Multiparameter MRI-based radiomics nomogram for preoperative prediction of brain invasion in atypical meningioma:a multicentre study.

OBJECTIVE: To develop a nomogram based on tumor and peritumoral edema (PE) radiomics features extracted from preoperative multiparameter MRI for predicting brain invasion (BI) in atypical meningioma (AM). METHODS: In this retrospective study, according to the 2021 WHO classification criteria, a total of 469 patients with pathologically confirmed AM from three medical centres were enrolled and divided into training (n = 273), internal validation (n = 117) and external validation (n = 79) cohorts. BI was diagnosed based on the histopathological examination. Preoperative contrast-enhanced T1-weighted MR images (T1C) and T2-weighted MR images (T2) for extracting meningioma features and T2-fluid attenuated inversion recovery (FLAIR) sequences for extracting meningioma and PE features were obtained. The multiple logistic regression was applied to develop separate multiparameter radiomics models for comparison. A nomogram was developed by combining radiomics features and clinical risk factors, and the clinical usefulness of the nomogram was verified using decision curve analysis. RESULTS: Among the clinical factors, PE volume and PE/tumor volume ratio are the risk of BI in AM. The combined nomogram based on multiparameter MRI radiomics features of meningioma and PE and clinical indicators achieved the best performance in predicting BI in AM, with area under the curve values of 0.862 (95% CI, 0.819-0.905) in the training cohort, 0.834 (95% CI, 0.780-0.908) in the internal validation cohort and 0.867 (95% CI, 0.785-0.950) in the external validation cohort, respectively. CONCLUSIONS: The nomogram based on tumor and PE radiomics features extracted from preoperative multiparameter MRI and clinical factors can predict the risk of BI in patients with AM.

Comparison of Different Fusion Radiomics for Predicting Benign and Malignant Sacral Tumors: A Pilot Study.

Differentiating between benign and malignant sacral tumors is crucial for determining appropriate treatment options. This study aims to develop two benchmark fusion models and a deep learning radiomic nomogram (DLRN) capable of distinguishing between benign and malignant sacral tumors using multiple imaging modalities. We reviewed axial T2-weighted imaging (T2WI) and non-contrast computed tomography (NCCT) of 134 patients pathologically confirmed as sacral tumors. The two benchmark fusion models were developed using fusion deep learning (DL) features and fusion classical machine learning (CML) features from multiple imaging modalities, employing logistic regression, K-nearest neighbor classification, and extremely randomized trees. The two benchmark models exhibiting the most robust predictive performance were merged with clinical data to formulate the DLRN. Performance assessment involved computing the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, negative predictive value (NPV), and positive predictive value (PPV). The DL benchmark fusion model demonstrated superior performance compared to the CML fusion model. The DLRN, identified as the optimal model, exhibited the highest predictive performance, achieving an accuracy of 0.889 and an AUC of 0.961 in the test sets. Calibration curves were utilized to evaluate the predictive capability of the models, and decision curve analysis (DCA) was conducted to assess the clinical net benefit of the DLR model. The DLRN could serve as a practical predictive tool, capable of distinguishing between benign and malignant sacral tumors, offering valuable information for risk counseling, and aiding in clinical treatment decisions.

Selective venous sampling for secondary hypertension.

Selective venous sampling (SVS), an invasive radiographic procedure that depends on contrast media, holds a unique role in diagnosing and guiding the treatment of certain types of secondary hypertension, particularly in patients who may be candidates for curative surgery. The adrenal venous sampling (AVS), in particular, is established as the gold standard for localizing and subtyping primary aldosteronism (PA). Throughout decades of clinical practice, AVS could be applied not only to PA but also to other endocrine diseases, such as adrenal Cushing syndrome (ACS) and Pheochromocytomas (PCCs). Notably, the application of AVS in ACS and PCCs remains less recognized compared to PA, with the low success rate of catheterization, the controversy of results interpretation, and the absence of a standardized protocol. Additionally, the AVS procedure necessitates enhancements to boost its success rate, with several helpful but imperfect methods emerging, yet continued exploration remains essential. We also observed renal venous sampling (RVS), an operation akin to AVS in principle, serves as an effective means of diagnosing renin-dependent hypertension, aiding in the identification of precise sources of renin excess and helping the selection of surgical candidates with renin angiotensin aldosterone system (RAAS) abnormal activation. Nonetheless, further basic and clinical research is needed. Selective venous sampling (SVS) can be used in identifying cases of secondary hypertension that are curable by surgical intervention. Adrenal venous sampling (AVS) and aldosterone measurement for classificatory diagnosis of primary aldosteronism (PA) are established worldwide. While its primary application is for PA, AVS also holds the potential for diagnosing other endocrine disorders, including adrenal Cushing's syndrome (ACS) and pheochromocytomas (PCCs) through the measurements of cortisol and catecholamine respectively. In addition, renal venous sampling and renin measurement can help to diagnose renovascular hypertension and reninoma.

