bluuebunny/crossref_metadata_2025_split huggingface dataset:
Abundant and cosmopolitan lineage of cyanopodoviruses lacking a DNA polymerase gene
Authors: Cai Lanlan , Chen Yue , Xiao Shiwei , Liu Riyue , He Maoqiu , Zhang Rui , Zeng Qinglu 
Published: November 2022

Abstract
Cyanopodoviruses affect the mortality and population dynamics of the unicellular picocyanobacteria Prochlorococcus and Synechococcus, the dominant primary producers in the oceans. Known cyanopodoviruses all contain the DNA polymerase gene (DNA pol) that is important for phage DNA replication and widely used in field quantification and diversity studies. However, we isolated 18 cyanopodoviruses without identifiable DNA pol. They form a new MPP-C clade that was separated from the existing MPP-A, MPP-B, and P-RSP2 clades. The MPP-C phages have the smallest genomes (37.3–37.9 kb) among sequenced cyanophages, and show longer latent periods than the MPP-B phages. Metagenomic reads of both clades are highly abundant in surface waters, but the MPP-C phages show higher relative abundance in surface waters than in deeper waters, while MPP-B phages have higher relative abundance in deeper waters. Our study reveals that cyanophages with distinct genomic contents and infection kinetics can exhibit different depth profiles in the oceans.
Stretchable π-conjugated polymer electrets for mechanoelectric generators
Authors: Shinohara Akira , Yoshida Manabu , Pan Chengjun , Nakanishi Takashi 
Published: November 2022

AbstractElectrets are materials that retain quasi-permanent electric charges and are attracting attention as key components of batteryless micropower supplies. A chemical structure that facilitates ionization and that can stabilize these charges, such as a π-conjugated system, is expected to increase the charge density compared with that of conventional insulating polymers. Here, we report a mechanoelectric generator (MEG) (vibrational energy harvester) that uses alkylated π-conjugated polymers (Alk-CPs), which can be monopolarized either into positive or negative mode electrets. With the attachment of insulating, bulky, yet flexible alkyl side chains to the π-conjugated backbone, the poled Alk-CPs showed long charge lifetime suitable for MEGs. The elastic modulus of the electret was adjusted to approximately match that of the stretchable polyurethane substrate by blending two miscible Alk-CPs with different elastic moduli, producing a laminated film that could be stretched up to 300%. The MEG presented showed conformability when applied to a deformable object.
Gradual differentiation uncoupled from cell cycle exit generates heterogeneity in the epidermal stem cell layer
Authors: Cockburn Katie , Annusver Karl , Gonzalez David G. , Ganesan Smirthy , May Dennis P. , Mesa Kailin R. , Kawaguchi Kyogo , Kasper Maria , Greco Valentina 
Published: November 2022

AbstractHighly regenerative tissues continuously produce terminally differentiated cells to replace those that are lost. How they orchestrate the complex transition from undifferentiated stem cells towards post-mitotic, molecularly distinct and often spatially segregated differentiated populations is not well understood. In the adult skin epidermis, the stem cell compartment contains molecularly heterogeneous subpopulations1–4 whose relationship to the complete trajectory of differentiation remains unknown. Here we show that differentiation, from commitment to exit from the stem cell layer, is a multi-day process wherein cells transit through a continuum of transcriptional changes with upregulation of differentiation genes preceding downregulation of typical stemness genes. Differentiation-committed cells remain capable of dividing to produce daughter cells fated to further differentiate, demonstrating that differentiation is uncoupled from cell cycle exit. These cell divisions are not required as part of an obligate transit-amplifying programme but help to buffer the differentiating cell pool during heightened demand. Thus, instead of distinct contributions from multiple progenitors, a continuous gradual differentiation process fuels homeostatic epidermal turnover.
Non-viral precision T cell receptor replacement for personalized cell therapy
Authors: Foy Susan P. , Jacoby Kyle , Bota Daniela A. , Hunter Theresa , Pan Zheng , Stawiski Eric , Ma Yan , Lu William , Peng Songming , Wang Clifford L. , Yuen Benjamin , Dalmas Olivier , Heeringa Katharine , Sennino Barbara , Conroy Andy , Bethune Michael T. , Mende Ines , White William , Kukreja Monica , Gunturu Swetha , Humphrey Emily , Hussaini Adeel , An Duo , Litterman Adam J. , Quach Boi Bryant , Ng Alphonsus H. C. , Lu Yue , Smith Chad , Campbell Katie M. , Anaya Daniel , Skrdlant Lindsey , Huang Eva Yi-Hsuan , Mendoza Ventura , Mathur Jyoti , Dengler Luke , Purandare Bhamini , Moot Robert , Yi Michael C. , Funke Roel , Sibley Alison , Stallings-Schmitt Todd , Oh David Y. , Chmielowski Bartosz , Abedi Mehrdad , Yuan Yuan , Sosman Jeffrey A. , Lee Sylvia M. , Schoenfeld Adam J. , Baltimore David , Heath James R. , Franzusoff Alex , Ribas Antoni , Rao Arati V. , Mandl Stefanie J. 
Published: November 2022

