Search

Increased death rates due to lung cancer have necessitated the search for potential novel anticancer compounds such as carbazole derivatives. Carbazoles are aromatic heterocyclic compounds with anticancer, antibacterial and anti-inflammatory activity. The study investigated the ability of the novel carbazole compound (Z)-4-[9-ethyl-9aH-carbazol-3-yl) amino] pent-3-en-2-one (ECAP) to induce cytotoxicity of lung cancer cells and its mechanism of action. ECAP was synthesized as a yellow powder with melting point of 240-247 °C. The 3-(4,5-dimethythiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT), lipid peroxidation and comet assays were used to assess the cytotoxic effect of the compound on A549 lung cancer cells. Protein expression was determined using western blots, apoptosis was measured by luminometry (caspase-3/7, -8 and -9) assay and flow cytometry was used to measure phosphatidylserine (PS) externalisation. ECAP induced a p53 mediated apoptosis of lung cancer cells due to a significant reduction in the expression of antioxidant defence proteins (Nrf2 and SOD), Hsp70 (p < 0.02) and Bcl-2 (p < 0.0006), thereby up-regulating reactive oxygen species (ROS) production. This resulted in DNA damage (p < 0.0001), up-regulation of Bax expression and caspase activity and induction of apoptosis in lung cancer cells. The results show the anticancer potential of ECAP on lung cancer.

ImportanceSARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis.MethodsRECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms.DiscussionRECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options.RegistrationNCT05172024.

Background and aimsManagement of patients with NASH who are at elevated risk of progressing to complications of cirrhosis (at-risk NASH) would be enhanced by an accurate, noninvasive diagnostic test. The new FAST™ score, a combination of FibroScan® parameters liver stiffness measurement (LSM) and controlled attenuation parameter (CAP) and aspartate aminotransferase (AST), has shown good diagnostic accuracy for at-risk NASH (area-under-the-Receiver-Operating-Characteristic [AUROC] = 0.80) in European cohorts. We aimed to validate the FAST™ score in a North American cohort and show how its diagnostic accuracy might vary by patient mix. We also compared the diagnostic performance of FAST™ to other non-invasive algorithms for the diagnosis of at-risk NASH.MethodsWe studied adults with biopsy-proven non-alcoholic fatty liver disease (NAFLD) from the multicenter NASH Clinical Research Network (CRN) Adult Database 2 (DB2) cohort study. At-risk-NASH was histologically defined as definite NASH with a NAFLD Activity Score (NAS) ≥ 4 with at least 1 point in each category and a fibrosis stage ≥ 2. We used the Echosens® formula for FAST™ from LSM (kPa), CAP (dB/m), and AST (U/L), and the FAST™-based Rule-Out (FAST™ ≤ 0.35, sensitivity = 90%) and Rule-In (FAST™ ≥ 0.67, specificity = 90%) zones. We determined the following diagnostic performance measures: AUROC, sensitivity (Se), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV); these were calculated for the total sample and by subgroups of patients and by FibroScan® exam features. We also compared the at-risk NASH diagnostic performance of FAST™ to other non-invasive algorithms: NAFLD fibrosis score (NFS), Fibrosis-4 (FIB-4) index, and AST to platelet ratio index (APRI).ResultsThe NASH CRN population of 585 patients was 62% female, 79% white, 14% Hispanic, and 73% obese; the mean age was 51 years. The mean (SD) AST and ALT were 50 (37) U/L and 66 (45) U/L, respectively. 214 (37%) had at-risk NASH. The AUROC of FAST™ for at-risk NASH in the NASH CRN study population was 0.81 (95% CI: 0.77, 0.84. Using FAST™-based cut-offs, 35% of patients were ruled-out with corresponding NPV = 0.90 and 27% of patients were ruled-in with corresponding PPV = 0.69. The diagnostic accuracy of FAST™ was higher in non-whites vs. whites (AUROC: 0.91 vs 0.78; p = 0.001), and in patients with a normal BMI vs. BMI > 35 kg/m2 (AUROC: 0.94 vs 0.78, p = 0.008). No differences were observed by other patient characteristics or FibroScan® exam features. The FAST™ score had higher diagnostic accuracy than other non-invasive algorithms for the diagnosis of at-risk NASH (AUROC for NFS, FIB-4, and APRI 0.67, 0.73, 0.74, respectively).ConclusionWe validated the FAST™ score for the diagnosis of at-risk NASH in a large, multi-racial population in North America, with a prevalence of at-risk NASH of 37%. Diagnostic performance varies by subgroups of NASH patients defined by race and obesity. FAST™ performed better than other non-invasive algorithms for the diagnosis of at-risk NASH.

