Search

This study aimed to assess the effects of Chinese Baijiu with different flavors as supplementary material on microbial communities and flavor formation during inoculated fermentation of Chinese Dongbei Suancai. The results showed that the addition of Fen flavor Baijiu significantly increased the relative abundance of Candida, Luzhou flavor Baijiu increased the relative abundance of Pedobacter and Hannaella, while Maotai flavor Baijiu increased the Chryseobacterium and Kazachstania. A total of 226 volatile metabolites were detected in Suancai fermented when adding different flavors of Baijiu. Furthermore, the significantly upregulated metabolites (p < 0.01) of Suancai after adding Baijiu increased by 328.57%, whereas the significantly downregulated metabolites decreased by 74.60%. Simultaneously, the addition of Baijiu promoted the synthesis and decomposition of amino acids and short-chain fatty acids in the early and middle stages of fermentation. Further, Maotai flavor Baijiu improved the diversification of metabolic pathways in the late stage of Suancai fermentation. The E-nose response showed that sulfur-organic, broad-alcohol, sulfur-chlor was the principal differential flavor in Suancai caused by adding Baijiu with different flavors. Simultaneously, Fen flavor Baijiu and Luzhou flavor Baijiu accelerated the formation of the Suancai flavor. These results indicated that Baijiu with different flavors had significant effects on the flavor formation of inoculated fermented Suancai. [ABSTRACT FROM AUTHOR]

Purpose: To investigate dynamic functional connectivity (dFC) within the cerebellar‐whole brain network and dynamic topological properties of the cerebellar network in obstructive sleep apnea (OSA) patients. Methods: Sixty male patients and 60 male healthy controls were included. The sliding window method examined the fluctuations in cerebellum‐whole brain dFC and connection strength in OSA. Furthermore, graph theory metrics evaluated the dynamic topological properties of the cerebellar network. Additionally, hidden Markov modeling validated the robustness of the dFC. The correlations between the abovementioned measures and clinical assessments were assessed. Results: Two dynamic network states were characterized. State 2 exhibited a heightened frequency, longer fractional occupancy, and greater mean dwell time in OSA. The cerebellar networks and cerebrocerebellar dFC alterations were mainly located in the default mode network, frontoparietal network, somatomotor network, right cerebellar CrusI/II, and other networks. Global properties indicated aberrant cerebellar topology in OSA. Dynamic properties were correlated with clinical indicators primarily on emotion, cognition, and sleep. Conclusion: Abnormal dFC in male OSA may indicate an imbalance between the integration and segregation of brain networks, concurrent with global topological alterations. Abnormal default mode network interactions with high‐order and low‐level cognitive networks, disrupting their coordination, may impair the regulation of cognitive, emotional, and sleep functions in OSA. [ABSTRACT FROM AUTHOR]

Objectives: To summarize the clinicopathological and genetic features of malignant paragangliomas in head and neck cancer and to explore the appropriate treatment options for this rare lesion. Methods: Six patients harboring head and neck malignant paraganglioma from Beijing Tongren Hospital were retrospectively reviewed. The clinicopathological characteristics, gene mutations, and prognosis of these patients were analyzed. Results: Of these 6 patients, 3 were male and 3 were female; 4 patients harbored malignant carotid body tumors, and two had malignant vagal paragangliomas. Three patients had cervical lymph node metastasis, two presented with lung and bone metastasis, and 1 had lung and liver metastasis. Of the 6 patients, four underwent surgical resection, and the other two patients denied surgery and instead received chemotherapy with paclitaxel, ifosfamide, and dacarbazine. These 2 patients with vagal paraganglioma received postoperative radiotherapy. All 6 patients are still alive at the present time, with a median follow-up time of 66 months. Positive Ki-67 expression in tumor tissue ranged from 1% to 40%. Genetic mutations in SDHD, SDHB, ATR, and MAP3K13 were identified in 4 patients. Conclusions: After comprehensive treatment, head and neck malignant paraganglioma can attain a favorable prognosis. Genetic mutations are commonly detected in patients with malignant paragangliomas. This study also identified mutations in ATR and MAP3K13 in these patients. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma, a leading cause of cancer-related mortality, demands precise prognostic indicators for effective management. The presence of spread through air space (STAS) indicates adverse tumor behavior. However, comparative differences between 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography(PET)/computed tomography(CT) and CT in predicting STAS in lung adenocarcinoma remain inadequately explored. This retrospective study analyzes preoperative CT and 18F-FDG PET/CT features to predict STAS, aiming to identify key predictive factors and enhance clinical decision-making. Methods: Between February 2022 and April 2023, 100 patients (108 lesions) who underwent surgery for clinical lung adenocarcinoma were enrolled. All these patients underwent 18F-FDG PET/CT, thin-section chest CT scan, and pathological biopsy. Univariate and multivariate logistic regression was used to analyze CT and 18F-FDG PET/CT image characteristics. Receiver operating characteristic curve analysis was performed to identify a cut-off value. Results: Sixty lesions were positive for STAS, and 48 lesions were negative for STAS. The STAS-positive was frequently observed in acinar predominant. However, STAS-negative was frequently observed in minimally invasive adenocarcinoma. Univariable analysis results revealed that CT features (including nodule type, maximum tumor diameter, maximum solid component diameter, consolidation tumor ratio, pleural indentation, lobulation, spiculation) and all 18F-FDG PET/CT characteristics were statistically significant difference in STAS-positive and STAS-negative lesions. And multivariate logistic regression results showed that the maximum tumor diameter and SUVmax were the independent influencing factors of CT and 18F-FDG PET/CT in STAS, respectively. The area under the curve of maximum tumor diameter and SUVmax was 0.68 vs. 0.82. The cut-off value for maximum tumor diameter and SUVmax was 2.35 vs. 5.05 with a sensitivity of 50.0% vs. 68.3% and specificity of 81.2% vs. 87.5%, which showed that SUVmax was superior to the maximum tumor diameter. Conclusion: The radiological features of SUVmax is the best model for predicting STAS in lung adenocarcinoma. These radiological features could predict STAS with excellent specificity but inferior sensitivity.Highlights: • Evaluated PET/CT and CT features for predicting STAS in lung adenocarcinoma. • SUVmax and maximum tumor diameter were independent influential factors for STAS(+) in lung adenocarcinoma. • SUVmax showed higher predictive efficacy than maximum tumor diameter. • Radiological characteristics may serve as noninvasive biomarkers for STAS prediction in lung adenocarcinoma. [ABSTRACT FROM AUTHOR]

