bluuebunny/crossref_metadata_2025_split huggingface dataset:
Th17 cells contribute to combination MEK inhibitor and anti-PD-L1 therapy resistance in KRAS/p53 mutant lung cancers
Authors: Peng David H. , Rodriguez B. Leticia , Diao Lixia , Gaudreau Pierre-Olivier , Padhye Aparna , Konen Jessica M. , Ochieng Joshua K. , Class Caleb A. , Fradette Jared J. , Gibson Laura , Chen Limo , Wang Jing , Byers Lauren A. , Gibbons Don. L. 
Published: May 2021

AbstractUnderstanding resistance mechanisms to targeted therapies and immune checkpoint blockade in mutant KRAS lung cancers is critical to developing novel combination therapies and improving patient survival. Here, we show that MEK inhibition enhanced PD-L1 expression while PD-L1 blockade upregulated MAPK signaling in mutant KRAS lung tumors. Combined MEK inhibition with anti-PD-L1 synergistically reduced lung tumor growth and metastasis, but tumors eventually developed resistance to sustained combinatorial therapy. Multi-platform profiling revealed that resistant lung tumors have increased infiltration of Th17 cells, which secrete IL-17 and IL-22 cytokines to promote lung cancer cell invasiveness and MEK inhibitor resistance. Antibody depletion of IL-17A in combination with MEK inhibition and PD-L1 blockade markedly reduced therapy-resistance in vivo. Clinically, increased expression of Th17-associated genes in patients treated with PD-1 blockade predicted poorer overall survival and response in melanoma and predicated poorer response to anti-PD1 in NSCLC patients. Here we show a triple combinatorial therapeutic strategy to overcome resistance to combined MEK inhibitor and PD-L1 blockade.
MDMA-assisted therapy for severe PTSD: a randomized, double-blind, placebo-controlled phase 3 study
Authors: Mitchell Jennifer M. , Bogenschutz Michael , Lilienstein Alia , Harrison Charlotte , Kleiman Sarah , Parker-Guilbert Kelly , Ot’alora G. Marcela , Garas Wael , Paleos Casey , Gorman Ingmar , Nicholas Christopher , Mithoefer Michael , Carlin Shannon , Poulter Bruce , Mithoefer Ann , Quevedo Sylvestre , Wells Gregory , Klaire Sukhpreet S. , van der Kolk Bessel , Tzarfaty Keren , Amiaz Revital , Worthy Ray , Shannon Scott , Woolley Joshua D. , Marta Cole , Gelfand Yevgeniy , Hapke Emma , Amar Simon , Wallach Yair , Brown Randall , Hamilton Scott , Wang Julie B. , Coker Allison , Matthews Rebecca , de Boer Alberdina , Yazar-Klosinski Berra , Emerson Amy , Doblin Rick 
Published: May 2021

AbstractPost-traumatic stress disorder (PTSD) presents a major public health problem for which currently available treatments are modestly effective. We report the findings of a randomized, double-blind, placebo-controlled, multi-site phase 3 clinical trial (NCT03537014) to test the efficacy and safety of 3,4-methylenedioxymethamphetamine (MDMA)-assisted therapy for the treatment of patients with severe PTSD, including those with common comorbidities such as dissociation, depression, a history of alcohol and substance use disorders, and childhood trauma. After psychiatric medication washout, participants (n = 90) were randomized 1:1 to receive manualized therapy with MDMA or with placebo, combined with three preparatory and nine integrative therapy sessions. PTSD symptoms, measured with the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5, the primary endpoint), and functional impairment, measured with the Sheehan Disability Scale (SDS, the secondary endpoint) were assessed at baseline and at 2 months after the last experimental session. Adverse events and suicidality were tracked throughout the study. MDMA was found to induce significant and robust attenuation in CAPS-5 score compared with placebo (P < 0.0001,d = 0.91) and to significantly decrease the SDS total score (P = 0.0116,d = 0.43). The mean change in CAPS-5 scores in participants completing treatment was −24.4 (s.d. 11.6) in the MDMA group and −13.9 (s.d. 11.5) in the placebo group. MDMA did not induce adverse events of abuse potential, suicidality or QT prolongation. These data indicate that, compared with manualized therapy with inactive placebo, MDMA-assisted therapy is highly efficacious in individuals with severe PTSD, and treatment is safe and well-tolerated, even in those with comorbidities. We conclude that MDMA-assisted therapy represents a potential breakthrough treatment that merits expedited clinical evaluation.
Structural and physical properties of 99 complex bulk chalcogenides crystals using first-principles calculations
Authors: Hasan Sahib , Baral Khagendra , Li Neng , Ching Wai-Yim 
Published: May 2021

