Colorectal cancer (CRC) constitutes a significant global health challenge, with recent studies underscoring the pivotal role of the gut microbiome in its pathogenesis and progression. Fecal microbiota transplantation (FMT) has emerged as a compelling therapeutic approach, offering the potential to modulate microbial composition and optimize treatment outcomes. Research suggests that specific bacterial strains are closely linked to CRC, influencing both its clinical management and therapeutic interventions. Moreover, the gut microbiome’s impact on immunotherapy responsiveness heralds new avenues for personalized medicine. Despite the promise of FMT, safety concerns, particularly in immunocompromised individuals, remain a critical issue. Clinical outcomes vary widely, influenced by genetic predispositions and the specific transplantation methodologies employed. Additionally, rigorous donor selection and screening protocols are paramount to minimize risks and maximize therapeutic efficacy. The current body of literature advocates for the establishment of standardized protocols and further clinical trials to substantiate FMT’s role in CRC management. As our understanding of the microbiome deepens, FMT is poised to become a cornerstone in CRC treatment, underscoring the imperative for continued research and clinical validation.

Introduction: Critically ill patients in intensive care units (ICUs) are at high risk of malnutrition, which can result in muscle atrophy, polyneuropathy, increased mortality, or prolonged hospitalizations with complications and higher costs during the recovery period. They often develop ICU-acquired weakness, exacerbated by sepsis, immobilization, and drug treatments, leading to rapid muscle mass loss and long-term complications. Studies indicate that adequate protein and calorie intake can decrease mortality and improve prognosis and recovery. However, optimal implementation remains a critical challenge. Objectives: This narrative review aims to summarize recent advances in nutritional strategies for critically ill patients. It highlights the benefits and limitations of current approaches including enteral (EN) and parenteral nutrition (PN) and examines their impact on clinical outcomes and overall mortality. Additionally, the review explores the emerging role of precision nutrition in critical care using technologies such as metabolomics and artificial intelligence (AI) to provide valuable insights into optimizing nutritional care in critically ill patients. Methods: A comprehensive literature search was conducted to identify recent studies, clinical guidelines, and expert consensus papers on nutritional support for ICU patients. The investigation focused on critical aspects such as the optimal timing for intervention, the route of administration, specific protein and energy targets, and technological innovations to support personalized nutrition, ensuring that each patient receives tailored support based on their unique needs. Results: Guidelines recommend initiating EN or PN nutrition within the first 48 h of admission, using indirect calorimetry (IC) to estimate energy needs, and supplementing protein up to 1.2 g/kg/day after stabilization. IC has gained importance in assessing energy needs but is still underused in the ICU. EN is preferred because it maintains intestinal integrity, reduces the risk of infections, and is recommended within the first 48 h of ICU admission. PN is used when EN is infeasible, but it increases the risk of infection. By integrating metabolomics with transcriptomic and genomic data, we can gain a deeper understanding of the effect of nutrition on cellular homeostasis, facilitating personalized treatments and enhancing the recovery of critically ill patients. Conclusions: AI is becoming increasingly important in monitoring and evaluating artificial nutrition, providing a more accurate and efficient alternative to traditional methods. AI can assist in identifying and managing malnutrition and is effective for estimating caloric and nutrient intake. AI minimizes human error, enables continuous monitoring, and integrates various data sources. The nutritional care of critically ill patients requires collaboration among specialists from diverse fields, including physicians, nutritionists, pharmacists, radiologists, IT experts, and policymakers.

The human gastrointestinal tract houses a diverse array of probiotic and pathogenic bacteria and any alterations in this microbial composition can exert a significant influence on an individual’s well-being. It is well-established that imbalances in the gut microbiota play a pivotal role in the development of liver diseases. In light of this, a new adjuvant therapy for liver diseases could be regulating the intestinal microbiota. Through fecal microbiota transplantation, patients whose microbiomes are compromised are treated with stool from healthy donors in an attempt to restore a normal microbiome and alleviate their symptoms. A review of cross-sectional studies and case reports suggests that fecal microbiota transplants may offer effective treatment for chronic liver diseases. Adding to the potential of this emerging therapy, recent research has indicated that fecal microbiota transplantation holds promise as a therapeutic approach specifically for liver cirrhosis. By introducing a diverse range of beneficial microorganisms into the gut, this innovative treatment aims to address the microbial imbalances often observed in cirrhotic patients. While further validation is still required, these preliminary findings highlight the potential impact of fecal microbiota transplantation as a novel and targeted method for managing liver cirrhosis. We aimed to summarize the current state of understanding regarding this procedure, as a new therapeutic method for liver cirrhosis, as well as to explain its clinical application and future potential.

