Purification and Characterization of a CkTLP Protein from Cynanchum komarovii Seeds that Confers Antifungal Activity

BACKGROUND: Cynanchum komarovii Al Iljinski is a desert plant that has been used as analgesic, anthelminthic and antidiarrheal, but also as a herbal medicine to treat cholecystitis in people. We have found that the protein extractions from C. komarovii seeds have strong antifungal activity. There is strong interest to develop protein medication and antifungal pesticides from C. komarovii for pharmacological or other uses. METHODOLOGY/PRINCIPAL FINDINGS: An antifungal protein with sequence homology to thaumatin-like proteins (TLPs) was isolated from C. komarovii seeds and named CkTLP. The three-dimensional structure prediction of CkTLP indicated the protein has an acid cleft and a hydrophobic patch. The protein showed antifungal activity against fungal growth of Verticillium dahliae, Fusarium oxysporum, Rhizoctonia solani, Botrytis cinerea and Valsa mali. The full-length cDNA was cloned by RT-PCR and RACE-PCR according to the partial protein sequences obtained by nanoESI-MS/MS. The real-time PCR showed the transcription level of CkTLP had a significant increase under the stress of abscisic acid (ABA), salicylic acid (SA), methyl jasmonate (MeJA), NaCl and drought, which indicates that CkTLP may play an important role in response to abiotic stresses. Histochemical staining showed GUS activity in almost the whole plant, especially in cotyledons, trichomes and vascular tissues of primary root and inflorescences. The CkTLP protein was located in the extracellular space/cell wall by CkTLP::GFP fusion protein in transgenic Arabidopsis. Furthermore, over-expression of CkTLP significantly enhanced the resistance of Arabidopsis against V. dahliae. CONCLUSIONS/SIGNIFICANCE: The results suggest that the CkTLP is a good candidate protein or gene for contributing to the development of disease-resistant crops

Formation conditions of natural gas fields in the lacustrine basin in eastern China: Insights into the first discovery within the Bohai Bay Basin

The hydrocarbon source of Bohai Bay Basin is dominated by oil-prone kerogens of type II2-II1 within semi-deep and deep lacustrine facies. In the Neogene period, faults were well-developed via significant structural activity. The Bohai Sea is generally considered to have no geological basis for the formation of large natural gas fields. Through analogous analysis of domestic and international gas fields, the key geological factors that restrict formation in continental rift lacustrine basins were studied, including gas source, preservation conditions, and reservoirs. A natural gas enrichment and accumulation model within a petroliferous basin is presented. The model indicates that rapid subsidence and high-intensity gas generation within petroliferous sags during the late stages were main contributors to natural gas field formation. Archean metamorphic buried hill reservoirs and thick, overpressure mudstone with strong vertical sealing ability provided favorable storage space and preservation, respectively. Using the model, an integrated Archaean metamorphic buried hill condensate gas reservoir, Bozhong 19–6, was discovered in the Bohai Bay Basin. The natural gas reserves are about 450×109 m3, equivalent to oil production of 800 ×106 m3, and signify a breakthrough in natural gas exploration of continental rift lacustrine basins in China

Chinese medicine in the treatment of non-alcoholic fatty liver disease based on network pharmacology: a review

Non-alcoholic fatty liver disease (NAFLD) is a clinicopathological syndrome characterized by abnormalities in hepatic fat deposition, the incidence of which has been increasing year by year in recent years. It has become the largest chronic liver disease globally and one of the important causes of cirrhosis and even primary liver cancer formation. The pathogenesis of NAFLD has not yet been fully clarified. Modern medicine lacks targeted clinical treatment protocols for NAFLD, and most drugs lack efficacy and have high side effects. In contrast, Traditional Chinese Medicine (TCM) has significant advantages in the treatment and prevention of NAFLD, which have been widely recognized by scholars around the world. In recent years, through the establishment of a “medicine-disease-target-pathway” network relationship, network pharmacology can explore the molecular basis of the role of medicines in disease prevention and treatment from various perspectives, predicting the pharmacological mechanism of the corresponding medicines. This approach is compatible with the holistic view and treatment based on pattern differentiation of TCM and has been widely used in TCM research. In this paper, by searching relevant databases such as PubMed, Web of Science, and Embase, we reviewed and analyzed the relevant signaling pathways and specific mechanisms of action of single Chinese medicine, Chinese medicine combinations, and Chinese patent medicine for the treatment of NAFLD in recent years. These related studies fully demonstrated the therapeutic characteristics of TCM with multi-components, multi-targets, and multi-pathways, which provided strong support for the exact efficacy of TCM exerted in the clinic. In conclusion, we believe that network pharmacology is more in line with the TCM mindset of treating diseases, but with some limitations. In the future, we should eliminate the potential risks of false positives and false negatives, clarify the interconnectivity between components, targets, and diseases, and conduct deeper clinical or experimental studies

