bluuebunny/crossref_metadata_2025 huggingface dataset:
Risk Profile of Thanksgiving Gatherers and Subsequent SARS-CoV2 Testing and Diagnosis
Authors: You William , Rane Madhura , Zimba Rebecca , Berry Amanda , Kulkarni Sarah , Westmoreland Drew , Parcesepe Angela , Chang Mindy , Maroko Andrew , Kochhar Shivani , Mirzayi Chloe , Grov Christian , Nash Denis
Published: April 2021

Background

During Fall 2020 in the United States (U.S.), despite high COVID-19 case numbers and recommendations from public health officials not to travel and gather with individuals outside one’s household, millions of people gathered for Thanksgiving. The objective of this study was to understand if individuals’ behaviors and risk perceptions influenced their decision to gather, and if they did gather, their subsequent test seeking and diagnoses.

Methods

Participants were part of the CHASING COVID Cohort study - a U.S. national prospective cohort. The study sample consisted of participants who completed routine questionnaires before and after Thanksgiving. Non-pharmaceutical interventions (NPIs) use informed behavioral risk scores and a score of perceived risk of COVID-19 were assigned to each participant. Multinomial logistic regression models were used to assess the association between higher risk behaviors and gathering with other households, and the association of gathering with subsequent testing and test positivity.

Results

A total of 1,932 (40.5%) cohort participants spent Thanksgiving with individuals from at least one other household. Participants with higher behavioral risk scores had greater odds of gathering with one other household (aOR: 2.35, 95% CI: 2.0, 2.7), two other households (aOR: 4.54, 95% CI: 3.7, 5.6), and three or more other households (aOR: 5.44, 95% CI: 4.1, 7.2). Participants perceiving COVID-19 as a low-risk to themselves and others had greater odds of gathering with one other household (aOR: 1.12, 95% CI: 0.97, 1.3), two other households (aOR: 1.39, 95% CI: 1.1, 1.7), and three or more other households (aOR: 1.86, 95% CI: 1.4, 2.4). Those who spent Thanksgiving with one or more other households had 1.23 times greater odds (95% CI: 1.1, 1.4) of having a COVID-19 test afterward. There was no association between gathering for Thanksgiving and subsequent COVID-19 test positivity or developing COVID-19 symptoms.

Conclusions

Those who gathered with other households for Thanksgiving tended to engage in higher-risk activities. Thanksgiving gathering with other households was not associated with subsequently testing positive for COVID-19, but only a small proportion obtained post-travel testing. Public health messaging should emphasize behavior change strategies that promote safer gathering.
Surveillance of potential pathogens and antibiotic resistance in wastewater and surface water from Boston, USA and Vellore, India using long-read metagenomic sequencing
Authors: Fuhrmeister Erica R. , Voth-Gaeddert Lee E. , Metilda Angeline , Tai Albert , Batorsky Rebecca E. , Veeraraghavan Balaji , Ward Honorine D. , Kang Gagandeep , Pickering Amy J.
Published: April 2021

Environmental sampling (wastewater) could be an efficient surveillance strategy to capture global emerging trends in the spread of antibiotic resistance. Long-read DNA sequencing can resolve the genetic context of antibiotic resistance genes (ARGs) and is a promising tool for non-culture-based monitoring of antibiotic-resistant pathogens and ARGs in environmental samples, but has not been rigorously validated against conventional methods. We tested long-read sequencing using the portable Nanopore MinION for surveying pathogens, ARGs, and antibiotic-resistant pathogens in municipal wastewater, hospital wastewater, and surface water collected from Boston, USA and Vellore, India. We compared detection of enteric pathogens by assembly of long reads, with and without short-read polishing, and unassembled raw long reads for ARGs to multiplex real-time PCR. Using real-time PCR as a benchmark, long-read metagenomics was 49% sensitive and 75% specific at pathogen detection in assembled contigs, and 16% sensitive and 100% specific at detecting 28 clinically relevant resistance genes in raw long reads. Short-read polishing did not substantially improve pathogen identification or impact ARG identification in the assembled contigs, demonstrating that short-read polishing is not required, which greatly reduces costs. The high specificity of ARG detection supports portable long-read sequencing as a valuable tool to profile ARGs and antibiotic-resistant pathogens for environmental surveillance programs.
Resting-state functional MRI signal fluctuations are correlated with brain amyloid-β deposition
Authors: Scheel Norman , Tarumi Takashi , Tomoto Tsubasa , Cullum C. Munro , Zhang Rong , Zhu David C.
Published: April 2021

Mounting evidence suggests that amyloid-β (Aβ) and vascular etiologies are intertwined in the pathogenesis of Alzheimer’s disease. Spontaneous fluctuations of the brain blood-oxygen-level-dependent (BOLD) signal, as measured by resting-state functional MRI (rs-fMRI), have been shown to be associated with neuronal activities as well as cerebrovascular hemodynamics. Nevertheless, it is unclear if rs-fMRI BOLD fluctuations are associated with brain Aβ deposition in individuals with an elevated risk of Alzheimer’s disease.

