Machine learning unveils immune-related signature in multicenter glioma studies.

In glioma molecular subtyping, existing biomarkers are limited, prompting the development of new ones. We present a multicenter study-derived consensus immune-related and prognostic gene signature (CIPS) using an optimal risk score model and 101 algorithms. CIPS, an independent risk factor, showed stable and powerful predictive performance for overall and progression-free survival, surpassing traditional clinical variables. The risk score correlated significantly with the immune microenvironment, indicating potential sensitivity to immunotherapy. High-risk groups exhibited distinct chemotherapy drug sensitivity. Seven signature genes, including IGFBP2 and TNFRSF12A, were validated by qRT-PCR, with higher expression in tumors and prognostic relevance. TNFRSF12A, upregulated in GBM, demonstrated inhibitory effects on glioma cell proliferation, migration, and invasion. CIPS emerges as a robust tool for enhancing individual glioma patient outcomes, while IGFBP2 and TNFRSF12A pose as promising tumor markers and therapeutic targets.

Double counting heart rate - Littmann sign in electrocardiogram.

This report highlights necessity of correctly and quickly identifying Littmann sign. Littmann sign is not common in clinical practice, which is easily overlooked by most physicians, leading to delays in the treatment of hyperkalemia. A 68 year old patient with hyperkalemia was found to have inconsistent heart rate displayed on electrocardiogram monitoring with cardiac auscultation and synchronous electrocardiogram in the early stages of onset. Hyperkalemia was highly suspected by the Littmann sign. After completing arterial blood gas analysis, hyperkalemia was identified and active potassium lowering treatment was immediately initiated. The Littmann syndrome disappeared, and the patient eventually recovered.

Pan-cancer analysis revealed prognosis value and immunological relevance of RAMPs.

Whether receptor activity-modifying proteins (RAMPs) play a key role in human cancer prognosis and immunity remains unknown. We used data from the public databases, The Cancer Genome Atlas, Therapeutically Applicable Research to Generate Effective Treatments, and the Genotype-Tissue Expression project. We utilized bioinformatics methods, R software, and a variety of online databases to analyze RAMPs. In general, RAMPs were significantly and differentially expressed in multiple tumors, and RAMP expression was closely associated with prognosis, immune checkpoints, RNA-editing genes, tumor mutational burden, microsatellite instability, ploidy, and stemness indices. In addition, the expression of RAMPs is strongly correlated with tumor-infiltrating lymphocytes in human cancers. Moreover, the RAMP co-expression network is largely involved in many immune-related biological processes. Quantitative reverse transcription polymerase chain reaction and Western blot proved that RAMP3 was highly expressed in glioma, and RAMP3 promoted tumor proliferation and migration. RAMPs exhibit potential as prognostic and immune-related biomarkers in human cancers. Moreover, RAMPs can be potentially developed as therapeutic targets or used to enhance the efficacy of immunotherapy.

Comparison of pulmonary artery sarcoma and pulmonary thromboembolism according to clinical and computed tomography pulmonary angiography and magnetic resonance imaging characteristics: a single-center retrospective study.

Background: Pulmonary artery sarcoma (PAS) is a very rare malignancy with a poor prognosis; however, its clinical manifestations and imaging findings are often indistinguishable from pulmonary thromboembolism (PTE). We thus aimed to accurately diagnose PAS by comparing the clinical and computed tomography pulmonary angiography (CTPA) and magnetic resonance imaging (MRI) imaging characteristics of PAS and PTE. Methods: This case-control study retrospectively enrolled 20 patients with PAS (from March 2017 to September 2022), 40 patients with central acute PTE, and 40 patients with central chronic PTE (from January 2021 to December 2022) in the China-Japan Friendship Hospital. The following clinical and imaging findings were compared between the three groups: initial symptoms; D-dimer, C-reactive protein, and N-terminal pro B-type natriuretic peptide levels; wall-eclipsing sign (WES); scope of lesion involvement; and morphological characteristics. Signal intensity was also observed on different MRI sequences. Results: The D-dimer level in PAS was significantly lower than that in central acute PTE (P<0.001). The WES was present in 17 cases of PAS (85.0%), which was a greater proportion than that of the central acute PTE and chronic PTE groups (all P values <0.001). The involvement of the pulmonary valve or right ventricular outflow tract was observed in five PAS cases but none of the central acute PTE or chronic PTE cases (all P values =0.001). In 19 PAS cases (95.0%), the lesions grew expansively in the central pulmonary artery. The proximal margin of 18 patients with PAS (90.0%) was bulging or lobulated. Nine cases of PAS (45.0%) showed aneurysm-like dilatation (grape-like sign) of the distal pulmonary artery, representing significantly greater proportion than that of the central acute PTE and chronic PTE groups (all P values <0.001). In 37 patients with central acute PTE (92.5%), the clots were observed to be floating in the pulmonary artery lumen with saddle, tubular or polypoid shape. Eccentric filling defects attached to the pulmonary artery wall were observed in 32 cases of central chronic PTE (80.0%). On MRI, PAS lesions were hyperintense on fat-suppressed T2-weighted imaging and diffusion-weighted imaging, demonstrating heterogeneous enhancement. Conclusions: Comprehensive analysis of the clinical data and imaging features on CTPA and MRI can aid in the accurate differential diagnosis of PAS and PTE.

