Search

Abstract Background Lignin is an aromatic polymer deposited in secondary cell walls of higher plants to provide strength, rigidity, and hydrophobicity to vascular tissues. Due to its interconnections with cell wall polysaccharides, lignin plays important roles during plant growth and defense, but also has a negative impact on industrial processes aimed at obtaining monosaccharides from plant biomass. Engineering lignin offers a solution to this issue. For example, previous work showed that heterologous expression of a coliphage S-adenosylmethionine hydrolase (AdoMetase) was an effective approach to reduce lignin in the model plant Arabidopsis. The efficacy of this engineering strategy remains to be evaluated in bioenergy crops. Results We studied the impact of expressing AdoMetase on lignin synthesis in sorghum (Sorghum bicolor L. Moench). Lignin content, monomer composition, and size, as well as biomass saccharification efficiency were determined in transgenic sorghum lines. The transcriptome and metabolome were analyzed in stems at three developmental stages. Plant growth and biomass composition was further evaluated under field conditions. Results evidenced that lignin was reduced by 18% in the best transgenic line, presumably due to reduced activity of the S-adenosylmethionine-dependent O-methyltransferases involved in lignin synthesis. The modified sorghum features altered lignin monomer composition and increased lignin molecular weights. The degree of methylation of glucuronic acid on xylan was reduced. These changes enabled a ~20% increase in glucose yield after biomass pretreatment and saccharification compared to wild type. RNA-seq and untargeted metabolomic analyses evidenced some pleiotropic effects associated with AdoMetase expression. The transgenic sorghum showed developmental delay and reduced biomass yields at harvest, especially under field growing conditions. Conclusions The expression of AdoMetase represents an effective lignin engineering approach in sorghum. However, considering that this strategy potentially impacts multiple S-adenosylmethionine-dependent methyltransferases, adequate promoters for fine-tuning AdoMetase expression will be needed to mitigate yield penalty.

Abstract DNA is the genetic code found inside all living cells and its molecular stability can also be utilized outside the cell. While extracellular DNA (eDNA) has been identified as a structural polymer in bacterial biofilms, whether it persists stably throughout development remains unclear. Here, we report that eDNA is temporarily invested in the biofilm matrix before being reclaimed later in development. Specifically, by imaging eDNA dynamics within undomesticated Bacillus subtilis biofilms, we found eDNA is produced during biofilm establishment before being globally degraded in a spatiotemporally coordinated pulse. We identified YhcR, a secreted Ca2+-dependent nuclease, as responsible for eDNA degradation in pellicle biofilms. YhcR cooperates with two other nucleases, NucA and NucB, to reclaim eDNA for its phosphate content in colony biofilms. Our results identify extracellular nucleases that are crucial for eDNA reclamation during biofilm development and we therefore propose a new role for eDNA as a dynamic metabolic reservoir.

Introduction: Overdose deaths from high-potency synthetic opioids, including fentanyl and its analogs, continue to rise along with emergency department (ED) visits for complications of opioid use disorder (OUD). Fentanyl accumulates in adipose tissue; although rare, this increases the risk of precipitated withdrawal in patients upon buprenorphine initiation. Many EDs have implemented medication for opioid use disorder (MOUD) programs using buprenorphine. However, few offer methadone, a proven therapy without the risk of precipitated withdrawal associated with buprenorphine initiation. We describe the addition of an ED-initiated methadone treatment pathway and compared its 72-hour follow-up outpatient treatment engagement rates to our existing ED-initiated buprenorphine MOUD program. Methods: We expanded our ED MOUD program with a methadone treatment pathway. From February 20–September 19, 2023, we screened 20,504 ED arrivals; 5.1% had signs of OUD. We enrolled 61 patients: 28 in the methadone; and 33 in the buprenorphine pathways. For patients who screened positive for opioid use, shared decision-making was employed to determine whether buprenorphine or methadone therapy was more appropriate. Patients in the methadone pathway received their first dose of up to 30 milligrams (mg) of methadone in the ED. Two additional methadone doses of up to 40 mg were dispensed at the time of the ED visit and held in the department, allowing patients to return each day for observed dosing until intake at an opioid treatment program (OTP). We compared 72-hour rates of outpatient follow-up treatment engagement at the OTP (for those on methadone) or at the addiction treatment center (ATC) (for those on buprenorphine) for the two treatment pathways. Results: Of the 28 patients enrolled in the methadone pathway, 12 (43%) successfully engaged in follow-up treatment at the OTP. Of the 33 patients enrolled in the buprenorphine pathway, 15 (45%) successfully engaged in follow-up treatment at the ATC (relative risk 1.06; 95% confidence interval 0.60–1.87). Conclusion: Methadone initiation in the ED to treat patients with OUD resulted in similar 72-hour follow-up outpatient treatment engagement rates compared to ED-buprenorphine initiation, providing another viable option for MOUD.

Producing scalable, economically viable, low-carbon biofuels or biochemicals hinges on more efficient bioconversion processes. While microbial conversion can offer robust solutions, the native microbial growth process often redirects a large fraction of carbon to CO2 and cell mass. By integrating genome-scale metabolic models with techno-economic and life cycle assessment models, this study analyzes the effects of converting cell mass lipids to hydrocarbon fuels, and CO2 to methanol on the facility’s costs and life-cycle carbon footprint. Results show that upgrading microbial lipids or both microbial lipids and CO2 using renewable hydrogen produces carbon-negative bisabolene. Additionally, on-site electrolytic hydrogen production offers a supply of pure oxygen to use in place of air for bioconversion and fuel combustion in the boiler. To reach cost parity with conventional jet fuel, renewable hydrogen needs to be produced at less than $2.2 to $3.1/kg, with a bisabolene yield of 80% of the theoretical yield, along with cell mass and CO2 yields of 22 wt% and 54 wt%, respectively. The economic combination of cell mass, CO2, and bisabolene yields demonstrated in this study provides practical insights for prioritizing research, selecting suitable hosts, and determining necessary engineered production levels.

Background Return-of-service (RoS) schemes are investment strategies that governments use to increase the pool of health professionals through the issuing of bursaries and scholarships to health sciences students in return for service after graduation. Despite using these schemes for many years, Eswatini, South Africa, Botswana and Lesotho have not assessed the costs and return on investment of these schemes. This study aimed to assess the costs and relative rates of contract defaulting in these four Southern African countries.Methods A retrospective cohort study was carried out by reviewing databases of RoS beneficiaries for selected health sciences programmes who were funded between 2000 and 2010. Costs of the schemes were assessed by country, degree type and whether bursary holders completed their required service or defaulted on their public service obligations.Results Of the 5616 beneficiaries who studied between 1995 and 2019 in the four countries, 1225 (21.8%) beneficiaries from 2/9 South African provinces and Eswatini were presented in the final analysis. Only Eswatini had data on debt recovery or financial repayments. Beneficiaries were mostly medical students and slightly biased towards males. Medical students benefited from 56.7% and 81.3% of the disbursement in Eswatini (~US$2 million) and South Africa (~US$57 million), respectively. Each South African medical student studying in Cuba cost more than five times the rate of medical students who studied in South Africa. Of the total expenditure, 47.7% and 39.3% of the total disbursement is spent on individuals who default the RoS scheme in South Africa and Eswatini, respectively.Conclusions RoS schemes in these countries have loss of return on investment due to poor monitoring. The schemes are costly, ineffective and have never been evaluated. There are poor mechanisms for identifying beneficiaries who exit their contracts prematurely and inadequate debt recovery processes.

