Primate-Specific DAZ Regulates Translation of Cell Proliferation-Related mRNAs and is Essential for Maintenance of Spermatogonia.

Primate-specific DAZ (deleted in azoospermia) has evolved in the azoospermia factor c (AZFc) locus on the Y chromosome. Loss of DAZ is associated with azoospermia in patients with deletion of the AZFc region (AZFc_del). However, the molecular mechanisms of DAZ in spermatogenesis remain uncertain. In this study, the molecular mechanism of DAZ is identified, which is unknown since it is identified 40 years ago because of the lack of a suitable model. Using clinical samples and cell models, it is shown that DAZ plays an important role in spermatogenesis and that loss of DAZ is associated with defective proliferation of c-KIT-positive spermatogonia in patients with AZFc_del. Mechanistically, it is shown that knockdown of DAZ significantly downregulated global translation and subsequently decreased cell proliferation. Furthermore, DAZ interacted with PABPC1 via the DAZ repeat domain to regulate global translation. DAZ targeted mRNAs that are involved in cell proliferation and cell cycle phase transition. These findings indicate that DAZ is a master translational regulator and essential for the maintenance of spermatogonia. Loss of DAZ may result in defective proliferation of c-KIT-positive spermatogonia and spermatogenic failure.

Disruption of metazoan gene regulatory networks in cancer alters the balance of co-expression between genes of unicellular and multicellular origins.

BACKGROUND: Metazoans inherited genes from unicellular ancestors that perform essential biological processes such as cell division, metabolism, and protein translation. Multicellularity requires careful control and coordination of these unicellular genes to maintain tissue integrity and homeostasis. Gene regulatory networks (GRNs) that arose during metazoan evolution are frequently altered in cancer, resulting in over-expression of unicellular genes. We propose that an imbalance in co-expression of unicellular (UC) and multicellular (MC) genes is a driving force in cancer. RESULTS: We combine gene co-expression analysis to infer changes to GRNs in cancer with protein sequence conservation data to distinguish genes with UC and MC origins. Co-expression networks created using RNA sequencing data from 31 tumor types and normal tissue samples are divided into modules enriched for UC genes, MC genes, or mixed UC-MC modules. The greatest differences between tumor and normal tissue co-expression networks occur within mixed UC-MC modules. MC and UC genes not commonly co-expressed in normal tissues form distinct co-expression modules seen only in tumors. The degree of rewiring of genes within mixed UC-MC modules increases with tumor grade and stage. Mixed UC-MC modules are enriched for somatic mutations in cancer genes, particularly amplifications, suggesting an important driver of the rewiring observed in tumors is copy number changes. CONCLUSIONS: Our study shows the greatest changes to gene co-expression patterns during tumor progression occur between genes of MC and UC origins, implicating the breakdown and rewiring of metazoan gene regulatory networks in cancer development and progression.

Corrigendum: Assessing heterogeneity of patient and health system delay among TB in a population with internal migrants in China.

[This corrects the article DOI: 10.3389/fpubh.2024.1354515.].

Spatial pattern of isoniazid-resistant tuberculosis and its associated factors among a population with migrants in China: a retrospective population-based study.

