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BackgroundAfter its emergence in China, the coronavirus SARS-CoV-2 has swept the world, leading to global health crises with millions of deaths. COVID-19 clinical manifestations differ in severity, ranging from mild symptoms to severe disease. Although perturbation of metabolism has been reported as a part of the host response to COVID-19 infection, scarce data exist that describe stage-specific changes in host metabolites during the infection and how this could stratify patients based on severity.MethodsGiven this knowledge gap, we performed targeted metabolomics profiling and then used machine learning models and biostatistics to characterize the alteration patterns of 50 metabolites and 17 blood parameters measured in a cohort of 295 human subjects. They were categorized into healthy controls, non-severe, severe and critical groups with their outcomes. Subject's demographic and clinical data were also used in the analyses to provide more robust predictive models.ResultsThe non-severe and severe COVID-19 patients experienced the strongest changes in metabolite repertoire, whereas less intense changes occur during the critical phase. Panels of 15, 14, 2 and 2 key metabolites were identified as predictors for non-severe, severe, critical and dead patients, respectively. Specifically, arginine and malonyl methylmalonyl succinylcarnitine were significant biomarkers for the onset of COVID-19 infection and tauroursodeoxycholic acid were potential biomarkers for disease progression. Measuring blood parameters enhanced the predictive power of metabolic signatures during critical illness.ConclusionsMetabolomic signatures are distinctive for each stage of COVID-19 infection. This has great translation potential as it opens new therapeutic and diagnostic prospective based on key metabolites.

Background: After its emergence in China, the coronavirus SARS-CoV-2 has swept the world, leading to global health crises with millions of deaths. COVID-19 clinical manifestations differ in severity, ranging from mild symptoms to severe disease. Although perturbation of metabolism has been reported as a part of the host response to COVID-19 infection, scarce data exist that describe stage-specific changes in host metabolites during the infection and how this could stratify patients based on severity. Methods: Given this knowledge gap, we performed targeted metabolomics profiling and then used machine learning models and biostatistics to characterize the alteration patterns of 50 metabolites and 17 blood parameters measured in a cohort of 295 human subjects. They were categorized into healthy controls, non-severe, severe and critical groups with their outcomes. Subject's demographic and clinical data were also used in the analyses to provide more robust predictive models. Results: The non-severe and severe COVID-19 patients experienced the strongest changes in metabolite repertoire, whereas less intense changes occur during the critical phase. Panels of 15, 14, 2 and 2 key metabolites were identified as predictors for non-severe, severe, critical and dead patients, respectively. Specifically, arginine and malonyl methylmalonyl succinylcarnitine were significant biomarkers for the onset of COVID-19 infection and tauroursodeoxycholic acid were potential biomarkers for disease progression. Measuring blood parameters enhanced the predictive power of metabolic signatures during critical illness. Conclusions: Metabolomic signatures are distinctive for each stage of COVID-19 infection. This has great translation potential as it opens new therapeutic and diagnostic prospective based on key metabolites. [ABSTRACT FROM AUTHOR]

Fractional calculus serves as a versatile and potent tool for the modeling and control of intricate systems. This discussion debates the system of DFDEs with two regimes; theoretically and numerically. For theoretical analysis, we have established the EUE by leveraging the definition of Hilfer (α,β)-framework. Our investigation involved the examination of the possessions of the FRD, FCD, and FHD, utilizing their forcefulness and qualifications to convert the concerning delay system into an equivalent one of fractional DVIEs. By employing the CMT, we have successfully demonstrated the prescribed requirements. For numerical analysis, the Galerkin algorithm was implemented by leveraging OSLPs as a base function. This algorithm allows us to estimate the solution to the concerning system by transforming it into a series of algebraic equations. By employing the software MATHEMATICA 11, we have effortlessly demonstrated the requirements estimation of the nodal values. One of the key advantages of the deployed algorithm is its ability to achieve accurate results with fewer iterations compared to alternative methods. To validate the effectiveness and precision of our analysis, we conducted a comprehensive evaluation through various linear and nonlinear numerical applications. The results of these tests, accompanied by figures and tables, further support the superiority of our algorithm. Finally, an analysis of the numerical algorithm employed was provided along with insightful suggestions for potential future research directions.

