bluuebunny/crossref_metadata_2025_split huggingface dataset:
Low-dissipation model of three-terminal refrigerator: performance bounds and comparative analyses
Authors: Li Zhexu , Gonzalez-Ayala Julian , Yang Hanxin , Guo Juncheng , Calvo Hernández A 
Published: January 2022

Abstract
In the present paper, a general non-combined model of three-terminal refrigerator beyond specific heat transfer mechanisms is established based on the low-dissipation assumption. The relation between the optimized cooling power and the corresponding coefficient of performance (COP) is analytically derived, according to which the COP at maximum cooling power (CMP) can be further determined. At two dissipation asymmetry limits, upper and lower bounds of CMP are obtained and found to be in good agreement with experimental and simulated results. Additionally, comparison of the obtained bounds with previous combined model is presented. In particular it is found that the upper bounds are the same, whereas the lower bounds are quite different. This feature indicates that the claimed universal equivalence for the combined and non-combined models under endoreversible assumption is invalid within the frame of low-dissipation assumption. Then, the equivalence between various finite-time thermodynamic models needs to be reevaluated regarding multi-terminal systems. Moreover, the correlation between the combined and non-combined models is further revealed by the derivation of the equivalent condition according to which the identical upper bounds and distinct lower bounds are theoretically shown. Finally, the proposed non-combined model is proved to be the appropriate model for describing various types of thermally driven refrigerator. This work may provide some instructive information for the further establishments and performance analyses of multi-terminal low-dissipation models.
Toward accurate diagnosis and surveillance of bacterial infections using enhanced strain-level metagenomic next-generation sequencing of infected body fluids
Authors: Ruan Zhi , Zou Shengmei , Wang Zeyu , Zhang Luhan , Chen Hangfei , Wu Yuye , Jia Huiqiong , Draz Mohamed S , Feng Ye 
Published: January 2022

Abstract
Metagenomic next-generation sequencing (mNGS) enables comprehensive pathogen detection and has become increasingly popular in clinical diagnosis. The distinct pathogenic traits between strains require mNGS to achieve a strain-level resolution, but an equivocal concept of ‘strain’ as well as the low pathogen loads in most clinical specimens hinders such strain awareness. Here we introduce a metagenomic intra-species typing (MIST) tool (https://github.com/pandafengye/MIST), which hierarchically organizes reference genomes based on average nucleotide identity (ANI) and performs maximum likelihood estimation to infer the strain-level compositional abundance. In silico analysis using synthetic datasets showed that MIST accurately predicted the strain composition at a 99.9% average nucleotide identity (ANI) resolution with a merely 0.001× sequencing depth. When applying MIST on 359 culture-positive and 359 culture-negative real-world specimens of infected body fluids, we found the presence of multiple-strain reached considerable frequencies (30.39%–93.22%), which were otherwise underestimated by current diagnostic techniques due to their limited resolution. Several high-risk clones were identified to be prevalent across samples, including Acinetobacter baumannii sequence type (ST)208/ST195, Staphylococcus aureus ST22/ST398 and Klebsiella pneumoniae ST11/ST15, indicating potential outbreak events occurring in the clinical settings. Interestingly, contaminations caused by the engineered Escherichia coli strain K-12 and BL21 throughout the mNGS datasets were also identified by MIST instead of the statistical decontamination approach. Our study systemically characterized the infected body fluids at the strain level for the first time. Extension of mNGS testing to the strain level can greatly benefit clinical diagnosis of bacterial infections, including the identification of multi-strain infection, decontamination and infection control surveillance.
Considerations for the implementation of machine learning into acute care settings
Authors: Bishara Andrew , Maze Elijah H , Maze Mervyn 
Published: January 2022

