Regional and epidemiological characteristics of tuberculosis and treatment outcomes in West China.

Objective: To understand the prevalence and treatment outcome of tuberculosis in a typically regional County from 2016 to 2021, so as to provide reference and basis for the prevention and treatment of tuberculosis in this area. Methods: Descriptive epidemiological methods were used to analyze the population, time and location distribution of pulmonary tuberculosis in Dazhu County from 2016 to 2021. The incidence rates were compared by Chi-square test and trend test, time distribution combined with seasonal index analysis, and the test level was α = 0.05. Results: A total of 2,899 cases of pulmonary tuberculosis were reported in Dazhu County from 2016 to 2021, with an average annual incidence rate of 44.29/100,000 and standardized reported incidence rate was 36.77/100,000, showing a downward trend year by year (χ2 trend = 124.629, p < 0.001). A total of 955 cases of pathogen positive were reported, showing an increasing trend year by year (χ2 trend = 59.773, p < 0.001). In terms of time distribution, the incidence rate was high in autumn and winter, and September and December were the peak of the disease in the whole year, and the overall trend increased first, then decreased and once again increased (F = 5.861, p < 0.05). In regional distribution, the highest annual average reported incidence rate was in concentrated population. The incidence rate of male was higher than female in population distribution. After standardization, the overall incidence rate increased from 34 to 45 years old (χ2 trend = 6963.101, p < 0.001), and decreased after 45 years old (χ2 trend = 1104.393, p < 0.001). The occupation distribution is mainly farmers (82.75%). The overall arrival rate and cure rate of patients showed an upward trend year by year (χ2 trend = 4.306, χ2 trend = 5.772, p < 0.001). Conclusion: The incidence rate of pulmonary tuberculosis in this regional county is decreasing year by year. Male patients are higher than female patients and have certain seasonal characteristics. Attention should be paid to male, older adult, farmers and other groups, and corresponding measures should be taken to strengthen the prevention and treatment of tuberculosis in high incidence areas.

Diagnostic performance of corona virus disease 2019 chest computer tomography image recognition based on deep learning: Systematic review and meta-analysis.

BACKGROUND: To analyze the diagnosis performance of deep learning model used in corona virus disease 2019 (COVID-19) computer tomography(CT) chest scans. The included sample contains healthy people, confirmed COVID-19 patients and unconfirmed suspected patients with corresponding symptoms. METHODS: PubMed, Web of Science, Wiley, China National Knowledge Infrastructure, WAN FANG DATA, and Cochrane Library were searched for articles. Three researchers independently screened the literature, extracted the data. Any differences will be resolved by consulting the third author to ensure that a highly reliable and useful research paper is produced. Data were extracted from the final articles, including: authors, country of study, study type, sample size, participant demographics, type and name of AI software, results (accuracy, sensitivity, specificity, ROC, and predictive values), other outcome(s) if applicable. RESULTS: Among the 3891 searched results, 32 articles describing 51,392 confirmed patients and 7686 non-infected individuals met the inclusion criteria. The pooled sensitivity, the pooled specificity, positive likelihood ratio, negative likelihood ratio and the pooled diagnostic odds ratio (OR) is 0.87(95%CI [confidence interval]: 0.85, 0.89), 0.85(95%CI: 0.82, 0.87), 6.7(95%CI: 5.7, 7.8), 0.14(95%CI: 0.12, 0.16), and 49(95%CI: 38, 65). Further, the AUROC (area under the receiver operating characteristic curve) is 0.94(95%CI: 0.91, 0.96). Secondary outcomes are specific sensitivity and specificity within subgroups defined by different models. Resnet has the best diagnostic performance, which has the highest sensitivity (0.91[95%CI: 0.87, 0.94]), specificity (0.90[95%CI: 0.86, 0.93]) and AUROC (0.96[95%CI: 0.94, 0.97]), according to the AUROC, we can get the rank Resnet > Densenet > VGG > Mobilenet > Inception > Effficient > Alexnet. CONCLUSIONS: Our study findings show that deep learning models have immense potential in accurately stratifying COVID-19 patients and in correctly differentiating them from patients with other types of pneumonia and normal patients. Implementation of deep learning-based tools can assist radiologists in correctly and quickly detecting COVID-19 and, consequently, in combating the COVID-19 pandemic.

Effects of potassium fertilization on potato starch physicochemical properties.

Potato starch serves as an excellent raw material or food additive in the food industry. With the advancement of the potato staple food strategy in China, improving the potato starch yield and quality has attracted more and more attention. Potassium is an essential nutrient for potato due to its direct effects on the yield and quality of potato tubers. Here, the effects of three different potassium levels on potato starch physicochemical properties were evaluated by field experiments. With increasing potassium fertilization rates, the amylose content, phosphorus content and particle size decreased, thereby resulting in low gelatinization temperature, breakdown and setback viscosity, and high swelling power, relative crystallinity and transparency. Our study indicated that enhanced potassium fertilization improved the resistance to heat and shear stress and decreased the retrogradation of starch, and the 270 kg/ha potassium fertilization rate could obtain the highest tuber and starch production with desirable starch physicochemical properties. The integrated results also provide some novel insights into the management of the fertilization conditions to obtain native starches with special properties.

[Effects of selenite addition on selenium absorption, root morphology and physiological characteristics of rape seedlings].

Abstract: The rape (Brassica napus L. cv. Xiangnongyou 571) was chosen as the experimental material to undergo solution cultivation at seedling stage to investigate the effects of selenite addition on the selenium (Se) absorption and distribution, root morphology and physiological characteristics of rape seedlings. The results showed that the bioaccumulation ability of Se decreased significantly with increasing the Se application rate, but the Se distribution coefficient remained around 0.9 with no significant influence. The application of 10 µmol . L-1 selenite stimulated the growth of rape seedlings through improving the root physiological characteristics and root morphology significantly, including significantly increasing the production of superoxide radical (O2∙-) rate and the activities of superoxide dismutase (SOD), peroxidase (POD) and fungal catalase (CAT) in the root system, which resulted in a reduction of the lipids peroxidation (MDA) content as much as 26.0%, consequently increasing the root activity as much as 17.4%. The promoting degrees of selenite on root morphological parameters were from strong to weak in such a tendency: root volume > total surface area > number of root forks > total root length > number of root tips > average diameter. However, such positive effects had no significant difference with those in treatment with 1 µmol . L-1 selenite, indicating that small amounts (≤ 10 Lmol . L-1) of selenite were able to increase the activity of antioxidant enzymes and reduce the content of MDA in root system, which could increase root activity and improve root morphology, hence increased the biomass of rape seedlings.