Wetting Behavior of Inkjet-Printed Electronic Inks on Patterned Substrates.

In inkjet printing technology, one important factor influencing the printing quality and reliability of printed films is the interaction of the jetted ink with the substrate surface. This short-range interaction determines the wettability and the adhesion of the ink to the solid surface and is hence responsible for the final shape of the deposited ink. Here, we investigate wetting morphologies of inkjet-printed inks on patterned substrates by carefully designed experimental test structures and simulations. The contact angles, the surface properties, and drop shapes, as well as their influence on the device variability, are experimentally and theoretically analyzed. For the simulations, we employ the phase-field method, which is based on the free energy minimization of the two-phase system with the given wetting boundary conditions. Through a systematic investigation of printed drops on patterned substrates consisting of hydrophilic and hydrophobic areas, we report that the printed morphology is related not only to the designed layout and the drop volume but also to the printing strategy and the wettability. Furthermore, we show how one can modify the intrinsic wettability of the patterned substrates to enhance the printing quality and reliability. Based on the present findings, we cast light on the improvement of the fabrication quality of thin film transistors.

Synthesis and Antiallodynic Activity of Cannabidiol Analogue on Peripheral Neuropathy in Mice.

Cannabidiol (CBD) is a substance that exerts several therapeutic actions, including analgesia. CBD is generally administered orally, but its poor water solubility and metabolism impair its bioavailability. Thus, the development of molecules with better pharmacokinetic profile from cannabidiol becomes an interesting strategy for the design of novel analgesic drugs for the relief of painful conditions that are difficult to manage clinically, such as neuropathic pain. In the present study, an unprecedented analogue of CBD (1) was synthesized and some of its physicochemical properties were evaluated in silico as well as its stability in an acid medium. Additionally, its effect was investigated in a model of neuropathic pain induced by the chemotherapy drug paclitaxel in mice, in comparison with cannabidiol itself. Cannabidiol (20 mg/kg), pregabalin (30 mg/kg), or analogue 1 (5, 10, and 20 mg/kg), administered on the 14th day after the first administration of paclitaxel, attenuated the mechanical allodynia of the sensitized animals. The antinociceptive activity of analogue 1 was attenuated by previous administration of a cannabinoid CB1 receptor antagonist, AM 251, which indicates that its mechanism of action is related to the activation of CB1 receptors. In conclusion, the CBD analogue 1 developed in this study shows great potential to be used in the treatment of neuropathic pain.

Discovery of Lead 2-Thiazolylhydrazones with Broad-Spectrum and Potent Antifungal Activity.

Opportunistic fungal infections represent a global health problem, mainly for immunocompromised individuals. New therapeutical options are needed since several fungal strains show resistance to clinically available antifungal agents. 2-Thiazolylhydrazones are well-known as potent compounds against Candida and Cryptococcus species. A scaffold-focused drug design using machine-learning models was established to optimize the 2-thiazolylhydrazone skeleton and obtain novel compounds with higher potency, better solubility in water, and enhanced absorption. Twenty-nine novel compounds were obtained and most showed low micromolar MIC values against different species of Candida and Cryptococcus spp., including Candida auris, an emerging multidrug-resistant yeast. Among the synthesized compounds, 2-thiazolylhydrazone 28 (MIC value ranging from 0.8 to 52.17 µM) was selected for further studies: cytotoxicity evaluation, permeability study in Caco-2 cell model, and in vivo efficacy against Cryptococcus neoformans in an invertebrate infection model. All results obtained indicate the great potential of 28 as a novel antifungal agent.

Molecular targets for Chagas disease: validation, challenges and lead compounds for widely exploited targets.