AbstractChalcogenide semiconductors and glasses have many applications in the civil and military fields, especially in relation to their electronic, optical and mechanical properties for energy conversion and in enviormental materials. However, they are much less systemically studied and their fundamental physical properties for a large class chalcogenide semiconductors are rather scattered and incomplete. Here, we present a detailed study using well defined first-principles calculations on the electronic structure, interatomic bonding, optical, and mechanical properties for 99 bulk chalcogenides including thirteen of these crytals which have never been calculated. Due to their unique composition and structures, these 99 bulk chalcogenides are divided into two main groups. The first group contains 54 quaternary crystals with the structure composition (A2BCQ4) (A = Ag, Cu; B = Zn, Cd, Hg, Mg, Sr, Ba; C = Si, Ge, Sn; Q = S, Se, Te), while the second group contains scattered ternary and quaternary chalcogenide crystals with a more diverse composition (AxByCzQn) (A = Ag, Cu, Ba, Cs, Li, Tl, K, Lu, Sr; B = Zn, Cd, Hg, Al, Ga, In, P, As, La, Lu, Pb, Cu, Ag; C = Si, Ge, Sn, As, Sb, Bi, Zr, Hf, Ga, In; Q = S, Se, Te; $$\hbox {x} = 1$$

x
=
1

, 2, 3; $$\hbox {y} = 0$$

y
=
0

, 1, 2, 5; $$\hbox {z} = 0$$

z
=
0

, 1, 2 and $$\hbox {n} = 3$$

n
=
3

, 4, 5, 6, 9). Moreover, the total bond order density (TBOD) is used as a single quantum mechanical metric to characterize the internal cohesion of these crystals enabling us to correlate them with the calculated properties, especially their mechanical properties. This work provides a very large database for bulk chalcogenides crucial for the future theoretical and experimental studies, opening opportunities for study the properties and potential application of a wide variety of chalcogenides.
Texture analysis of muscle MRI: machine learning-based classifications in idiopathic inflammatory myopathies
Authors: Nagawa Keita , Suzuki Masashi , Yamamoto Yuuya , Inoue Kaiji , Kozawa Eito , Mimura Toshihide , Nakamura Koichiro , Nagata Makoto , Niitsu Mamoru 
Published: May 2021

AbstractTo develop a machine learning (ML) model that predicts disease groups or autoantibodies in patients with idiopathic inflammatory myopathies (IIMs) using muscle MRI radiomics features. Twenty-two patients with dermatomyositis (DM), 14 with amyopathic dermatomyositis (ADM), 19 with polymyositis (PM) and 19 with non-IIM were enrolled. Using 2D manual segmentation, 93 original features as well as 93 local binary pattern (LBP) features were extracted from MRI (short-tau inversion recovery [STIR] imaging) of proximal limb muscles. To construct and compare ML models that predict disease groups using each set of features, dimensional reductions were performed using a reproducibility analysis by inter-reader and intra-reader correlation coefficients, collinearity analysis, and the sequential feature selection (SFS) algorithm. Models were created using the linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), support vector machine (SVM), k-nearest neighbors (k-NN), random forest (RF) and multi-layer perceptron (MLP) classifiers, and validated using tenfold cross-validation repeated 100 times. We also investigated whether it was possible to construct models predicting autoantibody status. Our ML-based MRI radiomics models showed the potential to distinguish between PM, DM, and ADM. Models using LBP features provided better results, with macro-average AUC values of 0.767 and 0.714, accuracy of 61.2 and 61.4%, and macro-average recall of 61.9 and 59.8%, in the LDA and k-NN classifiers, respectively. In contrast, the accuracies of radiomics models distinguishing between non-IIM and IIM disease groups were low. A subgroup analysis showed that classification models for anti-Jo-1 and anti-ARS antibodies provided AUC values of 0.646–0.853 and 0.692–0.792, with accuracy of 71.5–81.0 and 65.8–78.3%, respectively. ML-based TA of muscle MRI may be used to predict disease groups or the autoantibody status in patients with IIM and is useful in non-invasive assessments of disease mechanisms.
3-D health trajectories and related childhood predictors among older adults in China
Authors: Pan Chaoping , Wang Cen , Shrestha Bhawana , Wang Peigang 
Published: May 2021