Abstract Background The COVID-19 disrupted the provision of essential health services in numerous countries, potentially leading to outbreaks of deadly diseases. This study aims to investigate the effect of the COVID-19 pandemic on the utilization of essential health services in Iran. Methods An analytical cross-sectional study was conducted using interrupted time series (ITS) analysis. Data about five indicators, including 'childhood vaccination, infant care, hypertension screening, diabetes screening, and breast cancer screening,' were obtained from the electronic health record System in two-time intervals: 15 months before (November 2018 to January 2020) and 15 months after (January 2020 to May 2021) the onset of the COVID-19 pandemic. The data were analyzed by utilizing ITS. In addition, a Poisson model was employed due to the usage of count data. The Durbin-Watson (DW) test was used to identify the presence of lag-1 autocorrelation in the time series data. All statistical analysis was performed using R 4.3.1 software, considering a 5% significance level. Results The ITS analysis showed that the COVID-19 pandemic significantly affected the utilization of all essential health services (P

Abstract Investigative exploration and foraging leading to food consumption have vital importance, but are not well-understood. Since GABAergic inputs to the lateral and ventrolateral periaqueductal gray (l/vlPAG) control such behaviors, we dissected the role of vgat-expressing GABAergic l/vlPAG cells in exploration, foraging and hunting. Here, we show that in mice vgat l/vlPAG cells encode approach to food and consumption of both live prey and non-prey foods. The activity of these cells is necessary and sufficient for inducing food-seeking leading to subsequent consumption. Activation of vgat l/vlPAG cells produces exploratory foraging and compulsive eating without altering defensive behaviors. Moreover, l/vlPAG vgat cells are bidirectionally interconnected to several feeding, exploration and investigation nodes, including the zona incerta. Remarkably, the vgat l/vlPAG projection to the zona incerta bidirectionally controls approach towards food leading to consumption. These data indicate the PAG is not only a final downstream target of top-down exploration and foraging-related inputs, but that it also influences these behaviors through a bottom-up pathway.

Summary: Mathematical models of biomolecular networks are commonly used to study cellular processes; however, their usefulness to explain and predict dynamic behaviors is often questioned due to the unclear relationship between parameter uncertainty and network dynamics. In this work, we introduce PyDyNo (Python dynamic analysis of biochemical networks), a non-equilibrium reaction-flux based analysis to identify dominant reaction paths within a biochemical reaction network calibrated to experimental data. We first show, in a simplified apoptosis execution model, that despite the thousands of parameter vectors with equally good fits to experimental data, our framework identifies the dynamic differences between these parameter sets and outputs three dominant execution modes, which exhibit varying sensitivity to perturbations. We then apply our methodology to JAK2/STAT5 network in colony-forming unit-erythroid (CFU-E) cells and provide previously unrecognized mechanistic explanation for the survival responses of CFU-E cell population that would have been impossible to deduce with traditional protein-concentration based analyses.

Intracellular actin networks assemble through the addition of ATP-actin subunits at the growing barbed ends of actin filaments. This is followed by “aging” of the filament via ATP hydrolysis and subsequent phosphate release. Aged ADP-actin subunits thus “treadmill” through the filament before being released back into the cytoplasmic monomer pool as a result of depolymerization at filament pointed ends. The necessity for aging before filament disassembly is reinforced by preferential binding of cofilin to aged ADP-actin subunits over newly-assembled ADP-Pi actin subunits in the filament. Consequently, investigations into how cofilin influences pointed-end depolymerization have, thus far, focused exclusively on aged ADP-actin filaments. Using microfluidics-assisted Total Internal Reflection Fluorescence (mf-TIRF) microscopy, we reveal that, similar to their effects on ADP filaments, cofilin and cyclase-associated protein (CAP) also promote pointed-end depolymerization of ADP-Pi filaments. Interestingly, the maximal rates of ADP-Pi filament depolymerization by CAP and cofilin together remain approximately 20–40 times lower than for ADP filaments. Further, we find that the promotion of ADP-Pi pointed-end depolymerization is conserved for all three mammalian cofilin isoforms. Taken together, the mechanisms presented here open the possibility of newly-assembled actin filaments being directly disassembled from their pointed-ends, thus bypassing the slow step of Pi release in the aging process.

Summary: Neurons in the primary cortex carry sensory- and behavior-related information, but it remains an open question how this information emerges and intersects together during learning. Current evidence points to two possible learning-related changes: sensory information increases in the primary cortex or sensory information remains stable, but its readout efficiency in association cortices increases. We investigated this question by imaging neuronal activity in mouse primary somatosensory cortex before, during, and after learning of an object localization task. We quantified sensory- and behavior-related information and estimated how much sensory information was used to instruct perceptual choices as learning progressed. We find that sensory information increases from the start of training, while choice information is mostly present in the later stages of learning. Additionally, the readout of sensory information becomes more efficient with learning as early as in the primary sensory cortex. Together, our results highlight the importance of primary cortical neurons in perceptual learning.

Methanotrophic bacteria are promising hosts for methane bioconversion to biochemicals or bioproducts. However, due to limitations associated with long genetic manipulation timelines and, lack of choice in genetic tools required for strain engineering, methanotrophs are currently not employed for bioconversion technologies. In this study, a rapid and reproducible electroporation protocol is developed for type 1 methanotroph, Methylotuvimicrobium alcaliphilum using common laboratory solutions, analyzing optimal electroshock voltages and post-shock cell recovery time. Successful reproducibility of the developed method was achieved when different replicative plasmids were assessed on lab adapted vs. wild-type M. alcaliphilum strains (DASS vs. DSM19304). Overall, a ∼ 3-fold decrease in time is reported with use of electroporation protocol developed here, compared to conjugation, which is the traditionally employed approach. Additionally, an inducible (3-methyl benzoate) and a constitutive (sucrose phosphate synthase) promoter is characterized for their strength in driving gene expression.

Background Informal payments for healthcare are typically regressive and limit access to quality healthcare while increasing risk of catastrophic health expenditure, especially in developing countries. Different responses have been proposed, but little is known about how they influence the incentives driving this behaviour. We therefore identified providers’ preferences for policy interventions to overcome informal payments in Tanzania.Methods We undertook a discrete choice experiment (DCE) to elicit preferences over various policy options with 432 health providers in 42 public health facilities in Pwani and Dar es Salaam region. DCE attributes were derived from a multi-stage process including a literature review, qualitative interviews with key informants, a workshop with health stakeholders, expert opinions, and a pilot test. Each respondent received 12 unlabelled choice sets describing two hypothetical job-settings that varied across 6-attributes: mode of payment, supervision at facility, opportunity for private practice, awareness and monitoring, measures against informal payments, and incentive payments to encourage noninfraction. Mixed multinomial logit (MMNL) models were used for estimation.Results All attributes, apart from supervision at facility, significantly influenced providers’ choices (P < .001). Health providers strongly and significantly preferred incentive payments for non-infraction and opportunities for private practice, but significantly disliked disciplinary measures at district level. Preferences varied across the sample, although all groups significantly preferred the opportunity to practice privately and cashless payment. Disciplinary measures at district level were significantly disliked by unit in-charges, those who never engaged in informal payments, and who were not absent from work for official trip. 10% salary top-up were preferred incentive by all, except those who engaged in informal payments and absent from work for official trip.Conclusion Better working conditions, with improved earnings and career paths, were strongly preferred by all, different respondents groups had distinct preferences according to their characteristics, suggesting the need for adoption of tailored packages of interventions.

