Association between systemic immunity-inflammation index and hypertension in US adults from NHANES 1999-2018.

Hypertension is a disease closely related to inflammation, and the systemic immunity-inflammation index (SII) is a new and easily detectable inflammatory marker. We aimed to investigate the association between SII and hypertension risk in a adult population in the US. We utilized data from the National Health and Nutrition Examination Survey spanning from 1999 to 2018, incorporating comprehensive information from adults reporting hypertension. This included details on blood pressure monitoring, complete blood cell counts, and standard biochemical results. The SII was computed as the platelet count multiplied by the neutrophil count divided by the lymphocyte count. We employed a weighted multivariate logistic regression model to examine the correlation between SII and hypertension. Subgroup analyses were conducted to explore potential influencing factors. Furthermore, smooth curve fitting and two-piecewise logistic regression analysis were employed to describe non-linear relationships and identify inflection points. This population-based study involved 44,070 adults aged 20-85 years. Following Ln-transformation of the SII, multivariable logistic regression revealed that, in a fully adjusted model, participants in the highest quartile of Ln(SII) had a 12% increased risk of hypertension compared to those in the lowest quartile, which was statistically significant (OR:1.12; 95% CI 1.01, 1.24; P < 0.001), with a P for trend = 0.019. Subgroup analysis indicated no significant interactions between Ln(SII) and specific subgroups except for the body mass index subgroup (all P for interaction > 0.05). Additionally, the association between Ln(SII) and hypertension displayed a U-shaped curve, with an inflection point at 5.89 (1000 cells/µl). Based on this research result, we found a U-shaped correlation between elevated SII levels and hypertension risk in American adults, with a inflection point of 5.89 (1000 cells)/µl). To validate these findings, larger scale prospective surveys are needed to support the results of this study and investigate potential mechanisms.

College Organizational Innovation Performance-Oriented Internal Mechanism Analysis Using Lightweight Deep Learning under Health Psychology.

The purpose is to improve employees' initiative and innovation performance and further improve the overall organizational efficiency of colleges. From the perspective of health psychology, this work analyzes the internal mechanism between leadership empowerment behavior and employee innovation performance at China Agricultural University. By introducing two intermediate variables: task-based psychological capital (PsyCap) and innovative PsyCap, this work puts forward a lightweight deep learning (DL) model. It constructs the college organizational innovation performance (OIP)-oriented internal evaluation system from four dimensions. They are personal development support, power appointment, participation in decision-making, and work guidance. Then, the proposed lightweight DL model reveals the internal relationship between employees' innovation performance and innovation factors using the questionnaire survey method. Overall, 360 questionnaires are distributed. The results show that the average values of the four dimensions (S, P, D, and G) of leadership empowerment are greater than 3, which are 4.3144, 4.3493, 4.4253, and 4.5286, respectively. S, P, D, and G represent empowerment, decision-making, communication, and innovation, respectively. The results show a high level of innovation performance in all dimensions. The finding proves that the influencing factors of employee innovation performance mainly include personal development support, empowerment, participation in decision-making, and work guidance. The effects of different dimensions vary significantly. Finally, the lightweight DL model can improve the analysis accuracy of the college OIP-oriented internal evaluation system. Therefore, college leaders should use the DL model and empowerment behavior to improve employees' psychological quality, innovation enthusiasm, and work efficiency, ultimately benefiting employees.

An Empirical Study on Talent Management Strategies of Knowledge-Based Organizations Using Entrepreneurial Psychology and Key Competence.