A Watershed-Segmentation-Based Improved Algorithm for Extracting Cultivated Land Boundaries

To accurately extract cultivated land boundaries based on high-resolution remote sensing imagery, an improved watershed segmentation algorithm was proposed herein based on a combination of pre- and post-improvement procedures. Image contrast enhancement was used as the pre-improvement, while the color distance of the Commission Internationale de l´Eclairage (CIE) color space, including the Lab and Luv, was used as the regional similarity measure for region merging as the post-improvement. Furthermore, the area relative error criterion (δA), the pixel quantity error criterion (δP), and the consistency criterion (Khat) were used for evaluating the image segmentation accuracy. The region merging in Red–Green–Blue (RGB) color space was selected to compare the proposed algorithm by extracting cultivated land boundaries. The validation experiments were performed using a subset of Chinese Gaofen-2 (GF-2) remote sensing image with a coverage area of 0.12 km2. The results showed the following: (1) The contrast-enhanced image exhibited an obvious gain in terms of improving the image segmentation effect and time efficiency using the improved algorithm. The time efficiency increased by 10.31%, 60.00%, and 40.28%, respectively, in the RGB, Lab, and Luv color spaces. (2) The optimal segmentation and merging scale parameters in the RGB, Lab, and Luv color spaces were C for minimum areas of 2000, 1900, and 2000, and D for a color difference of 1000, 40, and 40. (3) The algorithm improved the time efficiency of cultivated land boundary extraction in the Lab and Luv color spaces by 35.16% and 29.58%, respectively, compared to the RGB color space. The extraction accuracy was compared to the RGB color space using the δA, δP, and Khat, that were improved by 76.92%, 62.01%, and 16.83%, respectively, in the Lab color space, while they were 55.79%, 49.67%, and 13.42% in the Luv color space. (4) Through the visual comparison, time efficiency, and segmentation accuracy, the comprehensive extraction effect using the proposed algorithm was obviously better than that of RGB color-based space algorithm. The established accuracy evaluation indicators were also proven to be consistent with the visual evaluation. (5) The proposed method has a satisfying transferability by a wider test area with a coverage area of 1 km2. In addition, the proposed method, based on the image contrast enhancement, was to perform the region merging in the CIE color space according to the simulated immersion watershed segmentation results. It is a useful attempt for the watershed segmentation algorithm to extract cultivated land boundaries, which provides a reference for enhancing the watershed algorithm

Numerical Study on Characteristics of Bedrock and Surface Failure in Mining of Shallow-Buried MCS