Abstract Neuroscientists have observed both cells in the brain that fire at specific points in time, known as “time cells”, and cells whose activity steadily increases or decreases over time, known as “ramping cells”. It is speculated that time and ramping cells support temporal computations in the brain and carry mnemonic information. However, due to the limitations in animal experiments, it is difficult to determine how these cells really contribute to behavior. Here, we show that time cells and ramping cells naturally emerge in the recurrent neural networks of deep reinforcement learning models performing simulated interval timing and working memory tasks, which have learned to estimate expected rewards in the future. We show that these cells do indeed carry information about time and items stored in working memory, but they contribute to behavior in large part by providing a dynamic representation on which policy can be computed. Moreover, the information that they do carry depends on both the task demands and the variables provided to the models. Our results suggest that time cells and ramping cells could contribute to temporal and mnemonic calculations, but the way in which they do so may be complex and unintuitive to human observers.

Abstract Personalized medicine plays an important role in treatment optimization for COVID-19 patient management. Early treatment in patients at high risk of severe complications is vital to prevent death and ventilator use. Predicting COVID-19 clinical outcomes using machine learning may provide a fast and data-driven solution for optimizing patient care by estimating the need for early treatment. In addition, it is essential to accurately predict risk across demographic groups, particularly those underrepresented in existing models. Unfortunately, there is a lack of studies demonstrating the equitable performance of machine learning models across patient demographics. To overcome this existing limitation, we generate a robust machine learning model to predict patient-specific risk of death or ventilator use in COVID-19 positive patients using features available at the time of diagnosis. We establish the value of our solution across patient demographics, including gender and race. In addition, we improve clinical trust in our automated predictions by generating interpretable patient clustering, patient-level clinical feature importance, and global clinical feature importance within our large real-world COVID-19 positive patient dataset. We achieved 89.38% area under receiver operating curve (AUROC) performance for severe outcomes prediction and our robust feature ranking approach identified the presence of dementia as a key indicator for worse patient outcomes. We also demonstrated that our deep-learning clustering approach outperforms traditional clustering in separating patients by severity of outcome based on mutual information performance. Finally, we developed an application for automated and fair patient risk assessment with minimal manual data entry using existing data exchange standards.

This study compared carcass yield and cutout value of conventional beef and dairy cattle to high-yielding (HY) and low-yielding (LY) crossbred beef × dairy cattle and identified the contribution of carcass regions to carcass yield andcutout value among beef × dairy crossbreds. Carcasses of conventional beef, beef × dairy crossbred, and dairy cattle were selected according to industry-average slaughter endpoints for their cattle type. Carcasses were fabricated at a commercial processing facility, and weights of carcass components were obtained. Post hoc subsampling was used to segregate HY and LY beef × dairy crossbreds based on subprimal yield. Multiple linear regression was used to assess carcass yield and sub-primal cutout value between the 4 cattle types (n=21 to 26 per cattle type). Beef cattle and HY crossbreds produced 1.59 to 3.04 percentage units greater (P0.05) between HY crossbreds and beef cattle, and subprimal to fat was lesser (P beef cattle > LY crossbreds > dairy cattle. In beef × dairy cattle, subprimal to bone in the round contributed most greatly to an increase (P=0.02), by 3.79 USD/45.4 kg, in subprimal cutout value. Together, these results suggested carcass value of beef × dairy cattle may be maximized when cattle are harvested at a lesser overall fatness than conventional beef cattle and when considerable muscling, especially in the round, is achieved.

Abstract Information about species distributions is lacking in many regions of the world, forcing resource managers to answer complex ecological questions with incomplete data. Information gaps are compounded by climate change, driving ecological bottlenecks that can act as new demographic constraints on fauna. Here, we construct greater sandhill crane (Antigone canadensis tabida) summering range in western North America using movement data from 120 GPS‐tagged individuals to determine how landscape composition shaped their distributions. Landscape variables developed from remotely sensed data were combined with bird locations to model distribution probabilities. Additionally, land‐use and ownership were summarized within summer range as a measure of general bird use. Wetland variables identified as important predictors of bird distributions were evaluated in a post hoc analysis to measure long‐term (1984–2022) effects of climate‐driven surface water drying. Wetlands and associated agricultural practices accounted for 1.2% of summer range but were key predictors of occurrence. Bird distributions were structured by riparian floodplains that concentrated wetlands, and flood‐irrigated agriculture in otherwise arid and semi‐arid landscapes. Findings highlighted the role of private lands in greater sandhill crane ecology as they accounted for 78% of predicted distributions. Wetland drying observed in portions of the range from 1984 to 2022 represented an emerging ecological bottleneck that could limit future greater sandhill crane summer range. Study outcomes provide novel insight into the significance of ecosystem services provided by flood‐irrigated agriculture that supported nearly 60% of wetland resources used by birds. Findings suggest greater sandhill cranes function as a surrogate species for agroecology and climate change adaptation strategies seeking to reduce agricultural water use through improved efficiency while also maintaining distinct flood‐irrigation practices supporting greater sandhill cranes and other wetland‐dependent wildlife. We make our wetland and sandhill crane summering distributions available as interactive web‐based mapping tools to inform conservation design.

The COVID-19 pandemic impacted the mental health of more citizens globally than any previous modern viral outbreak. In response to the psychological challenges associated with COVID-19, the COVID Stress Scales (CSS) were developed to assess the presence and severity of COVID-related distress. The initial North American validation study of the CSS identified that the scale comprised five factors: danger and contamination fears, fear of socioeconomic consequences, xenophobia, checking and reassurance seeking, and traumatic stress symptoms. The CSS have since been validated across a multitude of international populations. However, findings support a five- and six-factor model. Methodological issues make interpreting most studies supporting a five-factor model challenging. The purpose of this study was to re-evaluate the factor structure of the CSS using data from North American samples, to assess for potential factorial invariance, and compare these results to cross-cultural findings. Multiple confirmatory factor analyses (mCFA) were conducted across 28 different groups (e.g., age, ethnicity/race, sex) from two large independent North American samples from 2020 (n = 6827) and 2021 (n = 5787), assessing the fit indices of the five-, six-, and alternative-factor model of the CSS. The current results provide evidence for factorial invariance of the six-factor model of the CSS across different North American demographics and highlight potential challenges in interpreting the results of studies that have supported a five-factor model of the CSS.

