bluuebunny/crossref_metadata_2025_split huggingface dataset:
Obese dogs exhibit different fecal microbiome and specific microbial networks compared with normal weight dogs
Authors: Kim Hanbeen , Seo Jakyeom , Park Tansol , Seo Kangmin , Cho Hyunwoo , Chun Julan , Kim Kihyun 
Published: June 2022

Abstract
Background
Canine obesity is a major health concern that predisposes dogs to various disorders. The fecal microbiome has been attracting attention because of their impact on energy efficiency and metabolic disorders of host. However, little is known about specific microbial interactions, and how these may be affected by obesity in dogs. The objective of this study was to investigate the differences in fecal microbiome and specific microbial networks between obese and normal dogs. A total of 20 beagle dogs (males = 12, body weight [BW]: 10.5 ± 1.08 kg; females = 8, BW: 11.3 ± 1.71 kg; all 2-year-old) were fed to meet the maintenance energy requirements for 18 weeks. Then, 12 beagle dogs were selected based on body condition score (BCS) and divided into two groups: high BCS group (HBCS; BCS range: 7–9, males = 4, females = 2) and normal BCS group (NBCS; BCS range: 4–6, males = 4, females = 2). In the final week of the experiment, fecal samples were collected directly from the rectum, before breakfast, for analyzing the fecal microbiome using 16S rRNA gene amplicon sequencing.
Results
The HBCS group had a significantly higher final BW than the NBCS group (P < 0.01). The relative abundances of Faecalibacterium, Phascolarctobacterium, Megamonas, Bacteroides, Mucispirillum, and an unclassified genus within Ruminococcaceae were significantly higher in the HBCS group than those in the NBCS group (P < 0.05). Furthermore, some Kyoto Encyclopedia of Genes and Genomes (KEGG) modules related to amino acid biosynthesis and B vitamins biosynthesis were enriched in the HBCS group (P < 0.10), whereas those related to carbohydrate metabolism were enriched in the NBCS group (P < 0.10). Microbial network analysis revealed distinct co-occurrence and mutually exclusive interactions between the HBCS and NBCS groups.
Conclusions
In conclusion, several genera related to short-chain fatty acid production were enriched in the HBCS group. The enriched KEGG modules in the HBCS group enhanced energy efficiency through cross-feeding between auxotrophs and prototrophs. However, further studies are needed to investigate how specific networks can be interpreted in the context of fermentation characteristics in the lower gut and obesity in dogs.
Building a trustworthy AI differential diagnosis application for Crohn’s disease and intestinal tuberculosis
Authors: Lu Keming , Tong Yuanren , Yu Si , Lin Yucong , Yang Yingyun , Xu Hui , Li Yue , Yu Sheng 
Published: June 2022

Abstract
Background
Differentiating between Crohn’s disease (CD) and intestinal tuberculosis (ITB) with endoscopy is challenging. We aim to perform more accurate endoscopic diagnosis between CD and ITB by building a trustworthy AI differential diagnosis application.
Methods
A total of 1271 electronic health record (EHR) patients who had undergone colonoscopies at Peking Union Medical College Hospital (PUMCH) and were clinically diagnosed with CD (n = 875) or ITB (n = 396) were used in this study. We build a workflow to make diagnoses with EHRs and mine differential diagnosis features; this involves finetuning the pretrained language models, distilling them into a light and efficient TextCNN model, interpreting the neural network and selecting differential attribution features, and then adopting manual feature checking and carrying out debias training.
Results
The accuracy of debiased TextCNN on differential diagnosis between CD and ITB is 0.83 (CR F1: 0.87, ITB F1: 0.77), which is the best among the baselines. On the noisy validation set, its accuracy was 0.70 (CR F1: 0.87, ITB: 0.69), which was significantly higher than that of models without debias. We also find that the debiased model more easily mines the diagnostically significant features. The debiased TextCNN unearthed 39 diagnostic features in the form of phrases, 17 of which were key diagnostic features recognized by the guidelines.
Conclusion
We build a trustworthy AI differential diagnosis application for differentiating between CD and ITB focusing on accuracy, interpretability and robustness. The classifiers perform well, and the features which had statistical significance were in agreement with clinical guidelines.
High-throughput first-principle prediction of collinear magnetic topological materials
Authors: Li Gang , Su YunLong , Hu Jiayu , Cai Xiaochan , Shi Wujun , Xia Yunyouyou , Xu Yuanfeng , Xu Xuguang , Chen Yulin 
Published: June 2022