Background: Recently, long non-coding RNAs (lncRNAs) have been demonstrated as essential roles in tumor immune microenvironments (TIME). Nevertheless, researches on the clinical significance of TIME-related lncRNAs are limited in lung adenocarcinoma (LUAD). Methods: Single-cell RNA sequencing and bulk RNA sequencing data are integrated to identify TIME-related lncRNAs. A total of 1368 LUAD patients are enrolled from 6 independent datasets. An integrative machine learning framework is introduced to develop a TIME-related lncRNA signature (TRLS). Results: This study identified TIME-related lncRNAs from integrated analysis of single‑cell and bulk RNA sequencing data. According to these lncRNAs, a TIME-related lncRNA signature was developed and validated from an integrative procedure in six independent cohorts. TRLS exhibited a robust and reliable performance in predicting overall survival. Superior prediction performance barged TRLS to the forefront from comparison with general clinical features, molecular characters, and published signatures. Moreover, patients with low TRLS displayed abundant immune cell infiltration and active lipid metabolism, while patients with high TRLS harbored significant genomic alterations, high PD-L1 expression, and elevated DNA damage repair (DDR) relevance. Notably, subclass mapping analysis of nine immunotherapeutic cohorts demonstrated that patients with high TRLS were more sensitive to immunotherapy. Conclusions: This study developed a promising tool based on TIME-related lncRNAs, which might contribute to tailored treatment and prognosis management of LUAD patients. [ABSTRACT FROM AUTHOR]

Neuro‐COVID, a condition marked by persistent symptoms post‐COVID‐19 infection, notably affects various organs, with a particular focus on the central nervous system (CNS). Despite scant evidence of SARS‐CoV‐2 invasion in the CNS, the increasing incidence of Neuro‐COVID cases indicates the onset of acute neurological symptoms early in infection. The Omicron variant, distinguished by heightened neurotropism, penetrates the CNS via the olfactory bulb. This direct invasion induces inflammation and neuronal damage, emphasizing the need for vigilance regarding potential neurological complications. Our multicenter study represents a groundbreaking revelation, documenting the definite presence of SARS‐CoV‐2 in the cerebrospinal fluid (CSF) of a significant proportion of Neuro‐COVID patients. Furthermore, notable differences emerged between RNA‐CSF‐positive and negative patients, encompassing aspects such as blood–brain barrier integrity, extent of neuronal damage, and the activation status of inflammation. Despite inherent limitations, this research provides pivotal insights into the intricate interplay between SARS‐CoV‐2 and the CNS, underscoring the necessity for ongoing research to fully comprehend the virus's enduring effects on the CNS. The findings underscore the urgency of continuous investigation Neuro‐COVID to unravel the complexities of this relationship, and pivotal in addressing the long‐term consequences of COVID‐19 on neurological health. [ABSTRACT FROM AUTHOR]

As an important part of the energy transportation system, oil and gas pipelines are developing toward intelligence and digitalization. Vigorously developing and constructing pipeline networks based on intelligent methods such as big data and neural networks will help improve the efficiency of operation and management. This work provides an overview of recent developments of intelligent methods, including machine learning approaches, heuristic algorithms, and mathematical programming, used in the pipeline industry that can provide beneficial support for various applications enhancing operation and maintenance. Several aspects such as operating condition recognition, safety monitoring, pipeline remaining life prediction, and fault detection are reviewed and discussed. The study shows the need to focus on improving management level and ensuring pipeline safety. [ABSTRACT FROM AUTHOR]