bluuebunny/crossref_metadata_2025 huggingface dataset:
Natural Gas as a Key Alternative Energy Source in Sustainable Renewable Energy Transition: A Mini Review
Authors: Mohammad Norsyahida , Mohamad Ishak Waznatol Widad , Mustapa Siti Indati , Ayodele Bamidele Victor
Published: May 2021

Energy security and sustainability are undeniably the main concerns in combatting climate change. While an immediate call for all-green and renewable energy seems to be impossible due to huge financial implications and inadequate supporting energy structure, an alternative to fossil fuels needs to be established. Natural gas, a naturally occurring fossil gas is a cleaner energy source option compared to other fossil fuels such as coal, bitumen, and diesel. Natural gas makes the best fit for a sustainable renewable energy transition in any country around the globe due to its competitiveness towards other fossil fuels such as coal and its ability to aid the integration of renewables. This review highlights the technological pathways of utilizing natural gas in a transition to sustainable renewable energy systems, with a focus on the natural gas components and resources point of view for ASEAN member states (AMS). Policies that support the development of natural gas as a key alternative energy source in sustainable renewable energy transition would also be reviewed. This review aims to provide a thorough guide to researchers, stakeholders, and policymakers to construct and support efficient, reliable, affordable, sustainable, and environmentally friendly energy systems utilizing the abundant inexpensive natural gas.
Elastoplastic Deformation and Fracture Behavior of Cr-Coated Zr-4 Alloys for Accident Tolerant Fuel Claddings
Authors: Ma Xianfeng , Zhang Wenjie , Chen Zejia , Yang Dong , Jiang Jishen , Song Ligang , Tu Jiajun , Zhai Hailin
Published: May 2021

In situ tensile tests and crystal plasticity finite element modeling (CPFEM) were used to study the deformation and cracking behaviors of Cr-coated Zr-4 alloys for accident tolerant fuel claddings under tension. Based on the experimental results, vertical cracks in the coating generally initiated from the interface between the coating and the substrate, and expanded to the top surface of the coating. In addition, under large deformation, the vertical cracks also resulted in interfacial cracks that initiated from the cracking tips and propagated along the interface. According to the CPFEM, the cracking behaviors were mainly caused by the substantial stress concentration at the coating/substrate interface and at the grain boundaries in the Cr coating. The preferential crack initiation was related to the strain localization associated with grain orientation variation and strain mismatch.
Time to Listen: Children’s Voice in Geoscience Education Research
Authors: Neenan Emer Emily , Roche Joseph , Bell Laura
Published: May 2021

Arguably the greatest threat facing society is that posed by irreversible climate change. In tandem with mitigating the effects of climate change, we must now make decisions about issues such as renewable energy, sustainable and safe water supplies, management of renewable and non-renewable natural resources, and management of natural disasters. The current school-age generation will see the worst effects of climate change, including greater frequency and intensity of extreme weather events; shortages of water and other necessary resources; and dangers due to pollution and toxicity in human environments and the human food chain. The next generation is coming of age as difficult socio-political choices are being made at local and national levels to manage resources and mitigate environmental damage. It is therefore important to center the voices of children and young people in research aiming to address the social, political, and educational dimensions of geoscience topics, including climate change and related topics. This paper proposes the use of Children’s Research Advisory Groups (CRAGs) to meaningfully include children and young people as co-researchers in geoscience-related research.
Pathogen and Endophyte Assemblages Co-vary With Beech Bark Disease Progression, Tree Decline, and Regional Climate
Authors: Morrison Eric W. , Kasson Matt T. , Heath Jeremy J. , Garnas Jeff R.
Published: May 2021

Plant–pathogen interactions are often considered in a pairwise manner with minimal consideration of the impacts of the broader endophytic community on disease progression and/or outcomes for disease agents and hosts. Community interactions may be especially relevant in the context of disease complexes (i.e., interacting or functionally redundant causal agents) and decline diseases (where saprobes and weak pathogens synergize the effects of primary infections and hasten host mortality). Here we describe the bark endophyte communities associated with a widespread decline disease of American beech, beech bark disease (BBD), caused by an invasive scale insect (Cryptococcus fagisuga) and two fungal pathogens, Neonectria faginata and N. ditissima. We show that the two primary fungal disease agents co-occur more broadly than previously understood (35.5% of infected trees), including within the same 1-cm diameter phloem samples. The two species appear to have contrasting associations with climate and stages of tree decline, wherein N. faginata was associated with warmer and N. ditissima with cooler temperatures. Neonectria ditissima showed a positive association with tree crown dieback – no such association was observed for N. faginata. Further, we identify fungal endophytes that may modulate disease progression as entomopathogens, mycoparasites, saprotrophs, and/or additional pathogens, including Clonostachys rosea and Fusarium babinda. These fungi may alter the trajectory of disease via feedbacks with the primary disease agents or by altering symptom expression or rates of tree decline across the range of BBD.
Systematic Review on Local Ancestor Inference From a Mathematical and Algorithmic Perspective
Authors: Wu Jie , Liu Yangxiu , Zhao Yiqiang
Published: May 2021