INTRODUCTION: Chagas disease (CD) imposes social and economic burdens, yet the available treatments have limited efficacy in the disease's chronic phase and cause serious adverse effects. To address this challenge, target-based approaches are a possible strategy to develop new, safe, and active treatments for both phases of the disease. AREAS COVERED: This review delves into target-based approaches applied to CD drug discovery, emphasizing the studies from the last five years. We highlight the proteins cruzain (CZ), trypanothione reductase (TR), sterol 14 α-demethylase (CPY51), iron superoxide dismutase (Fe-SOD), proteasome, cytochrome b (Cytb), and cleavage and polyadenylation specificity factor 3 (CPSF3), chosen based on their biological and chemical validation as drug targets. For each, we discuss its biological relevance and validation as a target, currently related challenges, and the status of the most promising inhibitors. EXPERT OPINION: Target-based approaches toward developing potential CD therapeutics have yielded promising leads in recent years. We expect a significant advance in this field in the next decade, fueled by the new options for Trypanosoma cruzi genetic manipulation that arose in the past decade, combined with recent advances in computational chemistry and chemical biology.

Synthesis of cannabidiol-based compounds as ACE2 inhibitors with potential application in the treatment of COVID-19.

Cannabis is a general name for plants of the genus Cannabis. Used as fiber, medicine, drug, for religious, therapeutic, and hedonistic purposes along the millenia, it is mostly known for its psychoactive properties. One of its major constituents, cannabidiol (CBD), a non-psychoactive substance, among many other biological activities, has shown potential as an anti-SARS-CoV-2 drug. In this work, three derivatives and an analogue of CBD were synthesized, and cell viability and antiviral activities were evaluated. None of the compounds showed cytotoxicity up to a maximum concentration of 100 µM and, in contrast, displayed a significant antiviral activity, superior to remdesivir and nafamostat mesylate, with IC50 values ranging from 9.4 to 1.9 µM. In order to search for a possible molecular target, the inhibitory activity of the compounds against ACE2 was investigated, with expressive results (IC50 ranging from 3.96 µM to 0.01 µM).

Structure-based discovery of thiosemicarbazones as SARS-CoV-2 main protease inhibitors.

Aim: Discovery of novel SARS-CoV-2 main protease (Mpro) inhibitors using a structure-based drug discovery strategy. Materials & methods: Virtual screening employing covalent and noncovalent docking was performed to discover Mpro inhibitors, which were subsequently evaluated in biochemical and cellular assays. Results: 91 virtual hits were selected for biochemical assays, and four were confirmed as reversible inhibitors of SARS CoV-2 Mpro with IC50 values of 0.4-3 µM. They were also shown to inhibit SARS-CoV-1 Mpro and human cathepsin L. Molecular dynamics simulations indicated the stability of the Mpro inhibitor complexes and the interaction of ligands at the subsites. Conclusion: This approach led to the discovery of novel thiosemicarbazones as potent SARS-CoV-2 Mpro inhibitors.

Laser printed microelectronics.

Printed organic and inorganic electronics continue to be of large interest for sensors, bioelectronics, and security applications. Many printing techniques have been investigated, albeit often with typical minimum feature sizes in the tens of micrometer range and requiring post-processing procedures at elevated temperatures to enhance the performance of functional materials. Herein, we introduce laser printing with three different inks, for the semiconductor ZnO and the metals Pt and Ag, as a facile process for fabricating printed functional electronic devices with minimum feature sizes below 1 µm. The ZnO printing is based on laser-induced hydrothermal synthesis. Importantly, no sintering of any sort needs to be performed after laser printing for any of the three materials. To demonstrate the versatility of our approach, we show functional diodes, memristors, and a physically unclonable function based on a 6 × 6 memristor crossbar architecture. In addition, we realize functional transistors by combining laser printing and inkjet printing.

The molecular signaling of exercise and obesity in the microbiota-gut-brain axis.

