BACKGROUND: Vaccine hesitancy is a complex issue of global concern. As nurses play a vital role in delivering patient care and shaping public opinions on vaccines, interventions to address vaccine hesitancy in nursing are imperative. As such, identifying profiles of characteristics and attitudes contributing to hesitancy may help identify specific areas of focus to target tailored global vaccination uptake campaigns. The purpose of this study was to profile the characteristics and attitudes contributing to hesitancy toward COVID-19 and Influenza vaccines in the nursing community.
METHODS: This multisite, cross-sectional study recruited 1967 registered nurses and 1230 nursing students from the United Kingdom, Finland, and Italy between March and September 2023.
METHODS: Data collection involved an online survey adopting the Vaccination Attitudes Examination (VAX) Scale, the Bergen Social Media Addiction Scale, and questions pertaining to sociodemographic and occupational characteristics. A k-means cluster analysis was used to identify various clusters of hesitancy based on the VAX Scale. One-way ANOVA and chi-square tests were used to identify significant differences in sociodemographic characteristics, occupational factors, vaccination attitudes, and social media usage between the clusters.
RESULTS: Three distinct clusters were identified. Profile A showed high vaccine confidence, profile B displayed slight hesitancy, and profile C reported high levels of hesitancy. In profile C, higher levels of vaccine hesitancy were identified in younger, less experienced nurses with lower educational attainment. While older nurses with higher educational attainment, who were in senior roles, were more vaccine-confident and had a consistent history of accepting the Influenza and COVID-19 vaccinations (profile A). The study found Italian nurses highly hesitant (profile C), British nurses highly confident (profile A), and Finnish nurses evenly distributed between confident, slightly hesitant, and highly hesitant (profiles A, B, and C, respectively). In addition, more frequent usage of Instagram and TikTok was associated with vaccine hesitancy (profiles B and C), and LinkedIn and X were more common among vaccine-confident individuals (profile A).
CONCLUSIONS: This study has identified specific sociodemographic and occupational factors that are related to vaccine hesitancy in an international sample of nurses. Additionally, attitudes contributing to hesitancy were identified, with worries about unforeseen future effects of the vaccine being identified as a critical attitude that may undermine confidence and increase hesitancy in nursing. This study also sheds light on the influence that social media platforms have on vaccine hesitancy and, as such, indicates which platforms are effective to disseminate vaccination campaigns to global nursing communities.
CONCLUSIONS: Global vaccination campaigns should focus on specific profiles and clusters to promote vaccination in the international nursing community. Empowering nurses early in their careers will help to instill positive vaccination behaviors, ensuring a sustained uptake of vaccinations throughout the individual\'s career and beyond, with an impact on promoting vaccination at the public health level as well.

BACKGROUND: Mobile health (mHealth) solutions can improve the quality, accessibility, and equity of health services, fostering early rehabilitation. For individuals with hearing loss, mHealth apps might be designed to support the decision-making processes in auditory diagnostics and provide treatment recommendations to the user (eg, hearing aid need). For some individuals, such an mHealth app might be the first contact with a hearing diagnostic service and should motivate users with hearing loss to seek professional help in a targeted manner. However, personalizing treatment recommendations is only possible by knowing the individual\'s profile regarding the outcome of interest.
OBJECTIVE: This study aims to characterize individuals who are more or less prone to seeking professional help after the repeated use of an app-based hearing test. The goal was to derive relevant hearing-related traits and personality characteristics for personalized treatment recommendations for users of mHealth hearing solutions.
METHODS: In total, 185 (n=106, 57.3% female) nonaided older individuals (mean age 63.8, SD 6.6 y) with subjective hearing loss participated in a mobile study. We collected cross-sectional and longitudinal data on a comprehensive set of 83 hearing-related and psychological measures among those previously found to predict hearing help seeking. Readiness to seek help was assessed as the outcome variable at study end and after 2 months. Participants were classified into help seekers and nonseekers using several supervised machine learning algorithms (random forest, naïve Bayes, and support vector machine). The most relevant features for prediction were identified using feature importance analysis.
RESULTS: The algorithms correctly predicted action to seek help at study end in 65.9% (122/185) to 70.3% (130/185) of cases, reaching 74.8% (98/131) classification accuracy at follow-up. Among the most important features for classification beyond hearing performance were the perceived consequences of hearing loss in daily life, attitude toward hearing aids, motivation to seek help, physical health, sensory sensitivity personality trait, neuroticism, and income.
CONCLUSIONS: This study contributes to the identification of individual characteristics that predict help seeking in older individuals with self-reported hearing loss. Suggestions are made for their implementation in an individual-profiling algorithm and for deriving targeted recommendations in mHealth hearing apps.

