Clinical analysis of hyperbaric oxygen combined with subdural drilling and drainage in the management of subdural effusion type IV with intracranial infection in infant patients.

Background: To explore the therapeutic effect of hyperbaric oxygen combined with subdural drilling and drainage (SDD) on subdural effusion type IV with intracranial infection in infant patients. Methods: This retrospective controlled study included 328 infant patients with subdural effusion type 4 with intracranial infection between January 2005 and January 2023. 178 patients were treated by hyperbaric oxygen combined with SDD (group A). 142 cases were treated with SDD (group B). 97 infants were only received hyperbaric oxygen (group C). Clinical outcomes, the control time of intracranial infection, complications, and the degree of brain re-expansion after 6 months of treatment were compared among the three groups. According to the comprehensive evaluation of treatment effectiveness and imaging results, it is divided into four levels: cured, significantly effective, improved, and ineffective. Results: No patient died during follow-up. The three groups were similar regarding age, sex, the general information, and clinical symptoms (p > 0.05). All intracranial infections in the children were effectively controlled. There was no difference in infection control time between group A and group B, and there was no statistical significance. However, the control time of intracranial infection between the two groups was different from that of group C, which was statistically significant. Compared with group B and group C, the degree of brain re-expansion in group A has obvious advantages and significant differences. The effective rates of the three groups were 83.7%, 58.5%, and 56.7%, respectively. There were 28 cases of subcutaneous hydrops in group A and 22 cases of subcutaneous hydrops in group B after operation, and no other serious complications. Conclusion: The SDD is safe and effective for infant patients with intracranial infections through fluid replacement and intrathecal antibacterial. Hyperbaric oxygen is effective as an adjuvant therapy to promote brain re-expansion.

The efficacy of progressive muscle relaxation training on cancer-related fatigue and quality of life in patients with cancer: A systematic review and meta-analysis of randomized controlled studies.

BACKGROUND: Cancer-related fatigue is one of the most common symptoms in cancer patients, usually accompanied by anxiety, depression and insomnia, which seriously affect patients' quality of life. Progressive muscle relaxation training is widely used for cancer-related fatigue, but the overall effect is unclear. OBJECTIVES: The aim of this study was to summarize the evidence on the effects of progressive muscle relaxation training on cancer-related fatigue and quality of life in cancer patients. DESIGN: Systematic review and meta-analysis. METHODS: Nine electronic databases (PubMed, Excerpta Medica Database (Embase), The Cochrane Library (Cochrane Central Register of Controlled Trials, CENTRAL), Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Chinese Biomedical Literature Database (CBM), Chinese National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP) and Wanfang Database) were explored for randomized controlled trials (RCTs) published before February 2023. This study was reported based on the PRISMA 2020 statement. The Cochrane Collaboration's risk of bias assessment tool was used for methodological assessment, and the GRADE pro online assessment tool was used for evidence evaluation. The data were analyzed with the Review Manager 5.4 software. RESULTS: Twelve studies involving 1047 patients were included. Meta-analysis showed that progressive muscle relaxation training plus routine nursing produced more positive effects than routine nursing in improving cancer-related fatigue [SMD = -1.06, 95 % CI -1.49, -0.62, P < 0.00001], anxiety [SMD = -1.09, 95 % CI -1.40, -0.77, P < 0.00001], depression [SMD = -1.43, 95 % CI -1.76, -1.10, P < 0.00001], and quality of sleep [MD = -1.41, 95 % CI -1.74, -1.08, P < 0.00001]. However, there was no significant difference in improving quality of life [SMD = 0.27, 95 % CI -0.62, 1.15, P = 0.55]. Progressive resistance exercise plus routine nursing improved cancer-related fatigue more than progressive muscle relaxation training plus routine nursing [SMD = 1.11, 95 % CI 0.43, 1.78, P = 0.001]. There was low certainty of evidence that progressive muscle relaxation training improved cancer-related fatigue and quality of sleep, and the evidence that improved quality of life, anxiety and depression was very low. CONCLUSION: Current evidence suggested that progressive muscle relaxation training has the potential to improve cancer-related fatigue, anxiety, depression and quality of sleep in patients with cancer and is a low-load, simple exercise worthy of recommendation for cancer patients in fatigue state. Future research should focus on improving the methodological quality of randomized controlled trials to enhance the persuasive evidence of progressive muscle relaxation training efficacy.

The self-distillation trained multitask dense-attention network for diagnosing lung cancers based on CT scans.