Obesity is one of the major pandemics of the 21st century. Due to its multifactorial etiology, its treatment requires several actions, including dietary intervention and physical exercise. Excessive fat accumulation leads to several health problems involving alteration in the gut-microbiota-brain axis. This axis is characterized by multiple biological systems generating a network that allows bidirectional communication between intestinal bacteria and brain. This mutual communication maintains the homeostasis of the gastrointestinal, central nervous and microbial systems of animals. Moreover, this axis involves inflammatory, neural, and endocrine mechanisms, contributes to obesity pathogenesis. The axis also acts in appetite and satiety control and synthesizing hormones that participate in gastrointestinal functions. Exercise is a nonpharmacologic agent commonly used to prevent and treat obesity and other chronic degenerative diseases. Besides increasing energy expenditure, exercise induces the synthesis and liberation of several muscle-derived myokines and neuroendocrine peptides such as neuropeptide Y, peptide YY, ghrelin, and leptin, which act directly on the gut-microbiota-brain axis. Thus, exercise may serve as a rebalancing agent of the gut-microbiota-brain axis under the stimulus of chronic low-grade inflammation induced by obesity. So far, there is little evidence of modification of the gut-brain axis as a whole, and this narrative review aims to address the molecular pathways through which exercise may act in the context of disorders of the gut-brain axis due to obesity.

Inferior Alveolar Nerve Lateralization Surgery for Implant Installation in Atrophic Posterior Mandible With Accessory Mental Foramen: A Challenge for the Usual Technique.

ABSTRACT: Implantology allows edentulous patients to smile and chew with confidence. However, the atrophy at posterior region of the mandible is still a challenge due the presence of the inferior alveolar nerve (iAN). The options of restoration with oral implants in this area with great atrophies are few and hazardous. The possibilities are: bone grafting, short implants, which are not always possible. So, the solution falls on the techniques of inferior alveolar nerve lateralization (IANL) or transposition. The knowledge of the anatomy and path of the IAN is decisive in this type of surgery. But anatomical variations may occur. Like the presence of an accessory mental foramen. This clinical study will present a relatively rare case of the occurrence of an accessory mental foramen that obliged to change the technique of iAN lateralization to contour this anatomical variance and install oral implants, maintaining the integrity of the iAN bundle.

Severe COVID-19 Shares a Common Neutrophil Activation Signature with Other Acute Inflammatory States.

Severe COVID-19 patients present a clinical and laboratory overlap with other hyperinflammatory conditions such as hemophagocytic lymphohistiocytosis (HLH). However, the underlying mechanisms of these conditions remain to be explored. Here, we investigated the transcriptome of 1596 individuals, including patients with COVID-19 in comparison to healthy controls, other acute inflammatory states (HLH, multisystem inflammatory syndrome in children [MIS-C], Kawasaki disease [KD]), and different respiratory infections (seasonal coronavirus, influenza, bacterial pneumonia). We observed that COVID-19 and HLH share immunological pathways (cytokine/chemokine signaling and neutrophil-mediated immune responses), including gene signatures that stratify COVID-19 patients admitted to the intensive care unit (ICU) and COVID-19_nonICU patients. Of note, among the common differentially expressed genes (DEG), there is a cluster of neutrophil-associated genes that reflects a generalized hyperinflammatory state since it is also dysregulated in patients with KD and bacterial pneumonia. These genes are dysregulated at the protein level across several COVID-19 studies and form an interconnected network with differentially expressed plasma proteins that point to neutrophil hyperactivation in COVID-19 patients admitted to the intensive care unit. scRNAseq analysis indicated that these genes are specifically upregulated across different leukocyte populations, including lymphocyte subsets and immature neutrophils. Artificial intelligence modeling confirmed the strong association of these genes with COVID-19 severity. Thus, our work indicates putative therapeutic pathways for intervention.

The network interplay of interferon and Toll-like receptor signaling pathways in the anti-Candida immune response.