Background: Isoniazid-resistant, rifampicin-susceptible tuberculosis (Hr-TB) globally exhibits a high prevalence and serves as a potential precursor to multidrug-resistant tuberculosis (MDR-TB). Recognizing the spatial distribution of Hr-TB and identifying associated factors can provide strategic entry points for interventions aimed at early detection of Hr-TB and prevention of its progression to MDR-TB. This study aims to analyze spatial patterns and identify socioeconomic, demographic, and healthcare factors associated with Hr-TB in Shanghai at the county level. Method: We conducted a retrospective study utilizing data from TB patients with available Drug Susceptible Test (DST) results in Shanghai from 2010 to 2016. Spatial autocorrelation was explored using Global Moran's I and Getis-Ord Gi∗ statistics. A Bayesian hierarchical model with spatial effects was developed using the INLA package in R software to identify potential factors associated with Hr-TB at the county level. Results: A total of 8,865 TB patients with DST were included in this analysis. Among 758 Hr-TB patients, 622 (82.06%) were new cases without any previous treatment history. The drug-resistant rate of Hr-TB among new TB cases in Shanghai stood at 7.20% (622/8014), while for previously treated cases, the rate was 15.98% (136/851). Hotspot areas of Hr-TB were predominantly situated in southwestern Shanghai. Factors positively associated with Hr-TB included the percentage of older adult individuals (RR = 3.93, 95% Crl:1.93-8.03), the percentage of internal migrants (RR = 1.35, 95% Crl:1.15-1.35), and the number of healthcare institutions per 100 population (RR = 1.17, 95% Crl:1.02-1.34). Conclusion: We observed a spatial heterogeneity of Hr-TB in Shanghai, with hotspots in the Songjiang and Minhang districts. Based on the results of the models, the internal migrant population and older adult individuals in Shanghai may be contributing factors to the emergence of areas with high Hr-TB notification rates. Given these insights, we advocate for targeted interventions, especially in identified high-risk hotspots and high-risk areas.

Spatial Heterogeneity of Nontuberculous Mycobacterial Pulmonary Disease in Shanghai: Insights from a Ten-Year Population-Based Study.

OBJECTIVE: To investigate the spatial heterogeneity of nontuberculous mycobacterial pulmonary disease (NTM-PD) in Shanghai. METHODS: A population-based retrospective study was conducted using presumptive pulmonary tuberculosis surveillance data of Shanghai between 2010 and 2019. The study described the spatial distribution of NTM-PD notification rates, employing hierarchical Bayesian mapping for high-risk areas and the Getis-Ord Gi* statistic to identify hot spots and explore associated factors. RESULTS: Of 1652 NTM-PD cases, the most common species was Mycobacterium kansasii complex (MKC) (41.9%), followed by Mycobacterium avium complex (MAC) (27.1%) and Mycobacterium abscessus complex (MABC) (16.2%). MKC-PD patients were generally younger males with a higher incidence of pulmonary cavities, while MAC-PD patients were more often farmers or had a history of tuberculosis treatment. MKC-PD hot spots were primarily located in the areas alongside the Huangpu River, while MAC-PD hot spots were mainly in the western agricultural areas. Patients with MKC-PD and MAC-PD exhibited a higher risk of spatial clustering compared to those with MABC-PD. CONCLUSIONS: Different types of NTM-PD exhibit distinct patterns of spatial clustering and are associated with various factors. These findings underscore the importance of environmental and host factors in the epidemic of NTM-PD.

The relationship between dietary inflammatory index and metabolic syndrome and its components: a case study in Kashi urban, Xinjiang.

Introduction: This paper examines the association between the dietary inflammatory index (DII) and the risk of metabolic syndrome (MS) and its components among Uygur adults in Kashi, Xinjiang. Methods: The study used the multi-stage random cluster sampling method to investigate the adult residents of Uighu aged over 18 years old in one county and one township/street of three cities in Kashi between May and June 2021. All dietary data collected were analyzed for energy and nutrient intake with a nutritional analysis software, followed by a calculation of DII. Logistic regression was used to estimate the association between DII and the risks of MS and its components. Results: The maximum DII value across our 1,193 respondents was 4.570 to 4.058, with an average value of 0.256. When we analyzed the DII as a continuous variable, we determined the anti-inflammatory diet has been identified as a mitigating factor for metabolic syndrome (OR = 0.586, 95% CI = 0.395-0.870), obesity (OR = 0.594, 95% CI = 0.395-0.870), elevated fasting glucose levels (OR = 0.422, 95% CI = 0.267-0.668), and hypertension (OR = 0.698, 95% CI = 0.488-0.996). When the model was adjusted by sex, age, and occupation, we found a significant correlation between high- and low-density lipoproteinemia and DII (OR = 1.55, 95% CI = 1.040-2.323). The present study identified four distinct dietary patterns among the population under investigation. There was a linear trend in the incidence of MS and hypertension across low, middle, and high levels of fruits and milk dietary pattern model (p = 0.027; p = 0.033), within this dietary pattern may serve as protective factors against MS and hypertension, suggesting that fruits and milk within this dietary pattern may serve as protective factors against MS and hypertension. And the linear trend in the incidence of elevated fasting glucose and obesity across the low, medium, and high scores of meet and eggs dietary pattern (p = 0.006; p < 0.001), suggest that a diet rich in meat may potentially contribute to an increased risk of developing elevated fasting glucose levels and obesity. An observed linear trend in the incidence rate of high fasting blood glucose across low, moderate, and high scores of dried fruits and nuts dietary pattern (p = 0.014), indicating that increased consumption of nuts acted as a protective factor against elevated fasting blood glucose levels and contributed to their reduction. Discussion: The dietary inflammation index was integrated with the findings from the study on the dietary patterns of the sampled population, revealing that an anti-inflammatory diet demonstrated a protective effect against metabolic syndrome, obesity, high fasting blood glucose, and hypertension in this specific population. laying the foundation for further research.

