Reducing the vicissitudes of heterologous prochiral substrate catalysis by alcohol dehydrogenases through machine learning algorithms.

Alcohol dehydrogenases (ADHs) are popular catalysts for synthesizing chiral synthons a vital step for active pharmaceutical intermediate (API) production. They are grouped into three superfamilies namely, medium-chain (MDRs), short-chain dehydrogenase/reductases (SDRs), and iron-containing alcohol dehydrogenases. The former two are used extensively for producing various chiral synthons. Many studies screen multiple enzymes or engineer a specific enzyme for catalyzing a substrate of interest. These processes are resource-intensive and intricate. The current study attempts to decipher the ability to match different ADHs with their ideal substrates using machine learning algorithms. We explore the catalysis of 284 antibacterial ketone intermediates, against MDRs and SDRs to demonstrate a unique pattern of activity. To facilitate machine learning we curated a dataset comprising 33 features, encompassing 4 descriptors for each compound. Subsequently, an ensemble of machine learning techniques viz. Partial Least Squares (PLS) regression, k-Nearest Neighbors (kNN) regression, and Support Vector Machine (SVM) regression, was harnessed. Moreover, the assimilation of Principal Component Analysis (PCA) augmented precision and accuracy, thereby refining and demarcating diverse compound classes. As such, this classification is useful for discerning substrates amenable to diverse alcohol dehydrogenases, thereby mitigating the reliance on high-throughput screening or engineering in identifying the optimal enzyme for specific substrate.

Electro-Oxidation Reaction of Methanol over La2-xSrxNi1-y(Mn/Fe/Co)yO4+δ Ruddlesden-Popper Oxides.

Solution combustion-synthesized Ruddlesden-Popper oxides La1.4Sr0.6Ni0.9(Mn/Fe/Co)0.1O4+δ were explored for the methanol electro-oxidation reaction. With optimal doping of Sr2+ in the A site and Co2+ in the B site, Ni3+ with t2g6 dx2-y21 configuration in La1.4Sr0.6Ni0.9Co0.1O4+δ exhibited a tetragonal distortion with compression in axial bonds and elongation in equatorial bonds. This structural modification fostered an augmented overlap of dz2 orbitals with axial O 2p orbitals, leading to a heightened density of states at the Fermi level. Consequently, this facilitated not only elevated electrical conductivity but also a noteworthy reduction in the charge transfer resistance. These effects collectively contributed to the exceptional methanol oxidation activity of La1.4Sr0.6Ni0.9Co0.1O4+δ, as evidenced by an impressive current density of 21.4 mA cm-2 and retention of 95% of initial current density even after 10 h of prolonged reaction. The presence of Ni3+ further played a pivotal role in the creation of NiOOH, a crucial intermediate species, facilitated by the presence of surface oxygen vacancies. These factors synergistically enabled efficient methanol oxidation. In summary, our present study not only yields substantial insights but also paves the way for a novel avenue to fine-tune the activity of Ruddlesden-Popper oxides for the successful electro-oxidation of methanol.

Increased odds for COVID-19 infection among individuals with periodontal disease.

OBJECTIVES: Periodontal disease has been linked to multiple systemic conditions, but the relationship with COVID-19 still needs to be elucidated. We hypothesized that periodontal disease may be associated with COVID-19 infection. MATERIALS AND METHODS: This study utilized cross-sectional data to establish the strength of the association between periodontal disease and COVID-19 infection. The University of Florida Health Center's i2b2 patient's registry was used to generate patient counts through ICD-10 diagnostic codes. Univariate descriptive statistics of the patient population and logistic regression to estimate odds ratios of associations between periodontal disease and COVID-19 infection were used for analysis. RESULTS: Patients with periodontal disease were 4.4 times more likely to be positively diagnosed with COVID-19 than patients without PD. Associations remained similar and robust (P value < 0.0001) after adjustment for age (OR = 4.34; 95% CI, 3.68-5.09), gender (OR = 4.46; 95% CI, 3.79-5.23), and smoking status (OR = 4.77; 95% CI, 4.04-5.59). Associations were smaller but remained robust (P value < 0.0001) after adjusting for race (OR = 2.83; 95% CI, 2.40-3.32), obesity (OR = 2.53; 95% CI, 2.14-2.98), diabetes (OR = 3.32; 95% CI, 2.81-3.90), and cardiovascular disease (OR = 2.68; 95% CI, 2.27-3.14). CONCLUSIONS: Periodontal disease is significantly associated with increased odds for COVID-19 infection. CLINICAL RELEVANCE: With the caveat of a cross-sectional study design, these results suggest that periodontal disease may increase the odds for COVID-19 infection.

