Singleton {NOT} and Doubleton {YES; NOT} Gates Act as Functionally Complete Sets in DNA-Integrated Computational Circuits.

A functionally complete Boolean operator is sufficient for computational circuits of arbitrary complexity. We connected YES (buffer) with NOT (inverter) and two NOT four-way junction (4J) DNA gates to obtain IMPLY and NAND Boolean functions, respectively, each of which represents a functionally complete gate. The results show a technological path towards creating a DNA computational circuit of arbitrary complexity based on singleton NOT or a combination of NOT and YES gates, which is not possible in electronic computers. We, therefore, concluded that DNA-based circuits and molecular computation may offer opportunities unforeseen in electronics.

Structure-Kinetics Relationships of Opioids from Metadynamics and Machine Learning.

The nation's opioid overdose deaths reached an all-time high in 2021. The majority of deaths are due to synthetic opioids represented by fentanyl. Naloxone, which is an FDA-approved reversal agent, antagonizes opioids through competitive binding at the mu-opioid receptor (mOR). Thus, knowledge of opioid's residence time is important for assessing the effectiveness of naloxone. Here we estimated the residence times of 15 fentanyl and 4 morphine analogs using metadynamics, and compared them with the most recent measurement of the opioid kinetic, dissociation, and naloxone inhibitory constants (Mann, Li et al, Clin. Pharmacol. Therapeut. 2022). Importantly, the microscopic simulations offered a glimpse at the common binding mechanism and molecular determinants of dissociation kinetics for fentanyl analogs. The insights inspired us to develop a machine learning (ML) approach to analyze the kinetic impact of fentanyl's substituents based on the interactions with mOR residues. This proof-of-concept approach is general; for example, it may be used to tune ligand residence times in computer-aided drug discovery.

Structure-Kinetics Relationships of Opioids from Metadynamics and Machine Learning Analysis.

The nation's opioid overdose deaths reached an all-time high in 2021. The majority of deaths are due to synthetic opioids represented by fentanyl. Naloxone, which is a FDA-approved reversal agent, antagonizes opioids through competitive binding at the µ-opioid receptor (mOR). Thus, knowledge of the opioid's residence time is important for assessing the effectiveness of naloxone. Here, we estimated the residence times (τ) of 15 fentanyl and 4 morphine analogs using metadynamics and compared them with the most recent measurement of the opioid kinetic, dissociation, and naloxone inhibitory constants (Mann et al. Clin. Pharmacol. Therapeut. 2022, 120, 1020-1232). Importantly, the microscopic simulations offered a glimpse at the common binding mechanism and molecular determinants of dissociation kinetics for fentanyl analogs. The insights inspired us to develop a machine learning approach to analyze the kinetic impact of fentanyl's substituents based on the interactions with mOR residues. This proof-of-concept approach is general; for example, it may be used to tune ligand residence times in computer-aided drug discovery.

Patient Outcomes After Delirium Screening and Incident Alzheimer's Disease or Related Dementias in Skilled Nursing Facilities.

BACKGROUND: The extent to which a positive delirium screening and new diagnosis of Alzheimer's disease or related dementias (ADRD) increases the risk for re-hospitalization, long-term nursing home placement, and death remains unknown. OBJECTIVE: To compare long-term outcomes among newly admitted skilled nursing facility (SNF) patients with delirium, incident ADRD, and both conditions. DESIGN, SETTING, AND PARTICIPANTS: A retrospective cohort study of Medicare beneficiaries who entered a SNF from hospital with a minimum 14-day stay (n = 100,832) from 2015 to 2016. MAIN MEASURES: Return to home, hospital readmission, admission to a long-term care facility, or death. KEY RESULTS: Patients with delirium were as likely to be discharged home as patients diagnosed with ADRD (HR: 0.63, 95% CI: 0.59, 0.67; HR: 0.65, 95% CI: 0.64, 0.67). Patients with both delirium and ADRD were less likely to be discharged home (HR: 0.49, 95% CI: 0.47, 0.52) and showed increased risk of death (HR: 1.30, 95% CI: 1.17, 1.45). Patients with ADRD, regardless of delirium screening status, had increased risk for long-term nursing home care transfer (HR: 1.66, 95% CI: 1.63, 1.70; HR: 1.76, 95% CI: 1.69, 1.82). Patients with delirium and no ADRD showed increased risk of transfer to long-term nursing home care (HR: 1.25, 95% CI: 1.18, 1.33). The rate of deaths was higher among patients who screened positive for delirium without ADRD compared to the no delirium and no ADRD groups (HR: 2.35, 95% CI: 2.11, 2.61). CONCLUSION: A positive delirium screening increased risk of death and transfer to long-term care in the first 100 days after admission regardless of incident ADRD diagnosis. Patients with delirium and/or ADRD also are less likely to be discharged home. Our study builds on the evidence base that delirium is important to address in older adults as it is associated with negative outcomes.

