Cancer remains a major health problem and is associated with cachexia in up to 80% of cases, leading to decreased survival and quality of life. Cachexia involves complex metabolic disturbances in both protein and energy balance, muscle wasting phenomena, weight loss, systemic inflammation, overall decreased performance status, and tolerability to treatment. The clinical impact of cancer cachexia is very complex, with early detection of cachectic patients and identification of predictive biomarkers being two key factors for improving survival. Thus, a better understanding of the complexity of cancer cachexia phenomena and its main pathophysiological mechanism is much needed. Our review highlights the most important information about cancer cachexia, aiming to disseminate updated research findings about this highly deadly condition.

Amiodarone hydrochloride is an antiarrhythmic drug, with proven efficacy in prevention and treatment of numerous arrhythmias, atrial fibrillation especially, or ventricular arrhythmias, with a long half-life (55–60 days). The increased risk of developing amiodarone-induced pulmonary fibrosis is directly related to the dose and the duration of the intake. Amiodarone-induced pulmonary toxicity is conditioned by dose, patient’s age, and pre-existent pulmonary pathologies. The pattern for drug-induced lung injury may vary in many forms, but the amiodarone can cause polymorphous injuries such as diffuse alveolar damage, chronical interstitial pneumonia, organizing pneumonia, pulmonary hemorrhage, lung nodules or pleural disease. The pathological mechanism of pulmonary injury induced by amiodarone consists of the accumulation of phospholipid complexes in histocytes and type II pneumocytes. Differential diagnosis of pulmonary fibrosis induced by amiodarone is made mainly with idiopathic pulmonary fibrosis, left ventricular failure or infectious disease. Before starting treatment with amiodarone, patients should be informed of potential adverse effects and any new respiratory symptoms should promptly be reported to their family physician or attending physician. The assessment carried out at the initiation of amiodarone treatment should include at least chest X-ray and respiratory function tests and extrapulmonary evaluation.

Background: Carotid endarterectomy (CEA) is the first-line surgical intervention for cases of severe carotid stenoses. Unfortunately, the restenosis rate is high after CEA. This study aims to demonstrate the predictive role of carotid plaque features and inflammatory biomarkers (monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)) in carotid restenosis and mortality at 12 months following CEA. Methods: The present study was designed as an observational, analytical, retrospective cohort study and included all patients over 18 years of age with a minimum of 70% carotid stenosis and surgical indications for CEA admitted to the Vascular Surgery Clinic, Emergency County Hospital of Targu Mures, Romania between 2018 and 2021. Results: According to our results, the high pre-operative values of inflammatory biomarkers—MLR (OR: 10.37 and OR: 6.11; p < 0.001), NLR (OR: 34.22 and OR: 37.62; p < 0.001), PLR (OR: 12.02 and OR: 16.06; p < 0.001), SII (OR: 18.11 and OR: 31.70; p < 0.001), SIRI (OR: 16.64 and OR: 9.89; p < 0.001), and AISI (OR: 16.80 and OR: 8.24; p < 0.001)—are strong independent factors predicting the risk of 12-month restenosis and mortality following CEA. Moreover, unstable plaque (OR: 2.83, p < 0.001 and OR: 2.40, p = 0.04) and MI (OR: 3.16, p < 0.001 and OR: 2.83, p = 0.005) were independent predictors of all outcomes. Furthermore, AH (OR: 2.30; p = 0.006), AF (OR: 1.74; p = 0.02), tobacco (OR: 2.25; p < 0.001), obesity (OR: 1.90; p = 0.02), and thrombotic plaques (OR: 2.77; p < 0.001) were all independent predictors of restenosis, but not for mortality in all patients. In contrast, antiplatelet (OR: 0.46; p = 0.004), statin (OR: 0.59; p = 0.04), and ezetimibe (OR:0.45; p = 0.03) therapy were protective factors against restenosis, but not for mortality. Conclusions: Our data revealed that higher preoperative inflammatory biomarker values highly predict 12-month restenosis and mortality following CEA. Furthermore, age above 70, unstable plaque, cardiovascular disease, and dyslipidemia were risk factors for all outcomes. Additionally, AH, AF, smoking, and obesity were all independent predictors of restenosis but not of mortality in all patients. Antiplatelet and statin medication, on the other hand, were protective against restenosis but not against mortality.

