Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death worldwide, and classifying the developmental stages of HCC can help with early prognosis and treatment. This study aimed to investigate diagnostic and prognostic molecular signatures underlying the progression of HCC, including tumor initiation and growth, and to classify its developmental stages based on gene expression levels. We integrated data from two cancer systems, including 78 patients with Edmondson-Steiner (ES) grade and 417 patients with TNM stage cancer. Functional profiling was performed using identified signatures. Using a multinomial logistic regression model (MLR), we classified controls, early-stage HCC, and advanced-stage HCC. The model was validated in three independent cohorts comprising 45 patients (neoplastic stage), 394 patients (ES grade), and 466 patients (TNM stage). Multivariate Cox regression was employed for HCC prognosis prediction. We identified 35 genes with gradual upregulation or downregulation in both ES grade and TNM stage patients during HCC progression. These genes are involved in cell division, chromosome segregation, and mitotic cytokinesis, promoting tumor cell proliferation through the mitotic cell cycle. The MLR model accurately differentiated controls, early-stage HCC, and advanced-stage HCC across multiple cancer systems, which was further validated in various independent cohorts. Survival analysis revealed a subset of five genes from TNM stage (HR: 3.27, p < 0.0001) and three genes from ES grade (HR: 7.56, p < 0.0001) that showed significant association with HCC prognosis. The identified molecular signature not only initiates tumorigenesis but also promotes HCC development. It has the potential to improve clinical diagnosis, prognosis, and therapeutic interventions for HCC. This study enhances our understanding of HCC progression and provides valuable insights for precision medicine approaches.

BACKGROUND: Prior research has indicated a potential connection between psychological stress and how individuals perceive their own age. Building on this foundation, the current study explores the relationship between negative emotions and self-perceived age.
METHODS: We conducted a cross-sectional analysis using data from the UK Biobank, a comprehensive cohort study representing the UK population. The analysis included 347 892 participants, aged between 39 and 73 years, of which 184 765 were women, accounting for 53.1% of the sample. Participants were categorized into three groups based on their self-perceived age: feeling younger than their chronological age (group Younger), feeling older than their chronological age (group Older), and feeling as old as their actual age (group Same). To investigate the relationship between negative emotions and self-perceived age, we utilized a multinomial logistic regression model with the Younger group serving as the reference category.
RESULTS: Of 347 892 participants, after adjusted for covariates, the results showed that participants with irritability, nervous feelings, worrier/anxious feelings or fed-up feelings, worry too long and loneliness/isolation are more likely to be rated as \"about your age\" or \"older than you are,\" with \"younger than you are\" as the reference group, indicating that negative emotions may influence one\'s self-perceived age. Among those negative emotions, irritability has the most significant impact self-perceived age, with the odds ratios (ORs) being 1.44 (95% CI: 1.35-1.54) and 1.11 (95% CI: 1.09-1.14).
CONCLUSIONS: Negative emotions are associated with older self-perceived age, and irritability has the greatest impact. Further studies analyzing self-perceived age are needed to take psychological factors into consideration.

OBJECTIVE: Multicategory prediction models (MPMs) can be used in health care when the primary outcome of interest has more than two categories. The application of MPMs is scarce, possibly due to added methodological complexities compared to binary outcome models. We provide a guide of how to develop, validate, and update clinical prediction models based on multinomial logistic regression.
METHODS: We present guidance and recommendations based on recent methodological literature, illustrated by a previously developed and validated MPM for treatment outcomes in rheumatoid arthritis. Prediction models using multinomial logistic regression can be developed for nominal outcomes, but also for ordinal outcomes. This article is intended to supplement existing general guidance on prediction model research.
RESULTS: This guide is split into three parts: 1) outcome definition and variable selection, 2) model development, and 3) model evaluation (including performance assessment, internal and external validation, and model recalibration). We outline how to evaluate and interpret the predictive performance of MPMs. R code is provided.
CONCLUSIONS: We recommend the application of MPMs in clinical settings where the prediction of a multicategory outcome is of interest. Future methodological research could focus on MPM-specific considerations for variable selection and sample size criteria for external validation.

The transition to a low-carbon economy emphasizes the importance of green and low-carbon consumption; yet, there is often a discrepancy between consumers\' intentions and their actual behavior regarding organic foods. This study aims to identify strategies to bridge this gap. The research model of organic food consumption intention and behavior is constructed, and a structural equation model is used to test the research hypotheses based on a valid sample of 480 residents of Guangdong Province through an online questionnaire survey. Further, the intention‒behavior gap is defined and its determinants are investigated through multiclass logistic regression. Finally, we categorize and forecast the alignment between consumption intentions and behaviors using machine learning algorithms. The results reveal that attitudes, social interactions, and cognitive information play crucial roles in aligning intentions with behaviors. By enhancing social information exchange or improving cognitive understanding, consumers can reduce their intention‒behavior discrepancy. This research offers valuable policy recommendations for fostering green consumption among residents from various perspectives.