Impact of Early Introduction to the Neurosciences on West Virginia High School Students via the Brain Bee.

BACKGROUND: The science, technology, engineering, and math (STEM) fields are often underrepresented due to lack of interest or exposure. The Brain Bee is a neuroscience competition for high school students meant to inspire future leaders in the neurosciences. A regional Brain Bee competition hosted in West Virginia was led by medical students and neurology residents with the goal of increasing high school student interest in the neurosciences. ACTIVITY: The West Virginia Brain Bee competition consisted of a neuroanatomy practical, a written exam, and a clinical assessment. Other fun neuroscience educational activities were also offered to students throughout the competition day. Students were surveyed before and after the competition day. RESULTS: Student interest in pursuing a neuroscience career increased (3.24 to 3.58, p = 0.043), and confidence in neuroscience knowledge increased (2.88 to 3.12, p = 0.036). Qualitative assessment revealed the importance of role models and a supportive environment for student learning. CONCLUSION: The West Virginia Brain Bee increased high school student interest in and confidence of neuroscience knowledge. This competition may be a meaningful way to connect high school students with potential mentors in the neurosciences and may also help foster an interest in pursuing a career in the neurosciences in the future.

How µ-opioid receptor recognizes fentanyl.

Roughly half of the drug overdose-related deaths in the United States are related to synthetic opioids represented by fentanyl which is a potent agonist of mu-opioid receptor (mOR). In recent years, X-ray crystal structures of mOR in complex with morphine derivatives have been determined; however, structural basis of mOR activation by fentanyl-like opioids remains lacking. Exploiting the X-ray structure of BU72-bound mOR and several molecular simulation techniques, we elucidated the detailed binding mechanism of fentanyl. Surprisingly, in addition to the salt-bridge binding mode common to morphinan opiates, fentanyl can move deeper and form a stable hydrogen bond with the conserved His2976.52, which has been suggested to modulate mOR's ligand affinity and pH dependence by previous mutagenesis experiments. Intriguingly, this secondary binding mode is only accessible when His2976.52 adopts a neutral HID tautomer. Alternative binding modes may represent a general mechanism in G protein-coupled receptor-ligand recognition.

Kinetics and Mechanism of Fentanyl Dissociation from the µ-Opioid Receptor.

Driven by illicit fentanyl, opioid related deaths have reached the highest level in 2020. Currently, an opioid overdose is resuscitated by the use of naloxone, which competitively binds and antagonizes the µ-opioid receptor (mOR). Thus, knowledge of the residence times of opioids at mOR and the unbinding mechanisms is valuable for assessing the effectiveness of naloxone. In the present study, we calculate the fentanyl-mOR dissociation time and elucidate the mechanism by applying an enhanced sampling molecular dynamics (MD) technique. Two sets of metadynamics simulations with different initial structures were performed while accounting for the protonation state of the conserved H2976.52, which has been suggested to modulate the ligand-mOR affinity and binding mode. Surprisingly, with the Nδ-protonated H2976.52, fentanyl can descend as much as 10 Å below the level of the conserved D1473.32 before escaping the receptor and has a calculated residence time τ of 38 s. In contrast, with the Nϵ- and doubly protonated H2976.52, the calculated τ are 2.6 and 0.9 s, respectively. Analysis suggests that formation of the piperidine-Hid297 hydrogen bond strengthens the hydrophobic contacts with the transmembrane helix (TM) 6, allowing fentanyl to explore a deep pocket. Considering the experimental τ of ∼4 min for fentanyl and the role of TM6 in mOR activation, the deep insertion mechanism may be biologically relevant. The work paves the way for large-scale computational predictions of opioid dissociation rates to inform evaluation of strategies for opioid overdose reversal. The profound role of the histidine protonation state found here may shift the paradigm in computational studies of ligand-receptor kinetics.