AbstractThis study aimed to identify the multi-trajectories of 3-D health of older adults in China and to explore whether the childhood predictors are associated with 3-D health trajectory. Data came from five waves of the China Health and Retirement Longitudinal Study (CHARLS, 2011 to 2018). A multi-trajectory modeling approach was carried out to jointly estimate the trajectories of 3-D health. A multinomial regression model was used to investigate the relationships between childhood predictors and the joint trajectories. We identified three typical joint 3-D health trajectories. Female, childhood health, maternal and paternal educations, childhood friendships, family and neighborhood predictors could all affect 3-D health trajectories of older adults directly or indirectly through adult variables. The 3-D health trajectories showed increasing trends, thus the government should perform more interventions toward the childhood predictors for better health of older adults.
Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time
Authors: Ong Song-Quan , Ahmad Hamdan , Nair Gomesh , Isawasan Pradeep , Majid Abdul Hafiz Ab 
Published: May 2021

AbstractClassification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.
High-Speed Characterization of Vocal Fold Vibrations in Normally Cycling and Postmenopausal Women: Randomized Double-Blind Analyses
Authors: Patel Rita R. , Sandage Mary J. , Kluess Heidi , Plexico Laura W. 
Published: May 2021

Purpose
The aim of this study was to examine the influence of menstrual cycle phases (follicular, ovulatory, luteal, and ischemic) and hormone levels (estradiol, testosterone, progesterone, and neuropeptide Y) on vocal fold vibrations in reproductive and postmenopausal women.

Method

Glottal area waveforms were extracted from high-speed videoendoscopy during sustained phonation, inhalation phonation, and voice onset/offset in the reproductive (
n
= 15) and postmenopausal (
n
= 13) groups. Linear mixed-model analysis was conducted to evaluate hormone levels and high-speed videoendoscopy outcome variables between the reproductive and postmenopausal groups. In the reproductive group, simple linear regression and multiple regression were conducted to determine the effects of hormones on the dependent variables.

Results
Group differences between reproductive and postmenopausal women were identified for stiffness index, oscillatory onset time, and oscillatory offset time. Neuropeptide Y hormone in the ischemic phase significantly predicted changes in the reproductive group for some dependent variables; however, the relationship varied for sustained phonation and inhalation phonation.

Conclusion
These findings provide preliminary evidence that vocal fold vibrations in the reproductive group are different predominantly in the ischemic phase due to neuropeptide Y changes.
Blockchain‐enabled secure crowdsensing for trackside infrastructure information collection and validation in railway signalling data preparation
Authors: Muniandi Ganesan 
Published: May 2021

AbstractRail operators around the world are adopting advanced control systems for railway signalling and train protection to improve their safety performance. In these re‐signalling projects, the information about the already installed signals, point machines, track circuits etc. along the trackside infrastructure is essential for the configuration of advanced signalling equipment. The conventional information collection method which is based on unmanned aerial vehicles, helicopters etc. has the access limitations in terrains such as tunnels, hilly regions, river bridges, dense forests etc. To overcome these challenges, this paper proposes the railway vehicular crowdsensing method in which one group of trains participates in this information collection and another group of trains confirms the validity of the collected information. For information exchange between the trains and centralized server, this study chooses the permissioned blockchain‐based information transaction mechanism to ensure the trustworthiness. Furthermore, the railway markup language‐based blockchain databases are included for information immutability, crowd information integration, and the automatic execution of data preparation signalling rules. Finally, the case studies are carried out to analyse the adequacy of the proposed combination of crowdsensing based secure trackside infrastructure information collection and validation, permissioned blockchain‐enabled information transaction and blockchain databases in the proposed signalling data preparation process.
Blockchain‐enabled balise data security for train control system
Authors: Muniandi Ganesan 
Published: May 2021

