[Differences in Soil Fertility and Bacterial Community Structure Between Carbon Inputs such as Biochar and Organic Fertilizer and Their Relationship].

The potato planting area of Guizhou Province ranks second in China. However, due to factors such as climatic conditions and unbalanced fertilization, soil organic matter in potato fields is consumed rapidly and has a large deficit, which affects soil biological function and soil fertility. Biochar and organic fertilizer are effective ways to supplement foreign aid organic matter to improve soil quality. However, the differences in soil fertility and microbial community structure and their relationships under the conditions of organic fertilizer or biochar combined with chemical fertilizer are not clear. In this study, three treatments of conventional fertilization （NPK）, increased application of biochar （NPKB）, and increased application of organic fertilizer （NPKO） were set up to investigate the characteristics of potato rhizosphere soil, bacterial community composition, and diversity； to analyze the effects of these factors on the soil integrated fertility index； and to explore the direct and indirect effects of IFI on soil fertility and bacterial community structure differences between treatments and their driving factors. The results showed that soil pH, available phosphorus （AP）, available potassium （AK）, total nitrogen （TN）, organic carbon （SOC）, and C/N ratio were significantly higher in the NPKB and NPKO treatments than in the NPK treatment （P<0.05）. Soil IFI was greatest for NPKO, followed by NPKB and least for the NPK treatment. A total of 8 214 ASVs were obtained from all the soil samples, belonging to 26 phyla, 75 classes, 165 orders, 176 families, and 251 genera （excluding unidentified fungi）. Proteobacteria, Actinobacteria, and Chloroflexi were the dominant phyla, accounting for 54.85% of all ASVs. Compared to that in the NPK and NPKB treatments, the NPKO treatment had the highest bacterial diversity and number of significantly different taxa, and soil AN, AP, AK, SOC, TN, and IFI were significant correlates of bacterial diversity index （P<0.05）. Additionally, pH, TN, and SOC were significant influencers of bacterial taxa differences （P<0.05）, with importance ranked as TN （70.59%） > SOC （49.42%） > pH （27.08%）. Structural equations suggested that pH-related soil properties and bacterial community diversity were the direct pathways influencing IFI, and soil pH-related soil characteristics could also indirectly affect IFI by affecting bacterial Shannon diversity. These results indicate that soil fertility and bacterial community structure were significantly different and correlated between the biochar and organic fertilizer addition treatments and that pH and bacterial community diversity were the key factors influencing IFI, with the NPKO treatment in particular having the best effect on improving IFI. Considering the effect of soil fertilization and the functional group of bacteria, NPKO is the recommended combination for the best synergistic effect of soil fertilization, that is, N 150 kg·hm-2+P2O5 135 kg·hm-2+K2O 135 kg·hm-2+organic fertilizer 6.6 t·hm-2.

Structure evolution and specific effects for the catalysis of atomically ordered intermetallic compounds.

Atomically ordered intermetallic compounds (IMCs) have been extensively studied for exploring catalysts with high activity, selectivity, and longevity. Compared to random alloys, IMCs present a more pronounced geometric and electronic effect with desirable catalytic performance. Their well-defined structure makes IMCs ideal model catalysts for studying the catalytic mechanism. This review focuses especially on elemental composition, electron transfer, and structure/phase evolution under high temperature treatment conditions, providing direct evidence for the migration and rearrangement of metal atoms through electron microscopy. We then present the outstanding applications of IMCs in growing single-walled nanotubes, hydrogenation/dehydrogenation reactions, and electrocatalysis from the perspective of electronic, geometric, strain, and bifunctional effects of ordered IMCs. Finally, the current obstacles associated with the use of in situ techniques are proposed, as well as future research possibilities.

Alterations of resting-state network dynamics in Alzheimer's disease based on leading eigenvector dynamics analysis.