Streptococcus pyogenes is a human-specific pathogen that commonly colonizes the upper respiratory tract and skin, causing a wide variety of diseases ranging from pharyngitis to necrotizing fasciitis and toxic shock syndrome. S. pyogenes has a repertoire of secreted virulence factors that promote infection and evasion of the host immune system including the cytolysins streptolysin O (SLO) and streptolysin S (SLS). S. pyogenes does not naturally infect the upper respiratory tract of mice although mice transgenic for MHC class II human leukocyte antigens (HLA) become highly susceptible. Here we used HLA-transgenic mice to assess the role of both SLO and SLS during both nasopharyngeal and skin infection. Using S. pyogenes MGAS8232 as a model strain, we found that an SLS-deficient strain exhibited a 100-fold reduction in bacterial recovery from the nasopharynx and a 10-fold reduction in bacterial burden in the skin, whereas an SLO-deficient strain did not exhibit any infection defects in these models. Furthermore, depletion of neutrophils significantly restored the bacterial burden of the SLS-deficient bacteria in skin, but not in the nasopharynx. In mice nasally infected with the wildtype S. pyogenes, there was a marked change in localization of the tight junction protein ZO-1 at the site of infection, demonstrating damage to the nasal epithelia that was absent in mice infected with the SLS-deficient strain. Overall, we conclude that SLS is required for the establishment of nasopharyngeal infection and skin infection in HLA-transgenic mice by S. pyogenes MGAS8232 and provide evidence that SLS contributes to nasopharyngeal infection through the localized destruction of nasal epithelia.

Fetal alcohol spectrum disorders (FASD) are among the most common neurodevelopmental disorders and substantially impact public health. FASD can affect people of all races and ethnicities; however, there are important racial and ethnic disparities in alcohol-exposed pregnancy prevention, assessment and diagnosis of FASD, and interventions to support individuals with FASD and their families. In this article we use the Dis/Ability Studies and Critical Race Theory (Dis/Crit) framework to structure the exploration of disparities and possible solutions within these three areas (prevention, diagnosis, intervention). Dis/Crit provides a guide to understanding the intersection of dis/ability and race, while framing both as social constructs. Following the Dis/Crit framework, the systemic, historical, and contemporary racism and ableism present in psychological care is further discussed. We aim to elucidate these racial and ethnic disparities within the fields of psychology and neuropsychology through the Dis/Crit framework and provide potential points of action to reduce these disparities.

Background Sedentary behavior is a recognized mortality risk factor. The novel and validated convolutional neural network hip accelerometer posture algorithm highly accurately classifies sitting and postural changes compared with accelerometer count cut points. We examined the prospective associations of convolutional neural network hip accelerometer posture–classified total sitting time and mean sitting bout duration with all‐cause and cardiovascular disease (CVD) death. Methods and Results Women (n=5856; mean±SD age, 79±7 years; 33% Black women, 17% Hispanic or Latina women, 50% White women) in the Women's Health Initiative Objective Physical Activity and Cardiovascular Health (OPACH) Study wore the ActiGraph GT3X+ for ~7 days from May 2012 to April 2014 and were followed through February 19, 2022 for all‐cause and CVD death. The convolutional neural network hip accelerometer posture algorithm classified total sitting time and mean sitting bout duration from GT3X+ output. Over follow‐up (median, 8.4 years; range, 0.1–9.9), there were 1733 deaths (632 from CVD). Adjusted Cox regression hazard ratios (HRs) comparing women in the highest total sitting time quartile (>696 min/d) to those in the lowest (15 minutes) to the shortest (

Summary: Monocytes can develop an exhausted memory state characterized by reduced differentiation, pathogenic inflammation, and immune suppression that drives immune dysregulation during sepsis. Chromatin alterations, notably via histone modifications, underlie innate immune memory, but the contribution of DNA methylation remains poorly understood. Using an ex vivo sepsis model, we show altered DNA methylation throughout the genome of exhausted monocytes, including genes implicated in immune dysregulation during sepsis and COVID-19 infection (e.g., Plac8). These changes are recapitulated in septic mice induced by cecal slurry injection. Methylation profiles developed in septic mice are maintained during ex vivo culture, supporting the involvement of DNA methylation in stable monocyte exhaustion memory. Methylome reprogramming is driven in part by Wnt signaling inhibition in exhausted monocytes and can be reversed with DNA methyltransferase inhibitors, Wnt agonists, or immune training molecules. Our study demonstrates the significance of altered DNA methylation in the maintenance of stable monocyte exhaustion memory.

Abstract Background Forest conservation is a major global policy goal, due to the role forests play in climate change mitigation and biodiversity conservation. It is well recognized that the introduction of policies, whether aimed at forest conservation or with other objectives, has the potential to trigger unintended outcomes, such as displacement or leakage, which can undermine policy objectives. However, a set of outcomes that has escaped detailed scrutiny are anticipatory forest use behaviours, emerging when forest stakeholders anticipate policy implementation, deploying for example pre-emptive forest clearing, resulting in detrimental environmental outcomes. Lack of understanding of the extent and sectorial scope of these behaviours prevents us from devising strategies to address their potential detrimental consequences. Methods This protocol presents the methodology that will be followed to conduct a systematic map to identify, compile, review and describe the evidence available on anticipatory forest use behaviours in the context of policy introduction around the world. We will use two complementary search strategies, which we have tested before submitting this protocol. First, a systematic bibliographic search, and second, a citation chase approach. We will include articles based on a pre-defined set of criteria defined according to a Population, Intervention and Outcome (i.e. PIO) design. To support identification of knowledge gaps and clusters, we will report results of the systematic map in a narrative synthesis, an evidence atlas and other visualisations.

Abstract Background Cells orchestrate histone biogenesis with strict temporal and quantitative control. To efficiently regulate histone biogenesis, the repetitive Drosophila melanogaster replication-dependent histone genes are arrayed and clustered at a single locus. Regulatory factors concentrate in a nuclear body known as the histone locus body (HLB), which forms around the locus. Historically, HLB factors are largely discovered by chance, and few are known to interact directly with DNA. It is therefore unclear how the histone genes are specifically targeted for unique and coordinated regulation. Results To expand the list of known HLB factors, we performed a candidate-based screen by mapping 30 publicly available ChIP datasets of 27 unique factors to the Drosophila histone gene array. We identified novel transcription factor candidates, including the Drosophila Hox proteins Ultrabithorax (Ubx), Abdominal-A (Abd-A), and Abdominal-B (Abd-B), suggesting a new pathway for these factors in influencing body plan morphogenesis. Additionally, we identified six other factors that target the histone gene array: JIL-1, hormone-like receptor 78 (Hr78), the long isoform of female sterile homeotic (1) (fs(1)h) as well as the general transcription factors TBP associated factor 1 (TAF-1), Transcription Factor IIB (TFIIB), and Transcription Factor IIF (TFIIF). Conclusions Our foundational screen provides several candidates for future studies into factors that may influence histone biogenesis. Further, our study emphasizes the powerful reservoir of publicly available datasets, which can be mined as a primary screening technique.