Genotypic data provide deep insights into the population history and medical genetics. The local ancestry inference (LAI) (also termed local ancestry deconvolution) method uses the hidden Markov model (HMM) to solve the mathematical problem of ancestry reconstruction based on genomic data. HMM is combined with other statistical models and machine learning techniques for particular genetic tasks in a series of computer tools. In this article, we surveyed the mathematical structure, application characteristics, historical development, and benchmark analysis of the LAI method in detail, which will help researchers better understand and further develop LAI methods. Firstly, we extensively explore the mathematical structure of each model and its characteristic applications. Next, we use bibliometrics to show detailed model application fields and list articles to elaborate on the historical development. LAI publications had experienced a peak period during 2006–2016 and had kept on moving in the following years. The efficiency, accuracy, and stability of the existing models were evaluated by the benchmark. We find that phased data had higher accuracy in comparison with unphased data. We summarize these models with their distinct advantages and disadvantages. The Loter model uses dynamic programming to obtain a globally optimal solution with its parameter-free advantage. Aligned bases can be used directly in the Seqmix model if the genotype is hard to call. This research may help model developers to realize current challenges, develop more advanced models, and enable scholars to select appropriate models according to given populations and datasets.
Improving Genomic Prediction Using High-Dimensional Secondary Phenotypes
Authors: Arouisse Bader , Theeuwen Tom P. J. M. , van Eeuwijk Fred A. , Kruijer Willem
Published: May 2021

In the past decades, genomic prediction has had a large impact on plant breeding. Given the current advances of high-throughput phenotyping and sequencing technologies, it is increasingly common to observe a large number of traits, in addition to the target trait of interest. This raises the important question whether these additional or “secondary” traits can be used to improve genomic prediction for the target trait. With only a small number of secondary traits, this is known to be the case, given sufficiently high heritabilities and genetic correlations. Here we focus on the more challenging situation with a large number of secondary traits, which is increasingly common since the arrival of high-throughput phenotyping. In this case, secondary traits are usually incorporated through additional relatedness matrices. This approach is however infeasible when secondary traits are not measured on the test set, and cannot distinguish between genetic and non-genetic correlations. An alternative direction is to extend the classical selection indices using penalized regression. So far, penalized selection indices have not been applied in a genomic prediction setting, and require plot-level data in order to reliably estimate genetic correlations. Here we aim to overcome these limitations, using two novel approaches. Our first approach relies on a dimension reduction of the secondary traits, using either penalized regression or random forests (LS-BLUP/RF-BLUP). We then compute the bivariate GBLUP with the dimension reduction as secondary trait. For simulated data (with available plot-level data), we also use bivariate GBLUP with the penalized selection index as secondary trait (SI-BLUP). In our second approach (GM-BLUP), we follow existing multi-kernel methods but replace secondary traits by their genomic predictions, with the advantage that genomic prediction is also possible when secondary traits are only measured on the training set. For most of our simulated data, SI-BLUP was most accurate, often closely followed by RF-BLUP or LS-BLUP. In real datasets, involving metabolites in Arabidopsis and transcriptomics in maize, no method could substantially improve over univariate prediction when secondary traits were only available on the training set. LS-BLUP and RF-BLUP were most accurate when secondary traits were available also for the test set.
CMTM6-Deficient Monocytes in ANCA-Associated Vasculitis Fail to Present the Immune Checkpoint PD-L1
Authors: Zeisbrich Markus , Chevalier Nina , Sehnert Bettina , Rizzi Marta , Venhoff Nils , Thiel Jens , Voll Reinhard E.
Published: May 2021

Objectives

ANCA-associated vasculitides (AAV) affect small- and medium-sized blood vessels. In active disease, vessel wall infiltrates are mainly composed of monocytes and macrophages. Immune checkpoint molecules are crucial for the maintenance of self-tolerance and the prevention of autoimmune diseases. After checkpoint inhibitor therapy, the development of autoimmune vasculitis has been observed. However, defects of immune checkpoint molecules in AAV patients have not been identified yet.

Methods

Monocytes and monocyte-derived macrophages from AAV patients and healthy age-matched controls were tested for surface expression of immunoinhibitory checkpoint programmed cell death ligand-1 (PD-L1). Using in vitro co-culture approaches, the effect of monocyte PD-L1 expression on CD4+ T cell activation and proliferation was tested.

Results

Monocytes from AAV patients displayed lower PD-L1 expression and a defective PD-L1 presentation upon activation, an effect that was correlated with disease activity. Lower PD-L1 expression was due to increased lysosomal degradation of PD-L1 in AAV monocytes. We identified a reduced expression of CMTM6, a protein protecting PD-L1 from lysosomal breakdown, as the underlying molecular defect. PD-L1low AAV monocytes showed increased stimulatory capacity and induced T cell activation and proliferation. Inhibiting lysosomal function corrected this phenotype by increasing PD-L1, thus normalizing the pro-stimulatory behavior of AAV monocytes.