BACKGROUND: The latest international multidisciplinary histopathological classification of lung cancer indicates that a deeper study of the lung adenocarcinoma requires a comprehensive multidisciplinary platform. However, in the traditional pathological examination or previous computer-vision-based research, the entire lung is not considered in a comprehensive manner. PURPOSE: The study aims to develop a deep learning model proposed for diagnosing the lung adenocarcinoma histopathologically based on CT scans. Instead of just classifying the lung adenocarcinoma, the pathological report should be inferred based on both the invasiveness and growth pattern of the tumors. METHODS: A self-distillation trained multitask dense-attention network (SD-MdaNet) is proposed and validated based on 2412 labeled CT scans from 476 patients and 845 unlabeled scans. Inferring the pathological report is divided into two tasks, predicting the invasiveness of the lung tumor and inferring growth patterns of tumor cells in a comprehensive histopathological subtyping manner with excellent accuracy. In the proposed method, the dense-attention module is introduced to better extract features from a small dataset in the main branch of the MdaNet. Next, task-specific attention modules are utilized in different branches and finally integrated as a multitask model. The second task is a blend of classification and regression tasks. Thus, a specialized loss function is developed. In the proposed knowledge distillation (KD) process, the MdaNet as well as its main branch trained for solving two single tasks, respectively, are treated as multiple teachers to produce a student model. A novel KD loss function is developed to take the advantage of all the models as well as data with labels and without labels. RESULTS: SD-MdaNet achieves an AUC of 98.7 ± 0.4 % $98.7\pm 0.4\%$ on invasiveness prediction, and 91.6 ± 1.0 % $91.6\pm 1.0\%$ on predominant growth pattern prediction on our dataset. Moreover, the average mean squared error in inferring growth pattern proportion reaches 0.0217 ± 0.0019 $0.0217\pm 0.0019$ , and the AUC for predominant growth pattern proportion reaches 91.6 ± 1.0 % $91.6\pm 1.0\%$ . The proposed SD-MdaNet is significantly better than all other benchmarking methods ( F D R < 0.05 $FDR<0.05$ ). CONCLUSIONS: Experimental results demonstrate that the proposed SD-MdaNet can significantly improve the performance of the lung adenocarcinoma pathological diagnosis using only CT scans. Analyses and discussions are conducted to interpret the advantages of the SD-MdaNet.

Radioprotective efficacy of Astilbin in mitigating radiation-induced lung injury through inhibition of p53 acetylation.

Radiation-induced lung injury (RILI) is a common side effect in thoracic tumor patients undergoing radiotherapy. At present, there is no ideal radio-protective agent which is widely used in RILI treatment. Astilbin (AST), a bioactive flavonoid, exhibits various biological effects, including anti-inflammatory, antioxidant, and anti-fibrotic activities, which partly result from reducing oxidative stress and inflammation in various pathogenic conditions. However, the protective efficacy of AST to ameliorate RILI has not been reported. In this study, we employed network pharmacology, RNA sequencing, and experimental evaluation to reveal the effects and pharmacological mechanism of AST to treat RILI in vivo and in vitro. We observed that AST reduced radiation-induced apoptosis, DNA damage, inflammatory reactions, and the reactive oxygen species (ROS) level in human normal lung epithelial cells BEAS-2B. Further study showed that AST treatment significantly ameliorated RILI by reducing the radiation-induced pathology changes and inflammatory reaction of lung tissue in C57BL/6J mice. Mechanistically, the expression of epithelial-mesenchymal transition (EMT) markers and radiation-triggered acetylation of the p53 protein were alleviated by AST treatment. Furthermore, AST alleviated the acetylation of p53 after intervention of Trichostatin A (TSA). Our data indicate that AST can alleviate RILI by inhibiting inflammatory reactions and the EMT process through decreasing the expression of p53 acetylation. In conclusion, our study suggests that AST has great potential to be a new protective and therapeutic compound for RILI.

Effects of modified external ventricular drainage vs. an Ommaya reservoir in the management of hydrocephalus with intracranial infection in pediatric patients.

