bluuebunny/crossref_metadata_2025 huggingface dataset:
Long Term Effect of COVID-19 on the Brain: Review
Authors: Devkumar Shreerag , Jha Rakesh Kumar , Chandi Dhruba Hari
Published: August 2021

Corona viruses (CoVs) are well-covered RNA viruses that cause enteric and respiratory infections in humans and animals. Many human CoVs have recently gained global interest because of their lethal power and high contagious power. SARS-CoV-2, or COVID-19, is a pathogenic coV that first appeared in Wuhan, China.

Corona virus Disease 2019 (COVID-19) created by SARS-CoV-2, has been declared as pandemic by the World Health Organization since March 11, 2020. The epidemic started in Wuhan and spread rapidly around the world. Corona virus is facing a major epidemic: Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). SARS-CoV-2 is a virus closely related to SARS.

Corona virus (COVID-19) is caused by SARS-CoV-2 VIRUS, a complex clinical disorder characterized by severe pneumonia and acute respiratory stress syndrome. Serious and neurological disorders, such as encephalitis, coma, fever, epilepsy, and Guillain-Barré syndrome, are more common in cases of COVID-19. In addition, chronic autoimmune and neurodegenerative diseases may occur in SARS-CoV-2 immunopathology and colonization of intestinal and central nervous system, as well as systemic inflammatory response during COVID-19. Parkinson's disease is a common neurodegenerative condition that causes the development of motor and non-motor symptoms.
Emotional Intelligence and Stress Tolerance of Diabetic Physical Exercising and Diabetic Nonphysical Exercising Peoples on Critics
Authors: Vinu W.
Published: August 2021

Aim: This study is an attempt to analyze and interpret diabetic nonphysical exercising and diabetic physical exercising people on the psychological aspect of emotional intelligence.

Place and Duration of Study: Chidambaram, Cuddalore district, Tamilnadu, India. 1 year.

Methodology: For this study a normative survive method was used to collect data from diabetic physical exercising and diabetic nonphysical exercising people from Chidambaram, Cuddalore district, Tamilnadu, India. This investigate is an attempt to analyse and interpret diabetic physical exercising and diabetic nonphysical exercising people on the psychological aspect of EI. The problem of this study is a comparison of on EI of diabetic physical exercising and diabetic nonphysical exercising peoples. The sample in the present study was limited to 60 nondiabetic and 60 diabetic people.

Results: The result shows that the ‘r’ value obtained from the variable emotional stability and self-development on the sample of 60 on stress tolerance of diabetic physical exercising group was identified as 0.34 and 0.35 which was significant at 0.01 this shows that here remained a positive relationship between stress tolerance with emotional stability, Stress tolerance with self-development. When emotional stability increases stress tolerance increases when self-development develops stress tolerance increases. The diabetic non-physical exercising and diabetic physical exercising group significantly differ in their stress tolerance, comparatively, the mean value of 73.81 for diabetic physical exercising people with the mean value of 71.79 diabetic nonphysical exercising people is less. Hence it is proved that diabetic physical exercising people have more stress tolerance than diabetic nonphysical exercising people. This indicates that comparatively diabetic physical exercising people can withstand when deprived and tolerate critics of others because diabetic physical exercising people are more stress-tolerant when compared to diabetic nonphysical exercising people. The result of the diabetic physical exercising group's 'r’ value obtained from the variable EI on the sample of 60 on stress tolerant was identified as 0.25 which was significant at 0.05.

Conclusion: There was a positive relationship between stress tolerance with EI which specifies that when EI increases stress tolerance increases for diabetic physical exercising person’s vice versa.
A Brief Study on Retroperitoneal Paraganglioma
Authors: Pandey Milind , Vagha Sunita , Mahajan Gaurav , Manchanda Anchal
Published: August 2021

Paragangliomas are tumors of the autonomic nervous system, located extra-adrenally, presenting inside the base of the head, chest and abdomen. They can appear as a primary retroperitoneal neoplasm when viewed inside the abdominal cavity and might resemble as vascular malformations or any other conditions same as retroperitoneal organs particularly such as pancreas, kidney. These are relatively uncommon endocrine tumors that originate from specific tissue of the paraganglion. They synthesise, store and secrete catecholamines, which can contribute to headache, sweating, palpitation and hypertension. These may be mistaken for GISTs with no histological diagnosis and symptoms of catecholamine overload (non functional). We are reporting a case of 42 yrs male with clinical features of slow backache radiating to both lower legs and with the presence of tingling sensation. Corresponding contrast enhanced CT scan shows a para – aortic mass.
A Stability Indicating Reverse Phase High Performance Liquid Chromatography Method for Simultaneous Estimation of Hydroquinone, Hydrocortisone and Tretenoin in Cream Formulation
Authors: Shilu Raksha , Kapupara Pankaj , Patel Meghna
Published: August 2021

Objective: A simple, sensitive, rapid, precise and accurate stability indicating RP-HPLC method has been developed for simultaneous estimation of Hydroquinone, Hydrocortisone and Tretenoin from their Cream Formulation.

Method: The Chromatographic separation was achieved on a reversed-phase Inertsil C18 (4.6 mm I.D. × 250 mm, 5 µm) column using a mobile phase consisting of Buffer (pH 4.0) 0.05M potassium dihydrogen ortho phosphate-Methanol in the ratio of 80:20% V/V at a flow rate of 1ml/min and UV detection at λmax 265 nm. The method showed linearity with correlation coefficient of Hydroquinone, Hydrocortisone and Tretenoin was 0.998, 0.998 and 0.996 over the range of 40-120 µg/ml, 20-60 µg/ml and 0.25-0.75 µg/ml respectively.