This study presents a comprehensive analysis of rock properties for a selected group of six carbonate reservoir rock samples revealing complex structures at various length scales. Experimental laboratory methods as well as image analysis techniques were conducted in this study to characterize the macro- and micro-pores in mud- and grain-dominated limestones samples from the Upper Jurassic Arab Formation (Arab D member). Mercury Injection Capillary Pressure (MICP), porosimeter, and permeameter lab measurements were employed to assess the pore network heterogeneity and complexity. In addition, a multiscale rock imaging approach was implemented to detect grain and pore phases at several length scales using Thin Sections (TS), Scanning Electron Microscopy (SEM), Focused Ion Beam Scanning Electron Microscopy (FIB-SEM), as well as 3D X-ray Computed Tomography (CT), and micro-computed tomography images (MCT). Furthermore, the multifractal analysis method was applied on the MICP and FIB-SEM to characterize quantitatively the heterogeneity of the pores in the studied samples. Heterogeneous samples 3R, 4M, 5W, and 6M display the highest non-uniformity degree Δα values, falling within the range of [1.21, 1.39] based on FIB-SEM images. Samples 1G, 2R, 3R, and 5W exhibit more heterogeneous pore structure, with Δα values ranging from 0.73 to 1.49 based on the MICP experiments. The results and findings confirm the effectiveness of multifractal parameters Δα and the asymmetry degree in the vertical axis Δf(α) in quantifying and characterizing rock heterogeneity.

ObjectivesWe sought to 1) identify long COVID phenotypes based on patient reported outcome measures (PROMs) and 2) determine whether the phenotypes were associated with quality of life (QoL) and/or lung function.MethodsThis was a longitudinal cohort study of hospitalized and non-hospitalized patients from March 2020 to January 2022 that was conducted across 4 Post-COVID Recovery Clinics in British Columbia, Canada. Latent class analysis was used to identify long COVID phenotypes using baseline PROMs (fatigue, dyspnea, cough, anxiety, depression, and post-traumatic stress disorder). We then explored the association between the phenotypes and QoL (using the EuroQoL 5 dimensions visual analogue scale [EQ5D VAS]) and lung function (using the diffusing capacity of the lung for carbon monoxide [DLCO]).ResultsThere were 1,344 patients enrolled in the study (mean age 51 ±15 years; 780 [58%] were females; 769 (57%) were of a non-White race). Three distinct long COVID phenotypes were identified: Class 1) fatigue and dyspnea, Class 2) anxiety and depression, and Class 3) fatigue, dyspnea, anxiety, and depression. Class 3 had a significantly lower EQ5D VAS at 3 (50±19) and 6 months (54 ± 22) compared to Classes 1 and 2 (pConclusionsThere were 3 distinct long COVID phenotypes with different outcomes in QoL between 3 and 6 months after symptom onset. These phenotypes suggest that long COVID is a heterogeneous condition with distinct subpopulations who may have different outcomes and warrant tailored therapeutic approaches.

BackgroundAlthough the importance of concurrent treatment for multidrug-resistant tuberculosis (MDR-TB) and HIV co-infection has been increasingly recognized, there have been few studies reporting outcomes of MDR-TB and HIV co-treatment. We report final outcomes of comprehensive, integrated MDR-TB and HIV treatment in Lesotho and examine factors associated with death or treatment failure.MethodsWe reviewed clinical charts of all adult patients who initiated MDR-TB treatment in Lesotho between January 2008 and September 2009. We calculated hazard ratios (HR) and used multivariable Cox proportional hazards regression to identify predictors of poor outcomes.ResultsOf 134 confirmed MDR-TB patients, 83 (62%) were cured or completed treatment, 46 (34%) died, 3 (2%) transferred, 1 (1%) defaulted, and 1 (1%) failed treatment. Treatment outcomes did not differ significantly by HIV status. Among the 94 (70%) patients with HIV co-infection, 53% were already on antiretroviral therapy (ART) before MDR-TB treatment initiation, and 43% started ART a median of 16 days after the start of the MDR-TB regimen. Among HIV co-infected patients who died, those who had not started ART before MDR-TB treatment had a shorter median time to death (80 days vs. 138 days, p=0.065). In multivariable analysis, predictors of increased hazard of failure or death were low and severely low body mass index (HR 2.75, 95% confidence interval [CI] 1.27-5.93; HR 5.50, 95% CI 2.38-12.69), and a history of working in South Africa (HR 2.37, 95% CI 1.24-4.52).ConclusionsFavorable outcomes can be achieved in co-infected patients using a community-based treatment model when both MDR-TB and HIV disease are treated concurrently and treatment is initiated promptly.

