bluuebunny/crossref_metadata_2025 huggingface dataset:
Progressive changes in descriptive discourse in First Episode of Schizophrenia: A longitudinal computational semantics study
Authors: Alonso-Sánchez Maria Francisca , Ford Sabrina D. , MacKinley Michael , Silva Angélica , Limongi Roberto , Palaniyappan Lena
Published: October 2021

Computational semantics, a branch of computational linguistics, involves automated meaning analysis that relies on how words occur together in natural language. This offers a promising tool to study schizophrenia. At present, we do not know if these word level choices in speech are sensitive to illness stage (i.e. acute untreated vs. stable established state), track cognitive deficits in major domains (e.g. cognitive control, processing speed) and relate to established dimensions of formal thought disorder. Here we study samples of descriptive discourse in patients with untreated first episode of schizophrenia (x□ 2.8 days of lifetime daily dose exposure) and healthy subjects (246 samples of 1-minute speech; n=82, FES=46, HC=36) using a co-occurrence based vector embedding of words. We obtained six-month follow-up data in a subsample (99 speech samples, n=33, FES=20, HC=13). At baseline, the evidence for higher semantic similarity during descriptive discourse in FES was substantial, compared to null difference (Bayes Factor =6 for full description; 32 for 10-words window). Moreover, the was a linear increase in semantic similarity with time in FES compared to HC (Bayes Factor= 6). Higher semantic similarity related to lower Stroop performance (accuracy and interference, response time), and was present irrespective of the severity of clinically ascertained thought disorder. Automated analysis of non-intrusive 1-minute speech samples provides a window on cognitive control deficits, role functioning and tracks latent progression in schizophrenia.
Adaptive data-driven age and patch mixing in contact networks with recurrent mobility
Authors: Knight Jesse , Ma Huiting , Ghasemi Amir , Hamilton Mackenzie , Brown Kevin , Mishra Sharmistha
Published: October 2021

Infectious disease transmission models often stratify populations by age and geographic patches. Contact patterns between age groups and patches are key parameters in such models. Arenas et al. (2020) develop an approach to simulate contact patterns associated with recurrent mobility between patches, such as due to work, school, and other regular travel. Using their approach, mixing between patches is greater than mobility data alone would suggest, because individuals from patches A and B can form a contact if they meet in patch C. We build upon their approach to address three potential gaps that remain. First, our approach includes a distribution of contacts by age that is responsive to underlying age distribution of the mixing pool. Second, different age distributions by contact type are also maintained in our approach, such that changes to the numbers of different types of contacts are appropriately reflected in changes to the overall age mixing patterns. Finally, we introduce and distinguish between two mixing pools associated with each patch, with possible implications for the overall connectivity of the population: the home pool, in which contacts can only be formed with other individuals residing in the same patch; and the travel pool, in which contacts can be formed with some residents of, and any other visitors to the patch. We describe in detail the steps required to implement our approach, and present results of an example application.

Graphical Abstract
Importation Risk Stratification for COVID19 using Quantitative Serology
Authors: Williams David E
Published: October 2021

Recent work (Khoury et al.,Nature Medicine2021, 27 (7), 1205-1211) has shown that measurement of IgG antibody concentration in blood correlates well with vaccine efficacy. The present communication builds on this work and considers the probability of infection given immunity, taking into account the distribution across the population of antibody concentration in vaccinated or convalescent people. The model is consistent with the observed rates of breakthrough infection following vaccination or previous infection. The model is then developed to consider the use of quantitative measurement of antibody concentration on arrival as an aid to risk stratification of travellers. The model indicates that such a measurement could significantly decrease the quarantine time required to achieve a given level of importation risk.
Patient Attitudes About Light Therapy and Negative Ion Therapy for Nonseasonal Depression: An Online Survey Study
Authors: Lahouaoula Iman , Li Victor W. , Scott Aidan , Do André , Michalak Erin E. , Murphy Jill K. , Huang Samantha , Lam Raymond W.
Published: October 2021

Objective

No studies have yet evaluated whether light therapy or negative ion therapy can be used as maintenance treatment after acute treatment with antidepressants in patients with major depressive disorder. To address the importance of this question, we surveyed participants with depression to determine their knowledge and attitudes about light therapy and negative ion therapy, and their willingness to participate in a randomized clinical trial with these therapies substituting for antidepressants for maintenance treatment.

Methods

Participants with a self-reported diagnosis of depression were recruited by email, newsletters, and social media to complete an online survey with questions about awareness and effectiveness of light therapy and negative ion therapy for depression. Vignettes describing the use of these therapies for maintenance treatment were presented with follow up questions about the ease of use and reasons for wanting (and not wanting) to use the therapies instead of antidepressants. Another vignette described a randomized study with these therapies followed by questions on whether participants would likely volunteer for the study. Chi-square tests were used to examine differences in responses between therapies.