Result: The retention time was 3 min, 5 min and 6 min for Hydroquinone, Hydrocortisone and Tretenoin respectively. The mean recoveries were found to be in the range of 97.00 –101.00 % for all the components. The method was validated as per the ICH guidelines. The method was validated as per the ICH guidelines.

Conclusion: The method was stable and specific and when sample was stressed under different conditions like Acid, Base, Oxidative, Thermal and Photolytic, no interference of degradants were observed.
Synthesis of Indofulvin Pseudo‐Natural Products Yields a New Autophagy Inhibitor Chemotype
Authors: Burhop Annina , Bag Sukdev , Grigalunas Michael , Woitalla Sophie , Bodenbinder Pia , Brieger Lukas , Strohmann Carsten , Pahl Axel , Sievers Sonja , Waldmann Herbert
Published: August 2021

Chemical and biological limitations in bioactive compound design based on natural product (NP) structure can be overcome by the combination of NP‐derived fragments in unprecedented arrangements to afford “pseudo‐natural products” (pseudo‐NPs). A new pseudo‐NP design principle is described, i.e., the combination of NP‐fragments by transformations that are not part of current biosynthesis pathways. A collection of indofulvin pseudo‐NPs is obtained from 2‐hydroxyethyl‐indoles and ketones derived from the fragment‐sized NP griseofulvin by means of an iso‐oxa‐Pictet‐Spengler reaction. Cheminformatic analysis indicates that the indofulvins reside in an area of chemical space sparsely covered by NPs, drugs, and drug‐like compounds and they may combine favorable properties of these compound classes. Biological evaluation of the compound collection in different cell‐based assays and the unbiased high content cell painting assay reveal that the indofulvins define a new autophagy inhibitor chemotype that targets mitochondrial respiration.
Precursor comparisons for the upregulation of nicotinamide adenine dinucleotide. Novel approaches for better aging
Authors: Palmer Raymond D. , Elnashar Magdy Mahmoud , Vaccarezza Mauro
Published: August 2021

Nicotinamide adenine dinucleotide (NAD) is a coenzyme found in every human cell and regulates a number of systems across multiple cellular compartments and tissue types via an endogenous and exogenous influence. NAD levels are demonstrated to decline with age and therefore measures to counteract the waning of NAD have been devised. A number of NAD precursor candidates such as nicotinamide riboside (NR), nicotinamide mononucleotide (NMN), the reduced form of nicotinamide mononucleotide (NMNH), nicotinic acid (NA) nicotinamide (NAM), and dihydronicotinamide riboside (DNR) increase NAD levels in vitro and in vivo. This discussion will focus on the precursors NR, NMN, NMNH, and DNR in the upregulation of NAD. There are many publications on NAD precursors as it has become popular for human consumption in recent years due to its vital importance to the general consumer. However, there is no consensus between researchers and this was the aim of this review, to determine and discuss their areas of agreement versus disagreement, to highlight the gaps in research, and to give recommendations for future work. Bioavailability and potency of NR, NMNH, NMN, and DNR is also examined on the light of the most recent literature.
New functionalized 6‐thienylpyrimidine‐5‐carbonitriles as antiproliferative agents against human breast cancer cells
Authors: AboulWafa Omaima M. , Daabees Hoda M. G. , Hammad Ali , Badawi Waleed A.
Published: August 2021

6‐Thienylpyrimidine‐5‐carbonitrile derivatives were synthesized and screened for their in vitro antiproliferative activities against two human breast cancer cell lines in comparison to 5‐fluorouracil as a reference. Compounds 2, 3a–c, and 6b evolved as the most active congeners against both cell lines, while others showed selectivity for only one cell line. Compound 2 exerted its effect through inhibition of the epidermal growth factor receptor (EGFR), while 6b showed less aromatase inhibitory activity than letrozole. The rest of the tested compounds did not show significant inhibition, and it can be assumed that they exert their antiproliferative activity through different target mechanisms. In addition, caspase‐9 protein activation assays, cell cycle analysis using flow cytometry, and annexin V‐fluorescein isothiocyanate–propidium iodide (FITC/PI) dual staining assays were performed for the most active compounds. All the tested compounds were found to be potent pyrimidine derivatives able to initiate apoptosis in MCF‐7 and MDA‐MB‐231 cells.
Evaluation of Immune Response and Disease Status in Systemic Lupus Erythematosus Patients Following SARS–CoV‐2 Vaccination
Authors: Izmirly Peter M. , Kim Mimi Y. , Samanovic Marie , Fernandez‐Ruiz Ruth , Ohana Sharon , Deonaraine Kristina K. , Engel Alexis J. , Masson Mala , Xie Xianhong , Cornelius Amber R. , Herati Ramin S. , Haberman Rebecca H. , Scher Jose U. , Guttmann Allison , Blank Rebecca B. , Plotz Benjamin , Haj‐Ali Mayce , Banbury Brittany , Stream Sara , Hasan Ghadeer , Ho Gary , Rackoff Paula , Blazer Ashira D. , Tseng Chung‐E , Belmont H. Michael , Saxena Amit , Mulligan Mark J. , Clancy Robert M. , Buyon Jill P.
Published: August 2021

Objective

To evaluate seroreactivity and disease flares after COVID‐19 vaccination in a multiethnic/multiracial cohort of patients with systemic lupus erythematosus (SLE).

