outcomes of multifocal choroiditis/punctate inner choroidopathy (MFC/PIC) lesions with MEWDS-like features. METHODS: Six cases were studied retrospectively. All cases were given regional and oral corticosteroids. RESULTS: All cases showed an isolated juxtafoveal yellowish-white MFC/PIC lesion with disruption of RPE-Bruch's membrane-choriocapillaris complex (RPE-BM-CC), subretinal hyperreflective materials and choroidal thickening on optical coherence tomography. Two weeks after presentation, the grayish-white dots disappeared spontaneously and the corticosteroids were given. After four weeks, the ellipsoid zone (EZ) around the lesion and hyper-autofluorescence resolved. After 13 weeks, five cases showed shrinkage of the juxtafoveal lesion and restoration of foveal EZ. After six months, the juxtafoveal lesion became pigmented. Only one case developed type 2 choroidal neovascularization. CONCLUSIONS: The clinical course of MEWDS-like manifestations is still evanescent in our cases. The yellowish-white juxtafoveal MFC/PIC lesions with disruption of RPE-BM-CC and choroidal thickening showed a well-controlled prognosis after corticosteroid treatment.

[Effect of metabolic reprogramming on abdominal aortic aneurysm].

Abdominal aortic aneurysm (AAA) is a life-threatening disease that remains undetected until it acutely ruptures. Due to lack of effective pharmaceutic therapies, it is urgent to explore new prevention and treatment strategies. Metabolic reprogramming is a cellular process through which cells change their metabolic patterns to meet material and energy requirements, including glucose metabolism, lipid metabolism and amino acid metabolism. Recently, the regulatory role of metabolic reprogramming in cardiovascular diseases, especially AAA, has attracted significant attention. This review article focuses on the research progress regarding the effects of metabolic reprogramming of vascular smooth muscle cells (VSMCs) and macrophages on the occurrence and development of AAA, especially their roles in major pathological processes such as VSMCs apoptosis and phenotype transformation, extracellular matrix remodeling, oxidative stress, and inflammatory response. The aim is to provide new clues for the mechanism research and clinical treatment of AAA from the perspective of metabolism.

Deep-silicon photon-counting x-ray projection denoising through reinforcement learning.

BACKGROUND: In recent years, deep reinforcement learning (RL) has been applied to various medical tasks and produced encouraging results. OBJECTIVE: In this paper, we demonstrate the feasibility of deep RL for denoising simulated deep-silicon photon-counting CT (PCCT) data in both full and interior scan modes. PCCT offers higher spatial and spectral resolution than conventional CT, requiring advanced denoising methods to suppress noise increase. METHODS: In this work, we apply a dueling double deep Q network (DDDQN) to denoise PCCT data for maximum contrast-to-noise ratio (CNR) and a multi-agent approach to handle data non-stationarity. RESULTS: Using our method, we obtained significant image quality improvement for single-channel scans and consistent improvement for all three channels of multichannel scans. For the single-channel interior scans, the PSNR (dB) and SSIM increased from 33.4078 and 0.9165 to 37.4167 and 0.9790 respectively. For the multichannel interior scans, the channel-wise PSNR (dB) increased from 31.2348, 30.7114, and 30.4667 to 31.6182, 30.9783, and 30.8427 respectively. Similarly, the SSIM improved from 0.9415, 0.9445, and 0.9336 to 0.9504, 0.9493, and 0.0326 respectively. CONCLUSIONS: Our results show that the RL approach improves image quality effectively, efficiently, and consistently across multiple spectral channels and has great potential in clinical applications.

Multiple energy X-ray imaging of metal oxide particles inside gingival tissues.

