UNASSIGNED: The Life\'s Simple 7 score (LS7) promotes cardiovascular health (CVH). Despite this, some with optimal LS7 develop cardiovascular disease (CVD), while others with poor CVH do not, termed the \"CVH paradox.\" This paper explores pathways explaining this paradox.
UNASSIGNED: We examined methodological aspects: 1) misclassification bias in self-reported lifestyle factors (smoking, physical activity, diet); 2) cumulative exposure to risk factors over a lifetime, impacting the CVH paradox. Punctual risk factor assessments are suboptimal for predicting outcomes. We proposed personalized prevention using \"novel\" elements to refine CVH assessment: 1) subclinical vascular disease markers, 2) metabolic biomarkers in blood and urine, 3) emerging risk factors, 4) polygenic risk scores (PRS), 5) epigenetics, and 6) the exposome.
UNASSIGNED: Addressing the CVH paradox requires a multifaceted approach, reducing misclassification bias, considering cumulative risk exposure, and incorporating novel personalized prevention elements.
UNASSIGNED: A holistic, individualized approach to CVH assessment and CVD prevention can better reduce cardiovascular outcomes and improve population health. Collaboration among researchers, healthcare providers, policymakers, and communities is essential for effective implementation and realization of these strategies.

The rising obesity epidemic requires effective and sustainable weight loss intervention strategies that take into account both of individual preferences and environmental impact. This study aims to develop and evaluate the effectiveness of an innovative digital biohacking approach for dietary modifications in promoting sustainable weight loss and reducing carbon footprint impact. A pilot study was conducted involving four participants who monitored their weight, diet, and activities over the course of a year. Data on food consumption, carbon footprint impact, calorie intake, macronutrient composition, weight, and energy expenditure were collected. A digital replica of the metabolism based on nutritional information, the Personalized Metabolic Avatar (PMA), was used to simulate weight changes, plan, and execute the digital biohacking approach to dietary interventions. The dietary modifications suggested by the digital biohacking approach resulted in an average daily calorie reduction of 236.78 kcal (14.24%) and a 15.12% reduction in carbon footprint impact (-736.48 gCO2eq) per participant. Digital biohacking simulations using PMA showed significant differences in weight change compared to actual recorded data, indicating effective weight reduction with the digital biohacking diet. Additionally, linear regression analysis on real data revealed a significant correlation between adherence to the suggested diet and weight loss. In conclusion, the digital biohacking recommendations provide a personalized and sustainable approach to weight loss, simultaneously reducing calorie intake and minimizing the carbon footprint impact. This approach shows promise in combating obesity while considering both individual preferences and environmental sustainability.

UNASSIGNED: The Exacerbation of Chronic Obstructive Pulmonary Disease (ECOPD), especially if leading to hospitalization, increases the risk of death. Our scoping review aims to identify updated mortality risk factors for both short- and long-term periods.
UNASSIGNED: A comprehensive search, covering the period from January 2013 to February 2024, was performed to identify eligible studies that consider factors associated with death in hospitalized ECOPD. We considered short-term mortality, up to one year (including in-hospital mortality, IHM) and long-term mortality over one year, without time limits. We excluded studies concerning the intensive care area.
UNASSIGNED: We considered 38 studies, 32 and 8 reporting data about short- and long-term mortality, respectively. Two studies consider both periods. Several factors, some already known, others newly identified, have been evaluated and discussed. Some of these were related to the characteristics and severity of COPD (age, body mass index, lung impairment), and some considered the response to ECOPD. In this last context, we focused on the increasing role of biomarkers in predicting the mortality of patients, particularly IHM. Our factors associated with a worse prognosis may be helpful in clinical practice to identify patients at risk and, subsequently, determine a personalized approach.

The safety of the use of psychotropic drugs, widely used in neurological and psychiatric practice, is an urgent problem in personalized medicine. This narrative review demonstrated the variability in allelic frequencies of low-functioning and non-functional single nucleotide variants in genes encoding key isoenzymes of valproic acid P-oxidation in the liver across different ethnic/racial groups. The sensitivity and specificity of pharmacogenetic testing panels for predicting the rate of metabolism of valproic acid by P-oxidation can be increased by prioritizing the inclusion of the most common risk allele characteristic of a particular population (country).

Marfan syndrome (MIM: # 154700; MFS) is an autosomal dominant disease representing the most common form of heritable connective tissue disorder. The condition presents variable multiorgan expression, typically involving a triad of cardiovascular, eye, and skeletal manifestations. Other multisystemic features are often underdiagnosed. Moreover, the disease is characterized by age related penetrance. Diagnosis and management of MFS in the adult population are well-described in literature. Few studies are focused on MFS in the pediatric population, making the clinical approach (cardiac and multiorgan) to these cases challenging both in terms of diagnosis and serial follow-up. In this review, we provide an overview of MFS manifestations in children, with extensive revision of major organ involvement (cardiovascular ocular and skeletal). We attempt to shed light on minor aspects of MFS that can have a significant progressive impact on the health of affected children. MFS is an example of a syndrome where an early personalized approach to address a dynamic, genetically determined condition can make a difference in outcome. Applying an early multidisciplinary clinical approach to MFS cases can prevent acute and chronic complications, offer tailored management, and improve the quality of life of patients.