A curated list of targeted optimized promiscuous ketoreductases (TOP-K).

Enzymes are either specific or promiscuous catalysts in nature. The latter is portrayed by protein families like CYP450Es, Aldo-ketoreductases and short/medium-chain dehydrogenases which participate in detoxification or secondary metabolite production. However, enzymes are evolutionarily 'blind' to an ever-increasing synthetic substrate library. Industries and laboratories have circumvented this by high-throughput screening or site-specific engineering to synthesize the product of interest. However, this paradigm entails cost and time-intensive one-enzyme, one-substrate catalysis model. One of the superfamilies regularly used for chiral alcohol synthesis are short-chain dehydrogenases/reductases (SDRs). Our objective is to determine a superset of promiscuous SDRs that can catalyze multiple ketones. They are typically classified into shorter 'Classical' and longer 'Extended' type ketoreductases. However, current analysis of modelled SDRs reveals a length-independent conserved N-terminus Rossmann-fold and a variable substrate-binding C-terminus substrate-binding region for both categories. The latter is recognized to influence the enzyme's flexibility and substrate promiscuity and we hypothesize these properties are directly linked with each other. We tested this by catalyzing ketone intermediates with the essential and specific enzyme: FabG_E, as well as non-essential SDRs such as UcpA and IdnO. The experimental results confirmed this biochemical-biophysical association, making it an interesting filter for ascertaining promiscuous enzymes. Hence, we created a dataset of physicochemical properties derived from the protein sequences and employed machine learning algorithms to examine potential candidates. This resulted in 24 targeted optimized ketoreductases (TOP-K) from 81 014 members. The experimental validation of select TOP-Ks demonstrated the correlation between the C-terminal lid-loop structure, enzyme flexibility and turnover rate on pro-pharmaceutical substrates.

Electrochemical Performance of Polymer-Derived Silicon-Oxycarbide/Graphene Nanoplatelet Composites for High-Performance Li-Ion Batteries.

Amorphous polymer-derived silicon-oxycarbide (SiOC) ceramics have a high theoretical capacity and good structural stability, making them suitable anode materials for lithium-ion batteries. However, SiOC has low electronic conductivity, poor transport properties, low initial Couloumbic efficiency, and limited rate capability. Therefore, there is an urgent need to explore an efficient SiOC-based anode material that could mitigate the abovementioned limitations. In this study, we synthesized carbon-rich SiOC (SiOC-I) and silicon-rich SiOC (SiOC-II) and evaluated their elemental and structural characteristics using a broad spectrum of characterization techniques. Li-ion cells were fabricated for the first time by pairing a buckypaper composed of carbon nanotubes with SiOC-I or SiOC-II as the anode. When mixed with graphene nanoplatelets, the SiOC-II/GNP composites exhibited improved electrochemical performance. High specific capacity (average specific capacity of 744 mAh/g at a 0.1C rate) was achieved with the composite anode (25 wt % SiOC-II and 75% GNP), which was much better than that of monolithic SiOC-I, SiOC-II, or GNPs. This composite also exhibited excellent cycling stability, achieving 344 mAh/g after 260 cycles at a 0.5C rate and high reversibility. The enhanced electrochemical performance is attributed to better electronic conductivity, lower charge-transfer resistance, and short ion diffusion length. Due to their superior electrochemical performance, SiOC/GNP composites with CNT buckypaper as a current collector can be considered a promising anode material for LiBs.

The conundrum of bacteria-specific antibiotics.

