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Viral infections are one of the major causes of death worldwide, with HIV infection alone resulting in over 1.2 million casualties per year. Antiviral drugs are now being administered for a variety of viral infections, including HIV, hepatitis B and C, and influenza. These therapies target a specific phase of the virus's life cycle, yet their ultimate success depends on a variety of factors, such as adherence to a prescribed regimen and the emergence of viral drug resistance. The epidemiology and evolution of drug resistance have been extensively characterized, and it is generally assumed that drug resistance arises from mutations that alter the virus's susceptibility to the direct action of the drug. In this paper, we consider the possibility that a virus population can evolve towards synchronizing its life cycle with the pattern of drug therapy. The periodicity of the drug treatment could then allow for a virus strain whose life cycle length is a multiple of the dosing interval to replicate only when the concentration of the drug is lowest. This process, referred to as \"drug tolerance by synchronization\", could allow the virus population to maximize its overall fitness without having to alter drug binding or complete its life cycle in the drug's presence. We use mathematical models and stochastic simulations to show that life cycle synchronization can indeed be a mechanism of viral drug tolerance. We show that this effect is more likely to occur when the variability in both viral life cycle and drug dose timing are low. More generally, we find that in the presence of periodic drug levels, time-averaged calculations of viral fitness do not accurately predict drug levels needed to eradicate infection, even if there is no synchronization. We derive an analytical expression for viral fitness that is sufficient to explain the drug-pattern-dependent survival of strains with any life cycle length. We discuss the implications of these findings for clinically relevant antiviral strategies.

Compartments are ubiquitous throughout biology, yet their importance stretches back to the origin of cells. In the context of origin of life, we assume that a protocell, a compartment enclosing functional components, requires \\(N\\) components to be evolvable. We take interest in the timescale in which a minimal evolvable protocell is produced. We show that when protocells fuse and share information, the time to produce an evolvable protocell scales algebraically in \\(N\\), in contrast to an exponential scaling in the absence of fusion. We discuss the implications of this result for origins of life, as well as other biological processes.

ABSTRACT Chromophobe renal cell carcinoma (CRCC) is a distinct subtype of renal cell carcinoma with unique histological, immunohistochemical, cytogenetic, and ultrastructural features, which usually has a favorable clinical course, with only a small percentage of patients developing recurrence, metastasis, or death due to its complications. Sarcomatoid differentiation can occur in any subtype of renal cell carcinoma and currently represents the transformation into a higher degree of malignancy, its presence being associated with a reserved prognosis, with a reported incidence of average survival of less than 1 year after diagnosis. In this study, we present an unusual case of CRCC with massive sarcomatoid differentiation, which infiltrated the left adrenal gland and was surgically resected. The histological features of this tumor as well as a brief review of literature are presented.

Psoriasis vulgaris is a chronic, immune-mediated, inflammatory, polygenic skin disorder affecting approximately 2% of the population. It has a great impact on quality of life; patients often experience depression, anxiety, stigma as well as suicidal behavior. Even though psoriasis is one of the most studied dermatological conditions, the pathogenesis of the disease is still not completely elucidated. The complex interactions between keratinocytes, dendritic cells, T-lymphocytes, neutrophils and mast cells are responsible for the histopathological changes seen in psoriasis. The pathogenic model leading to the formation of psoriatic plaques has however evolved a lot over the years. There is now enough evidence to support the role of interleukin (IL) -23, IL-17, IL-22, T helper (Th) -17 cells, Th-22 cells, T regulatory cells, transforming growth factor (TGF)-β1 and IL-10 in the pathogenesis of the disease. Moreover, several inflammatory and anti-inflammatory molecules are currently being investigated, some of them showing promising results. The aim of this paper is to look over the most recent advances in the immunological pathways involved in the pathogenesis of psoriasis vulgaris.

Background Mortality is often used as an indicator of public health efforts. Even if mortality in psychiatric hospitals decreased since the introduction of modern treatment, the death toll is still high. The authors have analyzed the forensic autopsy data and the medical documentation regarding 115 death cases from psychiatric hospitals in south-eastern Romania during the period of 2000–2020. Results The average annual mortality rate was 5.13‰, the necropsy data corroborated with those from the medical documentary material indicates acute myocardial infarction as the dominant cause, with 65 (56.5%) cases, followed by upper respiratory tract occlusion with 23 cases (20%) and pulmonary thromboembolism in 4 cases (12.2%). Furthermore, in 6 cases (5.2%) the cause of death was traumatic: 4 cases of cranio-cerebral trauma and 2 cases of hanging. Conclusions In the mortality structure of psychiatric patients, cardiac death predominated, being influenced by the cardiotoxic effect of medication administered for the specific pathology; hence, an early involvement of cardiologists in the follow-up of patients and the finding of treatment schemes with a reduced cardiotoxic effect are required.

