Subfertility, a prevalent and emotionally taxing condition affecting couples worldwide, has garnered increasing attention in reproductive health. While its etiology remains multifaceted, emerging research has explored the role of serum homocysteine levels and nutrient deficiencies in influencing subfertility. This comprehensive review synthesizes current knowledge, beginning with an introduction to subfertility and the significance of investigating serum homocysteine levels. It proceeds to elucidate the role of nutrient deficiencies, particularly folate and vitamin B12, in homocysteine metabolism and examines existing research linking homocysteine to subfertility. The review explores potential mechanisms underlying this relationship, addressing the variability in study findings and their contributing factors. Implications for clinical practice, including assessing serum homocysteine levels, nutritional interventions, and personalized medicine, are discussed. Moreover, the review underscores the importance of ongoing research. It offers a call to action for advancing our understanding of subfertility and improving the lives of individuals and couples navigating reproduction challenges.

The shift towards personalized cancer medicine (PCM) represents a significant transformation in cancer care, emphasizing tailored treatments based on the genetic understanding of cancer at the cellular level. This review draws on recent literature to explore key factors influencing PCM implementation, highlighting the role of innovative leadership, interdisciplinary collaboration, and coordinated funding and regulatory strategies. Success in PCM relies on overcoming challenges such as integrating diverse medical disciplines, securing sustainable investment for shared infrastructures, and navigating complex regulatory landscapes. Effective leadership is crucial for fostering a culture of innovation and teamwork, essential for translating complex biological insights into personalized treatment strategies. The transition to PCM necessitates not only organizational adaptation but also the development of new professional roles and training programs, underscoring the need for a multidisciplinary approach and the importance of team science in overcoming the limitations of traditional medical paradigms. The conclusion underscores that PCM\'s success hinges on creating collaborative environments that support innovation, adaptability, and shared vision among all stakeholders involved in cancer care.

BACKGROUND: Wernicke encephalopathy (WE) is an acute and potentially fatal neuropsychiatric disorder resulting from thiamine deficiency: its etiology and clinical presentation can be heterogeneous and arduously recognized, especially in children and adolescents.
METHODS: An 8-year-old girl arrived to the emergency room with ataxic gait, nystagmus, and mental confusion after a 10-day history of repeated severe vomiting; her recent clinical history was characterized by restricted nutrition due to a choking phobia, which caused substantial weight loss. Brain magnetic resonance imaging revealed a bilaterally increased T2 signal in the medial areas of the thalami and cerebral periaqueductal region. Diagnosis of WE based on clinical and neuroradiological findings was established and confirmed after labwork showing low serum thiamine. Following psychiatric evaluation, the patient was also diagnosed with avoidance-restrictive food intake disorder (ARFID), which required starting cognitive behavioral therapy and introducing aripiprazole. The patient displayed improvement of the radiological findings after one month and complete resolution of her neurological symptoms and signs.
CONCLUSIONS: Eating disorders like ARFID might forerun acute signs of WE; this possibility should be considered even in pediatric patients, especially when atypical neurological pictures or feeding issues come out.

Artificial intelligence (AI) has emerged as a powerful tool to revolutionize the healthcare sector, including drug delivery and development. This review explores the current and future applications of AI in the pharmaceutical industry, focusing on drug delivery and development. It covers various aspects such as smart drug delivery networks, sensors, drug repurposing, statistical modeling, and simulation of biotechnological and biological systems. The integration of AI with nanotechnologies and nanomedicines is also examined. AI offers significant advancements in drug discovery by efficiently identifying compounds, validating drug targets, streamlining drug structures, and prioritizing response templates. Techniques like data mining, multitask learning, and high-throughput screening contribute to better drug discovery and development innovations. The review discusses AI applications in drug formulation and delivery, clinical trials, drug safety, and pharmacovigilance. It addresses regulatory considerations and challenges associated with AI in pharmaceuticals, including privacy, data security, and interpretability of AI models. The review concludes with future perspectives, highlighting emerging trends, addressing limitations and biases in AI models, and emphasizing the importance of collaboration and knowledge sharing. It provides a comprehensive overview of AI\'s potential to transform the pharmaceutical industry and improve patient care while identifying further research and development areas.