Design and construction of chemical-biological module clusters for degradation and assimilation of poly(ethylene terephthalate) waste.

The rising accumulation of poly(ethylene terephthalate) (PET) waste presents an urgent ecological challenge, necessitating an efficient and economical treatment technology. Here, we developed chemical-biological module clusters that perform chemical pretreatment, enzymatic degradation, and microbial assimilation for the large-scale treatment of PET waste. This module cluster included (i) a chemical pretreatment that involves incorporating polycaprolactone (PCL) at a weight ratio of 2% (PET:PCL = 98:2) into PET via mechanical blending, which effectively reduces the crystallinity and enhances degradation; (ii) enzymatic degradation using Thermobifida fusca cutinase variant (4Mz), that achieves complete degradation of pretreated PET at 300 g/L PET, with an enzymatic loading of 1 mg protein per gram of PET; and (iii) microbial assimilation, where Rhodococcus jostii RHA1 metabolizes the degradation products, assimilating each monomer at a rate above 90%. A comparative life cycle assessment demonstrated that the carbon emissions from our module clusters (0.25 kg CO2-eq/kg PET) are lower than those from other established approaches. This study pioneers a closed-loop system that seamlessly incorporates pretreatment, degradation, and assimilation processes, thus mitigating the environmental impacts of PET waste and propelling the development of a circular PET economy.

A Novel Network Pharmacology Strategy Based on the Universal Effectiveness-Common Mechanism of Medical Herbs Uncovers Therapeutic Targets in Traumatic Brain Injury.

Purpose: Many herbs can promote neurological recovery following traumatic brain injury (TBI). There must lie a shared mechanism behind the common effectiveness. We aimed to explore the key therapeutic targets for TBI based on the common effectiveness of the medicinal plants. Material and methods: The TBI-effective herbs were retrieved from the literature as imputes of network pharmacology. Then, the active ingredients in at least two herbs were screened out as common components. The hub targets of all active compounds were identified through Cytohubba. Next, AutoDock vina was used to rank the common compound-hub target interactions by molecular docking. A highly scored compound-target pair was selected for in vivo validation. Results: We enrolled sixteen TBI-effective medicinal herbs and screened out twenty-one common compounds, such as luteolin. Ten hub targets were recognized according to the topology of the protein-protein interaction network of targets, including epidermal growth factor receptor (EGFR). Molecular docking analysis suggested that luteolin could bind strongly to the active pocket of EGFR. Administration of luteolin or the selective EGFR inhibitor AZD3759 to TBI mice promoted the recovery of body weight and neurological function, reduced astrocyte activation and EGFR expression, decreased chondroitin sulfate proteoglycans deposition, and upregulated GAP43 levels in the cortex. The effects were similar to those when treated with the selective EGFR inhibitor. Conclusion: The common effectiveness-based, common target screening strategy suggests that inhibition of EGFR can be an effective therapy for TBI. This strategy can be applied to discover core targets and therapeutic compounds in other diseases.

Radiomics for predicting MGMT status in cerebral glioblastoma: comparison of different MRI sequences.

