bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evidence of emerging BBB changes in mid‐age apolipoprotein E epsilon‐4 carriers
Authors: Alruwais Nourah M. , Rusted Jenifer M. , Tabet Naji , Dowell Nicholas G. 
Published: November 2022

AbstractIntroductionStudies have recognized that the loss of the blood–brain barrier (BBB) integrity is a major structural biomarker where neurodegenerative disease potentially begins. Using a combination of high‐quality neuroimaging techniques, we investigated potential subtle differences in BBB permeability in mid‐age healthy people, comparing carriers of the apolipoprotein E epsilon‐4 (APOEε4) genotype, the biggest risk factor for late onset, non‐familial AD (LOAD) with APOEε3 carriers, the population norm.MethodsForty‐one cognitively healthy mid‐age participants (42–59) were genotyped and pseudo‐randomly selected to participate in the study by a third party. Blind to genotype, all participants had a structural brain scan acquisition including gadolinium‐based dynamic contrast‐enhanced magnetic resonance imaging acquired using a T1‐weighted 3D vibe sequence. A B1 map and T1 map were acquired as part of the multi‐parametric mapping acquisition.ResultsNon‐significant, but subtle differences in blood–brain barrier permeability were identified between healthy mid‐age APOEε4 and APOEε3 carriers, matched on age, education, and gender.DiscussionThis study demonstrated a tendency toward BBB permeability in APOEε4 participants emerging from mid‐age, with quantitative differences observable on a number of the measures. While the differences did not reach a statistical significance, the results from this study hint at early changes in ε4 carrier BBB that may help identify at‐risk populations and facilitate the development of early interventions to change the trajectory of decline.
Genomic alteration profile and PD‐L1 expression among different breast cancer subtypes in Chinese population and their correlations
Authors: Li Kai , Cao Li , Li Cheukfai , Wu Jundong , Chen Bo , Zhang Guochun , Li Xueri , Wen Lingzhu , Jia Minghan , Wei Guangnan , Lin Jiali , Li Yingzi , Zhang Yuchen , Mok Hsiaopei , Ren Chongyang , Wang Yulei , Qi Xiaofang , Guo Lijie , Che Yue , Liao Ning 
Published: November 2022

AbstractBackgroudThere were limitations existing in programmed cell‐death ligand 1 (PD‐L1) as predictive biomarkers for breast cancer (BC), hence exploring the correlation between PD‐L1 levels and other biomarkers in BC may become a very useful therapeutic clinical tool.MethodsA total of 301 Chinese patients with different BC subtypes including 47 HR+/HER2+, 185 HR+/HER2−, 38 HR−/HER2+, and 31 triple‐negative breast cancer (TNBC) were enrolled in our study. Next‐generation sequencing based Yuansu450 gene panel was used for genomic alteration identification and PD‐L1 expression was tested using immunohistochemistry.ResultsThe most prevalent BC‐related mutations were TP53 mutations, followed by mutations in PIK3CA, ERBB2, CDK12, and GATA3 in our Chinese cohort. We found that mutations DDR2 and MYCL were only mutated in HR−/HER2+ subtype, whereas H3‐3A and NRAS mutations were only occurred in HR−/HER2− subtype. The percentage of patients with PD‐L1‐positive expression was higher in patients with HR‐/HER2− mainly due to the percentage of PD‐L1‐high level. Mutational frequencies of TP53, MYC, FAT4, PBRM1, PREX2 were observed to have significant differences among patients with different BC subtypes based on PD‐L1 levels. Moreover, a positive correlation was observed between TMB and PD‐L1 level in HR+/HER2− subtype, and showed that the proportion of patients with high PD‐L1 expression was higher than that of patients with low PD‐L1 expression in the HR+/HER2− and HR+/HER2+ cohorts with high Ki67 expression.ConclusionsThe genomic alterations based on PD‐L1 and other biomarkers of different cohorts may provide more possibilities for the treatment of BC with different subtypes.
Internet‐administered, low‐intensity cognitive behavioral therapy for parents of children treated for cancer: A feasibility trial (ENGAGE)
Authors: Thiblin Ella , Woodford Joanne , Reuther Christina , Lundgren Johan , Lutvica Nina , von Essen Louise 
Published: November 2022