Conclusions

This study identifies a defect of the immunoinhibitory checkpoint PD-L1 in monocytes from patients with AAV. Low expression of CMTM6 results in enhanced lysosomal degradation of PD-L1, thus providing insufficient negative signaling to T cells. Correcting this defect by targeting lysosomal function may represent a novel strategy to treat AAV.
Return of the Salish Sea Harbor Porpoise, Phocoena phocoena: Knowledge Gaps, Current Research, and What We Need to Do to Protect Their Future
Authors: Elliser Cindy R. , Hall Anna
Published: May 2021

The harbor porpoise (Phocoena phocoena) is one of the most abundant coastal cetacean species in the Northern Hemisphere with differential levels of regional knowledge. Gaps are particularly evident for the Pacific subspeciesPhocoena phocoena vomerina. In the Salish Sea (a transboundary body of water spanning between Washington, United States and British Columbia (BC), Canada), there is a dearth of information on many aspects of the biology, ecology, behavior, sociality, and regionally specific threats. Here we present a case study of the Salish Sea harbor porpoise, combining historical and current research, from both BC and Washington, to provide a more holistic view of this species’ status, the knowledge continuum and gaps, risks from identified threats and what current research and collaborations are revealing about this enigmatic species. The Salish Sea harbor porpoise was abundant to the 1940s and 1950s, but by the 1990s their numbers were greatly reduced, and all but absent in some areas. By the early 2000s, numbers had resurged, and harbor porpoise are now once again found throughout much of the Salish Sea. Despite this, studies focused on Salish Sea harbor porpoises have been limited until recently. Current long-term research has been conducted from vessels and land in both Canada and the United States. Multi-faceted work using techniques including photo-identification (photo-ID), behavioral visual observations, acoustics, commercial fishery surveys, sighting reports, citizen science and other ecological data have provided insight into the seasonal variation in density and abundance, site fidelity, reproduction, by-catch rates, foraging and the identification of important habitats that are used intra- and inter-annually in this region. These may represent culturally and biologically significant habitats for Salish Sea harbor porpoise. Collaborations within and outside of the Salish Sea have revealed consistencies and dissimilarities between different communities or populations; indicating that some aspects are more uniform for the species, while others may be community or population specific. The importance of long-term broad and fine-scale research is highlighted, as well as recommendations to further close the knowledge gaps and reduce the known human threats within the Salish Sea.
A Mega-Nourishment (Sand Motor) Affects Landscape Diversity of Subtidal Benthic Fauna
Authors: Herman Peter M. J. , Moons J. J. Simeon , Wijsman Jeroen W. M. , Luijendijk Arjen P. , Ysebaert Tom
Published: May 2021

The Sand Motor is a very large (20 million m3) nourishment constructed along the coast in The Netherlands. The huge volume of sand is redistributed along the coast by natural forces stemming from tidal currents and waves. For environmental evaluation of this large construction, the benthic subtidal fauna has been sampled prior to the construction of the Sand Motor, and at 1, 2, 4, and 6 years after construction. Although some significant differences between years were detected, overall the total density, total biomass and average number of species per sample were surprisingly constant over this time period. However, large differences were found in the species accumulation curves over samples, and in the rank-biomass and rank-abundance plots. These were related to two important trends in the communities. First, the invasive mollusk Ensis leei, the biomass dominant in the years before construction of the Sand Motor, dwindled in importance in later years. Recruitment of the species failed, but it is unclear whether, and how, this is related to the construction of the Sand Motor. Second, the correlation structure between depth, grain size, bottom shear stress due to waves and currents, which is very tight along a linear coast, was disrupted by the Sand Motor. The community composition was shown to depend strongly on these physical factors. The nature of the dependencies did not change, but the range of different combinations of factors after construction of the Sand Motor was widely larger than before. Although samples had similar number of species per sample before and after construction, the average difference between samples after construction was much larger than before. The Sand Motor is a very large construction, leading to loss of a substantial area (order 100 ha) of submarine area, which recovers at a long time scale. Total disturbance of benthos by burial, expressed as area∗(time before full recovery) was shown to be similar for the Sand Motor and for other coastal nourishment schemes when expressed per unit volume of sediment applied. However, in contrast to beach and shoreface nourishments, the Sand Motor led to a habitat diversification in the coastal zone.
Humpback Whale (Megaptera novaeangliae) Song on a Subarctic Feeding Ground
Authors: Tyarks Saskia Cathrin , Aniceto Ana S. , Ahonen Heidi , Pedersen Geir , Lindstrøm Ulf
Published: May 2021

Male humpback whales (Megaptera novaeangliae) are known to produce long complex sequences of structured vocalizations called song. Singing behavior has traditionally been associated with low latitude breeding grounds but is increasingly reported outside these areas. This study provides the first report of humpback whale songs in the subarctic waters of Northern Norway using a long-term bottom-moored hydrophone. Data processed included the months January–June 2018 and December 2018–January 2019. Out of 189 days with recordings, humpback whale singing was heard on 79 days. Singing was first detected beginning of January 2018 with a peak in February and was heard until mid-April. No singing activity was found during the summer months and was heard again in December 2018, continuing over January 2019. A total of 131 song sessions, including 35 full sessions, were identified throughout the study period. The longest and shortest complete sessions lasted 815 and 13 min, respectively. The results confirm that singing can be heard over several months in winter and spring on a high latitude feeding ground. This provides additional evidence to the growing literature that singing is not an explicit behavior confined to low latitude breeding grounds. The peak of song occurrence in February appears to coincide with the reproductive cycle of humpback whales. Finally, this study indicates that song occurrence on a subarctic feeding ground likely aids the cultural transmission for the North Atlantic humpback whale population.
Designing Oxide Aerogels With Enhanced Sorptive and Degradative Activity for Acute Chemical Threats
Authors: Novak Travis G. , DeSario Paul A. , Long Jeffrey W. , Rolison Debra R.
Published: May 2021

