Influence of using synbiotics by various routes on Mandarah male chicks: intestinal bacterial counts, gut morphology and histological status.

This experiment investigated the influence of different synbiotic processing methods on the intestinal bacterial count, morphology and histological status of developed male Mandarah chicks. Two hundred and ten male Mandarah line chicks aged 1 d were randomized to receive one of 7 chicks. The method and dose for 1-time synbiotics administration to the day-old chicks were as follows: G1: chicks on basal diet received no treatment (control); G2: 0.25 mL synbiotics sprayed; G3: 0.50 mL synbiotics sprayed; G4: 0.25 mL of synbiotics are added to drinking water; G5: 0.50 mL of synbiotics are added to drinking water; G6: 0.25 mL of synbiotics dripped into the mouth; and G7: 0.50 mL of synbiotics dripped into mouth drops. Lactic acid bacteria(LAB) were significantly increased (P<0.0001) compared to the control group and other treated groups and had the maximum values after the use of synbiotics via drinking water (0.25 or 0.50 mL). Furthermore, when comparing the treated birds (G4, G5) with the control birds, the Escherichia coli concentration in the drinking water containing synbiotics was significantly lower. In addition, treated chickens at (G7) showed a higher duodenum, ileum villus height (VH), and VH. - Ileum crypt depth (CD) ratio compared to other groups. In addition, birds treated with 0.50 mL of synbiotics in drinking water (G5) performed better in duodenum, ileum, CD and VH. - CD ratio than the other groups. Meanwhile, intestinal tract length and visceral pH did not differ significantly between groups. It can be concluded that the use of 0.25 mL of synbiotics in drinking water can improve the overall health of birds.

The Planetary Child Health & Enterics Observatory (Plan-EO): A protocol for an interdisciplinary research initiative and web-based dashboard for mapping enteric infectious diseases and their risk factors and interventions in LMICs.

BACKGROUND: Diarrhea remains a leading cause of childhood illness throughout the world that is increasing due to climate change and is caused by various species of ecologically sensitive pathogens. The emerging Planetary Health movement emphasizes the interdependence of human health with natural systems, and much of its focus has been on infectious diseases and their interactions with environmental and human processes. Meanwhile, the era of big data has engendered a public appetite for interactive web-based dashboards for infectious diseases. However, enteric infectious diseases have been largely overlooked by these developments. METHODS: The Planetary Child Health & Enterics Observatory (Plan-EO) is a new initiative that builds on existing partnerships between epidemiologists, climatologists, bioinformaticians, and hydrologists as well as investigators in numerous low- and middle-income countries. Its objective is to provide the research and stakeholder community with an evidence base for the geographical targeting of enteropathogen-specific child health interventions such as novel vaccines. The initiative will produce, curate, and disseminate spatial data products relating to the distribution of enteric pathogens and their environmental and sociodemographic determinants. DISCUSSION: As climate change accelerates there is an urgent need for etiology-specific estimates of diarrheal disease burden at high spatiotemporal resolution. Plan-EO aims to address key challenges and knowledge gaps by making and disseminating rigorously obtained, generalizable disease burden estimates. Pre-processed environmental and EO-derived spatial data products will be housed, continually updated, and made publicly available for download to the research and stakeholder communities. These can then be used as inputs to identify and target priority populations living in transmission hotspots and for decision-making, scenario-planning, and disease burden projection. STUDY REGISTRATION: PROSPERO protocol #CRD42023384709.

Design, synthesis, and mechanistic insight of novel imidazolones as potential EGFR inhibitors and apoptosis inducers.