We recruited 33 patients with amnestic mild cognitive impairment who underwent rs-fMRI and positron emission tomography (PET). The Aβ standardized uptake value ratio (SUVR) was calculated with cortical white matter as the reference region to improve sensitivity for cortical Aβ quantification. We calculated the amplitudes of low-frequency fluctuations (ALFF) of local BOLD signals in the frequency band of 0.01-0.08 Hz. Applying physiological/vascular signal regression in stepwise increasing levels on the rs-fMRI data, we examined whether local correlations between ALFF and brain Aβ deposition were driven by vascular hemodynamics, spontaneous neuronal activities, or both.

We found that ALFF and Aβ SUVR were negatively correlated in brain regions involving the default-mode and visual networks, with peak correlation at the precuneus, and angular, lingual, and fusiform gyri. Regions with higher ALFF had less Aβ accumulation. The correlated cluster sizes in MNI space were reduced from 3018 mm3 with no physiological/vascular regression to 1072 mm3 with strong physiological/vascular regression, with mean cluster r values at approximately -0.47.

Results demonstrate that both vascular hemodynamics and neuronal activities, as reflected by BOLD fluctuations, are negatively associated with brain Aβ deposition. These findings further imply that local brain blood fluctuations due to either vascular hemodynamics or neuronal activities can affect Aβ homeostasis.
RELIABILITY METHODS FOR ANALYZING COVID-19 PANDEMIC SPREADING BEHAVIOR, LOCKDOWN IMPACT AND INFECTIOUSNESS
Authors: Puls Alicia , Bracke Stefan
Published: April 2021

In 2021, the COVID-19 pandemic continues to challenge the globalized world. Restrictions on the public life and lockdowns of different characteristics define the life in many countries. This paper focuses on the first year of the COVID-19 pandemic (01-28-2020 to 01-15-2021). As a transfer of methods used in reliability engineering for analyzing occurrence of infection, Weibull distribution models are used to evaluate the spreading behavior of COVID-19.

Key issues of this study are the differences of spreading behavior in first and second pandemic phase and the various impacts of lockdown measures with different characteristics (hard, light). Therefore, the occurrence of infection in normed time periods with and without lockdown measures are analyzed in detail on the example of Germany representing the spreading behavior in Europe. Additional information in comparison to classical infection analyzes models like SIR model is generated by the application of Weibull distribution models with easy interpretable parameters and the dynamic development of COVID-19 is outlined.

In a further step, the occurrence of infection of COVID-19 is put into the context of other common infectious diseases in Germany like Influenza or Norovirus to evaluate the infectiousness. Differences in spreading behavior of COVID-19 in comparison to these well-known infectious diseases are underlined for different pandemic phases.
Tocilizumab and mortality in hospitalised patients with covid-19. A systematic review comparing randomised trials with observational studies
Authors: Podmore Bélène , Qizilbash Nawab , Lacetera Alessandra , Ubillos Itziar , Andresen Kirsty , Martín Ana Roncero , Majuelos-Melguizo Jara , Cuñado Moral Ana , Campos Marina Hinojosa , Aronson Jeffrey K , Pocock Stuart
Published: April 2021

Objective

To summarise and compare evidence from randomised controlled trials and observational studies of the effect of tocilizumab on in-hospital mortality in patients with covid-19.

Design

Systematic review and meta-analysis.

Data sources

Searches conducted in Embase and PubMed from July 2020 until 1 March 2021.

Study Selection

Observational studies and randomised controlled trials (RCTs) assessing in-hospital mortality in patients receiving tocilizumab compared with standard care or placebo.

Data extraction

The primary outcome was in-hospital mortality at 30 days. The risk of bias in observational studies was assessed using the ROBINS-I tool. A fixed effect meta-analysis was used to combine relative risks, with random effects and risk of bias as a sensitivity analysis.

Results

Of 5,792 publications screened for inclusion, eight RCTs and 35 observational studies were identified. The RCTs showed an overall relative risk reduction in in-hospital mortality at 30 days of 0.86 (95% CI 0.78 to 0.96) with no statistically significant heterogeneity. 23 of the observational studies had a severe risk of bias, 10 of which did not adjust for potential confounders. The 10 observational studies with moderate risk of bias reported a larger reduction in mortality at 30-days (relative risk 0.72, 95% CI 0.64 to 0.81) but with significant heterogeneity (P<0.01).

Conclusion

This meta-analysis provides strong evidence from RCTs that tocilizumab reduces the risk of mortality in hospitalised covid-19 patients. Observational studies with moderate risk of bias exaggerated the benefits on mortality two-fold and showed heterogeneity. Collectively observational studies provide a less reliable evidence base for evaluating treatments for covid-19.

Summary box

What is already known on this topic

Early case reports suggested that tocilizumab might produce clinical and biochemical improvement in covid-19. This was followed by observational studies using retrospective data, largely supporting clinicians’ impressions of benefit.

This led to wider use of tocilizumab, despite failure to show benefit on all-cause mortality from early underpowered randomised controlled trials (RCTs) in severe covid-19. The RECOVERY trial, the largest trial, has recently shown clear overall benefit in hospitalised patients with covid-19.

What this study adds

This meta-analysis provides strong evidence from RCTs that tocilizumab reduces the risk of mortality in hospitalised covid-19 patients.

Observational studies with moderate risk of bias exaggerated the benefits on mortality by two-fold.