Fungal infections represent a major global health problem affecting over a billion people that kills more than 1.5 million annually. In this study, we employed an integrative approach to reveal the landscape of the human immune responses to Candida spp. through meta-analysis of microarray, bulk, and single-cell RNA sequencing (scRNA-seq) data for the blood transcriptome. We identified across these different studies a consistent interconnected network interplay of signaling molecules involved in both Toll-like receptor (TLR) and interferon (IFN) signaling cascades that is activated in response to different Candida species (C. albicans, C. auris, C. glabrata, C. parapsilosis, and C. tropicalis). Among these molecules are several types I IFN, indicating an overlap with antiviral immune responses. scRNA-seq data confirmed that genes commonly identified by the three transcriptomic methods show cell type-specific expression patterns in various innate and adaptive immune cells. These findings shed new light on the anti-Candida immune response, providing putative molecular pathways for therapeutic intervention.

Diagnostic accuracy of handheld cardiac ultrasound device for assessment of left ventricular structure and function: systematic review and meta-analysis.

OBJECTIVE: Handheld ultrasound devices (HUD) has diagnostic value in the assessment of patients with suspected left ventricular (LV) dysfunction. This meta-analysis evaluates the diagnostic ability of HUD compared with transthoracic echocardiography (TTE) and assesses the importance of operator experience. METHODS: MEDLINE and EMBASE databases were searched in October 2020. Diagnostic studies using HUD and TTE imaging to determine LV dysfunction were included. Pooled sensitivities and specificities, and summary receiver operating characteristic curves were used to determine the diagnostic ability of HUD and evaluate the impact of operator experience on test accuracy. RESULTS: Thirty-three studies with 6062 participants were included in the meta-analysis. Experienced operators could predict reduced LV ejection fraction (LVEF), wall motion abnormality (WMA), LV dilatation and LV hypertrophy with pooled sensitivities of 88%, 85%, 89% and 85%, respectively, and pooled specificities of 96%, 95%, 98% and 91%, respectively. Non-experienced operators are able to detect cardiac abnormalities with reasonable sensitivity and specificity. There was a significant difference in the diagnostic accuracy between experienced and inexperienced users in LV dilatation, LVEF (moderate/severe) and WMA. The diagnostic OR for LVEF (moderate/severe), LV dilatation and WMA in an experienced hand was 276 (95% CI 58 to 1320), 225 (95% CI 87 to 578) and 90 (95% CI 31 to 265), respectively, compared with 41 (95% CI 18 to 94), 45 (95% CI 16 to 123) and 28 (95% CI 20 to 41), respectively, for inexperienced users. CONCLUSION: This meta-analysis is the first to establish HUD as a powerful modality for predicting LV size and function. Experienced operators are able to accurately diagnose cardiac disease using HUD. A cautious, supervised approach should be implemented when imaging is performed by inexperienced users. This study provides a strong rationale for considering HUD as an auxiliary tool to physical examination in secondary care, to aid clinical decision making when considering referral for TTE. TRIAL REGISTRATION NUMBER: CRD42020182429.

De Novo Design of Molecules with Low Hole Reorganization Energy Based on a Quarter-Million Molecule DFT Screen.

Materials exhibiting higher mobilities than conventional organic semiconducting materials such as fullerenes and fused thiophenes are in high demand for applications in printed electronics. To discover new molecules in the heteroacene family that might show improved hole mobility, three de novo design methods were applied. Machine learning (ML) models were generated based on previously calculated hole reorganization energies of a quarter million examples of heteroacenes, where the energies were calculated by applying density functional theory (DFT) and a massive cloud computing environment. The three generative methods applied were (1) the continuous space method, where molecular structures are converted into continuous variables by applying the variational autoencoder/decoder technique; (2) the method based on reinforcement learning of SMILES strings (the REINVENT method); and (3) the junction tree variational autoencoder method that directly generates molecular graphs. Among the three methods, the second and third methods succeeded in obtaining chemical structures whose DFT-calculated hole reorganization energy was lower than the lowest energy in the training dataset. This suggests that an extrapolative materials design protocol can be developed by applying generative modeling to a quantitative structure-property relationship (QSPR) utility function.

Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting.