Results

A total of 221 participants completed the survey. Most of them were aware of both therapies, but more participants had heard of light therapy (95% compared to 62% for negative ion therapy, p<0.0001), had used light therapy (28% versus 16%, p<0.003), and regarded light therapy as effective (54% versus 37%, p<0.001). Both therapies were considered easy to use. The majority of participants (78%) thought that it was important to find non-medication therapies for maintenance treatment, and 77% responded that they would likely volunteer for a randomized study to determine efficacy of the two therapies for maintenance treatment.

Conclusion

People with depression are generally aware of light therapy and negative ion therapy and believe they would be good therapies to substitute for antidepressants in maintenance treatment. These findings support the importance and feasibility for a randomized relapse prevention trial with light therapy and negative ion therapy in patients with depression.
Assessing the Burden of COVID-19 in Developing Countries: Systematic Review, Meta-Analysis, and Public Policy Implications
Authors: Levin Andrew , Owusu-Boaitey Nana , Pugh Sierra , Fosdick Bailey K. , Zwi Anthony B. , Malani Anup , Soman Satej , Besançon Lonni , Kashnitsky Ilya , Ganesh Sachin , McLaughlin Aloysius , Song Gayeong , Uhm Rine , Herrera-Esposito Daniel , de los Campos Gustavo , Pecanha Antiono Ana Carolina , Tadese Enyew Birru , Meyerowitz-Katz Gideon
Published: October 2021

Introduction

The infection-fatality rate (IFR) of COVID-19 has been carefully measured and analyzed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries.

Methods

We systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using population representative samples collected by early 2021. For each of the antibody assays used in these serology studies, we identified data on assay characteristics, including the extent of seroreversion over time. We analyzed the serology data using a Bayesian model that incorporates conventional sampling uncertainty as well as uncertainties about assay sensitivity and specificity. We then calculated IFRs using individual case reports or aggregated public health updates, including age-specific estimates whenever feasible.

Results

Seroprevalence in many developing country locations was markedly higher than in high-income countries. In most locations, seroprevalence among older adults was similar to that of younger age cohorts, underscoring the limited capacity that these nations have to protect older age groups. Age-specific IFRs were roughly 2x higher than in high-income countries. The median value of the population IFR was about 0.5%, similar to that of high-income countries, because disparities in healthcare access were roughly offset by differences in population age structure.

Conclusion

The burden of COVID-19 is far higher in developing countries than in high-income countries, reflecting a combination of elevated transmission to middle-aged and older adults as well as limited access to adequate healthcare. These results underscore the critical need to accelerate the provision of vaccine doses to populations in developing countries.

Key Points

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Age-stratified infection fatality rates (IFRs) of COVID-19 in developing countries are about twice those of high-income countries.

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Seroprevalence (as measured by antibodies against SARS-CoV-2) is broadly similar across age cohorts, underscoring the challenges of protecting older age groups in developing countries.

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Population IFR in developing countries is similar to that of high-income countries, because differences in population age structure are roughly offset by disparities in healthcare access as well as elevated infection rates among older age cohorts.

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These results underscore the urgency of disseminating vaccines throughout the developing world.
Endemic Seasonal Coronavirus Neutralisation and COVID-19 severity
Authors: Wells David A. , Cantoni Diego , Mayora-Neto Martin , Di Genova Cecilia , Sampson Alexander , Ferrari Matteo , Carnell George , Nadesalingam Angalee , Smith Peter , Chan Andrew , Raddi Gianmarco , Castillo-Olivares Javier , Baxendale Helen , Temperton Nigel , Heeney Jonathan L.
Published: October 2021

The virus SARS-CoV-2, responsible for the global COVID-19 pandemic, spread rapidly around the world causing high morbidity and mortality because humans have no pre-existing immunity. However, there are four known, endemic seasonal coronaviruses in humans (HCoVs) and whether antibodies for these HCoVs play a role in severity of COVID-19 disease has generated a lot of interest. Of these seasonal viruses NL63 is of particular interest as it uses the same cell entry receptor as SARS-CoV-2.We use functional, neutralising assays to investigate cross reactive antibodies and their relationship with COVID-19 severity. We analysed neutralisation of SARS-CoV-2, NL63, HKU1, and 229E in 38 COVID-19 patients and 62 healthcare workers, and a further 182 samples to specifically study the relationship between SARS-CoV-2 and NL63.We found that although HCoV neutralisation was very common there was little evidence that these antibodies neutralised SARS-CoV-2. Despite no evidence in cross neutralisation, levels of NL63 neutralisating antibodies become elevated after exposure to SARS-CoV-2 through infection or following vaccination.
LOTVS: a global collection of permanent vegetation plots
Authors: Sperandii Marta Gaia , de Bello Francesco , Valencia Enrique , Götzenberger Lars , Bazzichetto Manuele , Galland Thomas , E-Vojtkó Anna , Conti Luisa , Adler Peter B. , Buckley Hannah , Danihelka Jiří , Day Nicola J. , Dengler Jürgen , Eldridge David J. , Estiarte Marc , García-González Ricardo , Garnier Eric , Gómez-García Daniel , Hallett Lauren , Harrison Susan , Herben Tomas , Ibáñez Ricardo , Jentsch Anke , Juergens Norbert , Kertész Miklós , Kimuyu Duncan M. , Klumpp Katja , Le Duc Mike , Louault Frédérique , Marrs Rob H. , Ónodi Gábor , Pakeman Robin J. , Pärtel Meelis , Peco Begoña , Peñuelas Josep , Rueda Marta , Schmidt Wolfgang , Schmiedel Ute , Schuetz Martin , Skalova Hana , Šmilauer Petr , Šmilauerová Marie , Smit Christian , Song Ming-Hua , Stock Martin , Val James , Vandvik Vigdis , Wesche Karsten , Wiser Susan K. , Woodcock Ben A. , Young Truman P. , Yu Fei-Hai , Zobel Martin , Lepš Jan
Published: October 2021

