bluuebunny/crossref_metadata_2025_split huggingface dataset:
Consensus‐based ethical best practices for performing educational point‐of‐care ultrasonography in the emergency department
Authors: Chao Samantha K. , Liu Yiju T. , Kropf Charles W. , Huang Robert D. , Theyyunni Nik , Taylor Lindsay A. , Firn Janice I. , Kessler Ross , Micheller Daniel R. , Battles Alethia J. , Rosculet Natalja P. , Ager Emily E. , Valentyne Alyssa A. , Schellack Christine J. , Hennessy John P. , White Cameron , Tucker Ryan V. 
Published: March 2024

AbstractObjectivesThere is no standardized protocol for performing educational point‐of‐care ultrasonography (POCUS) that addresses patient‐centered ethical issues such as obtaining informed consent. This study sought to define principles for ethical application of educational POCUS and develop consensus‐based best practice guidance.MethodsA questionnaire was developed by a trained ethicist after literature review with the help of a medical librarian. A diverse panel including experts in medical education, law, and bioethics; medical trainees; and individuals with no medical background was convened. The panel voted on their level of agreement with ethical principles and degree of appropriateness of behaviors in three rounds of a modified Delphi process. A high level of agreement was defined as 80% or greater consensus.ResultsPanelists voted on 38 total items: 15 related to the patient consent and selection process, eight related to practices while performing educational POCUS, and 15 scenarios involving POCUS application. A high level of agreement was achieved for 13 items related to patient consent and selection, eight items related to performance practices, and 10 scenarios of POCUS application.ConclusionsBased on expert consensus, ethical best practices include obtaining informed consent before performing educational POCUS, allowing patients to decline educational POCUS, informing patients the examination is not intended to be a part of their medical evaluation and is not billed, using appropriate draping techniques, maintaining a professional environment, and disclosing incidental findings in coordination with the primary team caring for the patient. These practices could be implemented at institutions to encourage ethical use of educational POCUS when training physicians, fellows, residents, and medical students.
Resolution of severe neurobehavioral difficulties in an individual with Primrose syndrome with sertraline
Authors: Moon Young Min , Park Sa Eun , Smith‐Hicks Constance , Hauptman Aaron 
Published: March 2024

AbstractPrimrose syndrome (PS) is a rare genetic disease characterized by developmental delay, intellectual disability, sensorineural hearing loss, and dysmorphic features. PS is caused by de novo pathogenic variants in the ZBTB20 gene, which encodes a transcription factor modulating neurogenesis. We describe resolution with sertraline of neurobehavioral difficulties in a 17‐year‐old Hispanic male with PS with de novo heterozygous c.1916G > A (p.C639Y) variant of ZBTB20. Neurobehavioral difficulties included aggression towards self and others, irritability, tearfulness, and mood liability that did not respond to behavioral interventions or aripiprazole. Treatment with sertraline, a medication indicated for psychiatric disorders including anxiety and depression, led to the resolution of neurobehavioral difficulties after 2 weeks of initiation of medication. The treatment course suggests that selective serotonin reuptake inhibitors, such as sertraline, may be a useful tool for neurobehavioral difficulties in PS over antipsychotics that are accompanied by complex side effect profiles, and suggest that anxiety is the primary cause of the neurobehavioral difficulties in this patient.
One‐Dimensional Covalent Organic Framework‐Based Multilevel Memristors for Neuromorphic Computing
Authors: Zhou Pan‐Ke , Li Yiping , Zeng Tao , Chee Mun Yin , Huang Yuxing , Yu Ziyue , Yu Hongling , Yu Hong , Huang Weiguo , Chen Xiong 
Published: March 2024