Assessing heterogeneity of patient and health system delay among TB in a population with internal migrants in China.

Backgrounds: The diagnostic delay of tuberculosis (TB) contributes to further transmission and impedes the implementation of the End TB Strategy. Therefore, we aimed to describe the characteristics of patient delay, health system delay, and total delay among TB patients in Shanghai, identify areas at high risk for delay, and explore the potential factors of long delay at individual and spatial levels. Method: The study included TB patients among migrants and residents in Shanghai between January 2010 and December 2018. Patient and health system delays exceeding 14 days and total delays exceeding 28 days were defined as long delays. Time trends of long delays were evaluated by Joinpoint regression. Multivariable logistic regression analysis was employed to analyze influencing factors of long delays. Spatial analysis of delays was conducted using ArcGIS, and the hierarchical Bayesian spatial model was utilized to explore associated spatial factors. Results: Overall, 61,050 TB patients were notified during the study period. Median patient, health system, and total delays were 12 days (IQR: 3-26), 9 days (IQR: 4-18), and 27 days (IQR: 15-43), respectively. Migrants, females, older adults, symptomatic visits to TB-designated facilities, and pathogen-positive were associated with longer patient delays, while pathogen-negative, active case findings and symptomatic visits to non-TB-designated facilities were associated with long health system delays (LHD). Spatial analysis revealed Chongming Island was a hotspot for patient delay, while western areas of Shanghai, with a high proportion of internal migrants and industrial parks, were at high risk for LHD. The application of rapid molecular diagnostic methods was associated with reduced health system delays. Conclusion: Despite a relatively shorter diagnostic delay of TB than in the other regions in China, there was vital social-demographic and spatial heterogeneity in the occurrence of long delays in Shanghai. While the active case finding and rapid molecular diagnosis reduced the delay, novel targeted interventions are still required to address the challenges of TB diagnosis among both migrants and residents in this urban setting.

Transmission of fluoroquinolones resistance among multidrug-resistant tuberculosis in Shanghai, China: a retrospective population-based genomic epidemiology study.

Fluoroquinolones (FQ) are essential for the treatment of multidrug-resistant tuberculosis (MDR-TB). The FQ resistance (FQ-R) rate in MDR-TB in China and its risk factors remain poorly understood. We conducted a retrospective, population-based genomic epidemiology study of MDR-TB patients in Shanghai, China, from 2009 to 2018. A genomic cluster was defined as strains with genetic distances ≤ 12 single nucleotide polymorphisms. The transmitted FQ-R was defined as the same FQ resistance-conferring mutations shared by ≥ 2 strains in a genomic cluster. We used multivariable logistic regression analysis to identify the risk factors for drug resistance. Among the total 850 MDR-TB patients included in the study, 72.8% (619/850) were male, the median age was 39 (interquartile range 28, 55) years, 52.7% (448/850) were migrants, and 34.5% (293/850) were previously treated patients. Most of the MDR-TB strains belong to the Beijing lineage (91.7%, 779/850). Overall, the genotypic resistance rate of FQ was 34.7% (295/850), and 47.1% (139/295) FQ-R patients were in genomic clusters, of which 98 (33.2%, 98/295) were presumed as transmitted FQ-R. Patients with treatment-naïve (aOR = 1.84; 95% CI: 1.09, 3.16), diagnosed in a district-level hospital (aOR = 2.69; 95% CI: 1.56, 4.75), and streptomycin resistance (aOR = 3.69; 95% CI: 1.65, 9.42) were significantly associated with the transmission of FQ-R. In summary, the prevalence of FQ-R among MDR-TB patients was high in Shanghai, and at least one-third were transmitted. Enforced interventions including surveillance of FQ drug susceptibility testing and screening among MDR-TB before initiation of treatment were urgently needed.