Predictions of xenobiotic hepatic clearance in humans using in vitro-to-in vivo extrapolation methods are frequently inaccurate and problematic. Multiple strategies are being pursued to disentangle responsible mechanisms. The objective of this work is to evaluate the feasibility of using insights gained from independent virtual experiments on two model systems to begin unraveling responsible mechanisms. The virtual culture is a software analog of hepatocytes in vitro, and the virtual human maps to hepatocytes within a liver within an idealized model human. Mobile objects (virtual compounds) map to amounts of xenobiotics. Earlier versions of the two systems achieved quantitative validation targets for intrinsic clearance (virtual culture) and hepatic clearance (virtual human). The major difference between the two systems is the spatial organization of the virtual hepatocytes. For each pair of experiments (virtual culture, virtual human), hepatocytes are configured the same. Probabilistic rules govern virtual compound movements and interactions with other objects. We focus on highly permeable virtual compounds and fix their extracellular unbound fraction at one of seven values (0.05-1.0). Hepatocytes contain objects that can bind and remove compounds, analogous to metabolism. We require that, for a subset of compound properties, per-hepatocyte compound exposure and removal rates during culture experiments directly predict corresponding measures made during virtual human experiments. That requirement serves as a cross-system validation target; we identify compound properties that enable achieving it. We then change compound properties, ceteris paribus, and provide model mechanism-based explanations for when and why measures made during culture experiments under- (or over-) predict corresponding measures made during virtual human experiments. The results show that, from the perspective of compound removal, the organization of hepatocytes within virtual livers is more efficient than within cultures, and the greater the efficiency difference, the larger the underprediction. That relationship is noteworthy because most in vitro-to-in vivo extrapolation methods abstract away the structural organization of hepatocytes within a liver. More work is needed on multiple fronts, including the study of an expanded variety of virtual compound properties. Nevertheless, the results support the feasibility of the approach and plan.

In plant cytokinesis, de novo formation of a cell plate evolving into the new cell wall partitions the cytoplasm of the dividing cell. In our earlier chemical genomics studies, we identified and characterized the small molecule endosidin-7, that specifically inhibits callose deposition at the cell plate, arresting late-stage cytokinesis in arabidopsis. Endosidin-7 has emerged as a very valuable tool for dissecting this essential plant process. To gain insights regarding its mode of action and the effects of cytokinesis inhibition on the overall plant response, we investigated the effect of endosidin-7 through a nuclear magnetic resonance spectroscopy (NMR) metabolomics approach. In this case study, metabolomics profiles of arabidopsis leaf and root tissues were analyzed at different growth stages and endosidin-7 exposure levels. The results show leaf and root-specific metabolic profile changes and the effects of endosidin-7 treatment on these metabolomes. Statistical analyses indicated that the effect of endosidin-7 treatment was more significant than the developmental impact. The endosidin-7 induced metabolic profiles suggest compensations for cytokinesis inhibition in central metabolism pathways. This study further shows that long-term treatment of endosidin-7 profoundly changes, likely via alteration of hormonal regulation, the primary metabolism of arabidopsis seedlings. Hormonal pathway-changes are likely reflecting the plant's responses, compensating for the arrested cell division, which in turn are leading to global metabolite modulation. The presented NMR spectral data are made available through the Metabolomics Workbench, providing a reference resource for the scientific community.