UNASSIGNED: Mathematical models play a crucial role in investigating complex biological systems, enabling a comprehensive understanding of interactions among various components and facilitating in silico testing of intervention strategies. Alzheimer\'s disease (AD) is characterized by multifactorial causes and intricate interactions among biological entities, necessitating a personalized approach due to the lack of effective treatments. Therefore, mathematical models offer promise as indispensable tools in combating AD. However, existing models in this emerging field often suffer from limitations such as inadequate validation or a narrow focus on single proteins or pathways.
UNASSIGNED: In this paper, we present a multiscale mathematical model that describes the progression of AD through a system of 19 ordinary differential equations. The equations describe the evolution of proteins (nanoscale), cell populations (microscale), and organ-level structures (macroscale) over a 50-year lifespan, as they relate to amyloid and tau accumulation, inflammation, and neuronal death.
UNASSIGNED: Distinguishing our model is a robust foundation in biological principles, ensuring improved justification for the included equations, and rigorous parameter justification derived from published experimental literature.
UNASSIGNED: This model represents an essential initial step toward constructing a predictive framework, which holds significant potential for identifying effective therapeutic targets in the fight against AD.

BACKGROUND: Cancer biomarkers have revolutionized the field of oncology by providing valuable insights into tumor changes and aiding in screening, diagnosis, prognosis, treatment prediction, and risk assessment. The emergence of \"omic\" technologies has enabled biomarkers to become reliable and accurate predictors of outcomes during cancer treatment.
BACKGROUND: In this review, we highlight the clinical utility of biomarkers in cancer identification and motivate researchers to establish a personalized/precision approach in oncology. By extending a multidisciplinary technology-based approach, biomarkers offer an alternative to traditional techniques, fulfilling the goal of cancer therapeutics to find a needle in a haystack.
UNASSIGNED: We target different forms of cancer to establish a dynamic role of biomarkers in understanding the spectrum of malignancies and their biochemical and molecular characterization, emphasizing their prospective contribution to cancer screening. Biomarkers offer a promising avenue for the early detection of human cancers and the exploration of novel technologies to predict disease severity, facilitating maximum survival and minimum mortality rates. This review provides a comprehensive overview of the potential of biomarkers in oncology and highlights their prospects in advancing cancer diagnosis and treatment.

Given its polygenic nature, there is a need for a personalized approach to schizophrenia. The aim of the study was to select laboratory biomarkers from blood, brain imaging, and clinical assessment, with an emphasis on patients\' self-report questionnaires. Metabolomics studies of serum samples from 51 patients and 45 healthy volunteers, based on the liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS/MS), led to the identification of 3 biochemical indicators (cortisol, glutamate, lactate) of schizophrenia. These metabolites were sequentially correlated with laboratory tests results, imaging results, and clinical assessment outcomes, including patient self-report outcomes. The hierarchical cluster analysis on the principal components (HCPC) was performed to identify the most homogeneous clinical groups. Significant correlations were noted between blood lactates and 11 clinical and 10 neuroimaging parameters. The increase in lactate and cortisol were significantly associated with a decrease in immunological parameters, especially with the level of reactive lymphocytes. The strongest correlations with the level of blood lactate and cortisol were demonstrated by brain glutamate, N-acetylaspartate and the concentrations of glutamate and glutamine, creatine and phosphocreatine in the prefrontal cortex. Metabolomics studies and the search for associations with brain parameters and self-reported outcomes may provide new diagnostic evidence to specific schizophrenia phenotypes.

Thyroid cancer (TC) is the most common malignant tumor of the endocrine glands and accounts to 3% of the total structure of oncological morbidity. Papillary thyroid cancer (PTC) is the most common histological variant of thyroid malignancies. It accounts for about 85% of all cases of thyroid cancer. Despite good postoperative results and excellent survival compared to many other malignancies, tumor metastases to the paratracheal lymph nodes are quite common. This review of the literature considers the current personalized approach to patients with papillary thyroid cancer and current aspects influencing the management of patients with PTC.
Рак щитовидной железы (РЩЖ) является наиболее частой злокачественной опухолью эндокринных желез и составляет до 3% в общей структуре онкологической заболеваемости. Папиллярный рак щитовидной железы (ПРЩЖ) является наиболее частым гистологическим вариантом злокачественных новообразований щитовидной железы, на его долю приходится около 85% всех случаев РЩЖ. Несмотря на благоприятные послеоперационные результаты и высокую выживаемость по сравнению со многими другими злокачественными заболеваниями, метастазы опухоли в паратрахеальные лимфатические узлы встречаются довольно часто. В обзоре литературы рассмотрен современный персонализированный подход к пациентам с ПРЩЖ и аспекты, влияющие на тактику ведения.

BACKGROUND: Pregnancy after liver transplantation poses a significant challenge to both the patient and the transplant team.
METHODS: We present the case of a 19-year-old European patient who underwent liver transplantation 5 years previously owing to autoimmune hepatitis. Poor compliance with immunosuppressive therapy and missed follow-up visits during the patient\'s first pregnancy likely contributed to her liver function deterioration, hospitalization, and failed pregnancy. Owing to the patient\'s complex medical history, combined immunosuppressive treatment, and risks to the fetus, her second pregnancy was high risk. However, close outpatient monitoring and adherence to treatment led to a successful, uneventful, full-term pregnancy and healthy delivery.
CONCLUSIONS: Liver transplant recipients who desire to become pregnant require careful planning and management to ensure optimal outcomes for both the mother and the fetus. A personalized strategy is necessary to balance the potential benefits of childbirth with the risks involved in pregnancy after liver transplantation.