Breast cancer (BC) is a global public health problem attributed to varying risk factors. The designing of a targeted screening program focused on at-risk women can be cost-effective in reducing its burden. A hospital based case control study was conducted on 138 cases of breast cancer and 169 healthy controls to investigate the reproductive and non-reproductive risk factors for breast cancer in Pakistani women. The odds ratios (ORs) and 95% confidence intervals (CIs) were computed with unconditional logistic regression. Almost all i.e. 97.83% of cases were married (OR=5.03),70.29% were illiterate (OR=1.88), 73.19% were aged >35 years (OR=0.632) and 81.16% belonged to the poor class(OR=1.81). Early age at menarche (OR, 2.55; 95% CI 1.50-4.31, P=0.0001), hormone replacement therapy (OR=2.057, 95% CI 1.283-3.295, P= 0.002) early pregnancy (OR,2.23, 95% CI 1.29-3.88, P=0.004), history of miscarriage (OR, 2.11, 95% CI 1.32-3.39,P=0.002) & oral contraceptive use (OR, 2.76, 95% CI 1.54-4.92, P= 0.006) were significantly associated with BC. The study highlights the dire need for effective public health programs for high-risk women to address this highly fatal disease.
Le cancer du sein (BC) est un problème de santé publique mondial attribué à divers facteurs de risque. La conception d\'un programme de dépistage ciblé axé sur les femmes à risque peut s\'avérer rentable pour réduire son fardeau. Une étude cas-témoins en milieu hospitalier a été menée sur 138 cas de cancer du sein et 169 témoins sains pour étudier les facteurs de risque reproductifs et non reproductifs du cancer du sein chez les femmes pakistanaises. Les rapports de cotes (OR) et les intervalles de confiance (IC) à 95 % ont été calculés par régression logistique inconditionnelle. La quasi-totalité soit 97,83% des cas étaient mariés (OR=5,03), 70,29% étaient analphabètes (OR=1,88), 73,19% étaient âgés de >35 ans (OR=0,632) et 81,16% appartenaient à la classe pauvre (OR=1,81). . Âge précoce aux premières règles (OR = 2,55 ; IC à 95 % 1,50-4,31, P = 0,0001), traitement hormonal substitutif (OR = 2,057, IC à 95 % 1,283-3,295, P = 0,002) grossesse précoce (OR , 2,23, IC à 95 % 1,29-3,88, P=0,004), les antécédents de fausse couche (OR, 2,11, IC à 95 % 1,32-3,39, P=0,002) et l\'utilisation de contraceptifs oraux (OR, 2,76, IC à 95 % 1,54-4,92, P= 0,006) étaient significativement associé à la Colombie-Britannique. L\'étude souligne le besoin urgent de programmes de santé publique efficaces destinés aux femmes à haut risque afin de lutter contre cette maladie hautement mortelle.

Mexico City is the location with the largest number of boxers in Mexico; in fact, it is the first city in the country to open a Technological Baccalaureate in Education and Sports Promotion with a pugilism orientation. This cross-sectional study aimed to determine the physical-functional profile of applicants for admission to the baccalaureate in sports. A total of 227 young athletes (44F; 183M; 15.65 (1.79) years; 63.66 (14.98) kg; >3 years of boxing experience) participated in this study. Body mass (BM), maximal isometric handgrip (HG) strength, the height of the countermovement jump (CMJ), the velocity of straight boxing punches (PV), and the rear hand punch impact force (PIF) were measured. The young boxers were profiled using unsupervised machine learning algorithms, and the probability of superiority (ρ) was calculated as the effect size of the differences. K-Medoids clustering resulted in two sex-independent significantly different groups: Profile 1 (n = 118) and Profile 2 (n = 109). Except for BM, Profile 2 was statistically higher (p < 0.001) with a clear distinction in terms of superiority on PIF (ρ = 0.118), the PIF-to-BM ratio (ρ = 0.017), the PIF-to-HG ratio (ρ = 0.079) and the PIF-to-BM+HG ratio (ρ = 0.008). In general, strength levels explained most of the data variation; therefore, it is reasonable to recommend the implementation of tests aimed at assessing the levels of isometric and applied strength in boxing gestures. The identification of these physical-functional profiles might help to differentiate training programs during sports specialization of young boxing athletes.