There is a continual debate on the pros and cons of broad-spectrum versus pathogen-specific antibiotics. The unmet need for a solution for antimicrobial resistance (AMR) has put this argument into sharper focus. A shortage of clinically differentiated antibiotics in late-stage clinical development coupled with the global unmet need in the face of the AMR onslaught has exacerbated the treatment options of drug-resistant bacterial infections. An added dimension to this problem is the current understanding of dysbiosis caused by antibiotics, often leading to negative fallout in immunocompromised patients. We attempt to deconstruct the nuances of this debate from an antibiotics discovery and a clinical standpoint.

Identification of key amino acid residues in OqxB mediated efflux of fluoroquinolones using site-directed mutagenesis.

OqxB belongs to the RND (Resistance-Nodulation-Division) efflux pump family, recognized widely as a major contributor towards enhancing antimicrobial resistance. It is known to be predominantly present in all Klebsiella spp. and is attributed for its role in increasing resistance against an array of antibiotics like nitrofurantoin, quinolones, ß-lactams and colistin. However, the presence of oqxB encoding this efflux pump is not limited only to Klebsiella spp., but is also found to occur via horizontal gene transfer in other bacterial genera like Escherichia coli, Enterobacter cloacae and Salmonella spp. Recently, we reported the crystal structure of OqxB and its structure-function relationship required for the efflux of fluoroquinolones. Extending these findings further, we characterized the structural architecture of this efflux pump along with identifying some critical amino acids at the substrate binding domain of OqxB. Based on our in silico modelling studies, both hydrophobic residues (F180, L280, L621, F626) and polar residues (R48, E50, E184, R157, R774) were found to be located at this site. The present work reports the importance of these key amino acid residues and the crucial ion-pair interactions at the substrate-binding pocket, thereby establishing their role in OqxB mediated efflux and the resultant resistance development against fluoroquinolones.

"It's a decision I have to make": Patient perspectives on smoking and cessation after lung cancer screening decisions.

Few studies exist showing that involvement in lung cancer screening (LCS) leads to a change in rates of cigarette smoking. We investigated LCS longitudinally to determine whether teachable moments for smoking cessation occur downstream from the initial provider-patient LCS shared decision-making discussion and self-reported effects on smoking behaviors. We performed up to two successive semi-structured interviews to assess the experiences of 39 individuals who formerly or currently smoked cigarettes who underwent LCS decision-making discussions performed during routine care from three established US medical center LCS programs. The majority of those who remembered hearing about the importance of smoking cessation after LCS-related encounters did not report communication about smoking influencing their motivation to quit or abstain from smoking, including patients who were found to have pulmonary nodules. Patients experienced little distress related to LCS discussions. Patients reported that there were other, more significant, reasons for quitting or abstinence. They recommended clinicians continue to ask about smoking at every clinical encounter, provide information comparing the benefits of LCS with those of quitting smoking, and have clinicians help them identify triggers or other motivators for improving smoking behaviors. Our findings suggest that there may be other teachable moment opportunities outside of LCS processes that could be utilized to motivate smoking reduction or cessation, or LCS processes could be improved to integrate cessation resources.

Validated In Silico Population Model of Escherichia coli.

Flux balance analysis (FBA) and ordinary differential equation models have been instrumental in depicting the metabolic functioning of a cell. Nevertheless, they demonstrate a population's average behavior (summation of individuals), thereby portraying homogeneity. However, living organisms such as Escherichia coli contain more biochemical reactions than engaging metabolites, making them an underdetermined and degenerate system. This results in a heterogeneous population with varying metabolic patterns. We have formulated a population systems biology model that predicts this degeneracy by emulating a diverse metabolic makeup with unique biochemical signatures. The model mimics the universally accepted experimental view that a subpopulation of bacteria, even under normal growth conditions, renders a unique biochemical state, leading to the synthesis of metabolites and persister progenitors of antibiotic resistance and biofilms. We validate the platform's predictions by producing commercially important heterologous (isobutanol) and homologous (shikimate) metabolites. The predicted fluxes are tested in vitro resulting in 32- and 42-fold increased product of isobutanol and shikimate, respectively. Moreover, we authenticate the platform by mimicking a bacterial population in the presence of glyphosate, a metabolic pathway inhibitor. Here, we observe a fraction of subsisting persisters despite inhibition, thus affirming the signature of a heterogeneous populace. The platform has multiple uses based on the disposition of the user.