As regards to the structural analysis and optimization of diverse potential EGFR inhibitors, two series of imidazolyl-2-cyanoprop-2-enimidothioates and ethyl imidazolylthiomethylacrylates were designed and constructed as potential EGFR suppressors. The cytotoxic effect of the prepared derivatives was assessed toward hepatic, breast, and prostate cancerous cells (Hep-G2, MCF-7, and PC-3). Three derivatives 3d, 3e, and 3f presented potent antiproliferative activity and selectivity against the examined tumor cells showing IC50 values at low micromolar levels. Hence, successive biological assays were applied to determine the probable mechanism of action of the new compounds. They exhibited significant EGFR suppression with an IC50 range of 0.137-0.507 µM. The most effective EGFR inhibitor 3f arrested the MCF-7 cell cycle at the S phase by inducing the apoptotic pathway that was confirmed via increasing the expression of Caspases 8, 9, and Bax, which are associated with Bcl-2 decline. Additionally, molecular docking displayed a distinctive interaction between 3f and EGFR binding pocket. Overall, this work introduces some novel imidazolyl-2-cyanoprop-2-enimidothioates and ethyl imidazolylthiomethylacrylates as potential cytotoxic and EGFR inhibitors that deserve further research in tumor therapy.

Novel benzochromenes: design, synthesis, cytotoxicity, molecular docking and mechanistic investigations.

Aim: A novel series of fused benzochromenes with expected cytotoxicity and HIF-1α inhibition was identified. Materials & methods: A bioisosterism-aided approach was applied to design new benzochromenes and assess their cytotoxicity against three cancer cell lines. The probable mechanistic effect and the in silico docking and pharmacokinetic profiles of the most effective derivatives were evaluated. Results: Compounds 3, 4, 5, 8 and 11 showed potent antiproliferative activity and excellent selectivity. Compound 8 showed significant HIF-1α inhibition with an IC50 value of 3.372 µM. It also enhanced apoptosis and arrested the HepG2 cell cycle at both the G0/G1 and S stages. Conclusion: Compound 8 was identified as a new potential anticancer candidate.

Molecular overlay-guided design of new CDK2 inhibitor thiazepinopurines: Synthesis, anticancer, and mechanistic investigations.

Adopting the molecular overlay approach, three novel sets of thiazepinopurines with expected cytotoxicity and CDK2 inhibition potential were designed and synthesized. This was accomplished through the heteroannelation of purines, for the first time, with thiazepine. The obtained thiazepinopurines derivatives were assessed for their cytotoxicity toward tumor cells of three different types, HepG2, MCF-7, and PC-3 as well as one normal cell (WI38). Among the studied compounds, 3b and 3c exhibited significant antiproliferative activity against tumor cells presenting IC50 range of 5.52-17.09 µM in comparison with Roscovitine (9.32-13.82 µM). Additionally, both compounds displayed superior selectivity indices (SI = 3.00-7.15) toward tested cancer cells. The 4-chlorophenyl analog 3b has shown the best selectivity index, and hence it has been subjected to additional investigations to determine its proper mechanistic effect. Accordingly, the CDK2 inhibition potential, apoptosis induction, and cell cycle analysis of MCF-7 were evaluated. Results revealed that this analog displayed a potent CDK2 inhibition potential with an IC50 value of 0.219 µM. Findings also showed that 3b was thought to arrest MCF-7 cell cycle at S phase together with apoptosis induction by the increased expression of Bax, Caspase-8, and -9 markers with a concomitant decrease in Bcl-2 expression. Besides, the probable interaction of 3b with CDK2 binding pocket was investigated by molecular docking.

Aminopyridone-linked benzimidazoles: a fragment-based drug design for the development of CDK9 inhibitors.

Aim: A fragment-based design and synthesis of three novel series of aminopyridone-linked benzimidazoles as potential anticancer candidates with significant CDK9 inhibition was implemented. Materials & methods: All synthesized compounds were submitted to National Cancer Institute, 60 cell lines and seven-dose cytotoxicity toward three cancer cells. Results: Compounds 2, 4a, 4c, 4d, 6a and 8a exhibited significant cytotoxicity and selectivity with IC50 range of 7.61-57.75 µM. Regarding the mechanism either in vitro or in silico, 4a, 6a and 8a displayed potent CDK9 inhibition with IC50 value of 0.424-8.461 µM. Compound 6a arrested the cell cycle at S phase and induced apoptosis in MCF-7 cells. Conclusion: Compound 6a is a promising CDK9 inhibitor that warrants additional research for cancer treatment.

Novel fused imidazotriazines acting as promising top. II inhibitors and apoptotic inducers with greater selectivity against head and neck tumors: Design, synthesis, and biological assessments.