While fingerprints are a highly used means of identification, not every fingerprint left behind on a potential crime scene can be used for identification purposes. In some cases, the fingerprint may be smudged, partially preserved or overlapping with other prints hence distorting the ridge pattern and may therefore be not appropriate for identification. Further, fingermark residue yields a very low abundance of genetic material for DNA analysis. In such cases, the fingermark may be used to retrieve basic donor information such as sex. The focus of this paper was to assess the possibility of differentiating between the sexes of the donor of latent fingermarks. Analytical method was GC-MS analysis of the chemical compounds of latent fingermarks using 22 male and 22 female donors. Results showed 44 identified compounds. Two alcohols, octadecanol C18 and eicosanol C20 , were found to show a difference that was statistically significant between male and female donors. There is also some evidence for the possibility of distinguishing sex of the fingermark donor based on the distribution of branched chain fatty acids, as free compounds or esterified in wax esters.

Nasopharyngeal Carcinoma (NPC) is an upper respiratory tract cancer prevalent in Southeast Asia and related to chronic EBV infection. microRNAs (miRNAs) regulate gene expression implicated in NPC\'s carcinogenesis. However, this circulating RNA molecule\'s role and clinical utility remain unknown. Therefore, this study examined the circulation of miRNAs and their association with clinical data.
160 plasma samples of NPC and 80 non-tumor samples were extracted to evaluate and validate the gene expressions. Quantification expression was performed using relative quantification of qPCR analysis level expression methods. The intrinsic cellular roles involving biological signaling in NPC\'s oncogenesis using Ingenuity Pathways Analysis (IPA) were also used.
The results of the quantification significance profiling of NPC samples revealed decreased miR- 29c-3p (fold change 1.16; p<0.05) and increased 195-5p expression (fold change 1.157; p<0.05). Furthermore, the validation of hsa-miR-29c-3p expression on plasma NPC with known tumor vs. non-tumor and significant changes was also performed using a fold change of 4.45 (medians of 31.45 ± 1.868 and 24.96 ± 1.872, respectively; p<0.0005). miR-29c had a 2.14 fold change correlated with T primary status with a median of 31.99±1.319 and 31.35±2.412, respectively (p<0.05). Stage status with fold change 1.99 also had median levels of 31.98±1.105 and 31.21 ± 2.355, respectively (p-value <0.05). Furthermore, the node\'s status for the lower expression of miR-29c with fold change 1.17 had median levels of 32.78 ± 2.221 and 31.33 ± 1.689, respectively (p-value of 0.7). Bioinformatics analysis established the roles and functions of miR-29 in NPC progression, cell death and survival, cellular development, cellular function, and cell maintenance by inhibiting COL4A, PI3K, VEGFA, JUN, and CDK6.
Overall, we conclude that decreased miR-29c expression is associated with poor clinical status and might inhibit NPC\'s five target genes.