AbstractIntroductionManagement of patients in the acute care setting requires accurate diagnosis and rapid initiation of validated treatments; therefore, this setting is likely to be an environment in which cognitive augmentation of the clinician’s provision of care with technology rooted in artificial intelligence, such as machine learning (ML), is likely to eventuate.Sources of dataPubMed and Google Scholar with search terms that included ML, intensive/critical care unit, electronic health records (EHR), anesthesia information management systems and clinical decision support were the primary sources for this report.Areas of agreementDifferent categories of learning of large clinical datasets, often contained in EHRs, are used for training in ML. Supervised learning uses algorithm-based models, including support vector machines, to pair patients’ attributes with an expected outcome. Unsupervised learning uses clustering algorithms to define to which disease grouping a patient’s attributes most closely approximates. Reinforcement learning algorithms use ongoing environmental feedback to deterministically pursue likely patient outcome.Areas of controversyApplication of ML can result in undesirable outcomes over concerns related to fairness, transparency, privacy and accountability. Whether these ML technologies irrevocably change the healthcare workforce remains unresolved.Growing pointsWell-resourced Learning Health Systems are likely to exploit ML technology to gain the fullest benefits for their patients. How these clinical advantages can be extended to patients in health systems that are neither well-endowed, nor have the necessary data gathering technologies, needs to be urgently addressed to avoid further disparities in healthcare.
Techno–economic–environmental feasibility study of a photovoltaic system in northern part of Iran including a two-stage multi-string inverter with DC–DC ZETA converter and a modified P&O algorithm
Authors: Semeskandeh Sina , Hojjat Mehrdad , Hosseini Abardeh Mohamad 
Published: January 2022

Abstract
Inverters play a significant role in the configuration of grid-connected photovoltaic (PV) systems. The perturb-and-observe (P&O) algorithm is a common method to derive the maximum power from grid-connected inverters; however, the possibility of losing maximum power due to sudden changes in radiation is a significant drawback of this control strategy. To overcome this barrier, the two-stage multi-string inverter using the ZETA DC–DC converter and a novel P&O algorithm has been proposed to increase the efficiency of these systems. The proposed inverter has been simulated in MATLAB/SIMULINK software. To investigate the performance of the proposed inverter, technical, environmental and economic feasibility studies have been performed for the construction of a 5-kW PV power plant in a northern city of Iran (Sari) using the RETScreen software developed by Natural Resources Canada. On the other hand, most feasibility studies for power-plant construction are based on the concept of inverter peak efficiency, which leads to non-optimal system design due to the short operation duration of the inverter at this value. However, the weighted European efficiency has been used in the feasibility study for more accurate computations. Moreover, the performance of the proposed inverter is compared to that of a two-stage multi-string inverter using a conventional P&O algorithm and the single-stage (central) inverter. The simulation results indicated that the proposed inverter injects 7.6 MW of power into the grid per year. Moreover, it prevents the emission of 88 tons of CO2 (over 20 years), which is equivalent to saving 1883.5 litres of gasoline per year.
The life cycle-dependent transcriptional profile of the obligate intracellular amoeba symbiontAmoebophilus asiaticus
Authors: Selberherr E , Penz T , König L , Conrady B , Siegl A , Horn M , Schmitz-Esser S 
Published: January 2022

AbstractFree-living amoebae often harbor obligate intracellular bacterial symbionts. Amoebophilus (A.) asiaticus is a representative of a lineage of amoeba symbionts in the phylum Bacteroidota. Here, we analyse the transcriptome of A. asiaticus strain 5a2 at four time points during its infection cycle and replication within the Acanthamoeba host using RNA sequencing. Our results reveal a dynamic transcriptional landscape throughout different A. asiaticus life cycle stages. Many intracellular bacteria and pathogens utilize eukaryotic-like proteins (ELPs) for host cell interaction and the A. asiaticus 5a2 genome shows a particularly high abundance of ELPs. We show the expression of all genes encoding ELPs and found many ELPs to be differentially expressed. At the replicative stage of A. asiaticus, ankyrin repeat proteins and tetratricopeptide/Sel1-like repeat proteins were upregulated. At the later time points, high expression levels of a type 6 secretion system that likely prepares for a new infection cycle after lysing its host, were found. This study reveals comprehensive insights into the intracellular lifestyle of A. asiaticus and highlights candidate genes for host cell interaction. The results from this study have implications for other intracellular bacteria such as other amoeba-associated bacteria and the arthropod symbionts Cardinium forming the sister lineage of A. asiaticus.
Close-kin mark–recapture abundance estimation: practical insights and lessons learned
Authors: Trenkel Verena M , Charrier Grégory , Lorance Pascal , Bravington Mark V 
Published: January 2022