BACKGROUND: Periodontal disease affects over 50% of the global population and is characterized by gingivitis as the initial sign. One dental health issue that may contribute to the development of periodontal disease is foreign body gingivitis (FBG), which can result from exposure to some kinds of foreign metal particles from dental products or food. OBJECTIVE: We design a novel, portable, affordable, multispectral X-ray and fluorescence optical microscopic imaging system dedicated to detecting and differentiating metal oxide particles in dental pathological tissues. A novel denoising algorithm is applied. We verify the feasibility and optimize the performance of the imaging system with numerical simulations. METHODS: The designed imaging system has a focused X-ray tube with tunable energy spectra and thin scintillator coupled with an optical microscope as detector. A simulated soft tissue phantom is embedded with 2-micron thick metal oxide discs as the imaged object. GATE software is used to optimize the systematic parameters such as energy bandwidth and X-ray photon number. We have also applied a novel denoising method, Noise2Sim with a two-layer UNet structure, to improve the simulated image quality. RESULTS: The use of an X-ray source operating with an energy bandwidth of 5 keV, X-ray photon number of 108, and an X-ray detector with a 0.5 micrometer pixel size in a 100 by 100-pixel array allowed for the detection of particles as small as 0.5 micrometer. With the Noise2Sim algorithm, the CNR has improved substantially. A typical example is that the Aluminum (Al) target's CNR is improved from 6.78 to 9.72 for the case of 108 X-ray photons with the Chromium (Cr) source of 5 keV bandwidth. CONCLUSIONS: Different metal oxide particles were differentiated using Contrast-to-Noise ratio (CNR) by utilizing four different X-ray spectra.

Discovery of Oogenesis Biomarkers from Mouse Oocytes Using a Single-Cell Proteomics Approach.

We established an efficient and simplified single-cell proteomics (ES-SCP) workflow to realize proteomics profiling at the single-oocyte level. With the ES-SCP workflow, we constructed a deep coverage proteome library during oocyte maturation, which contained more than 6000 protein groups, and identified and quantified more than 4000 protein groups from a pool of only 15 oocytes at germinal vesicle (GV), GV breakdown (GVBD), and metaphase II (MII) stages. More than 1500 protein groups can be identified from single oocytes. We found that marker proteins including maternal factors and mRNA regulators, such as ZAR1, TLE6, and BTG4, showed significant variations in abundance during oocyte maturation, and it was discovered that maternal mRNA degradation was indispensable during oocyte maturation. Proteomics analysis from single oocytes revealed that changes in antioxidant factors, maternal factors, mRNA stabilization, and energy metabolism were the factors that affect the oocyte quality during ovary aging. Our data laid the foundation for future innovations in assisted reproduction.

Engineering 2D MXene and LDH into 3D Hollow Framework for Boosting Photothermal Energy Storage and Microwave Absorption.

2D MXene is highly preferred for photothermal energy conversion and microwave absorption. However, the aggregation issue, insufficient dielectric loss capacity, and lack of magnetic loss capacity for MXene severely hinder its practical applications. Herein, the authors propose multi-dimensional nanostructure engineering to electrostatically assemble 2D MXene and layered double hydroxides (LDH) derived from ZIF-67 polyhedron into a 3D hollow framework (LDH@MXene), and subsequently calcined to construct a Co nanoparticle-modified 3D hollow C-LDH@MXene framework to encapsulate a paraffin wax (PW) phase change material (PCM). The 3D hollow C-LDH@MXene framework not only prevents 2D MXene from aggregation but also contributes a high thermal energy storage density (131.04 J g-1 ). Benefiting from a 3D conductive network facilitating the rapid transport of photons and phonons from the interface to the interior and the synergistic localized surface plasmon resonance (LSPR) effect of MXene and Co magnetic nanoparticles, the C-LDH@MXene-PW composite PCM yielded a high photothermal storage efficiency of 96.52%. Besides, C-LDH@MXene-PW composite PCMs also exhibited efficient microwave absorption with a minimum reflection loss of -20.87 dB at 13.30 GHz with a matching thickness of only 2 mm. This distinctive design provides constructive references for the development of integrated composite materials for energy storage and microwave absorption.

DULoc: quantitatively unmixing protein subcellular location patterns in immunofluorescence images based on deep learning features.

MOTIVATION: Knowledge of subcellular locations of proteins is of great significance for understanding their functions. The multi-label proteins that simultaneously reside in or move between more than one subcellular structure usually involve with complex cellular processes. Currently, the subcellular location annotations of proteins in most studies and databases are descriptive terms, which fail to capture the protein amount or fractions across different locations. This highly limits the understanding of complex spatial distribution and functional mechanism of multi-label proteins. Thus, quantitatively analyzing the multiplex location patterns of proteins is an urgent and challenging task. RESULTS: In this study, we developed a deep-learning-based pattern unmixing pipeline for protein subcellular localization (DULoc) to quantitatively estimate the fractions of proteins localizing in different subcellular compartments from immunofluorescence images. This model used a deep convolutional neural network to construct feature representations, and combined multiple nonlinear decomposing algorithms as the pattern unmixing method. Our experimental results showed that the DULoc can achieve over 0.93 correlation between estimated and true fractions on both real and synthetic datasets. In addition, we applied the DULoc method on the images in the human protein atlas database on a large scale, and showed that 70.52% of proteins can achieve consistent location orders with the database annotations. AVAILABILITY AND IMPLEMENTATION: The datasets and code are available at: https://github.com/PRBioimages/DULoc. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Multiple Local Symmetries Result in a Common Average Polar Axis in High-Strain BiFeO_{3}-Based Ceramics.