Abstract With concurrent global epidemics of chronic pain and opioid use disorders, there is a critical need to identify, target and manipulate specific cell populations expressing the mu-opioid receptor (MOR). However, available tools and transgenic models for gaining long-term genetic access to MOR+ neural cell types and circuits involved in modulating pain, analgesia and addiction across species are limited. To address this, we developed a catalog of MOR promoter (MORp) based constructs packaged into adeno-associated viral vectors that drive transgene expression in MOR+ cells. MORp constructs designed from promoter regions upstream of the mouse Oprm1 gene (mMORp) were validated for transduction efficiency and selectivity in endogenous MOR+ neurons in the brain, spinal cord, and periphery of mice, with additional studies revealing robust expression in rats, shrews, and human induced pluripotent stem cell (iPSC)-derived nociceptors. The use of mMORp for in vivo fiber photometry, behavioral chemogenetics, and intersectional genetic strategies is also demonstrated. Lastly, a human designed MORp (hMORp) efficiently transduced macaque cortical OPRM1+ cells. Together, our MORp toolkit provides researchers cell type specific genetic access to target and functionally manipulate mu-opioidergic neurons across a range of vertebrate species and translational models for pain, addiction, and neuropsychiatric disorders.

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information, with its application to neuroscience termed neuroinformatics. Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms, which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases. Importantly, integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile. In this review, we first summarize data mining studies utilizing datasets from the individual type of omics analysis, including epigenetics/epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and spatial omics, pertaining to Alzheimer's disease, Parkinson's disease, and multiple sclerosis. We then discuss multi-omics integration approaches, including independent biological integration and unsupervised integration methods, for more intuitive and informative interpretation of the biological data obtained across different omics layers. We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks. Finally, we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery, therapeutic development, and elucidation of disease mechanisms. We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

Aspergillus terreus has attracted interest due to its application in industrial biotechnology, particularly for the production of itaconic acid and bioactive secondary metabolites. As related species also seem to possess a prosperous secondary metabolism, they are of high interest for genome mining and exploitation. Here, we present draft genome sequences for six species from Aspergillus section Terrei and one species from Aspergillus section Nidulantes. Whole-genome phylogeny confirmed that section Terrei is monophyletic. Genome analyses identified between 70 and 108 key secondary metabolism genes in each of the genomes of section Terrei, the highest rate found in the genus Aspergillus so far. The respective enzymes fall into 167 distinct families with most of them corresponding to potentially unique compounds or compound families. Moreover, 53% of the families were only found in a single species, which supports the suitability of species from section Terrei for further genome mining. Intriguingly, this analysis, combined with heterologous gene expression and metabolite identification, suggested that species from section Terrei use a strategy for UV protection different to other species from the genus Aspergillus. Section Terrei contains a complete plant polysaccharide degrading potential and an even higher cellulolytic potential than other Aspergilli, possibly facilitating additional applications for these species in biotechnology.

We provide sufficient conditions on the primitives of a class of discontinuous Bayesian games such that all games in the class share equilibria. If a Bayesian game in the class also satisfies a weak efficiency condition, then we show its normal form is better-reply secure. The invariance property then provides an existence result for all Bayesian games in the class. Results are shown for both pure strategy and behavioral strategy equilibrium. We illustrate the application of the results with an example of a class of contests with bid caps.

Eutrophication of inland lakes poses various societal and ecological threats, making water quality monitoring crucial. Satellites provide a comprehensive and cost-effective supplement to traditional in situ sampling. The Sentinel-2 MultiSpectral Instrument (S2 MSI) offers unique spectral bands positioned to quantify chlorophyll a, a water-quality and trophic-state indicator, along with fine spatial resolution, enabling the monitoring of small waterbodies. In this study, two algorithms—the Maximum Chlorophyll Index (MCI) and the Normalized Difference Chlorophyll Index (NDCI)—were applied to S2 MSI data. They were calibrated and validated using in situ chlorophyll a measurements for 103 lakes across the contiguous U.S. Both algorithms were tested using top-of-atmosphere reflectances (ρt), Rayleigh-corrected reflectances (ρs), and remote sensing reflectances (Rrs). MCI slightly outperformed NDCI across all reflectance products. MCI using ρt showed the best overall performance, with a mean absolute error factor of 2.08 and a mean bias factor of 1.15. Conversion of derived chlorophyll a to trophic state improved the potential for management applications, with 82% accuracy using a binary classification. We report algorithm-to-chlorophyll-a conversions that show potential for application across the U.S., demonstrating that S2 can serve as a monitoring tool for inland lakes across broad spatial scales.

Vitamin D3 is a steroid hormone that confers anti-tumorigenic properties in prostate cells. Serum vitamin D3 deficiency has been associated with advanced prostate cancer (PCa), particularly affecting African American (AA) men. Therefore, elucidating the pleiotropic effects of vitamin D on signaling pathways, essential to maintaining non-malignancy, may provide additional drug targets to mitigate disparate outcomes for men with PCa, especially AA men. We conducted RNA sequencing on an AA non-malignant prostate cell line, RC-77N/E, comparing untreated cells to those treated with 10 nM of vitamin D3 metabolite, 1α,25(OH)2D3, at 24 h. Differential gene expression analysis revealed 1601 significant genes affected by 1α,25(OH)2D3 treatment. Pathway enrichment analysis predicted 1α,25(OH)2D3- mediated repression of prostate cancer, cell proliferation, actin cytoskeletal, and actin-related signaling pathways (p < 0.05). Prioritizing genes with vitamin D response elements and associating expression levels with overall survival (OS) in The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA PRAD) cohort, we identified ANLN (Anillin) and ECT2 (Epithelial Cell Transforming 2) as potential prognostic PCa biomarkers. Both genes were strongly correlated and significantly downregulated by 1α,25(OH)2D3 treatment, where low expression was statistically associated with better overall survival outcomes in the TCGA PRAD public cohort. Increased ANLN and ECT2 mRNA gene expression was significantly associated with PCa, and Gleason scores using both the TCGA cohort (p < 0.05) and an AA non-malignant/tumor-matched cohort. Our findings suggest 1α,25(OH)2D3 regulation of these biomarkers may be significant for PCa prevention. In addition, 1α,25(OH)2D3 could be used as an adjuvant treatment targeting actin cytoskeleton signaling and actin cytoskeleton-related signaling pathways, particularly among AA men.

Abstract The apical dendrites of pyramidal neurons in sensory cortex receive primarily top-down signals from associative and motor regions, while cell bodies and nearby dendrites are heavily targeted by locally recurrent or bottom-up inputs from the sensory periphery. Based on these differences, a number of theories in computational neuroscience postulate a unique role for apical dendrites in learning. However, due to technical challenges in data collection, little data is available for comparing the responses of apical dendrites to cell bodies over multiple days. Here we present a dataset collected through the Allen Institute Mindscope’s OpenScope program that addresses this need. This dataset comprises high-quality two-photon calcium imaging from the apical dendrites and the cell bodies of visual cortical pyramidal neurons, acquired over multiple days in awake, behaving mice that were presented with visual stimuli. Many of the cell bodies and dendrite segments were tracked over days, enabling analyses of how their responses change over time. This dataset allows neuroscientists to explore the differences between apical and somatic processing and plasticity.