Oxide aerogels are pore–solid networks notable for their low density, large pore volume, and high surface area. This three-dimensional arrangement of pore and solid provides critical properties: the high surface area required to maximize the number of active sites and a through-connected porosity that plumbs reactants to the active interior. In decontamination applications where reactivity beyond adsorption is desired to degrade deleterious molecules, oxide aerogels offer multiple avenues to add oxidative power to this unique arrangement of pore and solid. For protection against chemical warfare agents or toxic industrial chemicals, metal-oxide aerogels with their oxide/hydroxide surfaces afford stability under ambient conditions against competing sorbents such as water and oxygen. In this review, strategies to maximize sorptive capacity and degradation rate by modifying surface functionality, compositing with dissimilar oxides, or adding metallic nanoparticles and the subsequent impact on decontamination performance will be summarized and expected directions for future research will be discussed based on the observed trends.
Multi-Technique Investigation of a Biomimetic Insect Tarsal Adhesive Fluid
Authors: Fowler J. Elliott , Gorb Stanislav , Baio Joe E.
Published: May 2021

There is substantial motivation to develop novel adhesives which take advantage of the superior adhesive strength and adaptability of many natural animal adhesives; however, the tools typically used to study these mechanisms are incapable of determining the precise interactions of molecules at an adhesive interface. In this study, a surface specific, order sensitive vibrational spectroscopy called sum frequency generation (SFG) is, for the first time, combined with multiple bulk characterization techniques to examine a novel, simple biomimetic adhesive fluid inspired by tarsal fluid of insects. Insects perform complex adhesive demands, including sticking, climbing vertically and running upside-down with little difficulty. Thus, we hypothesize that both bulk and surface specific properties of the fluid contribute to the success of this wet adhesive mechanism. SFG spectra of biomimetic emulsion exhibited similar hydrocarbon organization on hydrophobic and hydrophilic substrates to natural beetle fluid previously studied with the same method. Bulk characterization techniques indicated that the emulsion had a shear-thinning profile with the ability to enhance traction forces during climbing and low surface tension ideal for surface wetting on the majority of natural surfaces. Multi-technique comparisons between emulsion and pure squalane revealed that a hydrocarbon only based fluid could not replicate the traction promoting properties of the emulsion. We conclude that the insect tarsal fluid adhesive mechanism relies upon contributions from both surface-specific properties optimizing traction force and bulk properties promoting rapid surface wetting and maintaining pull-off force for fast detachment.
Separate and Combined Effects of Geometrical and Mechanical Properties Changes Due to Aging on the Femoral Strength in Men and Women
Authors: Sahandifar Pooya , Kleiven Svein
Published: May 2021

Aging, from 40 to +80 years old, causes geometrical and mechanical properties changes in the proximal femur. The subperiosteal width expands faster in men compared to women during aging, while the cortical thickness varies unequally in each sector and differently between men and women. Another change which occurs during aging is bone mechanical properties such as stiffness and ultimate strains. Numerical analysis allows us to study the potential effects of each of the age-dependent changes on the fracture forces separately and combined. We investigated the effects of the geometrical and bone mechanical properties changes due to aging on the femoral strength during a common falling scenario using a transverse isotropic continuum damage model. First, the femur model was adapted from a previously developed human body model named THUMS v4.02. Then, three sets of models were developed to address each of the changes separately and combined for both sexes. We found that the fracture forces in women are on average 1500 N less than in men of the same age. The age-dependent geometrical changes increased the fracture forces in men (25 N/decade), whereas it reduced the fracture forces by 116 N/decade in women. The mechanical properties changes reduced the fracture forces in men more than in women (354.5 N/ decade vs. 225.4 N/decade). When accounting for both geometrical and mechanical properties changes due to aging, the fracture forces decreased by 10.7% of the baseline in women per decade compared to 7.2% per decade in men.
Pre-operative/Neoadjuvant Therapy and Vascular Debranching Followed by Resection for Locally Advanced Pancreatic Cancer (PREVADER): Clinical Feasibility Trial
Authors: Ronellenfitsch Ulrich , Michalski Christoph W. , Michl Patrick , Krug Sebastian , Ukkat Joerg , Kleeff Joerg
Published: May 2021

Introduction: Pancreatic cancer continues to have a poor outcome. Many patients are diagnosed with advanced disease, and in a considerable proportion, abutment or invasion of visceral arteries is present. Moreover, some patients have anatomical variations or stenosis of major visceral arteries requiring arterial reconstruction upon pancreatic cancer resection to avoid organ ischemia. Simultaneous arterial reconstruction during resection is associated with relevant morbidity and mortality. This trial evaluates the approach of visceral debranching, that is, arterial reconstruction, prior to neoadjuvant chemotherapy and tumor resection in patients with locally advanced, unresectable pancreatic cancer.