AbstractBackgroundParents of children treated for cancer may experience mental health difficulties, such as depression and anxiety. There is a lack of evidence‐based psychological interventions for parents, with psychological support needs unmet. An internet‐administered, guided, low‐intensity cognitive behavioral therapy‐based (LICBT) self‐help intervention may provide a solution.MethodsThe feasibility and acceptability of such an intervention was examined using a single‐arm feasibility trial (ENGAGE). Primary objectives examined: (1) estimates of recruitment and retention rates; (2) feasibility and acceptability of data collection instruments and procedures; and (3) intervention feasibility and acceptability. Clinical outcomes were collected at baseline, post‐treatment (12 weeks), and follow‐up (6 months).ResultsThe following progression criteria were met: sample size was exceeded within 5 months, with 11.0% enrolled of total population invited, study dropout rate was 24.0%, intervention dropout was 23.6%, missing data remained at ≤10% per measure, and no substantial negative consequences related to participation were reported. Intervention adherence was slightly lower than progression criteria (47.9%).ConclusionFindings suggest an internet‐administered, guided, LICBT self‐help intervention may represent a feasible and acceptable solution for parents of children treated for cancer. With minor study protocol and intervention modifications, progression to a pilot randomized controlled trial (RCT) and subsequent superiority RCT is warranted.
Enzymatic Modification of the 5’ Cap with Photocleavable ONB‐Derivatives Using GlaTgs V34A
Authors: Klöcker Nils , Anhäuser Lea , Rentmeister Andrea 
Published: November 2022

AbstractThe 5’ cap of mRNA plays a critical role in mRNA processing, quality control and turnover. Enzymatic availability of the 5’ cap governs translation and could be a tool to investigate cell fate decisions and protein functions or develop protein replacement therapies. We have previously reported on the chemical synthesis of 5’ cap analogues with photocleavable groups for this purpose. However, the synthesis is complex and post‐synthetic enzymatic installation may make the technique more applicable to biological researchers. Common 5’ cap analogues, like the cap 0, are commercially available and routinely used for in vitro transcription. Here, we report a facile enzymatic approach to attach photocleavable groups site‐specifically to the N2 position of m7G of the 5’ cap. By expanding the substrate scope of the methyltransferase variant GlaTgs V34A and using synthetic co‐substrate analogues, we could enzymatically photocage the 5’ cap and recover it after irradiation.
Primary retroperitoneal hydatid cyst, a rare novel differential diagnosis of retroperitoneal masses: A case report
Authors: Mehri Ali , Esparham Ali , Rezaei Reza 
Published: November 2022

AbstractThe presence of primary retroperitoneal hydatid cysts is rare, even in endemic areas. The authors report a young man with a retroperitoneal hydatid cyst who underwent total cystectomy. The surgeons should suspect hydatid cysts in case of any abdominal cysts, especially in endemic areas, and avoid any spillage and puncture.
Splenunculus mimicking splenomegaly in a patient with synchronous herpes simplex 1 viremia and myelosuppression
Authors: Paul Dion A. , La Paul Bao Duy , Abasszade Joshua Haron 
Published: November 2022

AbstractSplenunculus, or congenital accessory spleen, is a benign anatomical variation, and is rarely of clinical consideration in routine clinical practice. We describe a patient who presented with synchronous herpes simplex 1 viraemia and myelosuppression, with a splenunculus mimicking splenomegaly, and we discuss the implications on clinical practice, investigations, and management.
Tailored Particle Catalysts for Multistep One‐pot Chemoenzymatic Cascade in Pickering Emulsions
Authors: Wang Shan , Scandurra Luca , Hübner René , Nielsen Ulla Gro , Wu Changzhu 
Published: November 2022