Unraveling the efficacy network: A network meta-analysis of adjuvant external beam radiation therapy methods after hepatectomy.

BACKGROUND: Primary liver cancer is a malignant tumor with a high recurrence rate that significantly affects patient prognosis. Postoperative adjuvant external radiation therapy (RT) has been shown to effectively prevent recurrence after liver cancer resection. However, there are multiple RT techniques available, and the differential effects of these techniques in preventing postoperative liver cancer recurrence require further investigation. AIM: To assess the advantages and disadvantages of various adjuvant external RT methods after liver resection based on overall survival (OS) and disease-free survival (DFS) and to determine the optimal strategy. METHODS: This study involved network meta-analyses and followed the PRISMA guidelines. The data of qualified studies published before July 10, 2023, were collected from PubMed, Embase, the Web of Science, and the Cochrane Library. We included relevant studies on postoperative external beam RT after liver resection that had OS and DFS as the primary endpoints. The magnitudes of the effects were determined using risk ratios with 95% confidential intervals. The results were analyzed using R software and STATA software. RESULTS: A total of 12 studies, including 1265 patients with hepatocellular carcinoma (HCC) after liver resection, were included in this study. There was no significant heterogeneity in the direct paired comparisons, and there were no significant differences in the inclusion or exclusion criteria, intervention measures, or outcome indicators, meeting the assumptions of heterogeneity and transitivity. OS analysis revealed that patients who underwent stereotactic body radiotherapy (SBRT) after resection had longer OS than those who underwent intensity modulated radiotherapy (IMRT) or 3-dimensional conformal RT (3D-CRT). DFS analysis revealed that patients who underwent 3D-CRT after resection had the longest DFS. Patients who underwent IMRT after resection had longer OS than those who underwent 3D-CRT and longer DFS than those who underwent SBRT. CONCLUSION: HCC patients who undergo liver cancer resection must consider distinct advantages and disadvantages when choosing between SBRT and 3D-CRT. IMRT, a RT technique that is associated with longer OS than 3D-CRT and longer DFS than SBRT, may be a preferred option.

Developing the Lung Graph-Based Machine Learning Model for Identification of Fibrotic Interstitial Lung Diseases.

Accurate detection of fibrotic interstitial lung disease (f-ILD) is conducive to early intervention. Our aim was to develop a lung graph-based machine learning model to identify f-ILD. A total of 417 HRCTs from 279 patients with confirmed ILD (156 f-ILD and 123 non-f-ILD) were included in this study. A lung graph-based machine learning model based on HRCT was developed for aiding clinician to diagnose f-ILD. In this approach, local radiomics features were extracted from an automatically generated geometric atlas of the lung and used to build a series of specific lung graph models. Encoding these lung graphs, a lung descriptor was gained and became as a characterization of global radiomics feature distribution to diagnose f-ILD. The Weighted Ensemble model showed the best predictive performance in cross-validation. The classification accuracy of the model was significantly higher than that of the three radiologists at both the CT sequence level and the patient level. At the patient level, the diagnostic accuracy of the model versus radiologists A, B, and C was 0.986 (95% CI 0.959 to 1.000), 0.918 (95% CI 0.849 to 0.973), 0.822 (95% CI 0.726 to 0.904), and 0.904 (95% CI 0.836 to 0.973), respectively. There was a statistically significant difference in AUC values between the model and 3 physicians (p < 0.05). The lung graph-based machine learning model could identify f-ILD, and the diagnostic performance exceeded radiologists which could aid clinicians to assess ILD objectively.