Assessing the Financial Sustainability of High-Fidelity and Virtual Reality Simulation for Nursing Education: A Retrospective Case Analysis.

To stimulate classroom discussion and collaboration amid the COVID-19 pandemic, increasingly creative pedological methods for nursing education are necessary. Traditionally, high-fidelity simulation has been the standard for nursing education, but the use of virtual reality simulation is increasing. One of the major evaluative measures of simulation clinical training is the cost associated with each modality. In this retrospective case analysis, budget impact analysis methods were employed to compare high-fidelity simulation with virtual reality simulation. The components of each simulation pedagogy were compared in categorized cost buckets. Overall, virtual reality simulation education was determined to require 22% less time than high-fidelity simulation education. The cost associated with the virtual reality simulation was found to be 40% less expensive than the high-fidelity simulation. Our results demonstrate that virtual reality simulation is a financially advantageous, resource conscious pedagogical option for nursing education.

BSAC Vanguard Series: The future of drug development and the tension between access and excess.

There is a crying need for a new broad-spectrum antibiotic. The global unmet need has energized governments and researchers alike. We may soon have the next antibiotics coming to the aid of patients after a drought of over half a century. However, we need to traverse a complex causeway between access to new antibiotics and their overuse. In an ICU setting where time is premium, identifying the causative organism and its resistance pattern in the time window is often impossible; physicians may be forced to prescribe the latest antibiotics. This practice in the long term may give rise to a rapid spread of resistance among microbes. There is an urgent need to do a cost-benefit analysis of easy access and use of the new antibiotics.

Validated In Silico Model for Biofilm Formation in Escherichia coli.

Using Escherichia coli as the representative biofilm former, we report here the development of an in silico model built by simulating events that transform a free-living bacterial entity into self-encased multicellular biofilms. Published literature on ∼300 genes associated with pathways involved in biofilm formation was curated, static maps were created, and suitably interconnected with their respective metabolites using ordinary differential equations. Precise interplay of genetic networks that regulate the transitory switching of bacterial growth pattern in response to environmental changes and the resultant multicomponent synthesis of the extracellular matrix were appropriately represented. Subsequently, the in silico model was analyzed by simulating time-dependent changes in the concentration of components by using the R and python environment. The model was validated by simulating and verifying the impact of key gene knockouts (KOs) and systematic knockdowns on biofilm formation, thus ensuring the outcomes were comparable with the reported literature. Similarly, specific gene KOs in laboratory and pathogenic E. coli were constructed and assessed. MiaA, YdeO, and YgiV were found to be crucial in biofilm development. Furthermore, qRT-PCR confirmed the elevation of expression in biofilm-forming clinical isolates. Findings reported in this study offer opportunities for identifying biofilm inhibitors with applications in multiple industries. The application of this model can be extended to the health care sector specifically to develop novel adjunct therapies that prevent biofilms in medical implants and reduce emergence of biofilm-associated resistant polymicrobial-chronic infections. The in silico framework reported here is open source and accessible for further enhancements.

Novel non intrusive continuous use ZeBox technology to trap and kill airborne microbes.

Preventing nosocomial infection is a major unmet need of our times. Existing air decontamination technologies suffer from demerits such as toxicity of exposure, species specificity, noxious gas emission, environment-dependent performance and high power consumption. Here, we present a novel technology called "ZeBox" that transcends the conventional limitations and achieves high microbicidal efficiency. In ZeBox, a non-ionizing electric field extracts naturally charged microbes from flowing air and deposits them on engineered microbicidal surfaces. The surface's three dimensional topography traps the microbes long enough for them to be inactivated. The electric field and chemical surfaces synergistically achieve rapid inactivation of a broad spectrum of microbes. ZeBox achieved near complete kill of airborne microbes in challenge tests (5-9 log reduction) and [Formula: see text] efficiency in a fully functional stem cell research facility in the presence of humans. Thus, ZeBox fulfills the dire need for a real-time, continuous, safe, trap-and-kill air decontamination technology.