Collectively observational studies provide a less reliable evidence base for evaluating treatments for covid-19.
A Spatial Analysis of Hypertension Prevalence in Rural and Urban Malawi
Authors: Burns James , Crampin Mia , Price Alison , Grundy Chris , Carpenter James
Published: April 2021

Background

Non-communicable diseases (NCD) represent a large and rapidly growing disease burden in Malawi and the wider sub-Saharan Africa region. National and regional NCD prevalence estimates and mapping, establishment of associated risk factors, and trend monitoring are vital for sustaining hard-won gains in well-being and life expectancy from the successful management of infectious diseases.

Methods

Between 2012 and 2016, blood pressure was measured in a population-representative sample of 29,628 Malawian adults (18+ years) residing in two locations; the southern part of rural Karonga district and urban Area 25 in Lilongwe city. Each location was divided into approximately 200 zones with individuals assigned the zone in which their home was located. A conditional autoregressive (CAR) model was fitted to estimate zonal hypertension prevalence. Estimates were plotted on regional maps featuring key amenities, healthcare facilities, and transport links. Individual-level economic and lifestyle covariates were then incorporated to assess how much of the variation could be explained by those covariates.

Results

Variation in hypertension prevalence was observed in both the rural and urban location (P< 0.0005), with high-prevalence zones clustering in areas near to major transport links and/or concentrations of amenities. Covariates explained most of the variation in both sites (P> 0.14).

Conclusions

In rural and urban Malawi, hypertension prevalence is higher among those of relatively high wealth, those who are closer to local amenities, or a combination of these two factors. More detailed data are needed to determine if these associations are explained by wealth-consequent behaviours such as sedentary occupations and deleterious lifestyle choices.
Insulin Resistance and Metabolic Comorbidities in Alzheimer’s Disease
Authors: Johansson Martina
Published: April 2021

Alzheimer’s disease affects 50 million people worldwide and just like any modern lifestyle disease, it is steadily increasing. Unfortunately, a cure has not yet been found, despite decades of research. The pathophysiology of Alzheimer’s disease is extraordinarily complex and involves many different factors. Despite it being a protein misfolding disease, a lot of evidence currently point to insulin resistance, impaired glucose metabolism and comorbidities with other metabolic disorders such as obesity, elevated blood lipids, and non-alcoholic fatty liver disease, as a potential root cause. Genetics aside, it seems like poor metabolic functioning affects the brain and central nervous system a great deal: affecting mood, behaviour, and cognitive performance. Even mood disorders are interlinked with metabolic disorders and increase the risk for Alzheimer’s disease later in life. This is a summary of objectively chosen original research articles, published between 2011-2021 and with insulin resistance as the main objective for cognitive impairment and Alzheimer’s disease.
Genetic analyses on the health impacts of testosterone highlight effects on female-specific diseases and sex differences
Authors: Leinonen Jaakko T. , Mars Nina , Lehtonen Leevi E. , Ahola-Olli Ari , Ruotsalainen Sanni , Lehtimäki Terho , Kähönen Mika , Raitakari Olli , FinnGen  , Daly Mark , Tuomi Tiinamaija , Ripatti Samuli , Pirinen Matti , Tukiainen Taru
Published: April 2021

Testosterone (T) is linked with diverse characteristics of human health, yet, whether these associations reflect correlation or causation remains debated. Here, we provide a broad perspective on the role of T on complex diseases in both sexes leveraging genetic and health registry data from the UK Biobank and FinnGen (total N=625,650).

We find genetically predicted T affects sex-biased and sex-specific traits, with a particularly pronounced impact on female reproductive health. We show T levels are intricately involved in metabolism, sharing many associations with sex hormone binding globulin (SHBG), but report lack of direct causality behind most of these associations. Across other disease domains, including behavior, we find little evidence for a significant contribution from normal variation in T levels. Highlighting T’s unique biology, we show T associates with antagonistic effects on stroke risk and reproduction in males and females.

Overall, we underscore the involvement of T in both male and female health, and the complex mechanisms linking T levels to disease risk and sex differences.
Depression during the COVID-19 pandemic amongst residents of homeless shelters in France
Authors: Scarlett Honor , Davisse-Paturet Camille , Longchamps Cécile , Aarbaoui Tarik El , Allaire Cécile , Colleville Anne-Claire , Convence-Arulthas Mary , Crouzet Lisa , Ducarroz Simon , Melchior Maria ,   the ECHO study group
Published: April 2021

Background

Accumulating evidence suggests that the COVID-19 pandemic has negatively affected global mental health and well-being. However, the impact amongst homeless persons has not been fully evaluated. The ECHO study reports factors associated with depression amongst the homeless population living in shelters in France during the Spring of 2020.

Methods

Interview data were collected from 527 participants living in temporary and/or emergency accommodation following France’s first lockdown (02/05/20 – 07/06/20), in the metropolitan regions of Paris (74%), Lyon (19%) and Strasbourg (7%). Interviews were conducted in French, English, or with interpreters (33% of participants, ∼20 languages). Presence of depression was ascertained using the Patient Health Questionnaire (PHQ-9).

