bluuebunny/crossref_metadata_2025_split huggingface dataset:
Patterns of neural activity in response to threatening faces are predictive of autistic traits: modulatory effects of oxytocin receptor genotype
Authors: Zheng Xiaoxiao , Zhou Feng , Fu Meina , Xu Lei , Wang Jiayuan , Li Jialin , Li Keshuang , Sindermann Cornelia , Montag Christian , Becker Benjamin , Zhan Yang , Kendrick Keith M. 
Published: March 2024

AbstractAutistic individuals generally demonstrate impaired emotion recognition but it is unclear whether effects are emotion-specific or influenced by oxytocin receptor (OXTR) genotype. Here we implemented a dimensional approach using an implicit emotion recognition task together with functional MRI in a large cohort of neurotypical adult participants (N = 255, male = 131, aged 17–29 years) to establish associations between autistic traits and neural and behavioral responses to specific face emotions, together with modulatory effects of OXTR genotype. A searchlight-based multivariate pattern analysis (MVPA) revealed an extensive network of frontal, basal ganglia, cingulate and limbic regions exhibiting significant predictability for autistic traits from patterns of responses to angry relative to neutral expression faces. Functional connectivity analyses revealed a genotype interaction (OXTR SNPs rs2254298, rs2268491) for coupling between the orbitofrontal cortex and mid-cingulate during angry expression processing, with a negative association between coupling and autistic traits in the risk-allele group and a positive one in the non-risk allele group. Overall, results indicate extensive emotion-specific associations primarily between patterns of neural responses to angry faces and autistic traits in regions processing motivation, reward and salience but not in early visual processing. Functional connections between these identified regions were not only associated with autistic traits but also influenced by OXTR genotype. Thus, altered patterns of neural responses to threatening faces may be a potential biomarker for autistic symptoms although modulatory influences of OXTR genotype need to be taken into account.
PANoptosis: bridging apoptosis, pyroptosis, and necroptosis in cancer progression and treatment
Authors: Gao Jie , Xiong Anying , Liu Jiliu , Li Xiaolan , Wang Junyi , Zhang Lei , Liu Yao , Xiong Ying , Li Guoping , He Xiang 
Published: March 2024

AbstractThis comprehensive review explores the intricate mechanisms of PANoptosis and its implications in cancer. PANoptosis, a convergence of apoptosis, pyroptosis, and necroptosis, plays a crucial role in cell death and immune response regulation. The study delves into the molecular pathways of each cell death mechanism and their crosstalk within PANoptosis, emphasizing the shared components like caspases and the PANoptosome complex. It highlights the significant role of PANoptosis in various cancers, including respiratory, digestive, genitourinary, gliomas, and breast cancers, showing its impact on tumorigenesis and patient survival rates. We further discuss the interwoven relationship between PANoptosis and the tumor microenvironment (TME), illustrating how PANoptosis influences immune cell behavior and tumor progression. It underscores the dynamic interplay between tumors and their microenvironments, focusing on the roles of different immune cells and their interactions with cancer cells. Moreover, the review presents new breakthroughs in cancer therapy, emphasizing the potential of targeting PANoptosis to enhance anti-tumor immunity. It outlines various strategies to manipulate PANoptosis pathways for therapeutic purposes, such as targeting key signaling molecules like caspases, NLRP3, RIPK1, and RIPK3. The potential of novel treatments like immunogenic PANoptosis-initiated therapies and nanoparticle-based strategies is also explored.
Generation of glioblastoma in mice engrafted with human cytomegalovirus-infected astrocytes
Authors: Guyon Joris , Haidar Ahmad Sandy , El Baba Ranim , Le Quang Mégane , Bikfalvi Andreas , Daubon Thomas , Herbein Georges 
Published: March 2024

