bluuebunny/crossref_metadata_2025_split huggingface dataset:
ERIC-PCR-based molecular typing of multidrug-resistant Escherichia coli isolated from houseflies (Musca domestica) in the environment of milk and meat shops
Authors: Chandrakar C. , Shakya S. , Patyal A. , Jain A. , Ali S.L. , Mishra O.P. 
Published: August 2022

Abstract
The emergence and spread of antimicrobial resistance have become a major global public health concern. A component of this problem is the spread of antibiotic-resistant bacteria. Flies move freely between habitats of food-producing animals and human beings and thus have great potential for dissemination of antimicrobial-resistant bacteria from a contaminated environment to milk and meat markets, posing potential hazards for consumers. During the present study, a total of 150 houseflies were captured from milk and meat shops located in Durg and Raipur city of Chhattisgarh, India. The Escherichia coli were isolated from houseflies and characterized on the basis of cultural and molecular tests. Further, the isolates were subjected to antimicrobial susceptibility testing against frequently used antibiotics using the disk diffusion method. The antibiotic resistance genes and int1 gene were detected using polymerase chain reaction (PCR). A total of 45 E. coli isolates were obtained from the fly samples with an overall prevalence rate of 30·0%. Antibiogram results confirmed that E. coli isolates were resistant to multiple antibiotics. Out of the (45) isolates of E. coli, 17 (37·8%) isolates were extended-spectrum beta-lactamase (ESBL) producer and multi-drug-resistant (MDR). Out of the ESBL and MDR E. coli isolates, blaCTX-M (24·4%), blaTEM (11·1%), tetA (28·8%), tetB (26·7%), gyrA (26·7%), parC (31. 1%) and int1 genes (15·5%) were detected but none of the isolates were found positive for blaSHV gene. Findings of the present study confirm that MDR E. coli are widely distributed in houseflies and play an important role in the transmission of antibiotic-resistant bacteria from contaminated environments to milk and meat shop environment.
Identification of the ejecta deposit formed by the Australasian Tektite Event at Huai Om, northeastern Thailand
Authors: Tada Toshihiro , Tada Ryuji , Carling Paul A. , Songtham Wickanet , Chansom Praphas , Kogure Toshihiro , Chang Yu , Tajika Eiichi 
Published: August 2022

AbstractThe Australasian Tektite Event, approximately 0.8 Ma, is the youngest record of a large impact event on Earth. Although it is estimated that it occurred somewhere in Indochina based on the distribution of tektites, the crater has never been located. Here, we report the discovery and occurrence of shocked quartz with planar deformation features (PDFs) in the Quaternary depositional sequence at Huai Om in northeastern Thailand. Measurements of the orientation of lamellae using a universal stage microscope as well as observation using scanning electron microscopy and transmission electron microscopy were conducted to confirm the presence of PDFs. Together with the occurrence of in situ layered tektite fragments, we identify the depositional sequence as the ejecta deposit formed by the Australasian Tektite Event. We further describe the detailed lithostratigraphy of the ejecta deposit, which will allow the tracing of its distribution and lateral changes in its thickness, grain size, and grain composition. Further investigation of the lateral distribution of the ejecta deposit would provide information about the location, magnitude, and target rocks of the Australasian Tektite Event.
Compare the performance of multiple machine learning models in predicting tacrolimus concentration for infant patients with living donor liver transplantation
Authors: Song XueWu , Liu FangHao , Gao HuiEr , Yan MeiLing , Zhang FeiYu , Zhao Jia , Qin YinPeng , Li Yue , Zhang Yi 
Published: August 2022

AbstractBackgroundThis study aims to establish multiple ML models and compare their performance in predicting tacrolimus concentration for infant patients who received LDLT within 3 months after transplantation.MethodsRetrospectively collected basic information and relevant biochemical indicators of included infant patients. CMIA was used to determine tacrolimus C0. PCR was used to determine the donors' and recipients' CYP3A5 genotypes. Multivariate stepwise regression analysis and stepwise elimination covariates were used for covariates selection. Thirteen machine learning algorithms were applied for the development of prediction models. APE, the ratio of the APE ≤3 ng ml−1 and ideal rate (the proportion of the predicted value with a relative error of 30% or less) were used to evaluate the predictive performance of the model.ResultsA total of 163 infant patients were included in this study. In the case of the optimal combination of covariates, the Ridge model had the lowest APE, 2.01 (0.85, 3.35 ng ml−1). The highest ratio of the APE ≤3 ng ml−1 was the LAR model (71.77%). And the Ridge model showed the highest ideal rate (55.05%). For the Ridge model, GRWR was the most important predictor.ConclusionsCompared with other ML models, the Ridge model had good predictive performance and potential clinical application.
Micro‐morpho‐anatomical transitions at various stages of in vitro development of Crinum malabaricum Lekhak and Yadav: A critically endangered medicinal plant
Authors: Mani M. , Mathiyazhagan C. , Dey A. , Faisal M. , Alatar A. A. , Alok A. , Shekhawat M. S. 
Published: August 2022