Although the great effectiveness of doxorubicin (Dox) in the treatment of many types of tumors, it showed limited effectiveness against the head and neck squamous cell carcinoma (HNSCC) subtype which is attributed to its reported multiple drug resistance (MDR). In the current study, we considered the essential pharmacophoric features of Dox as an effective Top. II inhibitor and sought to develop a novel set of imidazo[1,2-a] [1,3,5]triazin-2-amines (2a-2p) as a suggested anticancer option that could intercalate the DNA base pairs. We evaluated the % inhibition of the newly synthesized compounds on thirteen cancer cell lines and the analysis of structure-activity relationships revealed that the human head and neck cancer cell line (HNO97) was the most sensitive to their growth inhibition effect. Then, the IC50 values were recorded against the most sensitive cancer cell lines (HNO97, MDA-MB-231, and HEPG2), and compared to the normal cell line OEC (human oral epithelial cells). Compounds 2f and 2g showed very strong activities against HNO97 with IC50 values of (4 ± 1 and 3 ± 1.5 µg/mL), respectively, compared to that of Dox (9 ± 1.6 µg/mL). Next, a quantitative determination of human DNA Top. II concentrations in the most sensitive cell line (HNO97) were recorded for the most active anticancer derivatives. Again, compound 2f showed a superior Top. II inhibition with 87.86% compared to that of Dox (86.44%), while compound 2g achieved an inhibition of 81.37% which was close to the effect of Dox. To further investigate their effects on cell cycle progression and apoptosis induction in HNO97 cells, both 2f and 2g were selected for analysis. Both candidates arrested cell cycle progression at both the S and G2-M phases, as well as increased the early and late apoptosis phase ratios. Besides, both 2f and 2g were subjected to protein expression analysis of apoptosis-related genes (p53, BAX, IL-6, and BCL2). Moreover, the antioxidant effect of 2f and 2g was evaluated by measuring GSH, MDA, and NO markers in HNO97 cells. Furthermore, molecular docking for the newly designed tricyclic derivatives against both the Top. II and DNA double helix was carried out.

Unified real-time environmental-epidemiological data for multiscale modeling of the COVID-19 pandemic.

An impressive number of COVID-19 data catalogs exist. However, none are fully optimized for data science applications. Inconsistent naming and data conventions, uneven quality control, and lack of alignment between disease data and potential predictors pose barriers to robust modeling and analysis. To address this gap, we generated a unified dataset that integrates and implements quality checks of the data from numerous leading sources of COVID-19 epidemiological and environmental data. We use a globally consistent hierarchy of administrative units to facilitate analysis within and across countries. The dataset applies this unified hierarchy to align COVID-19 epidemiological data with a number of other data types relevant to understanding and predicting COVID-19 risk, including hydrometeorological data, air quality, information on COVID-19 control policies, vaccine data, and key demographic characteristics.

Design and synthesis of novel uracil-linked Schiff bases as dual histone deacetylase type II/topoisomerase type I inhibitors with apoptotic potential.

Aim: The previously reported dual histone deacetylase type II (HDAC II) / topoisomerase type I (Topo I) inhibitors suffer pharmacokinetic limitations because of their huge molecular weights. Materials & methods: We report the design and synthesis of a smarter novel set of uracil-linked Schiff bases (19-30) as dual HDAC II/Topo I inhibitors keeping the essential pharmacophoric features. Cytotoxicity of all compounds was assessed against three cancer cell lines. Studies of their effects on the apoptotic BAX and antiapoptotic BCL2 genes, molecular docking studies, and absorption, distribution, metabolism and excretion studies were conducted. Results: Compounds 22, 25 and 30 exhibited significant activities. The bromophenyl derivative 22 displayed the best selectivity index, with IC50 values against HDAC II and Topo I of 1.12 and 13.44 µM, respectively. Conclusion: Compound 22 could be considered a lead HDAC II/Topo I inhibitor.

A novel class of phenylpyrazolone-sulphonamides rigid synthetic anticancer molecules selectively inhibit the isoform IX of carbonic anhydrases guided by molecular docking and orbital analyses.