AbstractMemristors are essential components of neuromorphic systems that mimic the synaptic plasticity observed in biological neurons. In this study, a novel approach employing one‐dimensional covalent organic framework (1D COF) films was explored to enhance the performance of memristors. The unique structural and electronic properties of two 1D COF films (COF‐4,4′‐methylenedianiline (MDA) and COF‐4,4′‐oxydianiline (ODA)) offer advantages for multilevel resistive switching, which is a key feature in neuromorphic computing applications. By further introducing a TiO2 layer on the COF‐ODA film, a built‐in electric field between the COF‐TiO2 interfaces could be generated, demonstrating the feasibility of utilizing COFs as a platform for constructing memristors with tunable resistive states. The 1D nanochannels of these COF structures contributed to the efficient modulation of electrical conductance, enabling precise control over synaptic weights in neuromorphic circuits. This study also investigated the potential of these COF‐based memristors to achieve energy‐efficient and high‐density memory devices.
Lactate dehydrogenase A is implicated in the pathogenesis of B‐cell lymphoma through regulation of the FER signaling pathway
Authors: Feng Xiumei , Ren Jing , Zhang Xunqi , Kong Dexiao , Yin Linlin , Zhou Qian , Wang Shunye , Li Ai , Guo Yanan , Wang Yongjing , Feng Xiaoli , Wang Xiaoyun , Niu Jianhua , Jiang Yang , Zheng Chengyun 
Published: March 2024

AbstractLactate dehydrogenase A (LDHA) is highly expressed in various tumors. However, the role of LDHA in the pathogenesis of B‐cell lymphoma remains unclear. Analysis of data from The Cancer Genome Atlas (TCGA) and Genotype‐Tissue Expression (GTEx) databases revealed an elevated LDHA expression in diffuse large B‐cell lymphoma (DLBC) tissues compared with normal tissues. Similarly, our results demonstrated a significant increase in LDHA expression in tumor tissues from the patients with B‐cell lymphoma compared with those with lymphadenitis. To further elucidate potential roles of LDHA in B‐cell lymphoma pathogenesis, we silenced LDHA in the Raji cells (a B‐cell lymphoma cell line) using shRNA techniques. Silencing LDHA led to reduced mitochondrial membrane integrity, adenosine triphosphate (ATP) production, glycolytic activity, cell viability and invasion. Notably, LDHA knockdown substantially suppressed in vivo growth of Raji cells and extended survival in mice bearing lymphoma (Raji cells). Moreover, proteomic analysis identified feline sarcoma‐related protein (FER) as a differential protein positively associated with LDHA expression. Treatment with E260, a FER inhibitor, significantly reduced the metabolism, proliferation and invasion of Raji cells. In summary, our findings highlight that LDHA plays multiple roles in B‐cell lymphoma pathogenesis via FER pathways, establishing LDHA/FER may as a potential therapeutic target.
MAIT cells are associated with responsiveness to neoadjuvant immunotherapy in COPD‐associated NSCLC
Authors: Yin Yanze , Zeng Ao , Abuduwayiti Abudumijiti , Xu Zhilong , Chen Keyi , Wang Chao , Fang Xinyun , Wang Jiarui , Jiang Gening , Dai Jie 
Published: March 2024

AbstractBackgroundPatients with non‐small cell lung cancer (NSCLC) and chronic obstructive pulmonary disease (COPD) experience worse clinical outcomes but respond better to immunotherapy than patients with NSCLC without COPD. Mucosal‐associated invariant T (MAIT) cells, a versatile population of innate immune T lymphocytes, have a crucial function in the response to infection and tumors. This study investigated the distribution of MAIT cells in COPD‐associated NSCLC and their involvement in the immune response.MethodsFlow cytometry, immunohistochemistry, and immunofluorescence were performed on tissue samples of patients with NSCLC, with or without COPD, treated with or without anti‐programmed death 1 (PD1) immunotherapy. MAIT cells were stimulated with 5‐OP‐RU using a mouse subcutaneous tumor model.ResultsTumors contained significantly more MAIT cells than paraneoplastic tissues, and CD8+ MAIT cells accounted for more than 90% of these cells. Patients with NSCLC and COPD had higher CD8+ MAIT cell counts than those with NSCLC without COPD. Additionally, patients with NSCLC and COPD displayed reduced expression of the activation marker, CD69, and functional markers, granzyme B (GZMB) and interferon γ (IFNγ), and higher expression of the immune exhaustion marker, PD1. Among patients who received immunotherapy, the proportion with a complete or partial response was higher in those with COPD than in those without COPD. In patients with NSCLC and COPD, the major pathologic response (MPR) group had higher MAIT levels than those in the no major pathologic response (NPR) group. In the mouse subcutaneous tumor model stimulation of MAIT cells using 5‐OP‐RU enhanced the antitumor effects of anti‐PD1.ConclusionsIn patients with NSCLC and COPD, response to immunotherapy is associated with accumulation of CD8+ MAIT cells showing immune exhaustion. These findings may contribute to innovative approaches for immunotherapy targeting CD8+ MAIT cells.
Primary glioblastoma multiform (GBM) of the optic nerve and chiasma: A case report and systematic review of the literature
Authors: Mulhem Ali 
Published: March 2024