Methods and Analysis: The trial includes patients with locally advanced, non-metastatic pancreatic cancer with arterial abutment or invasion (deemed primarily unresectable), variations in vascular anatomy, or stenosis of visceral arteries. The participants undergo visceral debranching, followed by current standard neoadjuvant chemotherapy (mFOLFIRINOX, gemcitabine–nab-paclitaxel, or other) and potential subsequent tumor resection. The primary outcome is feasibility, measured as the proportion of patients who start neoadjuvant therapy within 6 weeks of visceral debranching. The trial has an exact single-stage design. The proportion below which the treatment is considered ineffective is set at 0.7 (H0). The proportion above which the treatment warrants further exploration in a phase III trial is set at 0.9 (H1). With a power (1-beta) of 0.8 and a type 1 mistake (alpha) of 0.05, the required sample size is 28 patients. Feasibility of the approach will be assumed if 24 of the enrolled 28 patients proceed to neoadjuvant chemotherapy within 6 weeks from visceral debranching.

Discussion: This trial evaluates a new treatment sequence, that is, visceral debranching followed by chemotherapy and resection, for pancreatic cancer with invasion or abutment of visceral arteries. The primary objective of the trial is to evaluate feasibility. Trial results will allow for estimating treatment effects and calculating the sample size of a randomized controlled trial, in which the approach will be tested if the feasibility endpoint is met.

Clinical Trial Registration:clinicaltrials.gov, identifier: NCT04136769.
The Relationship Between Fragility Fractures and Pain Experience: A Systematic Review
Authors: Chen Pei-En , Chien Ching-Wen , Tung Tao-Hsin
Published: May 2021

Purpose: This systematic review is conducted to explore the relationship between fragility fractures and pain experience.

Methods: We searched for relevant studies on Pubmed, Embase, Web of Science, and the Cochrane library without restrictions on language from inception until February 4th, 2021. The risk of bias and methodological quality was evaluated using the Newcastle-Ottawa Scale and ROBINS-I tool.

Results: Twenty-one studies were included in this systematic review. The so-called study reported participants with continuous post-fracture pain. The included studies showed that post- fractured pain can decrease with time, however, the continual pain can last at least 1 year even longer, and some participants would need to self-manage pain. Moreover, the limited range of motion was considered as a factor that might distress the normal development of daily activities.

Conclusions: The current evidence could not fully support that pain continues to influence patients' lives after a fragility fracture. However, it still showed the pain might come with fracture. The findings also could be useful to help health care providers better recognize and manage this clinical consequence of fractures. Nonetheless, future large-scale longitudinal studies will be required to evaluate the long-term effects of pain in fragility fractures.
Noninvasive Ventilation in Patients With COVID-19-Related Acute Hypoxemic Respiratory Failure: A Retrospective Cohort Study
Authors: Fu Yingyun , Guan Lili , Wu Weibo , Yuan Jing , Zha Shanshan , Wen Junmin , Lin Zhenghao , Qiu Chen , Chen Rongchang , Liu Lei
Published: May 2021

Introduction: Noninvasive ventilation (NIV) has been used to alleviate hypoxemia and dyspnea, but there is no consensus on the application of NIV in patients with coronavirus disease 2019 (COVID-19). Some staff use NIV as the rescue therapy which might lead to the adverse outcomes. This study was to identify early factors associated with intubation to help the medical staff select appropriate patients for receiving NIV treatment.

Methods: Patients with laboratory-confirmed COVID-19 who were treated with NIV in emergency department or ICU of the Third People's Hospital (the only designated hospital for treating COVID-19 in Shenzhen) between January 1 and August 31, 2020, were retrospectively analyzed.

Results: Thirty-nine patients with COVID-19 treated with NIV were included; of them, 16 (41%) received endotracheal intubation and 3 (8%) died. Significant differences were observed between intubated and non-intubated patients in PaO2/FiO2 before NIV initiation, hospitalization duration, NIV as the rescue therapy, and PaO2/FiO2 of ≤200 mmHg after 1–2 h of NIV initiation. Notably, 1–2 h after NIV initiation, a PaO2/FiO2 of ≤200 mmHg (odds ratio [OR], 9.35; 95% confidence interval [CI], 1.84–47.62; P = 0.007) and NIV as the rescue therapy (OR, 5.43; 95% CI, 1.09–27.12; P = 0.039) were the risk factors for intubation.

Conclusions: In patients with COVID-19-related acute hypoxemic respiratory failure receiving NIV, close attention should be paid to PaO2/FiO2 after 1–2 h of NIV initiation. Also, using NIV as rescue therapy should draw our awareness that it might delay escalation of respiratory support and lead to adverse outcomes.
Broad-Spectrum Photo-Antimicrobial Polymers Based on Cationic Polystyrene and Rose Bengal
Authors: Gavara Raquel , de Llanos Rosa , Pérez-Laguna Vanesa , Arnau del Valle Carla , Miravet Juan F. , Rezusta Antonio , Galindo Francisco
Published: May 2021

New strategies to fight bacteria and fungi are necessary in view of the problem of iatrogenic and nosocomial infections combined with the growing threat of increased antimicrobial resistance. Recently, our group has prepared and described two new readily available materials based on the combination of Rose Bengal (singlet oxygen photosensitizer) and commercially available cationic polystyrene (macroporous resin Amberlite® IRA 900 or gel-type resin IRA 400). These materials showed high efficacy in the antimicrobial photodynamic inactivation (aPDI) of Pseudomonas aeruginosa. Here, we present the photobactericidal effect of these polymers against an extended group of pathogens like Escherichia coli, Enterococcus faecalis, Staphylococcus aureus, and the opportunistic yeast Candida albicans using green light. The most interesting finding is that the studied materials are able to reduce the population of both Gram-positive and Gram-negative bacteria with good activity, although, for C. albicans, in a moderate manner. In view of the results achieved and especially considering the inexpensiveness of these two types of photoactive polymers, we believe that they could be used as the starting point for the development of coatings for self-disinfecting surfaces.
Multi-Omics Integrative Analysis Uncovers Molecular Subtypes and mRNAs as Therapeutic Targets for Liver Cancer
Authors: Shen Yi , Xiong Wei , Gu Qi , Zhang Qin , Yue Jia , Liu Changsong , Wang Duan
Published: May 2021

Objective: This study aimed to systematically analyze molecular subtypes and therapeutic targets of liver cancer using integrated multi-omics analysis.

Methods: DNA copy number variations (CNVs), simple nucleotide variations (SNVs), methylation, transcriptome as well as corresponding clinical information for liver carcinoma were retrieved from The Cancer Genome Atlas (TCGA). Multi-omics analysis was performed to identify molecular subtypes of liver cancer via integrating CNV, methylation as well as transcriptome data. Immune scores of two molecular subtypes were estimated using tumor immune estimation resource (TIMER) tool. Key mRNAs were screened and prognosis analysis was performed, which were validated using RT-qPCR. Furthermore, mutation spectra were analyzed in the different subtypes.

Results: Two molecular subtypes (iC1 and iC2) were conducted for liver cancer. Compared with the iC2 subtype, the iC1 subtype had a worse prognosis and a higher immune score. Two key mRNAs (ANXA2 and CHAF1B) were significantly related to liver cancer patients' prognosis, which were both up-regulated in liver cancer tissues in comparison to normal tissues. Seventeen genes with p < 0.01 differed significantly for SNV loci between iC1 and iC2 subtypes.

Conclusion: Our integrated multi-omics analyses provided new insights into the molecular subtypes of liver cancer, helping to identify novel mRNAs as therapeutic targets and uncover the mechanisms of liver cancer.
Machine Learning Classification of Inflammatory Bowel Disease in Children Based on a Large Real-World Pediatric Cohort CEDATA-GPGE® Registry
Authors: Schneider Nicolas , Sohrabi Keywan , Schneider Henning , Zimmer Klaus-Peter , Fischer Patrick , de Laffolie Jan ,   CEDATA-GPGE Study Group
Published: May 2021

Introduction: The rising incidence of pediatric inflammatory bowel diseases (PIBD) facilitates the need for new methods of improving diagnosis latency, quality of care and documentation. Machine learning models have shown to be applicable to classifying PIBD when using histological data or extensive serology. This study aims to evaluate the performance of algorithms based on promptly available data more suited to clinical applications.

Methods: Data of inflammatory locations of the bowels from initial and follow-up visitations is extracted from the CEDATA-GPGE registry and two follow-up sets are split off containing only input from 2017 and 2018. Pre-processing excludes patients in remission and encodes the categorical data numerically. For classification of PIBD diagnosis, a support vector machine (SVM), a random forest algorithm (RF), extreme gradient boosting (XGBoost), a dense neural network (DNN) and a convolutional neural network (CNN) are employed. As best performer, a convolutional neural network is further improved using grid optimization.

Results: The achieved accuracy of the optimized neural network reaches up to 90.57% on data inserted into the registry in 2018. Less performant methods reach 88.78% for the DNN down to 83.94% for the XGBoost. The accuracy of prediction for the 2018 follow-up dataset is higher than those for older datasets. Neural networks yield a higher standard deviation with 3.45 for the CNN compared to 0.83–0.86 of the support vector machine and ensemble methods.

Discussion: The displayed accuracy of the convolutional neural network proofs the viability of machine learning classification in PIBD diagnostics using only timely available data.
Redox Polymers for Tissue Engineering
Authors: Molino Binbin Z. , Fukuda Junji , Molino Paul J. , Wallace Gordon G.
Published: May 2021

This review will focus on the targeted design, synthesis and application of redox polymers for use in regenerative medicine and tissue engineering. We define redox polymers to encompass a variety of polymeric materials, from the multifunctional conjugated conducting polymers to graphene and its derivatives, and have been adopted for use in the engineering of several types of stimulus responsive tissues. We will review the fundamental properties of organic conducting polymers (OCPs) and graphene, and how their properties are being tailored to enhance material - biological interfacing. We will highlight the recent development of high-resolution 3D fabrication processes suitable for biomaterials, and how the fabrication of intricate scaffolds at biologically relevant scales is providing exciting opportunities for the application of redox polymers for both in-vitro and in-vivo tissue engineering. We will discuss the application of OCPs in the controlled delivery of bioactive compounds, and the electrical and mechanical stimulation of cells to drive behaviour and processes towards the generation of specific functional tissue. We will highlight the relatively recent advances in the use of graphene and the exploitation of its physicochemical and electrical properties in tissue engineering. Finally, we will look forward at the future of organic conductors in tissue engineering applications, and where the combination of materials development and fabrication processes will next unite to provide future breakthroughs.
Increased Antimicrobial and Multidrug Resistance Downstream of Wastewater Treatment Plants in an Urban Watershed
Authors: Mukherjee Maitreyee , Laird Edward , Gentry Terry J. , Brooks John P. , Karthikeyan Raghupathy
Published: May 2021

Development and spread of antimicrobial resistance (AMR) and multidrug resistance (MDR) through propagation of antibiotic resistance genes (ARG) in various environments is a global emerging public health concern. The role of wastewater treatment plants (WWTPs) as hot spots for the dissemination of AMR and MDR has been widely pointed out by the scientific community. In this study, we collected surface water samples from sites upstream and downstream of two WWTP discharge points in an urban watershed in the Bryan-College Station (BCS), Texas area, over a period of nine months.E. coliisolates were tested for resistance to ampicillin, tetracycline, sulfamethoxazole, ciprofloxacin, cephalothin, cefoperazone, gentamycin, and imipenem using the Kirby-Bauer disc diffusion method. Antimicrobial resistant heterotrophic bacteria were cultured on R2A media amended with ampicillin, ciprofloxacin, tetracycline, and sulfamethoxazole for analyzing heterotrophic bacteria capable of growth on antibiotic-containing media. In addition, quantitative real-time polymerase chain reaction (qPCR) method was used to measure eight ARG –tetA, tetW, aacA, ampC, mecA, ermA, blaTEM, andintI1in the surface water collected at each time point. Significant associations (p< 0.05) were observed between the locations of sampling sites relative to WWTP discharge points and the rate ofE. coliisolate resistance to tetracycline, ampicillin, cefoperazone, ciprofloxacin, and sulfamethoxazole together with an increased rate of isolate MDR. The abundance of antibiotic-resistant heterotrophs was significantly greater (p< 0.05) downstream of WWTPs compared to upstream locations for all tested antibiotics. Consistent with the results from the culture-based methods, the concentrations of all ARG were substantially higher in the downstream sites compared to the upstream sites, particularly in the site immediately downstream of the WWTP effluent discharges (exceptmecA). In addition, the Class I integron (intI1) genes were detected in high amounts at all sites and all sampling points, and were about ∼20 times higher in the downstream sites (2.5 × 107copies/100 mL surface water) compared to the upstream sites (1.2 × 106copies/100 mL surface water). Results suggest that the treated WWTP effluent discharges into surface waters can potentially contribute to the occurrence and prevalence of AMR in urban watersheds. In addition to detecting increased ARG in the downstream sites by qPCR, findings from this study also report an increase in viable AMR (HPC) and MDR (E. coli) in these sites. This data will benefit establishment of improved environmental regulations and practices to help manage AMR/MDR and ARG discharges into the environment, and to develop mitigation strategies and effective treatment of wastewater.
Identification and Validation of Immune-Related Gene Signature for Predicting Lymph Node Metastasis and Prognosis in Lung Adenocarcinoma
Authors: Jia Ran , Sui Zhilin , Zhang Hongdian , Yu Zhentao
Published: May 2021

Lung cancer is a serious malignancy, and lung adenocarcinoma (LUAD) is the most common pathological subtype. Immune-related factors play an important role in lymph node metastasis. In this study, we obtained gene expression profile data for LUAD and normal tissues from the TCGA database and analyzed their immune-related genes (IRGs), and observed that 459 IRGs were differentially expressed. Further analysis of the correlation between differentially expressed IRGs and lymph node metastasis revealed 18 lymph node metastasis-associated IRGs. In addition, we analyzed the mutations status, function and pathway enrichment of these IRGs, and regulatory networks established through TF genes. We then identified eight IRGs (IKBKB, LTBR, MIF, PPARD, PPIA, PSME3, S100A6, SEMA4B) as the best predictors by LASSO Logistic analysis and used these IRGs to construct a model to predict lymph node metastasis in patients with LUAD (AUC 0.75; 95% CI: 0.7064–0.7978), and survival analysis showed that the risk score independently affected patient survival. We validated the predictive effect of risk scores on lymph node metastasis and survival using the GEO database as a validation cohort and the results showed good agreement. In addition, the risk score was highly correlated with infiltration of immune cells (mast cells activated, macrophages M2, macrophages M0 and B cells naïve), immune and stromal scores, and immune checkpoint genes (LTBR, CD40LG, EDA2R, and TNFRSF19). We identified key IRGs associated with lymph node metastasis in LUAD and constructed a reliable risk score model, which may provide valuable biomarkers for LUAD patients and further reveal the mechanism of its occurrence.
A Complex-Valued Oscillatory Neural Network for Storage and Retrieval of Multidimensional Aperiodic Signals
Authors: Biswas Dipayan , Pallikkulath Sooryakiran , Chakravarthy V. Srinivasa
Published: May 2021