Azaindole Based Potentiator of Antibiotics against Gram-Negative Bacteria.

We discovered azaindole-based compounds with weak innate activity that exhibit substantial potentiation of antibacterial activities of different antibiotics, viz., rifampicin, erythromycin, solithromycin, and novobiocin in Gram-negative bacteria. In the presence of the azaindole derivatives, these antibiotics exhibited submicromolar minimum inhibitory concentrations (MICs) against Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Acinetobacter baumannii. The fold improvements in MIC of these antibiotics that were otherwise weak or inactive on their own against these bacteria were also observed against drug-resistant clinical isolates. Our studies indicate that this selective potentiation is probably through destabilization of the outer membrane's integrity, known to be regulated by the lipopolysaccharides (LPS). Thus, the azaindole based compounds described here open opportunities for those antibiotics that are otherwise ineffective due to LPS mediated entry barriers in Gram-negative bacteria.

Structure and function relationship of OqxB efflux pump from Klebsiella pneumoniae.

OqxB is an RND (Resistance-Nodulation-Division) efflux pump that has emerged as a factor contributing to the antibiotic resistance in Klebsiella pneumoniae. OqxB underwent horizontal gene transfer and is now seen in other Gram-negative bacterial pathogens including Escherichia coli, Enterobacter cloacae and Salmonella spp., further disseminating multi-drug resistance. In this study, we describe crystal structure of OqxB with n-dodecyl-ß-D-maltoside (DDM) molecules bound in its substrate-binding pocket, at 1.85 Å resolution. We utilize this structure in computational studies to predict the key amino acids contributing to the efflux of fluoroquinolones by OqxB, distinct from analogous residues in related transporters AcrB and MexB. Finally, our complementation assays with mutated OqxB and minimum inhibitory concentration (MIC) experiments with clinical isolates of E. coli provide further evidence that the predicted structural features are indeed involved in ciprofloxacin efflux.

Learnings from past failures: Future routes of antimicrobial drug discovery.

Despite the unprecedented unmet need to discover new antibiotics, only a few molecules have been registered for clinical use. This shortage is primarily based on the scientific failure in the postgenomic era of drug discovery. It appears counterintuitive that knowledge of the bacterial genome was followed by the failure to produce new antibiotics using the paradigm of target-driven drug discovery. Here, I discuss the causes of the failures and also describe how small biotech is mitigating these risks and moving forward using new strategies to identify new antibiotics.

A Comparison of Web-Based Cancer Risk Calculators That Inform Shared Decision-making for Lung Cancer Screening.

INTRODUCTION: To align patient preferences and understanding with harm-benefit perception, the Centers for Medicare & Medicaid Services (CMS) mandates that providers engage patients in a collaborative shared decision-making (SDM) visit before LDCT. Nonetheless, patients and providers often turn instead to the web for help making decisions. Several web-based lung cancer risk calculators (LCRCs) provide risk predictions and screening recommendations; however, the accuracy, consistency, and subsequent user interpretation of these predictions between LCRCs is ambiguous. We conducted a systematic review to assess this variability. DESIGN: Through a systematic Internet search, we identified 10 publicly available LCRCs and categorized their input variables: demographic factors, cancer history, smoking status, and personal/environmental factors. To assess variance in LCRC risk prediction outputs, we developed 16 hypothetical patients along a risk continuum, illustrated by randomly assigned input variables, and individually compared them to each LCRC against the empirically validated "gold-standard" PLCO risk model in order to evaluate the accuracy of the LCRCs within identical time-windows. RESULTS: From the inclusion criteria, 11 calculators were initially identified. The analyzed calculators also vary in output characteristics and risk depiction for hypothetical patients. There were 13 total instances across ten hypothetical patients in which the sample standard error exceeded the mean risk percentage across all general samples and set standard calculations. The largest measured difference is 16.49% for patient 8, and the smallest difference is 0.01% for patient 2. The largest measured difference is 16.49% for patient 8, and the smallest difference is 0.01% for patient 2. CONCLUSION: Substantial variability in the depiction of lung cancer risk for hypothetical patients exists across the web-based LCRCs due to their respective inputs and risk prediction models. To foster informed decision-making in the SDM-LDCT context, the input variables, risk prediction models, risk depiction, and screening recommendations must be standardized to best practice.

