Mitochondrial dysfunctions are key features of Alzheimer\'s disease (AD). The occurrence of these disturbances in the peripheral cells of AD patients and their potential correlation with disease progression are underinvestigated. We studied mitochondrial structure, function and mitophagy in fibroblasts from healthy volunteers and AD patients at the prodromal (AD-MCI) or demented (AD-D) stages. We carried out correlation studies with clinical cognitive scores, namely, (i) Mini-Mental State Examination (MMSE) and (ii) Dementia Rating-Scale Sum of Boxes (CDR-SOB), and with (iii) amyloid beta (Aβ) plaque burden (PiB-PET imaging) and (iv) the accumulation of peripheral amyloid precursor protein C-terminal fragments (APP-CTFs). We revealed alterations in mitochondrial structure as well as specific mitochondrial dysfunction signatures in AD-MCI and AD-D fibroblasts and revealed that defective mitophagy and autophagy are linked to impaired lysosomal activity in AD-D fibroblasts. We reported significant correlations of a subset of these dysfunctions with cognitive decline, AD-related clinical hallmarks and peripheral APP-CTFs accumulation. This study emphasizes the potential use of peripheral cells for investigating AD pathophysiology.

Introduction. During the development of the SARS-CoV-2 pandemic in Antioquia, we experienced epidemiological peaks related to the α, ɣ, β, ƛ, and δ variants. δ had the highest incidence and prevalence. This lineage is of concern due to its clinical manifestations and epidemiological characteristics. A total of 253 δ sublineages have been reported in the PANGOLIN database. The sublineage identification through genomic analysis has made it possible to trace their evolution and propagation. Objective. To characterize the genetic diversity of the different SARS-CoV-2 δ sublineages in Antioquia and to describe its prevalence. Materials and methods. We collected sociodemographic information from 2,675 samples, and obtained 1,115 genomes from the GISAID database between July 12th, 2021, and January 18th, 2022. From the analyzed genomes, 515 were selected because of their high coverage values (>90%) to perform phylogenetic analysis and to infer allele frequencies of mutations of interest. Results. We characterized 24 sublineages. The most prevalent was AY.25. Mutations of interest as L452R, P681R, and P681H were identified in this sublineage, comprising a frequency close to 0.99. Conclusions. This study identified that the AY.25 sublineage has a transmission advantage compared to the other δ sublineages. This attribute may be related to the presence of the L452R and P681R mutations associated in other studies with higher evasion of the immune system and less efficacy of drugs against SARS-CoV-2.
Introducción. Durante el desarrollo de la pandemia por SARS-CoV-2 en Antioquia se presentaron picos epidemiológicos relacionados con las variantes α, ɣ, β, ƛ y δ, donde δ tuvo la mayor incidencia y prevalencia. Este linaje se considera una variante de preocupación dadas las manifestaciones clínicas que desencadena y sus características epidemiológicas. Se han informado 253 sublinajes δ en la base de datos PANGOLIN. La identificación de estos sublinajes mediante análisis genómico ha permitido rastrear su evolución y propagación. Objetivo. Caracterizar la diversidad genética de los diferentes sublinajes δ de SARSCoV-2 en Antioquia y determinar su prevalencia. Materiales y métodos. Se recopiló información sociodemográfica de 2.675 muestras y de 1.115 genomas del repositorio GISAID entre el 12 de julio de 2021 y el 18 de enero de 2022. Se seleccionaron 501 por su alto porcentaje de cobertura (>90 %) para realizar análisis filogenéticos e inferencia de frecuencias alélicas de mutaciones de interés. Resultados. Se caracterizaron 24 sublinajes donde el más prevalente fue AY.25. En este sublinaje se identificaron mutaciones de interés como L452R, P681R y P681H, que comprendían una frecuencia cercana a 0,99. Conclusiones. Este estudio permitió identificar que el sublinaje AY.25 tiene una ventaja de transmisión en comparación con los otros sublinajes δ. Esto puede estar relacionado con la presencia de las mutaciones L452R y P681R que en otros estudios se han visto asociadas con una mayor transmisibilidad, evasión del sistema inmunitario y menor eficacia de los medicamentos contra SARS-CoV-2.

