bluuebunny/crossref_metadata_2025 huggingface dataset:
Off-label use in Palliative Care – more common than expected. A retrospective chart review
Authors: Hagemann Vera , Bausewein Claudia , Rémi Constanze
Published: January 2021

Objective

Off-label drug use seems to be integral to palliative care pharmacotherapy. Balancing potential risks and benefits in the context of limited therapeutic options is challenging. To provide specific support for clinicians in dealing with off-label use, it is essential to understand off-label use in everyday clinical practice.

The aim of this pilot study was to quantify and describe off-label use in a palliative care unit.

Methods

Retrospective chart review of all adult patients treated on a palliative care unit in 10/2017. All data on drug use e.g. indication, dose, route of administration were extracted and matched with the prescribing information. Identified off-label use was subsequently compared with recommendations in the relevant literature. The main outcome measure was frequency and type of off-label drug use.

Results

2,352 drug application days (d) and 93 drugs were identified for 28 patients. Of all drugs, 47 (51%) were used off-label at least once. Most off-label uses concerned indication (57%), followed by mode of administration. In drugs highly relevant to palliative care the rate of off-label use was as high as 67%. The extent to which off-label therapy was supported by literature was very variable and ranged from 0 to 88%.

Conclusions

This single-unit data confirms the high prevalence of off-label use in palliative medicine and demonstrates that off-label use in palliative care is very multifaceted. The data presented allows for a more precise characterization of various aspects of off-label use in order to derive concrete further measures for research and clinical practice.

What is already known on this subject

Off-label drug use is likely to be common in palliative care, but detailed data is very limited

Off-label drug use is a potential threat for patient safety

Physicians state to make therapeutic decisions based on their own experience, due to a lack of available evidence and lack of support in assessment

What this study adds

off-label use in palliative care is multifaceted

the mode of administration (e.g. combination with other drugs in a syringe driver) is beside indication a common reasons for off label use

the proportion of off-label use without sound evidence is high.
Antipsychotics effects on network-level reconfiguration of cortical morphometry in first-episode schizophrenia
Authors: Jiang Yuchao , Wang Yingchan , Huang Huan , He Hui , Tang Yingying , Su Wenjun , Xu Lihua , Wei Yanyan , Zhang Tianhong , Hu Hao , Wang Jinhong , Wang Jijun , Luo Cheng , Yao Dezhong
Published: January 2021

Background

Cortical thickness reductions are evident in patients with schizophrenia. Associations between antipsychotic medications (APMs) and cortical morphometry have been explored in schizophrenia patients. This raises the question of whether the reconfiguration of morphological architecture by APM plays potential compensatory roles for abnormalities in the cerebral cortex.

Methods

Structural MRI were obtained from 127 medication-naive first-episode schizophrenia (FES) patients and 133 matched healthy controls. Patients received 12 weeks of APM and were categorized as responders (n=75) or nonresponders (n=52) at follow-up. Using surface-based morphometry and structural covariance analysis, this study investigated the short-term effects of antipsychotics on cortical thickness and cortico-cortical connectivity. Global efficiency was computed to characterize network integration of the large-scale structural connectome. The relationship between connectivity and cortical thinning was examined by the structural covariance analysis among top-n regions with thickness reduction.

Results

Widespread cortical thickness reductions were observed in pre-APM patients. Post-APM patients showed more reductions in cortical thickness, even in the frontotemporal regions without baseline reductions. Covariance analysis revealed strong cortico-cortical connectivity and higher network integration in responders than in nonresponders. Notably, the nonresponders lacked key nodes of the prefrontal and temporal regions for the covariance network between top-n regions with cortical thickness reductions.

Conclusions

Antipsychotic effects are not restricted to a single brain region but rather exhibit a network-level covariance pattern. Neuroimaging connectomics highlights the positive effects of antipsychotics on the reconfiguration of brain architecture, suggesting that abnormalities in regional morphology may be compensated by increasing interregional covariance when symptoms are controlled by antipsychotics.
Phenotyping in the era of genomics:MaTrics– a digital character matrix to document mammalian phenotypic traits coded numerically
Authors: Stefen Clara , Wagner Franziska , Asztalos Marika , Giere Peter , Grobe Peter , Hiller Michael , Hofmann Rebecca , Jähde Maria , Lächele Ulla , Lehmann Thomas , Ortmann Sylvia , Peters Benjamin , Ruf Irina , Schiffmann Christian , Thier Nadja , Unterhitzenberger Gabi , Vogt Lars , Rudolf Matthias , Wehner Peggy , Stuckas Heiko
Published: January 2021

A new and uniquely structured matrix of mammalian phenotypes,MaTrics(MammalianTraits for Comparative Genomics) is presented in a digital form. By focussing on mammalian species for which genome assemblies are available,MaTricsprovides an interface between mammalogy and comparative genomics.

MaTricswas developed as part of a project to link phenotypic differences between mammals to differences in their genomes usingForward Genomics.Apart from genomes this approach requires information on homologous phenotypes that are numerically encoded (presence-absence; multistate character coding*) in a matrix.MaTricsprovides these data, links them to at least one reference (e.g., literature, photographs, histological sections, CT-scans, or museum specimens) and makes them available in a machine actionable NEXUS-format. By making the data computer readable,MatTricsopens a new way for digitizing collections. Currently,MaTricscovers 147 mammalian species and includes 207 characters referring to structure, morphology, physiology, ecology and ethology. Researching these traits revealed substantial knowledge gaps, highlighting the need for substantial phenotyping efforts in the genomic era. Using the trait information documented inMaTrics, previous Forward Genomics screens identified changes in genes that are associated with various phenotypes, ranging from fully-aquatic lifestyle to dietary specializations. These results motivate the continuous expansion of phenotype information, both by filling research gaps or by adding additional taxa and traits.MaTricsis digitally available online within the data repository Morph·D·Base (www.morphdbase.de).
Function-structure Coupling: White matter fMRI hyper-activation associates with structural integrity reductions in schizophrenia
Authors: Jiang Yuchao , Luo Cheng , Li Xiangkui , Huang Huan , Zhao Guocheng , Li Xuan , Li Shicai , Song Xufeng , Yao Dezhong , Duan Mingjun
Published: January 2021

Background

White matter (WM) microstructure deficit may be an underlying factor in the brain dysconnectivity hypothesis of schizophrenia using diffusion tensor imaging (DTI). However, WM dysfunction is unclear in schizophrenia. This study aimed to investigate the association between structural deficits and functional disturbances in major WM tracts in schizophrenia.

Methods

Using functional magnetic resonance imaging (fMRI) and DTI, we developed the skeleton-based white matter functional analysis, which could achieve voxel-wise function–structure coupling by projecting the fMRI signals onto a skeleton in WM. We measured the fractional anisotropy (FA) and WM low-frequency oscillation activation and their couplings in ninety-three schizophrenia patients and 122 healthy controls (HCs). An independent open database (62 schizophrenia patients and 71 HCs) was used to test the reproducibility. Finally, associations between WM activations and five behaviour assessment categories (cognition, emotion, motor, personality and sensory) were examined.

Results

This study revealed a reversed pattern of structure and function in frontotemporal tracts, as follows. (1) WM hyper-activation was associated with reduced FA in schizophrenia. (2) The function–structure association was positive in healthy controls but negative in schizophrenia patients. Furthermore, function–structure dissociation was exacerbated by long illness duration and severe negative symptoms. (3) WM activations were significantly related to cognition and emotion.

Conclusions

This study indicated function–structure dys-coupling, with higher functional activation and reduced structural integration in frontotemporal WM, which may reflect a potential mechanism in WM neuropathologic processing of schizophrenia.
Differential investment in visual and olfactory brain regions mirrors the sensory needs of a paper wasp social parasite and its host
Authors: Rozanski Allison N. , Cini Alessandro , Lopreto Taylor E. , Gandia Kristine M. , Hauber Mark E. , Cervo Rita , Uy Floria M. K.
Published: January 2021

Obligate social parasites evolve traits to effectively locate and then exploit their hosts, whereas hosts have complex social behavioral repertoires, which include sensory recognition to reject potential conspecific intruders and heterospecific parasites. While social parasite and host behaviors have been studied extensively, less is known about how their sensory systems function to meet their specific selective pressures. Here, we compare investment in visual and olfactory brain regions in the paper waspPolistes dominula, and its obligate social parasiteP. sulcifer, to explore the link between sensory systems and brain plasticity. Our results show opposite and significant differences, consistent with their very different life-histories, in the sensory investments between these two closely-related species. Social parasites initially invest in the optic lobes to likely locate their hosts. After host colony usurpation, the parasite increases its brain volume, with specific investment in antennal lobes, which mirrors the behavioral switch from a usurping parasite to an integrated parasitic queen of the host colony. Contrastingly, hosts initially invest in the antennal lobes and sensory processing compared to social parasites, as predicted by their need to maintain social cohesion, allocate colony tasks, and recognize con- and heterospecific intruders. Host queens show a trend of higher investment in all sensory brain regions compared to workers, paralleling differences in task allocations. Our work provides novel insights into how intraspecific brain plasticity can facilitate the unique sensory adaptations needed to perform specific tasks by the host or to transition from searching to successful host exploitation by the social parasite.
Defining the cell surface proteomic landscape of multiple myeloma reveals immunotherapeutic strategies and biomarkers of drug resistance
Authors: Ferguson Ian D. , Escobar Bonell Patiño , Tuomivaara Sami T. , Lin Yu-Hsiu T. , Nix Matthew A. , Leung Kevin K. , Hale Martina , Choudhry Priya , Lopez-Girona Antonia , Ramos Emilio , Wong Sandy W. , Wolf Jeffrey L. , Martin Thomas G. , Shah Nina , Vandenberg Scott , Prakash Sonam , Besse Lenka , Driessen Christoph , Wells James A. , Wiita Arun P.
Published: January 2021

The myeloma cell surface proteome (“surfaceome”) not only determines tumor interaction with the microenvironment but serves as an emerging arena for therapeutic development. Here, we use glycoprotein capture proteomics to first define surface markers most-enriched on myeloma when compared to B-cell malignancy models, revealing unexpected biological signatures unique to malignant plasma cells. We next integrate our proteomic dataset with existing transcriptome databases, nominating CCR10 and TXNDC11 as possible monotherapeutic targets and CD48 as a promising co-target for increasing avidity of BCMA-directed cellular therapies. We further identify potential biomarkers of resistance to both proteasome inhibitors and lenalidomide including changes in CD53, EVI2B, CD10, and CD33. Comparison of short-term treatment with chronic resistance delineates large differences in surface proteome profile under each type of drug exposure. Finally, we develop a miniaturized version of the surface proteomics protocol and present the first surface proteomic profile of a primary myeloma patient plasma cell sample. Our dataset provides a unique resource to advance the biological, therapeutic, and diagnostic understanding of myeloma.
Seroepidemiological Study of Novel Corona Virus (CoVID-19) in Tehran, Iran
Authors: Tabanejad Zeinab , Darvish Sorena , Boroujeni Zeinab Borjian , Asadi Seyed Saeed , Mesri Morteza , Raiesi Omid , Getso Muhammad Ibrahim , Zareei Mahdi
Published: January 2021

A novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has now spread to all countries of the world, including Iran. Although new anti-coronavirus antibodies in patients may be identified by immunological methods with sufficient sensitivity and specificity, the conclusive diagnosis of the disease is by the molecular RT-PCR process. We used a population-based seroepidemiological survey to quantify the proportion of the exposed population with SARS-CoV-2 antibodies and evaluated whether the antibodies are a marker of total or partial immunity to the proportion of the population that remains susceptible to the virus. This cross-sectional study was conducted to investigate the seroprevalence of CoVID-19 in Tehran, the capital of Iran, between April and end of October 2020. Specimens of clotted and heparinized blood (2ml) were collected from the patients. The serum and plasma were separated and stored at − 80LJ°C until use. We examined serum anti-SARS-CoV-2 IgG and IgM antibodies from 1375 in-patients admitted to our hospitals using ELISA kits. In total, 1375 participants were enrolled in this study, and SARS-CoV-2 antibodies were detected using IgM-IgG antibody assay in 291 patients. Among the seropositive patients studied, 187 were men (64.3%), and 104 were women (35.7%) (P<0.05). The mean age of the patients was 49±8.4 years; the majority (27%) were in age group 31-40 years. Also, the lowest frequency of cases was reported in the age group of 1-10 years (P <0.05). We determined the seroprevalence of SARS-CoV-2 for IgM or IgG antibodies to be 21.2%. Diabetes mellitus was the most common underlying disease among SARS-CoV-2 patients [P=0.05; Odd Ratio=1.61(0.90-2.91)]. Conventional serological assays in SARS-CoV-2 cases, such as the enzyme-linked immunoassay (ELISA) for specific IgM and IgG antibodies, have a high-throughput advantage and minimize false-negative rates that occur with the RT-PCR method. This study determined the seroprevalence of SARS-CoV-2 antibodies to be 21%. Control of diabetes among other cases factors shall play important role in management and control of COVID-19.
Improved screening of COVID-19 cases through a Bayesian network symptoms model and psychophysical olfactory test
Authors: Eyheramendy Susana , Saa Pedro A. , Undurraga Eduardo A. , Valencia Carlos , López Carolina , Méndez Luis , Pizarro-Berdichevsky Javier , Finkelstein-Kulka Andrés , Solari Sandra , Salas Nicolás , Bahamondes Pedro , Ugarte Martín , Barceló Pablo , Arenas Marcelo , Agosin Eduardo
Published: January 2021

The infectiousness and presymptomatic transmission of SARS-CoV-2 hinder pandemic control efforts worldwide. Therefore, the frequency of testing, accessibility, and immediate results are critical for reopening societies until an effective vaccine becomes available for a substantial proportion of the population. The loss of sense of smell is among the earliest, most discriminant, and prevalent symptoms of COVID-19, with 75-98% prevalence when clinical olfactory tests are used. Frequent screening for olfactory dysfunction could substantially reduce viral spread. However, olfactory dysfunction is generally self-reported, which is problematic as partial olfactory impairment is broadly unrecognized. To address this limitation, we developed a rapid psychophysical olfactory test (KOR) deployed on a web platform for automated reporting and traceability based on a low-cost (about USD 0.50/test), six-odor olfactory identification kit. Based on test results, we defined an anosmia score –a classifier for olfactory impairment–, and a Bayesian Network (BN) model that incorporates other symptoms for detecting COVID-19. We trained and validated the BN model on two samples: suspected COVID-19 cases in five healthcare centers (n = 926; 32% COVID-19 prevalence) and healthy (asymptomatic) mining workers (n = 1, 365; 1.1% COVID-19 prevalence). All participants had COVID-19 assessment by RT-PCR assay. Using the BN model, we predicted COVID-19 status with 76% accuracy (AUC=0.79 [0.75 − 0.82]) in the healthcare sample and 84% accuracy (AUC=0.71 [0.63 − 0.79]) among miners. The KOR test and BN model enabled the detection of COVID-19 cases that otherwise appeared asymptomatic. Our results confirmed that olfactory dysfunction is the most discriminant symptom to predict COVID-19 status when based on olfactory function measurements. Overall, this work highlights the potential for low-cost, frequent, accessible, routine testing for COVID-19 surveillance to aid society’s reopening.
Ranking videolaryngoscopes by orotracheal intubation performance: protocol of a systematic review and network meta-analysis of clinical trials at patient level
Authors: de Carvalho Clístenes Crístian , da Silva Danielle Melo , Lemos Victor Macedo , dos Santos Thiago Gadelha Batista , Agra Ikaro Cavalcante , Miná Pinto Gustavo , Ramos Isabella Beserra , da Cunha Costa Yuri Soares , dos Santos Neto Jayme Marques
Published: January 2021

Background

Videolaryngoscopes (VLs) are regarded to improve glottic visualization as compared to Macintosh laryngoscope (ML). However, we currently do not know which one would be the best choice. We then designed this systematic review and network meta-analysis to rank the different VLs as compared to ML.

