Mechanistic and physiological insights into post-transcriptional regulation by small RNAs SgrS and DicF

Base pairing small regulatory RNAs (sRNAs) are important post-transcriptional regulators of gene expression in bacteria. These sRNAs deploy novel mechanisms to regulate mRNA targets leading to various physiological outcomes during stress conditions including, but not limited to, iron starvation, carbon flux and metabolism, virulence, and quorum sensing. In this study, we investigate the multitude of clever mechanisms that two sRNAs, SgrS and DicF, utilize to regulate gene expression, and the physiological consequences of such regulation. The SgrS sRNA participates in a response to a growth inhibitory stress condition called sugar-phosphate stress caused by the toxic accumulation of phosphorylated sugars. SgrS combats this stress with its RNA base pairing function by silencing translation of sugar transporters that import the stress molecules. SgrS was previously shown to negatively regulate the manXYZ broad sugar-substrate transporter. In this study we demonstrate that SgrS binds at manX and in the intergenic region of manXY to translationally silence this operon. We show that pairing at both these sites is critical for degradation of the manXYZ polycistron, and is also crucial for providing maximal relief from stress. SgrS is a dual-function sRNA in that in addition to its RNA function, it also produces a peptide called SgrT. Here, we investigate the mechanistic relationship between these two functions of SgrS. We demonstrate that while mutating the sgrT translation initiation sequences have little impact on SgrS base pairing properties, mutations in the sgrS base pairing region increase SgrT production. Further, the SgrS RNA function was the primary means of action against sugar-phosphate stress; SgrT production lags SgrS synthesis. We therefore propose a model in which the two independent functions of SgrS act at different stages in response to sugar-phosphate stress. The DicF sRNA is encoded on the dicBF operon on the cryptic Qin prophage in E. coli. The only known target of DicF is the ftsZ mRNA, whose gene product is essential for cell division in bacteria. Using reporter gene fusions to predicted target genes, we identified three genes in metabolism that are also targets of DicF. DicF also requires core E. coli proteins for its base pairing properties. We also demonstrate that in addition to inhibiting cell division, DicF leads to growth inhibition of cells. Lastly, the gene products of the dicBF operon are cumulatively toxic to E. coli cells. Characterizing mechanistic contributions of sRNAs to significant physiological outcomes will better our understanding of these novel regulatory RNA elements

Risk factors of asymptomatic bacteriuria and fetomaternal outcome following treatment in early versus late gestation

Background: Asymptomatic bacteriuria (ASB) has higher incidence in pregnant than in non-pregnant women and is difficult to diagnose. It is associated with fetomaternal complications like prelabour rupture of membranes, preterm labour, low birth weight and increased perinatal mortality. The aim of this study is to analyse various risk factors and the maternal and fetal outcome following treatment of asymptomatic bacteriuria in early versus late gestation.Methods: This prospective study was conducted in Thanjavur Medical college and Hospital in 2019. The study population comprises all pregnant women attending antenatal clinic for their 1st antenatal visit.Results: Total of 800 antenatal women were enrolled in 2 groups based on gestational age <20 weeks (n=394) and between 28 to 32 weeks (n=406) at the time of their 1st antenatal visit. Incidence of asymptomatic bacteriuria was 13.6% and 84.4% were in the age group of 21-30 years. High prevalence was noted in primigravidae (47.7%) and in lower socioeconomic class (70.9%). Commonest organism isolated was E. coli (42.2%) and most of the organisms were sensitive to gentamycin (89.9%) and cefotaxime (84.4%). Despite treatment of asymptomatic bacteriuria, complications like anaemia, gestational hypertension & preterm labour were higher in late detection group than in early detection group.Conclusions: This study shows high prevalence of asymptomatic bacteriuria in pregnant women. The chances of developing maternal complications were significantly reduced after antibiotic therapy of asymptomatic bacteriuria. Hence, early screening and treatment of asymptomatic bacteriuria needs to be incorporated in routine antenatal care

Telephone support and adherence in patients with chronic disease:A qualitative review of reviews