All the previously reported phenylpyrazoles as carbonic anhydrase inhibitors (CAIs) were found to have small sizes and high levels of flexibility, and hence showed low selectivity profiles toward a particular isoform of CA. Herein, we report the development of a more rigid ring system bearing a sulfonamide hydrophilic head and a lipophilic tail to develop novel molecules that are suggested to have a better selectivity toward a special CA isoform. Accordingly, three novel sets of pyrano[2,3-c]pyrazoles attached with sulfonamide head and aryl hydrophobic tail were synthesized to enhance the selectivity toward a specific isoform of human carbonic anhydrases (hCAs). The impact of both attachments on the potency and selectivity has been extensively discussed in terms of in vitro cytotoxicity evaluation under hypoxic conditions, structure-activity relationship and carbonic anhydrase enzyme assay. All of the new candidates displayed good cytotoxic activities against breast and colorectal carcinomas. Results of the carbonic anhydrase enzyme assay demonstrated the preferential of compounds 22, 24 and 27 to inhibit the isoform IX of hCAs selectively. Wound-healing assay has also been performed and revealed the potential of 27 to decrease the wound closure percentage in MCF-7 cells. Molecular docking and molecular orbital analysis have finally been conducted. Results indicate the potential binding interactions of 24 and 27 with several crucial amino acids of the hCA IX.Communicated by Ramaswamy H. Sarma.

Evolving Drivers of Brazilian SARS-CoV-2 Transmission: A Spatiotemporally Disaggregated Time Series Analysis of Meteorology, Policy, and Human Mobility.

Brazil has been severely affected by the COVID-19 pandemic. Temperature and humidity have been purported as drivers of SARS-CoV-2 transmission, but no consensus has been reached in the literature regarding the relative roles of meteorology, governmental policy, and mobility on transmission in Brazil. We compiled data on meteorology, governmental policy, and mobility in Brazil's 26 states and one federal district from June 2020 to August 2021. Associations between these variables and the time-varying reproductive number (R t ) of SARS-CoV-2 were examined using generalized additive models fit to data from the entire 15-month period and several shorter, 3-month periods. Accumulated local effects and variable importance metrics were calculated to analyze the relationship between input variables and R t . We found that transmission is strongly influenced by unmeasured sources of between-state heterogeneity and the near-recent trajectory of the pandemic. Increased temperature generally was associated with decreased transmission and increased specific humidity with increased transmission. However, the impacts of meteorology, policy, and mobility on R t varied in direction, magnitude, and significance across our study period. This time variance could explain inconsistencies in the published literature to date. While meteorology weakly modulates SARS-CoV-2 transmission, daily or seasonal weather variations alone will not stave off future surges in COVID-19 cases in Brazil. Investigating how the roles of environmental factors and disease control interventions may vary with time should be a deliberate consideration of future research on the drivers of SARS-CoV-2 transmission.

Phenylpyrazolone-1,2,3-triazole Hybrids as Potent Antiviral Agents with Promising SARS-CoV-2 Main Protease Inhibition Potential.

COVID-19 infection is now considered one of the leading causes of human death. As an attempt towards the discovery of novel medications for the COVID-19 pandemic, nineteen novel compounds containing 1,2,3-triazole side chains linked to phenylpyrazolone scaffold and terminal lipophilic aryl parts with prominent substituent functionalities were designed and synthesized via a click reaction based on our previous work. The novel compounds were assessed using an in vitro effect on the growth of SARS-CoV-2 virus-infested Vero cells with different compound concentrations: 1 and 10 µM. The data revealed that most of these derivatives showed potent cellular anti-COVID-19 activity and inhibited viral replication by more than 50% with no or weak cytotoxic effect on harboring cells. In addition, in vitro assay employing the SARS-CoV-2-Main protease inhibition assay was done to test the inhibitors' ability to block the common primary protease of the SARS-CoV-2 virus as a mode of action. The obtained results show that the one non-linker analog 6h and two amide-based linkers 6i and 6q were the most active compounds with IC50 values of 5.08, 3.16, and 7.55 µM, respectively, against the viral protease in comparison to data of the selective antiviral agent GC-376. Molecular modeling studies were done for compound placement within the binding pocket of protease which reveal conserved residues hydrogen bonding and non-hydrogen interactions of 6i analog fragments: triazole scaffold, aryl part, and linker. Moreover, the stability of compounds and their interactions with the target pocket were also studied and analyzed by molecular dynamic simulations. The physicochemical and toxicity profiles were predicted, and the results show that compounds behave as an antiviral activity with low or no cellular or organ toxicity. All research results point to the potential usage of new chemotype potent derivatives as promising leads to be explored in vivo that might open the door to rational drug development of SARS-CoV-2 Main protease potent medicines.