Methods

Ninety SLE patients and 20 healthy controls receiving a complete COVID‐19 vaccine regimen were included. IgG seroreactivity to the SARS–CoV‐2 spike receptor‐binding domain (RBD) and SARS–CoV‐2 microneutralization were used to evaluate B cell responses; interferon‐γ (IFNγ) production was measured by enzyme‐linked immunospot (ELISpot) assay in order to assess T cell responses. Disease activity was measured by the hybrid SLE Disease Activity Index (SLEDAI), and flares were identified according to the Safety of Estrogens in Lupus Erythematosus National Assessment–SLEDAI flare index.

Results

Overall, fully vaccinated SLE patients produced significantly lower IgG antibodies against SARS–CoV‐2 spike RBD compared to fully vaccinated controls. Twenty‐six SLE patients (28.8%) generated an IgG response below that of the lowest control (<100 units/ml). In logistic regression analyses, the use of any immunosuppressant or prednisone and a normal anti–double‐stranded DNA antibody level prior to vaccination were associated with decreased vaccine responses. IgG seroreactivity to the SARS–CoV‐2 spike RBD strongly correlated with the SARS–CoV‐2 microneutralization titers and correlated with antigen‐specific IFNγ production determined by ELISpot. In a subset of patients with poor antibody responses, IFNγ production was similarly diminished. Pre‐ and postvaccination SLEDAI scores were similar in both groups. Postvaccination flares occurred in 11.4% of patients; 1.3% of these were severe.

Conclusion

In a multiethnic/multiracial study of SLE patients, 29% had a low response to the COVID‐19 vaccine which was associated with receiving immunosuppressive therapy. Reassuringly, severe disease flares were rare. While minimal protective levels remain unknown, these data suggest that protocol development is needed to assess the efficacy of booster vaccination.
Activated Peripheral Blood B Cells in Rheumatoid Arthritis and Their Relationship to Anti–Tumor Necrosis Factor Treatment and Response: A Randomized Clinical Trial of the Effects of Anti–Tumor Necrosis Factor on B Cells
Authors: Meednu Nida , Barnard Jennifer , Callahan Kelly , Coca Andreea , Marston Bethany , Thiele Ralf , Tabechian Darren , Bolster Marcy , Curtis Jeffrey , Mackay Meggan , Graf Jonathan , Keating Richard , Smith Edwin , Boyle Karen , Keyes‐Elstein Lynette , Welch Beverly , Goldmuntz Ellen , Anolik Jennifer H.
Published: August 2021

Objective

B cells can become activated in germinal center (GC) reactions in secondary lymphoid tissue and in ectopic GCs in rheumatoid arthritis (RA) synovium that may be tumor necrosis factor (TNF) and lymphotoxin (LT) dependent. This study was undertaken to characterize the peripheral B cell compartment longitudinally during anti‐TNF therapy in RA.

Methods

Participants were randomized in a 2:1 ratio to receive standard dosing regimens of etanercept (n = 43) or adalimumab (n = 20) for 24 weeks. Eligible participants met the American College of Rheumatology 1987 criteria for RA, had clinically active disease (Disease Activity Score in 28 joints >4.4), and were receiving stable doses of methotrexate. The primary mechanistic end point was the change in switched memory B cell fraction from baseline to week 12 in each treatment group.

Results

B cell subsets remained surprisingly stable over the course of the study regardless of treatment group, with no significant change in memory B cells. Blockade of TNF and LT with etanercept compared to blockade of TNF alone with adalimumab did not translate into significant differences in clinical response. The frequencies of multiple activated B cell populations, including CD21− double‐negative memory and activated naive B cells, were higher in RA nonresponders at all time points, and CD95+ activated B cell frequencies were increased in patients receiving anti‐TNF treatment in the nonresponder group. In contrast, frequencies of transitional B cells—a putative regulatory subset—were lower in the nonresponders.

Conclusion

Overall, our results support the notion that peripheral blood B cell subsets are remarkably stable in RA and not differentially impacted by dual blockade of TNF and LT with etanercept or single blockade of TNF with adalimumab. Activated B cells do associate with a less robust response.
Derivative‐Free Optimization of a Fixed‐Bed Methanol Synthesis Reactor
Authors: Obut Salih
Published: August 2021

A one‐dimensional heterogeneous fixed‐bed methanol synthesis reactor model was developed for the optimization of carbon conversion and rate of methanol production. The developed model was validated both at pellet and reactor scales. The reactor inlet syngas composition and cooling water temperature, i.e., the design variables, providing the highest carbon conversion and rate of methanol production were determined by a constrained derivative‐free optimization algorithm. The results revealed that after optimization the carbon conversion was increased by 12 % and the rate of methanol production by 48 %. Under the optimized conditions, the stoichiometric number was in the range of industrial values.
Influence of the Fe : Ni Ratio in FexNi9‐xS8 (x=3–6) on the CO2 Electroreduction
Authors: Tetzlaff David , Pellumbi Kevinjeorjios , Puring Kai junge , Siegmund Daniel , Polet Wigbert S. K. , Checinski Marek P. , Apfel Ulf‐Peter
Published: August 2021