Over 9 million new active tuberculosis (TB) cases emerge each year from an enormous pool of 2 billion individuals latently infected with Mycobacterium tuberculosis (M. tb.) worldwide. About 3 million new TB cases per year are unaccounted for, and 1.5 million die. TB, however, is generally curable if diagnosed correctly and in a timely manner. The current diagnostic methods for TB, including state-of-the-art molecular tests, have failed in delivering the capacity needed in endemic countries to curtail this ongoing pandemic. Efficient, cost effective and scalable diagnostic approaches are critically needed. We report a multiplex TB serology panel using microbead suspension array containing a combination of 11 M.tb. antigens that demonstrated overall sensitivity of 91% in serum/plasma samples from TB patients confirmed by culture. Group wise sensitivities for sputum smear positive and negative patients were 95%, and 88%, respectively. Specificity of the test was 96% in untreated COPD patients and 91% in general healthy population. The sensitivity of this test is superior to that of the frontline sputum smear test with a comparable specificity (30-70%, and 93-99%, respectively). The multiplex serology test can be performed with scalability from 1 to 360 patients per day, and is amenable to automation for higher (1000s per day) throughput, thus enabling a scalable clinical work flow model for TB endemic countries. Taken together, the above results suggest that well defined antibody profiles in blood, analyzed by an appropriate technology platform, offer a valuable approach to TB diagnostics in endemic countries.

Microbiologically Influenced Corrosion (MIC) poses a significant challenge to various industries, leading to substantial economic losses and potential safety hazards. Despite extensive research on the MIC resistance of various materials, there is a lack of studies focusing on High Chromium White Iron (HCWI) alloys, which are widely used in wear-resistant applications. This study addresses this knowledge gap by providing a comprehensive investigation of the MIC resistance of three HCWI alloys with varying chromium contents (22 wt%, 30.7 wt%, and 21 wt%) in the presence of Pseudomonas aeruginosa (P. Aeruginosa), a common bacterial species associated with MIC. The alloys were exposed to an artificial seawater medium inoculated with P.Aeruginosa for 14 days, and their corrosion behaviour was evaluated using electrochemical techniques, surface analysis, and microscopy. Electrochemical Impedance Spectroscopy (EIS) results revealed that the alloy with the highest chromium content (A2, 30.7 wt% Cr) exhibited superior MIC resistance compared to the other alloys (A1, 22 wt% Cr and M1, 21 wt% Cr). The enhanced performance of alloy A2 was attributed to the formation of a more stable and protective passive film, as well as the development of a more compact and less permeable biofilm. The EIS data, interpreted using equivalent circuit models, showed that alloy A2 had the highest charge transfer resistance and the lowest biofilm capacitance, indicating a more effective barrier against corrosive species. Bode plots further confirmed the superior corrosion resistance of alloy A2, with higher impedance values and phase angles at low frequencies compared to alloys A1 and M1. Scanning Electron Microscopy (SEM) and optical microscopy analyses corroborated these findings, showing that alloy A2 had the lowest pit density and size after 14 days of exposure. The insights gained from this study highlight the critical role of chromium content in the MIC resistance of HCWI alloys and have significant implications for the design and selection of materials for applications prone to microbial corrosion. [ABSTRACT FROM AUTHOR]

