Clinical efficacy of different therapeutic strategies in patients with spontaneous rupture of the esophagus: a multicenter retrospective cohort study.

BACKGROUND: The therapeutic strategy for patients with spontaneous rupture of the esophagus includes surgical repair, endoscopic therapy, supportive care, and others. However, no evidence exists to direct clinical decision-making regarding the choice of operative and nonoperative management. The aim of this study was to determine the clinical efficacy of different therapeutic strategies in both general and stratified patients. METHODS: This study retrospectively analyzed a consecutive cohort of 101 patients at nine tertiary referral hospital centers in China. Patients were divided into operative and nonoperative groups based on the initial treatment. Short-term outcomes, including 90-day mortality, length of hospital stay, and postoperative leakage were compared. Subgroup analysis was performed based on treatment timing and Pittsburgh perforation severity score (PSS). RESULTS: Of 101 patients, 60 (58.4%) underwent operative management. A significant difference of 90-day mortality between operative and nonoperative groups was observed (15.0% vs. 34.1%, P=0.031). Operative management tend to yield similar therapeutic benefits in timely (OR, 0.250; 95% CI, 0.05-1.14, P=0.073) and delayed (OR, 0.42; 95% CI, 0.12-1.47, P=0.175) treatment groups. Based on PSS stratification, operative management significantly decreased the risk of 90-day mortality (OR, 0.211; 95% CI, 0.064-0.701; P=0.011) for patients in low- and moderate-risk groups but may be detrimental for patients in high-risk group (OR, 1.333; 95% CI, 0.233-7.626; P=0.746). CONCLUSIONS: Operative management might be superior to nonoperative management for low- and moderate-risk patients with spontaneous rupture of the esophagus. However, for patients at high risks, operative management might not provide additional benefits compared with nonoperative management. Further research involving larger sample sizes is required for accurate patient stratification and conclusive evidence-based guideline.

Pharmacokinetics and apparent Michaelis constant for metabolite conversion of sorafenib in healthy and hepatocellular carcinoma-bearing rats.

Aim: Investigation of the pharmacokinetics of sorafenib (SRF) in rats with hepatocellular carcinoma (HCC). Methods: A reproducible ultra-HPLC-MS method for simultaneous determination of serum SRF, N-hydroxymethyl sorafenib and N-demethylation sorafenib. Results: Both the maximum serum concentrations (2.5-times) and the area under the serum concentration-time curve from 0 h to infinity (4.5-times) of SRF were observed to be significantly higher, with a greater than 3.0-fold decrease in the clearance rate in the HCC-bearing rats compared with these values in healthy animals. Further study revealed approximately 3.8- and 3.2-times increases in the apparent Michaelis constant for N-hydroxymethyl sorafenib and N-demethylation sorafenib conversions in the HCC-bearing rats. Conclusion: The low efficiency for the SRF conversions was a key contributor to the increased serum concentrations of SRF.

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α-Linolenic Acid Inhibits RANKL-Induced Osteoclastogenesis In Vitro and Prevents Inflammation In Vivo.

Inflammation is an important risk factor for bone-destroying diseases. Our preliminary research found that Zanthoxylum bungeanum seed oil (ZBSO) is abundant in unsaturated fatty acids and could inhibit osteoclastogenesis in receptor activator of nuclear factor κB ligand (RANKL)-induced RAW264.7 cells. However, the key constituents in ZBSO in the prevention of osteoclastogenesis and its possible mechanism related to inflammation are still unclear. Therefore, in this study, oleic acid (OA), linoleic acid (LA), palmitoleic acid (PLA), and alpha-linolenic acid (ALA) in ZBSO, havingthe strongest effect on RANKL-induced osteoclastogenesis, were selected by a tartrate-resistant acid phosphatase (TRAP) staining method. Furthermore, the effects of the selected fatty acids on anti-inflammation and anti-osteoclastogenesis in vitro and in vivo were assessed using RT-qPCR. Among the four major unsaturated fatty acids we tested, ALA displayed the strongest inhibitory effect on osteoclastogenesis. The increased expression of free fatty acid receptor 4 (FFAR4) and ß-arrestin2 (ßarr2), as well as the decreased expression of nuclear factor-kappa B (NF-κB), tumor necrosis factor-α (TNF-α), nuclear factor of activated T-cells c1 (NFATc1), and tartrate-resistant acid phosphatase (TRAP) in RAW264.7 cells after ALA treatment were observed. Moreover, in ovariectomized osteoporotic rats with ALA preventive intervention, we found that the expression of TNF-α, interleukin-6 (IL-6), interleukin-1ß (IL-1ß), NFATc1, and TRAP were decreased, while with the ALA therapeutic intervention, downregulated expression of NF-κB, NFATc1, TRAP, and transforming growth factor beta-activated kinase 1 (TAK1) were noticed. These results indicate that ALA, as the major unsaturated fatty acid in ZBSO, could inhibit RANKL-induced osteoclastogenesis via the FFAR4/ßarr2 signaling pathway and could prevent inflammation, suggesting that ZBSO may be a promising potential natural product of unsaturated fatty acids and a dietary supplement for the prevention of osteoclastogenesis and inflammatory diseases.