Multi-scenario investment forecast of new energy projects based on multiple linear regression and comprehensive evaluation model of differentiated project priorities.

As China's resource shortage and environmental pollution intensify, the demand for new energy and electric energy substitution is becoming higher and higher. Accurately predicting the investment scale of China's new energy projects is of great practical significance for improving the efficiency of resource allocation and economically meeting energy demand. This paper builds a scientific and precise investment model for new energy projects from both macro and micro perspectives. First, from a macro perspective, considering macro indicators such as the external environment and internal economy, an annual total investment forecast model based on multiple linear regression is constructed, in order to predict the annual total investment scale of new energy investment entities and achieve preliminary accurate investment; second, designed the evaluation index system of different project priorities from three perspectives of external environment, internal development of enterprises and social development, and constructed the comprehensive weight design method based on AN-EWM and the comprehensive evaluation method of TOPSIS, in order to realize the priority of differentiated projects. Sorting; finally, a new energy project located in a city in northern China is selected as the research subject, and a multi-scenario example analysis is carried out. The results show that the new energy project investment scale index system constructed in this paper can effectively evaluate the investment capacity of the main body of the new energy project, and can better predict the total investment of the new energy investment project, so that the deviation rate can be controlled within 5 %, and the priority evaluation model constructed in this paper can provide a complete calculation method and a reference method for the judgement of the investment priority, which can promote accurate investment.

SDBA: Score Domain-Based Attention for DNA N4-Methylcytosine Site Prediction from Multiperspectives.

In tasks related to DNA sequence classification, choosing the appropriate encoding methods is challenging. Some of the methods encode sequences based on prior knowledge that limits the ability of the model to obtain multiperspective information from the sequences. We introduced a new trainable ensemble method based on the attention mechanism SDBA, which stands for Score Domain-Based Attention. Unlike other methods, we fed the task-independent encoding results into the models and dynamically ensembled features from different perspectives using the SDBA mechanism. This approach allows the model to acquire and weight sequence features voluntarily. SDBA is conceptually general and empirically powerful. It has achieved new state-of-the-art results on the benchmark data sets associated with DNA N4-methylcytosine site prediction.

Genotypic and spatial analysis of transmission dynamics of tuberculosis in Shanghai, China: a 10-year prospective population-based surveillance study.

Background: With improved tuberculosis (TB) control programs, the incidence of TB in China declined dramatically over the past few decades, but recently the rate of decrease has slowed, especially in large cities such as Shanghai. To help formulate strategies to further reduce TB incidence, we performed a 10-year study in Songjiang, a district of Shanghai, to delineate the characteristics, transmission patterns, and dynamic changes of the local TB burden. Methods: We conducted a population-based study of culture-positive pulmonary TB patients diagnosed in Songjiang during 2011-2020. Genomic clusters were defined with a threshold distance of 12-single-nucleotide-polymorphisms based on whole-genome sequencing, and risk factors for clustering were identified by logistic regression. Transmission inference was performed using phybreak. The distances between the residences of patients were compared to the genomic distances of their isolates. Spatial patient hotspots were defined with kernel density estimation. Findings: Of 2212 enrolled patients, 74.7% (1652/2212) were internal migrants. The clustering rate (25.2%, 558/2212) and spatial concentrations of clustered and unclustered patients were unchanged over the study period. Migrants had significantly higher TB rates but less clustering than residents. Clustering was highest in male migrants, younger patients and both residents and migrants employed in physical labor. Only 22.1% of transmission events occurred between residents and migrants, with residents more likely to transmit to migrants. The clustering risk decreased rapidly with increasing distances between patient residences, but more than half of clustered patient pairs lived ≥5 km apart. Epidemiologic links were identified for only 15.6% of clustered patients, mostly in close contacts. Interpretation: Although some of the TB in Songjiang's migrant population is caused by strains brought by infected migrants, local, recent transmission is an important driver of the TB burden. These results suggest that further reductions in TB incidence require novel strategies to detect TB early and interrupt urban transmission. Funding: Shanghai Municipal Science and Technology Major Project (ZD2021CY001), National Natural Science Foundation of China (82272376), National Research Council of Science and Technology Major Project of China (2017ZX10201302-006).