AbstractChemoenzymatic cascades are an important tool for advanced synthesis in chemistry. However, these cascades are often limited due to the incompatibility issue between two distinct catalysts and reactions. To address this issue, we present a simple multistep one‐pot platform, in which nanoparticle catalysts are prepared to allow chemo‐ and biocatalytic reactions performed sequentially in water and Pickering emulsions. The preparation of particle catalysts is accomplished in just two steps by polymer modifications and [RuCl2(p‐cymene)]2 coordination, while the benefits of using them for chemoenzymatic synthesis are multifaceted. They act not only as asymmetric catalysts for asymmetric transfer hydrogenation from acetophenone to 1‐phenylethanol in water with up to 99 % conversion and 93 % ee, but also as an emulsifier to form stable Pickering emulsions. By the addition of Candida antarctica lipase B into the emulsions, the second‐step reaction of enantioselective acylation was achieved with 38 % conversion and 99 % ee. Therefore, we successfully present a simple method to enable chemoenzymatic cascades by combining particle catalysts and enzymes in water and Pickering emulsions in a sequential fashion, which can be generalized for other cascade syntheses with different chemo‐ and biocatalysts in the future.
Roadmap for outlier detection in univariate linear calibration in analytical chemistry: Tutorial review
Authors: Ahmadiyeh Fatemeh , Sajedi‐Amin Sanaz , Kafili‐Hajlari Taha , Naseri Abdolhossein 
Published: November 2022

AbstractAssessment of the adequacy of a proposed linear calibration curve is necessarily subjective in chemical analysis. If the outlier points in calibration are not identified and discarded, the constructed model will not have much validity and does not warrant the accuracy and precision of prediction step. Recognizing of influential points, outlier data, and discarding them is one of the steps in data processing that has been considered in various sciences. The outlier points can arise from (I) bad design of calibration set and (II) gross error in doing experiments. Therefore, we aimed to extract a map that recognizes the following issues: (A) the existence of data with high regression coverage that is far from the rest and will strongly affect the accuracy of the calibration equation, high leverage points; (B) large error in the experimental process: The recorded signal does not match the desired concentration; and (C) points with a concentration lower than the limit of quantification, which is calculated by considering the standard error of regression instead of the standard deviation of blank.The efficiency of the proposed roadmap will be reviewed, and this will give a new perspective on the calibration equation to avoid common mistakes in analytical chemistry. To achieve the above goal, visual and statistically significant tests will be used and all tests will be performed in a simple Microsoft Excel environment.
Promoted Photothermal Catalytic CO Hydrogenation by Using TiC‐Supported Co−Fe5C2 Catalysts
Authors: Jiang Haoyang , Zhu Feng , Zhou Renjie , Wang Linyu , Xiao Yongcheng , Zhong Miao 
Published: November 2022

AbstractPhotothermal catalytic CO hydrogenation offers the potential to synthesize light hydrocarbons by using solar energy. However, the selectivity and activity of the reaction are still far below those achieved in conventional thermal catalytic processes. Herein, we report that the Co‐modified Fe5C2 on TiC catalyst promotes photothermal catalytic CO hydrogenation with a 59 % C2+ selectivity in the produced hydrocarbons and a 30 % single‐pass CO conversion at a high gas hourly space–time velocity of 12 000 mL g−1 h−1. Using in‐situ‐irradiated XPS, we show that light‐induced hot electron injection from TiC to Fe5C2 modulates the chemical state of Fe, thereby increasing the CO‐to‐C2+ conversion. This work suggests that it is possible for plasmon‐mediated surface chemistry to enhance the activity and selectivity of photothermal catalytic reactions.
Gated, Selective Anion Exchange in Functionalized Self‐Assembled Cage Complexes
Authors: da Camara Bryce , Ziv Noa Bar , Carta Veronica , Mota Orozco Gabriela A. , Wu Hoi‐Ting , Julian Ryan R. , Hooley Richard J. 
Published: November 2022

AbstractAppending functional groups to the exterior of Zn4L4 self‐assembled cages allows gated control of anion binding. While the unfunctionalized cages contain aryl groups in the ligand that can freely rotate, attaching inert functional groups creates a “doorstop”, preventing rotation and slowing the guest exchange rate, even though the interiors of the host cavities are identically structured. The effects on anion exchange are subtle and depend on multiple factors, including anion size, the nature of the leaving anion, and the electron‐withdrawing ability and steric bulk of the pendant groups. Multiple exchange mechanisms occur, and the nature of the external groups controls associative and dissociative exchange processes: these bulky groups affect both anion egress and ingress, introducing an extra layer of selectivity to the exchange. Small changes can have large effects: affinities for anions as similar as PF6− and SbF6− can vary by as much as 400‐fold between identically sized cavities.
Treatment‐related adverse events of antibody–drug conjugates in clinical trials: A systematic review and meta‐analysis
Authors: Zhu Youwen , Liu Kun , Wang Kailing , Zhu Hong 
Published: November 2022