BackgroundFew studies have examined outcomes for children treated for multidrug-resistant tuberculosis (MDR-TB), including those receiving concomitant treatment for MDR-TB and HIV co-infection. In Lesotho, where the adult HIV seroprevalence is estimated to be 24%, we sought to measure outcomes and adverse events in a cohort of children treated for MDR-TB using a community-based treatment delivery model.MethodsWe reviewed retrospectively the clinical charts of children ≤15 years of age treated for culture-confirmed or suspected MDR-TB between July 2007 and January 2011.ResultsNineteen children, ages two to 15, received treatment. At baseline, 74% of patients were co-infected with HIV, 63% were malnourished, 84% had severe radiographic findings, and 21% had extrapulmonary disease. Five (26%) children had culture-confirmed MDR-TB, ten (53%) did not have culture results available, and four (21%) subsequently had results indicating drug-susceptible TB. All children with HIV co-infection who were not already on antiretroviral therapy (ART) were initiated on ART a median of two weeks after the start of the MDR-TB regimen. Among the 17 patients with final outcomes, 15 (88%) patients were cured or completed treatment, two (12%) patients died, and none defaulted or were lost to follow-up. The majority of patients (95%) experienced adverse events; only two required permanent discontinuation of the offending agent, and only one required suspension of MDR-TB treatment for more than one week.ConclusionsPediatric MDR-TB and MDR-TB/HIV co-infection can be successfully treated using a combination of social support, close monitoring by community health workers and clinicians, and inpatient care when needed. In this cohort, adverse events were well tolerated and treatment outcomes were comparable to those reported in children with drug-susceptible TB and no HIV infection.

BACKGROUND: Although it is now widely recognized that reductions in maternal mortality and improvements in women's health cannot be achieved through simple, vertical strategies, few programs have provided successful models for how to integrate services into a comprehensive program for maternal health. We report our experience in rural Lesotho, where Partners In Health (PIH) in partnership with the Ministry of Health and Social Welfare implemented a program that provides comprehensive care of pregnant women from the community to the clinic level. METHODS: Between May and July 2009, PIH trained 100 women, many of whom were former traditional birth attendants, to serve as clinic-affiliated maternal health workers. They received performance-based incentives for accompanying pregnant women during antenatal care (ANC) visits and facility-based delivery. A nurse-midwife provided ANC and delivery care and supervised the maternal health workers. To overcome geographic barriers to delivering at the clinic, women who lived far from the clinic stayed at a maternal lying-in house prior to their expected delivery dates. We analyzed data routinely collected from delivery and ANC registers to compare service utilization before and after implementation of the program. RESULTS: After the establishment of the program, the average number first ANC visits increased from 20 to 31 per month. The clinic recorded 178 deliveries in the first year of the program and 216 in the second year, compared to 46 in the year preceding the program. During the first two years of the program, 49 women with complications were successfully transported to the district hospital, and no maternal deaths occurred among the women served by the program. CONCLUSIONS: Our results demonstrate that it is possible to achieve dramatic improvements in the utilization of maternal health services and facility-based delivery by strengthening human resource capacity, implementing active follow-up in the community, and de-incentivizing home births.

BACKGROUND: Little is known about treatment of multidrug-resistant tuberculosis (MDR-TB) in high HIV-prevalence settings such as sub-Saharan Africa. METHODOLOGY/PRINCIPAL FINDINGS: We did a retrospective analysis of early outcomes of the first cohort of patients registered in the Lesotho national MDR-TB program between July 21, 2007 and April 21, 2008. Seventy-six patients were included for analysis. Patient follow-up ended when an outcome was recorded, or on October 21, 2008 for those still on treatment. Fifty-six patients (74%) were infected with HIV; the median CD4 cell count was 184 cells/microl (range 5-824 cells/microl). By the end of the follow-up period, study patients had been followed for a median of 252 days (range 12-451 days). Twenty-two patients (29%) had died, and 52 patients (68%) were alive and in treatment. In patients who did not die, culture conversion was documented in 52/54 patients (96%). One patient had defaulted, and one patient had transferred out. Death occurred after a median of 66 days in treatment (range 12-374 days). CONCLUSIONS/SIGNIFICANCE: In a region where clinicians and program managers are increasingly confronted by drug-resistant tuberculosis, this report provides sobering evidence of the difficulty of MDR-TB treatment in high HIV-prevalence settings. In Lesotho, an innovative community-based treatment model that involved social and nutritional support, twice-daily directly observed treatment and early empiric use of second-line TB drugs was successful in reducing mortality of MDR-TB patients. Further research is urgently needed to improve MDR-TB treatment outcomes in high HIV-prevalence settings.