Abstract

Crinum malabaricum Lekhak & Yadav is a recently discovered and critically endangered aquatic bulbous plant of the family Amaryllidaceae. It gained attention as a wild source of the acetylcholinesterase inhibiting alkaloid ‘galanthamine’ used to treat Alzheimer and Parkinson diseases. The bulbs of this plant contain the highest amount of galanthamine among Crinum species.

In vitro regeneration systems were developed to produce quality uniform plantlets of C. malabaricum. Bright field light microscopy was used to analyse micro‐morpho‐anatomical developments taking place in the leaves and roots during in vitro, ex vitro and in vivo transitions of plantlets.

Leaves and roots of plants raised in vitro possessed a higher degree of microscopic structural anomalies, such as underdeveloped epicuticular wax deposition, immature and non‐functional stomata, more aquiferous parenchyma with a reduced lumen. Roots developed in vitro were characterized by extremely large, uneven cortical cells and reduced intercellular spaces. The vascular tissues were under‐developed and only primary vascular tissues were observed. As a result of ex vitro acclimation, there was a significant acceleration in the improvement of tissue systems in leaves and roots. Such plantlets can tolerate elevated temperatures and light under in vivo conditions.

Thus, the microscopic evaluation of the structural trajectory in different stages of plantlet development provides an understanding of the acclimation process and structural adaptations, which could help enhance survival of in vitro raised plantlets under ex vitro and in vivo conditions.
External drivers of participation in regional collaborative water planning
Authors: Bell Emily V. , Fencl Amanda , Mullin Megan 
Published: August 2022

AbstractWhat drives participation in collaborative planning? How does this vary across different institutional contexts? Public managers must navigate emerging challenges in public service provision; perceived risk and capacity to act can play a pivotal role, shaping managerial behavior. In water management, for example, issues stemming from climate change and water‐intensive growth create new concerns about continued water supply. Strategic decisions may improve local public service provision, but can also have cascading effects on other systems, as water is a mobile—and subtractable—resource. Many public water systems have participated in collaborative planning to overcome collective challenges for this reason, but participation is not feasible for all prospective participants. Using data from administrative records and surveys, we fit a binomial logistic model to examine the roles of capacity and perceived risk among water service providers as drivers of participation in collaborative planning forums. By evaluating this relationship in California and North Carolina, we find similar results across unique institutional contexts: participation in regional water planning is associated with perceived risk to water supply from changing climatic conditions, but not from perceived risk of changing patterns of demand. Also, system capacity—as measured by the size of the population served—corresponds to increased likelihood of participation.
Moore′s paradox generalized
Authors: de Almeida Claudio 
Published: August 2022

AbstractMoore′s paradox came of age when John N. Williams gave us a simple paradoxical argument according to which the Moorean believer must hold false belief while believing contingent propositions. Simplicity was key; it was groundbreaking for the topic. On Williams′s account, given only the notions of inconsistency and self‐refutation, the thesis that belief distributes over conjunction, and a tiny bit of classical logic, we can derive a paradox from the Moorean propositional schemata. But, as argued here, it′s easy to overestimate the significance of his argument to a proper understanding of the problem. His fundamental claim can be established in a way that shows how the paradox arises for any propositional attitude that distributes over conjunction, which gives us the opportunity to reconsider the problem we have been calling “Moore′s paradox”, and to conclude that all of the available analyses of the problem are, at best, incomplete. On this new approach, we lose a little formal simplicity vis‐à‐vis Williams′s approach, but make conceptual economy, as we gain a farther‐reaching problem than the one we have known.
Energy-Optimal Impedance Control of Cooperative Robot Manipulators
Authors: Ghorbanpour Amin , Richter Hanz 
Published: August 2022