Key Clinical MessagePrimary GBM of the optic nerve and chiasma should be included in the differential diagnosis of progressive lesions despite initial treatment; clinicians should avoid delay in confirming the histology to initiate proper treatment and improve prognosis.AbstractPrimary GBM of the optic nerve or chiasma is very rare. The characteristics of this condition have not been well‐described, which poses difficulties in establishing the correct diagnosis, affecting the treatment and the prognosis. We present a case of GBM of the optic chiasma diagnosed through an open biopsy at our centre. Following the PRISMA statement, we also conducted a systematic review after protocol registration in PROSPERO (CRD42021285855). We searched Medline and Embase through Ovid from inception until December 31, 2021. Two reviewers independently screened the studies. Studies were eligible for inclusion if they reported cases of primary GBM confined to the optic nerve or chiasma as the initial radiological diagnosis. A 77‐year‐old female was referred for progressive visual loss lasting 8 weeks. MRI revealed a suspected lesion in the left chiasma. The patient's vision deteriorated further despite initially diagnosing an inflammatory process and empirical treatment with corticosteroids. Subsequently, the patient underwent an open biopsy and surgical debulking. Histology, including epigenetic analysis, confirmed GBM grade IV. Radiochemotherapy was administered. The patient died 19 months after surgery. We identified 45 similar cases (22 female) reported in 35 studies between 1949 and 2020. The mean age of the cases was 61 (SD = 14.6). Most cases were misdiagnosed and mistreated accordingly, so there was a median delay of 8 weeks (IQR: 5–14 weeks) in obtaining histological confirmation of the diagnosis, delaying the initiation of appropriate treatment. Five cases became no treatment since the patients died shortly after the delayed histologic diagnosis. The Kaplan–Meier estimate indicated that most patients died within 20 months of presentation, with a 1‐year survival rate of 50%, and untreated cases had very low survival rates compared to treated cases. Primary GBM of the optic nerve and chiasma is a rare condition primarily affecting adults. The rarity of this condition contributes to initial misdiagnosis, mistreatment, and delays in confirming the histology and initiating appropriate treatment. The prognosis remains poor, but treatment, including surgery and radiochemotherapy, improves survival.
Challenges searching for alternatives – Substituting formaldehyde and pyrogallol in the “Two‐Color‐Chemiluminescence “
Authors: Volodin Niklas , Holfeld Martin , Eberhardt Pauline 
Published: March 2024

AbstractChemische Experimente erfordern einen sichereren und überlegten Umgang mit Gefahrstoffen. Schüler:innen müssen sensibilisiert werden richtig und vernünftig mit diesen Stoffen umzugehen, weshalb eine Vermeidung von Gefahrstoffen ein wichtiges Ziel im Chemieunterricht darstellt. Die Mint‐AG unserer Schule führt zu besonderen Anlässen Showexperimente vor, die andere Schüler:innen begeistern und ein gefördertes Interesse für die Naturwissenschaften wecken. Ein solcher Versuch ist auch die modifizierte Trautz‐Schorigin Reaktion, umgangssprachlich besser bekannt als „Zwei‐Farben‐Chemolumineszenz“. Dieses beliebte Showexperiment darf jedoch, aufgrund der jüngsten Verbote der Gefahrstoffverordnung zum Gebrauch von KMR‐Stoffen, wegen der Verwendung von Formalin und Pyrogallol, nicht mehr in das schulische Umfeld implementiert werden. Zwei Schüler der Mint‐AG haben deshalb als „Forschungsprojekt“ eine Ersatzstoffsuche zu dieser Reaktion erarbeitet.Im folgenden Artikel wird beschrieben, wie komplex eine solch simpel erscheinende Suche sein kann, und zu welchen Schwierigkeiten es dabei häufig kommt. Abschließend konnten unter Verwendung der gesundheitlich unbedenklichen und weiterhin kommerziell erhältlichen Chemikalien Dimethylsulfoxid (DMSO) und Gallussäure überzeugende Ergebnisse erzielt werden, womit diese eine geeignete Alternative zu den herkömmlichen Reagenzien darstellen.
The Importance of Reaction Energy in Predicting Chemical Reaction Barriers with Machine Learning Models
Authors: Lalith Nithin , Singh Aayush R. , Gauthier Joseph A. 
Published: March 2024