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of vascular plants in permanent plots. With 79 datasets from five continents and 7789 vegetation time-series monitored for at least six years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology.
“Epidemiological profile of patients with stage 5 chronic kidney disease on dialysis with Covid 19 infection in a Public Hospital-Perú”
Authors: Venegas-Justiniano Yanissa , Loza-Munarriz César , Hurtado-Aréstegui Abdías
Published: October 2021

Introduction

Chronic kidney disease (CKD) in Covid 19 is relevant, however, there are few descriptions and fewer in Peru. Our goal was to describe the epidemiological profile and the factors related to mortality and survival of patients with stage 5 (CKD) on chronic dialysis hospitalized for Covid-19 in a public hospital.

Methods

Retrospective case series. Patients with stage 5 CKD, older than 18 years, hospitalized for Covid-19 infection were included. The primary data source was medical records. The clinical and epidemiological profile of the study sample and the factors related to mortality and survival are described.

Results

105 medical records of patients with CKD 5 were evaluated. 57 (54,29%) were male, with a mean age of 58,59 ± 14,3 years. 84 (80%) patients survived and 21 (20%) died. The main cause of admission to hospitalization was respiratory failure in (80) 76,2%. The hospital stay was 11,76 ± 7,8 days. In the bivariate analysis: the increase in leukocytes, D dimer, ferritin, CRP, LDH and the decrease in lymphocytes, pH, bicarbonate and PaO2/FiO2 were related to mortality. In the multivariate analysis, only CRP> 10 mg/dl [HR: 10.72 (95% CI 1,4-81,58)] and a PaO2/FiO2 ≤ 150 mmHg [HR: 44,40 (95% CI 5,86-336,06)] they were factors related to poor survival.

Conclusions

CRP levels> 10mg/dl and PaO2/FiO2 ≤ 150 mmHg are the main factors related to mortality and poor survival in patients with stage 5 CKD hospitalized for Covid-19.
Genome-wide cell-free DNA termini in patients with cancer
Authors: Moldovan Norbert , van der Pol Ymke , van den Ende Tom , Boers Dries , Verkuijlen Sandra , Creemers Aafke , Ramaker Jip , Vu Trang , Fransen Marieke F. , Pegtel Michiel , Bahce Idris , van Laarhoven Hanneke , Mouliere Florent
Published: October 2021

The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 572 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection in resectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

One sentence summary

cell-free DNA fragment end sequence analysis enhances cancer detection, monitoring and prognosis.
Choroid plexus enlargement is associated with neuroinflammation and reduction of blood brain barrier permeability in depression
Authors: Althubaity Noha , Schubert Julia , Martins Daniel , Yousaf Tayyabah , Nettis Maria A. , Mondelli Valeria , Pariante Carmine , Harrison Neil A. , Bullmore Edward T. , Dima Danai , Turkheimer Federico E. , Veronese Mattia ,   the NIMA Consortium
Published: October 2021

Background

Recent studies have shown that choroid plexuses (CP) may be involved in the neuro-immune axes, playing a role in the interaction between the central and peripheral inflammation. Here we aimed to investigate CP volume alterations in depression and their associations with inflammation.

Methods

51 depressed participants (HDRS score >13) and 25 age- and sex-matched healthy controls (HCs) from the Wellcome Trust NIMA consortium were re-analysed for the study. All the participants underwent full peripheral cytokine profiling and simultaneous [11C]PK11195 PET/structural MRI imaging for measuring neuroinflammation and CP volume respectively.

Results

We found a significantly greater CP volume in depressed subjects compared to HCs (t(76) = +2.17) that was positively correlated with [11C]PK11195 PET binding in the anterior cingulate cortex (r=0.28, p=0.02), prefrontal cortex (r=0.24, p=0.04), and insular cortex (r=0.24, p=0.04), but not with the peripheral inflammatory markers: CRP levels (r=0.07, p=0.53), IL-6 (r=-0.08, p=0.61), and TNF-α (r=-0.06, p=0.70). The CP volume correlated with the [11C]PK11195 PET binding in CP (r=0.34, p=0.005). Integration of transcriptomic data from the Allen Human Brain Atlas with the brain map depicting the correlations between CP volume and PET imaging found significant gene enrichment for several pathways involved in neuroinflammatory response.

Conclusion

This result supports the hypothesis that changes in brain barriers may cause reduction in solute exchanges between blood and CSF, disturbing the brain homeostasis and ultimately contributing to inflammation in depression. Given that CP anomalies have been recently detected in other brain disorders, these results may not be specific to depression and might extend to other conditions with a peripheral inflammatory component.
Unraveling diagnostic co-morbidity makeup of each HF category as characteristically derived by ECG- and ECHO-findings
Authors: Zaman Azfar , Nogueira Marta Afonso , Szabo Erzsebet , Berta-Szabo Aniko , Zoccai Giuseppe Biondi , Campbell Niall , Koulaouzidis Georgios , Tsipas Dionissios , Kecskes Istvan
Published: October 2021

Background

Echocardiography (ECHO) is not widely available in primary care, the key structural (chamber enlargements) and functional abnormality are not easily available precluding the ability to diagnose HF other than through mainly symptomatic means. The opportunity for earlier detection of HF is lost.

Methods

Using a unique database, the etiology of HF is explored by prevalence analysis to unravel the diagnostic makeup of each HF category. Various relationships and patterns of comorbidities have been extracted between the Electrocardiogram (ECG) and ECHO parameters that contribute to HF, those relationships are then confirmed and categorized by a Principal Component Analysis (PCA). Finally, it was summarized what type of non-invasive ECG-like device should be used in primary care to better diagnose HF.

Results

The sensitivity of abnormal ECHO reaches 92% over the abnormal ECG of 81% in the detection of HF. The first five PCA are discovered, which cover 49% of all the variance. Left atrial enlargement is the most representative finding in the overall comorbidity rate, which coincides with the probability direction of HF (3rdas input, 1stas finding in the coefficients), and reaches the highest (250%) prevalence increase in function of decreasing LVEF.

Conclusions

The core structural and functional abnormalities diagnosed by ECHO with the ECG interpretation provide sufficient information to diagnose “consider HF” in primary care. This paper overview of a novel bio-signal-based system supported by Artificial Intelligence, able to replicate Echo-findings, predict HF and indicates its phenotype, suitable for use in Primary Care.
Predicting the unpredictable: how dynamic COVID-19 policies and restrictions challenge model forecasts
Authors: Houdroge Farah , Palmer Anna , Delport Dominic , Walsh Tom , Kelly Sherrie L , Hainsworth Samuel W , Abeysuriya Romesh , Stuart Robyn M , Kerr Cliff C , Coplan Paul , Wilson David P , Scott Nick
Published: October 2021

Introduction

To retrospectively assess the accuracy of a mathematical modelling study that projected the rate of COVID-19 diagnoses for 72 locations worldwide in 2021, and to identify predictors of model accuracy.

Methods

Between June and August 2020, an agent-based model was used to project rates of COVID-19 infection incidence and cases diagnosed as positive from 15 September to 31 October 2020 for 72 geographic settings. Five scenarios were modelled: a baseline scenario where no future changes were made to existing restrictions, and four scenarios representing small or moderate changes in restrictions at two intervals. Post hoc, upper and lower bounds for number of diagnosed Covid-19 cases were compared with actual data collected during the prediction window. A regression analysis with 17 covariates was performed to determine correlates of accurate projections.

Results

The actual data fell within the lower and upper bounds in 27 settings and out of bounds in 45 settings. The only statistically significant predictor of actual data within the predicted bounds was correct assumptions about future policy changes (OR = 15.04; 95%CI 2.20-208.70; p=0.016).

Conclusions

For this study, the accuracy of COVID-19 model projections was dependent on whether assumptions about future policies are correct. Frequent changes in restrictions implemented by governments, which the modelling team was not always able to predict, in part explains why the majority of model projections were inaccurate compared with actual outcomes and supports revision of projections when policies are changed as well as the importance of policy experts collaborating on modelling projects.
A Computational Growth Framework for Biological Tissues: Application to Growth of Aortic Root Aneurysm Repaired by the V-shape Surgery
Authors: Dong Hai , Liu Minliang , Qin Tongran , Liang Liang , Ziganshin Bulat , Ellauzi Hesham , Zafar Mohammad , Jang Sophie , Elefteriades John , Sun Wei , Gleason Rudolph L.
Published: October 2021

Ascending aortic aneurysms (AsAA) often include the dilatation of sinotubular junction (STJ) which usually leads to aortic insufficiency. The novel surgery of the V-shape resection of the noncoronary sinus, for treatment of AsAA with root ectasia, has been shown to be a simpler procedure compared to traditional surgeries. Our previous study showed that the repaired aortic root aneurysms grew after the surgery. In this study, we developed a novel computational growth framework to model the growth of the aortic root repaired by the V-shape surgery. Specifically, the unified-fiber-distribution (UFD) model was applied to describe the hyperelastic deformation of the aortic tissue. A novel kinematic growth evolution law was proposed based on existing observations that the growth rate is linearly dependent on the wall stress. Moreover, we also obtained patient-specific geometries of the repaired aortic root post-surgery at two follow-up time points (Post1 and Post2) for 5 patients, based on clinical CT images. The novel computational growth framework was implemented into the Abaqus UMAT user subroutine and applied to model the growth of the aortic root from Post1 to Post2. Patient-specific growth parameters were obtained by an optimization procedure. The predicted geometry and stress of the aortic root at Post2 agree well with the in vivo results. The novel computational growth framework and the optimized growth parameters could be applied to predict the growth of repaired aortic root aneurysms for new patients and to optimize repair strategies for AsAA.
Experience(s) of the medical profession: A qualitative study using narrative facilitators
Authors: Bourquin Céline , Orsini Sandy , Stiefel Friedrich
Published: October 2021

Physicians’ narratives are means to approach and comprehend their experiences. They reveal the practice of medicine, and inform about the physicians’ embedment in their work and the healthcare context. This study aimed to examine physicians’ experience by means of interviews based on “narrative facilitators”, which goal is to encourage storytelling and to support the narrative process. Core stories were elaborated on the key aspects that emerged from the analysis. Thirty-three physicians participated in the study. The findings showed a focus on the transformations of a profession, the need for physicians to adapt in terms of role and status, and their withstanding of conflicting projections from the public and patients. The institutional context was described as darkness in which physicians are moving. When reacting to the quotes from their peers, participants showed a variety of un-patterned stances with regard to different aspects of medicine and the medical profession. Findings also indicated that as narrators, physicians may have particular difficulties accessing their inner world. Disenchanted physicians are not beneficial, neither for the patient nor for the health care system, and their feeling of being worn out may do harm and is certainly negatively affecting themselves and their families.
Association between time spent with family and loneliness among Japanese workers during the COVID-19 pandemic: a cross-sectional study
Authors: Fujii Rintaro , Konno Yusuke , Tateishi Seiichiro , Hino Ayako , Tsuji Mayumi , Ikegami Kazunori , Nagata Masako , Yoshimura Reiji , Matsuda Shinya , Fujino Yoshihisa ,   for the CORoNaWork Project
Published: October 2021

Background

The current coronavirus (COVID-19) pandemic has had large impacts on society, including people practicing social distancing. This behavioral response has increased loneliness. Loneliness not only increases the risk of psychiatric disorders, but also affects occupational mental health. To avoid the negative effects of isolation, it is important to have social contact with other people, especially family members. Employment and economic instability caused by COVID-19 may have also affected family relationships. It is important to understand the association between family relationships and loneliness in workers under the pandemic.

Methods

We collected usable data from 27,036 Japanese workers who completed an online survey during the COVID-19 pandemic. Participants were asked how long they spend with members of their family during mealtimes or at home, and if they experienced loneliness; the latter was assessed by a single question. Other questions included whether participants lived with their spouse, or with someone in need of care. To estimate the odds ratios (ORs) of time with family associated with loneliness we used a multilevel logistic model nested in the prefecture of residence, with adjustments for age, sex, marital status, presence of a cohabitant requiring care, equivalent income, educational level, frequency of remote work, availability of someone for casual chat, smoking, drinking, time for leisure interests, and cumulative rates of COVID-19 in the prefecture.

Results

Ten percent (2,750) of the 27,036 participants reported loneliness. The survey showed a significant negative correlation between time spent with family and loneliness (p<0.001): participants who spent more time with family were less likely to feel loneliness. In addition, not living with a spouse and living with someone in need of care were associated with loneliness (not living with a spouse: p<0.001; living with someone in need of care: p<0.001).

Conclusion

Loneliness under COVID-19 pandemic conditions was negatively associated with time spent with family members, with the converse result found for participants cohabiting with someone in need of care. These associations suggest the potential value of changes to working practices and interventions to combat loneliness.
Community social vulnerability and access to medications for opioid use disorder within the continental US: A cross-sectional study
Authors: Joudrey Paul J. , Kolak Marynia , Lin Qinyun , Paykin Susan , Anguiano Vidal , Wang Emily A.
Published: October 2021

The COVID-19 pandemic, like past natural disasters, was associated with significant disruptions in medications for opioid use disorder services and increased opioid overdose and mortality. We examined the association between community vulnerability to disasters and pandemics and geographic access to each of the three medications for opioid use disorder within the continental US and if this association was impacted by urban, suburban, or rural classification. We found communities with greater vulnerability did not have greater geographic access to medications for opioid use disorder and the mismatch between vulnerability and medication access was greatest in suburban communities. Rural communities had poor geographic access to all three medications regardless of vulnerability. Future disaster preparedness planning should include anticipation of access to medications for opioid use disorder and better match the location of services to communities with greater vulnerability to prevent inequities in opioid overdose deaths.
Structural synaptic signatures of Alzheimer’s Disease and Dementia with Lewy Bodies in the male brain
Authors: Glebov Oleg O. , Williamson David , Owen Dylan M. , Hortobágyi Tibor , Troakes Claire , Aarsland Dag
Published: October 2021

The impact of Alzheimer’s Disease (AD) and Dementia with Lewy Bodies (DLB) on synaptic organisation remains poorly understood. Here, we found that in humans, DLB and AD were associated with increased synaptic levels of glutamate transporter vGlut1 and active zone protein Bassoon clustering respectively; these effects were only observed in male brain samples. These findings demonstrate disease- and sex-specific presynaptic structural remodelling in age-related neurodegenerative disorders.
Modelling of COVID-19 pandemic vis-à-vis some socio-economic factors
Authors: Oshinubi Kayode , Rachdi Mustapha , Demongeot Jacques
Published: October 2021

The impacts of COVID-19 outbreak on socio-economic status of countries across the globe cannot be overemphasized as we examine the role it played in various countries. A lot of people were out of jobs, many households were careful of their spending and a greater social fracture of the population in fourteen different countries has emerged. We considered periods of infection spread during the first and second wave in Organization for Economic Co-operation and Development (OECD) countries and countries in Africa, that is developed and developing countries alongside their social-economic data. We established a mathematical and statistical relationship between Theil and Gini index, then we studied the relationship between the data from epidemiology and socio-economic determinants using several machine learning and deep learning methods. High correlations were observed between some of the socio-economic and epidemiologic parameters and we predicted three of the socio-economic variables in order to validate our results. These result shows a sharp difference between the first and second wave of the pandemic confirming the real dynamics of the spread of the outbreak in several countries and ways by which it was mitigated.
SARS-CoV-2 infections elicit higher levels of original antigenic sin antibodies compared to SARS-CoV-2 mRNA vaccinations
Authors: Anderson Elizabeth M. , Eilola Theresa , Goodwin Eileen , Bolton Marcus J. , Gouma Sigrid , Goel Rishi R. , Painter Mark M. , Apostolidis Sokratis A. , Mathew Divij , Dunbar Debora , Fiore Danielle , Brock Amanda , Weaver JoEllen , Millar John S. , DerOhannessian Stephanie ,   The UPenn COVID Processing Unit, Greenplate Allison R. , Frank Ian , Rader Daniel J. , Wherry E. John , Hensley Scott E.
Published: October 2021

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccines elicit higher levels of antibodies compared to natural SARS-CoV-2 infections in most individuals; however, the specificities of antibodies elicited by vaccination versus infection remain incompletely understood. Here, we characterized the magnitude and specificity of SARS-CoV-2 spike-reactive antibodies from 10 acutely infected health care workers and 23 participants who received mRNA-based SARS-CoV-2 vaccines. We found that infection and primary mRNA vaccination elicited S1 and S2-reactive antibodies, while secondary vaccination boosted mostly S1 antibodies. Using magnetic bead-based absorption assays, we found that SARS-CoV-2 infections elicited a large proportion of original antigenic sin-like antibodies that bound efficiently to common seasonal human coronaviruses but poorly to SARS-CoV-2. In converse, vaccination only modestly boosted antibodies reactive to common seasonal human coronaviruses and these antibodies bound efficiently to SARS-CoV-2. Our data indicate that SARS-CoV-2 mRNA vaccinations elicit fundamentally different antibody responses compared to SARS-CoV-2 infections.

Abstract Figure

HIGHLIGHTS

SARS-CoV-2 mRNA vaccines elicit higher levels of antibodies compared to SARS-CoV-2 infections

The first dose of an mRNA vaccine generates both S1 and S2 responses while the second dose boosts primarily S1-specific antibodies

SARS-CoV-2 infections, but not mRNA vaccinations, elicit high levels of antibodies that bind strongly to seasonal coronaviruses but weakly to SARS-CoV-2
Estimates of pandemic excess mortality in India based on civil registration data
Authors: Banaji Murad , Gupta Aashish
Published: October 2021

Background

The population health impacts of the COVID-19 pandemic are less well understood in low-and middle-income countries, where mortality surveillance before the pandemic was patchy. Interpreting the limited all-cause mortality data available in India is challenging.

Objective

We use existing data on all-cause mortality from civil registration systems of twelve Indian states comprising around 60% of the national population to understand the scale and timing of excess deaths in India during the COVID-19 pandemic.

Methods

We carefully characterize the reasons why registration is incomplete and estimate the extent of coverage in the data. Comparing the pandemic period to 2019, we estimate excess mortality in twelve Indian states, and extrapolate our estimates to the rest of India. We explore sensitivity of the estimates to various assumptions.

Results

For the 12 states with available all-cause mortality data, we document an increase of 28% in deaths during April 2020–May 2021 relative to expectations from 2019. This level of increase in mortality, if it applies nationally, would imply 2.8–2.9 million excess deaths. More limited data from June 2021 increases national estimates of excess deaths during April 2020–June 2021 to 3.8 million. With more optimistic or pessimistic assumptions, excess deaths during this period could credibly lie between 2.8 million and 5.2 million. The scale of estimated excess deaths is broadly consistent with expectations based on seroprevalence data and international data on COVID-19 fatality rates. Moreover, the timing of excess deaths and recorded COVID-19 deaths is similar – they rise and fall at the same time.

Conclusions

The surveillance of pandemic mortality in India has been extremely poor, with around 8–10 times as many excess deaths as officially recorded COVID-19 deaths. India is among the countries most severely impacted by the pandemic. Our approach highlights the utility of all-cause mortality data, as well as the significant challenges in interpreting it.
Sex, Military Occupation, and Rank Are Associated with Risk of Anterior Cruciate Ligament Injury in Tactical-Athletes
Authors: Aguero Aubrey D , Irrgang James J , MacGregor Andrew J , Rothenberger Scott D , Hart Joseph M , Fraser John J
Published: October 2021

Backgroun

ACL injury is frequent within the U.S. military and represents a significant loss to readiness. Since recent changes to operational tempo, there has not been an analysis of ACL injury risk. There is sparse evidence on salient risk factors for ACL injury across all service members.

Hypothesis/Purpose

The aim of this study is to evaluate military occupation, sex, rank, and branch of service on ACL injury risk in the U.S. military from 2006 to 2018.

Study Design

Descriptive Epidemiology Study.

Methods

The Defense Medical Epidemiology Database was queried for the number of U.S. military members with ICD diagnosis codes 717.83 (Old disruption of ACL), 844.2 (Sprain of knee cruciate ligament), M23.61 (Other spontaneous disruption of ACL), and S83.51 (Sprain of ACL of knee) on their initial encounter from 2006 to 2018. Relative risk (RR) and chi-square statistics were calculated to assess sex and military occupation effects on ACL injury. A multivariable negative binomial regression model evaluated changes in ACL injury incidence with respect to sex, branch of service, and rank.

Results

The study period displayed a significant decrease in the ACL injury rate at 0.18 cases per 1000 person-years or relative decrease of 4.08% each year (p < 0.001) after averaging over the main and interactive effects of sex, rank, and branch of service. The interaction effect of time with sex indicated a steeper decline in ACL injury incidence in males as compared to females. The risk of ACL injury by sex was modified by rank. Furthermore, the incidence of ACL injury among military personnel varied depending on occupation.

Conclusion

Despite the decline in incidence among military members over time, the rates of ACL injury remain much higher than the general U.S. population. Sex, rank, branch of service, and military occupation were found to be risk factors for ACL injury.

Clinical Relevance

These results are evidence to support inquiry into the specific hazards associated with these factors. It is critical for policy makers to understand the salient risk factors for ACL injury to guide appropriate proactive measures to prevent injury.

What is known about this subject

ACL injury is a known command readiness issue in the military, and there is recent evidence of this within subpopulations of the military.

What this study adds to existing literature

This study provides updated trends in ACL injury across the military in light of changes to operational tempo and identifies salient risk factors for ACL injury, which have been previously unknown on a population basis.
Updating urinary microbiome analyses to enhance biologic interpretation
Authors: Siddiqui Nazema Y. , Ma Li , Brubaker Linda , Mao Jialiang , Hoffman Carter , Karstens Lisa
Published: October 2021

Objective

An approach for assessing the urinary microbiome is 16S rRNA gene sequencing, where a segment of the bacterial genome is amplified and sequenced. Methods used to analyze these data are rapidly evolving, although the research implications are not known. This re-analysis of an existing dataset aimed to determine the impact of updated bioinformatic and statistical techniques.

Methods

A prior Pelvic Floor Disorders Network (PFDN) study compared the urinary microbiome in 123 women with mixed urinary incontinence (MUI) and 84 controls. We used the PFDN’s unprocessed sequencing data of V1-V3 and V4-V6 16S variable regions, processed operational taxonomic unit (OTU) tables, and de-identified clinical data. We processed sequencing data with an updated bioinformatic pipeline, which used DADA2 to generate amplicon sequence variant (ASV) tables. Taxa from ASV tables were compared to OTU tables generated from the original processing; taxa from different variable regions (e.g., V1-V3 versus V4-V6) after updated processing were also compared. After updated processing, data were analyzed with multiple filtering thresholds. Several techniques were tested to cluster samples into microbial communities. Multivariable regression was used to test for associations between microbial communities and MUI, while controlling for potentially confounding variables.

Results

Of taxa identified through updated bioinformatic processing, only 40% were identified originally, though taxa identified through both methods represented >99% of sequencing data in terms of relative abundance. When different 16S rRNA gene regions were sequenced from the same samples, there were differences noted in recovered taxa. When the original clustering methods were applied to reprocessed sequencing data, we confirmed differences in microbial communities associated with MUI. However, when samples were clustered with a different methodology, microbial communities were no longer associated with MUI.