AbstractBackgroundAntibody–drug conjugates (ADCs) have complex molecular structures and have been tested in numerous clinical trials. Therefore, understanding the mechanisms of their toxicity when applied in medical practice is of high importance.MethodsIn a systematic review and meta‐analysis of data gathered from different scientific databases (PubMed, Embase, Cochrane, and Web of Science) between January 1, 2000, and June 7, 2022, the authors applied a random‐effects model with logit transformation and evaluated the heterogeneity between studies using I2 statistics. The primary outcome was the incidence and 95% confidence interval (CI) for all‐grade and grade ≥3 treatment‐related adverse events and differences between different drugs, molecular structures, and cancer types.ResultsIn total, 2511 records were identified that included 169 clinical trials involving 22,492 patients. The overall incidence of treatment‐related adverse events was 91.2% (95% CI, 90.7%–91.7%; I2 = 95.9%) for all‐grade adverse events and 46.1% (95% CI, 45.2%–47.0%; I2 = 96.3%) for grade ≥3 adverse events. The most common all‐grade adverse events were lymphopenia (53.0%; 95% CI, 48.7%–57.3%), nausea (44.1%; 95% CI, 43.2%–44.9%), neutropenia (43.7%; 95% CI, 42.6%–44.9%), blurred vision (40.5%; 95% CI, 37.4%–43.6%), and peripheral neuropathy (39.6%; 95% CI, 38.2%–41.1%); and the most common grade ≥3 adverse events were neutropenia (31.2%; 95% CI, 30.2%–32.3%), hypoesthesia (23.3%; 95% CI, 10.6%–35.9%), thrombocytopenia (22.6%; 95% CI, 21.3%–23.9%), febrile neutropenia (21.2%; 95% CI, 19.3%–23.1%), and lymphopenia (21.0%; 95% CI, 18.2%–23.7%).ConclusionsDifferent ADCs appear to affect various treatment‐related adverse events and provide comprehensive data on treatment‐related adverse events for ADCs. The current results provide an important reference for clinicians and patients on how to care for toxicities from ADCs in clinical practice.Lay summary

Unique anticancer drugs called antibody–drug conjugates (ADCs) have made significant progress in oncology in recent years because of their great success, and they are rapidly being used in the clinic as well as in hundreds of ongoing trials exploring their further use.

The occurrence of serious side effects (adverse events) related to the receipt of ADCs was studied using data from 169 clinical trials involving 22,492 patients to determine the treatment‐related causes of higher toxicity and adverse events in patients who receive ADCs, because these data are crucial for informing physicians how to safely treat patients using ADCs.

The results indicate that different ADCs appear to affect various adverse events related to their use, providing comprehensive data on these ADCs that provide an important reference for clinicians and patients on how to care for toxicities from ADCs in clinical practice.
DataPlane‐ML: An integrated attack detection and mitigation solution for software defined networks
Authors: Carvalho Ranyelson N. , Costa Lucas R. , Bordim Jacir L. , Alchieri Eduardo A. P. 
Published: November 2022

SummarySoftware defined network (SDN) is a paradigm that emphasizes the separation of the control plane from the data plane, offering advantages such as flexibility and programmability. However, from a security perspective, SDN also introduces new vulnerabilities due to the communication required between these planes. SYN Flood attacks are typical distributed denial‐of‐service (DDoS) attacks that especially challenge network administrators since they produce a large volume of semi‐open TCP connections to a target, compromising its availability. Most of the current solutions to detect and mitigate these attacks are designed to operate at the control plane, imposing an additional overhead on controller functions. Moreover, traffic‐blocking mechanisms, a widely used alternative to protect network resources, have the drawback of restricting legitimate traffic. This work proposes DataPlane‐ML, an integrated solution to detect and mitigate DDoS attacks on SDN, acting directly in the data plane. DataPlane‐ML uses machine learning techniques for attack detection and a mitigation solution based on the node's reputation to avoid blocking legitimate traffic during an attack. Experimental results show that DataPlane‐ML is faster than statistical‐based solutions for attack detection while presenting better accuracy. Moreover, the DataPlane‐ML mitigation solution can preserve more than of legitimate traffic during an attack.
NEEBS: Nonexpert large‐scale environment building system for deep neural network
Authors: Tajima Yoshiharu , Asaoka Masahiro , Tabuchi Akihiro , Kasagi Akihiko , Tabaru Tsuguchika 
Published: November 2022