AbstractImproving our fundamental understanding of complex heterocatalytic processes increasingly relies on electronic structure simulations and microkinetic models based on calculated energy differences. In particular, calculation of activation barriers, usually achieved through compute‐intensive saddle point search routines, remains a serious bottleneck in understanding trends in catalytic activity for highly branched reaction networks. Although the well‐known Brønsted‐Evans‐Polyani (BEP) scaling – a one‐feature linear regression model – has been widely applied in such microkinetic models, they still rely on calculated reaction energies and may not generalize beyond a single facet on a single class of materials, e. g., a terrace sites on transition metals. For highly branched and energetically shallow reaction networks, such as electrochemical CO2 reduction or wastewater remediation, calculating even reaction energies on many surfaces can become computationally intractable due to the combinatorial explosion of states that must be considered. Here, we investigate the feasibility of activation barrier prediction without knowledge of the reaction energy using linear and nonlinear machine learning (ML) models trained on a new database of over 500 dehydrogenation activation barriers. We also find that inclusion of the reaction energy significantly improves both classes of ML models, but complex nonlinear models can achieve performance similar to the simplest BEP scaling when predicting activation barriers on new systems. Additionally, inclusion of the reaction energy significantly improves generalizability to new systems beyond the training set. Our results suggest that the reaction energy is a critical feature to consider when building models to predict activation barriers, indicating that efforts to reliably predict reaction energies through, e. g., the Open Catalyst Project and others, will be an important route to effective model development for more complex systems.
Microbial Community Profiling Protocol with Full‐length 16S rRNA Sequences and Emu
Authors: Curry Kristen D. , Soriano Sirena , Nute Michael G. , Villapol Sonia , Dilthey Alexander , Treangen Todd J. 
Published: March 2024

Abstract16S rRNA targeted amplicon sequencing is an established standard for elucidating microbial community composition. While high‐throughput short‐read sequencing can elicit only a portion of the 16S rRNA gene due to their limited read length, third generation sequencing can read the 16S rRNA gene in its entirety and thus provide more precise taxonomic classification. Here, we present a protocol for generating full‐length 16S rRNA sequences with Oxford Nanopore Technologies (ONT) and a microbial community profile with Emu. We select Emu for analyzing ONT sequences as it leverages information from the entire community to overcome errors due to incomplete reference databases and hardware limitations to ultimately obtain species‐level resolution. This pipeline provides a low‐cost solution for characterizing microbiome composition by exploiting real‐time, long‐read ONT sequencing and tailored software for accurate characterization of microbial communities. © 2024 Wiley Periodicals LLC.Basic Protocol: Microbial community profiling with EmuSupport Protocol 1: Full‐length 16S rRNA microbial sequences with Oxford Nanopore Technologies sequencing platformSupport Protocol 2: Building a custom reference database for Emu
Improving cervical cancer classification in PAP smear images with enhanced segmentation and deep progressive learning‐based techniques
Authors: Mahajan Priyanka , Kaur Prabhpreet 
Published: March 2024

AbstractObjectiveCervical cancer, a prevalent and deadly disease among women, comes second only to breast cancer, with over 700 daily deaths. The Pap smear test is a widely utilized screening method for detecting cervical cancer in its early stages. However, this manual screening process is prone to a high rate of false‐positive outcomes because of human errors. Researchers are using machine learning and deep learning in computer‐aided diagnostic tools to address this issue. These tools automatically analyze and sort cervical cytology and colposcopy images, improving the precision of identifying various stages of cervical cancer.MethodologyThis article uses state‐of‐the‐art deep learning methods, such as ResNet‐50 for categorizing cervical cancer cells to assist medical professionals. The method includes three key steps: preprocessing, segmentation using k‐means clustering, and classifying cancer cells. The model is assessed based on performance metrics viz; precision, accuracy, kappa score, precision, sensitivity, and specificity. In the end, the high success rate shows that the ResNet50 model is a valuable tool for timely detection of cervical cancer.OutputsIn conclusion, the infected cervical region is pinpointed using spatial K‐means clustering and preprocessing operations. This sequence of actions is followed by a progressive learning technique. The Progressive Learning technique then proceeded through several stages: Stage 1 with 64 × 64 images, Stage 2 with 224 × 224 images, Stage 3 with 512 × 512 images, and the final Stage 4 with 1024 × 1024 images. The outcomes show that the suggested model is effective for analyzing Pap smear tests, achieving 97.4% accuracy and approx. 98% kappa score.
Controllable self‐transport of bouncing droplets on ultraslippery surfaces with wedge‐shaped grooves
Authors: Yue Chuchen , Dai Qingwen , Yang Xiaolong , Gachot Carsten , Huang Wei , Wang Xiaolei 
Published: March 2024