The electrochemical CO2 reduction (CO2R) is a promising approach to decrease the amount of CO2 in the atmosphere by producing commodity chemicals or fuels using renewable energies. Herein, the development of non‐noble metal electrocatalysts is regarded as a key point for achieving the transition of CO2R to industrial scales. Transition metal chalcogenides of the pentlandite structure (M9X8) have emerged as promising electrocatalysts to produce syngas. In this line, we present the electrochemical CO2R of FexNi9‐xS8 (x=3–6) with variable Fe : Ni ratios. All materials can reduce H2O/CO2 mixtures to CO or H2 respectively with varying efficiency depending on the Fe : Ni ratio and the water content. While CO2R in proton‐rich organic electrolytes was mainly accompanied by hydrogen evolution, the CO2R activity climaxed with F.E. of 3.6 % for CO and 0.3 % for methane using Fe3Ni6S8. Using electrolytes with low water content, CO production with F.E. close to 90 % was demonstrated. Counterintuitively, the variation of the Fe : Ni ratio led only to small alterations in the CO2R activity. Quantum mechanical studies were performed to get further information on the observed trends and provide further insight into structure/activity relationships for the Fe/Ni pentlandite system and its CO2R activity opening the path towards the development of more active and robust CO2R electrocatalysts.
Understanding Structure‐activity Relationship on Metal‐Organic‐Framework‐Derived Catalyst for CO2 Electroreduction to C2 Products
Authors: Han Yunxi , Zhu Shuaikang , Xu Shuang , Niu Xiaopo , Xu Zhihong , Zhao Rong , Wang Qingfa
Published: August 2021

Metal‐organic frameworks (MOFs) have been widely studied for electrochemical CO2 reduction reaction (CO2RR). However, the application of negative potential tends to trigger its structural reconstruction and component alteration. It is of great significance to study the relationship between the structural evolution of MOF‐derived materials and product selectivity under the reaction conditions. Herein, we fabricate a HKUST‐1 thin film on carbon fiber paper by a facile electrodeposition approach to investigate the variation of CO2RR activity with HKUST‐1 structural reconstruction. During the CO2RR process, the HKUST‐1 reconstructs into two structures successively over time: 3D nanospheres composed of numerous small fragments and 3D nano‐network composed of cross‐linked nanobelts in different directions. The former shows a better catalytic activity due to more active sites, lower charge transfer resistance and higher Cu+/Cu0 ratio. The optimum Faradaic efficiency (FE) of C2 products (ethylene and ethanol) reaches 58.6 % at −0.98 V versus reversible hydrogen electrode (RHE).
Strong Electrostatic Adsorption Strategy to Enhance Interaction Between Ultra‐Small Ru Nanoparticles and Carbon for High‐Efficient Electrocatalyst Toward HER in Acidic and Alkaline Media
Authors: Fan Xizheng , Pang Qingqing
Published: August 2021

Developing powerful and tolerant catalysts toward hydrogen evolution reaction (HER) is fairly meaningful and critical for the conversion and utilization of green energy. In this work, we exploit an improved, reliable, and convenient strong electrostatic adsorption strategy to synthesize Ru‐based electrocatalysts containing ultra‐small Ru nanoparticles (NPs). As verified by experimental studies and characterization analysis, the optimized treatment can strengthen the powerful interaction for anchoring ultra‐small Ru NPs dispersed on carbon substrate and prevent the migration and agglomeration of Ru NPs during catalytic reactions. It is demonstrated that the designed Ru−KB−H−6H exhibits exceptional HER performance with low overpotential (η10) and Tafel slope (52 mV and 41.5 mV dec−1 in 0.5 M H2SO4, 53 mV and 61.0 mV dec−1 in 1.0 M KOH). As expected, Ru−KB−H−6H displays dramatical stability with no unacceptable decline of LSV performance after 8000 cycles and long‐term test. This finding paves a practical way to fabricate high‐efficient, and steady electrocatalysts toward HER for industrial applications.
Hierarchically mesoporous carbon spheres coated with a single atomic Fe–N–C layer for balancing activity and mass transfer in fuel cells
Authors: Shu Chengyong , Tan Qiang , Deng Chengwei , Du Wei , Gan Zhuofan , Liu Yan , Fan Chao , Jin Hui , Tang Wei , Yang Xiao‐dong , Yang Xiaohua , Wu Yuping
Published: August 2021

Novel cost‐effective fuel cells have become more attractive due to the demands for rare and expensive platinum‐group metal (PGM) catalysts for mitigating the sluggish kinetics of the oxygen reduction reaction (ORR). The high‐cost PGM catalyst in fuel cells can be replaced by Earth‐abundant transition‐metal‐based catalysts, that is, an Fe–N–C catalyst, which is considered one of the most promising alternatives. However, the performance of the Fe–N–C catalyst is hindered by the low catalytic activity and poor stability, which is caused by insufficient active sites and the lack of optimization of the triple‐phase interface for mass transportation. Herein, a novel Fe–N–C catalyst consisting of mono‐dispersed hierarchically mesoporous carbon sphere cores and single Fe atom‐dispersed functional shells are presented. The synergistic effect between highly dispersed Fe‐active sites and well‐organized porous structures yields the combination of high ORR activity and high mass transfer performance. The half‐wave potential of the catalyst in 0.1 M H2SO4 is 0.82 V versus reversible hydrogen electrode, and the peak power density is 812 mW·cm−2 in H2–O2 fuel cells. Furthermore, it shows superior methanol tolerance, which is almost immune to methanol poisoning and generates up to 162 mW·cm−2 power density in direct methanol fuel cells.
ANN‐based modelling of peppermint flavour encapsulation process with ultrasound approach
Authors: Potdar Shital B. , Bhanvase Bharat A. , Saudagar Prakash , Potoroko Irina , Sonawane Shirish H.
Published: August 2021