Spatiotemporal variation in risk of Shigella infection in childhood: a global risk mapping and prediction model using individual participant data.

BACKGROUND: Diarrhoeal disease is a leading cause of childhood illness and death globally, and Shigella is a major aetiological contributor for which a vaccine might soon be available. The primary objective of this study was to model the spatiotemporal variation in paediatric Shigella infection and map its predicted prevalence across low-income and middle-income countries (LMICs). METHODS: Individual participant data for Shigella positivity in stool samples were sourced from multiple LMIC-based studies of children aged 59 months or younger. Covariates included household-level and participant-level factors ascertained by study investigators and environmental and hydrometeorological variables extracted from various data products at georeferenced child locations. Multivariate models were fitted and prevalence predictions obtained by syndrome and age stratum. FINDINGS: 20 studies from 23 countries (including locations in Central America and South America, sub-Saharan Africa, and south and southeast Asia) contributed 66 563 sample results. Age, symptom status, and study design contributed most to model performance followed by temperature, wind speed, relative humidity, and soil moisture. Probability of Shigella infection exceeded 20% when both precipitation and soil moisture were above average and had a 43% peak in uncomplicated diarrhoea cases at 33°C temperatures, above which it decreased. Compared with unimproved sanitation, improved sanitation decreased the odds of Shigella infection by 19% (odds ratio [OR]=0·81 [95% CI 0·76-0·86]) and open defecation decreased them by 18% (OR=0·82 [0·76-0·88]). INTERPRETATION: The distribution of Shigella is more sensitive to climatological factors, such as temperature, than previously recognised. Conditions in much of sub-Saharan Africa are particularly propitious for Shigella transmission, although hotspots also occur in South America and Central America, the Ganges-Brahmaputra Delta, and the island of New Guinea. These findings can inform prioritisation of populations for future vaccine trials and campaigns. FUNDING: NASA, National Institutes of Health-The National Institute of Allergy and Infectious Diseases, and Bill & Melinda Gates Foundation.

Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach.

BACKGROUND: Since the US reported its first COVID-19 case on January 21, 2020, the science community has been applying various techniques to forecast incident cases and deaths. To date, providing an accurate and robust forecast at a high spatial resolution has proved challenging, even in the short term. METHOD: Here we present a novel multi-stage deep learning model to forecast the number of COVID-19 cases and deaths for each US state at a weekly level for a forecast horizon of 1-4 weeks. The model is heavily data driven, and relies on epidemiological, mobility, survey, climate, demographic, and SARS-CoV-2 variant frequencies data. We implement a rigorous and robust evaluation of our model-specifically we report on weekly performance over a one-year period based on multiple error metrics, and explicitly assess how our model performance varies over space, chronological time, and different outbreak phases. FINDINGS: The proposed model is shown to consistently outperform the CDC ensemble model for all evaluation metrics in multiple spatiotemporal settings, especially for the longer-term (3 and 4 weeks ahead) forecast horizon. Our case study also highlights the potential value of variant frequencies data for use in short-term forecasting to identify forthcoming surges driven by new variants. INTERPRETATION: Based on our findings, the proposed forecasting framework improves upon the available state-of-the-art forecasting tools currently used to support public health decision making with respect to COVID-19 risk. FUNDING: This work was funded the NSF Rapid Response Research (RAPID) grant Award ID 2108526 and the CDC Contract #75D30120C09570.