Clot ratio, new clot burden score with deep learning, correlates with the risk stratification of patients with acute pulmonary embolism.

Background: Risk stratification for patients with acute pulmonary embolism (APE) is significantly important for treatment and prognosis evaluation. We aimed to develop a novel clot burden score on computed tomography pulmonary angiography (CTPA) based on deep learning (DL) algorithm for risk stratification of APE. Methods: The study retrospectively enrolled patients newly diagnosed with APE in China-Japan Friendship Hospital consecutively. We collected baseline data and CTPA parameters, and calculated four different clot burden scores, including Qanadli score, Mastora score, clot volume and clot ratio. The former two were calculated by two radiologists separately, while clot volume and clot ratio were based on the DL algorithm. The area under the curve (AUC) of four clot burden scores were analyzed. Results: Seventy patients were enrolled, including 17 in high-/intermediate-high risk and 53 in low-/intermediate-low risk. Clot burden was related to the risk stratification of APE. Among four clot burden scores, clot ratio had the highest AUC (0.719, 95% CI: 0.569-0.868) to predict patients with higher risk. In the patients with hemodynamically stable APE, only clot ratio presented statistical difference (P=0.046). Conclusions: Clot ratio is a new imaging marker of clot burden which correlates with the risk stratification of patients with APE. Higher clot ratio may indicate higher risk and acute right ventricular dysfunction in patients with hemodynamically stable status.

Causal effects of gut microbiota on sepsis and sepsis-related death: insights from genome-wide Mendelian randomization, single-cell RNA, bulk RNA sequencing, and network pharmacology.

BACKGROUND: Gut microbiota alterations have been implicated in sepsis and related infectious diseases, but the causal relationship and underlying mechanisms remain unclear. METHODS: We evaluated the association between gut microbiota composition and sepsis using two-sample Mendelian randomization (MR) analysis based on published genome-wide association study (GWAS) summary statistics. Sensitivity analyses were conducted to validate the robustness of the results. Reverse MR analysis and integration of GWAS and expression quantitative trait loci (eQTL) data were performed to identify potential genes and therapeutic targets. RESULTS: Our analysis identified 11 causal bacterial taxa associated with sepsis, with increased abundance of six taxa showing positive causal relationships. Ten taxa had causal effects on the 28-day survival outcome of septic patients, with increased abundance of six taxa showing positive associations. Sensitivity analyses confirmed the robustness of these associations. Reverse MR analysis did not provide evidence of reverse causality. Integration of GWAS and eQTL data revealed 76 genes passing the summary data-based Mendelian randomization (SMR) test. Differential expression of these genes was observed between sepsis patients and healthy individuals. These genes represent potential therapeutic targets for sepsis. Molecular docking analysis predicted potential drug-target interactions, further supporting their therapeutic potential. CONCLUSION: Our study provides insights for the development of personalized treatment strategies for sepsis and offers preliminary candidate targets and drugs for future drug development.

Assessment of lung deformation in patients with idiopathic pulmonary fibrosis with elastic registration technique on pulmonary three-dimensional ultrashort echo time MRI.