Biobanks, through the collection and storage of patient blood, tissue, genomic, and other biological samples, provide unique and rich resources for the research and management of chronic diseases such as cardiovascular diseases, diabetes, and cancer. These samples contain valuable cellular and molecular level information that can be utilized to decipher the pathogenesis of diseases, guide the development of novel diagnostic technologies, treatment methods, and personalized medical strategies. This article first outlines the historical evolution of biobanks, their classification, and the impact of technological advancements. Subsequently, it elaborates on the significant role of biobanks in revealing molecular biomarkers of chronic diseases, promoting the translation of basic research to clinical applications, and achieving individualized treatment and management. Additionally, challenges such as standardization of sample processing, information privacy, and security are discussed. Finally, from the perspectives of policy support, regulatory improvement, and public participation, this article provides a forecast on the future development directions of biobanks and strategies to address challenges, aiming to safeguard and enhance their unique advantages in supporting chronic disease prevention and treatment.

BACKGROUND: Pharmacogenetics evaluates how genetic variations influence drug responses. Nowadays, genetic tests have advanced, becoming more affordable, and its integration is supported by stronger clinical evidence. Guidelines such as those from CPIC (Clinical Pharmacogenetics Implementation Consortium) and resources like PharmGKB facilitate genotype-based prescribing; and organizations like the FDA promote genetic testing before initiating certain medications. Preventive pharmacogenetic panels seem promising, but further research on biomarkers and diverse populations is needed. The aim of this review is to analyze recent evidence on the genotype-drug response relationship to examine how the genetic profile of patients influences the clinical response to treatments, and analyze the areas of research that need further study to advance towards a genetic-based precision medicine.
METHODS: A systematic search was conducted on PubMed to identify articles investigating the genotype-drug response relationship. The search strategy included terms such as \"pharmacogenetics\", \"personalized treatment\", \"precision medicine\", \"dose adjustment\", \"individualized dosing\", \"clinical routine\" and \"clinical practice.\" Clinical trials, observational studies, and meta-analyses published in English or Spanish between 2013 and 2023 were included. The initial search resulted in a total of 136 articles for analysis.
RESULTS: 49 articles were included for the final analysis following review by two investigators. A relationship between genetic polymorphisms and drug response or toxicity was found for drugs such as opioids, GLP-1 agonists, tacrolimus, oral anticoagulants, antineoplastics, atypical antipsychotics, efavirenz, clopidogrel, lamotrigine, anti-TNF-α agents, voriconazole, antidepressants, or statins. However, for drugs like metformin, quetiapine, irinotecan, bisoprolol, and anti-VEGF agents, no statistically significant association between genotype and response was found.
CONCLUSIONS: The studies analyzed in this review suggest a strong correlation between genetic variability and individual drug responses, supporting the use of pharmacogenetics for treatment optimization. However, for certain drugs like metformin or quetiapine, the influence of genotype on their response remains unclear. More studies with larger sample sizes, greater ethnic diversity, and consideration of non-genetic factors are needed. The lack of standardization in analysis methods and accessibility to genetic testing are significant challenges in this field. As a conclusion, pharmacogenetics shows immense potential in personalized medicine, but further research is required.

In the United States, cancer is one of the major causes of death. In 2010 alone, over 1.5 million fresh instances were recorded and over 0.5 billion died. After the completion of human genome sequence, significant progress in characterizing human epigenomes, proteomes and metabolomes has been made; a stronger knowledge of pharmacogenomics has been established and the capacity for individual personalization of health care has grown considerably. Personalized medicine has recently been primarily used to systematically select or optimize the prevention and therapeutic care of the patient through genetic or other data about the particular patient. Molecular profiling in healthy samples and cancer patients can allow for more personalized medications than is currently available. Patient protein, genetic and metabolic information may be used for adapting medical attention to the needs of that individual. The development of complementary diagnostics is a key attribute of this medicinal model. Molecular tests measuring the level of proteins, genes or specific mutations are used to provide a specific treatment for a particular individual by stratify the status of a disease, selecting the right drugs and tailoring dosages to the particular needs of the patient. These methods are also available for assessing risk factors for a patient for a number of conditions and for tailoring individual preventive therapies. Recent advances of personalized cancer medicine, challenges and futures perspectives are discussed.