Oral mycobiota and pancreatic ductal adenocarcinoma.

Early detection of pancreatic ductal adenocarcinoma (PDAC) is essential for survival. Preliminary research demonstrated significant associations between structural alternation of mycobiota and PDAC. In this study, we investigated the associations between oral mycobiota and PDAC. We further explored mycobiota biomarkers for PDAC detection. We enrolled 34 PDAC patients and 35 matched healthy controls from West China hospital in Southwest China. Demographic data, clinical information, and salivary samples were collected. Mycobiota characteristics were defined using Internal Transcribed Spacer (ITS) ribosomal RNA sequencing. We found that the PDAC patients had significant increase in fungal abundance (P < 0.001) and significant decrease in fungal diversity (P < 0.001) in comparison to the healthy controls. A higher abundance of Basidiomycota and Unclassifed_p_Ascomycota was associated with an increased risk of PDAC. With each increase of abundance of g__unclassified_k__Fungi and g__unclassified_p__Ascomycota in PDAC patients, the risk of pancreatic cancer increased by 1.359 odds and 1.260 odds, respectively. Aspergillus (AUC = 0.983, 95% CI 0.951-1.000) and Cladosporium (AUC = 0.969, 95% CI 0.921-1.000) achieved high classification powers to distinguish PDAC patients from the healthy controls. The rapid, inexpensive tests of ITS1 sequencing of mycobiota and PCR detection of potential fungal biomarkers make it promising for the clinical practice to use oral microbes for PDAC early detection and prevention. Results of our study provide evidence that salivary mycobiota may provide insights into cancer risk, prevention, and detection.

Current treatment and outcome of esophageal perforation: A single-center experience and a pooled analysis.

BACKGROUND: Esophageal perforation has been one of the serious clinical emergencies, because of the high mortality and complication rates. However, the current prognosis of esophageal perforation and the outcomes of available treatment methods are not well defined. This study attempted to pool the immediate outcomes of esophageal perforation in the past 2 decades. METHODS: The clinical data of 22 consecutive adult patients with esophageal perforation in our center were analyzed. A pooled analysis was also conducted to summarize results from the literatures published between 1999 and 2020. Studies that met the inclusion criteria were assessed, and their methodological quality was examined. RESULTS: The mortality and complication rates in our center were 4.55% and 31.82%, separately. The pooled analysis included 45 studies published between 1999 and 2019, which highlighted an overall immediate mortality rate of 9.86%. Surgical treatments were associated with a pooled immediate mortality of 10.01%, and for conservative treatments of 6.49%. Besides, in the past decade, the mortality and complication rates decreased by 27.12% and 46.75%, respectively. CONCLUSIONS: In the past 2 decades, the overall immediate mortality rate of esophageal perforation was about 10% in the worldwide, and the outcomes of esophageal perforation treatment are getting better in the last 10 years. ETHICS REGISTRATION INFORMATION: LW2020011.

Discrimination of smoking status by MRI based on deep learning method.

BACKGROUND: This study aimed to assess the feasibility of deep learning-based magnetic resonance imaging (MRI) in the prediction of smoking status. METHODS: The head MRI 3D-T1WI images of 127 subjects (61 smokers and 66 non-smokers) were collected, and 176 image slices obtained for each subject. These subjects were 23-45 years old, and the smokers had at least 5 years of smoking experience. Approximate 25% of the subjects were randomly selected as the test set (15 smokers and 16 non-smokers), and the remaining subjects as the training set. Two deep learning models were developed: deep 3D convolutional neural network (Conv3D) and convolution neural network plus a recurrent neural network (RNN) with long short-term memory architecture (ConvLSTM). RESULTS: In the prediction of smoking status, Conv3D model achieved an accuracy of 80.6% (25/31), a sensitivity of 80.0% and a specificity of 81.3%, and ConvLSTM model achieved an accuracy of 93.5% (29/31), a sensitivity of 93.33% and a specificity of 93.75%. The accuracy obtained by these methods was significantly higher than that (<70%) obtained with support vector machine (SVM) methods. CONCLUSIONS: The deep learning-based MRI can accurately predict smoking status. Studies with large sample size are needed to improve the accuracy and to predict the level of nicotine dependence.

Mixture feature selection strategy applied in cancer classification from gene expression.

Recently, cancer classification based on gene expression has been developed. This gives a hope for the discrimination of cancer to a more systematic direction. However, there're many challenges existing in the new method. Maybe the most important one is the unbalance that so few training samples exist compared to so huge genes been collected. So feature selection becomes one center problem of the cancer classification. A novel mixture feature selection strategy has been proposed in this paper, it make use of the characters of filter and wrapper, and synthesis three feature selection methods: Pearson correlation analysis, Relief-F and SVM.