(1) Background: Heparin-Binding Epidermal Growth Factor-like Growth Factor (HB-EGF) is involved in wound healing, cardiac hypertrophy, and heart development processes. Recently, circulant HB-EGF was reported upregulated in severely hospitalized COVID-19 patients. However, the clinical correlations of HB-EGF plasma levels with COVID-19 patients\' characteristics have not been defined yet. In this study, we assessed the plasma HB-EGF correlations with the clinical and paraclinical patients\' data, evaluated its predictive clinical value, and built a risk prediction model for severe COVID-19 cases based on the resulting significant prognostic markers. (2) Methods: Our retrospective study enrolled 75 COVID-19 patients and 17 control cases from May 2020 to September 2020. We quantified plasma HB-EGF levels using the sandwich ELISA technique. Correlations between HB-EGF plasma levels with clinical and paraclinical patients\' data were calculated using two-tailed Spearman and Point-Biserial tests. Significantly upregulated parameters for severe COVID-19 cases were identified and selected to build a multivariate logistic regression prediction model. The clinical significance of the prediction model was assessed by risk prediction nomogram and decision curve analyses. (3) Results: HB-EGF plasma levels were significantly higher in the severe COVID-19 subgroup compared to the controls (p = 0.004) and moderate cases (p = 0.037). In the severe COVID-19 group, HB-EGF correlated with age (p = 0.028), pulse (p = 0.016), dyspnea (p = 0.014) and prothrombin time (PT) (p = 0.04). The multivariate risk prediction model built on seven identified risk parameters (age p = 0.043, HB-EGF p = 0.0374, Fibrinogen p = 0.009, PT p = 0.008, Creatinine p = 0.026, D-Dimers p = 0.024 and delta miR-195 p < 0.0001) identifies severe COVID-19 with AUC = 0.9556 (p < 0.0001). The decision curve analysis revealed that the nomogram model is clinically relevant throughout a wide threshold probability range. (4) Conclusions: Upregulated HB-EGF plasma levels might serve as a prognostic factor for severe COVID-19 and help build a reliable risk prediction nomogram that improves the identification of high-risk patients at an early stage of COVID-19.

To investigate the urinary microbiota composition in urolithiasis patients compared to healthy controls and to identify potential microbial markers and their association with clinical parameters.
A total of 66 samples, comprising 45 from urolithiasis patients and 21 from healthy controls, were analyzed. 16S rRNA gene sequencing was employed to determine the microbiota composition. Various statistical and bioinformatics tools, including ANOVA, PCoA, and LEfSe, were utilized to analyze the sequencing data and identify significant differences in microbial abundance.
No significant demographic differences were observed between the two groups. Post-quality control, clean tags ranged from 60,979 to 68,736. Significant differences in α-diversity were observed between the two groups. β-diversity analysis revealed distinct clustering of the urinary microbiota in urolithiasis patients and controls. Notably, Ruminococcaceae was predominant in urolithiasis samples, while Proteobacteria was more prevalent in healthy samples. Lactobacillus was significantly overrepresented in samples from healthy females.
The urinary microbiota composition in urolithiasis patients is distinct from that of healthy controls. Specific microbial taxa, such as Ruminococcaceae and Proteobacteria, could serve as potential biomarkers for urolithiasis. The findings pave the way for further exploration of the role of microbiota in urolithiasis and the development of microbiome-based therapeutic strategies.

Purines, pyrimidines, and amino acid level have gained attention recently as potential determinants of mental disorders. However, eating disorders patients (ED) have not been yet appropriately studied, especially subjects with coexisting mood disorders. This paper examines the serum level of nucleotide catabolites and plasma amino acids in eating disorders with hyperphagia, with and without Major Depressive Disorder (MDD). Samples were taken from adult persons suffering from eating disorders (two forms: simple obesity and binge eating disorder) with MDD (n = 20) and without (n = 17). Serum nucleotides and plasma amino acids concentrations were analyzed with high-performance liquid chromatography-mass spectrometry. The nucleotides metabolite in MDD patients had a significantly (p < 0.05) lower uridine. Among MDD patients with ED significantly (p < 0.05) higher levels of asparagine, glutamine, proline, and arginine were found as compared to the control group. This study demonstrated differences in nucleotide metabolite and amino acid pattern in depression patients with eating disorders. This may be relevant to the mechanisms and may help identify biomarkers.