OBJECTIVE: To assess lung deformation in patients with idiopathic pulmonary fibrosis (IPF) using with elastic registration algorithm applied to three-dimensional ultrashort echo time (3D-UTE) MRI and analyze relationship of lung deformation with the severity of IPF. METHODS: Seventy-six patients with IPF (mean age: 62 ± 6 years) and 62 age- and gender-matched healthy controls (mean age: 58 ± 4 years) were prospectively enrolled. End-inspiration and end-expiration images acquired with a single breath-hold 3D-UTE sequence were registered using elastic registration algorithm. Jacobian determinants were calculated from deformation fields and represented on color maps. Jac-mean (absolute value of the log means of Jacobian determinants) and the Dice similarity coefficient (Dice) were compared between different groups. RESULTS: Compared with healthy controls, the Jac-mean of IPF patients significantly decreased (0.21 ± 0.08 vs. 0.27 ± 0. 07, p < 0.001). Furthermore, the Jac-mean and Dice correlated with the metrics of pulmonary function tests and the composite physiological index. The lung deformation in IPF patients with dyspnea Medical Research Council (MRC) ≥ 3 (Jac-mean: 0.16 ± 0.03; Dice: 0.06 ± 0.02) was significantly lower than MRC1 (Jac-mean: 0. 25 ± 0.03, p < 0.001; Dice: 0.10 ± 0.01, p < 0.001) and MRC 2 (Jac-mean: 0.22 ± 0.11, p = 0.001; Dice: 0.08 ± 0.03, p = 0.006). Meanwhile, Jac-mean and Dice correlated with health-related quality of life, 6 min-walk distance, and the extent of pulmonary fibrosis. Jac-mean correlated with pulmonary vascular-related indexes on high-resolution CT. CONCLUSION: The decreased lung deformation in IPF patients correlated with the clinical severity of IPF patients. Elastic registration of inspiratory-to-expiratory 3D UTE MRI may be a new morphological and functional marker for non-radiation and noninvasive evaluation of IPF. CRITICAL RELEVANCE STATEMENT: This prospective study demonstrated that lung deformation decreased in idiopathic pulmonary fibrosis (IPF) patients and correlated with the severity of IPF. Elastic registration of inspiratory-to-expiratory three-dimensional ultrashort echo time (3D UTE) MRI may be a new morphological and functional marker for non-radiation and noninvasive evaluation of IPF. KEY POINTS: • Elastic registration of inspiratory-to-expiratory three-dimensional ultrashort echo time (3D UTE) MRI could evaluate lung deformation. • Lung deformation significantly decreased in idiopathic pulmonary fibrosis (IPF) patients, compared with the healthy controls. • Reduced lung deformation of IPF patients correlated with worsened pulmonary function and the composite physiological index (CPI).

A co-located QTL for seven spike architecture-related traits shows promising breeding use potential in common wheat (Triticum aestivum L.).

KEY MESSAGE: A co-located novel QTL for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs with potential of improving wheat yield was identified and validated. Spike-related traits, including fertile florets per spike (FFS), kernel weight per spike (KWS), total florets per spike (TFS), florets per spikelet (FPs), florets in the middle spikelet (FMs), fertile florets per spikelet (FFPs), and kernel weight per spikelet (KWPs), are key traits in improving wheat yield. In the present study, quantitative trait loci (QTL) for these traits evaluated under various environments were detected in a recombinant inbred line population (msf/Chuannong 16) mainly genotyped using the 16 K SNP array. Ultimately, we identified 60 QTL, but only QFFS.sau-MC-1A for FFS was a major and stably expressed QTL. It was located on chromosome arm 1AS, where loci for TFS, FPs, FMs, FFS, FFPs, KWS, and KWPs were also simultaneously co-mapped. The effect of QFFS.sau-MC-1A was further validated in three independent segregating populations using a Kompetitive Allele-Specific PCR marker. For the co-located QTL, QFFS.sau-MC-1A, the presence of a positive allele from msf was associate with increases for all traits: + 12.29% TFS, + 10.15% FPs, + 13.97% FMs, + 17.12% FFS, + 14.75% FFPs, + 22.17% KWS, and + 19.42% KWPs. Furthermore, pleiotropy analysis showed that the positive allele at QFFS.sau-MC-1A simultaneously increased the spike length, spikelet number per spike, and thousand-kernel weight. QFFS.sau-MC-1A represents a novel QTL for marker-assisted selection with the potential for improving wheat yield. Four genes, TraesCS1A03G0012700, TraesCS1A03G0015700, TraesCS1A03G0016000, and TraesCS1A03G0016300, which may affect spike development, were predicted in the physical interval harboring QFFS.sau-MC-1A. Our results will help in further fine mapping QFFS.sau-MC-1A and be useful for improving wheat yield.

Mosaic variegated aneuploidy syndrome with tetraploid, and predisposition to male infertility triggered by mutant CEP192.

