Guidelines and recommendations from public health authorities related to face masks have been essential in containing the COVID-19 pandemic. We assessed the prevalence and correlates of mask usage ...during the pandemic.
We examined a total of 13,723,810 responses to a daily cross-sectional online survey in 38 countries of people who completed from April 23, 2020 to October 31, 2020 and reported having been in public at least once during the last 7 days. The outcome was individual face mask usage in public settings, and the predictors were country fixed effects, country-level mask policy stringency, calendar time, individual sociodemographic factors, and health prevention behaviors. Associations were modeled using survey-weighted multivariable logistic regression.
Mask-wearing varied over time and across the 38 countries. While some countries consistently showed high prevalence throughout, in other countries mask usage increased gradually, and a few other countries remained at low prevalence. Controlling for time and country fixed effects, sociodemographic factors (older age, female gender, education, urbanicity) and stricter mask-related policies were significantly associated with higher mask usage in public settings. Crucially, social behaviors considered risky in the context of the pandemic (going out to large events, restaurants, shopping centers, and socializing outside of the household) were associated with lower mask use.
The decision to wear a face mask in public settings is significantly associated with sociodemographic factors, risky social behaviors, and mask policies. This has important implications for health prevention policies and messaging, including the potential need for more targeted policy and messaging design.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Healthcare recommender system (HRS) has shown the great potential of targeting medical experts or patients, and plays a key role in improving an individual's health by providing insightful ...recommendations. The HRSs generate recommendations based on a successful and widely applied method known as collaborative filtering (CF). Despite its success, the CF suffers from data sparsity and cold-start problem, which results in the poor quality of recommendations. In particular, it is a great challenge to seeking information relevant to patients' condition, and understanding the medical terms and relationships between them in HRSs. To address these problems, we design a novel collaborative variational deep learning model (CVDL) to exploit multi-sourced information for providing appropriate healthcare recommendations in primary care service. CVDL employs additional variational autoencoder (VAE) to learn deep latent representations for item contents (the description of primary care doctors) in latent space, instead of observation space through an inference network. Meanwhile, the CVDL extracts latent user (patient) features by incorporating user profile in a VAE neural network. Therefore, the CVDL can learn better implicit relationships between items and users from item content, user profile, and rating matrix. In addition, a Stochastic Gradient Variational Bayes (SGVB) approach is proposed to calculate the maximum posterior estimates for learning model parameters. The experiments conducted on three datasets have indicated that our method significantly outperforms the state-of-the-art hybrid CF methods.
Chitooligosaccharide is beneficial for inhibiting dyslipidemia and reducing atherosclerotic and hyperlipidemic risk. The purpose of this study was to investigate the cholesterol-regulating effects ...and potential mechanisms of Chitooligosaccharide tablets (CFTs) in high-fat diet-induced hyperlipidemic rats. The results revealed that CFTs can regulate serum lipid levels in hyperlipidemic rats in a dosage-dependent manner. Synchronously, gene expressions related to cholesterol excretion were upregulated in a dosage-dependent manner, including cholesterol 7α-hydroxylase (CYP7A1), liver X receptor α (LXRA), peroxisome proliferation-activated receptor-α (PPARα) and low-density lipoprotein receptor (LDLR), whereas cholesterol synthetic gene expressions including 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) and sterol-responsive element binding protein-2 (SREBP2) were reduced. This work highlights that CFTs have potential as natural products to prevent and treat metabolic hyperlipidemia syndrome, probably due to the reduction of cholesterol biosynthesis and through cholesterol elimination; they also improve the pathological changes of liver tissue in rats, alleviate liver damage, maintain normal lipid metabolism in the liver, ameliorate hepatic glycolipid disorders and accelerate TC operation, and reduce blood lipid levels.