Results

Amongst ECHO study participants, 30% had symptoms of moderate to severe depression (PHQ-9≥ 10). Multivariate analysis revealed depression to be associated with being female (aOR: 2.15; CI: 1.26-3.69), being single (aOR: 1.60; CI: 1.01-2.52), having a chronic illness (aOR: 2.32; CI: 1.43:-3.78), facing food insecurity (aOR: 2.12; CI: 1.40-3.22) and participants’ region of origin. Persons born in African and Eastern Mediterranean regions showed levels of depression comparable to those of French participants (30-33%) but higher than migrants from European countries (14%). Reduced rates of depression were observed amongst participants aged 30-49 (aOR: 0.60; CI: 0.38-0.95) and over 50 (aOR: 0.28; CI: 0.13-0.64), compared to 18-29-year-olds.

Conclusions

Our results indicate high levels of depression among homeless persons during the COVID-19 pandemic. The value of these findings extends beyond the health crisis, as predicted future instability and economic repercussions could particularly impact the mental health of this vulnerable group.
Knowledge and Impact of COVID-19 on Middle-Aged and Older People living with HIV in Lima, Peru
Authors: Diaz Monica M. , Cabrera Diego M. , Gil-Zacarías Marcela , Ramírez Valeria , Saavedra Manuel , Cárcamo Cesar , Hsieh Evelyn , García Patricia J.
Published: April 2021

COVID-19 has had an unprecedented worldwide impact, and Peru has had one of the highest COVID-19 case rates despite implementation of an early strict nationwide quarantine. Repercussions on Peru’s healthcare system may impact vulnerable populations, particularly people with HIV (PWH). We explored the knowledge of COVID-19 and the socioeconomic and health impact of the pandemic among middle-aged and older PWH. A cross-sectional telephone survey was administered to 156 PWH age ≥40 years receiving care in one of two large HIV clinics in Lima, Peru. The majority of PWH (age 52±7.7 years, 41% female, 65% completed secondary school or less) were knowledgeable regarding COVID-19 symptoms and prevention methods. Nearly half of those employed prior to the pandemic reported job loss. Female sex (unadjusted prevalence ratio [PR] 1.85 [95%CI 1.27-2.69]), low educational level (PR 1.62 [1.06-2.48]) and informal work (PR 1.58 [1.06-2.36]) were risk factors for unemployment but not in adjusted models. Increased anxiety was reported in 64% and stress in 77%. COVID-19 has had a substantial socioeconomic and mental health impact on PWH living in Lima, Peru, particularly those with lower educational levels and informal workers. Efforts are needed to ensure continued medical care and socioeconomic support of PWH in Peru.
Fatigue symptoms associated with COVID-19 in convalescent or recovered COVID-19 patients; a systematic review and meta-analysis
Authors: Rao Sanjay , Benzouak Tarek , Gunpat Sasha , Burns Rachel J. , Tahir Tayyeb A. , Jolles Stephen , Kisely Steve
Published: April 2021

Background

The prevalence and prognosis of post-acute stage SARS-CoV-2 infection fatigue symptoms remain largely unknown.

Aims

We performed a systematic review to evaluate the prevalence of fatigue in post-recovery from SARS-CoV-2 infection.

Method

Medline, Embase, PsycINFO, CINAHL, Web of Science, Scopus, trial registries, Cochrane Central Register of Controlled Trials and Google Scholar were searched for studies on fatigue in samples that recovered from PCR diagnosed COVID-19. English, French and Spanish studies were included. Meta-analyses were conducted separately for each recruitment setting.

Results

We identified 41 studies with 9362 patients that recovered from COVID-19. Post-COVID-19 patients self-report of fatigue was higher compared to healthy controls (RR = 3.688, 95%CI [2.502, 5.436], p < 0.001). Over 50% of patients discharged from inpatient care reported symptoms of fatigue during the first (ER = 0.517, 95%CI [0.278, 0.749]) and second month following recovery (ER = 0.527, 95%CI [0.337, 0.709]). 10% of the community patients reported fatigue in the first-month post-recovery. Patient setting moderated the association between COVID-19 recovery and fatigue symptoms (R2= 0.11, p < 0.001). Female patients recovering from COVID-19 had a greater self-report of fatigue (OR = 1.782, 95%CI [1.531, 2.870]). Patients recruited through social media had fatigue above 90% across multiple time points. Fatigue was highest in studies from Europe.

Conclusion

Fatigue is a symptom associated with functional challenges which could have economic and social impacts. Developing long-term planning for fatigue management amongst patients beyond the acute stages of SARS-CoV-2 infection is essential to optimizing patient care and public health outcomes. Further studies should examine the impact of sociodemographic, pandemic-related restrictions and pre-existing conditions on fatigue.
Targeted, collaborative biodiversity conservation in the global ocean can benefit fisheries economies
Authors: Rinnan D. Scott , Reygondeau Gabriel , McGowan Jennifer , Lam Vicky , Sumaila Rashid , Ranipeta Ajay , Kaschner Kristin , Garilao Cristina , Cheung William L. , Jetz Walter
Published: April 2021