For the first time, the origin of large electrostrain in pseudocubic BiFeO_{3}-based ceramics is verified with direct structural evidence backed by appropriate simulations. We employ advanced structural and microstructural characterizations of BiFeO_{3}-based ceramics that exhibit large electrostrain (>0.4%) to reveal the existence of multiple, nanoscale local symmetries, dominantly tetragonal or orthorhombic, which have a common, averaged direction of polarization over larger, meso- or microscale regions. Phase-field simulations confirm the existence of local nanoscale symmetries, thereby providing a new vision for designing high-performance lead-free ceramics for high-strain actuators.

MitraClip used for severe mitral regurgitation after surgery for type A aortic dissection combined with Marfan syndrome.

Mitral regurgitation is a rare but catastrophic condition in patients after surgery for type A aortic dissection. The second thoracotomy to complete the mitral valve operation could be fatal. Here, we report a case of severe mitral regurgitation treated with MitraClip in a 53-year-old woman after surgery for type A aortic dissection combined with Marfan syndrome. She was discharged uneventfully, and a significant reduction of regurgitation of mitral valve and tricuspid valve was observed at the 6-month follow-up. MitraClip could be an alternative device for such high-risk patients.

Clinical outcomes of obstructive sleep apnea in patients with acute coronary syndrome in relation to hyperuricemia status.

The clinical outcome of obstructive sleep apnea in patients with acute coronary syndrome in relation to hyperuricemia is still unclear. We aimed to explore the clinical prognosis of obstructive sleep apnea in patients with acute coronary syndrome in relation to hyperuricemia status. This was a prospective cohort study. We included consecutively eligible patients with acute coronary syndrome who underwent cardiorespiratory polygraphy between June 2015 and January 2020. According to apnea-hypopnea index ≥ 15 events per hr and serum uric acid level, the population was divided into four groups: hyperuricemia with obstructive sleep apnea; hyperuricemia with non-obstructive sleep apnea; no hyperuricemia with obstructive sleep apnea; and no hyperuricemia with non-obstructive sleep apnea. The primary endpoint was major adverse cardiovascular and cerebrovascular events, including cardiovascular death, myocardial infarction, stroke, ischaemia-driven revascularization, and readmission for unstable angina or heart failure. Spearman correlation analysis and Cox regression model were mainly used to estimate the data. The median follow-up was 2.9 years. Among 1925 patients with acute coronary syndrome, 29.6% had hyperuricemia and 52.6% had obstructive sleep apnea. Uric acid was negatively correlated with minimum arterial oxygen saturation and mean arterial oxygen saturation, and positively correlated with apnea-hypopnea index, oxygen desaturation index and the duration of time with arterial oxygen saturation < 90% (p < 0.001). During 2.9 (1.5, 3.6) years of follow-up, obstructive sleep apnea was associated with an increased risk of major adverse cardiovascular and cerebrovascular events in patients with hyperuricemia (23.5% versus 13.4%; adjusted hazard ratio: 1.834; 95% confidence interval: 1.192-2.821, p = 0.006), but not in patients without hyperuricemia (21.9% versus 19.2%; adjusted hazard ratio: 1.131; 95% confidence interval: 0.880-1.453, p = 0.336). There was a correlation between uric acid levels and sleep respiratory indicators. Obstructive sleep apnea was associated with increased risk of major adverse cardiovascular and cerebrovascular events in patients with acute coronary syndrome with hyperuricemia, but not in patients without hyperuricemia.

Non-alcoholic fatty liver disease and complications in type 1 and type 2 diabetes: A Mendelian randomization study.