Obesity is a global disease that causes many metabolic disorders. However, effective agents for the prevention or treatment of obesity remain limited. This study investigated the anti-obesity effect ...and mechanism of chitosan oligosaccharide capsules (COSCs) on rats suffering from obesity induced by a high-fat diet (HFD). After the eight-week administration of COSCs on obese rats, the body weight gain, fat/body ratio, and related biochemical indices were measured. The hepatic expressions of the leptin signal pathway (JAK2-STAT3) and gene expressions of adipogenesis-related targets were also determined. Our data showed that COSCs can regulate body weight gain, lipids, serum alanine aminotransferase, and aspartate aminotransferase, as well as upregulate the hepatic leptin receptor-b (LepRb) and the phosphorylation of JAK2 and STAT3. Meanwhile, marked increased expressions of liver sterol regulatory element-binding protein-1c, fatty acid synthase, acetyl-CoA carboxylase, 3-hydroxy-3-methylglutaryl-CoA reductase, adiponectin, adipose peroxisome proliferator-activated receptor γ, CCAAT-enhancer binding protein α, adipose differentiation-related protein, and SREBP-1c were observed. The results suggested that COSCs activate the JAK2-STAT3 signaling pathway to alleviate leptin resistance and suppress adipogenesis to reduce lipid accumulation. Thus, they can potentially be used for obesity treatment.
The objective of our study was to evaluate the utility of Rho/Z on dual-energy computed tomography (DECT) for the differentiation of osteoblastic metastases (OBMs) from bone islands (BIs).
DECT ...images of 110 patients with malignancies were collected. The effective atomic number (Z), electron density (Rho), dual energy index (DEI), and regular CT (rCT) values were measured by two observers. Independent-sample
-test was used to compare these values between OBMs and BIs. The diagnostic performance was assessed by receiver operating characteristic (ROC) analysis and the cutoff values were evaluated according to ROC curves.
A total of 205 OBMs and 120 BIs were included. The mean values of Z, Rho, DEI, and rCT of OBMs were significantly lower than those of BIs, whereas the standard deviation values were higher than those of BIs (all
≤ 0.05). ROC analysis showed that 11.86 was the optimal cutoff value for Z, rendering an area under the ROC curve (AUC) of 0.91, with a sensitivity of 91.2% and a specificity of 82.5%.
DECT can provide quantitative values of Z, Rho, and DEI and has good performance in differentiating between OBMs and BIs.
Feeding intolerance (FI) is a common disease in preterm infants, often causing a delay in individual development. Gut microbiota play an important role in nutrient absorption and metabolism of ...preterm infants. To date, few studies have focused on the community composition of gut microbiota of preterm infants with feeding intolerance. In this study, we collected fecal samples from 41 preterm infants diagnosed with feeding intolerance and 29 preterm infants without feeding intolerance, at three specific times during the development and prevalence of feeding intolerance (after birth, when feeding intolerance was diagnosed, after feeding intolerance was gone), from different hospitals for 16S rRNA gene sequencing. The gut microbiota community composition of preterm infants diagnosed with feeding intolerance was significantly different from that of preterm infants without feeding intolerance. At the time when feeding intolerance was diagnosed, the relative abundance of Klebsiella in preterm infants with feeding intolerance increased significantly, and was significantly higher than that of the preterm infants without feeding intolerance. After feeding intolerance was cured, the relative abundance of Klebsiella significantly decreased in the infants diagnosed with feeding intolerance, while the relative abundance of Klebsiella in preterm infants without feeding intolerance was not significantly altered during the development and prevalence of feeding intolerance. Furthermore, we verified that Klebsiella was effective in the diagnosis of feeding intolerance (AUC = 1) in preterm infants, suggesting that Klebsiella is a potential diagnostic biomarker for feeding intolerance.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
(SMV), which belongs to the
, causes significant reductions in soybean yield and seed quality. In this study, both tag-free and reporter gene
(
)-containing infectious clones for the SMV N1 strain ...were constructed by Gibson assembly and with the yeast homologous recombination system, respectively. Both infectious clones are suitable for agroinfiltration on the model host
and show strong infectivity for the natural host soybean and several other legume species. Both infectious clones were seed transmitted and caused typical virus symptoms on seeds and progeny plants. We used the SMV-GFP infectious clone to further investigate the role of key amino acids in the silencing suppressor helper component-proteinase (Hc-Pro). Among twelve amino acid substitution mutants, the co-expression of mutant 2-with an Asparagine→Leucine substitution at position 182 of the FRNK (Phe-Arg-Asn-Lys) motif-attenuated viral symptoms and alleviated the host growth retardation caused by SMV. Moreover, the Hc-Prom2 mutant showed stronger oligomerization than wild-type Hc-Pro. Taken together, the SMV infectious clones will be useful for studies of host-SMV interactions and functional gene characterization in soybeans and related legume species, especially in terms of seed transmission properties. Furthermore, the SMV-GFP infectious clone will also facilitate functional studies of both virus and host genes in an
transient expression system.