Profiles of citrus juice oxygenated heterocyclic aglycones (OHAs), which are notable marker secondary metabolites, were used to assess the authenticity of sweet orange and grapefruit juices in situations where mandarin and pomelo juices might be adulterants. Thirty-nine known OHAs, including 10 methoxyflavones, 13 coumarins, and 16 furanocoumarins, as well as 13 tentatively screened OHAs, were analyzed in orange, mandarin, grapefruit and pomelo juices using our newly developed high-resolution HPLC-UV and fluorescence detection method. Quantitative OHA profiles from 158 pure juice samples were obtained to establish a purity discriminant model using an omics strategy. Reduction of OHA variables showed that three important methoxyflavones, i.e. isosinensetin, tangeretin and sinensetin provided the best discrimination ability between sweet orange and mandarin juices. There are two subtypes of pomelos, Shatianyou Group and Wendan Group, of which juices should be separately compared to grapefruit juice. Five OHAs, namely meranzin, 3,5,6,7,8,3\',4\'-heptamethoxyflavone, osthole, 6\',7\'-epoxybergamottin, and bergamottin were found to discriminate Shatianyou Group of pomelo juice from grapefruit juice; whereas three OHAs, namely bergaptol, isomeranzin, and 6\',7\'-dihydroxybergamottin were able to discriminate Wendan Group of pomelo juice from grapefruit juice. The established partial least squares discriminant analysis (PLS-DA) models were capable of detecting as little as 10% mandarin juice in sweet orange juice and 10% pomelo juice in grapefruit juice, allowing for fast prescreening of excess addition with good reliability (root mean square error of prediction, RMSEP < 5%).

A greater comprehension of factors contributing to pleasure from food-related experiences could increase understanding of underlying processes around different eating behaviours. We explored drivers of food pleasure and whether certain consumer characteristics were associated with specific food pleasure profiles. This study aimed to investigate (1) how Danish consumers vary in terms of primary drivers of food pleasure, and (2) how differences in food pleasure are related to specific sociodemographic, lifestyle, health and eating behavioural personality traits. Three-hundred and fifty-five respondents (mean age 33.3 years) rated the importance of different drivers of food pleasure, along with sociodemographic, lifestyle, health and eating behaviour variables. Segmentation analysis was performed based on emerging food pleasure dimensions, and profiling of segments was conducted by multivariate regression analysis and calculations of odds ratios. The results demonstrated that five specific consumer segments could be defined, \'Sensory-pleasure Seekers\' (50%), \'Internal-pleasure Seekers\' (34%), \'Contextual-pleasure Seekers\' (17%), \'Exploratory-pleasure seekers\' (13%) and \'Confirming-pleasure seekers\' (5%), each with specific characteristics. Importantly, this research indicates that a link between mental health, personality, eating behaviour and perceived food pleasure is evident. These insights contribute to the comprehension of the complex nature of food choices of importance to accommodating public health issues.

Compared to traditional experimental approaches, computational modeling is a promising strategy to efficiently prioritize new candidates with low cost. In this study, we developed a novel data mining and computational modeling workflow proven to be applicable by screening new analgesic opioids. To this end, a large opioid data set was used as the probe to automatically obtain bioassay data from the PubChem portal. There were 114 PubChem bioassays selected to build quantitative structure-activity relationship (QSAR) models based on the testing results across the probe compounds. The compounds tested in each bioassay were used to develop 12 models using the combination of three machine learning approaches and four types of chemical descriptors. The model performance was evaluated by the coefficient of determination (R 2) obtained from 5-fold cross-validation. In total, 49 models developed for 14 bioassays were selected based on the criteria and were identified to be mainly associated with binding affinities to different opioid receptors. The models for these 14 bioassays were further used to fill data gaps in the probe opioids data set and to predict general drug compounds in the DrugBank data set. This study provides a universal modeling strategy that can take advantage of large public data sets for computer-aided drug design (CADD).

A riboswitch is a type of RNA molecule that regulates important biological functions by changing structure, typically under ligand-binding. We assess the extent that these ligand-bound structural alternatives are present in the Boltzmann sample, a standard RNA secondary structure prediction method, for three riboswitch test cases. We use the cluster analysis tool RNAStructProfiling to characterize the different modalities present among the suboptimal structures sampled. We compare these modalities to the putative base pairing models obtained from independent experiments using NMR or fluorescence spectroscopy. We find, somewhat unexpectedly, that profiling the Boltzmann sample captures evidence of ligand-bound conformations for two of three riboswitches studied. Moreover, this agreement between predicted modalities and experimental models is consistent with the classification of riboswitches into thermodynamic versus kinetic regulatory mechanisms. Our results support cluster analysis of Boltzmann samples by RNAStructProfiling as a possible basis for de novo identification of thermodynamic riboswitches, while highlighting the challenges for kinetic ones.