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This article is dedicated to the late Michael D. Fetters--a giant in the world of mixed methods research, an exceptional researcher and scholar, a professor of family medicine, a caring and beloved family physician, a lifelong learner, a colleague, a mentor, a steadfast advocate, a son, a sibling, a husband, a father, and, above all, a dear friend to everyone who knew him. Inspired by Professor Fetters's innovation, we offer an expanded definition of autoethnography through the formal introduction of the 10 dimensions of autoethnography, as well as the debut of mixed methods autoethnography and of integrated mixed methods autoethnography. An autoethnographic narrative writing style honors both the research genre and the mixed methods researchers' voices.

Surgery is the mainstay of treatment for meningioma, the most common primary intracranial tumor, but improvements in meningioma risk stratification are needed and indications for postoperative radiotherapy are controversial. Here we develop a targeted gene expression biomarker that predicts meningioma outcomes and radiotherapy responses. Using a discovery cohort of 173 meningiomas, we developed a 34-gene expression risk score and performed clinical and analytical validation of this biomarker on independent meningiomas from 12 institutions across 3 continents (N = 1,856), including 103 meningiomas from a prospective clinical trial. The gene expression biomarker improved discrimination of outcomes compared with all other systems tested (N = 9) in the clinical validation cohort for local recurrence (5-year area under the curve (AUC) 0.81) and overall survival (5-year AUC 0.80). The increase in AUC compared with the standard of care, World Health Organization 2021 grade, was 0.11 for local recurrence (95% confidence interval 0.07 to 0.17, P

Abstract Microphthalmia-associated transcription factor (MITF) is a master regulator of melanocyte function, development and plays a significant role in melanoma pathogenesis. MITF genomic amplification promotes melanoma development, and it can facilitate resistance to multiple therapies. Here, we show that MITF regulates a global antioxidant program that increases survival of melanoma cell lines by protecting the cells from reactive oxygen species (ROS)-induced damage. In addition, this redox program is correlated with MITF expression in human melanoma cell lines and patient-derived melanoma samples. Using a zebrafish melanoma model, we show that MITF decreases ROS-mediated DNA damage in vivo. Some of the MITF target genes involved, such as IDH1 and NNT, are regulated through direct MITF binding to canonical enhancer box (E-BOX) sequences proximal to their promoters. Utilizing functional experiments, we demonstrate the role of MITF and its target genes in reducing cytosolic and mitochondrial ROS. Collectively, our data identify MITF as a significant driver of the cellular antioxidant state.

Abstract Nearly 60 million people worldwide are infected with Hepatitis C Virus (HCV), a bloodborne pathogen which leads to liver cirrhosis and increases the risk of hepatocellular carcinoma. Those with limited access to healthcare resources, such as injection drug users and people in low- and middle-income countries, carry the highest burden. The current diagnostic algorithm for HCV is slow and costly, leading to a significant barrier in diagnosis and treatment for those most at risk from HCV. There remains no available vaccine for HCV, and infection is often asymptomatic until significant cirrhosis has occurred, which makes screening incredibly important to prevent liver damage and transmission. Recent investigation has sought to address these issues through improvements in various aspects of the diagnostic procedure, using methods such as isothermal amplification techniques for viral RNA amplification, the use of viral protein as an analyte, and the incorporation of streamlined, self-contained testing systems to reduce administrative skill requirements. This review provides a comprehensive overview of current commercial standards and novel improvements in HCV diagnostics, as well as a framework for future integration of these improvements to develop a one-step diagnostic that meets the needs of those most affected. Graphical Abstract