UNASSIGNED: Collisions are a significant cause of injury and fatality among young novice drivers. Using real crash data, this study further explores the multifaceted and complex nature of young novice drivers\' crash injury risk by synthesizing different driver attributes and crash scenarios in order to update and validate previous research findings and provide more feasible recommendations for preventive measures.
UNASSIGNED: Detailed data on traffic crash of young novice drivers were extracted from the National Automobile Accident In-Depth Investigation System (NAIS) in China, and a mixed research methodology using a Random Forest and multinomial logit modeling framework was used in order to explore and study the important influences on traffic crash injuries of young novice drivers in Songjiang District, Shanghai, during the period from 2018 to 2022.
UNASSIGNED: The results of the study showed that human, vehicle, road and environmental characteristics contributed 36.83%, 22.65%, 17.07% and 23.45% respectively to the prediction of crash injury level of novice drivers. Among the various single factors, driver negligence was the most important factor affecting the crash injury level of novice drivers. Age of the vehicle, crash location, road signal condition and time of crash all had a significant effect on the crash injury level of young novice drivers (95% of the confidence level).
UNASSIGNED: The study comprehensively analyzed young novice driver crash data to reveal the crash injury risk and its severity faced by young novice drivers in different contexts, and suggested targeted safety improvements. There are similarities and differences with the results of previous studies, in which there are new contributions to understanding the driving risks of young novice drivers in daytime and nighttime.

UNASSIGNED: Awake craniotomy is the standard of care for treating language eloquent gliomas. However, depending on preoperative functionality, it is not feasible in each patient and selection criteria are highly heterogeneous. Thus, this study aimed to identify broadly applicable predictor variables allowing for a more systematic and objective patient selection.
UNASSIGNED: We performed post-hoc analyses of preoperative language status, patient and tumor characteristics including language eloquence of 96 glioma patients treated in a single neurosurgical center between 05/2018 and 01/2021. Multinomial logistic regression and stepwise variable selection were applied to identify significant predictors of awake surgery feasibility.
UNASSIGNED: Stepwise backward selection confirmed that a higher number of paraphasias, lower age, and high language eloquence level were suitable indicators for an awake surgery in our cohort. Subsequent descriptive and ROC-analyses indicated a cut-off at ≤54 years and a language eloquence level of at least 6 for awake surgeries, which require further validation. A high language eloquence, lower age, preexisting semantic and phonological aphasic symptoms have shown to be suitable predictors.
UNASSIGNED: The combination of these factors may act as a basis for a systematic and standardized grading of patients\' suitability for an awake craniotomy which is easily integrable into the preoperative workflow across neurosurgical centers.

UNASSIGNED: The international development agenda emphasizes universal access to family planning, as seen in Sustainable Development Goal 3.7. However, the use of modern contraceptive methods remains low in developing countries, specifically in West Africa. This study aimed to assess the current status of contraceptive use in the region, focusing on different methods.
UNASSIGNED: We analyzed Demographic and Health Survey data from 13 West African nations (2012-2022) involving 117,165 married women. Using binary and multiple multinomial logistic regression, we identified key factors associated with contraceptive use. Adjusted odds ratios with 95% confidence intervals were utilized, and significance was determined at p ≤ 0.2 for binary regression and p < 0.05 for multiple multinomial regression.
UNASSIGNED: About 80.86% of women did not use any method, while 16.56% of women used modern methods. Maternal age of 35-49 years (RRR=0.77, 95% CI, 0.72,0.82), had given first birth after 20 years (RRR=0.80,95% CI, 0.77,0.83), cohabitation after 20 years old (RRR=1.24,95% CI, 1.18,1.29), being employed (RRR=1.38,95% CI, 1.33,1.43), women who have from 3-5, and more than five living children (RRR=2.06,95% CI,1.97,2.16, and (RRR=2.57, 95% CI, 2.42,2.74), primary(RRR=1.59, 95% CI, 1.52,1.66), secondary/higher education (RRR=2.08, 95% CI, 1.99,2.18), antenatal visit (RRR= 1.38, 95% CI 1.28,1.49), institutional delivery(AOR=1.42, 95% CI, 1.35,1.49), husband working status (RRR=1.39, 95% CI, 1.28,1.51), media exposure(RRR=1.23, 95% CI, 1.19,1.28), visited health facility more than once (RRR=1.09, 95% CI, 1.05,1.13), rural women (RRR=0.89,95% CI,0.85,0.93), female households (RRR=0.79, 95% CI,0.76,0.83), richer (RRR=1.42, 95% CI,1.33,1.51), and richest wealth indexes (RRR=1.69,95% CI,1.58,1.82) were associated.
UNASSIGNED: This study revealed a low level of contraceptive use among women in West Africa. Strengthening maternal reproductive health services, such as antenatal care, institutional delivery, and health visits, while also targeting mass media and disadvantaged women, has the potential to significantly increase the adoption of modern contraception techniques.