In this study, we report on mosaic variegated aneuploidy (MVA) syndrome with tetraploidy and predisposition to infertility in a family. Sequencing analysis identified that the CEP192 biallelic variants (c.1912C>T, p.His638Tyr and c.5750A>G, p.Asn1917Ser) segregated with microcephaly, short stature, limb-extremity dysplasia, and reduced testicular size, while CEP192 monoallelic variants segregated with infertility and/or reduced testicular size in the family. In 1,264 unrelated patients, variant screening for CEP192 identified a same variant (c.5750A>G, p.Asn1917Ser) and other variants significantly associated with infertility. Two lines of Cep192 mice model that are equivalent to human variants were generated. Embryos with Cep192 biallelic variants arrested at E7 because of cell apoptosis mediated by MVA/tetraploidy cell acumination. Mice with heterozygous variants replicated the predisposition to male infertility. Mouse primary embryonic fibroblasts with Cep192 biallelic variants cultured in vitro showed abnormal morphology, mitotic arresting, and disruption of spindle formation. In patient epithelial cells with biallelic variants cultured in vitro, the number of cells arrested during the prophase increased because of the failure of spindle formation. Accordingly, we present mutant CEP192, which is a link for the MVA syndrome with tetraploidy and the predisposition to male infertility.

Shatianyu dietary fiber (Citrus grandis L. Osbeck) promotes the production of active metabolites from its flavonoids during in vitro colonic fermentation.

BACKGROUND: Recent studies reveal that dietary fiber (DF) might play a critical role in the metabolism and bioactivity of flavonoids by regulating gut microbiota. We previously found that Shatianyu (Citrus grandis L. Osbeck) pulp was rich in flavonoids and DF, and Shatianyu pulp flavonoid extracts (SPFEs) were dominated by melitidin, obviously different from other citrus flavonoids dominated by naringin. The effects of Shatianyu pulp DF (SPDF) on the microbial metabolism and bioactivity of SPFEs is unknown. RESULTS: An in vitro colonic fermentation model was used to explore the effects of SPDF on the microbial metabolism and antioxidant activity of SPFEs in the present study. At the beginning of fermentation, SPDF promoted the microbial degradation of SPFEs. After 24 h-fermentation, the supplemented SPFEs were almost all degraded in SPFEs group, and the main metabolites detected were the dehydrogenation, hydroxylation and acetylation products of naringenin, the aglycone of the major SPFEs components. However, when SPFEs fermented with SPDF for 24 h, 60.7% of flavonoid compounds were retained, and SPFEs were mainly transformed to the ring fission metabolites, such as 3-(4-hydroxyphenyl) propionic acid, 3-phenylpropionic acid and 3-(3-hydroxy-phenyl) propionic acid. The fermentation metabolites of SPFEs showed stronger antioxidant activity than the original ones, with a further increase in SPDF supplemented group. Furthermore, SPFEs enriched microbiota participating in the deglycosylation and dehydrogenation of flavonoids, while co-supplementation of SPDF and SPFEs witnessed the bloom of Lactobacillaceae and Lactobacillus, contributing to the deglycosylation and ring fission of flavonoids. CONCLUSION: SDPF promote SPFEs to transform to active metabolites probably by regulating gut microbiota. © 2023 Society of Chemical Industry.

Comparison of cardiovascular metrics on computed tomography pulmonary angiography of the updated and old diagnostic criteria for pulmonary hypertension in patients with chronic thromboembolic pulmonary hypertension.

Background: In the 2022 European Society of Cardiology (ESC) and the European Respiratory Society (ERS) guidelines, the diagnostic criteria for pulmonary hypertension (PH) included a reduced mean pulmonary artery pressure (mPAP) of 20 mmHg (mPAP >20 mmHg). This study aimed to reassess cardiovascular metrics on computed tomography pulmonary angiography (CTPA) for chronic thromboembolic pulmonary hypertension (CTEPH) to optimize the timely diagnosis of patients with suspected PH. Methods: Patients with suspected CTEPH who underwent CTPA and right heart catheterization (RHC) between January 2019 and December 2022 in China-Japan Friendship Hospital were retrospectively included. They were grouped into CTEPH and non-PH groups according to the new and old criteria (2022 and 2015 ESC/ERS guidelines) for the diagnosis of PH. Cardiovascular metrics including the main pulmonary artery diameter (MPAd), Cobb angle, and right ventricular free wall thickness (RVWT), among others, were measured. The correlation of these metrics with hemodynamic data was analyzed with Spearman rank correlation analysis, while the differences in cardiovascular metrics between the updated (mPAP >20 mmHg) and old PH criteria (mPAP ≥25 mmHg) were compared with independent samples t-test or the Mann-Whitney test. Receiver operator characteristic (ROC) curve analysis was performed for the prediction model. Results: The study enrolled 180 patients (males n=86; age 55.5±12.0 years old). According to the old guidelines, 119 patients were placed into the PH group (mPAP ≥25 mmHg) , while according to the new guidelines, 130 patients were placed into the PH group (mPAP >20 mmHg). Cardiovascular metrics on CTPA between the updated and old guidelines were comparable (P>0.05). Compared to other metrics, an MPAd of 30.4 mm exhibited the highest area under the curve (AUC: 0.934±0.021), with a sensitivity of 0.88 and specificity of 0.90. MPAd [odds ratio (OR) =1.271], transverse diameter of the right ventricle (RVtd; OR =1.176), Cobb angle (OR =1.108), and RVWT (OR =3.655) were independent factors for diagnosing CTEPH (P<0.05). Cobb angle, right and left ventricular transverse diameter ratio, and right and left ventricular area ratio moderately correlated with mPAP (r=0.586, r=0.583, r=0.629) and pulmonary vascular resistance (PVR) (r=0.613, r=0.593, r=0.642). Conclusions: Cardiovascular metrics on CTPA were comparable between the new and old guidelines for CTEPH diagnosis. Cardiovascular metrics on CTPA can noninvasively assess the hemodynamics of patients with CTEPH.