Computed tomography (CT) of the chest, although not a screening test or diagnosis of infection with the new coronavirus, has a fundamental role in assessing the extent of lung involvement and complications such as pleural effusion. Considering the higher morbidity and mortality of elderly patients due to this infection, the objective of this study was to evaluate the imaging aspects and clinical correlations of an extreme age (≥80 years) with a confirmed diagnosis for COVID-19.
This was a retrospective and single-center cohort study. CT scans were categorized qualitatively and quantitatively. In the first case, 3 descriptors were used to describe CT findings: \"compatible\" (findings of greater specificity for COVID-19: opacities with attenuation in ground glass with peripheral and bilateral distribution, with rounded morphology, with or without consolidations, crazy-pavement aspect, inverted halo sign, or organizing pneumonia findings), \"doubtful\" (findings not specific or unusual for COVID-19: opacities with attenuation in ground glass with nonrounded morphology, central, diffuse, or unilateral distribution, with or without consolidation, lobar or segmental consolidation without ground-glass opacity, small centrilobular nodules with the appearance of \"tree-in-bud,\" excavations, pleural effusion, and thickening of interlobular septa), and \"negative\" (absence of pneumonia signs). For the quantitative assessment, which referred to the extent of pulmonary involvement, a tomographic severity classification was used: grade 1 (lung involvement ≤25%), grade 2 (pulmonary involvement between 26 and 50%), and grade 3 (pulmonary involvement >50%).
A total of 138 patients were evaluated, with an average age of 86.2 years (84 women and 34 men). The mean time interval between onset of symptoms and tomography was 5.63 days. The most prevalent comorbidity was systemic arterial hypertension (81.2%). Compatible, doubtful, and negative tests were 117 (84.7%), 20 (14.4%), and 1 (0.7%), respectively. As for compatible exams, the most common findings were opacities in peripheral ground glass and rounded morphology, followed by crazy paving. The prevalence of pleural effusion was 28.2% and consolidation was 63.7%, and none of these findings were influenced by the duration of symptoms (p = 0.08 and p = 0.2, respectively). The exams classified as grade 1, grade 2, and grade 3 were 57 (41.6%), 46 (33.6%), and 34 (24.8%), respectively. There were statistically significant associations between the classification of tomographic severity and outcomes such as invasive ventilation (p = 0.004), admission to the intensive care unit (p < 0.001), and death (p < 0.001).
Our results show that patients ≥80 years old present tomographic manifestations similar to those described for the general population (ground-glass opacities and \"crazy paving\") and that the extent of lung involvement is associated with the need for intensive care, invasive ventilation, and death. Although the literature describes an association between the stage of the disease and the appearance of consolidations and pleural effusion, this correlation was not observed in our study, which may suggest that this age-group is more predisposed to the appearance of such findings, typically described in the more advanced stages of infection.

COVID-19 is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and declared by the World Health Organization a global public health emergency. Among the severe outbreaks across South America, Uruguay has become known for curtailing SARS-CoV-2 exceptionally well. To understand the SARS-CoV-2 introductions, local transmissions, and associations with genomic and clinical parameters in Uruguay, we sequenced the viral genomes of 44 outpatients and inpatients in a private healthcare system in its capital, Montevideo, from March to May 2020. We performed a phylogeographic analysis using sequences from our cohort and other studies that indicate a minimum of 23 independent introductions into Uruguay, resulting in five major transmission clusters. Our data suggest that most introductions resulting in chains of transmission originate from other South American countries, with the earliest seeding of the virus in late February 2020, weeks before the borders were closed to all non-citizens and a partial lockdown implemented. Genetic analyses suggest a dominance of S and G clades (G, GH, GR) that make up >90% of the viral strains in our study. In our cohort, lethal outcome of SARS-CoV-2 infection significantly correlated with arterial hypertension, kidney failure, and ICU admission (FDR < 0.01), but not with any mutation in a structural or non-structural protein, such as the spike D614G mutation. Our study contributes genetic, phylodynamic, and clinical correlation data about the exceptionally well-curbed SARS-CoV-2 outbreak in Uruguay, which furthers the understanding of disease patterns and regional aspects of the pandemic in Latin America.