AbstractPreventing the accretion of droplets on surfaces is vital and slippery liquid‐infused porous surfaces (SLIPS) have promising application prospects, such as surface self‐cleaning and droplet transportation. In this work, controllable self‐transport of bouncing droplets on ultraslippery surfaces with wedge‐shaped grooves is reported. The impact behaviors of droplets on SLIPS under various impact velocities and diameters are explored, which can be classified as hover, total bounce, partial bounce, Worthington jet, and crush. SLIPS with wedge‐shaped grooves were designed to transport accreted droplets. An energy and transport model is established to explain the impact and self‐transport mechanism, where the Laplace pressure and moving resistance between droplets play a key role. Finally, SLIPS with branched wedge‐shaped grooves were designed for droplet self‐transport and demonstrated advantages. This work provides a general reference for spontaneous motion control of sessile droplets, droplets with initial impacting velocity, or even liquid films.
Recent progress of food‐derived bioactive peptides: Extraction, purification, function, and encapsulation
Authors: Jiang Yunsong , Sun Jinyuan , Chandrapala Jayani , Majzoobi Mahsa , Brennan Charles , Zeng Xin‐An , Sun Baoguo 
Published: March 2024

AbstractFunctional peptides constitute a class of small molecular peptide chains with specific functions in biology and are typically composed of various amino acids. The chemical‐synthesis methods for preparation of functional peptides can bring high toxicity to the human body. Therefore, there is a growing need to explore alternative, safter sources to obtain bioactive peptides. Food‐derived bioactive peptides (FBPs) stand out as an ideal substitution offering safety and accessibility that can be used in health products and pharmaceuticals to elicit their effects. Presently, the extraction, purification, functional properties, and bioavailability of FBPs have been poorly summarized. This review aims to address this gap by summarizing key aspects of FBPs, covering their source, methods of preparation, extraction, isolation, purification, and identification. Additionally, the review explores the functional characteristics and mechanism underlying FBPs. Emphasis is placed on strategies to enhance the stability and bioaccessibility of FBPs, crucial for their successful application in the food and medical industries. Existing research findings suggest that adopting appropriate methods can extract FBPs with high yield and purity. FBPs exhibit both in vitro and in vivo biological activities regulating relevant pathways, showcasing their potential in the medical field. In the quest for improved stability, the application of nanomaterials emerges as a promising strategy. These advancements collectively hint at a bright future for FBPs in both food and medical matrices. As the field progresses, further exploration and refinement of extraction techniques, functional properties, and bioavailability will contribute to unlocking the full potential of FBPs in various applications.
Prediction model of soil water infiltration under moistube irrigation
Authors: Li Binnan , Shen Lixia 
Published: March 2024

AbstractAs a new type of underground water‐saving irrigation method, moistube irrigation has great potential for promotion and development. However, the multi‐factor interaction influence and water infiltration prediction model of soil water infiltration under moistube irrigation need to be improved. This paper aims to obtain soil water infiltration data for different bulk densities (1.2, 1.3 and 1.4 g/cm3) and textures (loam, sandy loam and clay loam) under different pressure heads (1, 1.5 and 2 m) through an indoor moistube irrigation soil water infiltration test. By analysing multiple factors affecting soil water infiltration under moistube irrigation, the calculation method was determined with the initial soil moisture content, pressure head, bulk density and texture as the input variables and the Kostiakov model parameters as the output variables. Finally, the method of optimizing the back propagation (BP) neural network by a genetic algorithm (GA) was used to establish the Kostiakov prediction model of soil moisture in moistube irrigation, and the model was verified with analytics. The results showed that the Kostiakov prediction model based on GA‐BP had high accuracy and good consistency. The research results provide more practical proofs and perfect theoretical supplements for the study of soil water infiltration under moistube irrigation.