Background: Hydrocephalus with intracranial infection (HII) may cause pathological changes in brain tissue structure and irreversible damage to the nervous system. However, intracranial infection is a contraindication to ventriculo-peritoneal (VP) shunt surgery, and the prognosis is improved by early infection control and intracranial pressure reduction. This study evaluated the safety and efficacy of the Ommaya reservoir vs. modified external ventricular drainage (M-EVD) in the management of HII in pediatric patients. Methods: This retrospective controlled study included 45 pediatric patients with HII treated with an Ommaya reservoir (n = 24) or M-EVD (n = 21) between January 2018 and December 2022. Clinical outcomes, cerebrospinal fluid (CSF) test results, complications, and outcomes were compared between the Ommaya reservoir and M-EVD groups. Results: No patient died during the follow-up period. The two groups were similar regarding age, sex, admission temperature, weight, preoperative serum protein and albumin concentrations, CSF analysis (white blood cell count, glucose concentration, and protein content), and clinical symptoms (P > 0.05). Both groups had significant changes in the CSF test results postoperatively compared with preoperatively (P < 0.05). In the M-EVD group, the median days for 13 children to remove the external drainage tube and receive VP shunt was 19 days. The longest drainage tube retention time was 61 days, and there was no intracranial infection or serious complication related to the drainage tube. After the placement of the Ommaya, the median time required for CSF to return to normal was 21 days, and a total of 15 patients underwent VP shunt surgery. Conclusion: The Ommaya reservoir and M-EVD are safe and effective for pediatric patients with HII. Both methods reduce the intracranial pressure and alleviate the symptoms of hydrocephalus, although there are differences between the two methods.

Potential Functions of the tRNA-Derived Fragment tRF-Gly-GCC Associated With Oxidative Stress in Radiation-Induced Lung Injury.

Objective: Transfer RNA-derived small RNAs (tsRNAs) are a novel type of non-coding RNA with various regulatory functions. They are associated with oxidative stress in various diseases, but their potential functions in radiation-induced lung injury (RILI) remain uncertain. Methods: To explore the role of tsRNAs in RILI, we used X-rays to irradiate human bronchial epithelial cells and examined the expression profile of altered tsRNAs by RNA sequencing and bioinformatics analysis. Sequencing results were verified by qRT-PCR. tsRNA functions were explored using several methods, including CCK-8, reactive oxygen species (ROS) assays, cell transfection, and western blotting. Results: Eighty-six differentially expressed tRNA-derived fragments (tRFs) were identified: 64 were upregulated, and 22 were downregulated. Among them, the regulation of tRF-Gly-GCC, associated with oxidative stress, may be mediated by the inhibition of cell proliferation, promotion of ROS production, and apoptosis in the occurrence and development of RILI. A Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that the underlying molecular mechanism may involve the PI3K/AKT and the FOXO1 signaling pathways. Conclusion: Our findings provide new insights into the molecular mechanisms underpinning RILI, advancing the clinical prevention and treatment of this disease.

A deep learning based CT image analytics protocol to identify lung adenocarcinoma category and high-risk tumor area.

We present a protocol which implements deep learning-based identification of the lung adenocarcinoma category with high accuracy and generalizability, and labeling of the high-risk area on Computed Tomography (CT) images. The protocol details the execution of the python project based on the dataset used in the original publication or a custom dataset. Detailed steps include data standardization, data preprocessing, model implementation, results display through heatmaps, and statistical analysis process with Origin software or python codes. For complete details on the use and execution of this protocol, please refer to Chen et al. (2022).

Machine vision-assisted identification of the lung adenocarcinoma category and high-risk tumor area based on CT images.

Computed tomography (CT) is a widely used medical imaging technique. It is important to determine the relationship between CT images and pathological examination results of lung adenocarcinoma to better support its diagnosis. In this study, a bilateral-branch network with a knowledge distillation procedure (KDBBN) was developed for the auxiliary diagnosis of lung adenocarcinoma. KDBBN can automatically identify adenocarcinoma categories and detect the lesion area that most likely contributes to the identification of specific types of adenocarcinoma based on lung CT images. In addition, a knowledge distillation process was established for the proposed framework to ensure that the developed models can be applied to different datasets. The results of our comprehensive computational study confirmed that our method provides a reliable basis for adenocarcinoma diagnosis supplementary to the pathological examination. Meanwhile, the high-risk area labeled by KDBBN highly coincides with the related lesion area labeled by doctors in clinical diagnosis.

Construction of MicroRNA-mRNA Regulatory Network in the Molecular Mechanisms of Bleomycin-Induced Pulmonary Fibrosis.