Tracing-corrected estimates of disengagement from HIV care and mortality among patients enrolling in HIV care without overt immunosuppression in Tanzania.

In the era of "test and treat", it is important to understand HIV care outcomes and their determinants in patients presenting to care with early-stage disease. We surveyed 924 adults newly enrolling in HIV care at four clinics in Tanzania before the adoption of universal treatment eligibility, and collected longitudinal clinical data. Participants who defaulted from care were tracked in the community. Cumulative incidence of disengagement from care and death was estimated using competing risk methods. By 12 months after enrollment, 18.2% of patients had disengaged from care and 6.9% had died. Factors associated with disengagement included male sex (adjusted subhazard ratio [aSHR] versus female = 1.75, 95% confidence interval [CI]: 1.06-2.89), provider-initiated HIV diagnosis (aSHR versus self-referred = 1.71, 95% CI: 1.03-2.86), ineligibility for antiretroviral treatment (ART) at enrollment (aSHR versus eligibility = 2.82, 95% CI: 1.84-4.32) and increased anticipated stigma score (aSHR = 1.04 per 5-point increase, 95% CI: 1.02-1.05). Higher life satisfaction score (aSHR = 0.97 per 5-point increase, 95% CI: 0.95-0.99) and having 1-2 close friends (aSHR versus none = 0.58, 95% CI: 0.47-0.71) were protective. The findings highlight the continued importance of social environment for HIV care outcomes and the potential of universal ART eligibility to reduce HIV care attrition.

Utilization of cumulative antibiograms for public health surveillance: Trends in Escherichia coli and Klebsiella pneumoniae susceptibility, Massachusetts, 2008-2018.

BACKGROUND: Antimicrobial resistance is an urgent public health threat. Identifying trends in antimicrobial susceptibility can inform public health policy at the state and local levels. OBJECTIVE: To determine the ability of statewide antibiogram aggregation for public health surveillance to identify changes in antimicrobial resistance trends. DESIGN: Facility-level trend analysis. METHODS: Crude and adjusted trend analyses of the susceptibility of Escherichia coli and Klebsiella pneumoniae to particular antibiotics, as reported by aggregated antibiograms, were examined from 2008 through 2018. Multivariable regression analyses via generalized linear mixed models were used to examine associations between hospital characteristics and trends of E. coli and K. pneumoniae susceptibility to ciprofloxacin and ceftriaxone. RESULTS: E. coli and K. pneumoniae showed inverse trends in drug susceptibility over time. K. pneumoniae susceptibility to fluoroquinolones increased by 5% between 2008 and 2018 (P < .05). In contrast, E. coli susceptibility declined during the same period to ceftriaxone (6%), gentamicin (4%), and fluoroquinolones (4%) (P < .05). When compared to Boston hospitals, E. coli isolates from hospitals in other regions had a >4% higher proportion of susceptibility to ciprofloxacin and a >3% higher proportion of susceptibility to ceftriaxone (P < .05). Isolates of K. pneumoniae had higher susceptibility to ciprofloxacin (>3%) and ceftriaxone (>1.5%) in all regions when compared to Boston hospitals (P < .05). CONCLUSIONS: Cumulative antibiograms can be used to monitor antimicrobial resistance, to discern regional and facility differences, and to detect changes in trends. Furthermore, because the number of years that hospitals contributed reports to the state-level aggregate had no significant influence on susceptibility trends, other states should not be discouraged by incomplete hospital compliance.

How mu-Opioid Receptor Recognizes Fentanyl.