Fruits produce a wide variety of secondary metabolites of great economic value. Analytical measurement of the metabolites is tedious, time-consuming, and expensive. Additionally, metabolite concentrations vary greatly from tree to tree, making it difficult to choose trees for fruit collection. The current study tested whether deep learning-based models can be developed using fruit and leaf images alone to predict a metabolite's concentration class (high or low). We collected fruits and leaves (n = 1045) from neem trees grown in the wild across 0.6 million sq km, imaged them, and measured concentration of five metabolites (azadirachtin, deacetyl-salannin, salannin, nimbin and nimbolide) using high-performance liquid chromatography. We used the data to train deep learning models for metabolite class prediction. The best model out of the seven tested (YOLOv5, GoogLeNet, InceptionNet, EfficientNet_B0, Resnext_50, Resnet18, and SqueezeNet) provided a validation F1 score of 0.93 and a test F1 score of 0.88. The sensitivity and specificity of the fruit model alone in the test set were 83.52 ± 6.19 and 82.35 ± 5.96, and 79.40 ± 8.50 and 85.64 ± 6.21, for the low and the high classes, respectively. The sensitivity was further boosted to 92.67± 5.25 for the low class and 88.11 ± 9.17 for the high class, and the specificity to 100% for both classes, using a multi-analyte framework. We incorporated the multi-analyte model in an Android mobile App Fruit-In-Sight that uses fruit and leaf images to decide whether to 'pick' or 'not pick' the fruits from a specific tree based on the metabolite concentration class. Our study provides evidence that images of fruits and leaves alone can predict the concentration class of a secondary metabolite without using expensive laboratory equipment and cumbersome analytical procedures, thus simplifying the process of choosing the right tree for fruit collection. [ABSTRACT FROM AUTHOR]

Background: Ketamine has recently attracted considerable attention for its rapid effects on patients with major depressive disorder, including treatment-resistant depression (TRD). Despite ketamine's promising results in treating depression, a significant number of patients do not respond to the treatment, and predicting who will benefit remains a challenge. Although its antidepressant effects are known to be linked to its action as an antagonist of the N-methyl-D-aspartate (NMDA) receptor, the precise mechanisms that determine why some patients respond and others do not are still unclear. Objective: This study aims to understand the computational mechanisms underlying changes in the auditory mismatch negativity (MMN) response following treatment with intravenous ketamine. Moreover, we aim to link the computational mechanisms to their underlying neural causes and use the parameters of the neurocomputational model to make individual treatment predictions. Methods: This is a prospective study of 30 patients with TRD who are undergoing intravenous ketamine therapy. Prior to 3 out of 4 ketamine infusions, EEG will be recorded while patients complete the auditory MMN task. Depression, suicidality, and anxiety will be assessed throughout the study and a week after the last ketamine infusion. To translate the effects of ketamine on the MMN to computational mechanisms, we will model changes in the auditory MMN using the hierarchical Gaussian filter, a hierarchical Bayesian model. Furthermore, we will employ a conductance-based neural mass model of the electrophysiological data to link these computational mechanisms to their neural causes. Conclusion: The findings of this study may improve understanding of the mechanisms underlying response and resistance to ketamine treatment in patients with TRD. The parameters obtained from fitting computational models to EEG recordings may facilitate single-patient treatment predictions, which could provide clinically useful prognostic information. Trial registration: Clinicaltrials.gov NCT05464264. Registered June 24, 2022. [ABSTRACT FROM AUTHOR]