Recently, anti-programmed cell death 1 (PD-1) and anti-programmed cell death ligand 1 (PD-L1) immunotherapies have yielded promising outcomes for patients with advanced non-small cell lung cancer (NSCLC) and led to great interest in applying these agents to treat resectable early-stage NSCLC. The objective of our study was to evaluate PD-L1 protein expression in resectable early-stage NSCLC specimens from a large Northern European cohort, examine the relationship to clinical characteristics, and demonstrate the prognostic role in resected NSCLC.
A large cohort of 875 NSCLC tumors consisted of 337 patients from Sweden and 538 patients from Norway was studied. All the patients had undergone pulmonary resection, and most patients had had early-stage NSCLC. PD-L1 protein expression was assessed by immunohistochemistry using the Dako PD-L1 22C3 pharmDx kit. The tumor proportion score for PD-L1 protein expression was compared with comprehensive demographic and clinicopathologic data.
The overall prevalence of PD-L1 protein expression in the resectable NSCLC cohort was 9.5% at a tumor proportion score cutoff of ≥ 50%. Stage I NSCLC had lower PD-L1 expression compared with that of the other stages (P = .0012). PD-L1 expression correlated with wild-type EGFR gene expression (P = .0156) and mutated KRAS gene expression (P = .0004). No significant association was found between PD-L1 expression and mortality after multivariable adjustment for clinical characteristics, although the survival curves showed PD-L1 expression significantly correlated with a poor prognosis in the total NSCLC cohort and in the adenocarcinoma subgroup.
PD-L1 expression in the present large cohort of resectable NSCLC was relatively low compared with data from clinical trials of advanced NSCLC. PD-L1 expression correlated positively with tumor stage, wild-type EGFR, and KRAS mutation. PD-L1 expression was not found as an independent prognostic factor in the present study. These findings could be important in the future when evaluating the role of anti-PD-1/PD-L1 immunotherapy in the setting of neoadjuvant or adjuvant trials for early-stage resectable NSCLC.

Binge eating disorder (BED) increasingly affects population, but the mechanisms of the disease and its biomarkers are not well characterized. Recently, plasma purines, pyrimidines, amino acid and nicotinamide metabolites profiling attracted attention in studies on pathology and biomarkers of mental disorders but has not been adequately studied in BED. Blood and plasma samples were taken from patients with adult obese with BED (n = 20) and control adult obese without BED (n = 17). Plasma samples were analyzed for nucleotides and amino acid concentrations with high-performance liquid chromatography-mass spectrometry. BED had a significantly (p < 0.05) lower uridine and hypoxanthine to creatinine ratio compared to the control group. Among the amino acids BED patients had significantly (p < 0.05) lower concentrations of glutamic acid, leucine, isoleucine and the whole branched-chain amino acids group, while the concentration of citrulline was increased. Among nicotinamide metabolites, 1-methylnicotinamide levels were significantly (p < 0.05) lower. This study highlights potential use of profiling nucleotide metabolite and amino acid pattern in BED patients that may provide information on mechanisms and potential biomarkers. However, further investigation in larger population is necessary to identify clinical correlates of the observed changes.

Recent large-cohort sequencing studies have investigated the genomic landscape of meningiomas, identifying somatic coding alterations in NF2, SMARCB1, SMARCE1, TRAF7, KLF4, POLR2A, BAP1, and members of the PI3K and Hedgehog signaling pathways. Initial associations between clinical features and genomic subgroups have been described, including location, grade, and histology. However, further investigation using an expanded collection of samples is needed to confirm previous findings, as well as elucidate relationships not evident in smaller discovery cohorts.
Targeted sequencing of established meningioma driver genes was performed on a multiinstitution cohort of 3016 meningiomas for classification into mutually exclusive subgroups. Relevant clinical information was collected for all available cases and correlated with genomic subgroup. Nominal variables were analyzed using Fisher\'s exact tests, while ordinal and continuous variables were assessed using Kruskal-Wallis and 1-way ANOVA tests, respectively. Machine-learning approaches were used to predict genomic subgroup based on noninvasive clinical features.
Genomic subgroups were strongly associated with tumor locations, including correlation of HH tumors with midline location, and non-NF2 tumors in anterior skull base regions. NF2 meningiomas were significantly enriched in male patients, while KLF4 and POLR2A mutations were associated with female sex. Among histologies, the results confirmed previously identified relationships, and observed enrichment of microcystic features among \"mutation unknown\" samples. Additionally, KLF4-mutant meningiomas were associated with larger peritumoral brain edema, while SMARCB1 cases exhibited elevated Ki-67 index. Machine-learning methods revealed that observable, noninvasive patient features were largely predictive of each tumor\'s underlying driver mutation.
Using a rigorous and comprehensive approach, this study expands previously described correlations between genomic drivers and clinical features, enhancing our understanding of meningioma pathogenesis, and laying further groundwork for the use of targeted therapies. Importantly, the authors found that noninvasive patient variables exhibited a moderate predictive value of underlying genomic subgroup, which could improve with additional training data. With continued development, this framework may enable selection of appropriate precision medications without the need for invasive sampling procedures.