Low dose TGF-ß1 can improve vohwinkel syndrome by promoting the proliferation of keratinocytes.

Vohwinkel syndrome (VS) is a very rare autosomal dominant disorder that can cause disability and deformity in severe cases. Mutations of the LOR (loricrin) and GJB2 (Cx26) genes have been found in VS so far. Many studies have indicated that the differentiation and growth of epidermal keratinocytes are regulated by mutant Cx26, and it may explain the pathogenesis of VS. It has been found that transforming growth factor ß1 (TGF-ß1) expression was lower in G130V (OE1) and D66H (OE2) mutant keratinocytes in the VS model with GJB2 mutation as compared to normal keratinocytes (NC). TGF-ß is a cytokine involved in the regulation of processes like cell proliferation and differentiation in different types of cells. At present, many in vitro studies focus on TGF- ß 1 inhibition of keratinocyte growth.However, the relationship between TGF-ß1 and VS remains unknown. This study aimed at elucidating the role and potential pathogenic mechanism of TGF-ß in VS. The results indicated that the down-regulation expression of TGF-ß1 in VS was linked to cell proliferation inhibition through p-Smad3/c-myc. In contrast, low-dose TGF-ß1 treatment of VS keratinocytes can improve their proliferation inhibition and up-regulate the expression Cyclin D1. This suggests that low doses of TGF-ß1 can improve the proliferation of VS and provide new insights into its treatment.

Characteristics of Computed Tomography Images for Patients with Acute Liver Injury Caused by Sepsis under Deep Learning Algorithm.

This study was aimed at exploring the application of image segmentation based on full convolutional neural network (FCN) in liver computed tomography (CT) image segmentation and analyzing the clinical features of acute liver injury caused by sepsis. The Sigmoid function, encoder-decoder, and weighted cross entropy loss function were introduced and optimized based on FCN. The Dice value, precision, recall rate, volume overlap error (VOE), relative volume difference (RVD), and root mean square error (RMSE) values of the optimized algorithms were compared and analyzed. 92 patients with sepsis were selected as the research objects, and they were divided into a nonacute liver injury group (50 cases) and acute liver injury group (42 cases) based on whether they had acute liver injury. The differences in the proportion of patients with different disease histories, the proportion of patients with different infection sites, the number of organ failure, and the time of admission to intensive care unit (ICU) were compared between the two groups. It was found that the optimized window CT image Dice value after preprocessing (0.704 ± 0.06) was significantly higher than the other two methods (P < 0.05). The Dice value, precision, and recall rate of the optimized-FCN algorithm were (0.826 ± 0.06), (0.91 ± 0.08), and (0.88 ± 0.09), respectively, which were significantly higher than other algorithms (P < 0.05). The VOE, RVD, and RMSE values were (21.19 ± 1.97), (10.45 ± 1.02), and (0.25 ± 0.02), respectively, which were significantly lower than other algorithms (P < 0.05). The proportion of patients with a history of drinking in the nonacute liver injury group was lower than that in the acute liver injury group (P < 0.05), and the proportion of patients with a history of hypotension was greatly higher than that in the nonacute liver injury group (P < 0.01). CT images of sepsis patients with acute liver injury showed that large areas of liver parenchyma mixed with high-density hematoma, the number of organ failures, and the length of stay in ICU were significantly higher than those in the nonacute liver injury group (P < 0.05). It showed that the optimization algorithm based on FCN greatly improved the performance of CT image segmentation. Long-term drinking, low blood pressure, number of organ failures, and length of stay in ICU were all related to sepsis and acute liver injury. Conclusion in this study could provide a reference basis for the diagnosis and prognosis of acute liver injury caused by sepsis.

Applying Lean Six Sigma to Reduce the Incidence of Unplanned Surgery Cancellation at a Large Comprehensive Tertiary Hospital in China.

Unplanned surgery cancellation (USC) was an important quality management issue in the course of medical care for surgical patients, which caused inappropriate use of hospital resources and had negative impacts on quality and safety. This study used Lean Six Sigma to reduce the incidence of USC. Following the Lean Six Sigma DMAIC (Define, Measure, Analyze, Improve, and Control) process, the main factors influencing the USC were identified, such as the time of informing patient admission, the time of submitting operation notice, and the management of test report follow-up. A series of measures were implemented including improving the health education content of virtual bed patients, standardizing the way of communication between the Admission Management Center and the patients, improving the timing of anesthesia evaluation, optimizing the process of operation notice with an information system, and implementing the regulations of virtual bed management. The incidence of USC reduced from 10.21% in Jan. 2016 to 3.8% in Dec. 2016, and the Z-score increased from 1.25 to 1.68, which improved patient safety and demonstrated that Lean Six Sigma was an effective method to solve cross-department issues in hospital.

5,11,17,23-Tetra-tert-butyl-25,26,27,28-tetrakis(2-cyanobenzyloxy)-2,8,14,20-tetrathiacalix[4]arene-dichloromethane (1/2).

A new p-tert-butylthiacalix[4]arene derivative, C(72)H(68)N(4)O(4)S(4) x 2CH(2)Cl(2), has been synthesized and is comprised of one tetra-p-tert-butyltetrakis(2-cyanobenzyloxy)tetrathiacalix[4]arene and two dichloromethane molecules. The calix[4]arene molecule is centrosymmetric and adopts an unusual 1,2-alternate conformation via pi-pi interactions between adjacent cyanophenyl rings on the lower rim of the parent thiacalix[4]arene system.