This comprehensive review explores the genetic contributions to endometriosis and their potential impact on improving diagnostic techniques. The review begins by defining endometriosis and discussing its prevalence, emphasizing the need for a deeper understanding of the genetic basis of the condition. It highlights recent genome-wide association studies (GWAS) that have identified specific genetic variants associated with endometriosis, shedding light on the molecular pathways and mechanisms involved. The review addresses genetic heterogeneity across different populations and ethnicities, emphasizing the importance of considering population-specific markers in diagnostic approaches. It explores the diagnostic implications of genetic insights, including the potential use of genetic markers for precise and early detection, as well as risk prediction. The review also delves into the integration of genetic information with clinical parameters and imaging findings, and the exploration of multi-omics approaches for a comprehensive understanding of endometriosis. It discusses recent studies on genetic and epigenetic biomarkers, their potential as diagnostic tools, and the need for validation in independent cohorts. The review highlights the impact of new genomic technologies, such as next-generation sequencing, in improving diagnostic accuracy and personalized management. It identifies the challenges and future directions in translating genetic findings into diagnostic tools and emphasizes the transformative potential of genetic insights in endometriosis diagnosis. This review provides a roadmap for future research and underscores the significance of genetic insights in improving diagnostic precision and personalized care for individuals with endometriosis.

Background: Psoriasis is an immune-mediated chronic disorder associated with various comorbidities. Even though biologics and small-molecule inhibitors are the mainstay treatment for moderate-to-severe psoriasis, there is no current consensus regarding which agent should be used for a specific type of patient. This paper aims to test the reliability of blood-count-derived inflammatory markers in assessing treatment response to biologics and small-molecule inhibitors in psoriasis. Material and Methods: Bio-naïve adult patients diagnosed with chronic plaque psoriasis fulfilling the inclusion criteria were enrolled. They were divided into study subgroups based on treatment of choice, and blood-count-derived inflammatory markers were analyzed at baseline, three-month, six-month, and at twelve-month visits. Results: A total of 240 patients were included. The highest number of patients underwent treatment with ixekizumab. The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), platelet-to-monocyte ratio (PMR), monocyte-to-lymphocyte ratio (MLR), derived neutrophil-to-lymphocyte ratio (d-NLR), systemic inflammation response index (SIRI), systemic immune inflammation index (SII), and aggregate index of systemic inflammation (AISI) all varied significantly (p < 0.005) between the four visits. The psoriasis area severity index (PASI) score correlated with PLR, d-NLR, and SII, while the psoriasis scalp severity index (PSSI) score correlated with AISI and SIRI. More than half of patients reached the target goal of PASI90 at the six-month visit. A total of 77 patients were super-responders, with the highest number undergoing treatment with ixekizumab. Higher baseline values of d-NLR and SIRI are independent predictors of the super-responder status. Conclusions: Blood-count-derived inflammatory markers can serve as indicators of treatment response to biologics in psoriasis, while d-NLR and SIRI were independent predictors of super-responders in our study.

Psoriasis is a chronic immune-mediated disease, linked to local and systemic inflammation and predisposing patients to a higher risk of associated comorbidities. Cytokine levels are not widely available for disease progression monitoring due to high costs. Validated low-cost and reliable markers are needed for assessing disease progression and outcome. This study aims to assess the reliability of blood-count-derived inflammatory markers as disease predictors and to identify prognostic factors for disease severity. Patients fulfilling the inclusion criteria were enrolled in this study. Patients were divided into three study groups according to disease severity measured by the Body Surface Area (BSA) score: mild, moderate, and severe psoriasis. White blood cell count (WBC), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), derived neutrophil-to-lymphocyte ratio (d-NLR), systemic immune index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) positively were correlated with disease severity (p < 0.005). d-NLR, NLR, and SII are independent prognostic factors for mild and moderate psoriasis (p < 0.05). d-NLR is the only independent prognostic factor for all three study groups. Moderate psoriasis is defined by d-NLR values between 1.49 and 2.19. NLR, PLR, d-NLR, MLR, SII, SIRI, and AISI are useful indicators of systemic inflammation and disease severity in psoriasis.