Resolving a nearly 90-year-old enigma: The rare Fagus chienii is conspecific with F. hayatae based on molecular and morphological evidence.

Taxonomic uncertainties of rare species often hinder effective prioritization for conservation. One such taxonomic uncertainty is the 90-year-old enigma of Fagus chienii. F. chienii was previously only known from the type specimens collected in 1935 in Pingwu County of Sichuan Province, China, and has long been thought to be on the verge of extinction. However, morphological similarities to closely related Fagus species have led many to question the taxonomic status of F. chienii. To clarify this taxonomic uncertainty, we used the newly collected samples to reconstruct a molecular phylogeny of Chinese Fagus species against the phylogenetic backbone of the whole genus using seven nuclear genes. In addition, we examined nine morphological characters to determine whether F. chienii is morphologically distinct from its putatively closest relatives (F. hayatae, F.longipetiolata, and F.lucida). Both morphological and phylogenetic analyses indicated that F. chienii is conspecific with F. hayatae. We recommended that F. chienii should not be treated as a separate species in conservation management. However, conservation strategies such as in situ protection and ex situ germplasm preservation should be adopted to prevent the peculiar "F. chienii" population from extinction.

A machine learning model for diagnosing acute pulmonary embolism and comparison with Wells score, revised Geneva score, and Years algorithm.

BACKGROUND: Acute pulmonary embolism (APE) is a fatal cardiovascular disease, yet missed diagnosis and misdiagnosis often occur due to non-specific symptoms and signs. A simple, objective technique will help clinicians make a quick and precise diagnosis. In population studies, machine learning (ML) plays a critical role in characterizing cardiovascular risks, predicting outcomes, and identifying biomarkers. This work sought to develop an ML model for helping APE diagnosis and compare it against current clinical probability assessment models. METHODS: This is a single-center retrospective study. Patients with suspected APE were continuously enrolled and randomly divided into two groups including training and testing sets. A total of 8 ML models, including random forest (RF), Naïve Bayes, decision tree, K-nearest neighbors, logistic regression, multi-layer perceptron, support vector machine, and gradient boosting decision tree were developed based on the training set to diagnose APE. Thereafter, the model with the best diagnostic performance was selected and evaluated against the current clinical assessment strategies, including the Wells score, revised Geneva score, and Years algorithm. Eventually, the ML model was internally validated to assess the diagnostic performance using receiver operating characteristic (ROC) analysis. RESULTS: The ML models were constructed using eight clinical features, including D-dimer, cardiac troponin T (cTNT), arterial oxygen saturation, heart rate, chest pain, lower limb pain, hemoptysis, and chronic heart failure. Among eight ML models, the RF model achieved the best performance with the highest area under the curve (AUC) (AUC = 0.774). Compared to the current clinical assessment strategies, the RF model outperformed the Wells score (P = 0.030) and was not inferior to any other clinical probability assessment strategy. The AUC of the RF model for diagnosing APE onset in internal validation set was 0.726. CONCLUSIONS: Based on RF algorithm, a novel prediction model was finally constructed for APE diagnosis. When compared to the current clinical assessment strategies, the RF model achieved better diagnostic efficacy and accuracy. Therefore, the ML algorithm can be a useful tool in assisting with the diagnosis of APE.