SummaryDeep neural networks (DNNs) have greatly improved the accuracy of various tasks in areas such as natural language processing (NLP). Obtaining a highly accurate DNN model requires multiple repetitions of training on a huge dataset, which requires a large‐scale cluster the compute nodes of which are tightly connected by high‐speed interconnects to exchange a large amount of intermediate data with very short latency. However, fully using the computational power of a large‐scale cluster for training requires knowledge of its components such as a distributed file system, an interconnection, and optimized high‐performance libraries. We have developed a Non‐Expert large‐scale Environment Building System (NEEBS) that aids a user in building a fast‐running training environment on a large‐scale cluster. It automatically installs and configures the applications and necessary libraries. It also optimally prepares tools to stage both data and executable programs, and launcher scripts suitable for both the applications and job submission systems of the cluster. NEEBS achieves 93.91% throughput scalability in NLP pretraining. We also present an approach to reduce pretraining time of highly accurate DNN model for NLP using a large‐scale computation environment built using NEEBS. We trained a Bidirectional Encoder Representations from Transformers (BERT)‐3.9b and a BERT‐xlarge using a dense masked language model (MLM) on Megatron‐LM framework and evaluated the improvement in learning time and learning efficiency for a Japanese language dataset using 768 graphics processing units (GPUs) on the AI Bridging Cloud Infrastructure (ABCI). Our implementation NEEBS improved learning efficiency per iteration by a factor of 10 and completed the pretraining of BERT‐xlarge in 4.7 h. This pretraining takes 5 months on a single GPU. To determine if the BERT models are correctly pretrained, we evaluated their accuracy in two tasks, Stanford Natural Language Inference Corpus translated into Japanese (JSNLI) and Twitter reputation analysis (TwitterRA). BERT‐3.9b achieved 94.30% accuracy for JSNLI, and BERT‐xlarge achieved 90.63% accuracy for TwitterRA. We constructed pretrained models with comparable accuracy to other Japanese BERT models in a shorter time.
Coal rock image recognition method based on improved CLBP and receptive field theory
Authors: Sun Chuanmeng , Xu Ruijia , Wang Chong , Ma Tiehua , Chen Jiaxin 
Published: November 2022

AbstractRapid coal‐rock identification is one of the key technologies for intelligent and unmanned coal mining. Currently, the existing image recognition algorithms cannot satisfy practical needs in terms of recognition speed and accuracy. In view of the evident differences between coal and rock in visual attributes such as color, gloss and texture, the complete local binary pattern (CLBP) image feature descriptor is introduced for coal and rock image recognition. Given that the original algorithm oversimplifies local texture features by ignoring imaging information from higher‐order pixels and the concave and convex areas between adjacent sampling points, this paper proposes a higher‐order differential median CLBP image feature descriptor to replace the original CLBP center pixel gray with a local gray median, and replace the binary differential with a second‐order differential. Meanwhile, for the high dimensionality of CLBP descriptor histogram and feature redundancy, deep learning perceptual field theory is introduced to realize data nonlinear dimensionality reduction and deep feature extraction. With relevant experiments conducted, the following conclusion can be drawn: (1) Compared with that of the original CLBP, the recognition accuracy of the improved CLBP algorithm is greatly improved and finally stabilized above 94.3% under strong noise interference; (2) Compared with that of the original CLBP model, the single image recognition time of the coal rock image recognition model fusing the improved CLBP and the receptive field theory is 0.0035 s, a reduction of 71.0%; compared with the improved CLBP model (without the fusion of receptive field theory), it can shorten the recognition time by 97.0%, but the accuracy rate still maintains more than 98.5%. The method offers a valuable technical reference for the fields of mineral development and deep mining.