Correlation of drug exposure and bacterial susceptibility with treatment response for Mycobacterium avium complex lung disease: protocol for a prospective observational cohort study.

INTRODUCTION: The burden of Mycobacterium avium complex (MAC) lung disease is increasing globally and treatment outcome is in general poor. Therapeutic drug monitoring has the potential to improve treatment outcome by ensuring adequate drug exposure. However, very limited population-based studies exist for MAC lung disease. This study aims to describe the distribution of drug exposure for key antimycobacterial drugs at population level, and to analyse them in relationship to treatment outcome in patients with MAC lung disease. METHODS AND ANALYSIS: A prospective cohort aiming to include 100 adult patients diagnosed with and treated for MAC lung disease will be conducted in Shanghai Pulmonary Hospital, China. Blood samples will be collected after 1 month MAC treatment for measurement of macrolides, rifamycin, ethambutol, amikacin and/or fluoroquinolones, using a validated liquid-chromatography tandem mass spectrometry method. Respiratory samples will be collected at inclusion and once every 3 months for mycobacterial culture until treatment completion. Minimum inhibitory concentration (MIC) determination will be performed using a commercial broth microdilution plate. In addition to mycobacterial culture, disease severity and clinical improvement will be assessed from the perspective of lung function, radiological presentation and self-reported quality of life. Whole genome sequencing will be performed for any longitudinal isolates with significant change of MIC to explore the emergence of drug resistance-conferring mutations. The relationship between drug exposure and treatment outcome will be analysed and potential confounders will be considered for adjustment in multivariable models. Meanwhile, the associations between drug exposure in relation to MIC and markers of treatment response will be explored using Cox proportional hazards or binary logistic regression models, as appropriate. ETHICS AND DISSEMINATION: This study has been approved by the ethics committee of Shanghai Pulmonary Hospital (No. K22-149Z). Written and oral informed consent will be obtained from all participants. The study results will be submitted to a peer-reviewed journal. TRIAL REGISTERATION NUMBER: NCT05824988.

Highly efficient electroluminescence from SnO2 nanocrystals and Er3+ co-doped silica thin film via introducing Ca2.

Efficient and stable near-infrared silicon-based light source is a challenge for future optoelectronic integration and interconnection. In this paper, alkaline earth metal Ca2+ doped SiO2-SnO2: Er3+ films were prepared by sol-gel method. The oxygen vacancies introduced by the doped Ca2+ significantly increase the near-infrared luminescence intensity of Er3+ ions. It was found that the doping concentration of Sn precursors not only modulate the crystallinity of SnO2 nanocrystals but also enhance the luminescence performance of Er3+ ions. The stable electroluminescent devices based on SiO2-SnO2: Er3+/Ca2+ films exhibit the power efficiency as high as 1.04×10-2 with the external quantum efficiency exceeding 10%.

Alkaline earth metal ion doping to enhance the light emission from Er3+:SnO2 nanocrystal Co-doped silica films.