AIM: To investigate the potential causal relationship between non-alcoholic fatty liver disease (NAFLD) and complications in type 1 diabetes (T1D) and type 2 diabetes (T2D). MATERIALS AND METHODS: Two-sample Mendelian randomization (MR) analysis was conducted to appraise after controlling for the confounding factors. Genetic instrument variables for NAFLD surrogated by chronically elevated serum alanine transferase were derived from a recent genome-wide association study. Diabetes-related complications, including diabetic ketoacidosis, nephropathy and retinopathy, were included as outcomes. Four complementary MR methods were used to test reliability. RESULTS: Genetically instrumented NAFLD showed a suggestive causal association with ketoacidosis in T1D (odds ratio [OR]: 1.574; 95% confidence interval [CI]: 1.076, 2.302; P = .019; false discovery rate [FDR] = 0.096) and a significant causal association with early-stage kidney disease in T1D (OR: 1.249; 95% CI: 1.089, 1.432; P = 1.457 × 10-3 , FDR = 0.015). Sensitivity analysis indicated low heterogeneity, low pleiotropy and high reliability of the causal estimates. However, the MR analyses failed to show a causal association between NAFLD and T1D retinopathy, T2D ketoacidosis, nephropathy and retinopathy. CONCLUSIONS: This study supports a causal effect of genetically driven chronic serum alanine aminotransferase-associated NAFLD on early-stage kidney disease in T1D and a suggestive causal effect on ketoacidosis in T1D. However, MR studies did not provide enough evidence to suggest that NAFLD independently increases the risk of retinopathy in T1D and of ketoacidosis, nephropathy and retinopathy in T2D.

Increasing angular sampling through deep learning for stationary cardiac SPECT image reconstruction.

BACKGROUND: The GE Discovery NM (DNM) 530c/570c are dedicated cardiac SPECT scanners with 19 detector modules designed for stationary imaging. This study aims to incorporate additional projection angular sampling to improve reconstruction quality. A deep learning method is also proposed to generate synthetic dense-view image volumes from few-view counterparts. METHODS: By moving the detector array, a total of four projection angle sets were acquired and combined for image reconstructions. A deep neural network is proposed to generate synthetic four-angle images with 76 ([Formula: see text]) projections from corresponding one-angle images with 19 projections. Simulated data, pig, physical phantom, and human studies were used for network training and evaluation. Reconstruction results were quantitatively evaluated using representative image metrics. The myocardial perfusion defect size of different subjects was quantified using an FDA-cleared clinical software. RESULTS: Multi-angle reconstructions and network results have higher image resolution, improved uniformity on normal myocardium, more accurate defect quantification, and superior quantitative values on all the testing data. As validated against cardiac catheterization and diagnostic results, deep learning results showed improved image quality with better defect contrast on human studies. CONCLUSION: Increasing angular sampling can substantially improve image quality on DNM, and deep learning can be implemented to improve reconstruction quality in case of stationary imaging.

Electroceramics for High-Energy Density Capacitors: Current Status and Future Perspectives.

Materials exhibiting high energy/power density are currently needed to meet the growing demand of portable electronics, electric vehicles and large-scale energy storage devices. The highest energy densities are achieved for fuel cells, batteries, and supercapacitors, but conventional dielectric capacitors are receiving increased attention for pulsed power applications due to their high power density and their fast charge-discharge speed. The key to high energy density in dielectric capacitors is a large maximum but small remanent (zero in the case of linear dielectrics) polarization and a high electric breakdown strength. Polymer dielectric capacitors offer high power/energy density for applications at room temperature, but above 100 °C they are unreliable and suffer from dielectric breakdown. For high-temperature applications, therefore, dielectric ceramics are the only feasible alternative. Lead-based ceramics such as La-doped lead zirconate titanate exhibit good energy storage properties, but their toxicity raises concern over their use in consumer applications, where capacitors are exclusively lead free. Lead-free compositions with superior power density are thus required. In this paper, we introduce the fundamental principles of energy storage in dielectrics. We discuss key factors to improve energy storage properties such as the control of local structure, phase assemblage, dielectric layer thickness, microstructure, conductivity, and electrical homogeneity through the choice of base systems, dopants, and alloying additions, followed by a comprehensive review of the state-of-the-art. Finally, we comment on the future requirements for new materials in high power/energy density capacitor applications.

High Cycle-Life Twistocaloric Cooling of Poly-p-Phenylene Benzodioxole Fibers.