Abstract
We present practical lessons learned from applying the recent close-kin mark–recapture (CKMR) abundance estimation method to thornback ray (Raja clavata). For CKMR, related individuals are identified from their genotypes and their number and pattern is used for abundance estimation. We genotyped over 7000 individuals collected in the Bay of Biscay using Single Nucleotide Polymorphism (SNP) markers finding 99 parent–offspring pairs. The estimated number of adult thornback rays in the central Bay of Biscay was around 135000 (CV 0.19) in 2013. In total, four lessons were drawn: (i) CKMR helps identifying metapopulation structure, which if ignored might affect abundance estimates and/or time trends. There was strong evidence for two distinct local populations of thornback ray with no demographic connectivity. (ii) Demographic sample composition can affect precision and needs to include a range of birth years, which turned out to be difficult for thornback ray. (iii) Reasonable age information for potential offspring is essential. (iv) The sex of potential parents is needed and might be identified from sex-related SNPs. Reliable abundance estimation by CKMR appears feasible for a wide range of species provided that: sampling adequately covers potential local population structure, has appropriate demographic composition, and the age of potential offspring is reasonably well-known.
Phenotypic resistance to lenacapavir and monotherapy efficacy in a proof-of-concept clinical study
Authors: Margot Nicolas , Vanderveen Laurie , Naik Vidula , Ram Renee , Parvangada PC , Martin Ross , Rhee Martin , Callebaut Christian 
Published: January 2022

Abstract

Background
Lenacapavir in vitro resistance selections identified seven mutations in HIV-1 capsid protein (CA) associated with reduced susceptibility.

Objectives
To analyse lenacapavir activity against lenacapavir-associated resistance mutations in multiple assays. We also report Day 10 resistance analyses conducted in a Phase 1b study of lenacapavir (Study 4072) in people with HIV (PWH).

Methods
Mutations were inserted in a proviral DNA clone by site-directed mutagenesis, and viruses (n = 12) were generated by transfection. Sequences were used to generate single-cycle (SC) test vectors that were evaluated in a Gag-Pro assay, and replicative viruses were tested in a multicycle (MC) MT-2 assay to determine lenacapavir susceptibility. Study 4072 was a Phase 1b, double-blinded, placebo-controlled, dose-ranging, randomized study of lenacapavir in untreated PWH. Participants received a single dose of lenacapavir (up to 750 mg) or placebo (10 day monotherapy). CA resistance was characterized using genotypic and/or phenotypic assays.

Results
Lenacapavir susceptibility in the SC assay showed an inverse relationship between replication capacity and resistance. In Study 4072, all 29 participants receiving lenacapavir showed a robust virological response with no rebound. At baseline, no participant had resistance mutations to lenacapavir, and all had WT susceptibility to lenacapavir. Post-monotherapy analyses revealed the emergence of CA mutation Q67H at Day 10 in two participants.

Conclusions
In vitro assays confirmed that increased resistance to lenacapavir was associated with decreased replication capacity of mutant viruses. In the clinical study no pre-existing lenacapavir resistance was detected. Emergence of Q67H occurred at exposures below the dose used in current Phase 2/3 studies. These results support development of lenacapavir as an antiretroviral agent.
Comparative Greenness Metric Estimates for Content Uniformity Testing of Anti-Cov-2, GS-5734 in Commercial Vials: Validated Micellar Electrokinetic Chromatographic Assay
Authors: Elonsy Sohila M , Kamal Miranda F , Hamdy Mohamed M A , Abdel Moneim Mona M 
Published: January 2022

Abstract

Background
The antiviral drug GS-5734 remdesivir is a new phosphoramidate prodrug developed initially as a treatment for Ebola virus which then proved to have antiviral properties against other viruses. After clinical trials, it was the first antiviral to be approved by the U.S. Food and Drug Administration in 2020 to treat severe coronavirus (COVID-19) cases. The widespread current pandemic gave an urge to its fast production and marketing. Thus, new analytical methods must be available for its analysis in a fast and easy manner with low cost to be applicable in all laboratories.