Recurrent neural networks with associative memory properties are typically based on fixed-point dynamics, which is fundamentally distinct from the oscillatory dynamics of the brain. There have been proposals for oscillatory associative memories, but here too, in the majority of cases, only binary patterns are stored as oscillatory states in the network. Oscillatory neural network models typically operate at a single/common frequency. At multiple frequencies, even a pair of oscillators with real coupling exhibits rich dynamics of Arnold tongues, not easily harnessed to achieve reliable memory storage and retrieval. Since real brain dynamics comprises of a wide range of spectral components, there is a need for oscillatory neural network models that operate at multiple frequencies. We propose an oscillatory neural network that can model multiple time series simultaneously by performing a Fourier-like decomposition of the signals. We show that these enhanced properties of a network of Hopf oscillators become possible by operating in the complex-variable domain. In this model, the single neural oscillator is modeled as a Hopf oscillator, with adaptive frequency and dynamics described over the complex domain. We propose a novel form of coupling, dubbed “power coupling,” between complex Hopf oscillators. With power coupling, expressed naturally only in the complex-variable domain, it is possible to achieve stable (normalized) phase relationships in a network of multifrequency oscillators. Network connections are trained either by Hebb-like learning or by delta rule, adapted to the complex domain. The network is capable of modeling N-channel electroencephalogram time series with high accuracy and shows the potential as an effective model of large-scale brain dynamics.
In-Bed Sensorimotor Rehabilitation in Early and Late Subacute Stroke Using a Wearable Elbow Robot: A Pilot Study
Authors: Huang Mei Zhen , Yoon Yong-Soon , Yang Jisu , Yang Chung-Yong , Zhang Li-Qun
Published: May 2021

Objects: To evaluate the feasibility and effectiveness of in-bed wearable elbow robot training for motor recovery in patients with early and late subacute stroke.

Methods: Eleven in-patient stroke survivors (male/female: 7/4, age: 50.7 ± 10.6 years, post-stroke duration: 2.6 ± 1.9 months) received 15 sessions of training over about 4 weeks of hospital stay. During each hourly training, participants received passive stretching and active movement training with motivating games using a wearable elbow rehabilitation robot. Isometric maximum muscle strength (MVC) of elbow flexors and extensors was evaluated using the robot at the beginning and end of each training session. Clinical measures including Fugl-Meyer Assessment of upper extremity (FMA-UE), Motricity Index (MI) for upper extremities, Modified Ashworth Scale (MAS) were measured at baseline, after the 4-week training program, and at a 1-month follow-up. The muscle strength recovery curve over the training period was characterized as a logarithmic learning curve with three parameters (i.e., initial muscle strength, rate of improvement, and number of the training session).

Results: At the baseline, participants had moderate to severe upper limb motor impairment {FMA-UE [median (interquartile range)]: 28 (18–45)} and mild spasticity in elbow flexors {MAS [median (interquartile range)]: 0 (0–1)}. After about 4 weeks of training, significant improvements were observed in FMA-UE (p = 0.003) and MI (p = 0.005), and the improvements were sustained at the follow-up. The elbow flexors MVC significantly increased by 1.93 Nm (95% CI: 0.93 to 2.93 Nm, p = 0.017) and the elbow extensor MVC increased by 0.68 Nm (95% CI: 0.05 to 1.98 Nm, p = 0.036). Muscle strength recovery curve showed that patients with severe upper limb motor impairment had a greater improvement rate in elbow flexor strength than those with moderate motor impairment.

Conclusion: In-bed wearable elbow robotic rehabilitation is feasible and effective in improving biomechanical and clinical outcomes for early and late subacute stroke in-patients. Results from the pilot study suggested that patients with severe upper limb motor impairment may benefit more from the robot training compared to those with moderate impairment.
Deep Cross-User Models Reduce the Training Burden in Myoelectric Control
Authors: Campbell Evan , Phinyomark Angkoon , Scheme Erik
Published: May 2021

The effort, focus, and time to collect data and train EMG pattern recognition systems is one of the largest barriers to their widespread adoption in commercial applications. In addition to multiple repetitions of motions, including exemplars of confounding factors during the training protocol has been shown to be critical for robust machine learning models. This added training burden is prohibitive for most regular use cases, so cross-user models have been proposed that could leverage inter-repetition variability supplied by other users. Existing cross-user models have not yet achieved performance levels sufficient for commercialization and require users to closely adhere to a training protocol that is impractical without expert guidance. In this work, we extend a previously reported adaptive domain adversarial neural network (ADANN) to a cross-subject framework that requires very little training data from the end-user. We compare its performance to single-repetition within-user training and the previous state-of-the-art cross-subject technique, canonical correlation analysis (CCA). ADANN significantly outperformed CCA for both intact-limb (86.8–96.2%) and amputee (64.1–84.2%) populations. Moreover, the ADANN adaptation computation time was substantially lower than the time otherwise devoted to conducting a full within-subject training protocol. This study shows that cross-user models, enabled by deep-learned adaptations, may be a viable option for improved generalized pattern recognition-based myoelectric control.