Absenteeism by doctors in public healthcare facilities in rural Bangladesh is a form of chronic rule-breaking and is recognised as a critical problem by the government. We explored the factors underlying this phenomenon from doctors' perspectives. We conducted a facility-based cross-sectional survey in four government hospitals in Dhaka, Bangladesh. Junior doctors with experience in rural postings were interviewed to collect data on socio-demographic characteristics, work and living experience at the rural facilities, and associations with professional and social networks. Multiple logistic regression was used to determine the factors associated with rural retention. Of 308 respondents, 74% reported having served each term of their rural postings without interruptions. The main reasons for absenteeism reported by those who interrupted rural postings were formal training opportunities (65%), family commitments (41%), and a miscellaneous group of others (17%). Almost half of the respondents reported unmanageable workloads. Most (96%) faced challenges in their last rural posting, such as physically unsafe environments (70%), verbally abusive behaviour by patients/caregivers (67%) and absenteeism by colleagues that impacted them (48%). Respondents who did not serve their entire rural posting were less likely to report an unmanageable workload than respondents who did (AOR 0.39, 95% CI 0.22-0.70). Respondents with connections to influential people in the local community had a 2.4 times higher chance of serving in rural facilities without interruption than others (AOR 2.40, 95% CI 1.26-4.57). Our findings demonstrate that absenteeism is not universal and depends upon doctors' socio-political networks. Policy interventions rarely target unsupportive or threatening behaviour by caregivers and community members, a pivotal disincentive to doctors' willingness to work in underserved rural areas. Policy responses must promote opportunities for doctors with weak networks who are willing to attend work with appropriate support.

BackgroundLatent class analysis (LCA) identifies distinct groups within a heterogeneous population, but its application to accelerometry-assessed physical activity and sedentary behavior has not been systematically explored. We conducted a systematic scoping review to describe the application of LCA to accelerometry.MethodsComprehensive searches in PubMed, Web of Science, CINHAL, SPORTDiscus, and Embase identified studies published through December 31, 2021. Using Covidence, two researchers independently evaluated inclusion criteria and discrepancies were resolved by consensus. Studies with LCA applied to accelerometry or combined accelerometry/self-reported measures were selected. Data extracted included study characteristics and both accelerometry and LCA methods.ResultsOf 2555 papers found, 66 full-text papers were screened, and 12 papers (11 cross-sectional, 1 cohort) from 8 unique studies were included. Study sample sizes ranged from 217-7931 (mean 2249, standard deviation 2780). Across 8 unique studies, latent class variables included measures of physical activity (100%) and sedentary behavior (75%). About two-thirds (63%) of the studies used accelerometry only and 38% combined accelerometry and self-report to derive latent classes. The accelerometer-based variables in the LCA model included measures by day of the week (38%), weekday vs. weekend (13%), weekly average (13%), dichotomized minutes/day (13%), sex specific z-scores (13%), and hour-by-hour (13%). The criteria to guide the selection of the final number of classes and model fit varied across studies, including Bayesian Information Criterion (63%), substantive knowledge (63%), entropy (50%), Akaike information criterion (50%), sample size (50%), Bootstrap likelihood ratio test (38%), and visual inspection (38%). The studies explored up to 5 (25%), 6 (38%), or 7+ (38%) classes, ending with 3 (50%), 4 (13%), or 5 (38%) final classes.ConclusionsThis review explored the application of LCA to physical activity and sedentary behavior and identified areas of improvement for future studies leveraging LCA. LCA was used to identify unique groupings as a data reduction tool, to combine self-report and accelerometry, and to combine different physical activity intensities and sedentary behavior in one LCA model or separate models.

Introduction The willingness to pay per quality-adjusted life year gained (WTP/Q) is commonly used to determine whether an intervention is cost-effective in health technology assessment. This study aimed to evaluate the WTP/Q for different disease scenarios in a Chinese population.Methods The study employed a quadruple-bounded dichotomous choice contingent valuation method to estimate the WTP/Q in the general public. The estimation was conducted across chronic, terminal and rare disease scenarios. Face-to-face interviews were conducted in a Chinese general population recruited from Jiangsu province using a convenience sampling method. Interval regression analysis was performed to determine the relationship between respondents’ demographic and socioeconomic conditions and WTP/Q. Sensitivity analyses of removing protest responses and open question analyses were conducted.Results A total of 896 individuals participated in the study. The WTP/Q thresholds were 128 000 Chinese renminbi (RMB) ($36 364) for chronic diseases, 149 500 RMB ($42 472) for rare diseases and 140 800 RMB ($40 000) for terminal diseases, equivalent to 1.76, 2.06 and 1.94 times the gross domestic product per capita in China, respectively. The starting bid value had a positive influence on participants’ WTP/Q. Additionally, residing in an urban area (p

Most ultrasound-based processes root in empirical approaches. Because nearly all advances have been conducted in aqueous systems, there exists a paucity of information on sonoprocessing in other solvents, particularly ionic liquids (ILs). In this work, we modelled an ultrasonic horn-type sonoreactor and investigated the effects of ultrasound power, sonotrode immersion depth, and solvent’s thermodynamic properties on acoustic cavitation in nine imidazolium-based and three pyrrolidinium-based ILs. The model accounts for bubbles, acoustic impedance mismatch at interfaces, and treats the ILs as incompressible, Newtonian, and saturated with argon. Following a statistical analysis of the simulation results, we determined that viscosity and ultrasound input power are the most significant variables affecting the intensity of the acoustic pressure field (P), the volume of cavitation zones (V), and the magnitude of the maximum acoustic streaming surface velocity (u). V and u increase with the increase of ultrasound input power and the decrease in viscosity, whereas the magnitude of negative P decreases as ultrasound power and viscosity increase. Probe immersion depth positively correlates with V, but its impact on P and u is insignificant. 1-alkyl-3-methylimidazolium-based ILs yielded the largest V and the fastest acoustic jets – 0.77 cm3 and 24.4 m s−1 for 1-ethyl-3-methylimidazolium chloride at 60 W. 1-methyl-3-(3-sulfopropyl)-imidazolium-based ILs generated the smallest V and lowest u – 0.17 cm3 and 1.7 m s−1 for 1-methyl-3-(3-sulfopropyl)-imidazolium p-toluene sulfonate at 20 W. Sonochemiluminescence experiments validated the model.

Identification of enteric bacteria species by whole genome sequence (WGS) analysis requires a rapid and an easily standardized approach. We leveraged the principles of average nucleotide identity using MUMmer (ANIm) software, which calculates the percent bases aligned between two bacterial genomes and their corresponding ANI values, to set threshold values for determining species consistent with the conventional identification methods of known species. The performance of species identification was evaluated using two datasets: the Reference Genome Dataset v2 (RGDv2), consisting of 43 enteric genome assemblies representing 32 species, and the Test Genome Dataset (TGDv1), comprising 454 genome assemblies which is designed to represent all species needed to query for identification, as well as rare and closely related species. The RGDv2 contains six Campylobacter spp., three Escherichia/Shigella spp., one Grimontia hollisae, six Listeria spp., one Photobacterium damselae, two Salmonella spp., and thirteen Vibrio spp., while the TGDv1 contains 454 enteric bacterial genomes representing 42 different species. The analysis showed that, when a standard minimum of 70% genome bases alignment existed, the ANI threshold values determined for these species were ≥95 for Escherichia/Shigella and Vibrio species, ≥93% for Salmonella species, and ≥92% for Campylobacter and Listeria species. Using these metrics, the RGDv2 accurately classified all validation strains in TGDv1 at the species level, which is consistent with the classification based on previous gold standard methods.

