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Introduction: Acute COVID-19 infection causes significant alterations in the innate and adaptive immune systems. While most individuals recover naturally, some develop long COVID (LC) syndrome, marked by persistent or new symptoms weeks to months after SARS-CoV-2 infection. Despite its prevalence, there are no clinical tests to distinguish LC patients from those fully recovered. Understanding the immunological basis of LC is essential for improving diagnostic and treatment approaches. Methods: We performed deep immunophenotyping and functional assays to examine the immunological profiles of LC patients, individuals with active COVID-19, recovered patients, and healthy donors. This analysis assessed both innate and adaptive immune features, identifying potential biomarkers for LC syndrome. A Binomial Generalized Linear Model (BGLM) was used to pinpoint immune features characterizing LC. Results: COVID-19 patients exhibited depletion of innate immune cell subsets, including plasmacytoid and conventional dendritic cells, classical, non-classical, and intermediate monocytes, and monocyte-derived inflammatory dendritic cells. Elevated basal inflammation was observed in COVID-19 patients compared to LC patients, whose immune profiles were closer to those of healthy donors and recovered individuals. However, LC patients displayed persistent immune alterations, including reduced T cell subsets (CD4, CD8, Tregs) and switched memory B cells, similar to COVID-19 patients. Through BGLM, a unique adaptive immune signature for LC was identified, featuring memory CD8 and gd T cells with low proliferative capacity and diminished expression of activation and homing receptors. Discussion: The findings highlight a unique immunological signature associated with LC syndrome, characterized by persistent adaptive immune dysregulation. While LC patients displayed recovery in innate immune profiles comparable to healthy and Recovered individuals, deficits in T cell and memory B cell populations were evident, differentiating LC from full recovery. These findings provide insights into LC pathogenesis and may support the development of diagnostic tools and targeted therapies. [ABSTRACT FROM AUTHOR]

Background: Antibiotic resistance represents a growing concern. A new strategy developed to treat severe infections is represented by ceftazidime/avibactam (CZA/AVI). Despite the promising activities against more pathogens, continuous monitoring is required to identify potential antibiotic resistance in clinical practice settings. Therefore, real-world data from pharmacovigilance databases can help to better define the safety profile. Methods: We analyzed all Individual Case Safety Reports (ICSRs) collected in the EudraVigilance database focusing on ICSRs with at least one adverse event (AE) potentially suggestive of drug resistance (DR) and drug ineffectiveness (DI). Results: A total of 654 ICSRs related to CZA/AVI were retrieved from EudraVigilance, of which N = 378 (57.8%) were related to male and N = 230 (35.1%) to adult patients. A total of 80.2% of all AEs were serious but with a positive outcome. Overall, we found N = 129 (19.7%) cases of potential DR or DI after CZA/AVI administration. The majority of CZA/AVI-induced DR or DI occurred in adult male patients. The most frequently reported AEs were "drug ineffective" and "pathogen resistance". Lastly, CZA/AVI was mostly used for the treatment of "Klebsiella infection" and "Pneumonia". Conclusions: The present study showed how pharmacovigilance could play a key role in generating evidence about the safety profile of CZA/AVI. Further studies are warranted. [ABSTRACT FROM AUTHOR]

Introduction: Effective pain management is crucial for patient care, impacting comfort, recovery, and overall well-being. Traditional subjective pain assessment methods can be challenging, particularly in specific patient populations. This research explores an alternative approach using computer vision (CV) to detect pain through facial expressions. Methods: The study implements the YOLOv8 real-time object detection model to analyze facial expressions indicative of pain. Given four pain datasets, a dataset of pain-expressing faces was compiled, and each image was carefully labeled based on the presence of pain-associated Action Units (AUs). The labeling distinguished between two classes: pain and no pain. The pain category included specific AUs (AU4, AU6, AU7, AU9, AU10, and AU43) following the Prkachin and Solomon Pain Intensity (PSPI) scoring method. Images showing these AUs with a PSPI score above 2 were labeled as expressing pain. The manual labeling process utilized an open-source tool, makesense.ai, to ensure precise annotation. The dataset was then split into training and testing subsets, each containing a mix of pain and no-pain images. The YOLOv8 model underwent iterative training over 10 epochs. The model's performance was validated using precision, recall, and mean Average Precision (mAP) metrics, and F1 score. Results: When considering all classes collectively, our model attained a mAP of 0.893 at a threshold of 0.5. The precision for "pain" and "nopain" detection was 0.868 and 0.919, respectively. F1 scores for the classes "pain", "nopain", and "all classes" reached a peak value of 0.80. Finally, the model was tested on the Delaware dataset and in a real-world scenario. Discussion: Despite limitations, this study highlights the promise of using real-time computer vision models for pain detection, with potential applications in clinical settings. Future research will focus on evaluating the model's generalizability across diverse clinical scenarios and its integration into clinical workflows to improve patient care. [ABSTRACT FROM AUTHOR]