Using radiomics to predict O6-methylguanine-DNA methyltransferase promoter methylation status in patients with newly diagnosed glioblastoma and compare the performances of different MRI sequences. Preoperative MRI scans from 215 patients were included in this retrospective study. After image preprocessing and feature extraction, two kinds of machine-learning models were established and compared for their performances. One kind was established using all MRI sequences (T1-weighted image, T2-weighted image, contrast enhancement, fluid-attenuated inversion recovery, DWI_b_high, DWI_b_low and apparent diffusion coefficient), and the other kind was based on single MRI sequence as listed above. For the machine-learning model based on all sequences, a total of seven radiomic features were selected with the Maximum Relevance and Minimum Redundancy algorithm. The predictive accuracy was 0.993 and 0.750 in the training and validation sets, respectively, and the area under curves were 1.000 and 0.754 in the two sets, respectively. For the machine-learning model based on single sequence, the numbers of selected features were 8, 10, 10, 13, 9, 7 and 6 for T1-weighted image, T2-weighted image, contrast enhancement, fluid-attenuated inversion recovery, DWI_b_high, DWI_b_low and apparent diffusion coefficient, respectively, with predictive accuracies of 0.797-1.000 and 0.583-0.694 in the training and validation sets, respectively, and the area under curves of 0.874-1.000 and 0.538-0.697 in the two sets, respectively. Specifically, T1-weighted image-based model performed best, while contrast enhancement-based model performed worst in the independent validation set. The machine-learning models based on seven different single MRI sequences performed differently in predicting O6-methylguanine-DNA methyltransferase status in glioblastoma, while the machine-learning model based on the combination of all sequences performed best.

Single-incision plus one-port laparoscopy surgery versus conventional multi-port laparoscopy surgery for colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: The efficacy of single-incision plus one-port laparoscopic surgery (SILS + 1) versus conventional laparoscopic surgery (CLS) for colorectal cancer treatment remains unclear. This study compares the short-term and long-term outcomes of SILS + 1 and CLS using a high-quality systematic review and meta-analysis. METHOD: Literature search followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, drawing from PubMed, Embase, Web of Science, and the Cochrane Library until December 10, 2023. Statistical analysis was conducted using RevMan and Stata. RESULT: The review and meta-analysis included seven studies with 1740 colorectal cancer patients. Compared to CLS, SILS + 1 showed significant improvements in operation time (WMD = - 18.33, P < 0.00001), blood loss (WMD = - 21.31, P < 0.00001), incision length (WMD = - 2.07, P < 0.00001), time to first defecation (WMD = - 14.91, P = 0.009), time to oral intake (WMD = - 11.46, P = 0.04), and time to ambulation (WMD = - 11.52, P = 0.01). There were no significant differences in lymph node harvest, resection margins, complications, anastomotic leakage, hospital stay, disease-free survival, overall survival, and postoperative recurrence. CONCLUSIONS: Compared to CLS, SILS + 1 demonstrates superiority in shortening the surgical incision and promoting postoperative recovery. SILS + 1 can provide a safe and feasible alternative to CLS.

Ginseng fermentation solution affects the gut microbiota in zebrafish with alcoholic liver disease via PI3K/Akt pathway.

BACKGROUND: Ginsenosides have received increased amounts of attention due to their ability to modulate the intestinal flora, which may subsequently alleviate alcoholic liver disease (ALD). The effects of ginseng fermentation solution (GFS) on the gut microbiota and metabolism in ALD patients have not been explored. PURPOSE: This research aimed to explore the regulatory effect of GFS on ALD both in vitro and in vivo. METHOD: This study assessed the anti-ALD efficacy of GFS using an LO2 cell model and a zebrafish model. Untargeted metabolomics was used for differentially abundant metabolite analysis, and high-throughput 16S rRNA sequencing was used to examine the effect of GFS on ALD. RESULTS: The LO2 cell line experiments demonstrated that GFS effectively mitigated alcohol-induced oxidative stress and reduced apoptosis by upregulating PI3K and Bcl-2 expression and decreasing the levels of malondialdehyde, total cholesterol, and triglycerides. In zebrafish, GFS improved morphological and physiological parameters and diminished oxidative stress-induced ALD. Meanwhile, the results from Western blotting indicated that GFS enhanced the expression of PI3K, Akt, and Bcl-2 proteins while reducing Bax protein expression, thereby ameliorating the ALD model in zebrafish. Metabolomics data revealed significant changes in a total of 46 potential biomarkers. Among them, metabolites such as prostaglandin F2 alpha belong to arachidonic acid metabolism. In addition, GFS also partly reversed the imbalance of gut microbiota composition caused by alcohol. At the genus level, alcohol consumption elevated the presence of Flectobacillus, Curvibacter, among others, and diminished Elizabethkingia within the intestinal microbes of zebrafish. Conversely, GFS reversed these effects, notably enhancing the abundance of Proteobacteria and Archaea. Correlation analyses further indicated a significant negative correlation between prostaglandin F2 alpha, 11,14,15-THETA, Taurocholic acid and Curvibacter. CONCLUSION: This study highlights a novel mechanism by which GFS modulates anti-ALD activity through the PI3K/Akt signalling pathway by influencing the intestinal flora-metabolite axis. These results indicate the potential of GFS as a functional food for ALD treatment via modulation of the gut flora.