Alzheimer's disease (AD) is a neurodegenerative disease, and mild cognitive impairment (MCI) is considered a transitional stage between healthy aging and dementia. Early detection of MCI can help slow down the progression of AD. At present, there are few studies exploring the characteristics of abnormal dynamic brain activity in AD. This article uses a method called Leading Eigenvector Dynamics Analysis (LEiDA) to study resting-state functional magnetic resonance imaging (rs-fMRI) data of AD, MCI, and cognitively normal (CN) participants. By identifying repetitive states of phase coherence, inter group differences in brain dynamic activity indicators are examined. And the neurobehavioral scales were used to assess the relationship between abnormal dynamic activities and cognitive function. The results showed that in the indicators of occurrence probability and lifetime, the globally synchronized state of the patient group decreased. The activity state of the limbic regions significantly detected the difference between AD and the other two groups. Compared to CN, AD and MCI have varying degrees of increase in default and visual regions activity states. In addition, in the analysis related to the cognitive scales, it was found that individuals with poorer cognitive abilities were less active in the globally synchronized state, and more active in limbic regions activity state and visual regions activity state. Taken together, these findings reveal abnormal dynamic activity of resting-state networks in patients with AD and MCI, provide new insights into the dynamic analysis of brain networks, and contribute to a deeper understanding of abnormal spatial dynamic patterns in AD patients.

Molecular Editing of Pyrroles to Benzenes/Naphthalenes by N2O Deletion.

Molecular editing promises to facilitate the rapid diversification of complex molecular architectures by rapidly and conveniently altering core frameworks. This approach has the potential to accelerate both drug discovery and total synthesis. In this study, we present a novel protocol for the molecular editing of pyrroles. Initially, N-Boc pyrroles and alkynes are converted into N-bridged compounds through a Diels-Alder reaction. These compounds then undergo deprotection of the Boc group, nitrosylation, and cheletropic N2O extrusion to yield benzene or naphthalene products. By using benzyne as a substrate, this method can be conceptually viewed as a fusion of skeletal editing of the pyrrole ring and site-selective peripheral editing of the benzene ring. Furthermore, this proof-of-concept protocol has demonstrated its potential to transform the (hetero)arene motif from commercially available drugs, offering the possibility of generating new biologically active compounds.

Moderate/severe biatrial dilation predicts adverse events after ablation in atrial fibrillation with heart failure.

AIMS: To retrospectively compare the long-term outcomes following atrial fibrillation (AF) ablation between heart failure (HF) with preserved ejection fraction (EF) (HFpEF) and reduced/mildly reduced EF (HFr-mrEF) patients, and to identify novel predictors of adverse clinical events. METHODS: In total, 1402 AF patients with HF who underwent successful ablation were consecutively enrolled. Adverse clinical events including all-cause death, HF hospitalization, and stroke were followed up. Cox proportional hazards models were used to assess the associations between clinical factors and events. Kaplan-Meier analysis was performed to estimate the cumulative incidences of these events. A receiver operating characteristic curve was used to test the ability of these predictors. RESULTS: During a follow-up period of 42 ± 15 months, 265 (18.9%) patients experienced adverse clinical events after ablation. The cumulative incidence of adverse clinical events was significantly higher in HFr-mrEF than in HFpEF (25.4% vs. 15.7%, P < 0.001), the similar tendency was observed on all-cause death (10.5% vs. 6.5%, P = 0.011) and HF hospitalization (17.2% vs. 10.1%, P < 0.001). After multivariate adjustment, non-paroxysmal AF [hazard ratio (HR) 1.922, 95% confidence interval (CI) 1.130-3.268, P = 0.016], LAD ≥ 45 mm (HR 2.197, 95% CI 1.206-4.003, P < 0.001), LVEF (HR 0.959, 95% CI 0.946-0.981, P < 0.001), and RAD ≥ 45 mm (HR 2.044, 95% CI 1.362-3.238, P < 0.001) remained the independent predictors for developing adverse clinical events. A predictive model performed with non-paroxysmal AF, LAD ≥ 45 mm and RAD ≥ 45 mm yielded an area under curve of 0.728 (95% CI 0.696-0.760, P < 0.001). CONCLUSIONS: AF patients with HFpEF had better long-term outcomes than those with HFr-mrEF, and moderate/severe biatrial dilation could predict adverse clinical events following catheter ablation in AF and HF patients.

Biomimetic ZIF-8 Nanoparticles: A Novel Approach for Biomimetic Drug Delivery Systems.