Malaria is one of the most serious global infectious diseases. The pyrimidine biosynthetic enzyme Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) is an important target for antimalarial ...chemotherapy. We describe a detailed analysis of protein–ligand interactions between DHODH and a triazolopyrimidine-based inhibitor series to explore the effects of fluorine on affinity and species selectivity. We show that increasing fluorination dramatically increases binding to mammalian DHODHs, leading to a loss of species selectivity. Triazolopyrimidines bind Plasmodium and mammalian DHODHs in overlapping but distinct binding sites. Key hydrogen-bond and stacking interactions underlying strong binding to PfDHODH are absent in the mammalian enzymes. Increasing fluorine substitution leads to an increase in the entropic contribution to binding, suggesting that strong binding to mammalian DHODH is a consequence of an enhanced hydrophobic effect upon binding to an apolar pocket. We conclude that hydrophobic interactions between fluorine and hydrocarbons provide significant binding energy to protein–ligand interactions. Our studies define the requirements for species-selective binding to PfDHODH and show that the triazolopyrimidine scaffold can alternatively be tuned to inhibit human DHODH, an important target for autoimmune diseases.
Social networks can provide massive amounts of information for communication among users and communities. The trust relationships in social networks can be utilized to reveal user preferences for ...improving the quality of social recommendation, which aims to mitigate information overload and provide users with the most attractive and relevant items or services. However, the data sparsity and cold-start issue degrade recommendation performance significantly. To address these issues, a novel trust-embedded collaborative deep generative model (TCDG) is proposed for exploiting multisource information (content, rating and trust) to predict ratings. TCDG employs deep generative model to unsupervisedly learn deep latent representations for item content through an inference network in latent space instead of observation space. Meanwhile, TCDG adopts probabilistic matrix factorization to map users into low-dimensional latent feature spaces by trust relationships, which can reflect users’ mutual influence on the formation of users’ opinions more accurately and learn better implicit relationships between items and users from content, rating and trust. In addition, an approach with an annealing parameter to calculate the maximum a posteriori estimates is proposed to learn model parameters. Experiments using four real-world datasets are conducted to evaluate the prediction and top-ranking performance of our model. The results indicate that TDCG has better accuracy and robustness than other methods for making recommendations.
Objective:
We conducted a national US study of SARS-CoV-2 seroprevalence by Social Vulnerability Index (SVI) that included pediatric data and compared the Delta and Omicron periods during the ...COVID-19 pandemic. The objective of the current study was to assess the association between SVI and seroprevalence of infection-induced SARS-CoV-2 antibodies by period (Delta vs Omicron) and age group.
Methods:
We used results of infection-induced SARS-CoV-2 antibody assays of clinical sera specimens (N = 406 469) from 50 US states from September 2021 through February 2022 to estimate seroprevalence overall and by county SVI tercile. Bivariate analyses and multilevel logistic regression models assessed the association of seropositivity with SVI and its themes by age group (0-17, ≥18 y) and period (Delta: September–November 2021; Omicron: December 2021–February 2022).
Results:
Aggregate infection-induced SARS-CoV-2 antibody seroprevalence increased at all 3 SVI levels; it ranged from 25.8% to 33.5% in September 2021 and from 53.1% to 63.5% in February 2022. Of the 4 SVI themes, socioeconomic status had the strongest association with seroprevalence. During the Delta period, we found significantly more infections per reported case among people living in a county with high SVI (odds ratio OR = 2.76; 95% CI, 2.31-3.21) than in a county with low SVI (OR = 1.65; 95% CI, 1.33-1.97); we found no significant difference during the Omicron period. Otherwise, findings were consistent across subanalyses by age group and period.
Conclusions:
Among both children and adults, and during both the Delta and Omicron periods, counties with high SVI had significantly higher SARS-CoV-2 antibody seroprevalence than counties with low SVI did. These disparities reinforce SVI’s value in identifying communities that need tailored prevention efforts during public health emergencies and resources to recover from their effects.
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