Alkaline earth metal ions (Mg2+, Ca2+, Sr2+) have been introduced into Er3+:SnO2 nanocrystal co-doped silica thin films fabricated by a sol-gel method combined with a spin-coating technique. It is found that the incorporation of alkaline earth metal ions can enhance the light emission from Er3+ at the wavelength around 1540 nm and the strongest enhancement is observed in samples doped with 5 mol% Sr2+ ions. Based on X-ray diffraction, X-ray photoelectron spectroscopy and other spectroscopic measurements, the improved light emission can be attributed to more oxygen vacancies, better crystallinity and a stronger cross-relaxation process with the introduction of alkaline earth metal ions.

Silver(I)-Catalyzed Tandem Reaction of Enynones and 4-Alkenyl Isoxazoles: Synthesis of 2-(Furan-2-yl)-1,2-dihydropyridines.

Silver(I)-catalyzed tandem reaction of enynones with 4-alkenyl isoxazoles provides access to 2-(furan-2-yl)-1,2-dihydropyridines. No competitive cyclopropanation of alkenes and O-H insertion via (2-furyl)carbene complexes were observed. The cascade reaction proceeds via the formation of (2-furyl)metal carbene intermediate, the N-O bond cleavage of 4-alkenyl isoxazoles/rearrangement, subsequent 6π electrocyclic reaction, and [1,5] H-shift. The successive construction of both 1,2-dihydropyridine skeleton and furan frame has been achieved in the one-pot reaction. A broad range of readily available enynones and 4-alkenyl isoxazoles are suitable to this protocol; however, when R3 is the alkyl group such as n-Bu and Me, a complicated mixture was generated without the desired products. In addition, in the case of R4 = bulky group such as R3'SiOCH2, the reaction gave an in situ oxo-product of (2-furyl)silver carbene. An atom-economic strategy for the synthesis of 2-(furan-2-yl)-1,2-dihydropyridines has been established.

An interpretable hybrid predictive model of COVID-19 cases using autoregressive model and LSTM.

The Coronavirus Disease 2019 (COVID-19) has had a profound impact on global health and economy, making it crucial to build accurate and interpretable data-driven predictive models for COVID-19 cases to improve public policy making. The extremely large scale of the pandemic and the intrinsically changing transmission characteristics pose a great challenge for effectively predicting COVID-19 cases. To address this challenge, we propose a novel hybrid model in which the interpretability of the Autoregressive model (AR) and the predictive power of the long short-term memory neural networks (LSTM) join forces. The proposed hybrid model is formalized as a neural network with an architecture that connects two composing model blocks, of which the relative contribution is decided data-adaptively in the training procedure. We demonstrate the favorable performance of the hybrid model over its two single composing models as well as other popular predictive models through comprehensive numerical studies on two data sources under multiple evaluation metrics. Specifically, in county-level data of 8 California counties, our hybrid model achieves 4.173% MAPE, outperforming the composing AR (5.629%) and LSTM (4.934%) alone on average. In country-level datasets, our hybrid model outperforms the widely-used predictive models such as AR, LSTM, Support Vector Machines, Gradient Boosting, and Random Forest, in predicting the COVID-19 cases in Japan, Canada, Brazil, Argentina, Singapore, Italy, and the United Kingdom. In addition to the predictive performance, we illustrate the interpretability of our proposed hybrid model using the estimated AR component, which is a key feature that is not shared by most black-box predictive models for COVID-19 cases. Our study provides a new and promising direction for building effective and interpretable data-driven models for COVID-19 cases, which could have significant implications for public health policy making and control of the current COVID-19 and potential future pandemics.

Temperature Dependent Hydrogen Bond Toward High Emission in an Emerging Indium-Based Perovskite.

Low-dimensional organic-inorganic hybrid perovskites (OIHPs) with broadband emission attract immense scientific interest due to their potential application for the next generation of solid-state lighting. However, due to low exciton utilization, organic cations generally adjust structure rather than contribute the band edge to affect optical properties. Based on this, OIHPs are usually allowed to obtain a low photoluminescence quantum yield (PLQY). Herein, a good charge transfer carrier (p-phenylenediamine, PPDA) as organic cation is rationally employed and a novel indium-based perovskite is synthesized. By coupling with H2 O molecules, a strong interaction between organic and inorganic components is realized by hydrogen bonding, which has good transportability and greatly improves the exciton utilization. The regions of hydrogen bonding show high electron mobility, combined with the induced recombination center, improving the progress of charge relaxation. As a result, the regulation of hydrogen bond strength based on the microstructure optimization directly determines the optical emission intensity, realizing nearly 100% PLQY. Further, the polyhydrogen bond structure makes each component a stronger interaction, showing high stability in polar, organic, and acidic solvent, as well as long-term storing, which represents one of the highest overall performances for lighting in OIHPs.