Bleomycin is a common antitumor agent used to treat many different types of malignancies; however, its main side effect is pulmonary fibrosis. The mechanism of bleomycin-induced pulmonary fibrosis (BIPF) has not been fully elucidated. Therefore, to further explore the molecular mechanisms of BIPF, we screened for microRNA (miRNA) and mRNA expression obtained from BIPF samples from the Gene Expression Omnibus database. Subsequently, we identified the differentially expressed miRNAs and genes that overlapped with the differentially expressed miRNAs target genes, predicted by using the miRWalk database selected as a candidate. The candidate genes were visualized based on Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes analyses. A protein-protein interaction network was constructed. Hub differentially expressed genes were selected and corresponding miRNAs to construct a miRNA-mRNA regulation network. Then, we chose three key miRNAs to study their regulatory relationship in bleomycin-induced pulmonary fibrosis. Finally, mouse lung epithelial cells TC-1 and MLE-12 were treated with bleomycin with qPCR to validate the results of three important hub genes and all key miRNAs. And dual-luciferase report experiment was carried out to verify the interaction of mmu-miR-1946a and serpina3n. The results revealed that the imbalance of matrix metalloproteinase-9 (MMP-9) and tissue inhibitor of metalloproteinase-1 (TIMP-1) plays a pivotal role in the occurrence and development of BIPF. In addition, Serpina3n and mmu-miR-1946a were proved interaction and may be involved in the regulation of the balance between MMP-9 and TIMP-1. The experimental results also verify the analysis. Our findings provide new insights into the key mediators and pathways related to the molecular mechanisms of BIPF.

Prognostic Value of CT Imaging-Based Tumor Volume in Patients With Non-Surgical Esophageal Squamous Cell Carcinoma.

BACKGROUND: The American Joint Committee on Cancer-Tumor (AJCC-T) staging system for esophageal carcinoma patients, which is based on the depth of tumor invasion, is not applicable in some cases. This study aims to assess the prognostic value of CT imaging-based tumor volume and its usefulness for T staging in patients with non-surgical esophageal squamous cell carcinoma (ESCC). METHODS: We retrospectively reviewed the records of 158 ESCC patients undergoing definitive (chemo) radiotherapy from two hospitals. Tumor volume based on the CT imaging was calculated using the formula: V = πabc / 6. Three cutoff points for tumor volume were obtained with the X-tile software. Overall survival (OS) was analyzed using the Kaplan-Meier method. The -2 log-likelihood ratio and Akaike Information Criterion (AIC) value were evaluated to compare the AJCC-T staging system with the proposed T staging method. RESULTS: The median tumor volume was 19.8 cm³ (range from 1.0 to 319.5 cm³). The three optimal cutoff points of tumor volume were 12.7, 22.8, and 51.9 cm³, and the patients were divided into four groups named as proposed T1-T4 stages. The 3-year OS rates in patients with proposed T1 to T4 stages were 67.9%, 30.6%, 21.3%, and 5.3%, respectively. The -2 log-likelihood ratios of the AJCC-T stage and proposed T stage were 1,068.060 and 1,047.418, respectively. The difference in the AIC value between the two T staging systems was 18.642. CONCLUSION: CT imaging-based tumor volume was superior to the depth of tumor invasion for T staging in predicting the prognosis of non-surgical ESCC patient.

Tanshinone IIA ameliorates diabetic cardiomyopathy by inhibiting Grp78 and CHOP expression in STZ-induced diabetes rats.

Diabetic cardiomyopathy (DCM), one of the common diabetic complications, causes a high rate of mortality in patients with diabetes. Tanshinone IIA (TSIIA), one of the components of Salvia miltiorrhiza (Danshen), has anti-oxidative stress activity and is widely used to treat diabetes-associated diseases. However, its efficacy on DCM remains unclear. The present study aimed to investigate the potential therapeutic function of TSIIA on DCM in an experimental diabetic rat model. Streptozotocin (STZ)-induced diabetic rats were intraperitoneally injected with TSIIA for 6 weeks. The present results indicated that blood glucose concentration was slightly reduced in the low-dose TSIIA treatment group. TSIIA injection was also noted to improve cardiac function, and restore loss of mitochondrial cristae, swollen mitochondrial matrix and disorganized myofibrils in myocardial cells, which are thought to be characteristics of apoptosis. Furthermore, TSIIA injection could increase the activity of superoxide dismutase in STZ-induced diabetic rats, and suppress the endoplasmic reticulum (ER) stress signaling pathway via reducing the expression of glucose-regulated protein 78 and C/EBP homologous protein. These results provide evidence that TSIIA may ameliorate DCM in diabetic rats, possibly via suppressing oxidative stress and ER stress activation.