Background In this study, we compared programmed death-ligand 1 (PD-L1) expression in primary tissue samples and its soluble form (sPD-L1) concentration in matched preoperative plasma samples from gastric cancer patients to understand the relationship between tissue and plasma PD-L1 expression and to determine its diagnostic and prognostic value. Methods PD-L1 expression in tissue was assessed by immunohistochemistry and enzyme-linked immunosorbent assay (ELISA), and sPD-L1 concentration in plasma was quantified by ELISA. The levels of the CD274 gene, which encodes for PD-L1 protein, were examined as part of bulk tissue RNA-sequencing analyses. Additionally, we evaluated the association between sPD-L1 levels and various laboratory parameters, disease characteristics, and patient outcomes. Results GC patients had significantly higher levels of sPD-L1 in their plasma (71.69 pg/mL) compared to healthy controls (35.34 pg/mL) (p < 0.0001). Moreover, sPD-L1 levels were significantly correlated with tissue PD-L1 protein, CD274 mRNA expression, larger tumor size, advanced tumor stage, and lymph node metastasis. Elevated sPD-L1 levels (> 103.5 ng/mL) were associated with poor overall survival (HR = 2.16, 95%CI 1.15–4.08, p = 0.017). Furthermore, intratumoral neutrophil and dendritic cell levels were directly correlated with plasma sPD-L1 concentration in the GC patients. Conclusions sPD-L1 was readily measurable in GC patients, and its level was associated with GC tissue PD-L1 expression, greater inflammatory cell infiltration, disease progression, and survival. Thus, sPD-L1 may be a useful minimally invasive diagnostic and prognostic biomarker in GC patients.

Artificial Intelligence (AI) has emerged as a transformative technology with immense potential in the field of medicine. By leveraging machine learning and deep learning, AI can assist in diagnosis, treatment selection, and patient monitoring, enabling more accurate and efficient healthcare delivery. The widespread implementation of AI in healthcare has the role to revolutionize patients’ outcomes and transform the way healthcare is practiced, leading to improved accessibility, affordability, and quality of care. This article explores the diverse applications and reviews the current state of AI adoption in healthcare. It concludes by emphasizing the need for collaboration between physicians and technology experts to harness the full potential of AI.

Background: In recent decades, machine-learning (ML) technologies have advanced the management of high-dimensional and complex cancer data by developing reliable and user-friendly automated diagnostic tools for clinical applications. Immunohistochemistry (IHC) is an essential staining method that enables the identification of cellular origins by analyzing the expression of specific antigens within tissue samples. The aim of this study was to identify a model that could predict histopathological diagnoses based on specific immunohistochemical markers. Methods: The XGBoost learning model was applied, where the input variable (target variable) was the histopathological diagnosis and the predictors (independent variables influencing the target variable) were the immunohistochemical markers. Results: Our study demonstrated a precision rate of 85.97% within the dataset, indicating a high level of performance and suggesting that the model is generally reliable in producing accurate predictions. Conclusions: This study demonstrated the feasibility and clinical efficacy of utilizing the probabilistic decision tree algorithm to differentiate tumor diagnoses according to immunohistochemistry profiles.

Paraovarian cysts (POCs) develop within the broad ligament of the uterus. POCs are considered to be giant when the threshold of 150 mm is exceeded. Clinical signs and symptoms occur as a consequence of the pressure effect on adjacent organs or due to complications. Abdominal ultrasonography, computed tomography or magnetic resonance imaging are useful imaging tools, but most often the exact origin of such voluminous cysts is revealed only by surgical exploration. The review aims to appraise and update the diagnostic, the histological aspects and the treatment of the giant POCs in rare cases. We carried out a systematic search in Medline-PubMed, Google Scholar and ResearchGate electronic databases. Twenty-seven papers fulfilling the selection criteria were included in the review. The data extracted included information about first author, year of publication, country, patient age, size and side of the POCs, symptoms, tumoral markers, imaging methods, preoperative diagnosis, surgical management and histopathological findings. Although not very numerous, all the studies highlighted the low incidence of giant POCs, the impossibility of establishing the origin of the cystic mass by clinical and imaging methods even with advanced technical tools and the low risk of torsion (11.1%). Despite the recognized benign nature of POCs, we found an unexpected high percent (25.9%) of borderline giant POCs. Surgical excision is the only treatment option. Ovarian-sparing surgery was performed in 85.1% of the cases, and minimally invasive techniques were applied in only 42.9% of the patients, which demonstrates the need of a high-level laparoscopic expertise. Knowledge of this pathology, its recognition as a possible etiology of an abdominopelvic cyst, and a higher awareness of the possibility of a borderline histology in giant POCs are required for the proper management of these particular cases.

SARS‐CoV‐2 vaccines are highly efficient against severe forms of the disease, hospitalization and death. Nevertheless, insufficient protection against several circulating viral variants might suggest waning immunity and the need for an additional vaccine dose. We conducted a longitudinal study on the kinetics and persistence of immune responses in healthcare workers vaccinated with two doses of BNT162b2 mRNA vaccine with or without prior SARS‐CoV‐2 infection. No new infections were diagnosed during follow‐up. At 6 months, post‐vaccination or post‐infection, despite a downward trend in the level of anti‐S IgG antibodies, the neutralizing activity does not decrease significantly, remaining higher than 75% (85.14% for subjects with natural infection, 88.82% for vaccinated after prior infection and 78.37% for vaccinated only). In a live‐virus neutralization assay, the highest neutralization titres were present at baseline and at 6 months follow‐up in persons vaccinated after prior infection. Anti‐S IgA levels showed a significant descending trend in vaccinated subjects (p < 0.05) after 14 weeks. Cellular immune responses are present even in vaccinated participants with declining antibody levels (index ratio 1.1–3) or low neutralizing activity (30%–40%) at 6 months, although with lower T‐cell stimulation index (p = 0.046) and IFN‐γ secretion (p = 0.0007) compared to those with preserved humoral responses.