The empirical study reported here aims to improve the effectiveness of knowledge-based talent management in science and technology enterprises and promote the stable development of enterprises. First, the impact of entrepreneurs' psychological cognition and personal characteristics on entrepreneurial activities is analyzed based on entrepreneurial psychology. Then, the theory of key competence is introduced to study the management mode of knowledge-based talents. The advantages of talents in enterprises are sorted out through constructing the key competency model to manage talents efficiently. The technology-based enterprise M is taken as an example for analysis by the key competence model to obtain 18 key capability indexes. Through the principal component analysis of 255 employees' survey results, finally, four factors are extracted (business execution ability, team cooperation ability, strategic thinking ability, and management decision-making ability), which can reflect 68.92% of the total key competence. The average values of "business execution ability" and "team cooperation ability" in the first-level dimension of key competence index are 4.14 and 4.24, respectively, which can be regarded as the essential key competence. The investigation results of the academic qualifications of staff of M indicate that 6% of employees have a doctorate, 38% have a master's degree, 37% have a Bachelor's degree, and 19% have a junior college degree or below. Moreover, knowledge-based employees are basically satisfied with the organization and management of the company, but they are dissatisfied with the training mechanism and promotion mechanism. Therefore, enterprises should pay attention to the psychological needs of knowledge workers and the innovation of talent management. The research results are of significant value for science and technology enterprises to absorb and retain knowledge-based talents and promote the common development of enterprises and employees.

Rapid Detected and Diagnostic Assessment Vacuolating Cytotoxin A (vacA) Gene of Helicobacter pylori by Loop-Mediated Isothermal Amplification (LAMP).

The loop-mediated isothermal amplification (LAMP) assay as efficient and convenient detection method was applied to detect the vacuolating cytotoxin A (vacA) gene of Helicobacter pylori (H. pylori). The extracted genomic DNA of H. pylori, which was purified through magnetic nanoparticles (MNPs), was amplified through the LAMP reaction using designed primers. The effect of LAMP detected on H. pylori vacA gene was evaluated through agarose gel electrophoresis in a gel imaging system and fluorescence-intensity analysis after addition of fluorescent dye. 11 pathogenic bacterial strains of different species were found to be negative for vacA, while only a single positive result was obtained for H. pylori. The minimum detection limit of the vacA gene was established as 100 fg. We used the primers with specificity and sensitivity, which were designed by the specificity analysis and sensitivity analysis system. Once developed, the LAMP assay was be used to the detection of the vacA gene in the gastric juice of patients. In conclusion, the LAMP assay is an efficient and fast tool for detection of the H. pylori vacA gene, and also for direct detection of the vacA gene in the gastric juice of patients, with high sensitivity and specificity. Most importantly, the proposed detection method shows promising potential for clinical application in the future, where it can greatly reduce the difficulty of detection and also shorten detection times.

Enhanced immunotherapeutic effect of modified HPV16 E7-pulsed dendritic cell vaccine by an adeno-shRNA-SOCS1 virus.

Cervical cancer is the second most common cause of cancer-related deaths among women worldwide. However, no efficient therapy exists against cervical cancer and current treatments have several disadvantages. One possible novel approach is to develop immune-based strategies using tumor antigen-loaded dendritic cells (DCs) for the induction of cellular antitumor immunity. In this study, we created a modified HPV16 E7, HPV16mE7, to reduce its transformation activity and to enhance its antigenicity. The siRNA delivery technique was used to silence the suppressor of cytokine signaling 1 (SOCS1) gene in DCs. BM-derived DCs infected by ad-shRNA-SOCS1 were pulsed with the HPV16mE7 protein and then were transfused into mouse models bearing TC-1 tumor cells expressing HPV16 E6/E7. IFN-γ, cytokine (TNF-α, IL-12, IL-6) expression, anti-E7 antibody and cytotoxic T lymphocyte (CTL) levels were measured. The survival rate, survival days and the tumor volume of the mouse models from the different treatment groups were monitored. The data showed that the mE7-pulsed DC vaccine enhanced by adenovirus-mediated SOCS1 silencing exhibited better immunotherapeutic effect on the allografted tumor mouse models. The method by silencing SOCS1 in HPV16mE7 protein-pulsed DCs may provide a new strategy for the development of safe and effective immunotherapy for cervical cancer.