This study aimed to determine the prevalence and predictors of oral, ocular, or dermal e-liquid exposure and subsequent outcomes (becoming sick, going to the hospital) in the US. We examined survey data from the Population Assessment of Tobacco and Health Study Wave 5 (2018–2019). The analytic sample included US youth (aged 12–17 years), young adults (aged 18–24 years), and older adults (aged ≥ 25 years) who reported e-cigarette use in the past 12 months. We first determined the prevalence of self-reported e-liquid exposure (in the mouth, skin, or eyes), subsequently "becoming sick" from the exposure, and "going to the hospital" after the exposure. We also examined associations between these outcomes and the device type used (refillable tank /mod system, replaceable prefilled cartridges, disposable/ other device type). E-liquid exposure was reported by 25% of youth (aged 12–17 years), 25% of young adults (aged 18–24 years), and 19% of older adults (aged≥ 25 years). Among individuals reporting e-liquid exposure, subsequent sickness was reported by 10% of youth11% of young adults, and 14% of older adults, and "going to the hospital" was reported by 3.5% of youth, 2.7% of young adults, and 6.8% of older adults. Among young adults, the use of a refillable tank /mod system was associated with higher odds of e-liquid exposure (aOR = 2.2, 95% CI = 1.2, 4.1) than the use of other device types, including disposables. The findings suggest that, at a minimum, e-cigarettes/e-liquids may need warning labels that state the risks of e-liquid exposure and packaging regulations that promote device and bottle designs that minimize e-liquid spills. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity or multiple long-term conditions (MLTCs), the coexistence of two or more chronic conditions within an individual, presents a growing concern for healthcare systems and individuals' well-being. However, we know little about the experiences of those living with MLTCs in low- and middle-income countries (LMICs) such as India. We explore how people living with MLTCs describe their illness, their engagements with healthcare services, and challenges they face within primary care settings in Kerala, India. Methods: We designed a qualitative descriptive study and conducted in-depth, semi-structured interviews with 31 people (16 males and 15 females) from family health centres (FHCs) in Kerala. Interview data were recorded, transcribed, and thematic analysis using the Framework Method was undertaken. Findings: Two main themes and three sub-themes each were identified; (1) Illness impacts on life (a)physical issues (b) psychological difficulties (c) challenges of self-management and (2) Care-coordination maze (a)fragmentation and poor continuity of care (b) medication management; an uphill battle and (c) primary care falling short. All participants reported physical and psychological challenges associated with their MLTCs. Younger participants reported difficulties in their professional lives, while older participants found household activities challenging. Emotional struggles encompassed feelings of hopelessness and fear rooted in concerns about chronic illness and physical limitations. Older participants, adhering to Kerala's familial support norms, often found themselves emotionally distressed by the notion of burdening their children. Challenges in self-management, such as dietary restrictions, medication adherence, and physical activity engagement, were common. The study highlighted difficulties in coordinating care, primarily related to traveling to multiple healthcare facilities, and patients' perceptions of FHCs as fit for diabetes and hypertension management rather than their multiple conditions. Additionally, participants struggled to manage the task of remembering and consistently taking multiple medications, which was compounded by confusion and memory-related issues. Conclusion: This study offers an in-depth view of the experiences of individuals living with MLTCs from Kerala, India. It emphasizes the need for tailored and patient-centred approaches that enhance continuity and coordination of care to manage complex MLTCs in India and similar LMICs. [ABSTRACT FROM AUTHOR]

Elevated incidences of Amyotrophic Lateral Sclerosis/Parkinsonism Dementia complex (ALS/PDC) is associated with β-methylamino-L-alanine (BMAA), a non-protein amino acid. In particular, the native Chamorro people living in the island of Guam were exposed to BMAA by consuming a diet based on the cycad seeds. Carbamylated forms of BMAA are glutamate analogues. The mechanism of neurotoxicity of the BMAA is not completely understood, and BMAA acting as a glutamate receptor agonist may lead to excitotoxicity that interferes with glutamate transport systems. Though the interaction of BMAA with bicarbonate is known to produce carbamate adducts, here we demonstrate that BMAA and its primary and secondary adducts coexist in solution and undergoes a chemical exchange among them. Furthermore, we determined the rates of formation/cleavage of the carbamate adducts under equilibrium conditions using two-dimensional proton exchange NMR spectroscopy (EXSY). The coexistence of the multiple forms of BMAA at physiological conditions adds to the complexity of the mechanisms by which BMAA functions as a neurotoxin.