Encapsulation has great potential for preserving the flavour and health benefits of bioactive compounds. Hence, in the previous study, an attempt was made to encapsulate peppermint flavour in a gum arabic (GA) shell. To further understand the effect of a wide range of parameters, in the present study, artificial neural networks (ANNs) are developed. To predict the effect of various parameters on the encapsulation process, networks are developed with a back‐propagation algorithm. Input parameters for the ANN are flavour concentration, GA concentration, spray dryer temperature and feed flow rate to the spray dryer. The encapsulation process is evaluated in terms of encapsulation efficiency, product yield, and particle size. To predict all outputs simultaneously, a combined model is developed. The results showed that the combined model has similar accuracy as that of the individual model and also helps to save on processing time. For the combined model, the best prediction performance is obtained with 5‐4‐3 ANN architecture exhibiting an R2 value of 0.9991, and corresponding MSE values of 0.000 54, 0.000 63, and 0.000 61 for encapsulation efficiency, product yield, and particle size, respectively. This indicates that the developed ANN model is capable of predicting the encapsulation process. The interpolation and extrapolation ability of the developed network is also evaluated.
Natural language processing for the assessment of cardiovascular disease comorbidities: The cardio‐Canary comorbidity project
Authors: Berman Adam N. , Biery David W. , Ginder Curtis , Hulme Olivia L. , Marcusa Daniel , Leiva Orly , Wu Wanda Y. , Cardin Nicholas , Hainer Jon , Bhatt Deepak L. , Di Carli Marcelo F. , Turchin Alexander , Blankstein Ron
Published: August 2021

Objective: Accurate ascertainment of comorbidities is paramount in clinical research. While manual adjudication is labor‐intensive and expensive, the adoption of electronic health records enables computational analysis of free‐text documentation using natural language processing (NLP) tools.

Hypothesis: We sought to develop highly accurate NLP modules to assess for the presence of five key cardiovascular comorbidities in a large electronic health record system.

Methods: One‐thousand clinical notes were randomly selected from a cardiovascular registry at Mass General Brigham. Trained physicians manually adjudicated these notes for the following five diagnostic comorbidities: hypertension, dyslipidemia, diabetes, coronary artery disease, and stroke/transient ischemic attack. Using the open‐source Canary NLP system, five separate NLP modules were designed based on 800 “training‐set” notes and validated on 200 “test‐set” notes.

Results: Across the five NLP modules, the sentence‐level and note‐level sensitivity, specificity, and positive predictive value was always greater than 85% and was most often greater than 90%. Accuracy tended to be highest for conditions with greater diagnostic clarity (e.g. diabetes and hypertension) and slightly lower for conditions whose greater diagnostic challenges (e.g. myocardial infarction and embolic stroke) may lead to less definitive documentation.

Conclusion: We designed five open‐source and highly accurate NLP modules that can be used to assess for the presence of important cardiovascular comorbidities in free‐text health records. These modules have been placed in the public domain and can be used for clinical research, trial recruitment and population management at any institution as well as serve as the basis for further development of cardiovascular NLP tools.
Active Learning Training Strategy for Predicting O Adsorption Free Energy on Perovskite Catalysts using Inexpensive Catalyst Features
Authors: Shambhawi Shambhawi , Csányi Gábor , Lapkin Alexei A.
Published: August 2021

Machine learning (ML) based energy prediction models are among the most effective descriptor‐based catalyst screening tools for heterogeneous reaction systems. However, their implementations are limited due to expensive data labelling, ab initio feature evaluation and lack of universal catalyst features, that is, beyond d‐band theory. Herein, we propose an inexpensive geometric feature for application on systems beyond d‐band theory, for example perovskites comprising of s‐, p‐, d‐ and f‐block elements. We outline a workflow that inputs these features into an active learning algorithm that enables effective data labelling, whilst improving prediction accuracies of existing models. We then use batch sampling to define termination criteria and to implement time‐series error forecasting for further reducing the number of expensive data labelling for training. We implement this workflow to train ML models for predicting oxygen adsorption free energy on perovskites and achieve similar, if not better, prediction accuracies as obtained from ab initio features.
Improved heterogeneous data fusion and multi‐scale feature selection method for lung cancer subtype classification
Authors: Zhang Yanan , Zhao Juanjuan , Qiang Yan , Yang Xiaotang , Wu Wei , Jia Liye
Published: August 2021

The diagnosis of the disease requires a variety of data and indicators. In order to make the computer perform intelligent computation and diagnosis from a doctor's perspective, complementary information between different modal data needs to be taken into account. Meanwhile, the redundancy features with key information should be selected in order to reduce the complexity of calculation. In this study, an adaptive dynamic loss function is proposed to weight different scales in the multi‐scale expansion network of pathological images according to the doctor's diagnosis process. And an ant colony algorithm based on maximum information coefficient correlation was designed for unsupervised feature selection of fusion features combined image feature and patient differential genes. Experimental results show that the addition of pathological image information and genetic information plays an important role in the classification of lung cancer subtypes. Compared with other feature selection methods, the proposed algorithm can quickly converge. Combining pathological image and gene expression matrix for cancer diagnosis can improve the diagnostic accuracy of specific patients, with an accuracy of 95.62 and AUC achieves 0.897. The proposed method has high effectiveness and superior performance in the classification of lung cancer.
A fuzzy logic‐based approach for fuzzy queries over NoSQL graph database
Authors: Ahmadi Zahra , Parand Fereshteh‐Azadi , Matinfar Farzam
Published: August 2021