Objective
In the current study, a green and economic micellar electrokinetic chromatographic (MEKC) method is proposed for remdesivir analysis.

Methods
A fused-silica capillary (58.5 cm × 50 μm id, 50 cm effective length) with 20 mM borate buffer (pH 9) and 25 mM sodium dodecyl sulfate was used under a positive potential of 30 kV at 25°C with detection at 245 nm.

Results
Remdesivir analysis was achieved in approximately 5 min. The method proved to be linear in range of 1–50 μg/mL with correlation coefficient, r &gt; 0.999.

Conclusion
The MEKC method proposed was applied to the analysis of remdesivir in its commercial vials. The method was validated per International Conference on Harmonization guidelines.

Highlights
Green chemistry has been the focus of the analytical community in the past few years. This method is considered green due to its low energy and solvent consumption without sacrificing the method’s sensitivity or selectivity. The method’s green profile has been assessed by different greenness assessment scales to ensure the method is eco-friendly and can be used in the pharmaceutical industry.
Context-Dependent Viral Transgenerational Immune Priming in Honey Bees (Hymenoptera: Apidae)
Authors: Lang Sarah , Simone-Finstrom Michael , Healy Kristen 
Published: January 2022

Abstract
Transgenerational immune priming is the process of increased resistance to infection in offspring due to parental pathogen exposure. Honey bees (Apis mellifera L. (Hymenoptera: Apidae)) are hosts to multiple pathogens, and this complex immune function could help protect against overwhelming infection. Honey bees have demonstrated transgenerational immune priming for the bacterial pathogen Paenibacillus larvae; however, evidence for viral transgenerational immune priming is lacking across insects in general. Here we test for the presence of transgenerational immune priming in honey bees with Deformed wing virus (DWV) by injecting pupae from DWV-exposed queens and measuring virus titer and immune gene expression. Our data suggest that there is evidence for viral transgenerational immune priming in honey bees, but it is highly context-dependent based on route of maternal exposure and potentially host genetics or epigenetic factors.
Local control of stereotactic body radiotherapy with dynamic tumor tracking for lung tumors: a propensity score-matched analysis
Authors: Machitori Yumiko , Ito Kei , Kito Satoshi , Nakajima Yujiro , Saito Makoto , Karasawa Katsuyuki 
Published: January 2022

Abstract

Background
Dynamic tumor tracking (DTT) is a method of respiratory motion management in radiotherapy. It reduces the radiation field but risks delivering an insufficient radiation dose to the tumor. We investigated the local control of DTT-stereotactic body radiotherapy (SBRT) for lung tumors.

Methods
Patients treated with SBRT for early-stage, non-small-cell lung cancer and lung metastases (2013–18) were retrospectively reviewed. Patients with tumor motion &gt;1 cm were treated with DTT-SBRT (DTT group); those with tumor motion ≤1 cm were treated with static-SBRT (static group). A static planning target volume for the static-SBRT plan was also created for patients in the DTT group, and planning target volume reduction relative to the planning target volume for the DTT-SBRT plan was assessed. Patients were matched in a 1:1 ratio using a propensity score predictive of the SBRT technique.

Results
Of the 245 lesions in 218 patients (median follow-up, 25.4 months), 69 were treated with DTT-SBRT and 176 with static-SBRT. The median planning target volume reduction in the DTT group was 30.3%. After propensity score matching, 124 lesions were included (62 per group). Two-year local control rates for the DTT and static groups were 94.2 and 95.9%, respectively, for all lesions (P = 0.19) and 96.3 and 94.5%, respectively, for matched lesions (P = 0.79). In univariate analysis, DTT-SBRT was not associated with local control for all lesions (hazard ratio, 2.06; P = 0.20) or matched lesions (hazard ratio, 1.22; P = 0.79). No grade 4/5 toxicities were observed.