Divya Balasubramanian,1 Joanne Yoong,1–3 Hubertus JM Vrijhoef1,3–6 1Saw Swee Hock School of Public Health, National University Singapore, Singapore; 2Center for Economic and Social Research, University of Southern California, California, USA; 3Center for Health Services and Policy Research, National University Health System, Singapore; 4Scientific Center for Care and Welfare, Tilburg University, Tilburg, The Netherlands; 5Department of Patients & Care, Maastricht University Medical Center, Maastricht, The Netherlands; 6Department of Family Medicine and Chronic Care, Vrije Universiteit Brussels, Brussels, Belgium Abstract: Among patients with a chronic disease, low adherence to prescribed treatments is very common, leading to substantial morbidity, mortality, and increase in health care costs. Telephone or mobile phone support is a common form of intervention that can be used to improve their adherence. We reviewed existing systematic and nonsystematic reviews to analyze the effectiveness of telephone interventions to improve treatment adherence in patients with chronic disease. Secondary aims were to evaluate the selected reviews in terms of cost-effectiveness of the intervention and frequency of messages affecting the adherence outcomes. A search for reviews was conducted in three databases, including PubMed, the Cochrane Library, and CINAHL, and three reviews that met the inclusion criteria were selected for final analysis. A qualitative review of the selected reviews was conducted, and reviews were evaluated to extract and summarize the characteristics and outcomes. Two of the selected reviews studied mobile phone text messaging, and one review studied telephone or mobile phone consultation. All three reviews reported an overall improvement in adherence, but the reviews varied in the types of research and the outcome measures. However, none of the reviews reported costs as an outcome. The evidence from reviews to characterize the effectiveness or cost-effectiveness of telephone support as an intervention to improve adherence among people with chronic diseases is fairly small and weak. Telephone support interventions have to be evaluated more systematically in routine practice against a comprehensive set of criteria, including their relative costs and outcomes. Keywords: literature review, compliance, telemedicine, communicable diseases, cost-effectivenes

Synthesis and Characterization of Magnesium Doped Ferric Sulphate Nanoparticles (Mg-Fe2SO3 NPs) for Agriculture Applications

The present study aimed to synthesize the magnesium doped ferric sulphate nanoparticles (Mg-Fe2SO3 NPs) and investigate their seed germination efficacy. Mg-Fe2SO3 NPs were prepared by a simple and cost-effective method and subjected to characterization. The X-ray Diffraction (XRD) spectrum revealed the crystalline nature of Mg-Fe2SO3 NPs with an average crystallite size of 36.41 nm. The field emission scanning electron microscope (FESEM) image displayed the agglomeration of Mg-Fe2SO3 NPs with the shape of the grains appeared like starfish which has limbs grown from a common cluster. The energy dispersive X-ray spectroscopy (EDS) demonstrated the existence of C (10.5%), O (49.14%), Fe (26.67%), Mg (0.78%) and S (13.35%) elements in Mg-Fe2SO3 NPs. It also revealed the absence of impurities in the synthesized NPs. Through Fourier transform infrared spectroscopy (FTIR), Mg-Fe2SO3 NPs showed the characteristic peaks at 615.29cm-1, 1130.29cm-1, 1400.32 cm-1and 1633.71cm-1 which corresponded to Fe-O, C-N, O-H and N-H vibration respectively. Further, the seed germination study revealed that the Mg-Fe2SO3 NPs treatment caused a significant increase in seedling growth of cowpea (Vigna unguiculata) seeds compared to the untreated samples

GC-MS-based metabolomics analysis unravels the therapeutic potential of Neolamarckia cadamba fruit peel

Kadam (Neolamarckia cadamba (Roxb.) is an evergreen tropical tree widely grown in Asia, particularly in India. Neolamarckia cadamba commonly known as kadam, cadamba or burflower tree. The roots, leaves, barks, and fruits of N. cadamba possess medicinal properties and are commonly used in the pharmaceutical industry. Fruit peels are the main waste and may contain various biologically active compounds. However, no prior knowledge about the therapeutic compounds of the peel. The objective of the present study was to unveil therapeutic compounds from the peel by Gas Chromatography–Mass Spectrometry (GC-MS) based metabolomics analysis. Metabolites from the kadam fruit peel were isolated and derivatized using MSTFA, characterized by the GC-MS analysis. Raw spectral data were pre-processed, and peak identification was performed using SHIMADZU Postrun analyse software. The metabolites in N. cadamba fruit peel were identified by comparing the peaks with the mass spectral reference database NIST v20. The results showed that the peel of kadam fruit contains 149 metabolites, which were further categorized into 46 different metabolite classes, with 52 different metabolic pathways and 63 biological functions. The principal roles of the metabolites were identified by functional annotation and enrichment analysis. It revealed that metabolites were responsible for anti-inflammation, anti-oxidant, anti-microbial, and anti-cancer properties. In summary, the peel of kadam fruit also contains various therapeutic compounds like other cadamba parts (i.e., roots, leaves, barks, and fruits). Further, comparing the peel with other parts discloses the peel-specific metabolites. The results obtained in this study could be useful for the pharmaceutical industry

Suppressing H2 Evolution and Promoting Selective CO2 Electroreduction to CO at Low Overpotentials by Alloying Au with Pd