The massive production of data in the web environment increases the need for efficient and effective solutions to store and manage data. NoSQL databases with the capability of storing various types of data were introduced to be used in the management of big data. Besides, supporting flexible querying has significant impacts on data management usability and users prefer to ask their requests using fuzzy terms and get crisp results to make efficient decisions. In this paper, a fuzzy‐based approach is presented which adopts fuzzy queries and delivers crisp recommendations to the users. For this purpose, a counselor, which acts as a fuzzy agent and has knowledge about the data, defines fuzzy terms, membership functions and fuzzy rule tables in a way that each user can ask queries through fuzzy terms. The evaluation results show the efficiency of the proposed approach which removes the need for high‐level programming skills for users. As a result, our approach's efficiency and user acceptance are increased as well and made it an appropriate solution for using ambiguous queries in big graph databases.
Band Gap Tuning of Covalent Triazine‐Based Frameworks through Iron Doping for Visible‐Light‐Driven Photocatalytic Hydrogen Evolution
Authors: Gao Shengjie , Zhang Peng , Huang Guocheng , Chen Qiaoshan , Bi Jinhong , Wu Ling
Published: August 2021

Photocatalytic hydrogen energy production through water splitting paves a promising pathway for alleviating the increasingly severe energy crisis. Seeking affordable, highly active, and stable photocatalysts is crucial to access the technology in a sustainable manner. Herein, a trivalent iron‐doped covalent triazine‐based framework (CTF‐1) was elaborately designed in this study to finely tune the band structure and photocatalytic activity of CTF‐1 for H2 production. With optimal doping amount, Fe10/CTF‐1 exhibited a satisfying H2 production activity of 1460 μmol h−1 g−1, corresponding to 28‐fold enhancement compared with pure CTF‐1. The Fe3+ doping is responsible for a remarkedly broadened visible‐light adsorption range, improved reduction ability and inhibited electron–hole recombination of CTF‐1. Specifically, the doped Fe3+ could serve as photocatalytically active center and “electron relay” to accelerate charge separation and transformation. This study offers a feasible strategy to validly design and synthesize CTF‐based photocatalytic materials to efficiently utilize solar energy.
Single‐cell transcriptomes reveal heterogeneity of high‐grade serous ovarian carcinoma
Authors: Hao Qian , Li Jiajia , Zhang Qinghua , Xu Fei , Xie Bangxiang , Lu Hua , Wu Xiaohua , Zhou Xiang
Published: August 2021

Background

High‐grade serous ovarian carcinoma (HGSOC) is the most common and aggressive histotype of epithelial ovarian cancer. The heterogeneity and molecular basis of this disease remain incompletely understood.

Methods

To address this question, we have performed a single‐cell transcriptomics analysis of matched primary and metastatic HGSOC samples.

Results

A total of 13 571 cells are categorized into six distinct cell types, including epithelial cells, fibroblast cells, T cells, B cells, macrophages, and endothelial cells. A subset of aggressive epithelial cells with hyperproliferative and drug‐resistant potentials is identified. Several new markers that are highly expressed in epithelial cells are characterized, and their roles in ovarian cancer cell growth and migration are further confirmed. Dysregulation of multiple signaling pathways, including the translational machinery, is associated with ovarian cancer metastasis through the trajectory analysis. Moreover, single‐cell regulatory network inference and clustering (SCENIC) analysis reveals the gene regulatory networks and suggests the JUN signaling pathway as a potential therapeutic target for treatment of ovarian cancer, which is validated using the JUN/AP‐1 inhibitor T‐5224. Finally, our study depicts the epithelial‐fibroblast cell communication atlas and identifies several important receptor‐ligand complexes in ovarian cancer development.

Conclusions

This study uncovers new molecular features and the potential therapeutic target of HGSOC, which would advance the understanding and treatment of the disease.
Can functional genomic diversity provide novel insights into mechanisms of community assembly? A pilot study from an invaded alpine streambed
Authors: Marx Hannah E. , Carboni Marta , Douzet Rolland , Perrier Christophe , Delbart Franck , Thuiller Wilfried , Lavergne Sébastien , Tank David C.
Published: August 2021

An important focus of community ecology, including invasion biology, is to investigate functional trait diversity patterns to disentangle the effects of environmental and biotic interactions. However, a notable limitation is that studies usually rely on a small and easy‐to‐measure set of functional traits, which might not immediately reflect ongoing ecological responses to changing abiotic or biotic conditions, including those that occur at a molecular or physiological level. We explored the potential of using the diversity of expressed genes—functional genomic diversity (FGD)—to understand ecological dynamics of a recent and ongoing alpine invasion. We quantified FGD based on transcriptomic data measured for 26 plant species occurring along adjacent invaded and pristine streambeds. We used an RNA‐seq approach to summarize the overall number of expressed transcripts and their annotations to functional categories, and contrasted this with functional trait diversity (FTD) measured from a suite of characters that have been traditionally considered in plant ecology. We found greater FGD and FTD in the invaded community, independent of differences in species richness. However, the magnitude of functional dispersion was greater from the perspective of FGD than from FTD. Comparing FGD between congeneric alien–native species pairs, we did not find many significant differences in the proportion of genes whose annotations matched functional categories. Still, native species with a greater relative abundance in the invaded community compared with the pristine tended to express a greater fraction of genes at significant levels in the invaded community, suggesting that changes in FGD may relate to shifts in community composition. Comparisons of diversity patterns from the community to the species level offer complementary insights into processes and mechanisms driving invasion dynamics. FGD has the potential to illuminate cryptic changes in ecological diversity, and we foresee promising avenues for future extensions across taxonomic levels and macro‐ecosystems.
Diversity and habitat association of medium and large mammals in Gibe Sheleko National Park, Southern Ethiopia
Authors: Abie Kassahun , Tilahun Belete , Feyisa Abel , Kumssa Tewodros , Amare Alemneh
Published: August 2021