Conclusions
DTT-SBRT for lung tumors reduced the planning target volume, but not local control rates. DTT was useful for respiratory motion management.
Advances in Deep Neuropathological Phenotyping of Alzheimer Disease: Past, Present, and Future
Authors: Shakir Mustafa N , Dugger Brittany N 
Published: January 2022

Abstract
Alzheimer disease (AD) is a neurodegenerative disorder characterized pathologically by the presence of neurofibrillary tangles and amyloid beta (Aβ) plaques in the brain. The disease was first described in 1906 by Alois Alzheimer, and since then, there have been many advancements in technologies that have aided in unlocking the secrets of this devastating disease. Such advancements include improving microscopy and staining techniques, refining diagnostic criteria for the disease, and increased appreciation for disease heterogeneity both in neuroanatomic location of abnormalities as well as overlap with other brain diseases; for example, Lewy body disease and vascular dementia. Despite numerous advancements, there is still much to achieve as there is not a cure for AD and postmortem histological analyses is still the gold standard for appreciating AD neuropathologic changes. Recent technological advances such as in-vivo biomarkers and machine learning algorithms permit great strides in disease understanding, and pave the way for potential new therapies and precision medicine approaches. Here, we review the history of human AD neuropathology research to include the notable advancements in understanding common co-pathologies in the setting of AD, and microscopy and staining methods. We also discuss future approaches with a specific focus on deep phenotyping using machine learning.
The Impact of COVID-19 Among Black Girls: A Social-Ecological Perspective
Authors: Crooks Natasha , Sosina Wuraola , Debra Alyssa , Donenberg Geri 
Published: January 2022

Abstract

Objective
To explore the impact of the COVID-19 pandemic on Black adolescent girls’ physical, psychological, and sexual development.

Methods
Semistructured interviews were conducted with 25 girls (9–18 years old) primarily across the Midwestern United States. Interviews were conducted until theoretical saturation was reached. We conducted a conventional content analysis by reviewing transcripts, coding data, and developing themes.

Results
Utilizing the social-ecological model findings revealed themes related to the individual-, interpersonal-, institutional-, and community-level changes that Black girls experienced during the COVID-19 pandemic.

Conclusions
Black adolescent girls need opportunities to discuss the changes, receive relevant resources, and have spaces to support their physical, psychological, and sexual development. Systems such as families, schools, and clinics should implement programming to facilitate discussions around the impact of COVID-19 on Black girls.
Supernova siblings and their parent galaxies in the Zwicky Transient Facility Bright Transient Survey
Authors: Graham Melissa L , Fremling Christoffer , Perley Daniel A , Biswas Rahul , Phillips Christopher A , Sollerman Jesper , Nugent Peter E , Nance Sarafina , Dhawan Suhail , Nordin Jakob , Goobar Ariel , Miller Adam , Neill James D , Hall Xander J , Hankins Matthew J , Duev Dmitry A , Kasliwal Mansi M , Rigault Mickael , Bellm Eric C , Hale David , Mróz Przemek , Kulkarni S R 
Published: January 2022

ABSTRACT
Supernova (SN) siblings – two or more SNe in the same parent galaxy – are useful tools for exploring progenitor stellar populations as well as properties of the host galaxies such as distance, star-formation rate, dust extinction, and metallicity. Since the average SN rate for a Milky Way-type galaxy is just one per century, a large imaging survey is required to discover an appreciable sample of SN siblings. From the wide-field Zwicky Transient Facility (ZTF) Bright Transient Survey (which aims for spectroscopic completeness for all transients which peak brighter than r &lt; 18.5 mag) we present 10 SN siblings in five parent galaxies. For each of these families, we analyse the SN’s location within the host and its underlying stellar population, finding agreement with expectations that SNe from more massive progenitors are found nearer to their host core and in regions of more active star formation. We also present an analysis of the relative rates of core collapse and thermonuclear SN siblings, finding a significantly lower ratio than past SN sibling samples due to the unbiased nature of the ZTF.