CO2 electroreduction is a promising technology to produce chemicals and fuels from renewable resources. Polycrystalline and nanostructured metals have been tested extensively while less effort has been spent on understanding the performance of bimetallic alloys. In this work, we study compositionally variant, smooth Au–Pd thin film alloys to discard any morphological or mesoscopic effect on the electrocatalytic performance. We find that the onset potential of CO formation exhibits a strong dependence on the Pd content of the alloys. Strikingly, palladium, a hydrogen evolution catalyst with reasonable exchange current density, suppresses hydrogen evolution when alloyed with gold in the presence of CO2. Cyclic voltammetry, in situ surface enhanced infrared absorption spectroscopy, and potential-dependent online product analysis strongly suggest that by alloying Au with Pd a significant increase in the surface coverage of adsorbed CO occurs with increasing Pd content at low overpotentials (e.g., approximately −0.35 V vs RHE). Such an increase in CO coverage suppresses H2 evolution due to the lack of vacant active sites. Moreover, the overall increase in the binding energy with the CO2 intermediates gained with the addition of Pd increases the CO production at low overpotentials, where polycrystalline Au suffers from poor CO2 adsorption and poor selectivity for CO production. These results show that promising CO2 reduction electrode materials (e.g., Au) can be alloyed not only to tune the catalyst’s activity but also to deliberately decrease the availability of surface sites for competitive H2 evolution

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Effect of Hydrocortisone on Mortality and Organ Support in Patients With Severe COVID-19: The REMAP-CAP COVID-19 Corticosteroid Domain Randomized Clinical Trial.

Importance: Evidence regarding corticosteroid use for severe coronavirus disease 2019 (COVID-19) is limited. Objective: To determine whether hydrocortisone improves outcome for patients with severe COVID-19. Design, Setting, and Participants: An ongoing adaptive platform trial testing multiple interventions within multiple therapeutic domains, for example, antiviral agents, corticosteroids, or immunoglobulin. Between March 9 and June 17, 2020, 614 adult patients with suspected or confirmed COVID-19 were enrolled and randomized within at least 1 domain following admission to an intensive care unit (ICU) for respiratory or cardiovascular organ support at 121 sites in 8 countries. Of these, 403 were randomized to open-label interventions within the corticosteroid domain. The domain was halted after results from another trial were released. Follow-up ended August 12, 2020. Interventions: The corticosteroid domain randomized participants to a fixed 7-day course of intravenous hydrocortisone (50 mg or 100 mg every 6 hours) (n = 143), a shock-dependent course (50 mg every 6 hours when shock was clinically evident) (n = 152), or no hydrocortisone (n = 108). Main Outcomes and Measures: The primary end point was organ support-free days (days alive and free of ICU-based respiratory or cardiovascular support) within 21 days, where patients who died were assigned -1 day. The primary analysis was a bayesian cumulative logistic model that included all patients enrolled with severe COVID-19, adjusting for age, sex, site, region, time, assignment to interventions within other domains, and domain and intervention eligibility. Superiority was defined as the posterior probability of an odds ratio greater than 1 (threshold for trial conclusion of superiority >99%). Results: After excluding 19 participants who withdrew consent, there were 384 patients (mean age, 60 years; 29% female) randomized to the fixed-dose (n = 137), shock-dependent (n = 146), and no (n = 101) hydrocortisone groups; 379 (99%) completed the study and were included in the analysis. The mean age for the 3 groups ranged between 59.5 and 60.4 years; most patients were male (range, 70.6%-71.5%); mean body mass index ranged between 29.7 and 30.9; and patients receiving mechanical ventilation ranged between 50.0% and 63.5%. For the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively, the median organ support-free days were 0 (IQR, -1 to 15), 0 (IQR, -1 to 13), and 0 (-1 to 11) days (composed of 30%, 26%, and 33% mortality rates and 11.5, 9.5, and 6 median organ support-free days among survivors). The median adjusted odds ratio and bayesian probability of superiority were 1.43 (95% credible interval, 0.91-2.27) and 93% for fixed-dose hydrocortisone, respectively, and were 1.22 (95% credible interval, 0.76-1.94) and 80% for shock-dependent hydrocortisone compared with no hydrocortisone. Serious adverse events were reported in 4 (3%), 5 (3%), and 1 (1%) patients in the fixed-dose, shock-dependent, and no hydrocortisone groups, respectively. Conclusions and Relevance: Among patients with severe COVID-19, treatment with a 7-day fixed-dose course of hydrocortisone or shock-dependent dosing of hydrocortisone, compared with no hydrocortisone, resulted in 93% and 80% probabilities of superiority with regard to the odds of improvement in organ support-free days within 21 days. However, the trial was stopped early and no treatment strategy met prespecified criteria for statistical superiority, precluding definitive conclusions. Trial Registration: ClinicalTrials.gov Identifier: NCT02735707

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks