bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identifying human postural dynamics and control from unperturbed balance
Authors: Lee Jongwoo , Zhang Kuangen , Hogan Neville 
Published: March 2021

Abstract
Background
Upright standing requires control of an inherently unstable multi-joint human body within a small base of support, despite biological motor and / or sensory noise which challenge balance. Without applying perturbations, system identification methods have been regarded as inadequate, because the relevant internal biological noise processes are not accessible to direct measurement. As a result, unperturbed balance studies have been limited to investigation of behavioral patterns rather than possible underlying control strategies.

Methods
In this paper, we present a mathemathically rigorous system identification method that is applicable to study the dynamics and control of unperturbed balance. The method is derived from autocorrelation matrices with non-zero time lags and identifies the system matrix of a discrete-time dynamic system in the presence of unknown noise processes, without requiring any information about the strength of the noise.

Results
Unlike reasonable ‘least-squares’ approaches, the performance of the new method is consistent across a range of different combinations of internal and measurement noise strengths, even when measurement noise is substantial. We present a numerical example of a model that simulates human upright balancing and show that its dynamics can be identified accurately. With a biomechanically reasonable choice of state and input variables, a state feedback controller can also be identified.

Conclusions
This study provides a new method to correctly identify the dynamics of human standing without the need for known external perturbations. The method was numerically validated using simulation that included realistic features of human balance. This method avoids potential issues of adaptation or possible reflex responses evoked by external perturbations, and does not require expensive in-lab, high-precision measurement equipment. It may eventually enable diagnosis and treatment of individuals with impaired balance, and the development of safe and effective assistive and / or rehabilitative technologies.
An optimal glycemic load range is better for reducing obesity and diabetes risk among middle-aged and elderly adults
Authors: He Fengyi , Chen Chaogang , Li Feng , Qi Yiqin , Lin Xiuhong , Liang Ping , Ren Meng , Yan Li 
Published: March 2021

AbstractBackgroundDue to the lack of evidence, advice pertaining to glycemic load (GL) can be misleading. Does the excessive restriction of GL, mostly through an extreme reduction in carbohydrate intake, result in a relatively high intake of fat and protein and result in overweight and obesity? This study was performed to initially explore the optimal GL range.MethodsA cross-sectional study involving 2029 participants aged 40 years or older in Guangzhou, China was conducted. Participants were divided into four groups according to cluster analysis. Dietary data were assessed using a previously validated 3-day food record.ResultsInstead of participants with the highest [cluster 1, median (interquartile ranges) GL was 112(107–119)/1000 kcal] and the lowest GL intake [cluster 4, 90(82–96)/1000 kcal], those with moderate GL intakes [clusters 2 and 3, 93(85–102) and 93(85–99)/1000 kcal, respectively] had a lower prevalence of overweight, obesity and diabetes. In addition, clusters 2 and 3 were more consistent with the macronutrient intake reference with adequate micronutrient intake. Therefore, the optimal GL range was determined to be (85–100)/1000 kcal, rather than “lower is better”.ConclusionsReducing the GL intake to prevent diabetes deserves more attention in the context of a balanced diet. An appropriate GL may be better than excessive restriction.
Evaluation of a highly refined prediction model in knowledge-based volumetric modulated arc therapy planning for cervical cancer
Authors: Wang Mingli , Gu Huikuan , Hu Jiang , Liang Jian , Xu Sisi , Qi Zhenyu 
Published: March 2021

Abstract
Background and purpose
To explore whether a highly refined dose volume histograms (DVH) prediction model can improve the accuracy and reliability of knowledge-based volumetric modulated arc therapy (VMAT) planning for cervical cancer.

Methods and materials
The proposed model underwent repeated refining through progressive training until the training samples increased from initial 25 prior plans up to 100 cases. The estimated DVHs derived from the prediction models of different runs of training were compared in 35 new cervical cancer patients to analyze the effect of such an interactive plan and model evolution method. The reliability and efficiency of knowledge-based planning (KBP) using this highly refined model in improving the consistency and quality of the VMAT plans were also evaluated.

Results
The prediction ability was reinforced with the increased number of refinements in terms of normal tissue sparing. With enhanced prediction accuracy, more than 60% of automatic plan-6 (AP-6) plans (22/35) can be directly approved for clinical treatment without any manual revision. The plan quality scores for clinically approved plans (CPs) and manual plans (MPs) were on average 89.02 ± 4.83 and 86.48 ± 3.92 (p < 0.001). Knowledge-based planning significantly reduced the Dmean and V18 Gy for kidney (L/R), the Dmean, V30 Gy, and V40 Gy for bladder, rectum, and femoral head (L/R).

Conclusion
The proposed model evolution method provides a practical way for the KBP to enhance its prediction ability with minimal human intervene. This highly refined prediction model can better guide KBP in improving the consistency and quality of the VMAT plans.
Plaque associated microglia hyper-secrete extracellular vesicles and accelerate tau propagation in a humanized APP mouse model
Authors: Clayton Kevin , Delpech Jean Christophe , Herron Shawn , Iwahara Naotoshi , Ericsson Maria , Saito Takashi , Saido Takaomi C. , Ikezu Seiko , Ikezu Tsuneya 
Published: March 2021

Abstract
Background
Recent studies suggest that microglia contribute to tau pathology progression in Alzheimer’s disease. Amyloid plaque accumulation transforms microglia, the primary innate immune cells in the brain, into neurodegenerative microglia (MGnD), which exhibit enhanced phagocytosis of plaques, apoptotic neurons and dystrophic neurites containing aggregated and phosphorylated tau (p-tau). It remains unclear how microglia promote disease progression while actively phagocytosing pathological proteins, therefore ameliorating pathology.

Methods
Adeno-associated virus expressing P301L tau mutant (AAV-P301L-tau) was stereotaxically injected into the medial entorhinal cortex (MEC) in C57BL/6 (WT) and humanized APP mutant knock-in homozygote (AppNL-G-F) mice at 5 months of age. Mice were fed either chow containing a colony stimulating factor-1 receptor inhibitor (PLX5622) or control chow from 4 to 6 months of age to test the effect of microglia depletion. Animals were tested at 6 months of age for immunofluorescence, biochemistry, and FACS of microglia. In order to monitor microglial extracellular vesicle secretion in vivo, a novel lentiviral EV reporter system was engineered to express mEmerald-CD9 (mE-CD9) specifically in microglia, which was injected into the same region of MEC.

Results
Expressing P301L tau mutant in the MEC induced tau propagation to the granule cell layer of the hippocampal dentate gyrus, which was significantly exacerbated in AppNL-G-F mice compared to WT control mice. Administration of PLX5622 depleted nearly all microglia in mouse brains and dramatically reduced propagation of p-tau in WT and to a greater extent in AppNL-G-F mice, although it increased plaque burden and plaque-associated p-tau+ dystrophic neurites. Plaque-associated MGnD microglia strongly expressed an EV marker, tumor susceptibility gene 101, indicative of heightened synthesis of EVs. Intracortical injection of mE-CD9 lentivirus successfully induced microglia-specific expression of mE-CD9+ EV particles, which were significantly enhanced in Mac2+ MGnD microglia compared to Mac2− homeostatic microglia. Finally, consecutive intracortical injection of mE-CD9 lentivirus and AAV-P301L-tau into AppNL-G-F mice revealed encapsulation of p-tau in microglia-specific mE-CD9+ EVs as determined by super-resolution microscopy and immuno-electron microscopy.

Discussion
Our findings suggest that MGnD microglia hyper-secrete p-tau+ EVs while compacting Aβ plaques and clearing NP tau, which we propose as a novel mechanistic link between amyloid plaque deposition and exacerbation of tau propagation in AppNL-G-F mice.
Seroprevalence and associated risk factors for vector-borne pathogens in dogs from Egypt
Authors: Selim Abdelfattah , Alanazi Abdullah D. , Sazmand Alireza , Otranto Domenico 
Published: March 2021

Abstract
Background
Dogs play an important role as reservoirs of many zoonotic vector-borne pathogens worldwide, yet reports of canine vector-borne diseases (CVBDs) in Egypt are scarce.

Methods
Serum samples were collected from pet dogs (n = 500) of the three most common breeds (German Shepherd, Rottweiler and Pit Bull) in five Governates of Cairo (n = 230), Giza (n = 110), Al-Qalyubia (n = 60), Al-Gharbia (n = 60) and Kafr El-Sheikh (n = 40) with a hot desert climate. The presence of antibodies to Anaplasma spp. (A. phagocytophilum, A. platys), Ehrlichia spp. (E. canis, E. chaffeensis, E. ewingii), Borrelia burgdorferi (s.l.) and Dirofilaria immitis were assessed using IDEXX SNAP® 4Dx® ELISA tests. For each pathogen, risk factors (i.e. geographical area, keeping condition, sex, age, breed, tick infestation, weekly sanitation of dog enclosures and application of ectoparasiticides) were evaluated by logistic regression approach.

Results
In total, 18.2% (n = 91, 95% CI 15.1–21.8) of dogs scored seropositive for at least one pathogen, the most frequent being Ehrlichia spp. (n = 56; 11.2%; 95% CI 8.7–14.3) followed by Anaplasma spp. (n = 33; 6.6%, 95% CI 4.7–9.1), Borrelia burgdorferi (s.l.) (n = 9; 1.8%, 95% CI 0.9–3.4) and D. immitis (n = 7; 1.4%, 95% CI 0.9–2.9). In the tested population, 15.4% (95% CI 12.5–18.8) of dogs were exposed to a single pathogen while 2.4 (95% CI 1.4–4.2) and 0.4% (95% CI 0.1–1.4) were simultaneously exposed to two or three pathogens, respectively. Major risk factors associated with VBDs were living outdoors (Anaplasma spp., P = 0.0001; Ehrlichia spp., P = 0.0001), female sex (Ehrlichia spp., P = 0.005), German Shepherd breed (Anaplasma spp., P = 0.04; Ehrlichia spp., P = 0.03), tick infestation (Anaplasma spp., P = 0.0001; Ehrlichia spp., P = 0.0001; B. burgdorferi (s.l.), P = 0.003; D. immitis, P = 0.02), irregular sanitation (Anaplasma spp., P = 0.0001; Ehrlichia spp., P = 0.0001; B. burgdorferi (s.l.), P = 0.002; D. immitis, P = 0.01) and not using ectoparasiticides (Anaplasma spp., P = 0.0001; Ehrlichia spp., P = 0.0001; B. burgdorferi (s.l.), P = 0.007).

Conclusion
To our knowledge, this is the first large-scale seroepidemiological study of CVBDs in Egypt. Considering that all of the detected pathogens are potentially zoonotic, effective ectoparasite control strategies, regular examination of pet dogs and successful chemoprophylaxis are advocated.

Graphical Abstract
Soluble receptor for advanced glycation end products (sRAGE) as a biomarker of COVID-19 disease severity and indicator of the need for mechanical ventilation, ARDS and mortality
Authors: Lim Adeline , Radujkovic Aleksandar , Weigand Markus A. , Merle Uta 
Published: March 2021

Abstract
Background
COVID-19 pneumonia and subsequent respiratory failure is causing an immense strain on intensive care units globally. Early prediction of severe disease enables clinicians to avoid acute respiratory distress syndrome (ARDS) development and improve management of critically ill patients. The soluble receptor of advanced glycation endproducts (sRAGE) is a biomarker shown to predict ARDS. Although sRAGE level varies depending on the type of disease, there is limited information available on changes in sRAGE levels in COVID-19. Therefore, sRAGE was measured in COVID-19 patients to determine sRAGE level variation in COVID-19 severity and to examine its ability to predict the need for mechanical ventilation (MV) and mortality in COVID-19.

Methods
In this single-centre observational cohort study in Germany, serum sRAGE during acute COVID-19, 20 weeks after the start of COVID-19 symptoms, as well as in control groups of non-COVID-19 pneumonia patients and healthy controls were measured using ELISA. The primary endpoint was severe disease (high-flow nasal oxygen therapy (HFNO)/MV and need of organ support). The secondary endpoints were respiratory failure with need of MV and 30-day mortality. The area under the curve (AUC), cut-off based on Youden’s index and odds ratio with 95% CI for sRAGE were calculated with regard to prediction of MV need and mortality.

Results
Serum sRAGE in 164 COVID-19 patients, 101 matched COVID-19 convalescent patients, 23 non-COVID-19 pneumonia patients and 15 healthy volunteers were measured. sRAGE level increased with COVID-19 severity, need for oxygen therapy, HFNO/MV, ARDS severity, need of dialysis and catecholamine support, 30-day mortality, sequential organ failure assessment (SOFA) and quick SOFA (qSOFA) score. sRAGE was found to be a good predictor of MV need in COVID-19 inpatients and mortality with an AUC of 0.871 (0.770–0.973) and 0.903 (0.817–0.990), respectively. When adjusted for male gender, age, comorbidity and SOFA score ≥ 3, sRAGE was independently associated with risk of need for HFNO/MV. When adjusted for SOFA score ≥ 3, sRAGE was independently associated with risk of need for MV.