AbstractT cell receptors (TCRs) enable T cells to specifically recognize mutations in cancer cells1–3. Here we developed a clinical-grade approach based on CRISPR–Cas9 non-viral precision genome-editing to simultaneously knockout the two endogenous TCR genes TRAC (which encodes TCRα) and TRBC (which encodes TCRβ). We also inserted into the TRAC locus two chains of a neoantigen-specific TCR (neoTCR) isolated from circulating T cells of patients. The neoTCRs were isolated using a personalized library of soluble predicted neoantigen–HLA capture reagents. Sixteen patients with different refractory solid cancers received up to three distinct neoTCR transgenic cell products. Each product expressed a patient-specific neoTCR and was administered in a cell-dose-escalation, first-in-human phase I clinical trial (NCT03970382). One patient had grade 1 cytokine release syndrome and one patient had grade 3 encephalitis. All participants had the expected side effects from the lymphodepleting chemotherapy. Five patients had stable disease and the other eleven had disease progression as the best response on the therapy. neoTCR transgenic T cells were detected in tumour biopsy samples after infusion at frequencies higher than the native TCRs before infusion. This study demonstrates the feasibility of isolating and cloning multiple TCRs that recognize mutational neoantigens. Moreover, simultaneous knockout of the endogenous TCR and knock-in of neoTCRs using single-step, non-viral precision genome-editing are achieved. The manufacture of neoTCR engineered T cells at clinical grade, the safety of infusing up to three gene-edited neoTCR T cell products and the ability of the transgenic T cells to traffic to the tumours of patients are also demonstrated.
An engineered T7 RNA polymerase that produces mRNA free of immunostimulatory byproducts
Authors: Dousis Athanasios , Ravichandran Kanchana , Hobert Elissa M. , Moore Melissa J. , Rabideau Amy E. 
Published: November 2022

AbstractIn vitro transcription (IVT) is a DNA-templated process for synthesizing long RNA transcripts, including messenger RNA (mRNA). For many research and commercial applications, IVT of mRNA is typically performed using bacteriophage T7 RNA polymerase (T7 RNAP) owing to its ability to produce full-length RNA transcripts with high fidelity; however, T7 RNAP can also produce immunostimulatory byproducts such as double-stranded RNA that can affect protein expression. Such byproducts require complex purification processes, using methods such as reversed-phase high-performance liquid chromatography, to yield safe and effective mRNA-based medicines. To minimize the need for downstream purification processes, we rationally and computationally engineered a double mutant of T7 RNAP that produces substantially less immunostimulatory RNA during IVT compared with wild-type T7 RNAP. The resulting mutant allows for a simplified production process with similar mRNA potency, lower immunostimulatory content and quicker manufacturing time compared with wild-type T7 RNAP. Herein, we describe the computational design and development of this improved T7 RNAP variant.
Amyloid and tau PET-positive cognitively unimpaired individuals are at high risk for future cognitive decline
Authors: Ossenkoppele Rik , Pichet Binette Alexa , Groot Colin , Smith Ruben , Strandberg Olof , Palmqvist Sebastian , Stomrud Erik , Tideman Pontus , Ohlsson Tomas , Jögi Jonas , Johnson Keith , Sperling Reisa , Dore Vincent , Masters Colin L. , Rowe Christopher , Visser Denise , van Berckel Bart N. M. , van der Flier Wiesje M. , Baker Suzanne , Jagust William J. , Wiste Heather J. , Petersen Ronald C. , Jack Clifford R. , Hansson Oskar 
Published: November 2022

AbstractA major unanswered question in the dementia field is whether cognitively unimpaired individuals who harbor both Alzheimer’s disease neuropathological hallmarks (that is, amyloid-β plaques and tau neurofibrillary tangles) can preserve their cognition over time or are destined to decline. In this large multicenter amyloid and tau positron emission tomography (PET) study (n = 1,325), we examined the risk for future progression to mild cognitive impairment and the rate of cognitive decline over time among cognitively unimpaired individuals who were amyloid PET-positive (A+) and tau PET-positive (T+) in the medial temporal lobe (A+TMTL+) and/or in the temporal neocortex (A+TNEO-T+) and compared them with A+T−and A−T−groups. Cox proportional-hazards models showed a substantially increased risk for progression to mild cognitive impairment in the A+TNEO-T+(hazard ratio (HR) = 19.2, 95% confidence interval (CI) = 10.9–33.7), A+TMTL+(HR = 14.6, 95% CI = 8.1–26.4) and A+T−(HR = 2.4, 95% CI = 1.4–4.3) groups versus the A−T−(reference) group. Both A+TMTL+(HR = 6.0, 95% CI = 3.4–10.6) and A+TNEO-T+(HR = 7.9, 95% CI = 4.7–13.5) groups also showed faster clinical progression to mild cognitive impairment than the A+T−group. Linear mixed-effect models indicated that the A+TNEO-T+(β = −0.056 ± 0.005,T = −11.55,P < 0.001), A+TMTL+(β = −0.024 ± 0.005,T = −4.72,P < 0.001) and A+T−(β = −0.008 ± 0.002,T = −3.46,P < 0.001) groups showed significantly faster longitudinal global cognitive decline compared to the A−T−(reference) group (allP < 0.001). Both A+TNEO-T+(P < 0.001) and A+TMTL+(P = 0.002) groups also progressed faster than the A+T−group. In summary, evidence of advanced Alzheimer’s disease pathological changes provided by a combination of abnormal amyloid and tau PET examinations is strongly associated with short-term (that is, 3–5 years) cognitive decline in cognitively unimpaired individuals and is therefore of high clinical relevance.
A split Bregman method solving optimal reactive power dispatch for a doubly-fed induction generator-based wind farm
Authors: Rong Fei , He Lingqi , Huang Sheng , Lyu Mingcheng , He Chao , Li Xueping , Zhao Chunyi 
Published: November 2022

AbstractThis paper proposes an optimal reactive power control method to maximize wind farm revenue and minimize the total electrical losses of a doubly-fed induction generator (DFIG)-based wind farm. Specifically, the split Bregman method is used to solve the optimal control problem in a distributed manner. That is, the optimization problem is decomposed into sub-problems by the optimal distributed control strategy, and each sub-problem is solved independently in each local controller through the parallel method, which reduces the calculating burden and improves the information privacy. Thus, when a fault occurs, the proposed distributed control strategy can overcome the system fault and improve the reliability and security of the system. Furthermore, an economic financial model of annual revenue is contributed to examine the income impact with or without certified emission reduction (CER) by the clean development mechanism (CDM). Compared with the dual ascent (DA) method, sequential quadratic programming (SQP) method and the proportional dispatch method (PDM), the annual revenue (AR) of the wind farm using the proposed split Bregman method is the highest. Simulation results demonstrate that this method has promising performance in both optimization quality and computational efficiency.
Integration of origami and deployable concept in volumetric modular units
Authors: Beatini Valentina , Gatheeshgar Perampalam , Rajanayagam Heshachanaa , Poologanathan Keerthan , Suntharalingam Thadshajini , Perera Dilini , Kanthasamy Elilarasi , Nagaratnam Brabha 
Published: November 2022

AbstractModular building systems (MBS) and Origami are two emerging methods used in current construction practice. Origami is directly associated with the principles of the ancient Japanese art of paper folding, characterised by high morphological possibilities and ultimately creates foldable structures with tuneable mechanical properties. However, there is a lack of knowledge on the structural behaviour of origami for architectural engineering applications. MBS is a volumetric prefabricated construction technique enhancing productivity in construction. In this paper, a modular unit is designed which employs origami techniques. The roof and floor panels of the modular units formed with steel joists were substituted with origami sandwich panels, while corner posts were substituted with origami columns. The origami-like foldable system demonstrated superior efficiency in constructability, being highly compact during transportation and requiring few operations for the in-situ installation. The structural performances of the developed and foldable modular units were assessed through finite element analysis. It was found that, without increasing the self-weight of the system, the design of origami-like modular units can be tuned for high structural performances and various structural sizes, which can impact the usability of space and the aesthetics of architecture. While this is a preliminary study and physical testing is needed, the positive results open the possibility of exploring highly deployable modular structures of novel shapes that can be employed during post-disaster and emergencies (Covid-19).
Secondary caries and marginal adaptation of ion-releasing versus resin composite restorations: a systematic review and meta-analysis of randomized clinical trials
Authors: Albelasy Eman H. , Hamama Hamdi H. , Chew Hooi Pin , Montaser Marmar , Mahmoud Salah H. 
Published: November 2022

AbstractThis systematic review was aimed to evaluate occurrence of secondary caries and marginal adaptation in ion-releasing materials versus resin composite. Electronic search of PubMed, Scopus, and Open Grey databases with no date or language restrictions until May 21st, 2021, was conducted. Randomized clinical trials that compared ion-releasing restorations versus resin composite were included. For quantitative analysis, a random-effects meta-analysis with risk difference as an effect measure and a 95% confidence interval was used. Quality of evidence was assessed using The Grading of Recommendations, Assessment, Development, and Evaluation criteria. The risk of bias was evaluated using the Cochran Collaboration Risk of Bias tool. The inclusion criteria were met by 22 studies, and 10 studies were included in the meta-analysis. Three follow-up periods (1 year, 18 months–2 years, and 3 years) were evaluated. The overall quality of evidence for secondary caries and marginal adaptation outcomes was low. The results of the meta-analysis showed no significant difference (p > 0.05) in both outcomes between ion-releasing materials and resin composite. The occurrence of secondary caries was not dependent on the nature of the restorative material. It is more likely a complex process that involves the same risk factors as primary carious lesions.
Opportunistic deep learning powered calcium scoring in oncologic patients with very high coronary artery calcium (≥ 1000) undergoing 18F-FDG PET/CT
Authors: Sartoretti Elisabeth , Gennari Antonio G. , Maurer Alexander , Sartoretti Thomas , Skawran Stephan , Schwyzer Moritz , Rossi Alexia , Giannopoulos Andreas A. , Buechel Ronny R. , Gebhard Catherine , Huellner Martin W. , Messerli Michael 
Published: November 2022

AbstractOur aim was to identify and quantify high coronary artery calcium (CAC) with deep learning (DL)-powered CAC scoring (CACS) in oncological patients with known very high CAC (≥ 1000) undergoing 18F-FDG-PET/CT for re-/staging. 100 patients were enrolled: 50 patients with Agatston scores ≥ 1000 (high CACS group), 50 patients with Agatston scores < 1000 (negative control group). All patients underwent oncological 18F-FDG-PET/CT and cardiac SPECT myocardial perfusion imaging (MPI) by 99mTc-tetrofosmin within 6 months. CACS was manually performed on dedicated non-contrast ECG-gated CT scans obtained from SPECT-MPI (reference standard). Additionally, CACS was performed fully automatically with a user-independent DL-CACS tool on non-contrast, free-breathing, non-gated CT scans from 18F-FDG-PET/CT examinations. Image quality and noise of CT scans was assessed. Agatston scores obtained by manual CACS and DL tool were compared. The high CACS group had Agatston scores of 2200 ± 1620 (reference standard) and 1300 ± 1011 (DL tool, average underestimation of 38.6 ± 26%) with an intraclass correlation of 0.714 (95% CI 0.546, 0.827). Sufficient image quality significantly improved the DL tool’s capability of correctly assigning Agatston scores ≥ 1000 (p = 0.01). In the control group, the DL tool correctly assigned Agatston scores < 1000 in all cases. In conclusion, DL-based CACS performed on non-contrast free-breathing, non-gated CT scans from 18F-FDG-PET/CT examinations of patients with known very high (≥ 1000) CAC underestimates CAC load, but correctly assigns an Agatston scores ≥ 1000 in over 70% of cases, provided sufficient CT image quality. Subgroup analyses of the control group showed that the DL tool does not generate false-positives.
Spatial distribution characteristics of heavy metal(loid)s health risk in soil at scale on town level
Authors: Gong Cang , Lu Haichuan , Zhang Zhixiang , Wang Liang , Xia Xiang , Wang Lihua , Xiang Zhiyu , Shuai Linyang , Ding Yang , Chen Yong , Wang Shunxiang 
Published: November 2022

AbstractIn order to reveal the Spatial distribution characteristics of heavy metal(loid)s health risk in soil on the town-scale, 788 topsoil samples were collected from a town in the hinterland of Chengdu Plain, with 5 subordinate communities and 17 administrative villages as the research sub regions. The USEPA health risk assessment model was used to assess the health risks of heavy metal(loid)s Cd, Hg, As, Cu, Pb, Cr, Zn and Ni in the soil, the health risk analysis method system based on the geographic detector and the optimized rank-size theory model are used to clarify the spatial differentiation and risk level difference of health risk in the study area. The results showed that the average values of Cd, Hg, As, Pb, Cr, Cu, Ni and Zn in the soil of the study area were 0.221, 0.155, 9.76, 32.2, 91.9, 35.2, 37.1 and 108.8 mg/kg, respectively. The health risks of heavy metal(loid)s in soil to adults and children are generally within the acceptable range, but the maximum hazard index of children and the maximum non-carcinogenic risk value of Cr to children are 2.653303 and 1.213098 respectively, which were exceeding the acceptable range. The carcinogenic risk of Cr and As to adults and children and the carcinogenic risk of Cd to children are at 1 × 10–4 to 1 × 10–6, exceeding the 10–6 health threshold. The q-value range of heavy metal(loid)s health risk spatial differentiation of soil in the study area is 0.016–0.425. The spatial differentiation of non-carcinogenic risk of Hg, As, Ni, Pb, Cd and Cr and the spatial differentiation of carcinogenic risk of Cr and As are larger, which needs further attention. The strictly controlled area of heavy metal(loid)s health risk in the soil of the study area (R ≥ 1.1) is mainly concentrated in the central, western and northeast sub regions, and most sub regions belong to the safe utilization area (0.9 < R < 1.1). The health risk assessment of heavy metal(loid)s in soil on a town scale is of positive significance for enriching health risk research methods, measuring health risk levels at different scales, and formulating refined risk management and control strategies.
Predicting willingness to donate blood based on machine learning: two blood donor recruitments during COVID-19 outbreaks
Authors: Wu Hong-yun , Li Zheng-gang , Sun Xin-kai , Bai Wei-min , Wang An-di , Ma Yu-chi , Diao Ren-hua , Fan Eng-yong , Zhao Fang , Liu Yun-qi , Hong Yi-zhou , Guo Ming-hua , Xue Hui , Liang Wen-biao 
Published: November 2022

AbstractMachine learning methods are a novel way to predict and rank donors' willingness to donate blood and to achieve precision recruitment, which can improve the recruitment efficiency and meet the challenge of blood shortage. We collected information about experienced blood donors via short message service (SMS) recruitment and developed 7 machine learning-based recruitment models using PyCharm-Python Environment and 13 features which were described as a method for ranking and predicting donors’ intentions to donate blood with a floating number between 0 and 1. Performance of the prediction models was assessed by the Area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score in the full dataset, and by the accuracy in the four sub-datasets. The developed models were applied to prospective validations of recruiting experienced blood donors during two COVID-19 pandemics, while the routine method was used as a control. Overall, a total of 95,476 recruitments via SMS and their donation results were enrolled in our modelling study. The strongest predictor features for the donation of experienced donors were blood donation interval, age, and donation frequency. Among the seven baseline models, the eXtreme Gradient Boosting (XGBoost) and Support vector machine models (SVM) achieved the best performance: mean (95%CI) with the highest AUC: 0.809 (0.806–0.811), accuracy: 0.815 (0.812–0.818), precision: 0.840 (0.835–0.845), and F1 score of XGBoost: 0.843 (0.840–0.845) and recall of SVM: 0.991 (0.988–0.994). The hit rate of the XGBoost model alone and the combined XGBoost and SVM models were 1.25 and 1.80 times higher than that of the conventional method as a control in 2 recruitments respectively, and the hit rate of the high willingness to donate group was 1.96 times higher than that of the low willingness to donate group. Our results suggested that the machine learning models could predict and determine the experienced donors with a strong willingness to donate blood by a ranking score based on personalized donation data and demographical details, significantly improve the recruitment rate of blood donors and help blood agencies to maintain the blood supply in emergencies.