Metal-organic frameworks (MOFs) are porous materials resulting from the coordination of metal clusters or ions with organic ligands, merging macromolecular and coordination chemistry features. Among these, zeolitic imidazolate framework-8 (ZIF-8) stands out as a widely utilized MOF known for its robust stability in aqueous environments owing to the robust interaction between its constituent zinc ions (Zn2+) and 2-methylimidazole (2-MIM). ZIF-8 readily decomposes under acidic conditions, serving as a promising candidate for pH-responsive drug delivery systems. Moreover, biomimetic materials typically possess good biocompatibility, reducing immune reactions. By mimicking natural structures or surface features within the body, they enhance the targeting of nanoparticles, prolong their circulation time, and increase their bioavailability in vivo. This review explores the latest advancements in biomimetic ZIF-8 nanoparticles for drug delivery, elucidating the primary obstacles and future prospects in utilizing ZIF-8 for drug delivery applications.

A Rat Model of Middle Cerebral Artery Occlusion/Reperfusion without Damaging the Anatomical Structure of Cerebral Vessels.

Ischemic stroke stands as the primary cause of long-term disability and mortality among adults worldwide. Animal models of ischemic stroke have significantly contributed to our understanding of its pathological mechanisms and the development of potential treatments. Presently, there are two common methods involving filament (endovascular suture) techniques to induce animal models of cerebral ischemia. However, these methods have inherent limitations, such as reduced blood perfusion to the brain, damage to the external carotid artery system, impaired food and/or water intake, and sensory dysfunction of the face. This article introduces a new method for inducing a rat ischemic stroke model without compromising the cerebral vascular anatomy. In this study, the common carotid artery (CCA) of Sprague-Dawley rats was exposed, and an incision was made. A filament was then inserted through the incision into the internal carotid artery to occlude the middle cerebral artery. After 1.5 h of induced ischemia, the occluding filament was fully removed from both the internal carotid artery and the CCA. The incision in the CCA was subsequently sutured using 11-0 microsurgical sutures under a microscope (magnification 4x). Through the utilization of microsurgical techniques to repair the CCA, this study successfully developed a unique method to induce an ischemic stroke model in rats while preserving the anatomical integrity of cerebral blood vessels.

Discovery of an immunosuppressive functional metabolite from the insect-derived endophytic Aspergillus taichungensis SMU01.

Three p-terphenyl metabolites (1-3), three indole-diterpenoids (4-6), an herbicide sesquiterpene (7), a flavonoid (8), and five other small molecules containing nitrogen (9-13) were isolated from the medicinal insect (Periplaneta americana)-derived endophytic Aspergillus taichungensis SMU01. Their chemical structures were elucidated on the basis of spectroscopic data and quantum chemical computational methods. Biological activity of these isolates in the differentiation of mouse CD4+ T cell subsets was evaluated. Importantly, metabolites 2 targeting JAK-STAT signaling pathway could hold potential benefits in maintaining peripheral immune homeostasis and alleviating the progression of autoimmune diseases.

Effect of cytochrome P450 3A4 on tissue distribution of humantenmine, koumine, and gelsemine, three alkaloids from the toxic plant Gelsemium.

Humantenmine, koumine, and gelsemine are three indole alkaloids found in the highly toxic plant Gelsemium. Humantenmine was the most toxic, followed by gelsemine and koumine. The aim of this study was to investigate and analyze the effects of these three substances on tissue distribution and toxicity in mice pretreated with the Cytochrome P450 3A4 (CYP3A4) inducer ketoconazole and the inhibitor rifampicin. The in vivo test results showed that the three alkaloids were absorbed rapidly and had the ability to penetrate the blood-brain barrier. At 5 min after intraperitoneal injection, the three alkaloids were widely distributed in various tissues and organs, the spleen and pancreas were the most distributed, and the content of all tissues decreased significantly at 20 min. Induction or inhibition of CYP3A4 in vivo can regulate the distribution and elimination effects of the three alkaloids in various tissues and organs. Additionally, induction of CYP3A4 can reduce the toxicity of humantenmine, and vice versa. Changes in CYP3A4 levels may account for the difference in toxicity of humantenmine. These findings provide a reliable and detailed dataset for drug interactions, tissue distribution, and toxicity studies of Gelsemium alkaloids.