Conclusions
Serum sRAGE concentrations are elevated in COVID-19 patients as disease severity increases. sRAGE should be considered as a biomarker for predicting the need for MV and mortality in COVID-19.
Why do some inter-organisational collaborations in healthcare work when others do not? A realist review
Authors: Aunger Justin Avery , Millar Ross , Greenhalgh Joanne , Mannion Russell , Rafferty Anne-Marie , McLeod Hugh 
Published: March 2021

Abstract
Background
Inter-organisational collaboration is increasingly prominent within contemporary healthcare systems. A range of collaboration types such as alliances, networks, and mergers have been proposed as a means to turnaround organisations, by reducing duplication of effort, enabling resource sharing, and promoting innovations. However, in practice, due to the complexity of the process, such efforts are often rife with difficulty. Notable contributions have sought to make sense of this area; however, further understanding is needed in order to gain a better understanding of why some inter-organisational collaborations work when others do not, to be able to more effectively implement collaborations in the future.

Methods
Realist review methodology was used with the intention of formulating context-mechanism-outcome configurations (CMOCs) to explain how inter-organisational collaborations work and why, combining systematic and purposive literature search techniques. The systematic review encompassed searches for reviews, commentaries, opinion pieces, and case studies on HMIC, MEDLINE, PsycINFO, and Social Policy and Practice databases, and further searches were conducted using Google Scholar. Data were extracted from included studies according to relevance to the realist review.

Results
Fifty-three papers were included, informing the development of programme theories of how, why, and when inter-organisational collaborations in healthcare work. Formulation of our programme theories incorporated the concepts of partnership synergy and collaborative inertia and found that it was essential to consider mechanisms underlying partnership functioning, such as building trust and faith in the collaboration to maximise synergy and thus collaborative performance. More integrative or mandated collaboration may lean more heavily on contract to drive collaborative behaviour.

Conclusion
As the first realist review of inter-organisational collaborations in healthcare as an intervention for improvement, this review provides actionable evidence for policymakers and implementers, enhancing understanding of mechanisms underlying the functioning and performing of inter-organisational collaborations, as well as how to configure the context to aid success. Next steps in this research will test the results against further case studies and primary data to produce a further refined theory.

Systematic review registration
PROSPERO CRD42019149009
Direct impact of commonly used dietary emulsifiers on human gut microbiota
Authors: Naimi Sabrine , Viennois Emilie , Gewirtz Andrew T. , Chassaing Benoit 
Published: March 2021

Abstract
Background
Epidemiologic evidence and animal studies implicate dietary emulsifiers in contributing to the increased prevalence of diseases associated with intestinal inflammation, including inflammatory bowel diseases and metabolic syndrome. Two synthetic emulsifiers in particular, carboxymethylcellulose and polysorbate 80, profoundly impact intestinal microbiota in a manner that promotes gut inflammation and associated disease states. In contrast, the extent to which other food additives with emulsifying properties might impact intestinal microbiota composition and function is not yet known.

Methods
To help fill this knowledge gap, we examined here the extent to which a human microbiota, maintained ex vivo in the MiniBioReactor Array model, was impacted by 20 different commonly used dietary emulsifiers. Microbiota density, composition, gene expression, and pro-inflammatory potential (bioactive lipopolysaccharide and flagellin) were measured daily.

Results
In accordance with previous studies, both carboxymethylcellulose and polysorbate 80 induced a lasting seemingly detrimental impact on microbiota composition and function. While many of the other 18 additives tested had impacts of similar extent, some, such as lecithin, did not significantly impact microbiota in this model. Particularly stark detrimental impacts were observed in response to various carrageenans and gums, which altered microbiota density, composition, and expression of pro-inflammatory molecules.

Conclusions
These results indicate that numerous, but not all, commonly used emulsifiers can directly alter gut microbiota in a manner expected to promote intestinal inflammation. Moreover, these data suggest that clinical trials are needed to reduce the usage of the most detrimental compounds in favor of the use of emulsifying agents with no or low impact on the microbiota.
Revealing taxon-specific heavy metal-resistance mechanisms in denitrifying phosphorus removal sludge using genome-centric metaproteomics
Authors: Lin Yuan , Wang Liye , Xu Ke , Li Kan , Ren Hongqiang 
Published: March 2021

AbstractBackgroundDenitrifying phosphorus removal sludge (DPRS) is widely adopted for nitrogen and phosphorus removal in wastewater treatment but faces threats from heavy metals. However, a lack of understanding of the taxon-specific heavy metal-resistance mechanisms hinders the targeted optimization of DPRS’s robustness in nutrient removal.ResultsWe obtained 403 high- or medium-quality metagenome-assembled genomes from DPRS treated by elevating cadmium, nickel, and chromium pressure. Then, the proteomic responses of individual taxa under heavy metal pressures were characterized, with an emphasis on functions involving heavy metal resistance and maintenance of nutrient metabolism. When oxygen availability was constrained by high-concentration heavy metals, comammoxNitrospiraoverproduced highly oxygen-affinitive hemoglobin and electron-transporting cytochrome c-like proteins, underpinning its ability to enhance oxygen acquisition and utilization. In contrast,Nitrosomonasoverexpressed ammonia monooxygenase and nitrite reductase to facilitate the partial nitrification and denitrification process for maintaining nitrogen removal. Comparisons between phosphorus-accumulating organisms (PAOs) demonstrated different heavy metal-resistance mechanisms adopted byDechloromonasandCandidatusAccumulibacter, despite their high genomic similarities. In particular,Dechloromonasoutcompeted the canonical PAOCandidatusAccumulibacter in synthesizing polyphosphate, a potential public good for heavy metal detoxification. The superiority ofDechloromonasin energy utilization, radical elimination, and damaged cell component repair also contributed to its dominance under heavy metal pressures. Moreover, the enrichment analysis revealed that functions involved in extracellular polymeric substance formation, siderophore activity, and heavy metal efflux were significantly overexpressed due to the related activities of specific taxa.ConclusionsOur study demonstrates that heavy metal-resistance mechanisms within a multipartite community are highly heterogeneous between different taxa. These findings provide a fundamental understanding of how the heterogeneity of individual microorganisms contributes to the metabolic versatility and robustness of microbiomes inhabiting dynamic environments, which is vital for manipulating the adaptation of microbial assemblages under adverse environmental stimuli.
Geospatial epidemiology of leprosy in northwest Bangladesh: a 20-year retrospective observational study
Authors: Bulstra Caroline A. , Blok David J. , Alam Khorshed , Butlin C. Ruth , Roy Johan Chandra , Bowers Bob , Nicholls Peter , de Vlas Sake J. , Richardus Jan Hendrik 
Published: March 2021

Abstract
Background
Leprosy is known to be unevenly distributed between and within countries. High risk areas or ‘hotspots’ are potential targets for preventive interventions, but the underlying epidemiologic mechanisms that enable hotspots to emerge, are not yet fully understood. In this study, we identified and characterized leprosy hotspots in Bangladesh, a country with one of the highest leprosy endemicity levels globally.

Methods
We used data from four high-endemic districts in northwest Bangladesh including 20 623 registered cases between January 2000 and April 2019 (among ~ 7 million population). Incidences per union (smallest administrative unit) were calculated using geospatial population density estimates. A geospatial Poisson model was used to detect incidence hotspots over three (overlapping) 10-year timeframes: 2000–2009, 2005–2014 and 2010–2019. Ordinal regression models were used to assess whether patient characteristics were significantly different for cases outside hotspots, as compared to cases within weak (i.e., relative risk (RR) of one to two), medium (i.e., RR of two to three), and strong (i.e., RR higher than three) hotspots.

Results
New case detection rates dropped from 44/100 000 in 2000 to 10/100 000 in 2019. Statistically significant hotspots were identified during all timeframes and were often located at areas with high population densities. The RR for leprosy was up to 12 times higher for inhabitants of hotspots than for people living outside hotspots. Within strong hotspots (1930 cases among less than 1% of the population), significantly more child cases (i.e., below 15 years of age) were detected, indicating recent transmission. Cases in hotspots were not significantly more likely to be detected actively.

Conclusions
Leprosy showed a heterogeneous distribution with clear hotspots in northwest Bangladesh throughout a 20-year period of decreasing incidence. Findings confirm that leprosy hotspots represent areas of higher transmission activity and are not solely the result of active case finding strategies.