UNASSIGNED: Malaria prevention and control is a major public health problem of tropical countries including India. Usage of insecticide-treated bed nets, and early treatment especially in high-risk areas are the crucial factors for the malaria prevention at household levels. This study aimed to determine the crucial factors associated with malaria prevention at households\' level such as household\'s characteristics, education, knowledge and awareness, insecticide treated bed nets usage, early treatment etc.
UNASSIGNED: Data of 1989 households was used from the cross-sectional survey of malaria-endemic areas of Assam. Principal component analysis and multinomial logistic regression model were used to compute the composite scores of malaria awareness and prevention practices, and to estimate the associated factors with malaria prevention practices, respectively.
UNASSIGNED: The average age of household respondents were 41.1 ± 12.0 years and among them 71% were males. Almost 47% respondents were illiterate, and 38.6% of the respondents were farmers and 35% were employed. Multinomial logistic regression analysis indicates that malaria prevention practices are associated with age, education, religion, type of house and occupation of household heads and their level of malaria awareness among them. The prevention practices were significantly five times associated [Adjusted Rates Ratio (ARR): 5.0, 95% CI: 2.7-9.4] with the high level of malaria awareness compared with the low level of awareness. Overall, the level of prevention awareness, education, occupation, and house type related to the standard of living was significantly associated with the malaria prevention practices.
UNASSIGNED: Malaria awareness and education are the key factors of malaria prevention practices that need to be accelerated for effective control of malaria. Malaria education and increasing awareness of people have a high impact on malaria prevention practices and their control.

There is a critical need to understand vaccine decision-making in high-risk groups. This study explored flu vaccine acceptance among Jordanian parents of diabetic children. Employing a cross-sectional approach, 405 parents from multiple healthcare centers across Jordan were recruited through stratified sampling, ensuring a broad representation of socioeconomic backgrounds. A structured questionnaire, distributed both in-person and online, evaluated their knowledge, attitudes, and acceptance of the flu vaccine for their diabetic children. The results indicated that only 6.4% of the study sample reported vaccinating their children against the flu annually, and only 23% are planning to vaccinate their children this year. A multinomial logistic regression analysis revealed notable variability in responses. Specifically, parents with a positive attitude towards the flu vaccine and those with older children had less odds to reject the vaccine (OR = 0.589, 95% CI (0.518-0.670), p < 0.001 and OR = 0.846, 95% CI (0.736-0.974), p = 0.02, respectively). Conversely, prevalent misconceptions regarding vaccine safety and efficacy emerged as significant barriers to acceptance. Our findings advocate for targeted educational programs that directly address and debunk these specific misconceptions. Additionally, strengthened healthcare communication to provide clear, consistent information about the flu vaccine\'s safety and benefits is vital to help enhance vaccine uptake among this vulnerable population, emphasizing the need to address specific concerns and misinformation directly.

The Middle Pleistocene (MP) saw the emergence of new species of hominins: Homo sapiens in Africa, H. neanderthalensis, and possibly Denisovans in Eurasia, whose most recent common ancestor is thought to have lived in Africa around 600 ka ago. However, hominin remains from this period present a wide range of morphological variation making it difficult to securely determine their taxonomic attribution and their phylogenetic position within the Homo genus. This study proposes to reconsider the phenetic relationships between MP hominin fossils in order to clarify evolutionary trends and contacts between the populations they represent.
We used a Geometric Morphometrics approach to quantify the morphological variation of the calvarium of controversial MP specimens from Africa and Eurasia by using a comparative sample that can be divided into 5 groups: H. ergaster, H. erectus, H. neanderthalensis, and H. sapiens, as well as individuals from current modern human populations. We performed a Generalized Procrustes Analysis, a Principal Component Analysis, and Multinomial Principal Component Logistic Regressions to determine the phenetic affinities of the controversial Middle Pleistocene specimens with the other groups.
MP African and Eurasian specimens represent several populations, some of which show strong affinities with H. neanderthalensis in Europe or H. sapiens in Africa, others presenting multiple affinities.
These MP populations might have contributed to the emergence of these two species in different proportions. This study proposes a new framework for the human evolutionary history during the MP.