A Typology of Social Media Use by Human Service Nonprofits: Mixed Methods Study.

BACKGROUND: Nonprofit organizations are increasingly using social media to improve their communication strategies with the broader population. However, within the domain of human service nonprofits, there is hesitancy to fully use social media tools, and there is limited scope among organizational personnel in applying their potential beyond self-promotion and service advertisement. There is a pressing need for greater conceptual clarity to support education and training on the varied reasons for using social media to increase organizational outcomes. OBJECTIVE: This study leverages the potential of Twitter (subsequently rebranded as X [X Corp]) to examine the online communication content within a sample (n=133) of nonprofit sexual assault (SA) centers in Canada. To achieve this, we developed a typology using a qualitative and supervised machine learning model for the automatic classification of tweets posted by these centers. METHODS: Using a mixed methods approach that combines machine learning and qualitative analysis, we manually coded 10,809 tweets from 133 SA centers in Canada, spanning the period from March 2009 to March 2023. These manually labeled tweets were used as the training data set for the supervised machine learning process, which allowed us to classify 286,551 organizational tweets. The classification model based on supervised machine learning yielded satisfactory results, prompting the use of unsupervised machine learning to classify the topics within each thematic category and identify latent topics. The qualitative thematic analysis, in combination with topic modeling, provided a contextual understanding of each theme. Sentiment analysis was conducted to reveal the emotions conveyed in the tweets. We conducted validation of the model with 2 independent data sets. RESULTS: Manual annotation of 10,809 tweets identified seven thematic categories: (1) community engagement, (2) organization administration, (3) public awareness, (4) political advocacy, (5) support for others, (6) partnerships, and (7) appreciation. Organization administration was the most frequent segment, and political advocacy and partnerships were the smallest segments. The supervised machine learning model achieved an accuracy of 63.4% in classifying tweets. The sentiment analysis revealed a prevalence of neutral sentiment across all categories. The emotion analysis indicated that fear was predominant, whereas joy was associated with the partnership and appreciation tweets. Topic modeling identified distinct themes within each category, providing valuable insights into the prevalent discussions surrounding SA and related issues. CONCLUSIONS: This research contributes an original theoretical model that sheds light on how human service nonprofits use social media to achieve their online organizational communication objectives across 7 thematic categories. The study advances our comprehension of social media use by nonprofits, presenting a comprehensive typology that captures the diverse communication objectives and contents of these organizations, which provide content to expand training and education for nonprofit leaders to connect and engage with the public, policy experts, other organizations, and potential service users.

Interleukin-21 receptor signaling promotes metabolic dysfunction-associated steatohepatitis-driven hepatocellular carcinoma by inducing immunosuppressive IgA+ B cells.

BACKGROUND: Dysregulation of immune surveillance is tightly linked to the development of metabolic dysfunction-associated steatohepatitis (MASH)-driven hepatocellular carcinoma (HCC); however, its underlying mechanisms remain unclear. Herein, we aimed to determine the role of interleukin-21 receptor (IL-21R) in MASH-driven HCC. METHODS: The clinical significance of IL-21R was assessed in human HCC specimens using immunohistochemistry staining. Furthermore, the expression of IL-21R in mice was assessed in the STAM model. Thereafter, two different MASH-driven HCC mouse models were applied between IL-21R-deficient mice and wild type controls to explore the role of IL-21R in MASH-driven HCC. To further elucidate the potential mechanisms by which IL-21R affected MASH-driven HCC, whole transcriptome sequencing, flow cytometry and adoptive lymphocyte transfer were performed. Finally, flow cytometry, enzyme-linked immunosorbent assay, immunofluorescent staining, chromatin immunoprecipitation assay and western blotting were conducted to explore the mechanism by which IL-21R induced IgA+ B cells. RESULTS: HCC patients with high IL-21R expression exhibited poor relapse-free survival, advanced TNM stage and severe steatosis. Additionally, IL-21R was demonstrated to be upregulated in mouse liver tumors. Particularly, ablation of IL-21R impeded MASH-driven hepatocarcinogenesis with dramatically reduction of lipid accumulation. Moreover, cytotoxic CD8+ T lymphocyte activation was enhanced in the absence of IL-21R due to the reduction of immunosuppressive IgA+ B cells. Mechanistically, the IL-21R-STAT1-c-Jun/c-Fos regulatory axis was activated in MASH-driven HCC and thus promoted the transcription of Igha, resulting in the induction of IgA+ B cells. CONCLUSIONS: IL-21R plays a cancer-promoting role by inducing IgA+ B cells in MASH-driven hepatocarcinogenesis. Targeting IL-21R signaling represents a potential therapeutic strategy for cancer therapy.