Abstract
The success of topological band theory and symmetry-based topological classification significantly advances our understanding of the Berry phase. Based on the critical concept of topological obstruction, efficient theoretical frameworks, including topological quantum chemistry and symmetry indicator theory, were developed, making a massive characterization of real materials possible. However, the classification of magnetic materials often involves the complexity of their unknown magnetic structures, which are often hard to know from experiments, thus, hindering the topological classification. In this paper, we design a high-throughput workflow to classify magnetic topological materials by automating the search for collinear magnetic structures and the characterization of their topological natures. We computed 1049 chosen transition metal compounds (TMCs) without oxygen and identified 64 topological insulators and 53 semimetals, which become 73 and 26 when U correction is further considered. Due to the lack of magnetic structure information from experiments, our high-throughput predictions provide insightful reference results and make the first step towards a complete diagnosis of magnetic topological materials.
Research on chemical resistance characteristics of water-soaked coal with different metamorphic degrees
Authors: Zhang Xun , Zhao Mengfan , Yang Jing , Lu Bing , Wang Gang , Dai Fengwei 
Published: June 2022

Abstract
In order to reduce the risk of spontaneous combustion of coal left after long-term flooding in the goaf of the mine, in this paper, the inhibitory properties of different inhibitors on two kinds of water-leached coals with different metamorphic degrees were studied in depth. The experiment selected Ping Zhuang lignite and Sha qu coking coal as research objects. The raw coal and water-soaked coal samples were compared and analyzed by thermogravimetric experiment method and Fourier transform infrared spectroscopy experiment method. research shows, the activation temperature of soaked lignite and coking coal decreased by 7.91 and 2.25°C, respectively. The activation energy decreased by 43.18 kJ·mol− 1 and 20.58 kJ·mol− 1, respectively, the natural tendency of coal is enhanced after being soaked in water, and water soaking has a greater impact on low-metamorphic lignite. Then four kinds of inhibitors, MgCl2, TEMPO, TPPI and PA, were added to the two water-soaked coals respectively. It was found that TPPI can significantly reduce the heat release rate of water-immersed lignite, the reduction value is 10.49 W/mg, Dry cracking temperature of water-immersed lignite increased by 11.75 ℃, PA greatly increased the combustion activation energy of water-leached coking coal by 25.77 kJ/mol. Meanwhile, it was found from the microscopic active groups that TTPI increased the content of water-immersed lignite ether bonds by 4.84%. The absorption peak intensity of oxygen-containing functional groups such as C = O is significantly weakened. Similarly, PA caused water leaching of coking coal to produce large amounts of stable ethers, which increased by 5.21%, The largest reduction in hydroxyl content. After heating, TPPI decomposes into phosphoric acid, which can inhibit the increase of active groups such as a large number of oxygen-containing functional groups in water-immersed lignite, thereby reducing the risk of spontaneous combustion. As a metal chelator, PA can reduce the catalytic effect of metal ions in water-leached coking coal with fewer active groups, it inhibits coal spontaneous combustion by generating stable metal complexes to increase activation energy. This indicates that TTPI has the best inhibitory effect on water-leached lignite, while PA is more suitable for water-leached coking coal.
Use of a Simulated Patient Case and Structured Debrief to Explore Trainee Responses to a “Non-Compliant Patient”
Authors: Sous Waseem , Frank Kay , Cronkright Peter , Germain Lauren J. 
Published: June 2022

Abstract
Background: Labeling a patient “non-compliant” is a form of dehumanization that can deprive the patient of positive human qualities and/or agency in the mind of a physician. The term “non-compliant” is frequently used in medical record documentation and has been shown to compromise care, particularly for marginalized communities. There is limited literature on the impact of the label on medical trainees. We aimed to explore how internal medicine residents and fellows (trainees) perceive the term “non-compliant patient” and its impact on their practice after interacting with a simulated refugee patient who has not followed a physician’s recommendations. Methods: Kolb’s experiential learning cycle guided the design of the educational session which was part of a required communication skills curriculum for trainees. A scenario was created to simulate a refugee patient who had not adhered to their treatment plan and could potentially be labeled as “non-compliant.” Trainees participated in the 3-hour session consisting of a remote simulated patient encounter immediately followed by a virtual structured debrief session that was recorded and transcribed. Thematic analysis of debrief transcripts was conducted starting with the use of provisional codes from the literature on the doctor-patient relationship and de/humanization. Results: In group debrief sessions, trainees reflected upon the standardized patient case and chose to also discuss similar cases they had experienced in clinical practice. Trainees indicated that the term “non-compliant patient” served as a biasing function and described how this bias negatively impacted the doctor-patient relationship. Trainees described how marginalized communities might be more susceptible to the negative connotation associated with the term “non-compliant patient.” For some trainees, the term triggered further investigation of underlying barriers to care and exploration of the social determinants of health. Conclusions: The use of the phrase “non-compliant patient,” though common in medical practice, may lead to patient dehumanization among trainees. A simulated refugee patient encounter followed by a facilitated group debrief allowed participants to verbalize and reflect on the meaning and possible impact of the label.
Comparison of tropospheric delay correction methods of InSAR analysis using a meso-scale meteorological model: Case study from Japan
Authors: Sailellah Sardila Nurulhikmah , Fukushima Yo 
Published: June 2022

Abstract
A major source of errors in interferometric synthetic aperture radar (InSAR), used for mapping ground deformation, is the delay caused by changes in the propagation velocity of radar microwaves in the troposphere. It is common to correct this tropospheric delay noise using numerical weather models because of their widespread global availability. A variety of correction methods and tools exist and selecting the most appropriate one by considering weather models, delay models, and delay calculation algorithms is essential for specific applications. We compared the performance of two tropospheric delay correction methods applied to Advanced Land Observing Satellite-2 (ALOS-2) data acquired over Japan, where the atmospheric field is complex with significant seasonal variation. In particular, we tested 1) a method of delay integration along the slant radar line-of-sight (LOS) path using the mesoscale model (MSM) provided by the Japan Meteorological Agency and 2) the Generic Atmospheric Correction Online Service (GACOS) for InSAR, which estimates delay using the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis products along with an iterative decomposition approach. Results showed that tropospheric delay correction using the slant delay integration approach with MSM, which has a finer temporal and spatial resolution, performed slightly better than GACOS, which used ECMWF data. We further found that the differences in these tropospheric delay models would have limited significance, suggesting that the difference in performance mainly originates from differences in the numerical weather models being used. This study highlights the importance of using the best-available numerical weather model data for tropospheric delay calculations.
Machine learning approach for ball milling of alumina ceramics
Authors: Yu Jungwon , Kati Raju , Jin So-Hyun , Lee Youngjae , Lee Hyun Kwuon 
Published: June 2022

Abstract
In this work, machine learning (ML) approach based on polynomial regression was explored to analyze the optimal processing parameters and predict the target particle sizes for ball milling of alumina ceramics. Data points were experimentally obtained by measuring the particle sizes. Prediction interval (PI)-based optimization methods using polynomial regression analysis are proposed. As a first step, functional relations between the inputs and the responses are derived by applying the regression analysis. Later, based on these relations, objective functions to be maximized are defined by desirability approach. Finally, the proposed PI-based methods optimize both parameter points and intervals of the target mill for accomplishing user-specified target responses. The optimization results show that the PI-based point optimization methods can select and recommend statistically reliable optimized parameter points even though unique solutions for the objective functions do not exist. From the results of confirmation experiments, it is established that the optimized parameter points can produce desired particle sizes with quality responses quite similar to the target responses.
Effectiveness of the Chronic Care Model for Adults with Type 2 Diabetes in Primary Care: A Systematic Review and Meta-analysis
Authors: Goh Lay Hoon , Siah Chiew Jiat Rosalind , Tam Wilson Wai San , Tai E Shyong , Young Doris Yee Ling 
Published: June 2022

Abstract
Background Mixed evidence exists regarding the effectiveness of Chronic Care Model (CCM) with patient outcomes. Aim of this review is to examine effectiveness of CCM interventions on improving hemoglobin A1c (HbA1c), systolic BP (SBP), diastolic BP (DBP), LDL cholesterol and BMI among primary care adults with type 2 diabetes.Methods MEDLINE, Embase, CINAHL, Cochrane Central Registry of Controlled Trials, Scopus and Web of Science were searched from January 1990 to June 2021 for RCTs comparing CCM interventions against usual care among adults with type 2 diabetes mellitus in primary care with HbA1c, SBP, DBP, LDL cholesterol and BMI as outcomes. An abbreviated search was performed from 2021 to April 2022. This study followed PRISMA guideline for data extractions and Cochrane risk of bias assessment. Two reviewers independently extracted data. Meta-analysis was performed using Review Manager software. Heterogeneity was evaluated using c2 and I2 test statistics. Overall effects were evaluated using Z statistic.Results A total of 17 studies involving 16485 patients with type 2 diabetes were identified. Most studies had low risks of bias. Meta-analysis of all 17 studies revealed that CCM interventions significantly decreased HbA1c levels compared to usual care with mean difference (MD) -0.21%, 95% CI, -0.30 to -0.13; Z = 5.07, p<0.00001. Larger effects were experienced amongst higher baseline HbA1c ³8% adults (MD -0.36%, 95% CI -0.51 to -0.21; Z = 5.05, p<0.00001) and when 4 or more CCM elements were used in the interventions (MD -0.25%, 95% CI -0.35 to -0.15; Z = 4.85, p<0.00001). Interventions with CCM also decreased SBP (MD -2.93 mmHg, 95% CI -4.46 to -1.40, Z = 3.75, p=0.0002) and DBP (MD -1.35 mmHg, 95% CI -2.05 to -0.65, Z = 3.79, p=0.0002) compared to usual care. However, CCM had no impact on LDL-cholesterol levels and BMI.Conclusions CCM interventions as compared to usual care improve glycemic control among adults with type 2 diabetes in primary care, especially in those with poorly controlled glycemia with greater reductions when mean baseline HbA1c is ³8% and with interventions with 4 or more CCM elements.PROSPERO registration: Registration no. CRD42021273959.
Spin-orbit torque mediated coupling of terahertz light with nanometer-wavelength magnon modes
Authors: Salikhov Ruslan , Ilyakov Igor , Körber Lukas , Kakay Attila , Gallardo Rodolfo , Ponomaryov Alexey , Deinert Jan-Christoph , Oliveira Thales , Lenz Kilian , Fassbender Jürgen , Bonetti Stefano , Hellwig Olav , Lindner Jürgen , Kovalev Sergey 
Published: June 2022

Abstract
Nonvolatile and energy-efficient spin-based technologies call for new prospects for realization of logic devices able to operate at terahertz (THz) frequencies. For instance, magnonic elements require an efficient generation of high-energy exchange spin waves at nanometer wavelengths. For this to happen, a substantial coupling of the electro-magnetic stimulus, such as coherent THz field pulses, to the magnon modes is needed. However, the efficient excitation of non-uniform spin waves using THz light is elusive, due to the large momentum mismatch between the millimeter-wave radiation and the exchange-dominated, nanometer-sized, spin waves. Here, we overcome this fundamental problem of light-matter interaction via thin film engineering, exploiting relativistic spin-orbit torques confined to the interfaces of heavy-metal/ferromagnet heterostructures. Using single-cycle broadband THz radiation, we are able to excite spin-wave modes with a frequency of up to 0.6 THz and a wavelength as short as 6 nm. Numerical simulations demonstrate that the coupling of THz light with the exchange-dominated magnons originates solely from interfacial spin-orbit torques. Our results are of general applicability to other magnetic multilayered structures, and offer the prospective of nanoscale control of high-frequency signals.
SARS-CoV-2 Nsp6 causes cardiac defects through MGA/MAX complex-mediated increased glycolysis
Authors: Zhu Jun-yi , Wang Guanglei , Huang Xiaohu , Lee Hangnoh , Lee Jin-Gu , Yang Penghua , de Leemput Joyce van , Huang Weiliang , Kane Maureen , Yang Peixin , Han Zhe 
Published: June 2022

Abstract
SARS-CoV-2 infection causes COVID-19, a severe acute respiratory disease associated with cardiovascular complications including long-term outcomes. The presence of virus in cardiac tissue of patients with COVID-19 suggests this is a direct, rather than secondary, effect of infection. By expressing individual SARS-CoV-2 proteins in the Drosophila heart we demonstrated interaction of virus Nsp6 with host proteins of the MGA/MAX complex (MGA, PCGF6 and TFDP1). Complementing transcriptomic data from the fly heart revealed that this interaction blocks the antagonistic MGA/MAX complex, which shifts the balance towards MYC/MAX and activates glycolysis—with similar findings in mouse cardiomyocytes. Further, the Nsp6-induced glycolysis disrupted cardiac mitochondrial function, known to increase reactive oxygen species (ROS) in heart failure; this could explain COVID-19-associated cardiac pathology. Furthermore, inhibiting the glycolysis pathway by 2-deoxy-D-glucose (2DG) treatment attenuated the Nsp6-induced cardiac phenotype in fly and mice; thus, suggesting glycolysis as a potential pharmacological target for treating COVID-19-associated heart failure.
Roots and associated mycorrhizal fungi are important determinants of leaf litter decomposition and home-field advantage in subtropical forests
Authors: Wang Zhenyu , Wan Xiaohua , Liang Yifan , Huang Zhiqun 
Published: June 2022

Abstract
Aims The ‘home-field advantage (HFA) hypothesis’ predicts that litter decomposes faster in its original environment (“home”) than in the foreign environment (“guest”). The vast majority of tree species are primarily symbiotic with arbuscular mycorrhizal (AM) or ectomycorrhizal (ECM) fungi. To date, how different roots and associated mycorrhizae affect litter decay rates and HFA effects is not well known. Methods To fill this gap, we conducted a litter transplant and mycorrhizal-cut experiment in one arbuscular mycorrhizal (AM)- and one ectomycorrhizal (ECM)- associated tree species plantation in subtropical China, and tested whether roots and their associated mycorrhizal fungi affect the litter decomposition rate and HFA effect. Results Over a period of 720 days, we found that AM litter rots faster in the presence of fine roots and mycorrhizae at home, while the ECM litter decomposition rate did not change significantly with and without roots and mycorrhizae. AM litter showed no HFA effect regardless of the presence or absence of roots and associated mycorrhizae, while ECM litter showed a negative HFA effect only in the presence of roots and mycorrhizae. The negative HFA effect of ECM litter was attributed to the higher saprophytic fungal abundance and P-acquiring enzyme activities in the guest than in the home environment. Conclusions Our results indicated that variation in the interaction between mycorrhizal and saprotrophic fungi is a key factor in determining litter decomposition rates and the HFA effect through modification of saprophytic fungal abundance and P-acquiring enzyme activities.