The anticancer and EGFR-TK/CDK-9 dual inhibitory potentials of new synthetic pyranopyrazole and pyrazolone derivatives: X-ray crystallography, in vitro, and in silico mechanistic investigations.

Treatment options for the management of breast cancer are still inadequate. This inadequacy is attributed to the lack of effective targeted medications, often resulting in the recurrence of metastatic disorders. Cumulative evidence suggests that epidermal growth factor receptor (EGFR-TK) and cyclin-dependent kinases-9 (CDK-9) overexpression correlates with worse overall survival in breast cancer patients. Pyranopyrazole and pyrazolone are privileged options for the development of anticancer agents. Inspired by this proven scientific fact, we report here the synthesis of two new series of suggested anticancer molecules incorporating both heterocycles together with their characterization by IR, 1H NMR, 13C NMR, 13C NMR-DEPT, and X-ray diffraction methods. An attempt to get the pyranopyrazole-gold complexes was conducted but unexpectedly yielded benzylidene-2,4-dihydro-3H-pyrazol-3-one instead. This unexpected result was confirmed by X-ray crystallographic analysis. All newly synthesized compounds were assessed for their anti-proliferative activity against two different human breast cancer cells, and the obtained results were compared with the reference drug Staurosporine. The target compounds revealed variable cytotoxicity with IC50 at a low micromolar range with superior selectivity indices. Target enzyme EGFR-TK and CDK-9 assays showed that compounds 22 and 23 effectively inhibited both biological targets with IC50 values of 0.143 and 0.121 µM, respectively. Molecular docking experiments and molecular dynamics simulation were also conducted to further rationalize the in vitro obtained results.Communicated by Ramaswamy H. Sarma.

Exploring the dual effect of novel 1,4-diarylpyranopyrazoles as antiviral and anti-inflammatory for the management of SARS-CoV-2 and associated inflammatory symptoms.

COVID-19 and associated substantial inflammations continue to threaten humankind triggering death worldwide. So, the development of new effective antiviral and anti-inflammatory medications is a major scientific goal. Pyranopyrazoles have occupied a crucial position in medicinal chemistry because of their biological importance. Here, we report the design and synthesis of a series of sixteen pyranopyrazole derivatives substituted with two aryl groups at N-1 and C-4. The designed compounds are suggested to show dual activity to combat the emerging Coronaviruses and associated substantial inflammations. All compounds were evaluated for their in vitro antiviral activity and cytotoxicity against SARS-CoV infected Vero cells. As well, the in vitro assay of all derivatives against the SARS-CoV Mpro target was performed. Results revealed the potential of three pyranopyrazoles (22, 27, and 31) to potently inhibit the viral main protease with IC50 values of 2.01, 1.83, and 4.60 µM respectively compared with 12.85 and 82.17 µM for GC-376 and lopinavir. Additionally, in vivo anti-inflammatory testing for the most active compound 27 proved its ability to reduce levels of two cytokines (TNF-α and IL-6). Molecular docking and dynamics simulation revealed consistent results with the in vitro enzymatic assay and indicated the stability of the putative complex of 27 with SARS-CoV-2 Mpro. The assessment of metabolic stability and physicochemical properties of 27 have also been conducted. This investigation identified a set of metabolically stable pyranopyrazoles as effective anti-SARS-CoV-2 Mpro and suppressors of host cell cytokine release. We believe that the new compounds deserve further chemical optimization and evaluation for COVID-19 treatment.

Synthesis, structural characterization, DFT calculations, molecular docking, and molecular dynamics simulations of a novel ferrocene derivative to unravel its potential antitumor activity.