Abstract
An impedance-based control scheme is introduced for cooperative manipulators grasping a rigid object. The position and orientation of the payload are to be maintained close to the desired trajectory, trading off tracking accuracy by low energy consumption and maintaining stability. To this end, the augmented dynamics of the robots, their actuators, and the payload are formed, and an impedance control is adopted. A virtual control strategy is used to decouple torque control from actuator control. An optimization problem is then formulated using energy balance equations. The optimization finds the damping and stiffness gains of the impedance relation such that the energy consumption is minimized. Furthermore, L2 stability techniques are used to guarantee the stability of the controller. A numerical example is provided to demonstrate the results.
Machine-Learning Clustering Methods Applied to Detection of Noise Sources in Low-Speed Axial Fan
Authors: Tieghi Lorenzo , Becker Stefan , Corsini Alessandro , Delibra Giovanni , Schoder Stefan , Czwielong Felix 
Published: August 2022

Abstract
The integration of rotating machineries in human-populated environments requires to limit noise emissions, with multiple aspects impacting on control of amplitude and frequency of the acoustic signature. This is a key issue to address and when combined with compliance of minimum efficiency grades, further complicates the design of axial fans. The aim of this research is to assess the capability of unsupervised learning techniques in unveiling the mechanisms that concur to the sound generation process in axial fans starting from high-fidelity simulations. To this aim, a numerical dataset was generated by means of large Eddy simulation (LES) simulation of a low-speed axial fan. The dataset is enriched with sound source computed solving a-posteriori the perturbed convective wave equation (PCWE). First, the instantaneous flow features are associated with the sound sources through correlation matrices and then projected on latent basis to highlight the features with the highest importance. This analysis in also carried out on a reduced dataset, derived by considering two surfaces at 50% and 95% of the blade span. The sampled features on the surfaces are then exploited to train three cluster algorithms based on partitional, density and Gaussian criteria. The cluster algorithms are optimized and their results are compared, with the Gaussian Mixture one demonstrating the highest similarity (&gt;80%). The derived clusters are analyzed, and the role of statistical distribution of velocity and pressure gradients is underlined. This suggests that design choices that affect these aspects may be beneficial to control the generation of noise sources.
Withdrawal of inhaled corticosteroids from patients with COPD with mild or moderate airflow limitation in primary care: a feasibility randomised trial
Authors: Harries Timothy H , Gilworth Gill , Corrigan Christopher J , Murphy Patrick , Hart Nicholas , Thomas Mike , White Patrick T 
Published: August 2022

BackgroundInhaled corticosteroids (ICS) are frequently prescribed outside guidelines to patients with chronic obstructive pulmonary disease (COPD) with mild/moderate airflow limitation and low exacerbation risk. This primary care trial explored the feasibility of identifying patients with mild/moderate COPD taking ICS, and the acceptability of ICS withdrawal.MethodsOpen feasibility trial. Outcome measures included prevalence of suitable participants, feasibility of their identification, their willingness-to-accept open randomisation to ICS withdrawal or continuation over 6 months follow-up.Results392 (13%) of 2967 patients with COPD from 20 practices (209 618 population) identified as eligible for ICS withdrawal by electronic search algorithm. After individual patient record review, 243 (62%) were excluded because of: severe airflow limitation (65, 17%); one or more severe or two or more moderate COPD exacerbations in the previous year (86, 22%); asthma (15, 4%); and severe comorbidities (77, 20%). After exclusion, 149 patients with COPD were invited to participate and 61 agreed to randomisation. At clinical assessment, 10 patients exhibited undocumented airflow reversibility (forced expiratory volume in 1 s (FEV1) reversibility >12% and >200 mL); 2 had suffered two or more undocumented, moderate exacerbations in the previous year; 7 had severe airflow limitation; and 2 had normal spirometry. Finally, 40 were randomised. One patient died and one was lost to follow-up. 18 (45%) of the 38 (10 withdrawal and 8 usual care) exhibited previously undocumented FEV1variability suggestive of asthma, supported in the withdrawal group by significant associations with elevated fractional exhaled nitric oxide (p=0.04), elevated symptom score (p=0.04), poorer quality of life (p=0.04) and atopic status (p=0.01).ConclusionsIdentifying primary care patients with mild/moderate COPD suitable for ICS withdrawal is feasible but requires real-time verification because of unreliable recording of exacerbations and lung function. Suitable patients accepted randomisation to ICS withdrawal or continuation for the purposes of future studies. Follow-up compliance was high. Nearly 50% of participants with a diagnosis of mild/moderate COPD demonstrated previously undocumented FEV1variability during follow-up, mandating monitoring for at least 6 months following withdrawal to exclude undiagnosed asthma.
The spectrum of Hawking radiation in Tsallis statistical mechanics
Authors: Liu Yang 
Published: August 2022