AbstractMounting evidence is identifying human cytomegalovirus (HCMV) as a potential oncogenic virus. HCMV has been detected in glioblastoma multiforme (GB). Herewith, we present the first experimental evidence for the generation of CMV-Elicited Glioblastoma Cells (CEGBCs) possessing glioblastoma-like traits that lead to the formation of glioblastoma in orthotopically xenografted mice. In addition to the already reported oncogenic HCMV-DB strain, we isolated three HCMV clinical strains from GB tissues that transformed HAs toward CEGBCs and generated spheroids from CEGBCs that resulted in the appearance of glioblastoma-like tumors in xenografted mice. These tumors were nestin-positive mostly in the invasive part surrounded by GFAP-positive reactive astrocytes. The glioblastoma immunohistochemistry phenotype was confirmed by EGFR and cMet gene amplification in the tumor parallel to the detection of HCMV IE and UL69 genes and proteins. Our results fit with an HCMV-induced glioblastoma model of oncogenesis in vivo which will open the door to new therapeutic approaches and assess the anti-HCMV treatment as well as immunotherapy in fighting GB which is characterized by poor prognosis.
Mycobacterium tuberculosis inhibits METTL14-mediated m6A methylation of Nox2 mRNA and suppresses anti-TB immunity
Authors: Ma Mingtong , Duan Yongjia , Peng Cheng , Wu You , Zhang Xinning , Chang Boran , Wang Fei , Yang Hua , Zheng Ruijuan , Cheng Hongyu , Cheng Yuanna , He Yifan , Huang Jingping , Lei Jinming , Ma Hanyu , Li Liru , Wang Jie , Huang Xiaochen , Tang Fen , Liu Jun , Li Jinsong , Ying Ruoyan , Wang Peng , Sha Wei , Gao Yawei , Wang Lin , Ge Baoxue 
Published: March 2024

AbstractInternal N6-methyladenosine (m6A) modifications are among the most abundant modifications of messenger RNA, playing a critical role in diverse biological and pathological processes. However, the functional role and regulatory mechanism of m6A modifications in the immune response to Mycobacterium tuberculosis infection remains unknown. Here, we report that methyltransferase-like 14 (METTL14)-dependent m6A methylation of NAPDH oxidase 2 (Nox2) mRNA was crucial for the host immune defense against M. tuberculosis infection and that M. tuberculosis-secreted antigen EsxB (Rv3874) inhibited METTL14-dependent m6A methylation of Nox2 mRNA. Mechanistically, EsxB interacted with p38 MAP kinase and disrupted the association of TAB1 with p38, thus inhibiting the TAB1-mediated autophosphorylation of p38. Interaction of EsxB with p38 also impeded the binding of p38 with METTL14, thereby inhibiting the p38-mediated phosphorylation of METTL14 at Thr72. Inhibition of p38 by EsxB restrained liquid–liquid phase separation (LLPS) of METTL14 and its subsequent interaction with METTL3, preventing the m6A modification of Nox2 mRNA and its association with the m6A-binding protein IGF2BP1 to destabilize Nox2 mRNA, reduce ROS levels, and increase intracellular survival of M. tuberculosis. Moreover, deletion or mutation of the phosphorylation site on METTL14 impaired the inhibition of ROS level by EsxB and increased bacterial burden or histological damage in the lungs during infection in mice. These findings identify a previously unknown mechanism that M. tuberculosis employs to suppress host immunity, providing insights that may empower the development of effective immunomodulators that target M. tuberculosis.
Genomic insights into familial adenomatous polyposis: unraveling a rare case with whole APC gene deletion and intellectual disability
Authors: Tanabe Hiroki , Ijiri Masami , Takahashi Kenji , Sasagawa Honoka , Kamanaka Tomomi , Kuroda Shohei , Sato Hiroki , Sarashina Takeo , Mizukami Yusuke , Makita Yoshio , Okumura Toshikatsu 
Published: March 2024

Abstract
A young patient diagnosed with advanced colon cancer and liver metastasis was found to have familial adenomatous polyposis (FAP) through comprehensive genomic analysis. Whole-genome array comparative genomic hybridization (aCGH) revealed germline deletions at chromosome 5q22.1-22.2 encompassing the entire APC gene. The patient and her son exhibited mild intellectual disability without developmental delay. This case highlights the need for further exploration of the characteristics associated with whole APC deletions. aCGH is a valuable tool for studying FAP and provides a detailed analysis of large deletions.
Predicting mortality from AI cardiac volumes mass and coronary calcium on chest computed tomography
Authors: Miller Robert J. H. , Killekar Aditya , Shanbhag Aakash , Bednarski Bryan , Michalowska Anna M. , Ruddy Terrence D. , Einstein Andrew J. , Newby David E. , Lemley Mark , Pieszko Konrad , Van Kriekinge Serge D. , Kavanagh Paul B. , Liang Joanna X. , Huang Cathleen , Dey Damini , Berman Daniel S. , Slomka Piotr J. 
Published: March 2024