Complete documentation on the status of mammals is indispensable for appropriate conservation measures in protected areas. However, there is inadequate information on mammalian resources in the ecosystem of Gibe Sheleko National Park (GSNP). Thus, the study aimed to assess species diversity, abundance, and habitat association of medium‐ and large‐sized mammals in GSNP. We stratified the study area into five dominant habitat types, namely dense forest, wooded grassland, grassland, riverine forest, and farmland habitat types based on land cover and vegetation structures and further employed stratified random sampling technique across each habitat type. The sample transects covered 20% of the study area. Transect width ranged from 50 m to 400 m based on vegetation cover and visibility of mammals. The main data were collected via direct observation. Data were analyzed via chi‐square test and species diversity indexes. We recorded the total of 20 mammals species' those belong to 10 families of which 8 species were large‐sized and 12 species medium‐sized mammals. There were two IUCN vulnerable species, namelyHippopotamus amphibiousandPanthera pardus, and two globally near‐threatened species, particularlyLitocranius walleriandCaracal caracalin the study area. Dense forest held the highest species diversity of medium‐ and large‐sized mammals (H′ = 2.28) with the highest evenness index (J = 0.84). Riverine forest had the least diversity with uneven population distribution.Papio anubiswas the most abundance species, whereasCaracal caracalwas the least abundant in the study area. GSNP is home for threatened and spectacular mammals species'; hence, an appropriate conservation measure is mandatory to keep existing mammals species'.
Combined evaluation of right ventricular function using echocardiography in non‐ischaemic dilated cardiomyopathy
Authors: Ishiwata Jumpei , Daimon Masao , Nakanishi Koki , Sugimoto Tadafumi , Kawata Takayuki , Shinozaki Tomohiro , Nakao Tomoko , Hirokawa Megumi , Sawada Naoko , Yoshida Yuriko , Amiya Eisuke , Hatano Masaru , Morita Hiroyuki , Yatomi Yutaka , Komuro Issei
Published: August 2021

Aims

Although comprehensive assessment of right ventricular (RV) function using multiple echocardiographic parameters is recommended for management of patients with non‐ischaemic dilated cardiomyopathy (DCM), it is unclear which RV parameters to combine. Additionally, normalization of RV parameters by estimated pulmonary artery systolic pressure (PASP), in consideration of RV–pulmonary artery coupling, may be clinically significant. The aim of our study was to elucidate the best combination of echocardiographic RV functional parameters, with or without indexing for PASP, to predict outcome in patients with heart failure with reduced ejection fraction secondary to DCM.

Methods and results

We retrospectively analysed 109 DCM patients with left ventricular ejection fraction <40%. RV size was assessed by RV end‐diastolic area (RVEDA) and RV end‐systolic area (RVESA) from RV‐focused apical four‐chamber view. RV function was assessed by fractional area change (FAC) and tricuspid annular plane systolic excursion (TAPSE) and by RV longitudinal strain (RVLS) using two‐dimensional speckle‐tracking echocardiography. All functional parameters were also indexed for estimated PASP. Cox analyses were used to evaluate the association of RV morphology and functional parameters with 1 year outcome (composite of left ventricular assist device implantation and all‐cause death). Area under the curve was used to compare prognostic values. Mean age was 44 ± 14 years, and 76 (69.7%) were men. Mean left ventricular ejection fraction was 21.9%, median RVEDA was 22.1 cm2, FAC was 27.0%, TAPSE was 15.0 mm, and RVLS was −12.5%. Forty‐one (37.6%) patients experienced the primary outcome. Multivariate Cox analysis revealed that RVEDA, RVESA, FAC, TAPSE, RVLS, FAC/PASP, and RVLS/PASP were independent predictors for primary outcome (all P < 0.05). However, normalization with PASP did not improve area under the curve for any RV functional parameters. When we evaluate hazard ratios according to the combination of two echocardiographic parameters of RV function, patients with impairment of both FAC (<27%) and RVLS (>−8.6%) had significantly higher hazard ratio than those with either impairment alone (11.3 vs. 3.4, P < 0.001); the other combinations did not improve prognostic value.

Conclusions

Normalizing echocardiographic RV parameters for PASP did not improve the prognostic values for our population. Meanwhile, combined evaluation of FAC and RVLS improved risk stratification in patients with heart failure with reduced ejection fraction secondary to DCM.
Granzyme A and CD160 expression delineates ILC1 with graded functions in the mouse liver
Authors: Di Censo Chiara , Marotel Marie , Mattiola Irene , Müller Lena , Scarno Gianluca , Pietropaolo Giuseppe , Peruzzi Giovanna , Laffranchi Mattia , Mazej Julija , Hasim Mohamed Shaad , Asif Sara , Russo Eleonora , Tomaipitinca Luana , Stabile Helena , Lee Seung‐Hwan , Vian Laura , Gadina Massimo , Gismondi Angela , Shih Han‐Yu , Mikami Yohei , Capuano Cristina , Bernardini Giovanni , Bonelli Michael , Sozzani Silvano , Diefenbach Andreas , Ardolino Michele , Santoni Angela , Sciumè Giuseppe
Published: August 2021