Background: Periodically, humanity is often faced with new and emerging viruses that can be a significant global threat. It has already been over a century post-the Spanish Flu pandemic, and we are witnessing a new type of coronavirus, the SARS-CoV-2, which is responsible for Covid-19. It emerged from the city of Wuhan (China) in December 2019, and within a few months, the virus propagated itself globally now resulting more than 50 million cases with over 1 million deaths. The high infection rates coupled with dynamic population movement demands for tools, especially within a Brazilian context, that will support health managers to develop policies for controlling and combating the new virus. Methods: In this work, we propose a tool for real-time spatio-temporal analysis using a machine learning approach. The COVID-SGIS system brings together routinely collected health data on Covid-19 distributed across public health systems in Brazil, as well as taking to under consideration the geographic and time-dependent features of Covid-19 so as to make spatio-temporal predictions. The data are sub-divided by federative unit and municipality. In our case study, we made spatio-temporal predictions of the distribution of cases and deaths in Brazil and in each federative unit. Four regression methods were investigated: linear regression, support vector machines (polynomial kernels and RBF), multilayer perceptrons, and random forests. We use the percentage RMSE and the correlation coefficient as quality metrics. Results: For qualitative evaluation, we made spatio-temporal predictions for the period from 25 to 27 May 2020. Considering qualitatively and quantitatively the case of the State of Pernambuco and Brazil as a whole, linear regression presented the best prediction results (thematic maps with good data distribution, correlation coefficient >0.99 and RMSE (%) <4% for Pernambuco and around 5% for Brazil) with low training time: [0.00; 0.04 ms], CI 95%. Conclusion: Spatio-temporal analysis provided a broader assessment of those in the regions where the accumulated confirmed cases of Covid-19 were concentrated. It was possible to differentiate in the thematic maps the regions with the highest concentration of cases from the regions with low concentration and regions in the transition range. This approach is fundamental to support health managers and epidemiologists to elaborate policies and plans to control the Covid-19 pandemics.

Is There an Exercise-Intensity Threshold Capable of Avoiding the Leaky Gut?

Endurance-sport athletes have a high incidence of gastrointestinal disorders, compromising performance and impacting overall health status. An increase in several proinflammatory cytokines and proteins (LPS, I-FABP, IL-6, IL-1ß, TNF-α, IFN-γ, C-reactive protein) has been observed in ultramarathoners and triathlon athletes. One of the most common effects of this type of physical activity is the increase in intestinal permeability, known as leaky gut. The intestinal mucosa's degradation can be identified and analyzed by a series of molecular biomarkers, including the lactulose/rhamnose ratio, occludin and claudin (tight junctions), lipopolysaccharides, and I-FABP. Identifying the molecular mechanisms involved in the induction of leaky gut by physical exercise can assist in the determination of safe exercise thresholds for the preservation of the gastrointestinal tract. It was recently shown that 60 min of vigorous endurance training at 70% of the maximum work capacity led to the characteristic responses of leaky gut. It is believed that other factors may contribute to this effect, such as altitude, environmental temperature, fluid restriction, age and trainability. On the other hand, moderate physical training and dietary interventions such as probiotics and prebiotics can improve intestinal health and gut microbiota composition. This review seeks to discuss the molecular mechanisms involved in the intestinal mucosa's adaptation and response to exercise and discuss the role of the intestinal microbiota in mitigating these effects.

Electrochemical evidence of nitrate release from the nitrooxy compound 4-((nitrooxy) methyl)-3-nitrobenzoic acid and its antinociceptive and anti-inflammatory activities in mice.