Dialogic communication on local government social media during the first wave of COVID-19: Evidence from the health commissions of prefecture-level cities in China.

Although some scholars have explored the level and determinants of Dialogic Communication on Government Social Media (DCGSM), none have conducted their studies in the context of public crisis. The current study contributes to the understanding on DCGSM by 16,822 posts crawled from the official Sina Weibo accounts of 104 Chinese health commissions in prefecture-level cities during the first wave of the COVID-19 pandemic. Results show that Chinese local government agencies have great variations in their DCGSM during the pandemic and the overall performance is poor. Furthermore, Chinese local governments prefer to conserve visitors and generate return visits, rather than dialogic loops development and the usefulness of information enhancement. The findings suggest that both public pressure and peer pressure contribute to the DCGSM of Chinese local governments during the public health crisis. In addition, the effect of public pressure is stronger than that of the peer pressure, indicating that local government agencies have experienced more demand-pull DCGSM.

Predicting COVID-19 vaccination intentions: the roles of threat appraisal, coping appraisal, subjective norms, and negative affect.

BACKGROUND: As a new disease, communities possess little natural immunity to COVID-19 and vaccines are considered critical to preventing and reducing the incidence of severe illness. This study, inspired by Protection Motivation Theory (PMT), examines the relationship between citizens' threat appraisal, coping appraisal, subjective norms, negative affect, and their COVID-19 vaccination intentions. METHODS: A sample of 340 citizens from two main cities in Mainland China, Xi'an and Wuxi, was used for data analysis. Structural Equation Modeling (SEM) was employed with latent and observed variables to test hypotheses. Data were analyzed using AMOS 24.0. RESULTS: Several findings extend current understanding. Firstly, our proposed model explains 73% of the variance in vaccination intentions. Secondly, perceived severity only indirectly shapes COVID-19 vaccination intentions through negative affect. Thirdly, negative affect and response costs are negatively related to COVID-19 vaccination intentions. Finally, Perceived probability, subjective norms, response efficacy and self-efficacy are positively related to COVID-19 vaccination intentions; among them, self-efficacy contributes the most, followed by response efficacy and subjective norms, and lastly perceived probability. CONCLUSION: Theoretically, this study increases current understanding about subjective norms and affective responses. We provoke a certain amount of thought about the role of affect response in relation to threat appraisal and vaccination intentions. Specifically, governments must be vigilant that citizens' negative affect, such as fear, may cause vaccine hesitation.

Experimental observations on metal-like carrier transport and Mott hopping conduction behaviours in boron-doped Si nanocrystal multilayers.

Studies on the carrier transport characteristics of semiconductor nanomaterials are the important and interesting issues which are helpful for developing the next generation of optoelectronic devices. In this work, we fabricate B-doped Si nanocrystals/SiO2multilayers by plasma enhanced chemical vapor deposition with subsequent high temperature annealing. The electronic transport behaviors are studied via Hall measurements within a wide temperature range (30-660 K). It is found that when the temperature is above 300 K, all the B-doped Si nanocrystals with the size near 4.0 nm exhibit the semiconductor-like conduction characteristics, while the conduction of Si nanocrystals with large size near 7.0 nm transforms from semiconductor-like to metal-like at high B-doping ratios. The critical carrier concentration of conduction transition can reach as high as 2.2 × 1020cm-3, which is significantly higher than that of bulk counterpart and may be even higher for the smaller Si nanocrystals. Meanwhile, the Mott variable-range hopping dominates the carrier transport when the temperature is below 100 K. The localization radius of carriers can be regulated by the B-doping ratios and Si NCs size, which is contributed to the metallic insulator transition.