Introduction. In response to the COVID-19 pandemic in the Russian Federation, comprehensive response measures were taken. One of these measures was the development of a viral genome aggregation platform (VGARus) to monitor virus variability. The aim of this paper is to describe the role of the VGARus platform in tracking genetic variation in SARS-CoV-2. Materials and methods. VGARus utilizes sequencing data and bioinformatics tools to monitor genetic variations in SARS-CoV-2. The viral genomes were aligned using NextClade, which also translated them into amino acids and identified mutations. The viral variability over time was analyzed by counting the number of amino acid changes compared to the reference sequence. Results. The analysis of data within VGARus enabled the identification of new virus variants, contributing to improved diagnostic tests and vaccine development. The platform allowed for the prediction of epidemiologic trends, facilitating a rapid response to changes in the epidemiologic situation. For example, using VGARus, an increase in COVID-19 incidence was accurately predicted in the summer of 2022 and early 2023, which were associated with the emergence of Omicron subvariants BA.5 and XBB. Data from the platform helps validate the effectiveness of primers and DNA probes to ensure high diagnostic accuracy and reduce the risk of false negatives. Conclusion. VGARus demonstrates the growing role of genomic surveillance in combating COVID-19 and improving preparedness for future infectious disease outbreaks. The platform is a powerful tool for generating evidence-based solutions to combat a pandemic and mitigate its health, economic and societal impacts. It provides the ability to promptly obtain information on the epidemiologic situation in a particular region of the Russian Federation, use genomic data for phylogenetic analysis, compare the mutational spectrum of SARS-CoV-2 sequences with foreign samples. VGARus data allow for both retrospective analysis and predictive hypotheses. For example, we can clearly see the dynamics of the change of different virus variants: sequences belonging to the Alpha, Beta, Delta, Omicron lineages and many less common ones, clearly form the upsurges of morbidity, the interaction of which is reflected in the epidemiological picture. It is also currently being expanded to monitor other pathogens, increasing its public health relevance.

Abstract Postoperative fluid overload (FO) after cardiac surgery is common and affects recovery. Predicting FO could help optimize fluid management. This post-hoc analysis of the HERACLES randomized controlled trial evaluated the predictive value of MR-proADM for FO post-cardiac surgery. MR-proADM levels were measured at four different timepoints in 33 patients undergoing elective cardiac surgery. Patients were divided into FO (> 5% weight gain) and no-FO at ICU discharge. The primary outcome was the predictive power of MR-proADM at ICU admission for FO at discharge. Secondary outcomes included the predictive value of MR-proADM for FO on day 6 post-surgery and changes over time. The association between MR-proADM and FO at ICU discharge or day 6 post-surgery was not significant (crude odds ratio (cOR): 4.3 (95% CI 0.5–40.9, p = 0.201) and cOR 1.1 (95% CI 0.04–28.3, p = 0.954)). MR-proADM levels over time did not differ significantly between patients with and without FO at ICU discharge (p = 0.803). MR-proADM at ICU admission was not associated with fluid overload at ICU discharge in patients undergoing elective cardiac surgery. MR-proADM levels over time were not significantly different between groups, although elevated levels were observed in patients with FO.

The aim of the work is to analyze and summarize the available data on e-cigarettes and their effect on the cardiovascular system. The review presents materials by domestic and foreign authors on the effect of electronic cigarettes (e-cigarettes) on the body. 69 different literature sources were used to write the article — articles published in the international citation databases PubMed (MEDLINE), Scopus, as well as fundamental research and monographs published in the RSCI. The data were selected according to the keywords "cardiovascular diseases", "risk factors", "arterial hypertension", "chronic heart failure", "electronic cigarettes", "vapes". Materials whose authorship has not been established, textbooks, near-scientific Internet resources, as well as publications that do not correspond to the subject of the study were excluded from the analysis. According to the results of the review, data on the negative effects of e-cigarettes on the respiratory, reproductive, cardiovascular system and oral cavity were revealed, as well as the main chemical compounds in the vapor composition that can harm the health of e-cigarette users were analyzed. The idea of e-cigarettes as a safer alternative to traditional smoking has been shown to be controversial in many ways and requires further study. This information may be necessary for practitioners in order to prevent diseases and protect public health.

Abstract The ongoing worldwide effort to reduce animal numbers in research often omits the issue of pre-weaning mortality in mouse breeding. A conservative estimate of 20% mortality would mean approximately 1.1 M mice die annually in the EU before scientific use. We hypothesize that pre-weaning mortality in laboratory mouse breeding is associated with cage social and macro/micro-environment conditions. Here we count pups from 509 C57BL/6J litters daily for accurate detection of mortality, and monitor cage micro-environment for 172 C57BL/6J litters. Probability of pups to die increases with the increase in dam age, number and age of older pups in the cage (of overlapped/cohabitating litters), and in small (11 pups) focal litters. Higher temperatures (>23.6 °C) and nest scores (>3.75) compensate for some of the socially-associated risks for pup death. These findings can be implemented in strategies for reducing pre-weaning mouse mortality, a more welfare-friendly and sustainable approach for science.