Development and validation of a lung graph-based machine learning model to predict acute pulmonary thromboembolism on chest noncontrast computed tomography.

Background: Computed tomography pulmonary angiography (CTPA) is a first-line noninvasive method to diagnose acute pulmonary thromboembolism (APE); however, whether chest noncontrast CT (NC-CT) could aid in the diagnosis of APE remains unknown. The aim of this study was to build and evaluate a holistic lung graph-based machine learning (HLG-ML) using NC-CT for the diagnosis of APE and to compare its performance with that of radiologists and the YEARS algorithm. Methods: This study enrolled 178 cases (77 males; age 63.9±16.7 years) who underwent NC-CT and CTPA in the same day from January 2019 to December 2020. Of these patients, 133 (75% of cases; 58 males; age 65.4±15.6 years) were placed into a training group and 45 (25% of cases; 19 males; age 59.6±19.2 years) into a testing group. The other 43 cases (18 males; age 62.8±20.0 years) were used to externally validate the model between January 2021 and March 2022. A HLG was developed with a pulmonary radiomics descriptor derived from NC-CT images. The approach extracted local radiomics features and encoded these local features into a radiomics descriptor as a characterization of global radiomics feature distribution. Subsequently, 8 ML models were trained and compared based on the radiomics descriptor. In the validation group, area under the curves (AUCs) of the HLG-ML model in the diagnosis of APE were compared with those of the 3 radiologists and the YEARS algorithm. Results: Among the 8 ML models, gradient boosting decision tree demonstrated the best classification performance (AUC =0.772) on the training set. In the testing set, the AUC of gradient boosting decision trees was 0.857 [95% confidence intervals (CIs): 0.699-0.951]. In the validation set, the performance of gradient boosting decision tree (AUC =0.810; 95% CI: 0.669-0.952; Youden index =0.621) outperformed 3 radiologists (AUC =0.508, 95% CI: 0.335-0.681, Youden index =0.016; AUC =0.504, 95% CI: 0.354-0.654, Youden index =0.008; AUC =0.527, 95% CI: 0.363-0.691, Youden index =0.050) and the YEARS algorithm (AUC =0.618; 95% CI: 0.469-0.767; Youden index =0.237). Conclusions: Compared to all 3 radiologists and the YEARS algorithm, the proposed HLG-based gradient boosting decision tree model achieved a superior performance in the diagnosis of APE on the NC-CT and may thus serve as a valuable tool for physicians in the diagnosis of APE.

Cardiovascular metrics on CT pulmonary angiography in patients with pulmonary hypertension - re-evaluation under the updated guidelines of pulmonary hypertension.

PURPOSE: To re-assess cardiovascular metrics on computed tomography pulmonary angiography (CTPA) in predicting pulmonary hypertension (PH) under the 2022 ESC/ERS guidelines. MATERIALS AND METHODS: This observational study retrospectively included 272 patients (female 143, mean age = 54.9 ± 12.5 years old) with suspected PH. 218 patients were grouped to evaluate cardiovascular metrics on CTPA and develop a binary logistic regression model. The other 54 patients were grouped into the validation group to assess the performance of the prediction model under the updated criteria. Based on mean pulmonary artery pressure (mPAP), patients were divided into three groups: group A consisted of patients with mPAP ≤ 20 mmHg, group B included patients with 20 mmHg < mPAP < 25 mmHg, and group C comprised patients with mPAP ≥ 25 mmHg. Cardiovascular metrics among the three groups were compared, and receiver operating characteristic curves (ROCs) were used to evaluate the performance of cardiovascular metrics in predicting mPAP > 20 mmHg. RESULTS: The main pulmonary arterial diameter (MPAd), MPAd/ascending aorta diameter ratio (MPAd/AAd ratio), and right ventricular free wall thickness (RVFWT) showed significant differences among the three groups (p < 0.05). The area under curve (AUC) of MPAd was larger than MPAd/AAd ratio and RVFWT. A MPAd cutoff value of 30.0 mm has a sensitivity of 83.1% and a specificity of 90.4%. The AUC of the binary logistic regression model (Z = - 12.98187 + 0.31053 MPAd + 1.04863 RVFWT) was 0.938 ± 0.018. In the validation group, the AUC, sensitivity, specificity, and accuracy of the prediction model were 0.878, 92.7%, 76.9%, and 88.9%, respectively. CONCLUSION: Under the updated criteria, MPAd with a threshold value of 30.0 mm has better sensitivity and specificity in predicting PH. The binary logistic regression model may improve the diagnostic accuracy. CRITICAL RELEVANCE STATEMENT: Under the updated criteria, the main pulmonary arterial diameter with a threshold value of 30.0 mm has better sensitivity and specificity in predicting pulmonary hypertension. The binary logistic regression model may improve diagnostic accuracy. KEY POINTS: • According to 2022 ESC/ERS guidelines, a MPAd cutoff value of 30.0 mm has better sensitivity and specificity in predicting mPAP > 20 mmHg • A binary logistic regression model (Z = - 12.98187 + 0.31053 MPAd + 1.04863 RVFWT) was developed and had a sensitivity, specificity, and accuracy of 92.7%, 76.9%, and 88.9% in predicting mPAP > 20 mmHg. • A binary logistic regression prediction model outperforms MPAd in predicting mPAP > 20 mmHg.