Thrombin receptor activating peptide-6 decreases acute graft-versus-host disease through activating GPR15.

G-protein coupled receptor 15 (GPR15) is expressed on T-cells. We previously reported knockout of GPR15 increased acute graft-versus-host disease (GvHD) in mice. In this study, we identified thrombin receptor activating peptide-6 (TRAP-6, peptide sequence: SFLLRN) as an activator of GPR15. GRP15 and ß-arrestin2 were needed for TRAP-6-mediated inhibition of mixed lymphocyte reactions. TRAP-6 decreased acute GvHD in allotransplant models in mice, an effect dependent on GPR15-expression in donor T-cells. RNA-seq and protein analyses indicated TRAP-6 increased binding of ß-arrestin2/TAB1 and inhibited phosphorylation of TAK1 and NF-κB-P65. GPR15 is expressed differently on CD4+ T-cells and CD8+ T-cells. TRAP-6 inhibited phosphorylation of NF-κB-P65 in CD4+ T-cells but increased granzyme B expression in CD8+ T-cells. TRAP-6 decreased acute GvHD without inhibiting graft-versus-tumor (GvT) efficacy against A20 lymphoma cells. SALLRN, a mutant of TRAP-6, preserved the anti-acute GvHD effect but avoided the adverse effects of TRAP-6. TRAP-6 and SALLRN also decreased allogeneic and xenogeneic reactions induced by human blood mononuclear cells. In conclusion, TRAP-6 activated GPR15 on T-cells and decreased acute GvHD in mice without impairing GvT efficacy.

MRI-Based Machine Learning Fusion Models to Distinguish Encephalitis and Gliomas.

This paper aims to compare the performance of the classical machine learning (CML) model and the deep learning (DL) model, and to assess the effectiveness of utilizing fusion radiomics from both CML and DL in distinguishing encephalitis from glioma in atypical cases. We analysed the axial FLAIR images of preoperative MRI in 116 patients pathologically confirmed as gliomas and clinically diagnosed with encephalitis. The 3 CML models (logistic regression (LR), support vector machine (SVM) and multi-layer perceptron (MLP)), 3 DL models (DenseNet 121, ResNet 50 and ResNet 18) and a deep learning radiomic (DLR) model were established, respectively. The area under the receiver operating curve (AUC) and sensitivity, specificity, accuracy, negative predictive value (NPV) and positive predictive value (PPV) were calculated for the training and validation sets. In addition, a deep learning radiomic nomogram (DLRN) and a web calculator were designed as a tool to aid clinical decision-making. The best DL model (ResNet50) consistently outperformed the best CML model (LR). The DLR model had the best predictive performance, with AUC, sensitivity, specificity, accuracy, NPV and PPV of 0.879, 0.929, 0.800, 0.875, 0.867 and 0.889 in the validation sets, respectively. Calibration curve of DLR model shows good agreement between prediction and observation, and the decision curve analysis (DCA) indicated that the DLR model had higher overall net benefit than the other two models (ResNet50 and LR). Meanwhile, the DLRN and web calculator can provide dynamic assessments. Machine learning (ML) models have the potential to non-invasively differentiate between encephalitis and glioma in atypical cases. Furthermore, combining DL and CML techniques could enhance the performance of the ML models.

Chronic cadmium exposure impairs flight behavior by dampening flight muscle carbon metabolism in bumblebees.