Abstract Pseudomonas putida has emerged as a promising host for the conversion of biomass‐derived sugars and aromatic intermediates into commercially relevant biofuels and bioproducts. Most of the strain development studies previously published have focused on P. putida KT2440, which has been engineered to produce a variety of non‐native bioproducts. However, P. putida is not capable of metabolizing pentose sugars, which can constitute up to 25% of biomass hydrolysates. Related P. putida isolates that metabolize a larger fraction of biomass‐derived carbon may be attractive as complementary hosts to P. putida KT2440. Here we describe genetic tool development for P. putida M2, a soil isolate that can metabolize pentose sugars. The functionality of five inducible promoter systems and 12 ribosome binding sites was assessed to regulate gene expression. The utility of these expression systems was confirmed by the production of indigoidine from C6 and C5 sugars. Chromosomal integration and expression of non‐native genes was achieved by using chassis‐independent recombinase‐assisted genome engineering (CRAGE) for single‐step gene integration of biosynthetic pathways directly into the genome of P. putida M2. These genetic tools provide a foundation to develop hosts complementary to P. putida KT2440 and expand the ability of this versatile microbial group to convert biomass to bioproducts.

In the original publication [...]

Laccases from white-rot fungi catalyze lignin depolymerization, a critical first step to upgrading lignin to valuable biodiesel fuels and chemicals. In this study, a wildtype laccase from the basidiomycete Fomitiporia mediterranea (Fom_lac) and a variant engineered to have a carbohydrate-binding module (Fom_CBM) were studied for their ability to catalyze cleavage of β-O-4′ ether and C–C bonds in phenolic and non-phenolic lignin dimers using a nanostructure-initiator mass spectrometry-based assay. Fom_lac and Fom_CBM catalyze β-O-4′ ether and C–C bond breaking, with higher activity under acidic conditions (pH < 6). The potential of Fom_lac and Fom_CBM to enhance saccharification yields from untreated and ionic liquid pretreated pine was also investigated. Adding Fom_CBM to mixtures of cellulases and hemicellulases improved sugar yields by 140% on untreated pine and 32% on cholinium lysinate pretreated pine when compared to the inclusion of Fom_lac to the same mixtures. Adding either Fom_lac or Fom_CBM to mixtures of cellulases and hemicellulases effectively accelerates enzymatic hydrolysis, demonstrating its potential applications for lignocellulose valorization. We postulate that additional increases in sugar yields for the Fom_CBM enzyme mixtures were due to Fom_CBM being brought more proximal to lignin through binding to either cellulose or lignin itself.

Background Governments use return-of-service (RoS) schemes to train, employ and retain health professionals in the public sector. We determined the effectiveness of RoS schemes in four Southern African countries.Methods This retrospective cohort study used databases of RoS beneficiaries from South Africa, Botswana, Eswatini and Lesotho. We ascertained the period of funding for beneficiaries between 2000 and 2010, study programme, selection criteria, study country and if they completed their studies. Records were sought to track beneficiaries’ service and fulfilment of their RoS obligations. Data were sought at the provincial level in South Africa and nationally for the other three countries. Binomial logistics regression and Kaplan-Meier survival estimates were used to determine risk factors and predictors of defaulting.Results Most beneficiary enrolment (eg, decision on why they were funded, socioeconomic status, disability status, high school results) and service data (eg, health facilities where they worked, how long they worked at each health facility, movement between health facilities) were not available. A total of 5616 beneficiaries were drawn from the four countries’ databases. Of those with full data available, 21.7% (229/1056) were retained/served beyond their obligatory period and 20.2% (213/1056) were still serving. A total of 24.3% (95% CI: 21.7% to 26.9%; n=257/1056) of beneficiaries in the final subanalysis of two South African provinces fulfilled their contractual obligations. Only 32.2% (277/861) of beneficiaries undertook internship within their funding provinces. Governments needed to fund six beneficiaries to have one beneficiary complete their contractual obligation if they undertook internship outside their province.Conclusion Record keeping in all countries was poor, hampering the effectiveness of RoS schemes. Of the units with full data available, the retention rate was below 25%, and internship being undertaken outside the funding province was associated with higher defaulter rates, calling for a policy overhaul.

Summary: Maximizing the production of heterologous biomolecules is a complex problem that can be addressed with a systems-level understanding of cellular metabolism and regulation. Specifically, growth-coupling approaches can increase product titers and yields and also enhance production rates. However, implementing these methods for non-canonical carbon streams is challenging due to gaps in metabolic models. Over four design-build-test-learn cycles, we rewire Pseudomonas putida KT2440 for growth-coupled production of indigoidine from para-coumarate. We explore 4,114 potential growth-coupling solutions and refine one design through laboratory evolution and ensemble data-driven methods. The final growth-coupled strain produces 7.3 g/L indigoidine at 77% maximum theoretical yield in para-coumarate minimal medium. The iterative use of growth-coupling designs and functional genomics with experimental validation was highly effective and agnostic to specific hosts, carbon streams, and final products and thus generalizable across many systems.

Ionic liquids (ILs) are seen as a more sustainable alternative to volatile organic solvents that are accelerating innovations in many industries such as energy storage, separations, and bioprocessing. The ability to effectively deconstruct lignocellulosic biomass is a significant hurdle in the biorefining/bioprocessing industry and presents limitations towards the commercial production of bioproducts (such as biofuels, biomaterials, etc.). Certain ILs have been shown to promote effective lignin removal, cellulose recovery, and sugar yields from various biomass feedstocks such as corn stover, wheat straw, sugarcane bagasse, sorghum, switchgrass, miscanthus, poplar, pine, eucalyptus, and certain mixtures of municipal solid waste. However, these improvements are often counteracted by the limited biocompatibility of ILs, which results in an IL-induced reduction in enzyme activity and stability—an important downstream step in the conversion of biomass to biofuels/bioproducts. As a result, significant efforts have been made to discover and engineer compatible enzyme-IL systems and to improve our understanding on the effect that these ILs have on these systems. This review seeks to examine the impact of ionic liquids on enzymes involved in lignocellulosic biomass deconstruction, with a specific focus on their relevance in the context of pretreatment. Beyond presenting an overview of the ionic liquid pretreatment landscape, we outline the main factors that influence enzyme activity and stability in the presence of ILs This data is consolidated and analyzed to apply this body of knowledge towards new innovations that could lead to improvements in the processing of biomass to biofuels and bioproducts.

Summary: During binocular rivalry (BR) only one eye’s view is perceived. Neural underpinnings of BR are debated. Recent studies suggest that primary visual cortex (V1) initiates BR. One trigger might be response suppression across most V1 neurons at the onset of BR. Here, we utilize a variant of BR called binocular rivalry flash suppression (BRFS) to test this hypothesis. BRFS is identical to BR, except stimuli are shown with a ∼1s delay. If V1 response suppression was required to initiate BR, it should occur during BRFS as well. To test this, we compared V1 spiking in two macaques observing BRFS. We found that BRFS resulted in response facilitation rather than response suppression across V1 neurons. However, BRFS still reduces responses in a subset of V1 neurons due to the adaptive effects of asynchronous stimulus presentation. We argue that this selective response suppression could serve as an alternate initiator of BR.