AbstractChest computed tomography is one of the most common diagnostic tests, with 15 million scans performed annually in the United States. Coronary calcium can be visualized on these scans, but other measures of cardiac risk such as atrial and ventricular volumes have classically required administration of contrast. Here we show that a fully automated pipeline, incorporating two artificial intelligence models, automatically quantifies coronary calcium, left atrial volume, left ventricular mass, and other cardiac chamber volumes in 29,687 patients from three cohorts. The model processes chamber volumes and coronary artery calcium with an end-to-end time of ~18 s, while failing to segment only 0.1% of cases. Coronary calcium, left atrial volume, and left ventricular mass index are independently associated with all-cause and cardiovascular mortality and significantly improve risk classification compared to identification of abnormalities by a radiologist. This automated approach can be integrated into clinical workflows to improve identification of abnormalities and risk stratification, allowing physicians to improve clinical decision-making.
An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations
Authors: Noh Juran , Doan Hieu A. , Job Heather , Robertson Lily A. , Zhang Lu , Assary Rajeev S. , Mueller Karl , Murugesan Vijayakumar , Liang Yangang 
Published: March 2024

AbstractSolubility of redox-active molecules is an important determining factor of the energy density in redox flow batteries. However, the advancement of electrolyte materials discovery has been constrained by the absence of extensive experimental solubility datasets, which are crucial for leveraging data-driven methodologies. In this study, we design and investigate a highly automated workflow that synergizes a high-throughput experimentation platform with a state-of-the-art active learning algorithm to significantly enhance the solubility of redox-active molecules in organic solvents. Our platform identifies multiple solvents that achieve a remarkable solubility threshold exceeding 6.20 M for the archetype redox-active molecule, 2,1,3-benzothiadiazole, from a comprehensive library of more than 2000 potential solvents. Significantly, our integrated strategy necessitates solubility assessments for fewer than 10% of these candidates, underscoring the efficiency of our approach. Our results also show that binary solvent mixtures, particularly those incorporating 1,4-dioxane, are instrumental in boosting the solubility of 2,1,3-benzothiadiazole. Beyond designing an efficient workflow for developing high-performance redox flow batteries, our machine learning-guided high-throughput robotic platform presents a robust and general approach for expedited discovery of functional materials.
Cell surface patching via CXCR4-targeted nanothreads for cancer metastasis inhibition
Authors: Zhou Minglu , Liu Chendong , Li Bo , Li Junlin , Zhang Ping , Huang Yuan , Li Lian 
Published: March 2024

AbstractThe binding of therapeutic antagonists to their receptors often fail to translate into adequate manipulation of downstream pathways. To fix this ‘bug’, here we report a strategy that stitches cell surface ‘patches’ to promote receptor clustering, thereby synchronizing subsequent mechano-transduction. The “patches” are sewn with two interactable nanothreads. In sequence, Nanothread-1 strings together adjacent receptors while presenting decoy receptors. Nanothread-2 then targets these decoys multivalently, intertwining with Nanothread-1 into a coiled-coil supramolecular network. This stepwise actuation clusters an extensive vicinity of receptors, integrating mechano-transduction to disrupt signal transmission. When applied to antagonize chemokine receptors CXCR4 expressed in metastatic breast cancer of female mice, this strategy elicits and consolidates multiple events, including interception of metastatic cascade, reversal of immunosuppression, and potentiation of photodynamic immunotherapy, reducing the metastatic burden. Collectively, our work provides a generalizable tool to spatially rearrange cell-surface receptors to improve therapeutic outcomes.
Revolutionizing heart disease prediction with quantum-enhanced machine learning
Authors: Babu S. Venkatesh , Ramya P. , Gracewell Jeffin 
Published: March 2024

AbstractThe recent developments in quantum technology have opened up new opportunities for machine learning algorithms to assist the healthcare industry in diagnosing complex health disorders, such as heart disease. In this work, we summarize the effectiveness of QuEML in heart disease prediction. To evaluate the performance of QuEML against traditional machine learning algorithms, the Kaggle heart disease dataset was used which contains 1190 samples out of which 53% of samples are labeled as positive samples and rest 47% samples are labeled as negative samples. The performance of QuEML was evaluated in terms of accuracy, precision, recall, specificity, F1 score, and training time against traditional machine learning algorithms. From the experimental results, it has been observed that proposed quantum approaches predicted around 50.03% of positive samples as positive and an average of 44.65% of negative samples are predicted as negative whereas traditional machine learning approaches could predict around 49.78% of positive samples as positive and 44.31% of negative samples as negative. Furthermore, the computational complexity of QuEML was measured which consumed average of 670 µs for its training whereas traditional machine learning algorithms could consume an average 862.5 µs for training. Hence, QuEL was found to be a promising approach in heart disease prediction with an accuracy rate of 0.6% higher and training time of 192.5 µs faster than that of traditional machine learning approaches.
CD4+ T cell mitochondrial genotype in Multiple Sclerosis: a cross-sectional and longitudinal analysis
Authors: Cortes-Figueiredo Filipe , Asseyer Susanna , Chien Claudia , Zimmermann Hanna G. , Ruprecht Klemens , Schmitz-Hübsch Tanja , Bellmann-Strobl Judith , Paul Friedemann , Morais Vanessa A. 
Published: March 2024