Cadmium pollution affects the global ecosystem because cadmium can be transferred up the food chain. The bumblebee, Bombus terrestris, is an important insect pollinator. Their foraging activity on flowers exposes them to harmful heavy metals, which damages their health and leads to massive population declines. However, the effects of chronic exposure to heavy metals on the flight performance of bumblebees have not yet been characterized. Here, we studied variation in the flight capacity of bumblebees induced by chronic cadmium exposure at field-realistic concentrations using behavioral, physiological, and molecular approaches. Chronic cadmium exposure caused a significant reduction in the duration, distance, and mean velocity of bumblebee flight. Transcriptome analysis showed that the impairment of carbon metabolism and mitochondrial dysfunction in the flight muscle were the primary causes. Physiological, biochemical, and metabolomic analyses validated disruptions in energy metabolism, and impairments in mitochondrial respiratory chain complexes activities. Histological analysis revealed muscle fiber damage and mitochondrial loss. Exogenous decanoic acid or citric acid partially restored sustained flight ability of bumblebees by mitigating muscle fiber damage and increasing energy generation. These findings provide insights into how long-term cadmium stress affects the flight ability of insects and will aid human muscle or exercise-related disease research.

Regulation of ULK1 by WTAP/IGF2BP3 axis enhances mitophagy and progression in epithelial ovarian cancer.

There is a pressing need for innovative therapeutic strategies for patients with epithelial ovarian cancer (EOC). Previous studies have shown that UNC-51-like kinase 1 (ULK1), a serine/threonine kinase, is crucial in regulating cellular autophagy and mitophagy across various tumor types. However, the clinical implications, biological functions, and potential mechanisms of ULK1 in EOC remain poorly understood. This study demonstrates that ULK1 expression is upregulated in EOC tissue samples and EOC cell lines, with increased ULK1 expression correlating with poor prognosis. Functionally, overexpressed ULK1 enhances the proliferation and migration abilities of EOC cells both in vitro and in vivo. Mechanistically, ULK1 was identified as an m6A target of WTAP. WTAP-mediated m6A modification of ULK1 enhanced its mRNA stability in an IGF2BP3-dependent manner, leading to elevated ULK1 expression and enhanced mitophagy in EOC. In summary, our research reveals that the WTAP/IGF2BP3-ULK1 axis significantly influences protective mitophagy in EOC, contributing to its progression. Therefore, the regulatory mechanisms and biological function of ULK1 identify it as a potential molecular target for therapeutic intervention in EOC.

Photo-Induced Disproportionation-Mediated Photodynamic Therapy: Simultaneous Oxidation of Tetrahydrobiopterin and Generation of Superoxide Radicals.

We herein present an approach of photo-induced disproportionation for preparation of Type-I photodynamic agents. As a proof of concept, BODIPY-based photosensitizers were rationally designed and prepared. The photo-induced intermolecular electron transfer between homotypic chromophores leads to the disproportionation reaction, resulting in the formation of charged intermediates, cationic and anionic radicals. The cationic radicals efficiently oxidize the cellularimportant coenzyme, tetrahydrobiopterin (BH4 ), and the anionic radicals transfer electrons to oxygen to produce superoxide radicals (O2 - ⋅). One of our Type-I photodynamic agents not only self-assembles in water but also effectively targets the endoplasmic reticulum. It displayed excellent photocytotoxicity even in highly hypoxic environments (2 % O2 ), with a half-maximal inhibitory concentration (IC50 ) of 0.96 µM, and demonstrated outstanding antitumor efficacy in murine models bearing HeLa tumors.

Carp scales derived double cross-linking hydrogels achieve collagen peptides sustained-released for bone regeneration.

Collagen peptide exhibits a great activity in osteogenic differentiation and wound healing. However, uncontrolled collagen peptide release in bone defects leads to unsatisfactory bone regeneration. In this work, we prepared collagen peptide loaded calcium alginate hydrogel (SA-CP/Ca) derived from Asia carp scales by mixing sodium alginate solution, collagen peptides, calcium carbonate, covalent cross-linking agents N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC), and N-hydroxysuccinimide (NHS) in one pot. Physically and chemically double cross-linking realized higher crosslink density, smaller porosity and pore size, and higher energy storage modulus and loss modulus, achieving sustained release of collagen peptides. The release profile is fitted to Keppas-Sahlin model, to find SA-CP/Ca hydrogels are more inclined to release collagen peptides through expansion and degradation. The compatibility and osteogenic ability of SA-CP/Ca are demonstrated in vitro and in vivo.