AbstractThe train control system is the railway system's brain, ensuring the train protection and the railway network's operating performance. This control system relies on the balise data received via near‐field wireless communication to localize the train and update real‐time operating conditions and constraints. The attackers can capture these data through their balise antenna and corrupt them through replay or false data injection attacks. This corrupted data can compromise train safety and jeopardize the entire train fleet operations. To overcome these attacks and to ensure the trustworthiness of balise and data integrity, this study proposes the permissioned blockchain‐enabled two novel architectures for data transactions. Besides, each balise is equipped with a novel built‐in blockchain cryptography algorithm to create its secret and public keys to provide the key integrity without needing third‐party Certification Authority of conventional Public‐Key Infrastructure based security systems. Each balise can create the unique signature using a ‘nonce’ signal sent by the train control system in the static architecture or using a self‐generated ‘k‐once’ secret key per train control system in dynamic architecture. Finally, the case studies are carried out to confirm the security sufficiency of the proposed architectures.
Study of blockchain's consensus mechanism based on score
Authors: Cai Shaobin , Han Tangxuan , Wang Yuhao , Zhang Hu 
Published: May 2021

AbstractThe consensus mechanism is a key technology to achieve state consistency among distributed nodes and it determines the consensus efficiency and stability of the blockchain system. If the consensus efficiency and stability are improved, that can promote the development of the entire society. Therefore, it is necessary to improve the consensus efficiency and stability of the blockchain system. However, there are many disadvantages in the existing consensus mechanism, such as high communication complexity, low throughput, and poor scalability. For solving these disadvantages, a blockchain consensus mechanism Score‐Based Byzantine Fault Tolerance (SBBFT) is proposed. First, the score of nodes are obtained by Analytical Hierarchy Process (AHP) and SBBFT uses the score of the node to choose a node to be the primary node and acknowledgment node. Second, SBBFT selects acknowledgment nodes to be an acknowledgment node subset. This subset can change the communication of nodes from all‐to‐all to all‐to‐c. Moreover, the view change of acknowledgment node subset can make the system resistant to attacks from more malicious nodes. According to the experiment, 900,000 transactions from Ethereum, the result demonstrates SBBFT can significantly reduce the communication complexity, improve the consensus efficiency and stability of the system.
Hybrid piezo/triboelectric nanogenerator for stray magnetic energy harvesting and self‐powered sensing applications
Authors: Yang Aijun , Wang Chaoyu , Ma Jing , Fan Chengyu , Lv Pinlei , Bai Yuchen , Rong Yiming , Wang Xiaohua , Yuan Huan , Rong Mingzhe 
Published: May 2021

AbstractStray magnetic fields with a fixed frequency of 50/60 Hz are ubiquitous in buildings, factories, and power system equipment. Researchers are increasingly focusing on harvesting electrical energy from stray magnetic fields to provide sustainable energy for the Internet of Things (IoT) devices. Magneto‐mechano‐electric energy conversion is the most efficient way to convert low‐frequency stray magnetic fields into electricity. In this study, we proposed a hybrid piezo/triboelectric nanogenerator (HP/TENG) on the basis of a cantilever beam to use stray magnetic fields from the surrounding environment. The hybrid nanogenerator provided high output voltage/current and power of ∼176 V/375 μA and 4.7 mW (matched impedance of 20 kΩ) in a magnetic field environment of 4 Oe. The device provided a stable 3.6 V direct current output by incorporating energy management circuitry to sustainably drive power to commercial wireless temperature/humidity sensors. The HP/TENG has a significant application potential in IoT, which can use stray magnetic energy and a power wireless sensor system.
20 Years of Forging N-Heterocycles from Acrylamides through Domino/Cascade Reactions
Authors: Comesse Sébastien , Alahyen Ismail , Benhamou Laure , Dalla Vincent , Taillier Catherine 
Published: May 2021