Activated pancreatic stellate cells (PaSC) are key participants in the stroma of pancreatic cancer, secreting extracellular matrix proteins and inflammatory mediators. Tumors are poorly vascularized, creating metabolic stress conditions in cancer and stromal cells that necessitate adaptive homeostatic cellular programs. Activation of autophagy and the endoplasmic reticulum unfolded protein response (UPR) have been described in hepatic stellate cells, but the role of these processes in PaSC responses to metabolic stress is unknown. We reported that the PI3K/mTOR pathway, which AMPK can regulate through multiple inputs, modulates PaSC activation and fibrogenic potential. Here, using primary and immortalized mouse PaSC, we assess the relative contributions of AMPK/mTOR signaling, autophagy and the UPR to cell fate responses during metabolic stress induced by mitochondrial dysfunction. The mitochondrial uncoupler rottlerin at low doses (0.5-2.5 μM) was added to cells cultured in 10% FBS complete media. Mitochondria rapidly depolarized, followed by altered mitochondrial dynamics and decreased cellular ATP levels. This mitochondrial dysfunction elicited rapid, sustained AMPK activation, mTOR pathway inhibition, and blockade of autophagic flux. Rottlerin treatment also induced rapid, sustained PERK/CHOP UPR signaling. Subsequently, high doses (>5 μM) induced loss of cell viability and cell death. Interestingly, AMPK knock-down using siRNA did not prevent rottlerin-induced mTOR inhibition, autophagy, or CHOP upregulation, suggesting that AMPK is dispensable for these responses. Moreover, CHOP genetic deletion, but not AMPK knock-down, prevented rottlerin-induced apoptosis and supported cell survival, suggesting that UPR signaling is a major modulator of cell fate in PaSC during metabolic stress. Further, short-term rottlerin treatment reduced both PaSC fibrogenic potential and IL-6 mRNA expression. In contrast, expression levels of the angiogenic factors HGF and VEGFα were unaffected, and the immune modulator IL-4 was markedly upregulated. These data imply that metabolic stress-induced PaSC reprogramming differentially modulates neighboring cells in the tumor microenvironment.

Multiplex methodologies, especially those with high-throughput capabilities generate large volumes of data. Accumulation of such data (e.g., genomics, proteomics, metabolomics etc.) is fast becoming more common and thus requires the development and implementation of effective data mining strategies designed for biological and clinical applications. Multiplex microbead immunoassay (MMIA), on xMAP or MagPix platform (Luminex), which is amenable to automation, offers a major advantage over conventional methods such as Western blot or ELISA, for increasing the efficiencies in serodiagnosis of infectious diseases. MMIA allows detection of antibodies and/or antigens efficiently for a wide range of infectious agents simultaneously in host blood samples, in one reaction vessel. In the process, MMIA generates large volumes of data. In this report we demonstrate the application of data mining tools on how the inherent large volume data can improve the assay tolerance (measured in terms of sensitivity and specificity) by analysis of experimental data accumulated over a span of two years. The combination of prior knowledge with machine learning tools provides an efficient approach to improve the diagnostic power of the assay in a continuous basis. Furthermore, this study provides an in-depth knowledge base to study pathological trends of infectious agents in mouse colonies on a multivariate scale. Data mining techniques using serodetection of infections in mice, developed in this study, can be used as a general model for more complex applications in epidemiology and clinical translational research.

Sleep, specifically non-rapid eye movement (NREM) sleep, is thought to play a critical role in the consolidation of recent memories. Two main oscillatory activities observed during NREM, cortical slow oscillations (SO, 0.5-1.0 Hz) and thalamic spindles (12-15 Hz), have been shown to independently correlate with memory improvement. Yet, it is not known how these thalamocortical events interact, or the significance of this interaction, during the consolidation process. Here, we found that systemic administration of the GABAergic drug (zolpidem) increased both the phase-amplitude coupling between SO and spindles, and verbal memory improvement in humans. These results suggest that thalamic spindles that occur during transitions to the cortical SO Up state are optimal for memory consolidation. Our study predicts that the timely interactions between cortical and thalamic events during consolidation, contribute to memory improvement and is mediated by the level of inhibitory neurotransmission.