AbstractMultiple Sclerosis (MS) is a chronic autoimmune demyelinating disease of the central nervous system (CNS), with a largely unknown etiology, where mitochondrial dysfunction likely contributes to neuroaxonal loss and brain atrophy. Mirroring the CNS, peripheral immune cells from patients with MS, particularly CD4+ T cells, show inappropriate mitochondrial phenotypes and/or oxidative phosphorylation (OxPhos) insufficiency, with a still unknown contribution of mitochondrial DNA (mtDNA). We hypothesized that mitochondrial genotype in CD4+ T cells might influence MS disease activity and progression. Thus, we performed a retrospective cross-sectional and longitudinal study on patients with a recent diagnosis of either Clinically Isolated Syndrome (CIS) or Relapsing–Remitting MS (RRMS) at two timepoints: 6 months (VIS1) and 36 months (VIS2) after disease onset. Our primary outcomes were the differences in mtDNA extracted from CD4+ T cells between: (I) patients with CIS/RRMS (PwMS) at VIS1 and age- and sex-matched healthy controls (HC), in the cross-sectional analysis, and (II) different diagnostic evolutions in PwMS from VIS1 to VIS2, in the longitudinal analysis. We successfully performed mtDNA whole genome sequencing (mean coverage: 2055.77 reads/base pair) in 183 samples (61 triplets). Nonetheless, mitochondrial genotype was not associated with a diagnosis of CIS/RRMS, nor with longitudinal diagnostic evolution.
Resonant Raman scattering of few layers CrBr3
Authors: Kipczak Łucja , Karmakar Arka , Grzeszczyk Magdalena , Janiszewska Róża , Woźniak Tomasz , Chen Zhaolong , Pawłowski Jan , Watanabe Kenji , Taniguchi Takashi , Babiński Adam , Koperski Maciej , Molas Maciej R. 
Published: March 2024

AbstractWe investigate the vibrational and magnetic properties of thin layers of chromium tribromide (CrBr3) with a thickness ranging from three to twenty layers (3–20 L) revealed by the Raman scattering (RS) technique. Systematic dependence of the RS process efficiency on the energy of the laser excitation is explored for four different excitation energies: 1.96 eV, 2.21 eV, 2.41 eV, and 3.06 eV. Our characterization demonstrates that for 12 L CrBr3, 3.06 eV excitation could be considered resonant with interband electronic transitions due to the enhanced intensity of the Raman-active scattering resonances and the qualitative change in the Raman spectra. Polarization-resolved RS measurements for 12 L CrBr3 and first-principles calculations allow us to identify five observable phonon modes characterized by distinct symmetries, classified as the A$$_\text {g}$$

g

and E$$_\text {g}$$

g

modes. The evolution of phonon modes with temperature for a 16 L CrBr3 encapsulated in hexagonal boron nitride flakes demonstrates alterations of phonon energies and/or linewidths of resonances indicative of a transition between the paramagnetic and ferromagnetic state at Curie temperature ($$T_\text {C} \approx 50$$

T
C

≈
50

K). The exploration of the effects of thickness on the phonon energies demonstrated small variations pronounces exclusively for the thinnest layers in the vicinity of 3–5 L. We propose that this observation can be due to the strong localization in the real space of interband electronic excitations, limiting the effects of confinement for resonantly excited Raman modes to atomically thin layers.
Self-similarity study based on the particle sizes of coal-series diatomite
Authors: Cheng Liang , Wang Guangming , Ma Zhijun , Guo Hao , Gao Ye , Zhang Qi , Gao Jing , Fu Hanghang 
Published: March 2024