AbstractHawking radiation is one of the cores in modern gravitational theory. Several articles have calculated the spectrum of Hawking radiation in Boltzmann–Gibbs statistical mechanics. However, based on recent researches, gravitational systems cannot be studied by the standard statistical mechanics. In this article, we calculate the modification to the spectrum of Hawking radiation in Tsallis statistical mechanics. We obtain the modified Stefan–Boltzmann’s law and modified power of Hawking radiation. We confirm the conclusion proposed by Giddings, namely, the radiation should originate from the effective radius, which extends well outside the horizon of black-hole. The lifetime of black hole and the effect of large q are discussed as well.
Optimal Modeling of Anti-Breast Cancer Candidate Drugs Based on Graph Model Feature Selection
Authors: Chen Rongyuan , He Zhixiong , Huang Shaonian , Shen Lizhi , Zhou Xiancheng 
Published: August 2022

Breast cancer is one of the most widespread and fatal cancers in women. At present, anticancer drug-inhibiting estrogen receptor

α

subtype (ER

α

) can greatly improve the cure rate for breast cancer patients, so the research and development of this kind of drugs are very urgent. In this paper, the problem of how to screen excellent anticancer drugs is abstracted as an optimization problem. Firstly, the graph model is used to extract low-dimensional features with strong distinguishing and describing ability according to various attributes of candidate compounds, and then, kernel functions are used to map these features to high-dimensional space. Then, the quantitative analysis model of ER

α

biological activity and the classification model based on ADMET properties of the support vector machine are constructed. Finally, sequential least square programming (SLSQP) is utilized to solve the ER

α

biological activity model. The experimental results show that for anticancer data sets, compared with principal component analysis (PCA), the error rate of the graph model constructed in this paper is reduced by 6.4%, 15%, and 7.8% on mean absolute error (MAE), mean squared error (MSE), and root mean square error (RMSE), respectively. In terms of classification prediction, compared with principal component analysis (PCA), the recall and precision rates of this method are enhanced by 19.5% and 12.41%, respectively. Finally, the optimal biological activity value (IC50_nM) 34.6 and inhibitory biological activity value (pIC50) 7.46 were obtained.
High-Resolution Profiling of Lung Adenocarcinoma Identifies Expression Subtypes with Specific Biomarkers and Clinically Relevant Vulnerabilities
Authors: Roh Whijae , Geffen Yifat , Cha Hongui , Miller Mendy , Anand Shankara , Kim Jaegil , Heiman David I. , Gainor Justin F. , Laird Peter W. , Cherniack Andrew D. , Ock Chan-Young , Lee Se-Hoon , Getz Gad ,   for the National Cancer Institute Center for Cancer Genomics Tumor Molecular Pathology (TMP) Analysis Working Group
Published: August 2022

Abstract

Lung adenocarcinoma (LUAD) is one of the most common cancer types and has various treatment options. Better biomarkers to predict therapeutic response are needed to guide choice of treatment modality and to improve precision medicine. Here, we used a consensus hierarchical clustering approach on 509 LUAD cases from The Cancer Genome Atlas to identify five robust LUAD expression subtypes. Genomic and proteomic data from patient samples and cell lines was then integrated to help define biomarkers of response to targeted therapies and immunotherapies. This approach defined subtypes with unique proteogenomic and dependency profiles. Subtype 4 (S4)–associated cell lines exhibited specific vulnerability to loss of CDK6 and CDK6-cyclin D3 complex gene (CCND3). Subtype 3 (S3) was characterized by dependency on CDK4, immune-related expression patterns, and altered MET signaling. Experimental validation showed that S3-associated cell lines responded to MET inhibitors, leading to increased expression of programmed death-ligand 1 (PD-L1). In an independent real-world patient dataset, patients with S3 tumors were enriched with responders to immune checkpoint blockade. Genomic features in S3 and S4 were further identified as biomarkers for enabling clinical diagnosis of these subtypes. Overall, our consensus hierarchical clustering approach identified robust tumor expression subtypes, and our subsequent integrative analysis of genomics, proteomics, and CRISPR screening data revealed subtype-specific biology and vulnerabilities. These LUAD expression subtypes and their biomarkers could help identify patients likely to respond to CDK4/6, MET, or PD-L1 inhibitors, potentially improving patient outcome.