Methods

We will conduct a search in PubMed, LILACS, Scielo, Embase, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL; 2020, Issue 6) on 11/01/2021. We will include randomized clinical trials fully reported with patients aged ≥ 16 years, comparing VLs with ML for failed intubation with the device, failed first intubation attempts, number of intubation attempts, time for intubation, difficulty of intubation, and improved visualization of the larynx. Pooled effects will be estimated by both fixed and random-effects models and presented according to qualitative and quantitative heterogeneity assessment. Sensitivity analyses will be performed as well as a priori subgroup, meta-regression and multiple meta-regression analyses. Additionally, network meta-analyses will be applied to rank the different VLs as compared to ML. We will also assess the risk of selective publication by funnel plot asymmetry.

Discussion

This systematic review and network meta-analysis aim at helping health services and clinicians involved in airway manipulation choose the best VLs for orotracheal intubation.

Systematic review registration

The current protocol was submitted to PROSPERO on 07/01/2021.
An Evaluation of Methods for Monitoring Annual Quality Measures by Month to Predict Year-End Values
Authors: Johnson Todd R , Kookal Krishna Kumar , Applegate R Joseph , Bangar Suhasini , Yansane Alfa , White Joel M , Brandon Ryan , Simmons Kristen , Mullins Joanna , Neumann Ana , Walji Muhammad F , Kalenderian Elsbeth
Published: January 2021

Background

An increasing number of healthcare quality measures are designed for annual reporting. These measures require an entire year of data to accurately report the percentage of patients who met the measure. Annual measures give providers latitude to prioritize clinical workload and patient needs; however, they do not provide a direct means to monitor performance throughout the reporting year. Although there are many possible methods for measuring annual measures at finer-grained timescales, our applied work showed that the most obvious methods could give a misleading and inaccurate view of progress throughout the year. Neither the definitions of the annual measures, nor the research literature, provided any guidance on the best methods for interim monitoring of annual measures.

Objective

Our objective was to evaluate four different methods for monitoring annually reported quality measures monthly to best predict year-end performance throughout the reporting year.

Methods

We developed four methods for monitoring annual measures by month: 1) Monthly Proportion: The proportion of patients with one or more encounters in the month who still needed to meet the measure at their first encounter of the month and met the measure by the end of the month; (2) Monthly Lookback Proportion: The proportion of patients seen in the month who met the measure by the end of the month, regardless of whether it was met in that month or previously in the reporting year; (3) Rolling 12 Month: The annual measure reported as if each month was the twelfth month of a twelve-month reporting period; and (4) YTD (Year-to-Date) Cumulative: The proportion of patients with one or more visits from the start of the reporting year through the month who satisfy the measure. We applied each method to two annual dental quality measures using data from two reporting years, and four different dental sites. We used mean squared error (MSE) to evaluate year-end predictive performance.

Results

Method 3 (Rolling 12 Month) had the lowest MSE in 11 out of 16 cases (2 measures X 2 years X 4 sites) and lowest total MSE (262.39) across all 16 cases. In 5 of the 16 cases, YTD Cumulative had the lowest MSE.

Conclusions

The Rolling 12 Month method was best for predicting the year-end value across both measures and all four sites.
Polymeric assembly of endogenous Tuberous Sclerosis Protein Complex
Authors: Dai David L. , Hasan S. M. Naimul , Woollard Geoffrey , Bueler Stephanie A. , Julien Jean-Philippe , Rubinstein John L , Mazhab-Jafari Mohammad T.
Published: January 2021

Tuberous Sclerosis protein complex (pTSC) nucleates a proteinaceous signaling hub that integrates information about the internal and external energy status of the cell in regulation of growth and energy consumption. Biochemical and electron cryomicroscopy (cryoEM) studies of recombinant pTSC have revealed the structure and stoichiometry of the pTSC and have hinted at the possibility that the complex form large oligomers. Here, we have partially purified endogenous pTSC from fasted mammalian brains of rat and pig by leveraging a recombinant antigen binding fragment (Fab) specific for the TSC2 subunit of pTSC. We demonstrate Fabdependent purification of pTSC from membrane solubilized fractions of the brain homogenates. Negative stain electron microscopy of the samples purified from pig brain demonstrates rod-shaped protein particles with a width of 10 nm, a variable length as small as 40 nm and a high degree of conformational flexibility. Larger filaments are evident with a similar 10 nm width and up to 1 μm in length in linear and web-like organizations prepared from pig brain. These observations suggest polymerization of endogenous pTSC into filamentous super-structures.
STING suppresses cancer pain via immune and neuronal modulation
Authors: Wang Kaiyuan , Donnelly Christopher R. , Jiang Changyu , Liao Yihan , Tao Xueshu , Bang Sangsu , Lee Michael , Hilton Matthew J. , Ji Ru-Rong
Published: January 2021