Abstract While significant advances have been made in understanding renal pathophysiology, less is known about the role of glycosphingolipid (GSL) metabolism in driving organ dysfunction. Here, we used a small molecule inhibitor of glucosylceramide synthase to modulate GSL levels in three mouse models of distinct renal pathologies: Alport syndrome (Col4a3 KO), polycystic kidney disease (Nek8 jck ), and steroid-resistant nephrotic syndrome (Nphs2 cKO). At the tissue level, we identified a core immune-enriched transcriptional signature that was shared across models and enriched in human polycystic kidney disease. Single nuclei analysis identified robust transcriptional changes across multiple kidney cell types, including epithelial and immune lineages. To further explore the role of GSL modulation in macrophage biology, we performed in vitro studies with homeostatic and inflammatory bone marrow-derived macrophages. Cumulatively, this study provides a comprehensive overview of renal dysfunction and the effect of GSL modulation on kidney-derived cells in the setting of renal dysfunction.

Sulfated polysaccharides have a variety of important biologically active properties, such as anticoagulant, hypolipidemic, antiviral activity, the ability to be a means of targeted drug delivery and to improve the water solubility of certain drugs. Initial and sulfated polysaccharides’ biological activity depends on the method of their preparation, composition and structure. Currently, there is an extensive body of literature data on methods for the sulfation of various natural polysaccharides. However, modern reviews on this topic mainly focus on the biological activity and application of sulfated polymers, rather than on synthesis methods. The latest comprehensive review on methods for the synthesis of sulfated polysaccharides was performed by Caputo in 2019. To further study this area, you need to know the latest trends in this topic. Based on this, we decided to create a new, up-to-date review covering most of the existing methods for the synthesis of sulfated polysaccharides. This work examined methods for the synthesis of biologically active polysaccharide sulfates and their effect on polymer characteristics, as well as the advantages and disadvantages of each method. Traditional methods for sulfating polysaccharides were reviewed such as using a complex of sulfur trioxide with pyridine, and new methods based on the use of toxic free and corrosive free reagents. Some data on the biological activity of the obtained polysaccharides are considered.

Aim. To evaluate the effectiveness and safety of Extimia® (empegfilgrastim, JSC "BIOCAD") in reducing the frequency, duration of neutropenia, the incidence of febrile neutropenia (FN) and infections caused by FN in patients with solid tumors receiving myelosuppressive therapy. Materials and methods. The paper presents the final results of a multicenter prospective observational post-marketing study of the safety and effectiveness of Extimia® (empegfilgrastim) in patients with solid tumors receiving cytotoxic therapy. For the primary prevention of FN, all patients received empegfilgrastim at 7.5 mg subcutaneously once per course of chemotherapy (CT) 24 hours after the end of CT administration. The primary endpoint included an assessment of the relative dose-intensity (RDI) of the CT courses administered. The endpoints of interest included the assessment of the RDI of CT courses by nosology and CT regimen, the frequency of dose-limiting neutropenia, and the incidence of all adverse events (AEs) in patients who received at least one dose of the study medication, including serious AEs. Results. From February 2021 to December 2022, 3218 patients with various malignancies were included in 41 study centers of the Russian Fede- ration. Of these, 3217 (99.97%) patients received at least one dose of the study drug, and 2663 (82.8%) patients were included in the RDI evaluation population according to the study protocol. The mean age in this group was 56.9 (18–84) years. RDI ≥85% was achieved in 2,415 (90.7%) patients. The mean RDI was 96.2%, with a median of 100%. FN risk factors were present in 1216 (45.7%) patients, with age ≥65 years being the most common risk factor at 761/2663 (28.6%). It should be noted that in patients younger than 65 years, the RDI was 91.5%, and in elderly patients (≥65 years) 88.7%. Dose-limiting neutropenia was reported in 19 (0.7%) patients. There were 74 cases of grade 3–4 AEs (according to CTCAE v.5) in 59 (1.8%) patients. The most common were neutropenia, anemia, and diarrhea in 19 (0.7%), 7 (0.2%), and 6 (0.2%) patients, respectively. Serious AEs were reported in 17 patients (0.5%). Conclusion. Primary prophylaxis of FN with long-acting granulocyte colony-stimulating factor empegfilgrastim effectively maintains RDI in various nosological and therapeutic groups of patients with different CT regimens in real-world clinical practice.

