Bachmosegaard7342

In the clinical management of hypopharyngeal squamous cell carcinoma (HSCC), preoperative identification of early recurrence (≤2 years) after curative resection is essential. Thus, we aimed to develop a CT-based radiomic signature to predict early recurrence in HSCC patients preoperatively.

In total, 167 HSCC patients who underwent partial surgery were enrolled in this retrospective study and divided into two groups, i.e., the training cohort (

= 133) and the validation cohort (

= 34). Each individual was followed up for at least for 2 years. Radiomic features were extracted from CT images, and the radiomic signature was built with the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) model. The associations of preoperative clinical factors with early recurrence were evaluated. A radiomic signature-combined model was built, and the area under the curve (AUC) was used to explore their performance in discriminating early recurrence.

Among the 1415 features, 335 of them were selected using the variance threshold method. Then, the SelectKBest method was further used for the selection of 31 candidate features. Finally, 11 out of 31 optimal features were identified with the LASSO algorithm. In the LR classifier, the AUCs of the training and validation sets in discriminating early recurrence were 0.83 (95% CI 0.76-0.90) (sensitivity 0.8 and specificity 0.83) and 0.83 (95% CI 0.67-0.99) (sensitivity 0.69 and specificity 0.71), respectively.

Using the radiomic signature, we developed a radiomic signature to preoperatively predict early recurrence in patients with HSCC, which may serve as a potential noninvasive tool to guide personalized treatment.

Using the radiomic signature, we developed a radiomic signature to preoperatively predict early recurrence in patients with HSCC, which may serve as a potential noninvasive tool to guide personalized treatment.

To investigate whether preventive administration of a proton pump inhibitor (PPI) can reduce the occurrence and development of traumatic granuloma (TG) following type IV-VI cordectomy.

We retrospectively analyzed the status of postoperative granulomas in 37 patients who underwent type IV-VI cordectomy due to glottic cancer and determined whether postoperative administration of a PPI had any impact on granuloma formation and development.

The percentage and number of patients with granuloma in the PPI treatment group (experimental group) at the 1st, 2nd, 3rd, and 6th month following surgery were 81.25% (13/16), 25.00% (4/16), 18.75% (3/16), and 0.00% (0/16), respectively. The percentage and number of patients with granuloma in the no-PPI group (control group) were 95.24% (20/21), 71.43% (15/21), 52.38% (11/21), and 14.29% (3/21), respectively. The granuloma percentage of the PPI treatment group was lower than that of the control group at all postoperative time points assessed. The differences were not statistically significant at the 1st month (

= 0.175) but were statistically significant at the 2nd and 3rd months after surgery (

= 0.005,

= 0.037).

Preventive use of a PPI in patients after type IV-VI cordectomy can shorten the TG recovery duration and may reduce the severity of TG, but it cannot prevent TG from occurring. Our results should be confirmed by prospective randomized controlled trials with large sample sizes.

Preventive use of a PPI in patients after type IV-VI cordectomy can shorten the TG recovery duration and may reduce the severity of TG, but it cannot prevent TG from occurring. Our results should be confirmed by prospective randomized controlled trials with large sample sizes.Doxorubicin is an anthracycline antibiotic that is used for the treatment of various types of cancer. However, its clinical usage is limited due to its potential life-threatening adverse effects, such as cardio- and nephrotoxicities. Nonetheless, simultaneous administration of doxorubicin and antioxidants, such as those found in green tea leaves, could reduce cardiac and renal tissue damage caused by oxidative stress. The methylxanthine fraction isolated from Bancha tea leaves were tested in vitro for its antioxidant activity and in vivo for its organoprotective properties against doxorubicin-induced cardio- and nephrotoxicities in a rat model. The in vivo study was conducted on male Wistar rats divided into 6 groups. Methylxanthines were administered at high (5 mg/kg body weight) and low (1 mg/kg body weight) doses, while doxorubicin was administered at a cumulative dose of 20 mg/kg body weight. Serum creatinine, uric acid, and urea concentrations, as well as serum enzyme levels (creatinine kinase (CK), creatinine kinase MB fraction (CK-MB), aspartate aminotransferase (AST), and lactate dehydrogenase (LDH)) and electrolytes (Na+, K+, and Cl-), were analysed. In addition, histological analysis was performed to assess cardiac and renal tissue damage. The concomitant administration of Bancha methylxanthines and doxorubicin showed a dose-dependent reduction in the serum biochemical parameters, indicating a decrease in the cardiac and renal tissue damage caused by the antibiotic. Histological analysis showed that pretreatment with methylxanthines at the dose of 5 mg/kg resulted in an almost normal myocardial structure and a significant decrease in the morphological kidney changes caused by doxorubicin exposure compared with the group that received doxorubicin alone. The putative mechanism is most likely related to a reduction in the oxidative stress caused by doxorubicin.Microorganisms in the human body play a vital role in metabolism, immune defense, nutrient absorption, cancer control, and prevention of pathogen colonization. More and more biological and clinical studies have shown that the imbalance of microbial communities is closely related to the occurrence and development of various complex human diseases. Finding potential microbial-disease associations is critical for understanding the pathology of a few diseases and thus further improving disease diagnosis and prognosis. In this study, we proposed a novel computational model to predict disease-associated microbes. Specifically, we first constructed a heterogeneous interconnection network based on known microbe-disease associations deposited in a few databases, the similarity between diseases, and the similarity between microorganisms. We then predicted novel microbe-disease associations by a new method called the double-ended restart random walk model (DRWHMDA) implemented on the interconnection network. In addition, we performed case studies of colon cancer and asthma for further evaluation. The results indicate that 10 and 9 of the top 10 microorganisms predicted to be associated with colorectal cancer and asthma were validated by relevant literatures, respectively. Our method is expected to be effective in identifying disease-related microorganisms and will help to reveal the relationship between microorganisms and complex human diseases.