Moderate replacement of fish oil with palmitic acid-stimulated mitochondrial fusion promotes ß-oxidation by Mfn2 interacting with Cpt1α via its GTPase-domain.

The mitochondrial matrix serves as the principal locale for the process of fatty acids (FAs) ß-oxidation. Preserving the integrity and homeostasis of mitochondria, which is accomplished through ongoing fusion and fission events, is of paramount importance for the effective execution of FAs ß-oxidation. There has been no investigation to date into whether and how mitochondrial fusion directly enhances FAs ß-oxidation. The underlying mechanism of a balanced FAs ratio favoring hepatic lipid homeostasis remains largely unclear. To address such gaps, the present study was conducted to investigate the mechanism through which a balanced dietary FAs ratio enhances hepatic FAs ß-oxidation. The investigation specifically focused on the involvement of Mfn2-mediated mitochondrial fusion in the regulation of Cpt1α in this process. In the present study, the yellow catfish (Pelteobagrus fulvidraco), recognized as a model organism for lipid metabolism, were subjected to eight weeks of in vivo feeding with six distinct diets featuring varying FAs ratios. Additionally, in vitro experiments were conducted to inhibit Mfn2-mediated mitochondrial fusion in isolated hepatocytes, achieved through the transfection of hepatocytes with si-mfn2. Further, deletion mutants for both Mfn2 and Cpt1α were constructed to elucidate the critical regions responsible for the interactions between these two proteins within the system. The key findings were: (1) Substituting palmitic acid (PA) for fish oil (FO) proved to be enhanced in reducing hepatic lipid accumulation. This beneficial effect was primarily attributed to the activation of mitochondrial FAs ß-oxidation; (2) The balanced replacement of PA stimulated Mfn2-mediated mitochondrial fusion by diminishing Mfn2 ubiquitination, thereby enhancing its protein retention within the mitochondria; (3) Mfn2-mediated mitochondrial fusion promoted FAs ß-oxidation through direct interaction between Mfn2 and Cpt1α via its GTPase-domains, which is essential for the maintenance of Cpt1 activity. Notably, the present research results unveil a previously undisclosed mechanism wherein Mfn2-mediated mitochondrial fusion promotes FAs ß-oxidation by directly augmenting the capacity for FA transport into mitochondria (MT), in addition to expanding the mitochondrial matrix. This underscores the pivotal role of mitochondrial fusion in preserving hepatic lipid homeostasis. The present results further confirm that these mechanisms are evolutionarily conserved, extending their relevance from fish to mammals.

Prognostic value of Hematoxylin and eosin staining tumor-infiltrating lymphocytes (H&E-TILs) in patients with esophageal squamous cell carcinoma treated with chemoradiotherapy.

BACKGROUND: Tumor-infiltrating lymphocytes (TILs) by routine hematoxylin and eosin staining (H&E-TILs) are a robust prognostic biomarker in various cancers. However, the role of H&E-TILs in esophageal squamous cell carcinoma (ESCC) treated with concurrent chemoradiotherapy (CCRT) has not been reported. The purpose of this study was to assess the prognostic value of H&E-TILs in ESCC treated with CCRT. METHODS: The clinical data of 160 patients with ESCC treated with CCRT in our center between Jan. 2014 and Dec. 2021 were collected and retrospectively reviewed, and propensity score matching (PSM) analyses were performed. The H&E-TILs sections before CCRT were reassessed by two experienced pathologists independently. The H&E-TILs sections were classified into a positive group (+, > 10%) and a negative group (-, ≤ 10%) using 10% as the cutoff. The effects of H&E-TILs on overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS), and locoregional recurrence-free survival (LRFS) were explored using the Kaplan‒Meier method, and the log-rank test was used to test the differences. Multivariable analysis was performed using the Cox proportion hazards model. RESULTS: The short-term response to CCRT and the OS (P < 0.001), DMFS (P = 0.001), and LRFS (P < 0.001) rates were significantly different between the H&E-TILs (+) and H&E-TILs (-) groups. Subgroup analysis showed that H&E-TILs(+) with CR + PR group had a longer survival than H&E-TILs(-) with CR + PR, H&E-TILs(+) with SD + PD and H&E-TILs(-) with SD + PD group, respectively(P < 0.001). Furthermore, based on TCGA data, patients in the high TILs group had a better prognosis than those in the low TILs group. Multivariate analyses indicated that H&E-TILs and the short-term response to CCRT were the only two independent factors affecting OS, PFS, DMFS, and LRFS simultaneously, and H&E-TILs expression was associated with an even better prognosis for those patients with CR + PR. CONCLUSIONS: H&E-TILs may be an effective and beneficial prognostic biomarker for ESCC patients treated with CCRT. Patients with H&E-TILs (+) with PR + CR would achieve excellent survival. Further prospective studies are required to validate the conclusions.