Lychee Pulp-Derived Dietary Fiber-Bound Phenolic Complex Upregulates the SCFAs-GPRs-ENS Pathway and Aquaporins in Loperamide-Induced Constipated Mice by Reshaping Gut Microbiome.

This study aimed to investigate the effects of the lychee pulp-derived dietary fiber-bound phenolic complex (DF-BPC) on a murine model of loperamide-induced constipation and its molecular mechanism associated with gut microbiota modification. DF-BPC supplementation mitigated loperamide-induced dyschezia, intestinal hypomotility, and colonic impairment, as evidenced by the increased gastro-intestinal transit rate and mucus cell counts. By comparison, short-chain fatty acids (SCFAs) contents and relative abundances of associated genera (Butyricimonas, Clostridium, and Lactobacillus) were effectively upregulated following DF-BPC supplementation. Notably, DF-BPC significantly enhanced expressions of G protein-coupled receptor (GPR) 41 and 43, reaching 1.43- and 1.62-fold increase, respectively. Neurotransmitter secretions were simultaneously altered in DF-BPC-treated mice, suggesting upregulation of the SCFAs-GPRs-enteric nervous system pathway. The overexpression of aquaporins (AQP3, 8, and 9) was stimulated partly through GPRs activation. Mild inflammation associated with constipation was inhibited by suppressing LBP-TLR4-NF-κB signaling translocation. These findings suggest that DF-BPC from lychee pulp has the potential to alleviate constipation in mice through modifying the gut microbiome.

A major QTL simultaneously increases the number of spikelets per spike and thousand-kernel weight in a wheat line.

KEY MESSAGE: A novel and stably expressed QTL QSNS.sicau-SSY-7A for spikelet number per spike in wheat without negative effects on thousand-kernel weight was identified and validated in different genetic backgrounds. Spikelet number per spike (SNS) is an important determinant of yield in wheat. In the present study, we combined bulked segregant analysis (BSA) and the wheat 660 K single-nucleotide polymorphism (SNP) array to rapidly identify genomic regions associated with SNS from a recombinant inbred line (RIL) population derived from a cross between the wheat lines S849-8 and SY95-71. A genetic map was constructed using Kompetitive Allele Specific PCR markers in the SNP-enriched region on the long arm of chromosome 7A. A major and stably expressed QTL, QSNS.sicau-SSY-7A, was detected in multiple environments. It was located in a 1.6 cM interval on chromosome arm 7AL flanked by the markers AX-109983514 and AX-109820548. This QTL explained 6.86-15.72% of the phenotypic variance, with LOD values ranging from 3.66 to 8.66. Several genes associated with plant growth and development were identified in the interval where QSNS.sicau-SSY-7A was located on the 'Chinese Spring' wheat and wild emmer reference genomes. Furthermore, the effects of QSNS.sicau-SSY-7A and WHEAT ORTHOLOG OFAPO1(WAPO1) on SNS were analyzed. Interestingly, QSNS.sicau-SSY-7A significantly increased SNS without negative effects on thousand-kernel weight, anthesis date and plant height, demonstrating its great potential for breeding aimed at improving grain yield. Taken together, these results indicate that QSNS.sicau-SSY-7A is a promising locus for yield improvement, and its linkage markers are helpful for fine mapping and molecular breeding.