Significance:
Integrative analysis of multiomic and drug dependency data uncovers robust lung adenocarcinoma expression subtypes with unique therapeutic vulnerabilities and subtype-specific biomarkers of response.
Clinico-genomic Characterization ofATMand HRD in Pancreas Cancer: Application for Practice
Authors: Park Wungki , O'Connor Catherine A. , Bandlamudi Chaitanya , Forman Daniella , Chou Joanne F. , Umeda Shigeaki , Reyngold Marsha , Varghese Anna M. , Keane Fergus , Balogun Fiyinfolu , Yu Kenneth H. , Kelsen David P. , Crane Christopher , Capanu Marinela , Iacobuzio-Donahue Christine , O'Reilly Eileen M. 
Published: August 2022

AbstractPurpose:Characterizing germline and somatic ATM variants (gATMm, sATMm) zygosity and their contribution to homologous recombination deficiency (HRD) is important for therapeutic strategy in pancreatic ductal adenocarcinoma (PDAC).Experimental Design:Clinico-genomic data for patients with PDAC and other cancers with ATM variants were abstracted. Genomic instability scores (GIS) were derived from ATM-mutant cancers and overall survival (OS) was evaluated.Results:Forty-six patients had PDAC and pathogenic ATM variants including 24 (52%) stage III/IV: gATMm (N = 24), and sATMm (N = 22). Twenty-seven (59%) had biallelic, 15 (33%) monoallelic, and 4 indeterminate (8%) variants. Median OS for advanced-stage cohort at diagnosis (N = 24) was 19.7 months [95% confidence interval (CI): 12.3–not reached (NR)], 27.1 months (95% CI: 22.7–NR) for gATMm (n = 11), and 12.3 months for sATMm (n = 13; 95% CI: 11.9–NR; P = 0.025). GIS was computed for 33 patients with PDAC and compared with other ATM-mutant cancers enriched for HRD. The median was lower (median, 11; range, 2–29) relative to breast (18, 3–55) or ovarian (25, 3–56) ATM-mutant cancers (P &lt; 0.001 and P = 0.003, respectively). Interestingly, biallelic pathogenic ATM variants were mutually exclusive with TP53. Other canonical driver gene (KRAS, CDKN2A, SMAD4) variants were less frequent in ATM-mutant PDAC.Conclusions:ATM variants in PDAC represent a distinct biologic group and appear to have favorable OS. Nonetheless, pathogenic ATM variants do not confer an HRD signature in PDAC and ATM should be considered as a non-core HR gene in this disease.
Vaivém Histórico
Authors: Baniwa Denilson 
Published: August 2022

A invenção da tradição brasileira tem na sua raiz o apagamento de memórias ancestrais a este território também inventado.O que somos hoje é um juntado de recortes e refilamentos ao longo dos anos, em que apenas o que servia como escada para oprogresso fora aproveitado. Quanto àqueles que não se comportavam dentro da panela colonizadora, eram lançados à margem para que perecessem, sem luzes ou olhos que os notassem. Esquecimento era a pena a ser cumprida por não caberem nas retificações do “País do Futuro”. Hoje, como a volta da maré que pega alguns muitos de surpresa, corpos que haviam sido esquecidos voltam e afogam a História do Brasil. Um requerimento de luz sobre as ruínas. Vozes roucas de tanto gritar do lado de fora hoje assaltam a mesa grande, desta vez não atrás de farelos que caem das mãos gordas de quem se lambuzava há éculos, mas atrás da coxa do porco europeu trazido por Cristóvão Colombo, ou do próprio europeu, se for o caso. Rescrever a história é raspar escórias e cracas agarradas do imaginário colonizatório e, a partir daí, sobrepor camadas de urucum, argila, jenipapo, carvão, crajiru e memórias daqueles que viraram alienígenas do progresso.