The opioid crisis has escalated during the COVID-19 pandemic. More than half of the overdose-related deaths are related to synthetic opioids represented by fentanyl which is a potent agonist of mu-opioid receptor (mOR). In recent years, crystal structures of mOR complexed with morphine derivatives have been determined; however, structural basis of mOR activation by fentanyl-like synthetic opioids remains lacking. Exploiting the X-ray structure of mOR bound to a morphinan ligand and several state-of-the-art simulation techniques, including weighted ensemble and continuous constant pH molecular dynamics, we elucidated the detailed binding mechanism of fentanyl with mOR. Surprisingly, in addition to the orthosteric site common to morphinan opiates, fentanyl can move deeper and bind mOR through hydrogen bonding with a conserved histidine H297, which has been shown to modulate mOR's ligand affinity and pH dependence in mutagenesis experiments, but its precise role remains unclear. Intriguingly, the secondary binding mode is only accessible when H297 adopts a neutral HID tautomer. Alternative binding modes and involvement of tautomer states may represent general mechanisms in G protein-coupled receptor (GPCR)-ligand recognition. Our work provides a starting point for understanding mOR activation by fentanyl analogs that are emerging at a rapid pace and assisting the design of safer analgesics to combat the opioid crisis. Current protein simulation studies employ standard protonation and tautomer states; our work demonstrates the need to move beyond the practice to advance our understanding of protein-ligand recognition.

How µ-Opioid Receptor Recognizes Fentanyl.

In 2019, drug overdose has claimed over 70,000 lives in the United States. More than half of the deaths are related to synthetic opioids represented by fentanyl which is a potent agonist of mu-opioid receptor (mOR). In recent years, the crystal structures of mOR in complex with morphine derivatives have been determined; however, structural basis of mOR activation by fentanyl-like synthetic opioids remains lacking. Exploiting the X-ray structure of mOR bound to a morphinan ligand and several state-of-the-art simulation techniques, including weighted ensemble and continuous constant pH molecular dynamics, we elucidated the detailed binding mechanism of fentanyl with mOR. Surprisingly, in addition to forming a salt-bridge with Asp1473.32 in the orthosteric site common to morphinan opiates, fentanyl can move deeper and bind mOR through hydrogen bonding with a conserved histidine His2976.52, which has been shown to modulate mOR's ligand affinity and pH dependence in mutagenesis experiments, but its precise role remains unclear. Intriguingly, the secondary binding mode is only accessible when His297 adopts a neutral HID tautomer. Alternative binding modes and involvement of tautomer states may represent general mechanisms in G protein-coupled receptor (GPCR)-ligand recognition. Our work provides a starting point for understanding the molecular basis of mOR activation by fentanyl which has many analogs emerging at a rapid pace. The knowledge may also inform the design of safer analgesics to combat the opioid crisis. Current protein simulation studies employ standard protonation and tautomer states; our work demonstrates the need to move beyond the practice to advance our understanding of protein-ligand recognition.

Linking Epidemiology and Whole-Genome Sequencing to Investigate Salmonella Outbreak, Massachusetts, USA, 2018.

Cross-discipline collaboration among state and local health departments improved foodborne illness surveillance for a 2018 Salmonella enterica serovar Enteritidis outbreak in Massachusetts, USA. Prompt linking of epidemiologic and laboratory data and implementation of in-state whole-genome sequencing and analysis improved public health surveillance capacity for outbreak detection and control.

Treatment of Staphylococcus aureus skin infection in vivo using rifampicin loaded lipid nanoparticles.

We have previously reported on a novel nanoparticle formulation that was effective at killing Staphylococcus aureus in vitro. Here, we report for the first time, the antibacterial effects of a lipidic nano-carrier containing rifampicin (NanoRIF) which can be used to successfully treat Methicillin-Resistant S. aureus (MRSA) infection at a reduced antibiotic dosage compared to the free drug in a skin wound model in mice. The formulation used contains the lipid monoolein, a cationic lipid N-[1-(2,3-dioleoyloxy)propyl]-N,N,N-trimethylammonium methyl-sulfate (DOTAP) and the antibiotic. We have shown that rifampicin-loaded nanoparticles are more effective at treating infection in the skin wound model than the antibiotic alone. Cryo-TEM was used to capture for the first time, interactions of the formed nanoparticles with the cell wall of an individual bacterium. Our data strongly indicate enhanced binding of these charged nanoparticles with the negatively charged bacterial membrane. The efficacy we have now observed in vivo is of significant importance for the continued development of nanomedicine-based strategies to combat antibiotic resistant bacterial skin infections.

Acute levodopa dosing around-the-clock ameliorates REM sleep without atonia in hemiparkinsonian rats.