Marine protected areas (MPAs) are key to averting continued loss of species and ecosystem services in our oceans, but concerns around economic trade-offs hamper progress. Here we provide optimized planning scenarios for global MPA networks that secure species habitat while minimizing impacts on fisheries revenues. We found that MPA coverage requirements differ vastly among nations, and that two-thirds of nations benefit economically from a collaborative approach. Immediate global protection of marine biodiversity habitat comes with losses of ~19% of total fisheries revenues, but international cooperation in concert with high seas protection improves economic losses for most countries, safeguards all species, and could save ~5B USD annually worldwide. Nations and fishery economies both share benefits from a coordinated approach to conserving marine biodiversity, with direct relevance to current international policies.
A deep learning approach to neurite prediction in high throughput fluorescence imaging
Authors: Barch Mariya , Cobb Melanie M. , Tokuno Zachary , Leddy Jen , Prenton Keili , Manubens-Gil Linus , Bellini Nicole , Lam Stephanie , Kaye Julia , Dierssen Mara , Finkbeiner Steven
Published: April 2021

Changes to neuronal morphology and loss of neurites and synaptic connections can be an important early indicator of neurological diseases, and a pathognomonic sign of neurodevelopmental disorders. These changes are typically detectable by microscopy in cell culture or histological samples, but quantification can be challenging. The neurites extending from cell soma can be quite thin, dim, overlapping and complex, making them laborious to trace manually and difficult to annotate and quantify computationally or automatically. Moreover, the tools available to aid this aim are limited in their capacity to generalize to high throughput image acquisition such as time-lapse or longitudinal imaging, where imaging conditions can change dramatically over the course of the experiment. In order to facilitate neurite quantification, we developed a deep learning (DL) neurite annotation prediction algorithm (NAPA) to predict the structure and length of neurites. NAPA overcomes experimental variation inherent to fluorescence imaging by learning more broader features that are important for neurite recognition. Based on a dataset with partial annotation, NAPA generated predictions on several unannotated datasets, and was able to capture differences between disease and control conditions. We also defined a sequence of steps to generate custom models with a small number of annotation inputs, and extended the predictions to a 3D tissue sample and longitudinal imaging. With this algorithm we developed an approach to quantify neurites with an accuracy that nears and sometimes exceeds human curation, in 1/100thof the time. This approach makes accurate analysis of large or longitudinal datasets feasible across a broad range of datasets.
Transient amplification enhances the persistence of tropicalising coral populations in marginal high latitude environments
Authors: Cant James , Cook Katie , Reimer James D. , Mezaki Takuma , Nakamura Masako , O’Flaherty Cliodhna , Salguero-Gómez Roberto , Beger Maria
Published: April 2021

Predicting the viability of species exposed to increasing climatic stress requires an appreciation for the mechanisms underpinning the success or failure of marginal populations. Rather than traditional metrics of long-term population performance, here we illustrate that short-term (i.e. transient) demographic characteristics, including measures of resistance, recovery, and compensation, are fundamental in the poleward range expansion of hard corals, facilitating the establishment of coral populations at higher-latitudes. Through the annual census of tropical and subtropicalAcroporaspp. colonies in Japan, between 2017-2019, we show how the transient amplification potential of a subtropical coral population supports its enhanced growth within unstable environmental conditions. The transient dynamics of both the tropical and subtropical populations were strongly influenced by their corresponding recruitment patterns. However, we demonstrate that variation in colony survival and fragmentation patterns between the two populations determines their relative capacities for transient amplification. This latitudinal variation in the transient dynamics ofAcroporaspp. populations emphasizes that coral populations can possess the demographic plasticity necessary for exploiting more variable, marginal conditions.
Cannabidiol as an add-on therapy to overcome the slow-onset and, possibly, resistance to antidepressant treatment: involvement of NAPE-PLD in the medial prefrontal cortex
Authors: Scarante Franciele F. , Lopes Vinícius D. , Fusse Eduardo J. , Vicente Maria A. , Araújo Melissa R. , Scomparin Davi S. , Aguiar Rafael P. , Guimarães Francisco S. , Nardini Viviani , Sorgi Carlos Arterio , Faccioli Lucia H. , Hallak Jaime E. C. , Joca Samia , Mackie Kenneth , Zuardi Antonio Waldo , Crippa José Alexandre S. , Campos Alline C.
Published: April 2021

Antidepressants such as serotonin uptake inhibitors are the first-line pharmacological treatment for chronic stress-related psychiatric disorders. However, their late-onset therapeutic action and frequent side effects, however, are important challenges for clinicians and patients. Besides, around 30% of major depression patients are considered treatment-resistant. Cannabidiol (CBD) is a non-psychotomimetic phytocannabinoid with a wide range of psychopharmacological effects, but its mechanism of action remains unclear. Here, we found that in male mice submitted to two different repeated stress protocols (chronic unpredictable and social defeat stress), low doses of CBD (7.5mg/Kg) caused an early-onset behavioral effect when combined to the antidepressant escitalopram (ESC-10mg/Kg). The behavioral effects of the ESC+CBD combination depended on the expression/activity of the N-acyl phosphatidylethanolamine phospholipase D (NAPE-PLD, responsible for synthesizing the endocannabinoid anandamide), but not the DAGLα, enzyme in the ventromedial prefrontal cortex. In addition, we described a case series with three treatment-resistant depression that were successfully treated with CBD as adjuvant therapy, as evaluated by standardized clinical rating scales. After 12 weeks of treatment, two patients were considered depression remitted (MADRS score lower than 10) while one patient successfully responded to CBD as add-on treatment (more than 50% decrease from the baseline MADRS). Our results suggest that CBD might be useful as an add-on therapy for optimizing the action of antidepressants. They also suggest that CBD’s beneficial actions depends on the facilitation of N-acylethanolamines actions in the medial prefrontal cortex.