Introduction: A key element for a healthy lifestyle in the formative years of a young adult is a balanced, healthy, individualized diet. Aim: The aim of this study was to analyze the eating behavior and lifestyles of students at a university in Romania, as well as the extent to which the study program interferes with these factors. Methods: A retrospective study was performed, with the data being collected through an online questionnaire via the Google Forms platform; data collection for the current study was carried out in November 2024 during a student session. Results: Out of the total of 501 questionnaires collected, 416 were completed by women and 85 by men. It can be observed that 57.65% of men (49 participants) eat three meals a day compared to 53.13% of women (221 participants). The university program influenced the students’ meal schedules for 59.88% (n = 300) of participants, while 30.94% (n = 155) declared that they never have an ordered meal schedule. For 39.92% of students, the exam period has an influence on the meal schedule, including an increase the intake of sweet foods (59.88%), and some declared that they forget to eat (33.93%). Conclusions: The food and lifestyle behaviors in the studied group show health risk elements, especially an increase in tobacco consumption, a lack of regular meal schedules, and the consumption of an excess of unhealthy snacks. It was found that intensive study schedules may intensify this behavior.

Background/Objectives: Ventilator-associated pneumonia (VAP) is the most common nosocomial infection encountered in the intensive care unit (ICU) and is associated with prolonged hospitalization and increased mortality. We evaluated the causative pathogens involved and their resistance to the major classes of antibiotics in patients with VAP and assessed the differences between patients with and without coronavirus disease 2019 (COVID-19). Materials and Methods: This study was a single-center, cross-sectional, retrospective analysis involving 122 patients who were hospitalized in the ICU of Târgu Mureș County Clinical Hospital from 1 April 2021, to 1 April 2023. This study compares patients with VAP in COVID-19 and non-COVID-19 groups, examining the clinical progression, duration of ventilation and hospitalization, mortality, pathogen distribution, and the emergence of multidrug-resistant strains. Results: A length of stay in the ICU exceeding 11.5 days was associated with the development of multidrug-resistant (MDR) infections (AUC: 0.708, p < 0.001). Similarly, a duration of MV exceeding 196 h was associated with MDR acquisition (AUC: 0.695, p = 0.002). Additionally, a Clinical Pulmonary Infection Score (CPIS) greater than 5 was associated with MDR development (AUC: 0.854, p < 0.001) in the whole group of patients. The most commonly isolated strains were Acinetobacter spp., Pseudomonas spp., Klebsiella spp., and Staphylococcus aureus. Among non-COVID-19 patients, there was a notably higher frequency of MDR Acinetobacter baumannii. A bacterial resistance to carbapenems was found in Acinetobacter spp. (51.6%), Klebsiella spp. (22.6%), and Pseudomonas spp. (25.8%). Conclusions: COVID-19 patients experienced longer ventilation, higher mortality, and an increased risk of developing MDR. Carbapenem resistance was universal in Acinetobacter spp. and Klebsiella pneumoniae, whereas resistance in Pseudomonas aeruginosa was more prevalent among non-COVID-19 patients. The Clinical Pulmonary Infection Score (CPIS) strongly correlates with developing MDR pathogens in both patient groups.

Gastric cancer stands as the fourth leading cause of cancer-related deaths globally, primarily comprising adenocarcinomas, categorized by anatomic location and histologic type. Often diagnosed at advanced stages, gastric cancer prognosis remains poor. To address the critical need for accurate tumoral markers for gastric cancer diagnosis, we conducted a study to assess classical markers like CEA and CA-19-9 alongside the novel marker miR-106. Our investigation revealed distinct dynamics of these markers compared to non-cancerous groups, although no disparities were observed across different disease stages. Univariable and multivariable logistic regression analyses demonstrated that elevated levels of miR-106, CEA and CA 19-9 were predictive of a positive histopathological exam, with the respective odds ratios of 12.032 (95% CI: 1.948–74.305), 30 (95% CI: 3.141–286.576), and 55.866 (95% CI: 4.512–691.687). Subsequently, we utilized predicted probabilities from regression models to construct receiver operating characteristic (ROC) curves, identifying CA 19-9 as the optimal predictor for gastric adenocarcinoma diagnosis when considering age and gender, with an area under the curve (AUC) of 0.936 (p < 0.001). Hence, classical markers exhibit superior performance compared to the novel marker miR-106 in predicting gastric adenocarcinoma.