Type 1 innate lymphoid cells (ILC1) are tissue‐resident lymphocytes that provide early protection against bacterial and viral infections. Discrete transcriptional states of ILC1 have been identified in homeostatic and pathological contexts. However, whether these states delineate ILC1 with different functional properties is not completely understood. Here, we show that liver ILC1 are heterogeneous for the expression of distinct effector molecules and surface receptors, including granzyme A (GzmA) and CD160, in mice. ILC1 expressing high levels of GzmA are enriched in the liver of adult mice, and represent the main hepatic ILC1 population at birth. However, the heterogeneity of GzmA and CD160 expression in hepatic ILC1 begins perinatally and increases with age. GzmA+ ILC1 differ from NK cells for the limited homeostatic requirements of JAK/STAT signals and the transcription factor Nfil3. Moreover, by employing Rorc(γt)‐fate map (fm) reporter mice, we established that ILC3‐ILC1 plasticity contributes to delineate the heterogeneity of liver ILC1, with RORγt‐fm+ cells skewed toward a GzmA–CD160+ phenotype. Finally, we showed that ILC1 defined by the expression of GzmA and CD160 are characterized by graded cytotoxic potential and ability to produce IFN‐γ. In conclusion, our findings help deconvoluting ILC1 heterogeneity and provide evidence for functional diversification of liver ILC1.
Relevance of the Catholyte Mixing Method for Solid‐State Composite Cathodes
Authors: Morant-Miñana Maria Carmen , Liendo Guillermo , Cabello Marta , Quintela Amaia , Blanco June , Martin-Fuentes Silvia , Armand Michel , Otaegui Laida , Villaverde Aitor
Published: August 2021

The significant impact of the process steps on the electrode performance is one of the least developed aspects in the field of solid‐state batteries despite being a key issue for the transference of lab‐scale developments to production scale. To demonstrate that the knowledge of production parameters is essential, a set of high active material loading solid‐state batteries with a lithium metal anode and a polymer electrolyte is fabricated using different mixing methods for the catholyte preparation. Depending on the shear rate of the mixer, the polymer molecular weight and consequently, the viscosity of the catholyte is affected and these differences are preserved during the slurry preparation and electrode coating. The electrochemical performance of each cathode is studied in full‐cell configuration obtaining high areal capacities (≈1 mAh cm−2) and high specific capacities (92%, 82%, and 95% of the theoretical capacity of LiFePO4). After 50 cycles, composite cathodes mixed with high‐shear‐rate techniques experience a capacity fade related with the larger degree of deagglomeration of the C65 occurring when less viscous catholytes are used. Low‐shear‐rate cathodes keep the starting capacity, revealing a protective role of the catholyte during the wet‐mixing process.
Vegetation disturbances and flood energy during an extreme flood on a sub‐tropical river
Authors: Sharpe Richard , Kemp Justine
Published: August 2021

The advent of 2D hydraulic modelling has improved our understanding of flood hydraulics, thresholds, and dynamic effects on floodplain geomorphology and riparian vegetation at the morphological‐unit scale. Hydraulic concepts of bed shear stress, stream power maxima, and energy (cumulative stream power) have been used to characterize floods and define their geomorphic effectiveness. These hydraulic concepts were developed in the context of reach‐averaged, 1D hydraulic analyses, but their application to 2D model results is problematic due to differences in the treatment of energy losses in 1D and 2D analyses. Here we present methods for estimating total and boundary resistance from 2D modelling of an extreme flood on a subtropical river. Hydraulic model results are correlated with observations of the flood impacts on floodplain geomorphology and the riparian vegetation to identify thresholds and compute variants of flood energy. Comparison of LiDAR data in 2011 and 2014 shows that the 2011 flood produced 2–4 m of erosion on floodplain bars that were previously forested or grass‐covered. Deposition on flood levees, dunes, and chute bars was up to 3.4 m thick. Various hydraulic metrics were trialled as candidates for thresholds of vegetation disturbance. The accuracy of thresholds using metrics extracted at the flood peak (i.e. boundary resistance and stream power maxima) was similar to that using energy as a threshold. Disturbance to forest and grass on vegetated bars was associated with stream powers of >834 W/m2and unit flows of >26 m2/s, respectively. Correlation of the hydraulic metrics with erosion and deposition depths showed no substantial improvement in using flood energy compared to metrics extracted at the flood peak for describing erosion and deposition. The extent of vegetation disturbances and morphological adjustments was limited for this extreme flood, and further 2D studies are needed to compare disturbance thresholds across different environments.
Verdichtungseigenschaften von schiefrig‐phyllitischem Tunnelausbruchmaterial
Authors: Voit Klaus , Depiné Manuel , Hofmann Matthias , Orsi Georg , Murr Roland , Zangerl Christian , Bergmeister Konrad
Published: August 2021

Large quantities of excavated rocks are generated during tunnel driving. Recycling possibilities and total percentage of recycling are depending on the rock conditions (rock type and rock properties), as well as the applied driving method. If recycling of the excavated rock mass is not possible or reasonable from a technical or economical point of view, the excavated material needs to be deposited in landfills. Thereby, the consumed landfill volume depends on the material volume of non‐recyclable rock and its compactability as a function of the loosening of the rock by excavation and landfill installation. Both, material volume and compactability of the excavated material, are difficult to evaluate in advance. Apart from unpredictable lithological changes and variation of the driving parameters (e.g. depth of advance in conventional driving, contact pressure of tunnel boring machine), external influences – like afflux of water or weather conditions during installation of the material – significantly affect the compactability of the excavated aggregates. In this study, the actual example of phyllitic rock material excavated by conventional drilling and blasting from the main tunnel tubes of the Brenner Base Tunnel has been chosen to take a closer look at the research question concerning the compactability of phyllitic rock material. Since excavation material is increasingly used in construction industry, detailed knowledge on this matter is necessary for a successful application.