Fusion Radiomics-Based Prediction of Response to Neoadjuvant Chemotherapy for Osteosarcoma.

RATIONALE AND OBJECTIVES: Neoadjuvant chemotherapy (NAC) is the most crucial prognostic factor for osteosarcoma (OS), it significantly prolongs progression-free survival and improves the quality of life. This study aims to develop a deep learning radiomics (DLR) model to accurately predict the response to NAC in patients diagnosed with OS using preoperative MR images. METHODS: We reviewed axial T2-weighted imaging (T2WI) and contrast-enhanced T1-weighted (T1CE) of 106 patients pathologically confirmed as OS. First, the Auto3DSeg framework was utilized for automated OS segmentation. Second, using three feature extraction methods, nine risk classification models were constructed based on three classifiers. The area under the receiver operating curve (AUC), sensitivity, specificity, accuracy, negative predictive value and positive predictive value were calculated for performance evaluation. Additionally, we developed a deep learning radiomics nomogram with clinical indicators. RESULTS: The model for OS automatic segmentation achieved a Dice coefficient of 0.868 across datasets. To predict the response to NAC, the DLR model achieved the highest prediction performance with an accuracy of 93.8% and an AUC of 0.961 in the test sets. We used calibration curves to assess the predictive ability of the models and performed decision curve analysis to evaluate the clinical net benefit of the DLR model. CONCLUSION: The DLR model can serve as a pragmatic prediction tool, capable of identifying patients with poor response to NAC, providing information for risk counseling, and assisting in making clinical treatment decisions. Poor responders are better advised to undergo immunotherapy and receive the best supportive care.

Clinical characteristics of tracheobronchial Talaromyces marneffei infection in non-HIV-infected patients in South China.

OBJECTIVES: Tracheobronchial Talaromyces marneffei (T. marneffei) infections among non-HIV-infected patients are rare. To improve understanding, we analysed the clinical features, immune mechanisms, treatment, and prognosis. METHODS: Data on hospitalized patients with tracheobronchial T. marneffei infections from September 2013 to May 2022 were collected. The clinical and imaging features were analysed. RESULTS: Nineteen patients were enrolled, with a median age of 52 years (45-62 years). The most common symptoms were cough, expectoration, fever, weight loss, and anaemia. The total white blood cell and neutrophil counts, erythrocyte sedimentation rate, C-reactive protein, procalcitonin and globulin were increased, and the serum albumin levels were decreased. Chest CT manifestations included patchy shadows, masses, obstructive atelectasis, cavities, pleural effusion, and hilar and mediastinal lymphadenopathy. The fibreoptic bronchoscopy findings included masses, polyps or nodules with mucosal oedema, hypertrophic bulges, lumen stenosis or obstruction, and purulent secretions. T. marneffei infection was confirmed in 10 patients by positive culture, in five by both culture and metagenomic next-generation sequencing (mNGS), in two by mNGS, in one by culture and pathology and in 1 by histopathology. BALF (15/19, 78.9%) had the highest culture positive rate, followed by sputum (3/19), bronchial mucosa (1/1), lung biopsy (1/2); 36.8% of the patients were coinfected with other pathogens. For induction therapy, 7, 6, 2, and 4 patients received voriconazole, amphotericin B, voriconazole combined with amphotericin B, and fluconazole therapy, respectively, and 26.3% received treatment combined with nebulization and/or administration of amphotericin B under fibreoptic bronchoscopy. Four patients were treated for underlying diseases or coinfection, 31.6% were cured, 42.1% improved, and 26.3% died. CONCLUSIONS: T. marneffei infection is common in the tracheobronchial airway tissue or secretions, and bronchoscopy has important diagnostic and treatment value. Antifungal therapy, including systemic therapy, involves triazoles and amphotericin administration, and aerosol inhalation and administration of amphotericin B under bronchoscopy are important.