Conclusions

Updated bioinformatic processing techniques recover many different taxa compared to prior techniques, though most of these differences exist in low abundance taxa that occupy a small proportion of the overall microbiome. Detection of high abundance taxa are not significantly impacted by bioinformatic strategy. However, there are different biases for less abundant taxa; these differences as well as downstream clustering methodology and filtering thresholds may affect interpretation of overall results.
ModelMatcher: A scientist-centric online platform to facilitate collaborations between stakeholders of rare and undiagnosed disease research
Authors: Harnish J. Michael , Li Lucian , Rogic Sanja , Poirier-Morency Guillaume , Kim Seon-Young ,   Undiagnosed Diseases Network, Boycott Kym M. , Wangler Michael F. , Bellen Hugo J. , Hieter Philip , Pavlidis Paul , Liu Zhandong , Yamamoto Shinya
Published: October 2021

Next-generation sequencing is a prevalent diagnostic tool for undiagnosed diseases, and has played a significant role in rare disease gene discovery. While this technology resolves some cases, others are given a list of possibly damaging genetic variants necessitating functional studies. Productive collaborations between scientists, clinicians, and patients can help resolve such medical mysteries, and provide insights into in vivo function of human genes. Furthermore, facilitating interactions between scientists and research funders, including non-profit organizations or commercial entities, can dramatically reduce the time to translate discoveries from bench to bedside. Several systems designed to connect clinicians and researchers with a shared gene of interest have been successful. However, these platforms exclude some stakeholders based on their role or geography. Here we describe ModelMatcher, a global online matchmaking tool designed to facilitate cross-disciplinary collaborations, especially between scientists and other stakeholders of rare and undiagnosed disease research. ModelMatcher is integrated into the Rare Diseases Models and Mechanisms Network and Matchmaker Exchange, allowing users to identify potential collaborators in other registries. This living database decreases the time from when a scientist or clinician is making discoveries regarding their genes of interest, to when they identify collaborators and sponsors to facilitate translational and therapeutic research.
Hippocampus does not appear to be a major target of thalamic nucleus reuniens
Authors: Andrianova Lilya , Brady Erica S , Margetts-Smith Gabriella , Kohli Shivali , Cavanagh Jonathan , McBain Chris J , Craig Michael T
Published: October 2021

The prefrontal – hippocampal – entorhinal system is perhaps the most widely-studied circuit in cognitive and systems neuroscience, due to its role in supporting cognitive functions such as working memory and decision-making. Disrupted communication within this circuit is a key feature of disorders such as schizophrenia and dementia. Nucleus reuniens (NRe) is a midline thalamic nucleus that sits at the nexus of this circuit, linking these regions together. As there are no direct projections from prefrontal cortex to hippocampus, the accepted model is that the NRe mediates prefrontal drive of hippocampal activity, although these connections are poorly defined at the cellular and synaptic level. Usingex vivooptogenetics and electrophysiology, alongside monosynaptic circuit-tracing, we sought to test the mechanisms through which NRe could drive hippocampal activity. Unexpectedly, we found no evidence that pyramidal cells in CA1 receive input from NRe, with midline thalamic input to hippocampus proper appearing selective for GABAergic interneurons. In other regions targeted by NRe, we found that pyramidal cells in prosubiculum and subiculum received synaptic inputs from NRe that were at least an order of magnitude weaker than those in prefrontal or entorhinal cortices. We conclude that, contrary to widely-held assumptions in the field, the hippocampus is not a major target of nucleus reuniens.
A spike-sorting method based on hierarchical clustering to discriminate extracellularly recorded simple spikes and complex spikes from cerebellar Purkinje cells
Authors: Michikawa Takayuki , Isobe Keisuke , Itohara Shigeyoshi
Published: October 2021

Background

In the cerebellar cortex, Purkinje cells are the only output neurons and exhibit two types of discharge. Most Purkinje cell discharges are simple spikes, which are commonly appearing action potentials exhibiting a rich variety of firing patterns with a rate of up to 400 Hz. More infrequent discharges are complex spikes, which consist of a short burst of impulses accompanied by a massive increase in dendritic Ca2+ with a firing rate of around 1 Hz. The discrimination of these spikes in extracellular single-unit recordings is not always straightforward, as their waveforms vary depending on recording conditions and intrinsic fluctuations.

New Method

To discriminate complex spikes from simple spikes in the extracellular single-unit data, we developed a semiautomatic spike-sorting method based on divisive hierarchical clustering.

Results

Quantitative evaluation using parallel in vivo two-photon Ca2+ imaging of Purkinje cell dendrites indicated that 96.6% of the complex spikes were detected using our spike-sorting method from extracellular single-unit recordings obtained from anesthetized mice.

Comparison with Existing Method(s)

No reports have conducted a quantitative evaluation of spike-sorting algorithms used for the classification of extracellular spikes recorded from cerebellar Purkinje cells.

Conclusions

Our method could be expected to contribute to research in information processing in the cerebellar cortex and the development of a fully automatic spike-sorting algorithm by providing ground-truth data useful for deep learning.

Highlights

A spike-sorting algorithm on hierarchical clustering was developed.

It was applied to extracellular recordings from cerebellar Purkinje cells.

Complex and simple spikes were discriminated based on their waveforms.

Spike-sorting performance was quantified using in vivo Ca2+ imaging data.

The algorithm isolated over 96.6% of complex spikes.