Highlights

In mice, cannabidiol (CBD), but not escitalopram, induced a fast-onset anti-stress action.

Combinations of sub-effective doses of CBD and escitalopram produce anti-stress effects after only 7 days.

The Escitalopram + CBD treatment modulated synaptic protein markers in the medial prefrontal cortex.

CRISPR-Cas9-mediated knockdown of NAPE-PLD in the medial PFC prevents the anti-stress effect of the Escitalopram + CBD.

Adding CBD to an antidepressants regimen successfully treated three patients with treatment resistant depression.

Graphical abstract
Jetlag Expectations, not Circadian Parameters, Predict Jetlag Symptom Severity in Travelers
Authors: Ullrich Maximilian , Fischer Dorothee , Deutsch Sebastian , Meissner Karin , Winnebeck Eva C
Published: April 2021

After a flight across multiple time zones, most people show a transient state of circadian misalignment causing temporary malaise known as jetlag disorder. The severity of the elicited symptoms is postulated to depend mostly on circadian factors such as the number of time zones crossed and the direction of travel. Here, we examined the influence of prior expectation on symptom severity, compared to said “classic” determinants, in order to gauge potential psychosocial effects in jetlag disorder.

To this end, we monitored jetlag symptoms in travel-inexperienced individuals (n=90, 18-37y) via detailed questionnaires twice daily for one week before and after flights crossing >3 time zones. We found pronounced differences in individual symptom load that could be grouped into 4 basic symptom trajectories. Both traditional and newly devised metrics of jetlag symptom intensity and duration (accounting for individual symptom trajectories) recapitulated previous results of jetlag prevalence at about 50-60% as well as general symptom dynamics.

Surprisingly, however, regression models showed very low predictive power for any of the jetlag outcomes. The classic circadian determinants, including number of time zones crossed and direction of travel, exhibited little to no link with jetlag symptom intensity and duration. Only expectation emerged as a parameter with systematic, albeit small, predictive value.

These results suggest expectation as a relevant factor in jetlag experience - hinting at potential placebo effects and new treatment options. Our findings also caution against jetlag recommendations based on circadian principles but insufficient evidence linking circadian re-synchronization dynamics with ensuing symptom intensity and duration.

Significance Statement

Jetlag disorder afflicts millions of travelers each year - a nuisance on holiday trips but also a danger in safety and performance-critical operations. For effective prevention and treatment, it is critical to understand what influences jetlag severity, i.e. jetlag symptom intensity and duration. In contrast to what guidelines state, in our study, we did not find that symptom severity could be explained by the number of time zones crossed or travel direction. Rather, travelers’ expectations about how long and strongly they will suffer from jetlag symptoms was the only factor systematically predicting jetlag severity. If this holds true not only for subjective but also objective symptoms, we need to revisit assumptions about how circadian desynchronization relates to experienced jetlag symptoms.
Reinforcement learning derived chemotherapeutic schedules for robust patient-specific therapy
Authors: Eastman Brydon , Przedborski Michelle , Kohandel Mohammad
Published: April 2021

The in-silico development of a chemotherapeutic dosing schedule for treating cancer relies upon a parameterization of a particular tumour growth model to describe the dynamics of the cancer in response to the dose of the drug. In practice, it is often prohibitively difficult to ensure the validity of patient-specific parameterizations of these models for any particular patient. As a result, sensitivities to these particular parameters can result in therapeutic dosing schedules that are optimal in principle not performing well on particular patients. In this study, we demonstrate that chemotherapeutic dosing strategies learned via reinforcement learning methods are more robust to perturbations in patient-specific parameter values than those learned via classical optimal control methods. By training a reinforcement learning agent on mean-value parameters and allowing the agent periodic access to a more easily measurable metric, relative bone marrow density, for the purpose of optimizing dose schedule while reducing drug toxicity, we are able to develop drug dosing schedules that outperform schedules learned via classical optimal control methods, even when such methods are allowed to leverage the same bone marrow measurements.
Predicted structural mimicry of spike receptor-binding motifs from highly pathogenic human coronaviruses
Authors: Beaudoin Christopher A , Jamasb Arian R , Alsulami Ali F , Copoiu Liviu , van Tonder Andries J , Hala Sharif , Bannerman Bridget P , Thomas Sherine E , Vedithi Sundeep Chaitanya , Torres Pedro H M , Blundell Tom L
Published: April 2021

Viruses often encode proteins that mimic host proteins in order to facilitate infection. Little work has been done to understand the potential mimicry of the SARS-CoV-2, SARS-CoV, and MERS-CoV spike proteins, particularly the receptor-binding motifs, which could be important in determining tropism of the virus. Here, we use structural bioinformatics software to characterize potential mimicry of the three coronavirus spike protein receptor-binding motifs. We utilize sequence-independent alignment tools to compare structurally known or predicted three-dimensional protein models with the receptor-binding motifs and verify potential mimicry with protein docking simulations. Both human and non-human proteins were found to be similar to all three receptor-binding motifs. Similarity to human proteins may reveal which pathways the spike protein is co-opting, while analogous non-human proteins may indicate shared host interaction partners and overlapping antibody cross-reactivity. These findings can help guide experimental efforts to further understand potential interactions between human and coronavirus proteins.