T. marneffei infection involving the tracheobronchial region in airway tissue or secretions is high, and bronchoscopy has important value in diagnosing and treating these patientsThe use of triazoles and amphotericin and the aerosol inhalation and instillation of amphotericin B under bronchoscopy are essential to antifungal therapy.

Effects of ginseng on short-chain fatty acids and intestinal microbiota in rats with spleen-qi deficiency based on gas chromatography-mass spectrometry and 16s rRNA technology.

RATIONALE: Spleen-qi deficiency syndrome, a common weakness syndrome in traditional Chinese medicine, results from insufficient spleen-qi levels. For centuries, ginseng has been relied upon as a traditional Chinese medicine to treat spleen-qi deficiency syndrome. Until now, the mechanism feature of ginseng in treating temper deficiency through intestinal bacteria and short-chain fatty acid (SCFA) metabolites has not been fully elucidated. METHODS: This study established a rat model of spleen-qi deficiency via multi-factor compound modeling that involved fatigue injury and a controlled diet. The content of SCFAs between different treatment groups was determined by gas chromatography-mass spectrometry. And the 16s rRNA sequencing technology was applied to reveal the effects of ginseng on the intestinal microecological environment of the rats. RESULTS: It was found that the ginseng treatment group exhibited the most remarkable regulatory effect on propionic acid, surpassing all other administration groups. Ginseng increased the relative abundance of beneficial bacteria and decreased that of harmful bacteria at the genus level in rats with spleen-qi deficiency syndrome. And propionic acid is significantly positively correlated with Lactobacillus level and significantly negatively correlated with uncultured_bacterium_f_Muribaculaceae (p < 0.05). n-Butyric acid is negatively correlated with the Faecalibaculum level (p < 0.01). n-Valeric acid is significantly negatively correlated with the Romboutsia level (p < 0.01). CONCLUSION: The mechanism of ginseng treatment for spleen-qi deficiency is elucidated from the perspective of gut microbiota and its metabolite SCFAs. It provides a new way for further development and utilization of ginseng and a theoretical basis.

Radiogenomic Analysis of Vascular Endothelial Growth Factor in Patients With Glioblastoma.

OBJECTIVES: This article aims to predict the presence of vascular endothelial growth factor (VEGF) expression and to predict the expression level of VEGF by machine learning based on preoperative magnetic resonance imaging (MRI) of glioblastoma (GBM). METHODS: We analyzed the axial T2-weighted images (T2WI) and T1-weighted contrast-enhancement images of preoperative MRI in 217 patients with pathologically diagnosed GBM. Patients were divided into negative and positive VEGF groups, with the latter group further subdivided into low and high expression. The machine learning models were established with the maximum relevance and minimum redundancy algorithm and the extreme gradient boosting classifier. The area under the receiver operating curve (AUC) and accuracy were calculated for the training and validation sets. RESULTS: Positive VEGF in GBM was 63.1% (137/217), with a high expression ratio of 53.3% (73/137). To predict the positive and negative VEGF expression, 7 radiomic features were selected, with 3 features from T1CE and 4 from T2WI. The accuracy and AUC were 0.83 and 0.81, respectively, in the training set and were 0.73 and 0.74, respectively, in the validation set. To predict high and low levels, 7 radiomic features were selected, with 2 from T1CE, 1 from T2WI, and 4 from the data combinations of T1CE and T2WI. The accuracy and AUC were 0.88 and 0.88, respectively, in the training set and were 0.72 and 0.72, respectively, in the validation set. CONCLUSION: The VEGF expression status in GBM can be predicted using a machine learning model. Radiomic features resulting from data combinations of different MRI sequences could be helpful.