Abstract Despite a significant accumulation of research, there has been little systemic implementation of evidence-based practices (EBP) in youth mental health care. The fragmentation of the evidence base complicates implementation efforts. In light of this challenge, we sought to pilot a system that consolidates and coordinates the entire evidence base in a single direct service model (i.e., Managing and Adapting Practice; MAP) in the context of a legal reform of psychotherapy training in Germany. This pilot study aimed to evaluate the feasibility of the implementation of MAP into the curriculum of the reformed German master's program. Eligible participants were students in the master’s program at Philipps-University Marburg during the winter-term 2022/2023. Students first learned about MAP through introductions and role plays (seminar 1), followed by actively planning and conducting interventions using MAP resources for patients in a case seminar under supervision (seminar 2). A repeated-measures survey was conducted to investigate students’ knowledge gains, perception of MAP and changes in their self-rated confidence to use EBP. Results indicated that students perceive MAP to be manageable to learn. Positive progress was achieved with regard to their knowledge and self-reported confidence to use EBP, although interpretation and generalization of the results are limited by small and homogeneous samples, lack of statistical power and missing comparison groups. The feasibility of the implementation and suitability of measures are discussed. Important implications could be drawn with regard to future investigations.

Current treatment of chronic hepatitis B virus (HBV) infection, pegylated interferon-α (pegIFN-α) and nucleos(t)ide analogue (NA), can suppress HBV replication, reverse liver inflammation and fibrosis, and decrease risks of cirrhosis and hepatocellular carcinoma, but hepatitis B surface antigen (HBsAg) loss is rare. Functional HBV cure is defined as undetectable HBsAg and unquantifiable serum HBV DNA for at least 24 weeks after a finite course of therapy. This requires suppression of HBV replication and viral protein production as well as restoration of immune response to HBV. Direct-acting antivirals targeting virus entry, capsid assembly, viral protein production and secretion are in clinical trials. In parallel, immune modulatory therapies to stimulate HBV-specific immune response and to remove immune blockade are being tested. Clinical trials of direct-acting antivirals alone or immune modulatory therapies alone have not been successful in achieving HBV cure. Recent combinations of direct-acting antivirals and immune modulatory therapies have shown promising results particularly with combinations that included pegIFN-α. These results need to be confirmed in larger studies with longer follow-up, and further work is needed to develop simpler regimens with fewer drugs that can be administered orally and safely. While there is a strong desire to develop finite therapies that can achieve HBV cure, safety is paramount and new therapies must provide incremental value compared to standard of care, which is predominantly long-term NA therapy.

Abstract Background SARS-CoV-2-infected patients may develop new conditions in the period after the acute infection. These conditions, the post-acute sequelae of SARS-CoV-2 infection (PASC, or Long COVID), involve a diverse set of organ systems. Limited studies have investigated the predictability of Long COVID development and its associated risk factors. Methods In this retrospective cohort study, we used electronic healthcare records from two large-scale PCORnet clinical research networks, INSIGHT (~1.4 million patients from New York) and OneFlorida+ (~0.7 million patients from Florida), to identify factors associated with having Long COVID, and to develop machine learning-based models for predicting Long COVID development. Both SARS-CoV-2-infected and non-infected adults were analysed during the period of March 2020 to November 2021. Factors associated with Long COVID risk were identified by removing background associations and correcting for multiple tests. Results We observed complex association patterns between baseline factors and a variety of Long COVID conditions, and we highlight that severe acute SARS-CoV-2 infection, being underweight, and having baseline comorbidities (e.g., cancer and cirrhosis) are likely associated with increased risk of developing Long COVID. Several Long COVID conditions, e.g., dementia, malnutrition, chronic obstructive pulmonary disease, heart failure, PASC diagnosis U099, and acute kidney failure are well predicted (C-index > 0.8). Moderately predictable conditions include atelectasis, pulmonary embolism, diabetes, pulmonary fibrosis, and thromboembolic disease (C-index 0.7–0.8). Less predictable conditions include fatigue, anxiety, sleep disorders, and depression (C-index around 0.6). Conclusions This observational study suggests that association patterns between investigated factors and Long COVID are complex, and the predictability of different Long COVID conditions varies. However, machine learning-based predictive models can help in identifying patients who are at risk of developing a variety of Long COVID conditions.