AbstractCoal-series diatomite (CSD) is widely distributed in China and has poor functional and structural properties and exhibits limited utilization of high value-added materials, resulting in a serious waste of resources and tremendous pressure on the environment. Moreover, due to differences in the mineralogical characteristics of CSD, different particle size scales (PSSs) have different functional structures and exhibit different self-similarities. In this study, we took CSD as the research object and PSS as the entry point and carried out a self-similarity study based on gas adsorption and an image processing method to illustrate the microstructures and self-similarities of different PSSs. The results showed that the pore structure of the CSD was dominated by mesopores and macropores and basically lacked micropores. The fractal dimensions were calculated with the Frenkel-Haisey-Hill (FHH) model and Menger model, and the DF1 values for − 0.025 mm and − 2 mm were 2.51 and 2.48, respectively, and the DM1 values were 3.75 and 3.79, respectively, indicating that the mesopore structure of the fine PSS was complex, whereas macropores were present in the coarse PSS. MATLAB was programmed to obtain grayscale thresholds, binarized images, grayscale histograms, three-dimensional (3D) reconstruction images and box dimensions, which enabled us to observe the microstructures and self-similarities of the CSD. Self-similarity studies based on particle sizes are very important for functional application of CSD.Please note that article title mismatch between MS and JS we have followed MS, kindly check and cofirm.Yes, I have checked and confirmed.Kindly check and confirm corresponding author mail id are correctly identified.Yes, I have checked and confirmed.
No gender differences in the 24-month course of non-invasive liver fibrosis markers after DAA therapy in HCV-mono and HCV/HIV-coinfected patients
Authors: Collazos Julio , Pérez-Is Laura , de la Fuente Belén , Morano Luis , Rivas-Carmenado Maria , Rodriguez Manuel , Romero-Favela Adolfo , de Jesús Fonseca-González Galilea , Melón Santiago , Diaz-Arias Javier , Valle-Garay Eulalia , Asensi Víctor 
Published: March 2024

AbstractUntreated HCV mono and HCV/HIV coinfected women have lower degrees of liver fibrosis (LF) compared to men. Direct acting antiviral (DAA) therapy attains viral eradication in > 90% of patients with progressive LF decline in parallel. Gender-related differences in LF regression in the long term assessed by non-invasive liver fibrosis markers (NILFM) in HCV mono and HCV/HIV coinfected after DAA treatment have not been explored so far. 374 HCV-infected adult patients, 214 of them HCV/HIV coinfected, were followed-up for 24 months after starting DAA therapy. LF was assessed by NILFM: transient elastometry (TE) and several biochemical indexes (APRI, Forns, FIB-4). Men had significantly more advanced LF at baseline than women assessed by NILFM. No LF differences at baseline in age, HIV coinfection course (CD4, HIV viral load), and HCV features (HCV viral load, genotype) were detected. No significant gender differences in LF decline after comparing 24-month and baseline LF values were observed. LF changes after DAA therapy were similar in HCV mono and HCV/HIV coinfected patients and in both sexes. Gender did not influence the course of LF decline after DAA assessed by NILFM: TE (P = 0.8), APRI (P = 0.9), Forns (P = 0.4) and FIB-4 (P = 0.7) by multivariate analysis. No gender differences in the 24 month LF decline after DAA with independence of having HCV mono or HCV/HIV coinfection were found.
Signal mining and risk analysis of Alprazolam adverse events based on the FAERS database
Authors: Huang Feng , San Xiao , Liu Qingqian , Zhu Haohao , Xu Wenrong 
Published: March 2024

AbstractThis study aims to evaluate the safety of Alprazolam by analyzing the FAERS database, provide data analysis for monitoring adverse drug reactions. This research encompasses adverse event (AE) reports related to Alprazolam from the first quarter of 2004 to the second quarter of 2023. Four signal mining and analysis methods were utilized, including Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM). Further exploration was conducted regarding patient characteristics and types of AEs. A total of 23,575 AE reports in which Alprazolam was the primary suspect drug were collected, identifying 347 Preferred Term (PT) signals and 27 System Organ Classes (SOCs). The number of AE reports increased annually, especially in 2015, 2018, 2019, and 2020. The main affected groups were females and the age range of 18 to 45. Psychiatric disorders, Nervous system disorders, and Gastrointestinal disorders were the most common the organ system in which the AEs occurred. There is a certain risk of drug abuse and suicide with Alprazolam. Most notably, several AEs not recorded in the Alprazolam leaflet appeared among the top 30 PTs in signal strength, including but not limited to Benzodiazepine drug level abnormal, Acquired amegakaryocytic thrombocytopenia, Cutaneous T-cell dyscrasia, and Coronary No-reflow Phenomenon. For the first time, AEs related to the cardiovascular system and platelet function were unveiled. The severe AE reports that resulted in "hospitalization" and "death" accounted for 30.96% and 21.86%. This study highlights the risks of suicide and misuse of Alprazolam. Other potential severe or fatal AEs, such as those related to the cardiovascular system, platelet function, and others, require further research to determine their precise mechanisms and risk factors.