The first cure of HIV-1 infection was achieved through complex, multimodal therapy including myeloablative chemotherapy, total body irradiation, anti-thymocyte globulin, and allogeneic stem cell transplantation with a CCR5 delta32 homozygous donor. The contributions of each component of this therapy to HIV-1 eradication are unclear. To assess the impact of cytotoxic chemotherapy alone on HIV-1 persistence, we longitudinally evaluated low-level plasma viremia and HIV-1 DNA in PBMC from patients in the ACTG A5001/ALLRT cohort on suppressive antiretroviral therapy (ART) who underwent chemotherapy for HIV-1 related lymphoma without interrupting ART. Plasma HIV-1 RNA, total HIV-1 DNA and 2-LTR circles (2-LTRs) in PBMC were measured using sensitive qPCR assays. In the 9 patients who received moderately intensive chemotherapy for HIV-1 related lymphoma with uninterrupted ART, low-level plasma HIV-1 RNA did not change significantly with chemotherapy: median HIV-1 RNA was 1 copy/mL (interquartile range: 1.0 to 20) pre-chemotherapy versus 4 copies/mL (interquartile range: 1.0 to 7.0) post-chemotherapy. HIV-1 DNA levels also did not change significantly, with median pre-chemotherapy HIV-1 DNA of 355 copies/106 CD4+ cells versus 228 copies/106 CD4+ cells post-chemotherapy. 2-LTRs were detectable in 2 of 9 patients pre-chemotherapy and in 3 of 9 patients post-chemotherapy. In summary, moderately intensive chemotherapy for HIV-1 related lymphoma in the context of continuous ART did not have a prolonged impact on HIV-1 persistence. Clinical trials registration unique identifier: NCT00001137.

Introduction: Promoting smoking cessation is a global public health priority. E-cigarettes are increasingly being used by individuals to try quitting smoking. Identifying sources and types of information available to adults who are trying to quit, and the impact of this information during a quit attempt, is critical to augment the potential public health benefit of e-cigarettes for reducing cigarette smoking. Methods: US adults (N = 857) who reported using e-cigarettes in a recent smoking cessation attempt completed an anonymous, cross sectional, online survey. We examined sources of information and type of information received when using e-cigarettes to quit smoking and their associations with the duration of abstinence achieved. Results: The two most commonly reported information sources were friends (43.9%) and the internet (35.2%), while 14.0% received information from a healthcare provider. People received information on type of device (48.5%), flavor (46.3%), and nicotine concentration (43.6%). More people received information about gradually switching from smoking to vaping (46.7%) than abruptly switching (30.2%). Obtaining information from healthcare providers (β (SE) = 0.16 (0.08), p = 0.04), getting information about abruptly switching to e-cigarettes (β (SE) = 0.14 (0.06), p = 0.01) and what nicotine concentrations to use (β (SE) = 0.18 (0.05), p = 0.03) were associated with longer quit durations. Conclusions: Amidst the growing popularity of e-cigarettes use for quitting smoking, our results highlight common sources of information and types of information received by individuals. Few people received information from healthcare providers indicating a gap in cessation support that can be filled. Providing information about immediate switching to e-cigarettes and nicotine concentrations to use may help in increasing quit rates and duration. [ABSTRACT FROM AUTHOR]