Highlights

Potential coronavirus spike protein mimicry revealed by structural comparison

Human and non-human protein potential interactions with virus identified

Predicted structural mimicry corroborated by protein-protein docking

Epitope-based alignments may help guide vaccine efforts

Graphical abstract
Orientation and color tuning of the human visual gamma rhythm
Authors: Li Ye , Bosking William , Beauchamp Michael S. , Sheth Sameer A. , Yoshor Daniel , Bartoli Eleonora , Foster Brett L.
Published: April 2021

Narrowband gamma oscillations (NBG: ∼20-60Hz) in visual cortex reflect rhythmic fluctuations in population activity generated by underlying circuits tuned for stimulus location, orientation, and color. Consequently, the amplitude and frequency of induced NBG activity is highly sensitive to these stimulus features. For example, in the non-human primate, NBG displays biases in orientation and color tuning at the population level. Such biases may relate to recent reports describing the large-scale organization of single-cell orientation and color tuning in visual cortex, thus providing a potential bridge between measurements made at different scales. Similar biases in NBG population tuning have been predicted to exist in the human visual cortex, but this has yet to be fully examined. Using intracranial recordings from human visual cortex, we investigated the tuning of NBG to orientation and color, both independently and in conjunction. NBG was shown to display a cardinal orientation bias (horizontal) and also an end- and mid-spectral color bias (red/blue and green). When jointly probed, the cardinal bias for orientation was attenuated and an end-spectral preference for red and blue predominated. These data both elaborate on the close, yet complex, link between the population dynamics driving NBG oscillations and known feature selectivity biases in visual cortex, adding to a growing set of stimulus dependencies associated with the genesis of NBG. Together, these two factors may provide a fruitful testing ground for examining multi-scale models of brain activity, and impose new constraints on the functional significance of the visual gamma rhythm.

Significance Statement

Oscillations in electrophysiological activity occur in visual cortex in response to stimuli that strongly drive the orientation or color selectivity of visual neurons. The significance of this induced ‘gamma rhythm’ to brain function remains unclear. Answering this question requires understanding how and why some stimuli can reliably generate gamma activity while others do not. We examined how different orientations and colors independently and jointly modulate gamma oscillations in the human brain. Our data show gamma oscillations are greatest for certain orientations and colors that reflect known biases in visual cortex. Such findings complicate the functional significance of gamma activity, but open new avenues for linking circuits to population dynamics in visual cortex.

Classification

Neuroscience
Aerobic glycolysis is important for zebrafish larval wound closure and tail regeneration
Authors: Scott Claire A. , Carney Tom J. , Amaya Enrique
Published: April 2021

The underlying mechanisms of appendage regeneration remain largely unknown and uncovering these mechanisms in capable organisms has far-reaching implications for potential treatments in humans. Recent studies implicate a requirement for metabolic reprogramming reminiscent of the Warburg effect during successful appendage and organ regeneration. As changes are thus predicted to be highly dynamic, methods permitting direct, real-time visualization of metabolites at the tissue and organismal level, would offer a significant advance in defining the influence of metabolism on regeneration and healing. We sought to examine whether glycolytic activity was altered during larval fin regeneration, utilising the genetically encoded biosensor, Laconic, enabling the spatiotemporal assessment of lactate levels in living zebrafish. We present evidence for a rapid increase in lactate levels within minutes following injury, with a role of aerobic glycolysis in actomyosin contraction and wound closure. We also find a second wave of lactate production, associated with overall larval tail regeneration. Chemical inhibition of glycolysis attenuates both contraction of the wound and regrowth of tissue following tail amputation, suggesting aerobic glycolysis is necessary at two distinct stages of regeneration.
In vitroeffects of S-Licarbazepine as a potential precision therapy onSCN8Avariants causing neuropsychiatric disorders
Authors: Bayraktar Erva , Liu Yuanyuan , Hedrich Ulrike B.S. , Sara Yildirim , Lerche Holger , Wuttke Thomas V , Lauxmann Stephan
Published: April 2021

Background and Purpose

Among genetic epilepsies, variants in sodium channel coding genes constitute a major subgroup. Variants inSCN8A, the coding gene for NaV1.6 channels, are characterized by a variety of symptoms including intractable epileptic seizures, psychomotor delay, progressive cognitive decline, and others such as autistic features, ataxia or dystonia. Standard anticonvulsant treatment has only limited impact on the course of disease.

Experimental Approach

Personalized therapeutic regimens tailored to disease-causing pathophysiological mechanisms may offer the specificity required to overcome intractability. Toward this aim, we investigatedin vitroin neuroblastoma cells the effects of S-Licarbazepine, a third-generation dibenzazepine and enhancer of slow inactivation of voltage gated sodium channels, on three gain-of-function NaV1.6 variants linked to representative phenotypes of mild epilepsy (G1475R), developmental and epileptic encephalopathy (M1760I) and intellectual disability without epilepsy (A1622D).