Dexmedetomidine, a selective α2-adrenergic agonist, is favoured in intensive care for its minimal respiratory depression. This study evaluated the reporting frequency of rhabdomyolysis with dexmedetomidine compared to midazolam and propofol using the European pharmacovigilance database Eudravigilance. We conducted an observational, retrospective analysis of Individual Case Safety Reports (ICSRs) from 1 January 2013, to 31 December 2023. Primary and secondary outcomes included the reporting frequencies of rhabdomyolysis and its indicative signs and symptoms, respectively. We retrieved 19,268 ICSRs, of which 364 reported rhabdomyolysis associated with dexmedetomidine (3.8%), midazolam (10.2%), propofol (76.9%), or combinations thereof (9.1%). Dexmedetomidine showed a significantly lower reporting frequency of rhabdomyolysis compared to propofol (ROR, 0.32; 95% CI, 0.19–0.55) but no significant difference compared to midazolam. Subgroup analyses revealed higher frequencies in males, especially with propofol. Despite limitations such as underreporting, our findings suggest dexmedetomidine poses a lower rhabdomyolysis risk than propofol, supporting its safe use for sedation in high-risk patients. It is important to note that due to the retrospective design of this study our findings are indicative of correlations rather than causation. Continuous monitoring and further studies are recommended to validate these results. [ABSTRACT FROM AUTHOR]

Background: Pericapsular nerve group (PENG) block, although effective for pain management following total hip arthroplasty (THA), does not cover skin analgesia. In this randomized controlled trial, we compared the effectiveness of PENG block combined with lateral femoral cutaneous nerve (LFCN) block or wound infiltration (WI) on postoperative analgesia and functional outcomes. Methods: Fifty patients undergoing posterior-approached THA under spinal anesthesia were randomly allocated to receive LFCN block with 10 mL of 0.5% ropivacaine or WI with 20 mL of 0.5% ropivacaine. In both groups, PENG block was performed by injecting 20 mL of 0.5% ropivacaine. Primary outcomes were static and dynamic pain scores (0–10 numeric rating scale) measured in the first 24 h after surgery. Secondary outcomes included postoperative opioid consumption, functional assessment and length of hospital stay. Results: Postoperative static NRS of patients receiving LFCN was higher than that of patients receiving WI at 6 h but lower at 24 h, with a median (IQR) of 3 (2–4) vs. 2 (1–2) (p < 0.001) and 2 (2–3) vs. 3 (3–4) (p = 0.02), respectively. Static pain scores at 12 h did not show significant differences, with an NRS of 3 (2–4) for WI vs. 3 (3–4) for LFCN (p = 0.94). Dynamic pain and range of movement followed a similar trend. No significant differences were detected in other outcomes. Conclusions: LFCN block was not inferior to WI for postoperative analgesia and functional recovery in association with PENG block during the first postoperative day, although it had worse short-term pain scores. Based on these results, it is reasonable to consider LFCN block as a valid alternative to WI or even a complementary technique added to WI to enhance skin analgesia during the first 24 h after THA. Future studies are expected to confirm this hypothesis and find the best combination between PENG block and other techniques to enhance analgesia after THA. [ABSTRACT FROM AUTHOR]

The composition of the intestinal microbiota plays a critical role in shaping the immune system. Modern lifestyle, the inappropriate use of antibiotics, and exposure to pollution have significantly affected the composition of commensal microorganisms. The intestinal microbiota has been shown to sustain inappropriate autoimmune responses at distant sites in animal models of disease, and may also have a role in immune-mediated central nervous system (CNS) diseases such as multiple sclerosis (MS). We studied the composition of the gut mycobiota in fecal samples from 27 persons with MS (pwMS) and in 18 healthy donors (HD), including 5 pairs of homozygous twins discordant for MS. We found a tendency towards higher fungal abundance and richness in the MS group, and we observed that MS twins showed a higher rate of food-associated strains, such as Saccharomyces cerevisiae. We then found that in pwMS, a distinct population of cells with antibacterial and antifungal activity is expanded during the remitting phase and markedly decreases during clinically and/or radiologically active disease. These cells, named MAIT (mucosal-associated invariant T cells) lymphocytes, were significantly more activated in pwMS compared to HD in response to S. cerevisiae and Candida albicans strains isolated from fecal samples. This activation was also mediated by fungal-induced IL-23 secretion by innate immune cells. Finally, immunofluorescent stainings of MS post-mortem brain tissues from persons with the secondary progressive form of the disease showed that MAIT cells cross the blood–brain barrier (BBB) and produce pro-inflammatory cytokines in the brain. These results were in agreement with the hypothesis that dysbiosis of the gut microbiota might determine the inappropriate response of a subset of pathogenic mucosal T cells and favor the development of systemic inflammatory and autoimmune diseases. [ABSTRACT FROM AUTHOR]