Background: Limited data exists regarding risk factors for adverse outcomes in older adults hospitalized with Community-Acquired Pneumonia (CAP) in low- and middle-income countries such as India. This multisite study aimed to assess outcomes and associated risk factors among adults aged ≥60 years hospitalized with pneumonia. Methods: Between December 2018 and March 2020, we enrolled ≥60-year-old adults admitted within 48 hours for CAP treatment across 16 public and private facilities in four sites. Clinical data and nasal/oropharyngeal specimens were collected by trained nurses and tested for influenza, respiratory syncytial virus (RSV), and other respiratory viruses (ORV) using the qPCR. Participants were evaluated regularly until discharge, as well as on the 7th and 30th days post-discharge. Outcomes included ICU admission and in-hospital or 30-day post-discharge mortality. A hierarchical framework for multivariable logistic regression and Cox proportional hazard models identified risk factors (e.g., demographics, clinical features, etiologic agents) associated with critical care or death. Findings: Of 1,090 CAP patients, the median age was 69 years; 38.4% were female. Influenza viruses were detected in 12.3%, RSV in 2.2%, and ORV in 6.3% of participants. Critical care was required for 39.4%, with 9.9% in-hospital mortality and 5% 30-day post-discharge mortality. Only 41% of influenza CAP patients received antiviral treatment. Admission factors independently associated with ICU admission included respiratory rate >30/min, blood urea nitrogen>19mg/dl, altered sensorium, anemia, oxygen saturation <90%, prior cardiovascular diseases, chronic respiratory diseases, and private hospital admission. Diabetes, anemia, low oxygen saturation at admission, ICU admission, and mechanical ventilation were associated with 30-day mortality. Conclusion: High ICU admission and 30-day mortality rates were observed among older adults with pneumonia, with a significant proportion linked to influenza and RSV infections. Comprehensive guidelines for CAP prevention and management in older adults are needed, especially with the co-circulation of SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Therapeutic response to selective serotonin (5-HT) reuptake inhibitors in Major Depressive Disorder (MDD) varies considerably among patients, and the onset of antidepressant therapeutic action is delayed until after 2 to 4 weeks of treatment. The objective of this study was to analyze changes within methoxyindole and kynurenine (KYN) branches of tryptophan pathway to determine whether differential regulation within these branches may contribute to mechanism of variation in response to treatment. Metabolomics approach was used to characterize early biochemical changes in tryptophan pathway and correlated biochemical changes with treatment outcome. Outpatients with MDD were randomly assigned to sertraline (n = 35) or placebo (n = 40) in a double-blind 4-week trial; response to treatment was measured using the 17-item Hamilton Rating Scale for Depression (HAMD17). Targeted electrochemistry based metabolomic platform (LCECA) was used to profile serum samples from MDD patients. The response rate was slightly higher for sertraline than for placebo (21/35 [60%] vs. 20/40 [50%], respectively, χ(2)(1)  = 0.75, p = 0.39). Patients showing a good response to sertraline had higher pretreatment levels of 5-methoxytryptamine (5-MTPM), greater reduction in 5-MTPM levels after treatment, an increase in 5-Methoxytryptophol (5-MTPOL) and Melatonin (MEL) levels, and decreases in the (KYN)/MEL and 3-Hydroxykynurenine (3-OHKY)/MEL ratios post-treatment compared to pretreatment. These changes were not seen in the patients showing poor response to sertraline. In the placebo group, more favorable treatment outcome was associated with increases in 5-MTPOL and MEL levels and significant decreases in the KYN/MEL and 3-OHKY/MEL; changes in 5-MTPM levels were not associated with the 4-week response. These results suggest that recovery from a depressed state due to treatment with drug or with placebo could be associated with preferential utilization of serotonin for production of melatonin and 5-MTPOL.

The assembly of pili on the cell wall of Gram-positive bacteria requires transpeptidase enzymes called sortases. In Streptococcus agalactiae, the PI-1 pilus island of strain 2603V/R encodes two pilus-specific sortases (SrtC1 and SrtC2) and three pilins (GBS80, GBS52 and GBS104). Although either pilus-specific sortase is sufficient for the polymerization of the major pilin, GBS80, incorporation of the minor pilins GBS52 and GBS104 into the pilus structure requires SrtC1 and SrtC2, respectively. The S. agalactiae housekeeping sortase, SrtA, whose gene is present at a different location and does not catalyze pilus polymerization, was shown to be involved in cell wall anchoring of pilus polymers. To understand the structural basis of sortases involved in such diverse functions, we determined the crystal structures of S. agalactiae SrtC1 and SrtA. Both enzymes are made of an eight-stranded beta-barrel core with variations in their active site architecture. SrtA exhibits a catalytic triad arrangement similar to that in Streptococcus pyogenes SrtA but different from that in Staphylococcus aureus SrtA. In contrast, the SrtC1 enzyme contains an N-terminal helical domain and a 'lid' in its putative active site, which is similar to that seen in Streptococcus pneumoniae pilus-specific sortases, although with subtle differences in positioning and composition. To understand the effect of such differences on substrate recognition, we have also determined the crystal structure of a SrtC1 mutant, in which the conserved DP(W/F/Y) motif was replaced with the sorting signal motif of GBS80, IPNTG. By comparing the structures of WT wild type SrtA and SrtC1 and the 'lid' mutant of SrtC1, we propose that structural elements within the active site and the lid may be important for defining the role of specific sortase in pili biogenesis.