It is an urgent need to develop efficient solid state cooling technologies and materials with high cycle life. Poly-p-phenylene benzodioxole (PBO) is a high performance fiber with excellent mechanical properties. In this work, for the first time, elasto- and twistocaloric cooling of PBO fibers by stretching and twisting of the PBO fiber bundles is reported. The cooling temperature reaches -0.4 and -1.3 K, for fiber stretching and twisting, respectively. A self-coiled PBO fiber achieves maximum cooling of -3.7 K upon stretching by 35% strain, with an exceptionally high cycle life of 200 000 times. During the twisting of the PBO fibers, reversible changes in the intensity of the diffraction peaks in X-ray diffraction patterns are observed. A strain-sensitive color change application is realized by coating a self-coiled PBO fiber with liquid crystallite dyes. This work provides new perspectives for PBO fibers as a high cycle-life solid-state refrigeration material.

Targeting the inward rectifier potassium channel 5.1 in thyroid cancer: artificial intelligence-facilitated molecular docking for drug discovery.

BACKGROUND: Recurrent and metastatic thyroid cancer is more invasive and can transform to dedifferentiated thyroid cancer, thus leading to a severe decline in the 10-year survival. The thyroid-stimulating hormone receptor (TSHR) plays an important role in differentiation process. We aim to find a therapeutic target in redifferentiation strategies for thyroid cancer. METHODS: Our study integrated the differentially expressed genes acquired from the Gene Expression Omnibus database by comparing TSHR expression levels in the Cancer Genome Atlas database. We conducted functional enrichment analysis and verified the expression of these genes by RT-PCR in 68 pairs of thyroid tumor and paratumor tissues. Artificial intelligence-enabled virtual screening was combined with the VirtualFlow platform for deep docking. RESULTS: We identified five genes (KCNJ16, SLC26A4, TG, TPO, and SYT1) as potential cancer treatment targets. TSHR and KCNJ16 were downregulated in the thyroid tumor tissues, compared with paired normal tissues. In addition, KCNJ16 was lower in the vascular/capsular invasion group. Enrichment analyses revealed that KCNJ16 may play a significant role in cell growth and differentiation. The inward rectifier potassium channel 5.1 (Kir5.1, encoded by KCNJ16) emerged as an interesting target in thyroid cancer. Artificial intelligence-facilitated molecular docking identified Z2087256678_2, Z2211139111_1, Z2211139111_2, and PV-000592319198_1 (-7.3 kcal/mol) as the most potent commercially available molecular targeting Kir5.1. CONCLUSION: This study may provide greater insights into the differentiation features associated with TSHR expression in thyroid cancer, and Kir5.1 may be a potential therapeutic target in the redifferentiation strategies for recurrent and metastatic thyroid cancer.

Relationship between endoscopic gastric abnormalities and colorectal polyps: a cross-sectional study based on 33439 Chinese patients.

Background: No study on the relationship between common abnormalities of the upper digestive tract and colorectal polyps (CPs) has been conducted. Methods: 33439 patients were enrolled in this cross-sectional study, of which 7700 had available Helicobacter pylori (H.pylori) information. All participants underwent colonoscopy and esophagogastroduodenoscopy (EGD) simultaneously or within six months at Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology from January 2015 to November 2021. The study assessed whether the risk of CPs was affected by the following gastroesophageal diseases: atrophic gastritis (AG), gastric polyps, Barrett's esophagus and reflux esophagitis, bile reflux, gastric ulcer, gastric mucosal erosion, superficial gastritis, and gastric H.pylori infection. The crude and adjusted odds ratios (ORs) of H.pylori on the occurrence of CPs were computed by logistic regression. Additionally, we also evaluated whether AG had an impact on the relationship between H.pylori infection and CPs. Results: A total of 10600 cases (31.7%) were diagnosed as CPs. Multivariate logistic analysis showed that age, male (OR, 1.80; 95% confidence interval [CI], 1.61 to 2.02), gastric polyps (OR, 1.61; 95% CI, 1.05 to 2.46 for hyperplastic polyps; OR, 1.45; 95% CI, 1.09 to 1.94 for fundic gland polyps), H.pylori infection (OR, 1.21; 95% CI, 1.07 to 1.37) and atrophic gastritis (OR, 1.38; 95% CI, 1.21 to 1.56) were independent risk factors for colorectal polyps. Moreover, the combined effect of H.pylori infection and AG was slightly greater than the sum of their individual effects on the risk of CPs, but there was no additive interaction between them. Conclusions: Gastric conditions including gastric polyps, H.pylori infection, and AG increased the risk of CPs. However, Barrett's esophagus and reflux esophagitis, bile reflux, erosive gastritis, gastric ulcer, and superficial gastritis might not have relationship with CPs occurrence.