Utilization Pattern of Computed Tomographic Colonography in the United States: Analysis of the U.S. National Health Interview Survey.

CT colonography for colorectal cancer screening has been proved to be effective and cost-saving. CT colonography uses minimally invasive evaluation of colorectum and has better patient acceptance, which appears to be a promising screening modality to improve low colorectal cancer screening rate. This study investigated the utilization patterns of CT colonography and factors associated with its use among U.S. adult population. This retrospective cross-sectional study analyzed the National Health Interview Survey 2015 and 2018. U.S. adults ages 45 or older without a history of colorectal cancer were included. Survey design-adjusted Wald F tests were used to compare the utilization of CT colonography during the study period. Multivariable logistic regression was used to identify the predictors of CT colonography among individual socioeconomic and health-related characteristics. The study sample included 34,768 individuals representing 129,430,319 U.S. adult population ages 45 or older. The overall utilization of CT colonography increased from 0.79% in 2015 to 1.33% in 2018 (P < 0.001). 54.5% study participants reported being up-to-date on recommended colorectal cancer screening; of those, 1.8% used CT colonography. Compared with individuals ages 65+, those ages 45-49 years were 2.08 times (OR, 2.08, 95% confidence interval, 1.01-4.35) more likely to use CT colonography. Socioeconomically disadvantaged characteristics (e.g., racial/ethnic minority, low income, publicly funded insurance) were associated with a greater likelihood of CT colonography. This study demonstrated an increasing trend in utilization of CT colonography for colorectal cancer screening in U.S. adults. Younger individuals, racial/ethnic minorities, or those with lower income appear to have a higher CT colonography utilization. PREVENTION RELEVANCE: Although computed tomographic (CT) colonography has been proved to be cost-effective and have better patient acceptance, its overall utilization for colorectal cancer (CRC) screening is low (<1.4%) among US adults aged 45+ in 2018. More efforts are needed to implement strategies to increase CT colonography for effective CRC prevention.

Health benefits and economic advantages associated with increased utilization of a smoking cessation program.

Rationale, aim & objective: The goal of this study was to examine the health and economic impacts related to increased utilization of the Duke Smoking Cessation Program resulting from the addition of two relatively new referral methods - Best Practice Advisory and Population Outreach. Materials & methods: In a companion paper 'Comparison of Referral Methods into a Smoking Cessation Program', we report results from a retrospective, observational, comparative effectiveness study comparing the impact of three referral methods - Traditional Referral, Best Practice Advisory and Population Outreach on utilization of the Duke Smoking Cessation Program. In this paper we take the next step in this comparative assessment by developing a Markov model to estimate the improvement in health and economic outcomes when two referral methods - Best Practice Advisory and Population Outreach - are added to Traditional Referral. Data used in this analysis were collected from Duke Primary Care and Disadvantaged Care clinics over a 1-year period (1 October 2017-30 September 2018). Results: The addition of two new referral methods - Best Practice Advisory and Population Outreach - to Traditional Referral increased the utilization of the Duke Smoking Cessation Program in Primary Care clinics from 129 to 329 smokers and in Disadvantaged Care clinics from 206 to 401 smokers. The addition of these referral methods was estimated to result in 967 life-years gained, 408 discounted quality-adjusted life-years saved and total discounted lifetime direct healthcare cost savings of US$46,376,285. Conclusion: Health systems may achieve increased patient health and decreased healthcare costs by adding Best Practice Advisory and Population Outreach strategies to refer patients to smoking cessation services.