Abstract Lignin, the second most abundant biopolymer found in nature, has emerged as a potential source of sustainable fuels, chemicals, and materials. Finding suitable solvents, as well as technologies for efficient and affordable lignin dissolution and depolymerization, are major obstacles in the conversion of lignin to value-added products. Certain ionic liquids (ILs) are capable of dissolving and depolymerizing lignin but designing and developing an effective IL for lignin dissolution remains quite challenging. To address this issue, the COnductor-like Screening MOdel for Real Solvents (COSMO-RS) model was used to screen 5670 ILs by computing logarithmic activity coefficients (ln(γ)) and excess enthalpies (H E ) of lignin, respectively. Based on the COSMO-RS computed thermodynamic properties (ln(γ) and H E ) of lignin, anions such as acetate, methyl carbonate, octanoate, glycinate, alaninate, and lysinate in combination with cations like tetraalkylammonium, tetraalkylphosphonium, and pyridinium are predicted to be suitable solvents for lignin dissolution. The dissolution properties such as interaction energy between anion and cation, viscosity, Hansen solubility parameters, dissociation constants, and Kamlet–Taft parameters of selected ILs were evaluated to assess their propensity for lignin dissolution. Furthermore, molecular dynamics (MD) simulations were performed to understand the structural and dynamic properties of tetrabutylammonium [TBA]+-based ILs and lignin mixtures and to shed light on the mechanisms involved in lignin dissolution. MD simulation results suggested [TBA]+-based ILs have the potential to dissolve lignin because of their higher contact probability and interaction energies with lignin when compared to cholinium lysinate.

Abstract Background Lignocellulosic resources are promising feedstocks for the manufacture of bio-based products and bioenergy. However, the inherent recalcitrance of biomass to conversion into simple sugars currently hinders the deployment of advanced bioproducts at large scale. Lignin is a primary contributor to biomass recalcitrance as it protects cell wall polysaccharides from degradation and can inhibit hydrolytic enzymes via non-productive adsorption. Several engineering strategies have been designed to reduce lignin or modify its monomeric composition. For example, expression of bacterial 3-dehydroshikimate dehydratase (QsuB) in poplar trees resulted in a reduction in lignin due to redirection of metabolic flux toward 3,4-dihydroxybenzoate at the expense of lignin. This reduction was accompanied with remarkable changes in the pools of aromatic compounds that accumulate in the biomass. Results The impact of these modifications on downstream biomass deconstruction and conversion into advanced bioproducts was evaluated in the current study. Using ionic liquid pretreatment followed by enzymatic saccharification, biomass from engineered trees released more glucose and xylose compared to wild-type control trees under optimum conditions. Fermentation of the resulting hydrolysates using Rhodosporidium toruloides strains engineered to produce α-bisabolene, epi-isozizaene, and fatty alcohols showed no negative impact on cell growth and yielded higher titers of bioproducts (as much as + 58%) in the case of QsuB transgenics trees. Conclusion Our data show that low-recalcitrant poplar biomass obtained with the QsuB technology has the potential to improve the production of advanced bioproducts.

Abstract Background Fetal alcohol spectrum disorder (FASD) is a lifelong condition. Early interventions targeting core neurocognitive deficits have the potential to confer long-term neurodevelopmental benefits. Time-targeted choline supplementation is one such intervention that has been shown to provide neurodevelopmental benefits that emerge with age during childhood. We present a long-term follow-up study evaluating the neurodevelopmental effects of early choline supplementation in children with FASD approximately 7 years on average after an initial efficacy trial. Methods The initial study was a randomized, double-blind, placebo-controlled trial of choline vs. placebo in 2.5 to 5 year olds with FASD. Participants in this long-term follow-up study include 18 children (9 placebo; 9 choline) seen 7 years on average following initial trial completion. The mean age at follow-up was 11.0 years old. Diagnoses were 28% fetal alcohol syndrome (FAS), 28% partial FAS, and 44% alcohol-related neurodevelopmental disorder. The follow-up included measures of executive functioning and an MRI scan. Results Children who received choline had better performance on several tasks of lower-order executive function (e.g., processing speed) and showed higher white matter microstructure organization (i.e., greater axon coherence) in the splenium of the corpus callosum compared to the placebo group. Conclusions These preliminary findings, although exploratory at this stage, highlight potential long-term benefits of choline as a neurodevelopmental intervention for FASD and suggest that choline may affect white matter development, representing a potential target of choline in this population. Trial registration Prior to enrollment, this trial was registered with clinicaltrials.gov ( NCT01149538 ) on June 23, 2010.

Abstract Background Rhodosporidium toruloides is capable of co-utilization of complex carbon sources and robust growth from lignocellulosic hydrolysates. This oleaginous yeast is therefore an attractive host for heterologous production of valuable bioproducts at high titers from low-cost, deconstructed biomass in an economically and environmentally sustainable manner. Here we demonstrate this by engineering R. toruloides to produce the polyketide triacetic acid lactone (TAL) directly from unfiltered hydrolysate deconstructed from biomass with minimal unit process operations. Results Introduction of the 2-pyrone synthase gene into R. toruloides enabled the organism to produce 2.4 g/L TAL from simple media or 2.0 g/L from hydrolysate produced from sorghum biomass. Both of these titers are on par with titers from other better-studied microbial hosts after they had been heavily engineered. We next demonstrate that filtered hydrolysates produced from ensiled sorghum are superior to those derived from dried sorghum for TAL production, likely due to the substantial organic acids produced during ensiling. We also demonstrate that the organic acids found in ensiled biomass can be used for direct synthesis of ionic liquids within the biomass pretreatment process, enabling consolidation of unit operations of in-situ ionic liquid synthesis, pretreatment, saccharification, and fermentation into a one-pot, separations-free process. Finally, we demonstrate this consolidation in a 2 L bioreactor using unfiltered hydrolysate, producing 3.9 g/L TAL. Conclusion Many steps involved in deconstructing biomass into fermentable substrate can be combined into a distinct operation, and directly fed to cultures of engineered R. toruloides cultures for subsequent valorization into gram per liter titers of TAL in a cost-effective manner.

While agreeing with the science of the “planetary boundaries” work of Johan Rockström and colleagues, as well as their normative support for political measures to restrict the human economy to the realm inside those boundaries, a recent article by Brand et al. in this journal criticizes the former mainly on the grounds that they pay too little attention to capitalism’s alleged growth imperative and to certain technocratic and/or global-only interpretations to which the planetary boundaries framework is dangerously open. I argue that Brand et al. do not refute or disagree with Rockström et al., as they claim, but rather point out what the latter omit. Rockström et al. consciously limited the scope of their work, and therefore a polemical criticism of their omissions is not justified. I also argue against the centrality of the concept “capitalism” in Brand et al.’s critique, claiming that growth/degrowth analyses and strategies for degrowth do not need to go into the issues of capitalism vs. alternatives to it because drivers of growth are deeper than such systems concepts allow us to investigate. Capitalism and socialism do explain some things, but mainly, they themselves have to be explained in a full analysis of both over-growth and what to do about it politically in democracies. Shifts toward acceptance of material-energy limitations must be psychological and social, whatever the economic system’s rules on such things as ownership of the means of production, economic-power equality, the money system, or macro-economic incentives to growth.