Considering the many biological activities of nitric oxide (NO), some lines of research focused on the modulation of these activities through the provision of this mediator by designing and synthesizing compounds coupled with an NO donor group. Thus, the objectives of the present study were to carry out an electrochemical investigation of the nitrooxy compound 4-((nitrooxy) methyl)-3-nitrobenzoic acid (1) and evaluate its activities and putative mechanisms in experimental models of pain and inflammation. Voltammetric studies performed in aprotic medium (mimetic of membranes) showed important electrochemical reduction mechanisms: nitroaromatic reduction, self-protonation, and finally reductive elimination, which leads to nitrate release. Systemic administration of the nitrooxy compound (1) inhibited the nociceptive response induced by heat and the tactile hypersensitivity and paw edema induced by carrageenan in mice. The activities in the models of inflammatory pain and edema were associated with reduced neutrophil recruitment and production of inflammatory cytokines, such as interleukin (IL)-1ß, IL-6, tumor necrosis factor-α and CXCL-1, and increased production of IL-10. Concluding, electrochemical analysis revealed unequivocally that electron transfer at the nitro group of the nitrooxy compound (1) results in the cleavage of the organic nitrate, potentially resulting in the generation of NO. This electrochemical mechanism may be compared to a biochemical electron-transfer mediated nitrate release that, by appropriate in vivo bioreduction (enzymatic or not) would lead to NO production. Compound (1) exhibits activities in models of inflammatory pain and edema that may be due to reduced recruitment of neutrophils and production of inflammatory cytokines and increased production of IL-10. These results reinforce the interest in the investigation of NO donor compounds as candidates for analgesic and anti-inflammatory drugs.

COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19.

Background: The global burden of the new coronavirus SARS-CoV-2 is increasing at an unprecedented rate. The current spread of Covid-19 in Brazil is problematic causing a huge public health burden to its population and national health-care service. To evaluate strategies for alleviating such problems, it is necessary to forecast the number of cases and deaths in order to aid the stakeholders in the process of making decisions against the disease. We propose a novel system for real-time forecast of the cumulative cases of Covid-19 in Brazil. Methods: We developed the novel COVID-SGIS application for the real-time surveillance, forecast and spatial visualization of Covid-19 for Brazil. This system captures routinely reported Covid-19 information from 27 federative units from the Brazil.io database. It utilizes all Covid-19 confirmed case data that have been notified through the National Notification System, from March to May 2020. Time series ARIMA models were integrated for the forecast of cumulative number of Covid-19 cases and deaths. These include 6-days forecasts as graphical outputs for each federative unit in Brazil, separately, with its corresponding 95% CI for statistical significance. In addition, a worst and best scenarios are presented. Results: The following federative units (out of 27) were flagged by our ARIMA models showing statistically significant increasing temporal patterns of Covid-19 cases during the specified day-to-day period: Bahia, Maranhão, Piauí, Rio Grande do Norte, Amapá, Rondônia, where their day-to-day forecasts were within the 95% CI limits. Equally, the same findings were observed for Espírito Santo, Minas Gerais, Paraná, and Santa Catarina. The overall percentage error between the forecasted values and the actual values varied between 2.56 and 6.50%. For the days when the forecasts fell outside the forecast interval, the percentage errors in relation to the worst case scenario were below 5%. Conclusion: The proposed method for dynamic forecasting may be used to guide social policies and plan direct interventions in a cost-effective, concise, and robust manner. This novel tools can play an important role for guiding the course of action against the Covid-19 pandemic for Brazil and country neighbors in South America.

Reduced Duration of Postchikungunya Musculoskeletal Pain in Rheumatological Patients Treated with Biologicals.

Chikungunya fever (CHIK) has caused important epidemic outbreaks in the Americas, with musculoskeletal involvement being the main manifestation, causing chronic symptoms in half of the affected patients. This study was performed to evaluate the clinical course of the infection in 168 patients with autoimmune inflammatory disease using biological disease-modifying antirheumatic drugs (bDMARDs), comparing this group with 56 household controls. Anti-CHIKV IgG serology was positive in 42 (25%) of the patients in the bDMARD group and in 15 (27%) of the controls (p=0.79). Of those with positive serology, 32 (76%) and 14 (93%) were symptomatic among subjects in the bDMARD and control groups, respectively (p=0.87). Persistence of musculoskeletal symptoms for more than three months occurred in 64% of the patients in the control group and only in 28% in the bDMARD group (p=0.021), maintaining a statistically significant difference only for users of anti-TNF. This study found that patients affected by chikungunya fever using bDMARDs did not present severe forms or complications in the acute phase of the disease, and patients using anti-TNF biologicals had a lower frequency of chronic joint symptoms than the household controls. This favorable outcome may be related to the cytokine blockade, with a reduction in the inflammatory response and joint damage.