Ischemic heart disease represents a significant global burden of morbidity and mortality. While revascularization strategies are well defined in acute settings, there are uncertainties regarding chronic coronary artery disease treatment. Recent trials have raised doubts about the necessity of revascularization for \"stable\", chronic coronary syndromes or disease, leading to a shift towards a more conservative approach. However, the issue remains far from settled. In this narrative review, we offer a summary of the most pertinent evidence regarding revascularization for chronic coronary disease, while reflecting on less-often-discussed details of major clinical trials. The cumulative evidence available indicates that there can be a prognostic benefit from revascularization in chronic coronary syndrome patients, provided there is significant ischemia, as demonstrated by either imaging or coronary physiology. Trials that have effectively met this criterion consistently demonstrate a reduction in rates of spontaneous myocardial infarction, which holds both prognostic and clinical significance. The prognostic benefit of revascularization in patients with heart failure with reduced ejection fraction remains especially problematic, with a single contemporary trial favouring surgical revascularization. The very recent publication of a trial focused on revascularizing non-flow-limiting \"vulnerable\" plaques adds further complexity to the field. The ongoing debates surrounding revascularization in chronic coronary syndromes emphasize the importance of personalized strategies. Revascularization, added to the foundational pillar of medical therapy, should be considered, taking into account symptoms, patient preferences, coronary anatomy and physiology, ischemia tests and intra-coronary imaging.

This comprehensive review explores the mechanical and anatomical axis approaches in total knee replacement (TKR) surgery, addressing the ongoing debate within the orthopedic community. Emphasizing the significance of TKR in alleviating knee-related disorders, this review underscores the pivotal role of accurate alignment in achieving optimal surgical outcomes. The purpose is to navigate the divide between the well-established mechanical axis approach, focusing on a straight-line alignment, and the anatomical axis approach, aligning with natural knee landmarks. The analysis delves into the advantages, disadvantages, and clinical implications of each approach, offering a nuanced perspective on their efficacy. The conclusion emphasizes a patient-centric approach, recommending the adoption of hybrid strategies and the incorporation of emerging technologies for enhanced precision. The future of TKR aligns with personalized medicine, leveraging advancements in computer-assisted navigation, robotics, and patient-specific implants. Ongoing professional development and interdisciplinary collaboration are crucial for surgeons, and as the field evolves, innovations in artificial intelligence, imaging, and 3D printing are expected to shape the trajectory of TKR alignment approaches.

OBJECTIVE: The present study aims to review the existing literature to identify pathophysiological proteins in obesity by conducting a systematic review of proteomics studies. Proteomics may reveal the mechanisms of obesity development and clarify the links between obesity and related diseases, improving our comprehension of obesity and its clinical implications.
RESULTS: Most of the molecular events implicated in obesity development remain incomplete. Proteomics stands as a powerful tool for elucidating the intricate interactions among proteins in the context of obesity. This methodology has the potential to identify proteins involved in pathological processes and to evaluate changes in protein abundance during obesity development, contributing to the identification of early disease predisposition, monitoring the effectiveness of interventions and improving disease management overall. Despite many non-targeted proteomic studies exploring obesity, a comprehensive and up-to-date systematic review of the molecular events implicated in obesity development is lacking. The lack of such a review presents a significant challenge for researchers trying to interpret the existing literature. This systematic review was conducted following the PRISMA guidelines and included sixteen human proteomic studies, each of which delineated proteins exhibiting significant alterations in obesity. A total of 41 proteins were reported to be altered in obesity by at least two or more studies. These proteins were involved in metabolic pathways, oxidative stress responses, inflammatory processes, protein folding, coagulation, as well as structure/cytoskeleton. Many of the identified proteomic biomarkers of obesity have also been reported to be dysregulated in obesity-related disease. Among them, seven proteins, which belong to metabolic pathways (aldehyde dehydrogenase and apolipoprotein A1), the chaperone family (albumin, heat shock protein beta 1, protein disulfide-isomerase A3) and oxidative stress and inflammation proteins (catalase and complement C3), could potentially serve as biomarkers for the progression of obesity and the development of comorbidities, contributing to personalized medicine in the field of obesity. Our systematic review in proteomics represents a substantial step forward in unravelling the complexities of protein alterations associated with obesity. It provides valuable insights into the pathophysiological mechanisms underlying obesity, thereby opening avenues for the discovery of potential biomarkers and the development of personalized medicine in obesity.