Key Results

S-Licarbazepine strongly enhances the slow and - less pronounced – the fast inactivation of NaV1.6 wildtype channels. It acts similarly on all tested variants and irrespective of their particular biophysical dysfunction mechanism. Beyond that S-Licarbazepine has variant-specific effects including a partial reversal of pathologically slowed fast inactivation dynamics (A1622D, M1760I) and a trend to reduce the enhanced persistent Na+current by A1622D variant channels.

Conclusion and Implications

These data bring out that S-Licarbazepine not only owns substance-specific effects, but also holds variant-specific effects, which can variably contribute to functional compensation of distinct channel-specific biophysical properties and thereby highlighting the role of personalized approaches, which likely will be key to improved and successful treatment not only ofSCN8A-related disease.

Bullet points

What is already known?S-Lic strongly modulates slow and - to a less extend - fast inactivation of wild-type NaV1.6 channels.

What this study adds?Differential modulatory effects of S-Lic extend to NaV1.6 A1622D, M1760I and G1475R variant channels irrespective of their leading biophysical mode of gain-of-function and variably contribute to variant-specific functional compensation of their altered biophysical properties.

Clinical significance:These data suggest therapeutic potential of S-Lic forSCN8Aneuropsychiatric disorders and highlight the role of personalized approaches aimed at increasingly precise correction of underlying pathophysiological mechanisms.
Electrocorticography is superior to subthalamic local field potentials for movement decoding in Parkinson’s disease
Authors: Merk Timon , Peterson Victoria , Lipski Witold , Blankertz Benjamin , Turner Robert S. , Li Ningfei , Horn Andreas , Richardson R. Mark , Neumann Wolf-Julian
Published: April 2021

Brain signal decoding promises significant advances in the development of clinical brain computer interfaces (BCI). In Parkinson’s disease (PD), first bidirectional BCI implants for adaptive deep brain stimulation (DBS) are now available. Brain signal decoding can extend the clinical utility of adaptive DBS but the impact of neural source, computational methods and PD pathophysiology on decoding performance are unknown. This represents an unmet need for the development of future neurotechnology. To address this, we developed an invasive brain-signal decoding approach based on intraoperative sensorimotor electrocorticography (ECoG) and subthalamic LFP to predict grip-force, a representative movement decoding application, in 11 PD patients undergoing DBS. We demonstrate that ECoG is superior to subthalamic LFP for accurate grip-force decoding. Gradient boosted decision trees (XGBOOST) outperformed other model architectures. ECoG based decoding performance negatively correlated with motor impairment, which could be attributed to subthalamic beta bursts in the motor preparation and movement period. This highlights the impact of PD pathophysiology on the neural capacity to encode movement kinematics. Finally, we developed a connectomic analysis that could predict grip-force decoding performance of individual ECoG channels across patients by using their connectomic fingerprints. Our study provides a neurophysiological and computational framework for invasive brain signal decoding to aid the development of an individualized precision-medicine approach to intelligent adaptive DBS.

Significance Statement

Neurotechnology will revolutionize the treatment of neurological and psychiatric patients, promising novel treatment avenues for previously intractable brain disorders. However, optimal surgical and computational approaches and their interactions with neurological disorders are unknown. How can recent advances in machine learning and connectomics aid the precision and performance of invasive brain signal decoding strategies? Do the brain disorders treated with such approaches have impact on decoding performance? We propose a real time compatible advanced machine learning pipeline for invasively recorded brain signals in Parkinson’s disease (PD) patients. We report optimal movement decoding strategies with respect to signal source, model architecture and connectomic fingerprint and demonstrate that PD pathophysiology significantly and negatively impacts movement decoding. Our study has broad impacts for the development of smart brain implants for the treatment of PD and other brain disorders.
Effects of non-invasive brain stimulation on visual perspective taking: A meta-analytic study
Authors: Yao Yuan-Wei , Chopurian Vivien , Zhang Lei , Lamm Claus , Heekeren Hauke R.
Published: April 2021

Visual perspective taking (VPT) is a critical ability required by complex social interaction. Non-invasive brain stimulation (NIBS) has been increasingly used to examine the causal relationship between brain activity and VPT, yet with heterogeneous results. In the current study, we conducted two meta-analyses to examine the effects of NIBS of the right temporoparietal junction (rTPJ) or dorsomedial prefrontal cortex (dmPFC) on VPT, respectively. We performed a comprehensive literature search to identify qualified studies, and computed the standardized effect size (ES) for each combination of VPT level (Level-1: visibility judgment; Level-2: mental rotation) and perspective (self and other). Thirteen studies (rTPJ: 12 studies, 23 ESs; dmPFC: 4 studies, 14 ESs) were included in the meta-analyses. Random-effects models were used to generate the overall effects. Subgroup analyses for distinct VPT conditions were also performed. We found that rTPJ stimulation significantly improved participants’ visibility judgment from the allocentric perspective, whereas its effects on other VPT conditions are negligible. Stimulation of dmPFC appeared to influence Level-1 performance from the egocentric perspective, although it was only based on a small number of studies. Notably, contrary to some theoretical models, we did not find strong evidence that these regions are involved in Level-2 VPT with a higher requirement of mental rotation. These findings not only advanced our understanding of the causal roles of the rTPJ and dmPFC in VPT, but also revealed the efficacy of NIBS on VPT is relatively small. Researchers should also be cautious about the potential publication bias and selective reporting.