Rapid-eye-movement (REM) sleep without atonia (RSWA), a marker of REM sleep behavior disorder (RBD), is frequently comorbid with Parkinson's disease (PD). Although rodent models are commonly used for studying PD, the neurobiological and behavioral correlates of RBD remain poorly understood. Therefore, we developed a behavior-based criteria to identify RSWA in the hemiparkinsonian rat model of PD. Video recordings of rats were analyzed, to develop a criteria consisting of behavioral signs that occurred during polysomnographically confirmed epochs of sleep-wake stages. The sleep-slouch, a postural shift of the body or head caused only by gravity, was identified as a unique behavioral sign of REM sleep onset and was altered in hemiparkinsonian rats during RSWA. There was a significant correlation between the behavior-based criteria and polysomnograms for all sleep-wake stages in control but not hemiparkinsonian rats indicating a deterioration of sleep-wake architecture in parkinsonism. We then tested the efficacy of levodopa in ameliorating RSWA using intermittent and around-the-clock (ATC) dosing regimens. ATC levodopa dosing at 4 mg/kg for 48 h caused a significant reduction of RSWA as measured by polysomnography and the behavioral-based criteria along with an amelioration of forelimb motor deficits. Our findings show that the phenomenological correlates of RSWA can be reliably characterized in the hemiparkinsonian rat model. ATC levodopa administration ameliorates RSWA in this model without deleterious consequences to the overall sleep-wake architecture and therapeutic benefits for parkinsonian motor deficits. These findings suggest that further study may allow for the application of a similar approach to treat RBD in PD patients.

The prevalence of complications associated with lumbar and thoracic spinal deformity surgery in the elderly population: a meta-analysis.

BACKGROUND: The prevalence of spinal deformities increases with age, affecting between 30% and 68% of the elderly population (ages ≥65). The reported prevalence of complications associated with surgery for spinal deformities in this population ranges between 37% and 71%. Given the wide range of reported complication rates, the decision to perform surgery remains controversial. METHODS: A comprehensive search was conducted using PubMed, Embase, and Cochrane to identify studies reporting complications for spinal deformity surgery in the elderly population. Pooled prevalence estimates for individual complication types were calculated using the random-effects model. RESULTS: Of 5,586 articles, 14 met inclusion criteria. Fourteen complication types were reported, with at least 2 studies for each complication with the following pooled prevalence: reoperation (prevalence 19%; 95% CI, 9-36%; 107 patients); hardware failure (11%; 95% CI, 5-25%; 52 patients); infection (7%; 95% CI, 4-12%; 262 patients); pseudarthrosis (6%; 95% CI, 3-12%; 149 patients); radiculopathy (6%; 95% CI, 1-33%; 116 patients); cardiovascular event (5%; 95% CI, 1-32%; 121 patients); neurological deficit (5%; 95% CI, 2-15%; 248 patients); deep vein thrombosis (3%; 95% CI, 1-7%; 230 patients); pulmonary embolism (3%; 95% CI, 1-7%; 210 patients); pneumonia (3%; 95% CI, 1-11%; 210 patients); cerebrovascular or stroke event (2%; 95% CI, 0-9%; 85 patients); death (2%; 95% CI, 1-9%; 113 patients); myocardial infarction (2%; 95% CI, 1-6%; 210 patients); and postoperative hemorrhage (1%; 95% CI, 0-10%; 85 patients). CONCLUSIONS: Most complication types following spinal deformity surgery in the elderly had prevalence point estimates of <6%, while all were at least ≤19%. Additional studies are needed to further explore composite prevalence estimates and prevalence associated with traditional surgical approaches as compared to minimally-invasive procedures in the elderly.

The Massachusetts Hepatitis C Testing Cascade, 2014-2016.

OBJECTIVES: To characterize hepatitis C testing in Massachusetts and guide stakeholders in addressing the needs of people living with hepatitis C. METHODS: All persons with a positive laboratory report for anti-hepatitis C virus (HCV) antibody, between 2014 and 2016, were included in the testing cascade. Outcomes were HCV tests received after a positive anti-HCV antibody test: nucleic acid test or genotype test. Logistic regression analyses were performed to determine factors associated with progression through the HCV testing cascade. RESULTS: Among those reported anti-HCV antibody positive, a total of 13 194 (61%) cases had a subsequent RNA-based test, and 79% (10 374/13 194) were confirmed with current, active HCV infection. For confirmed HCV cases, 44% (4557/10 374) had a genotype identified. The median time from an antibody-positive test to a RNA-based test was 29 days (interquartile range [IQR] = 7-151). Differences in moving through the testing cascade were observed by birth cohort and race/ethnicity. CONCLUSIONS: Improved surveillance capture of demographic information is needed to help public health agencies ensure equity in HCV diagnosis and linkage to care.