Abdominal Palpation Does Not Modify the Number of Bowel Sounds in Healthy Volunteers and Gastrointestinal Outpatients.

BACKGROUND: The effect of abdominal palpation on bowel sounds is controversial. The authors developed an auscultation apparatus to count bowel sounds and determined whether abdominal palpation modifies the number of bowel sounds in healthy volunteers and gastrointestinal outpatients. METHODS: Four medical students developed an auscultation apparatus by attaching a Littmann stethoscope to an electret condenser microphone. The students examined 20 healthy volunteers and 20 gastrointestinal outpatients between March and June 2018. Abdominal auscultation lasting 4 minutes (1-minute each quadrant) was performed before and after abdominal palpation with registration of sound tracings. The software Audacity was used to count the bowel sounds. The effect of palpation on bowel sounds was analyzed using Generalized Estimating Equations. RESULTS: The volunteers were predominantly young (mean ± SD, 21 ± 2 years) and men (70%), whereas the outpatients were older (60 ± 11 years) and women (80%). The apparatus was able to generate sound tracings with good quality from all participants. In the comparison before/after palpation, the number of bowel sounds did not differ either in volunteers (mean ± SD, 12.6 ± 4.7 and 11.6 ± 3.5; P = 0.482) or in patients (15.6 ± 7.5 and 15.8 ± 7.9; P = 0.714). In the analysis of all participants, the difference before-after palpation was not statistically significant (mean ± SD, 14.1 ± 6.3 and 13.7 ± 6.4, respectively; P = 0.550; mean difference = 0.4; 95% CI -1.2 to 2.0) and did not depend on the group studied. CONCLUSIONS: Using an apparatus devised by medical students, the authors found that abdominal palpation did not modify the number of bowel sounds in healthy volunteers and gastrointestinal outpatients.

Combining Cloud-Based Free-Energy Calculations, Synthetically Aware Enumerations, and Goal-Directed Generative Machine Learning for Rapid Large-Scale Chemical Exploration and Optimization.

The hit identification process usually involves the profiling of millions to more recently billions of compounds either via traditional experimental high-throughput screens (HTS) or computational virtual high-throughput screens (vHTS). We have previously demonstrated that, by coupling reaction-based enumeration, active learning, and free energy calculations, a similarly large-scale exploration of chemical space can be extended to the hit-to-lead process. In this work, we augment that approach by coupling large scale enumeration and cloud-based free energy perturbation (FEP) profiling with goal-directed generative machine learning, which results in a higher enrichment of potent ideas compared to large scale enumeration alone, while simultaneously staying within the bounds of predefined drug-like property space. We can achieve this by building the molecular distribution for generative machine learning from the PathFinder rules-based enumeration and optimizing for a weighted sum QSAR-based multiparameter optimization function. We examine the utility of this combined approach by designing potent inhibitors of cyclin-dependent kinase 2 (CDK2) and demonstrate a coupled workflow that can (1) provide a 6.4-fold enrichment improvement in identifying <10 nM compounds over random selection and a 1.5-fold enrichment in identifying <10 nM compounds over our previous method, (2) rapidly explore relevant chemical space outside the bounds of commercial reagents, (3) use generative ML approaches to "learn" the SAR from large scale in silico enumerations and generate novel idea molecules for a flexible receptor site that are both potent and within relevant physicochemical space, and (4) produce over 3 000 000 idea molecules and run 1935 FEP simulations, identifying 69 ideas with a predicted IC50 < 10 nM and 358 ideas with a predicted IC50 < 100 nM. The reported data suggest combining both reaction-based and generative machine learning for ideation results in a higher enrichment of potent compounds over previously described approaches and has the potential to rapidly accelerate the discovery of novel chemical matter within a predefined potency and property space.