AbstractAcrylamides are versatile building blocks that are easily obtained from readily available starting materials. During the last 20 years, these valuable substrates bearing a nucleophilic nitrogen atom and an electrophilic double bond have proven to be efficient domino partners, leading to a wide variety of complex aza-heterocycles of synthetic relevance. In this non-exhaustive review, metal-free and metal-triggered reactions followed by an annulation will be presented; these two approaches allow good modulation of the reactivity of the polyvalent acrylamides.1	Introduction2	Metal-Free Annulations2.1	Domino Reactions Triggered by a Michael Addition2.2	Domino Reactions Triggered by an Aza-Michael Addition2.3	Domino Processes Triggered by an Acylation Reaction2.4	Domino Reactions Triggered by a Baylis–Hillman Reaction2.5	Cycloadditions and Domino Reactions2.6	Miscellaneous Domino Reactions3	Metal-Triggered/Mediated Annulations3.1	Zinc-Promoted Transformations3.2	Rhodium-Catalyzed Functionalization/Annulation Cascades3.3	Cobalt-Catalyzed Functionalization/Annulation Cascades3.4	Ruthenium-Catalyzed Functionalization/Annulation Cascades3.5	Iron-Catalyzed Functionalization/Annulation Cascades3.6	Palladium-Catalyzed Functionalization/Annulation Cascades3.7	Copper-Catalyzed Transformations3.8	Transition Metals Acting in Tandem in Domino Processes4	Radical Cascade Reactions5	Conclusion
Arterial Thrombosis in Patients with Antiphospholipid Syndrome: A Review and Meta-Analysis
Authors: Aibar Jesus , Schulman Sam 
Published: May 2021

AbstractThere is a scarcity of high-quality randomized controlled trials (RCTs) comparing antithrombotic regimens for secondary prevention of arterial thrombosis (AT) in antiphospholipid syndrome (APS). We reviewed different antithrombotic regimens used for this purpose. We searched for studies on management of AT in APS on PubMed and Web of Science. Eleven studies (5 RCTs, 3 prospective, and 3 retrospective cohort studies) comparing different regimens and reporting outcomes specifically for patients with index AT events were identified. Treatments were vitamin K antagonists (VKA; 9 studies), non-VKA oral anticoagulant (NOAC; 3 studies), single antiplatelet therapy (SAPT; 7 studies), dual antiplatelet therapy (DAPT; 2 studies), and VKA combined with SAPT (4 studies). We performed a meta-analysis for the outcomes: recurrent AT, any (arterial or venous) recurrent thromboembolism, and major bleeding. Recurrent AT was reduced with VKA plus SAPT versus VKA (risk ratio [RR]: 0.43; 95% confidence interval [CI]: 0.22–0.85) and with DAPT versus SAPT (RR: 0.29; 95% CI: 0.09–0.99). Any recurrent thromboembolism was reduced with VKA plus SAPT versus VKA alone (RR: 0.41; 95% CI: 0.24–0.69) and versus SAPT alone (RR: 0.36; 95% CI: 0.13–0.96). There were no significant differences between other treatments for thromboembolism and for none of the comparisons regarding major bleeding. In a sensitivity analysis, excluding low-quality studies, VKA was more effective than NOAC to prevent recurrent AT (RR: 0.25; 95% CI: 0.07–0.93). Combined antithrombotic therapy might be more effective than single agents as secondary prophylaxis in APS with AT, and does not seem to compromise with safety, but the quality of evidence is generally low. NOACs should be avoided for patients with APS and AT.
Vascularized Rib Bone Grafting: Indications, Techniques, and Clinical Outcomes
Authors: Winocour Sebastian J. , Agrawal Nikhil , Wagner Kathryn M. , Davis Matthew J. , Abu-Ghname Amjed , Shekher Rohil , Raber Michael R. , Bohl Michael A. , Ropper Alexander E. , Reece Edward M. 
Published: May 2021

AbstractPseudarthrosis is a difficult complication often seen in patients with complex spinal pathology. To supplement existing neurosurgical approaches to cervicothoracic spinal instrumentation and fusion, novel vascularized rib bone grafts can be utilized in patients at high risk for failed spinal fusion. In this article, we discuss the indications, benefits, surgical technique, feasibility, and limitations of using rib vascularized rib bone grafts to augment spinal fusion.