Microscopic Behaviors of Tri- n-Butyl Phosphate, n-Dodecane, and Their Mixtures at Air/Liquid and Liquid/Liquid Interfaces: An AMBER Polarizable Force Field Study.

In solvent extraction processes for recovering metal ions from used nuclear fuel, as well as other industrial applications, a better understanding of the metal complex phase transfer phenomenon would greatly aid ligand design and process optimization. We have approached this challenge by utilizing the classical molecular dynamics simulations technique to gain visual appreciation of the vapor/liquid and liquid/liquid interface between tri- n-butyl phosphate (TBP) and n-dodecane with air and water. In this study, we successfully reparameterized polarizable force fields for TBP and n-dodecane that accurately reproduced several of their thermophysical properties such as density, heat of vaporization, and dipole moment. Our models were able to predict the surface and interfacial tension of different systems when compared to experimental results that were also performed by us. Through this study, we gained atomistic understanding of the behaviors of TBP and n-dodecane at the interface against air and water, useful in further computational studies of such systems. Finally, our studies indicate that the initial configuration of a simulation may have a large effect on the final result.

Using public health surveillance data to measure Clostridium difficile infection population burden in Massachusetts.

Clostridium difficile occurs both inside and outside of health care facilities, but surveillance has been traditionally limited to the hospital setting. To measure the population-based burden of C difficile infection (CDI), we used multiple routine sources of data. We found an overall rate of CDI in Massachusetts in 2016 of 132.5 per 100,000 population, with mortality in 2014 of 6.4 per 100,000 population. Population-based measurement of CDI burden appears feasible without conducting a special study.

Quantifying Dimer and Trimer Formation of Tri-n-butyl Phosphates in Different Alkane Diluents: FTIR Study.

Tri-n-butyl phosphate (TBP), a representative of neutral organophosphorous metal-ion-extracting reagents, is an important ligand used in solvent extraction processes for the recovery of uranium and plutonium from spent nuclear fuel, as well as other non-nuclear applications. Ligand-ligand and organic solvent-ligand interactions play an important role in these processes. The self-association behavior of TBP in various alkane diluents of different chain lengths (8, 12, and 16 carbons) and a branched alkane (iso-octane) was investigated by Fourier transform infrared spectroscopic measurements. By careful deconvolution of the spectra into multiple peaks, our results indicate that TBP self-associates to form not only dimers, as previous studies showed, but also trimers in the practical concentration range. Using a mathematical fitting procedure, the dimerization and trimerization constants were determined. As expected, these equilibrium constants are dependent on the solvent used. As the alkane chain for linear hydrocarbon solvents becomes longer, dimerization decreases whereas trimerization increases. For the more branched hydrocarbon, we observe a significantly higher dimerization constant. These effects are most likely due to the intermolecular van der Waals interactions between the butyl tails of each TBP molecule and the diluent hydrocarbon chain as all solvents in this study are relatively nonpolar.

Quantifying Dimer and Trimer Formation by Tri-n-butyl Phosphates in n-Dodecane: Molecular Dynamics Simulations.

Tri-n-butyl phosphate (TBP), a representative of neutral organophosphorous ligands, is an important extractant used in the solvent extraction process for the recovery of uranium and plutonium from spent nuclear fuel. Microscopic pictures of TBP isomerism and its behavior in n-dodecane diluent were investigated utilizing MD simulations with previously optimized force field parameters for TBP and n-dodecane. Potential mean force (PMF) calculations on a single TBP molecule show seven probable TBP isomers. Radial distribution functions (RDFs) of TBP suggest the existence of TBP trimers at high TBP concentrations in addition to dimers. 2D PMF calculations were performed to determine the angle and distance criteria for TBP trimers. The dimerization and trimerization constants of TBP in n-dodecane were obtained and match our own experimental values using the FTIR technique. The new insights into the conformational behaviors of the TBP molecule as a monomer and as part of an aggregate could greatly aid in the understanding of the complexation between TBP and metal ions in a solvent extraction system.