An NGS-based assay for accurate detection and quantification of immune gene expression in mouse tumor models.

Tumor microenvironment (TME) is a complex dynamic system with many tumor-interacting components including tumor-infiltrating leukocytes (TILs), cancer associated fibroblasts, blood vessels, and other stromal constituents. It intrinsically affects tumor development and pharmacology of oncology therapeutics, particularly immune-oncology (IO) treatments. Accurate measurement of TME is therefore of great importance for understanding the tumor immunity, identifying IO treatment mechanisms, developing predictive biomarkers, and ultimately, improving the treatment of cancer. Here, we introduce a mouse-IO NGS-based (NGSmIO) assay for accurately detecting and quantifying the mRNA expression of 1080 TME related genes in mouse tumor models. The NGSmIO panel was shown to be superior to the commonly used microarray approach by hosting 300 more relevant genes to better characterize various lineage of immune cells, exhibits improved mRNA and protein expression correlation to flow cytometry, shows stronger correlation with mRNA expression than RNAseq with 10x higher sequencing depth, and demonstrates higher sensitivity in measuring low-expressed genes. We describe two studies; firstly, detecting the pharmacodynamic change of interferon-γ expression levels upon anti-PD-1: anti-CD4 combination treatment in MC38 and Hepa 1-6 tumors; and secondly, benchmarking baseline TILs in 14 syngeneic tumors using transcript level expression of lineage specific genes, which demonstrate effective and robust applications of the NGSmIO panel.

Non-Hermitian Strongly Interacting Dirac Fermions.

Exotic quantum phases and phase transition in the strongly interacting Dirac systems have attracted tremendous interests. On the other hand, non-Hermitian physics, usually associated with dissipation arising from the coupling to environment, emerges as a frontier of modern physics in recent years. In this Letter, we investigate the interplay between non-Hermitian physics and strong correlation in Dirac-fermion systems. We generalize the projector quantum Monte-Carlo (PQMC) algorithm to the non-Hermitian interacting fermionic systems. Employing PQMC simulation, we decipher the ground-state phase diagram of the honeycomb Hubbard model with spin resolved non-Hermitian asymmetric hopping processes. The antiferromagnetic (AFM) ordering induced by Hubbard interaction is enhanced by the non-Hermitian asymmetric hopping. Combining PQMC simulation and renormalization group analysis, we reveal that the quantum phase transition between Dirac semi-metal and AFM phases belongs to Hermitian chiral XY universality class, implying that a Hermitian Gross-Neveu transition is emergent at the quantum critical point although the model is non-Hermitian.

Fe-TiO2-x/TiO2 S-scheme homojunction for efficient photocatalytic CO2 reduction.

CO2-to-high value-added chemicals via a photocatalytic route is of interest but strangled by the low efficiency. Herein, a novel Fe-TiO2-x/TiO2 S-scheme homojunction was designed and constructed by using a facile surface modification approach whereby oxygen vacancy (OV) and Fe introducing on the TiO2 nanorod surface. The as-synthesized Fe-TiO2-x/TiO2 S-scheme homojunction exhibits positive properties on promoting photocatalytic CO2 reduction: i) the nanorod structure provides numerous active sites and a radical charge transfer path; ii) the doped Fe and OV not only synergistically enhance light utilization but also promote CO2 adsorption; iii) the Fe-TiO2-x/TiO2 S-scheme homojunction benefits photoexcited charge separation and retains stronger redox capacity. Thanks to those good characters, the Fe-TiO2-x/TiO2 homojunction exhibits superior CO2 reduction performances with optimized CO/CH4 generation rates of 122/22 µmol g-1h-1 which exceed those of pure TiO2 by more than 9.4/7.3 folds and most currently reported catalytic systems. This manuscript develops a facile and universal approach to synthesize well-defined homojunction and may inspire the construction of other more high-efficiency photocatalysts toward CO2 reduction and beyond.