Agonists of the innate immune regulator stimulator of interferon genes (STING) have shown great efficacy in promoting antitumor immunity in preclinical models, leading to their exploration in cancer immunotherapy trials. Patients with advanced stage cancers frequently suffer from severe pain as a result of bone metastasis and bone destruction, for which there is no efficacious treatment. Here, using multiple mouse models of metastatic bone cancer, we report that STING agonists confer remarkable protection against cancer pain, bone destruction, and local tumor burden. Repeated systemic administration of STING agonists robustly attenuated bone cancer-induced pain symptoms and improved locomotor function. Interestingly, STING agonists provided acute pain relief through direct neuronal modulation, asex vivoincubation of STING agonists reduced excitability of pain-sensing nociceptive neurons from tumor-bearing mice. In addition, STING agonists protected local bone destruction and reduced local tumor burden through modulation of osteoclast and immune cell function in the tumor microenvironment, providing long-term cancer pain relief. Finally, thesein vivoeffects were dependent on host-intrinsic STING andIfnar1. Overall, STING activation provides unique advantages in controlling metastatic bone cancer pain through distinct and synergistic actions on nociceptors, immune cells, and osteoclasts.
scAdapt: Virtual adversarial domain adaptation network for single cell RNA-seq data classification across platforms and species
Authors: Zhou Xiang , Chai Hua , Zeng Yuansong , Zhao Huiying , Luo Ching-Hsing , Yang Yuedong
Published: January 2021

Motivation

In single cell analyses, cell types are conventionally identified based on known marker gene expressions. Such approaches are time-consuming and irreproducible. Therefore, many new supervised methods have been developed to identify cell types for target datasets using the rapid accumulation of public datasets. However, these approaches are sensitive to batch effects or biological variations since the data distributions are different in cross-platforms or species predictions.

Results

We developed scAdapt, a virtual adversarial domain adaptation network to transfer cell labels between datasets with batch effects. scAdapt used both the labeled source and unlabeled target data to train an enhanced classifier, and aligned the labeled source centroid and pseudo-labeled target centroid to generate a joint embedding. We demonstrate that scAdapt outperforms existing methods for classification in simulated, cross-platforms, cross-species, and spatial transcriptomic datasets. Further quantitative evaluations and visualizations for the aligned embeddings confirm the superiority in cell mixing and preserving discriminative cluster structure present in the original datasets.

Availability

https://github.com/zhoux85/scAdapt.

Contact

angyd25@mail.sysu.edu.cnorluojinx5@mail.sysu.edu.cn
ExpertRNA: A new framework for RNA structure prediction
Authors: Liu Menghan , Pedrielli Giulia , Poppleton Erik , Šulc Petr , Bertsekas Dimitri P.
Published: January 2021

Ribonucleic acid (RNA) is a fundamental biological molecule that is essential to all living organisms, performing a versatile array of cellular tasks. The function of many RNA molecules is strongly related to the structure it adopts. As a result, great effort is being dedicated to the design of efficient algorithms that solve the “folding problem”: given a sequence of nucleotides, return a probable list of base pairs, referred to as the secondary structure prediction. Early algorithms have largely relied on finding the structure with minimum free energy. However, the predictions rely on effective simplified free energy models that may not correctly identify the correct structure as the one with the lowest free energy. In light of this, new, data-driven approaches that not only consider free energy, but also use machine learning techniques to learn motifs have also been investigated, and have recently been shown to outperform free energy based algorithms on several experimental data sets.

In this work, we introduce the new ExpertRNA algorithm that provides a modular framework which can easily incorporate an arbitrary number of rewards (free energy or non-parametric/data driven) and secondary structure prediction algorithms. We argue that this capability of ExpertRNA has the potential to balance out different strengths and weaknesses of state-of-the-art folding tools. We test the ExpertRNA on several RNA sequence-structure data sets, and we compare the performance of ExpertRNA against a state-of-the-art folding algorithm. We find that ExpertRNA produces, on average, more accurate predictions than the structure prediction algorithm used, thus validating the promise of the approach.
Associations between lower limb isometric torque, isokinetic torque, and explosive force with phases of reactive stepping in young, healthy adults
Authors: Saumur Tyler M. , Nestico Jacqueline , Mochizuki George , Perry Stephen D. , Mansfield Avril , Mathur Sunita
Published: January 2021

Reactive stepping is one of the only strategies that can lead to successful stabilization following a large challenge to balance. Improving function of specific muscles associated with reactive stepping may improve features of reactive balance control. Accordingly, this study aimed to determine the relationship between lower limb muscle strength and explosive force with force plate-derived timing measures of reactive stepping. Nineteen young, healthy adults (27.6 ± 3.0 years of age; 10 women: 9 men) responded to 6 perturbations (~13-15% of body weight) using an anterior lean-and-release system (causing a forward fall), where they were instructed to recover balance in as few steps as possible. Foot-off, swing, and restabilization times were estimated from force plates. Peak isokinetic torque, isometric torque, and explosive force of the knee extensors/flexors and plantar/dorsiflexors were measured using isokinetic dynamometry. Correlations were run based ona priorihypotheses and corrected for the number of comparisons (Bonferroni) for each variable. Knee extensor explosive force was negatively correlated with swing time (r = −0.582, p = 0.009). Knee flexor peak isometric torque also showed a negative association with restabilization time (r = −0.459, p = 0.048), however this was not statistically significant after correcting for multiple comparisons. There was no significant relationship between foot-off time and knee or plantar flexor explosive force (p > 0.025). These findings suggest that there may be utility to identifying specific aspects of reactive step timing when studying the relationship between muscle strength and reactive balance control. Exercise training aimed at improving falls risk should consider targeting specific aspects of muscle strength depending on specific deficits in reactive stepping.
In-Pero: Exploiting deep learning embeddings of protein sequences to predict the localisation of peroxisomal proteins
Authors: Anteghini Marco , dos Santos Vitor AP Martins , Saccenti Edoardo
Published: January 2021

Peroxisomes are ubiquitous membrane-bound organelles, and aberrant localisation of peroxisomal proteins contributes to the pathogenesis of several disorders. Many computational methods focus on assigning protein sequences to subcellular compartments, but there are no specific tools tailored for the sub-localisation (matrix vs membrane) of peroxisome proteins. We present here In-Pero, a new method for predicting protein sub-peroxisomal cellular localisation. In-Pero combines standard machine learning approaches with recently proposed multi-dimensional deep-learning representations of the protein amino-acid sequence. It showed a classification accuracy above 0.9 in predicting peroxisomal matrix and membrane proteins. The method is trained and tested using a double cross-validation approach on a curated data set comprising 160 peroxisomal proteins with experimental evidence for sub-peroxisomal localisation. We further show that the proposed approach can be easily adapted (In-Mito) to the prediction of mitochondrial protein localisation obtaining performances for certain classes of proteins (matrix and inner-membrane) superior to existing tools. All data sets and codes are available athttps://github.com/MarcoAnteghiniand atwww.systemsbiology.nl
Lipophilic Nanocrystal Prodrug-Release Defines the Extended Pharmacokinetic Profiles of a Year-Long Cabotegravir
Authors: Gautam Nagsen , McMillan JoEllyn M. , Kumar Devendra , Bade Aditya N. , Pan Qiaoyu , Kulkarni Tanmay A. , Li Wenkuan , Smith Nathan A , Dyavar Shetty Bhagya L. , Sillman Brady , Szlachetka Adam , Edagwa Benson J. , Gendelman Howard E. , Alnouti Yazen
Published: January 2021

A single, once every eight-week cabotegravir (CAB) long-acting parenteral is more effective than daily oral emtricitabine and tenofovir disoproxil fumarate in preventing human immunodeficiency virus type one (HIV-1) transmission. Extending CAB dosing to a yearly injectable can advance efforts leading to the elimination of viral transmission. The current submission adds rigor, reproducibility and mechanistic insights for the extended apparent half-life of a yearlong antiretroviral injectable. Pharmacokinetic (PK) profiles of a nanoformulated fatty acid ester CAB prodrug (named NM2CAB) were affirmed at two academic and one contract research laboratory. PK profiles showed plasma CAB levels at or above the protein-adjusted 90% inhibitory concentration for up to one year after a single dose. Measures of drug biodistribution demonstrated sustained native drug at the muscle injection site and in lymphoid tissues (spleen and lymph nodes). The results paralleled NM2CAB uptake and retention in human macrophages. NM2CAB nanocrystals were stable in blood, tissue and liver homogenates. The long apparent drug half-life followed pH-dependent slow prodrug release in weeks from the nanocrystal. In contrast, solubilized prodrug was hydrolyzed in hours in plasma and tissues recorded from multiple mammalian species at basic pH. No measurable toxicities were recorded. These results, taken together, affirm the pharmacological mechanistic properties of a year-long nanoformulated CAB prodrug supporting the established protocol design for formulation safety, rigor and reproducibility.
Identifying neuron subtype-specific metabolic network changes in single cell transcriptomics of Alzheimer’s Disease using perturb-Met
Authors: Wang Yuliang
Published: January 2021

Metabolic aberrations are a prominent feature of Alzheimer’s Disease (AD). Different neuronal subtypes have selective vulnerability in AD. Despite the recent advance of single cell and single nucleus RNA-seq of AD brains, genome-scale metabolic network changes in neuronal subtypes have not been systematically studied with detail. To bridge this knowledge gap, I developed a computational method called perturb-Met that can uncover transcriptional dysregulation centered at hundreds of metabolites in a metabolic network. perturb-Met successfully recapitulated known glycolysis, cholesterol, and other metabolic defects in APOE4-neurons and microglia, many of which are missed by current methods. Applying perturb-Met on AD snRNA-seq data, I revealed that the four neuronal subtypes in the entorhinal cortex shows subtype-specific metabolic changes, namely mitochondrial complex I metabolism, ganglioside metabolism, galactose and heparan sulfate metabolism, as well as glucose and lipid metabolism, respectively. perturb-Met also revealed significant changes in protein glycosylation in the neuron subtype specifically found in AD brains. These subtype-specific metabolic changes may potentially underlie their selective vulnerability in AD. perturb-Met is a valuable tool to discover potential metabolic network changes in many other single cell or bulk transcriptomic studies.
Resonance in physiologically structured population models
Authors: Gross Kevin , de Roos André M.
Published: January 2021

Ecologists have long sought to understand how the dynamics of natural populations are affected by the environmental variation those populations experience. A transfer function is a useful tool for this purpose, as it uses linearization theory to show how the frequency spectrum of the fluctuations in a population’s abundance relates to the frequency spectrum of environmental variation. Here, we show how to derive and to compute the transfer function for a continuous-time model of a population that is structured by a continuous individual-level state variable such as size. To illustrate, we derive, compute, and analyze the transfer function for a size-structured population model of stony corals with open recruitment, parameterized for a common Indo-Pacific coral species complex. This analysis identifies a sharp multi-decade resonance driven by space competition between existing coral colonies and incoming recruits. The resonant frequency is most strongly determined by the rate at which colonies grow, and the potential for resonant oscillations is greatest when colony growth is only weakly density-dependent. While these resonant oscillations are unlikely to be a predominant dynamical feature of degraded reefs, they suggest dynamical possibilities for marine invertebrates in more pristine waters. The size-structured model that we analyze is a leading example of a broader class of physiologically structured population models, and the methods we present should apply to a wide variety of models in this class.
Packing the Standard Genetic Code in its box: 3-dimensional late Crick wobble
Authors: Yarus Michael
Published: January 2021

Minimally-evolved codes are constructed with randomly chosen Standard Genetic Code (SGC) triplets, and completed with completely random triplet assignments. Such “genetic codes” have not evolved, but retain SGC qualities. Retained qualities are inescapable, part of the logic of code evolution. For example, sensitivity of coding to arbitrary assignments, which must be <≈ 10%, is intrinsic. Such sensitivity comes from elementary combinatorial properties of coding, and constrains any SGC evolution hypothesis. Similarly, evolution of last-evolved functions is difficult, due to late kinetic phenomena, likely common across codes. Census of minimally-evolved code assignments shows that shape and size of wobble domains controls packing into a coding table, strongly shifting accuracy of codon assignments. Access to the SGC therefore requires a plausible pathway to limited randomness, avoiding difficult completion while packing a highly ordered, degenerate code into a fixed three-dimensional space. Late Crick wobble in a 3-dimensional genetic code assembled by lateral transfer satisfies these varied, simultaneous requirements. By allowing parallel evolution of SGC domains, it can yield shortened evolution to SGC-level order, and allow the code to arise in smaller populations. It effectively yields full codes. Less obviously, it unifies well-studied sources for order in amino acid coding, including a stereochemical minority of triplet-amino acid associations. Finally, fusion of its intermediates into the definitive SGC is credible, mirroring broadly-accepted later cellular evolution.
Spatial pattern analysis of line-segment data in ecology
Authors: Yates Luke A. , Brook Barry W. , Buettel Jessie C.
Published: January 2021

The spatial analysis of linear features (lines and curves) is a challenging and rarely attempted problem in ecology. Existing methods are typically expressed in abstract mathematical formalism, making it difficult to assess their relevance and transferability into an ecological setting. A set of concrete and accessible tools is needed.

We develop a new method to analyse the spatial patterning of line-segment data. It is based on a generalisation of Ripley’sK-function and includes an analogue of the transformedL-function, together with estimators and theoretical expectation values. We introduce a class of line-segment processes, related to the Boolean model, which we use in conjunction with Monte-Carlo methods and information criteria to generate and compare candidate models. We demonstrate the utility of our method using fallen tree (dead log) data collected from two one-hectare Australian tall eucalypt forest plots.

Comparing six line-segment models, we find for both plots that the distribution of fallen logs is best explained by plot-level spatial heterogeneity. The use of non-uniform distributions to model dead-log orientation on the forest floor improves model performance in one of the two sites. Our case study highlights the challenges of model comparison in spatial-pattern analysis, where Monte-Carlo approaches based on the discrepancy of simulated summary functions can generate a different ranking of models than that of information criteria.

These methods are of a general nature and are applicable to any line-segment data. In the context of forest ecology, the integration of fallen logs as linear structural features in a landscape with the point locations of living trees, and a quantification of their interactions, will yield new insights into the functional and structural role of tree fall in forest communities and their enduring post-mortem ecological legacy as spatially distributed decomposing logs.
Modelling pooling strategies for SARS-CoV-2 testing in a university setting
Authors: Hemani Gibran , Thomas Amy C , Walker Josephine G. , Trickey Adam , Nixon Emily , Ellis David , Kwiatkowska Rachel , Relton Caroline , Danon Leon , Christensen Hannah , Brooks-Pollock Ellen
Published: January 2021

Pre-symptomatic and asymptomatic transmission of SARS-CoV-2 are important elements in the Covid-19 pandemic, and until vaccines are made widely available there remains a reliance on testing to manage the spread of the disease, alongside non-pharmaceutical interventions such as measures to reduce close social interactions. In the UK, many universities opened for blended learning for the 2020-2021 academic year, with a mixture of face to face and online teaching. In this study we present a simulation framework to evaluate the effectiveness of different asymptomatic testing strategies within a university setting, across a range of transmission scenarios. We show that when positive cases are clustered by known social structures, such as student households, the pooling of samples by these social structures can substantially reduce the total cost of conducting RT-qPCR tests. We also note that routine recording of quantitative RT-qPCR results would facilitate future modelling studies.
Clinical utility of Corona Virus Disease-19 serum IgG, IgM, and neutralizing antibodies and inflammatory markers
Authors: Schaefer Ernst J. , Comite Florence , Dulipsingh Latha , Lang Maxine , Jimison Jessica , Grajower Martin M. , Lebowitz Nathan E. , Geller Andrew S. , Diffenderfer Margaret R. , He Lihong , Breton Gary , Dansinger Michael L. , Saida Ben , Yuan Chong
Published: January 2021

Most deaths from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection occur in older subjects. We assessed age effects and clinical utility of serum SARS-CoV-2 immunoglobulin G (IgG), immunoglobulin M (IgM), and neutralizing antibodies and serum inflammatory markers. Serum IgG, IgM, and neutralizing antibody levels were measured using chemiluminescence assays from Diazyme (Poway, CA), while serum interleukin-6 (IL-6), C reactive protein (CRP), and ferritin were measured with immunoassays obtained from Roche (Indianapolis, IN). In 79,005 subjects, IgG and IgM levels were positive (≥1.0 arbitrary units [AU]/mL) in 5.29% and 3.25% of subjects, respectively. In antibody positive subjects, median IgG levels were 3.93 AU/mL if <45 years of age, 10.18 AU/mL if 45-64 years of age, and 10.85 AU/mL if ≥65 years of age (p<0.0001). In SARS-CoV-2 RNA positive cases, family members and exposed subjects (n=1,111), antibody testing was found to be valuable for case finding, and persistent IgM levels were associated with chronic symptoms. In non-hospitalized and hospitalized subjects assessed for SARS-CoV-2 RNA (n=278), median IgG levels in AU/mL were 0.05 in negative subjects (n=100), 14.83 in positive outpatients (n=129), and 30.61 in positive hospitalized patients (n=49, p<0.0001). Neutralizing antibody levels correlated significantly with IgG (r=0.875; p<0.0001). Two or more of the criteria of IL-6 ≥10 pg/mL, CRP ≥10 mg/L, and/or IgM >1.0 AU/mL occurred in 97.7% of inpatients versus 1.8% of outpatients (>50-fold relative risk, C statistic 0.986, p<0.0001). Our data indicate that: 1) IgG levels are significantly higher in positive older subjects, possibly to compensate for decreased cellular immunity with aging; 2) IgG levels are important for case finding in family clusters; 3) IgG levels are significantly correlated with neutralizing antibody levels; 4) persistently elevated IgM levels are associated with chronic disease; and 5) markedly elevated IL-6, hs-CRP, and/or positive IgM accurately identify SARS-CoV-2 RNA positive subjects requiring hospitalization.
SARS-CoV-2 B.1.1.7 sensitivity to mRNA vaccine-elicited, convalescent and monoclonal antibodies
Authors: Collier Dami A. , De Marco Anna , Ferreira Isabella A.T.M. , Meng Bo , Datir Rawlings , Walls Alexandra C. , Kemp S Steven A. , Bassi Jessica , Pinto Dora , Fregni Chiara Silacci , Bianchi Siro , Tortorici M. Alejandra , Bowen John , Culap Katja , Jaconi Stefano , Cameroni Elisabetta , Snell Gyorgy , Pizzuto Matteo S. , Pellanda Alessandra Franzetti , Garzoni Christian , Riva Agostino ,   The CITIID-NIHR BioResource COVID-19 Collaboration, Elmer Anne , Kingston Nathalie , Graves Barbara , McCoy Laura E , Smith Kenneth GC , Bradley John R. , Temperton Nigel , Ceron-Gutierrez L Lourdes , Barcenas-Morales Gabriela ,   The COVID-19 Genomics UK (COG-UK) consortium, Harvey William , Virgin Herbert W. , Lanzavecchia Antonio , Piccoli Luca , Doffinger Rainer , Wills Mark , Veesler David , Corti Davide , Gupta Ravindra K.
Published: January 2021

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) transmission is uncontrolled in many parts of the world, compounded in some areas by higher transmission potential of the B1.1.7 variant now seen in 50 countries. It is unclear whether responses to SARS-CoV-2 vaccines based on the prototypic strain will be impacted by mutations found in B.1.1.7. Here we assessed immune responses following vaccination with mRNA-based vaccine BNT162b2. We measured neutralising antibody responses following a single immunization using pseudoviruses expressing the wild-type Spike protein or the 8 amino acid mutations found in the B.1.1.7 spike protein. The vaccine sera exhibited a broad range of neutralising titres against the wild-type pseudoviruses that were modestly reduced against B.1.1.7 variant. This reduction was also evident in sera from some convalescent patients. Decreased B.1.1.7 neutralisation was also observed with monoclonal antibodies targeting the N-terminal domain (9 out of 10), the Receptor Binding Motif (RBM) (5 out of 31), but not in neutralising mAbs binding outside the RBM. Introduction of the E484K mutation in a B.1.1.7 background to reflect newly emerging viruses in the UK led to a more substantial loss of neutralising activity by vaccine-elicited antibodies and mAbs (19 out of 31) over that conferred by the B.1.1.7 mutations alone. E484K emergence on a B.1.1.7 background represents a threat to the vaccine BNT162b.