Low molecular heparin (LWMH) therapy can prevent the occurrence of VTE in tumor patients and may have a direct antitumor effect. However, the expression pattern of VEGF-A and microRNAs was less reported in cervical cancer subjects who received concurrent chemoradiotherapy (CCRT) or received anticoagulant treatment with low molecular weight heparin (LWMH) after CCRT (CCRT+LWMH).

In this study, 30 cervical cancer subjects treated with CCRT and 30 cervical cancer patients treated with CCRT+LWMH were enrolled. We screened five miRNAs (miR-15a-5p, miR-16-5p, miR-29a-3p, miR-195-5p, and miR-205-5p), which have multiple binding sites with VEGF-A and are highly expressed in serum of patients with cervical cancer, by RT-qPCR. The expression level of VEGF-A was also detected by RT-qPCR and ELISA. Statistical methods were used for difference and correlation analyses.

We observed the curative effect in the two treatment methods. In the CCRT group, the total effective rate was 60.00%, and in the CCRT+LWMT group, thepatients with VTE, which exhibited usage potential in the treatment of venous thromboembolism.

These data revealed roles for VEGF-A and these miRNAs as potential biomarkers in cervical cancer patients with VTE, which exhibited usage potential in the treatment of venous thromboembolism.Gene differential expression studies can serve to explore and understand the laws and characteristics of animal life activities, and the difference in gene expression between different animal tissues has been well demonstrated and studied. However, for the world-famous rare and protected species giant panda (Ailuropoda melanoleuca), only the transcriptome of the blood and spleen has been reported separately. Here, in order to explore the transcriptome differences between the different tissues of the giant panda, transcriptome profiles of the heart, liver, spleen, lung, and kidney from five captive giant pandas were constructed with Illumina HiSeq 2500 platform. The comparative analysis of the intertissue gene expression patterns was carried out based on the generated RNA sequencing datasets. Analyses of Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein-protein interaction (PPI) network were performed according to the identified differentially expressed genes (DEGs). We generated 194.52 GB clean base data from twenty-five sequencing libraries and identified 18,701 genes, including 3492 novel genes. With corrected p value 2, we finally obtained 921, 553, 574, 457, and 638 tissue-specific DEGs in the heart, liver, spleen, lung, and kidney, respectively. In addition, we identified TTN, CAV3, LDB3, TRDN, and ACTN2 in the heart; FGA, AHSG, and SERPINC1 in the liver; CD19, CD79B, and IL21R in the spleen; NKX2-4 and SFTPB in the lung; GC and HRG in the kidney as hub genes in the PPI network. The results of the analyses showed a similar gene expression pattern between the spleen and lung. This study provided for the first time the heart, liver, lung, and kidney's transcriptome resources of the giant panda, and it provided a valuable resource for further genetic research or other potential research.In this research, the photoplethysmogram (PPG) waveform analysis is utilized to develop a logistic regression-based predictive model for the classification of diabetes. The classifier has three predictors age, b/a, and SP indices in which they achieved an overall accuracy of 92.3% in the prediction of diabetes. In this study, a total of 587 subjects were enrolled. A total of 459 subjects were used for model training and development, while the rest of the 128 subjects were used for model testing and validation. The classifier was able to diagnose 63 patients correctly as diabetes while 27 subjects were wrongly classified as nondiabetes with an accuracy of 70%. Again, the model classified 479 subjects as nondiabetes correctly while it incorrectly classified 18 subjects as diabetes with an accuracy of 96.4%. see more Finally, the proposed model revealed an overall predictive accuracy of 92.3% which makes it a reliable surrogate measure for diabetes classification and prediction in clinical settings.

The current study examined gender-related differences in hemispheric asymmetries of graph metrics, calculated from a cortical thickness-based brain structural covariance network named hemispheric morphological network.

Using the T1-weighted magnetic resonance imaging scans of 285 participants (150 females, 135 males) retrieved from the Human Connectome Project (HCP), hemispheric morphological networks were constructed per participant. In these hemispheric morphologic networks, the degree of similarity between two different brain regions in terms of the distributed patterns of cortical thickness values (the Jensen-Shannon divergence) was defined as weight of network edge that connects two different brain regions. After the calculation and summation of global and local graph metrics (across the network sparsity levels

= 0.10-0.36), asymmetry indexes of these graph metrics were derived.

Hemispheric morphological networks satisfied small-worldness and global efficiency for the network sparsity ranges of

= 0.