In this article, we describe a set of subsequent five-steps chemical reactions to synthesize a ferrocene derivative named 1-(5-(diphenylphosphaneyl)cyclopenta-1,3-dien-1-yl)ethyl)imino)-1,3-dihydroisobenzofuran-5-yl)methanol (compound 10). Structural characterization of 10 and its intermediate products was also performed and reported to attest to their formation. A molecular docking study was performed to propose the novel synthesized ferrocene derivative (10) as a potential antitumor candidate targeting the mitogen-activated protein (MAP) kinases interacting kinase (Mnk) 1. The computed docking score of (10) at -9.50 kcal/mol compared to the native anticancer staurosporine at -8.72 kcal/mol postulated a promising anticancer activity. Also, molecular dynamics (MD) simulations were carried out for 500 ns followed by MM-GBSA-binding free energy calculations for both the docked complexes of ferrocene and staurosporine to give more deep insights into their dynamic behavior in physiological conditions. Furthermore, DFT calculations were performed to unravel some of the physiochemical characteristics of the ferrocene derivative (10). The quantum mechanics calculations shed the light on some of the structural and electrochemical configurations of (10) which would open the horizon for further investigation. HighlightsThe synthesis of a ferrocene derivative named 1-(5-(diphenylphosphaneyl)cyclopenta-1,3-dien-1-yl)ethyl)imino)-1,3-dihydroisobenzofuran-5-yl)methanol (compound 10) was described.Structural characterizations of ferrocene derivative (10) and its intermediate products were also performed.DFT calculations, molecular docking, molecular dynamics, and MM-GBSA calculations were carried out.Computational studies revealed the antitumor potential of ferrocene derivative (10) through targeting and inhibiting mitogen-activated protein (MAP) kinases interacting kinase (Mnk) 1.Communicated by Ramaswamy H. Sarma.

Effects of hydrometeorological and other factors on SARS-CoV-2 reproduction number in three contiguous countries of tropical Andean South America: a spatiotemporally disaggregated time series analysis.

Background: The COVID-19 pandemic has caused societal disruption globally, and South America has been hit harder than other lower-income regions. This study modeled the effects of six weather variables on district-level SARS-CoV-2 reproduction numbers (Rt ) in three contiguous countries of tropical Andean South America (Colombia, Ecuador, and Peru), adjusting for environmental, policy, healthcare infrastructural and other factors. Methods: Daily time-series data on SARS-CoV-2 infections were sourced from the health authorities of the three countries at the smallest available administrative level. Rt values were calculated and merged by date and unit ID with variables from a unified COVID-19 dataset and other publicly available sources for May-December, 2020. Generalized additive models were fitted. Findings: Relative humidity and solar radiation were inversely associated with SARS-CoV-2 Rt . Days with radiation above 1000 kJ/m2 saw a 1.3% reduction in Rt , and those with humidity above 50% recorded a 0.9% reduction in Rt . Transmission was highest in densely populated districts, and lowest in districts with poor healthcare access and on days with lowest population mobility. Wind speed, temperature, region, aggregate government policy response, and population age structure had little impact. The fully adjusted model explained 4.3% of Rt variance. Interpretation: Dry atmospheric conditions of low humidity increase district-level SARS-CoV-2 reproduction numbers, while higher levels of solar radiation decrease district-level SARS-CoV-2 reproduction numbers - effects that are comparable in magnitude to population factors like lockdown compliance. Weather monitoring could be incorporated into disease surveillance and early warning systems in conjunction with more established risk indicators and surveillance measures. Funding: NASA's Group on Earth Observations Work Programme (16-GEO16-0047).

In vitro and computational investigations of novel synthetic carboxamide-linked pyridopyrrolopyrimidines with potent activity as SARS-CoV-2-MPro inhibitors.

An essential target for COVID-19 is the main protease of SARS-CoV-2 (Mpro). With the objective of targeting this receptor, a novel set of pyrido[1,2-a]pyrrolo[2,3-d]pyrimidines with terminal carboxamide fragments was designed, synthesized, and considered as an initial motif for the creation of effective pan-coronavirus inhibitors. Accordingly, nine derivatives (21-29) have been introduced for in vitro assay to evaluate their antiviral activity and cytotoxicity effect against COVID-19 virus using Vero cells. The obtained data revealed that the majority of these derivatives showed potent cellular anti-COVID-19 activity and prevent viral growth by more than 90% at two different concentrations with weak or even no detectable cytotoxic effect on Vero cells. Extensive molecular docking simulations highlighted proper non-covalent interaction of new compounds within the binding pocket of Mpro as a potential target for their antiviral activity. In vitro assay for all the synthesized derivatives against the viral Mpro target indicated that compounds 25 and 29 have promising inhibitory activity with IC50 values at low micromolar concentrations. The molecular dynamic simulation results predicted the stability of compound 29 in the binding cavity of SARS-CoV-2 Mpro and hence supported the high inhibitory activity shown by the In vitro assay. These results suggested that compounds 25 and 29 merit further investigations as promising drug candidates for the management of SARS-CoV-2.