Coal is one of the important energy sources for industry. When it is mined, it will cause the destruction of bedrock and surface. However, it is more severe in mining shallow-buried multi coal seams (SBMCS). To better reveal the characteristics of the bedrock and surface damage, we have carried out a theoretical analysis, as well as used numerical simulations and field monitoring methods to study the surface and bedrock damage caused by the mining of SBMCS. The characteristics of bedrock and surface failure structure, settlement, and stress distribution were studied and analyzed. The findings show that the collapsed block, formed by the rupture of the overlying stratum, interacts with the surrounding rock to form large cavities and gaps, and the stress concentration occurs between them. The maximum downward vertical concentration stress is about 9.79 MPa. The mining of the lower coal seam can lead to repeated failure of the upper bedrock and goaf. The settlement of bedrock presents gradient change, and the settlement of upper bedrock is large, about 8.0 m, and the maximum settlement is 8.183 m, while that of lower bedrock is small and about 3.5–4.0 m. The weak rock stratum in the bedrock is crushed by the change stress of repeated mining, and formed a broken rock stratum. The cracks in the bedrock develop directly to the ground. On the ground, tensile cracks, compression uplift, stepped cracks, and even collapse pits are easy to cause in mining SBMCS. Affected by repeated mining, the variation of surface vertical stress is complex and disorderly in the middle of the basin, and the variation of horizontal stress is mainly concentrated on the edge of the basin. The maximum stress reaches 100 KPa, and the minimum stress is about 78 KPa. Through theoretical analysis and discussion, the size of the key blocks is directly related to the thickness and strength of the rock stratum

COVID-19 Resulting in Potential Hearing Damage of Rodents

Objectives To find out the association between the sensorineural hearing loss and coronavirus disease 2019 (COVID-19), the expression of ACE2 and TMPRSS2 in hamsters and mice was detected

Novel compound heterozygous pathogenic variants in the SLC3A1 gene in a Chinese family with cystinuria

Abstract Background Cystinuria is an autosomal recessive disorder characterized by a cystine transport deficiency in the renal tubules due to mutations in two genes: SLC3A1 and SLC7A9. Cystinuria can be classified into three forms based on the genotype: type A, due to mutations in the SLC3A1 gene; type B, due to mutations in the SLC7A9 gene; and type AB, due to mutations in both genes. Methods We report a 12-year-old boy from central China with cystine stones. He was from a non-consanguineous family that had no known history of genetic disease. A physical examination showed normal development and neurological behaviors. Whole-exome and Sanger sequencing were used to identify and verify the suspected pathogenic variants. Results The compound heterozygous variants c.898_905del (p.Arg301AlafsTer6) is located in exon5 and c.1898_1899insAT (p.Asp634LeufsTer46) is located in exon10 of SLC3A1 (NM_000341.4) were deemed responsible for type A cystinuria family. The variant c.898_905del was reported in a Japanese patient in 2000, and the variant c.1898_1899insAT is novel. Conclusion A novel pathogenic heterozygous variant pair of the SLC3A1 gene was identified in a Chinese boy with type A cystinuria, enriching the mutational spectrum of the SLC3A1 gene. We attempted to find a pattern for the association between the genotype of SLC3A1 variants and the manifestations of cystinuria in patients with different onset ages. Our findings have important implications for genetic counseling and the early clinical diagnosis of cystinuria

A risk prediction model for efficient intubation in the emergency department: A 4‐year single‐center retrospective analysis

Abstract Objective To analyze the risk factors associated with intubated critically ill patients in the emergency department (ED) and develop a prediction model by machine learning algorithms. Methods This study was conducted in an academic tertiary hospital in Hangzhou, China. Critically ill patients admitted to the ED were retrospectively analyzed from May 2018 to July 2022. The demographic characteristics, distribution of organ dysfunction, parameters for different organs’ examination, and status of mechanical ventilation were recorded. These patients were assigned to the intubation and non‐intubation groups according to ventilation support. We used the eXtreme Gradient Boosting (XGBoost) algorithm to develop the prediction model and compared it with other algorithms, such as logistic regression, artificial neural network, and random forest. SHapley Additive exPlanations was used to analyze the risk factors of intubated critically ill patients in the ED. Results Of 14,589 critically ill patients, 10,212 comprised the training group and 4377 comprised the test group; 2289 intubated patients were obtained from the electronic medical records. The mean age, mean scores of vital signs, parameters of different organs, and blood oxygen examination results differed significantly between the two groups (p < 0.05). The white blood cell count, international normalized ratio, respiratory rate, and pH are the top four risk factors for intubation in critically ill patients. Based on the risk factors in different predictive models, the XGBoost model showed the highest area under the receiver operating characteristic curve (0.84) for predicting ED intubation. Conclusions For critically ill patients in the ED, the proposed model can predict potential intubation based on the risk factors in the clinically predictive model