Narazaciclib, a novel multi-kinase inhibitor with potent activity against CSF1R, FLT3 and CDK6, shows strong anti-AML activity in defined preclinical models.

CSF1R is a receptor tyrosine kinase responsible for the growth/survival/polarization of macrophages and overexpressed in some AML patients. We hypothesized that a novel multi-kinase inhibitor (TKi), narazaciclib (HX301/ON123300), with high potency against CSF1R (IC50 ~ 0.285 nM), would have anti-AML effects. We tested this by confirming HX301's high potency against CSF1R (IC50 ~ 0.285 nM), as well as other kinases, e.g. FLT3 (IC50 of ~ 19.77 nM) and CDK6 (0.53 nM). An in vitro proliferation assay showed that narazaciclib has a high growth inhibitory effect in cell cultures where CSF1R or mutant FLT3-ITD variants that may be proliferation drivers, including primary macrophages (IC50 of 72.5 nM) and a subset of AML lines (IC50 < 1.5 µM). In vivo pharmacology modeling of narazaciclib using five AML xenografts resulted in: inhibition of MV4-11 (FLT3-ITD) subcutaneous tumor growth and complete suppression of AM7577-PDX (FLT3-ITD/CSF1Rmed) systemic growth, likely due to the suppression of FLT3-ITD activity; complete suppression of AM8096-PDX (CSF1Rhi/wild-type FLT3) growth, likely due to the inhibition of CSF1R ("a putative driver"); and nonresponse of both AM5512-PDX and AM7407-PDX (wild-type FLT3/CSF1Rlo). Significant leukemia load reductions in bone marrow, where disease originated, were also achieved in both responders (AM7577/AM8096), implicating that HX301 might be a potentially more effective therapy than those only affecting peripheral leukemic cells. Altogether, narazaciclib can potentially be a candidate treatment for a subset of AML with CSF1Rhi and/or mutant FLT3-ITD variants, particularly second generation FLT3 inhibitor resistant variants.

ATG-101 Is a Tetravalent PD-L1×4-1BB Bispecific Antibody That Stimulates Antitumor Immunity through PD-L1 Blockade and PD-L1-Directed 4-1BB Activation.

Immune checkpoint inhibitors (ICI) have transformed cancer treatment. However, only a minority of patients achieve a profound response. Many patients are innately resistant while others acquire resistance to ICIs. Furthermore, hepatotoxicity and suboptimal efficacy have hampered the clinical development of agonists of 4-1BB, a promising immune-stimulating target. To effectively target 4-1BB and treat diseases resistant to ICIs, we engineered ATG-101, a tetravalent "2+2″ PD-L1×4-1BB bispecific antibody. ATG-101 bound PD-L1 and 4-1BB concurrently, with a greater affinity for PD-L1, and potently activated 4-1BB+ T cells when cross-linked with PD-L1-positive cells. ATG-101 activated exhausted T cells upon PD-L1 binding, indicating a possible role in reversing T-cell dysfunction. ATG-101 displayed potent antitumor activity in numerous in vivo tumor models, including those resistant or refractory to ICIs. ATG-101 greatly increased the proliferation of CD8+ T cells, the infiltration of effector memory T cells, and the ratio of CD8+ T/regulatory T cells in the tumor microenvironment (TME), rendering an immunologically "cold" tumor "hot." Comprehensive characterization of the TME after ATG-101 treatment using single-cell RNA sequencing further revealed an altered immune landscape that reflected increased antitumor immunity. ATG-101 was well tolerated and did not induce hepatotoxicity in non-human primates. According to computational semimechanistic pharmacology modeling, 4-1BB/ATG-101/PD-L1 trimer formation and PD-L1 receptor occupancy were both maximized at around 2 mg/kg of ATG-101, providing guidance regarding the optimal biological dose for clinical trials. In summary, by localizing to PD-L1-rich microenvironments and activating 4-1BB+ immune cells in a PD-L1 cross-linking-dependent manner, ATG-101 safely inhibits growth of ICI resistant and refractory tumors. SIGNIFICANCE: The tetravalent PD-L1×4-1BB bispecific antibody ATG-101 activates 4-1BB+ T cells in a PD-L1 cross-linking-dependent manner, minimizing the hepatotoxicity of existing 4-1BB agonists and suppressing growth of ICI-resistant tumors. See related commentary by Ha et al., p. 1546.