A Deep Learning Approach to Forecast Short-Term COVID-19 Cases and Deaths in the US

Since the US reported its first COVID-19 case on January 21, 2020, the science community has been applying various techniques to forecast incident cases and deaths. To date, providing an accurate and robust forecast at a high spatial resolution has proved challenging, even in the short term. Here we present a novel multi-stage deep learning model to forecast the number of COVID-19 cases and deaths for each US state at a weekly level for a forecast horizon of 1 to 4 weeks. The model is heavily data driven, and relies on epidemiological, mobility, survey, climate, and demographic. We further present results from a case study that incorporates SARS-CoV-2 genomic data (i.e. variant cases) to demonstrate the value of incorporating variant cases data into model forecast tools. We implement a rigorous and robust evaluation of our model - specifically we report on weekly performance over a one-year period based on multiple error metrics, and explicitly assess how our model performance varies over space, chronological time, and different outbreak phases. The proposed model is shown to consistently outperform the CDC ensemble model for all evaluation metrics in multiple spatiotemporal settings, especially for the longer-term (3 and 4 weeks ahead) forecast horizon. Our case study also highlights the potential value of virus genomic data for use in short-term forecasting to identify forthcoming surges driven by new variants. Based on our findings, the proposed forecasting framework improves upon the available forecasting tools currently used to support public health decision making with respect to COVID-19 risk. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSA systematic review of the COVID-19 forecasting and the EPIFORGE 2020 guidelines reveal the lack of consistency, reproducibility, comparability, and quality in the current COVID-19 forecasting literature. To provide an updated survey of the literature, we carried out our literature search on Google Scholar, PubMed, and medRxi, using the terms "Covid-19," "SARS-CoV-2," "coronavirus," "short-term," "forecasting," and "genomic surveillance." Although the literature includes a significant number of papers, it remains lacking with respect to rigorous model evaluation, interpretability and translation. Furthermore, while SARS-CoV-2 genomic surveillance is emerging as a vital necessity to fight COVID-19 (i.e. wastewater sampling and airport screening), to our knowledge, no published forecasting model has illustrated the value of virus genomic data for informing future outbreaks. Added value of this studyWe propose a multi-stage deep learning model to forecast COVID-19 cases and deaths with a horizon window of four weeks. The data driven model relies on a comprehensive set of input features, including epidemiological, mobility, behavioral survey, climate, and demographic. We present a robust evaluation framework to systematically assess the model performance over a one-year time span, and using multiple error metrics. This rigorous evaluation framework reveals how the predictive accuracy varies over chronological time, space, and outbreak phase. Further, a comparative analysis against the CDC ensemble, the best performing model in the COVID-19 ForecastHub, shows the model to consistently outperform the CDC ensemble for all evaluation metrics in multiple spatiotemporal settings, especially for the longer forecasting windows. We also conduct a feature analysis, and show that the role of explanatory features changes over time. Specifically, we note a changing role of climate variables on model performance in the latter half of the study period. Lastly, we present a case study that reveals how incorporating SARS-CoV-2 genomic surveillance data may improve forecasting accuracy compared to a model without variant cases data. Implications of all the available evidenceResults from the robust evaluation analysis highlight extreme model performance variability over time and space, and suggest that forecasting models should be accompanied with specifications on the conditions under which they perform best (and worst), in order to maximize their value and utility in aiding public health decision making. The feature analysis reveals the complex and changing role of factors contributing to COVID-19 transmission over time, and suggests a possible seasonality effect of climate on COVID-19 spread, but only after August 2021. Finally, the case study highlights the added value of using genomic surveillance data in short-term epidemiological forecasting models, especially during the early stage of new variant introductions.