Construction and validation of artificial intelligence pathomics models for predicting pathological staging in colorectal cancer: Using multimodal data and clinical variables.

OBJECTIVE: This retrospective observational study aims to develop and validate artificial intelligence (AI) pathomics models based on pathological Hematoxylin-Eosin (HE) slides and pathological immunohistochemistry (Ki67) slides for predicting the pathological staging of colorectal cancer. The goal is to enable AI-assisted accurate pathological staging, supporting healthcare professionals in making efficient and precise staging assessments. METHODS: This study included a total of 267 colorectal cancer patients (training cohort: n = 213; testing cohort: n = 54). Logistic regression algorithms were used to construct the models. The HE image features were used to build the HE model, the Ki67 image features were used for the Ki67 model, and the combined model included features from both the HE and Ki67 images, as well as tumor markers (CEA, CA724, CA125, and CA242). The predictive results of the HE model, Ki67 model, and tumor markers were visualized through a nomogram. The models were evaluated using ROC curve analysis, and their clinical value was estimated using decision curve analysis (DCA). RESULTS: A total of 260 deep learning features were extracted from HE or Ki67 images. The AUC for the HE model and Ki67 model in the training cohort was 0.885 and 0.890, and in the testing cohort, it was 0.703 and 0.767, respectively. The combined model and nomogram in the training cohort had AUC values of 0.907 and 0.926, and in the testing cohort, they had AUC values of 0.814 and 0.817. In clinical DCA, the net benefit of the Ki67 model was superior to the HE model. The combined model and nomogram showed significantly higher net benefits compared to the individual HE model or Ki67 model. CONCLUSION: The combined model and nomogram, which integrate pathomics multi-modal data and clinical-pathological variables, demonstrated superior performance in distinguishing between Stage I-II and Stage III colorectal cancer. This provides valuable support for clinical decision-making and may improve treatment strategies and patient prognosis. Furthermore, the use of immunohistochemistry (Ki67) slides for pathomics modeling outperformed HE slide, offering new insights for future pathomics research.

Association between the cumulative triglyceride-glucose index and the recurrence of atrial fibrillation after radiofrequency catheter ablation.

BACKGROUND: Triglyceride-glucose (TyG) index values are a new surrogate marker for insulin resistance. This study aimed to explore the relationship between cumulative TyG index values and atrial fibrillation (AF) recurrence after radiofrequency catheter ablation (RFCA). METHODS: A total of 576 patients with AF who underwent RFCA at the Second Affiliated Hospital of Xi'an Jiaotong University were included in this study. The participants were grouped based on cumulative TyG index values tertiles within 3 months after ablation. Cox regression and restricted cubic spline analyses were used to determine the relationship between cumulative TyG index values and AF recurrence. The predictive value of all risk factors was assessed by receiver operating curve analysis. RESULTS: There were 375 patients completed the study (age: 63.23 ± 10.73 years, 64.27% male). The risk of AF recurrence increased with increasing cumulative TyG index values tertiles. After adjusting for potential confounders, patients in the medium cumulative TyG index group [hazard ratio (HR) = 4.949, 95% CI: 1.778-13.778, P = 0.002] and the high cumulative TyG index group (HR = 8.716, 95% CI: 3.371-22.536, P < 0.001) had a higher risk of AF recurrence than those in the low cumulative TyG index group. The restricted cubic spline regression model also showed an increased risk of AF recurrence with increasing cumulative TyG index values. When considering cumulative TyG index values, left atrial diameter, and lactate dehydrogenase levels as a comprehensive factor, the model could effectively predict AF recurrence after RFCA [area under the curve (AUC) = 0.847, 95% CI: 0.797-0.897, P < 0.001]. CONCLUSIONS: Cumulative TyG index values were a risk factor for AF recurrence after RFCA. Monitoring longitudinal TyG index values may assist with optimized for risk stratification and outcome prediction for AF recurrence.