bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distinct correlation network of clinical characteristics in suicide attempters having adolescent major depressive disorder with non-suicidal self-injury
Authors: Peng Bo , Wang Ruoxi , Zuo Wenlong , Liu Haitao , Deng Chunshan , Jing Xiaoyuan , Hu Hongtao , Zhao Weitan , Qin Peiwu , Dai Lei , Chen Zuxin , Zhang Yingli , Liu Xin-an 
Published: March 2024

AbstractSuicidal behavior and non-suicidal self-injury (NSSI) are common in adolescent patients with major depressive disorder (MDD). Thus, delineating the unique characteristics of suicide attempters having adolescent MDD with NSSI is important for suicide prediction in the clinical setting. Here, we performed psychological and biochemical assessments of 130 youths having MDD with NSSI. Participants were divided into two groups according to the presence/absence of suicide attempts (SAs). Our results demonstrated that the age of suicide attempters is lower than that of non-attempters in participants having adolescent MDD with NSSI; suicide attempters had higher Barratt Impulsiveness Scale (BIS-11) impulsivity scores and lower serum CRP and cortisol levels than those having MDD with NSSI alone, suggesting levels of cortisol and CRP were inversely correlated with SAs in patients with adolescent MDD with NSSI. Furthermore, multivariate regression analysis revealed that NSSI frequency in the last month and CRP levels were suicidal ideation predictors in adolescent MDD with NSSI, which may indicate that the increased frequency of NSSI behavior is a potential risk factor for suicide. Additionally, we explored the correlation between psychological and blood biochemical indicators to distinguish suicide attempters among participants having adolescent MDD with NSSI and identified a unique correlation network that could serve as a marker for suicide attempters. Our research data further suggested a complex correlation between the psychological and behavioral indicators of impulsivity and anger. Therefore, our study findings may provide clues to identify good clinical warning signs for SA in patients with adolescent MDD with NSSI.
Gut microbial CAZymes markers for depression
Authors: Xie Peijun , Zhou Xingyu , Li Yifan , Wu Jing , Zhang Hanping , Huang Yu , Tan Xunmin , Wen Lu , Olasunkanmi Oluwatayo Israel , Zhou Jingjing , Sun Zuoli , Liu Min , Zhang Guofu , Wang Ying , Xie Peng , Yang Jian , Zheng Peng 
Published: March 2024

AbstractMajor depressive disorder (MDD) is a serious mental illness, characterized by disturbances of gut microbiome, it is required to further explore how the carbohydrate-active enzymes (CAZymes) were changed in MDD. Here, using the metagenomic data from patients with MDD (n = 118) and heath controls (HC, n = 118), we found that the whole CAZymes signatures of MDD were significantly discriminated from that in HC. α-diversity indexes of the two groups were also significantly different. The patients with MDD were characterized by enriched Glycoside Hydrolases (GHs) and Polysaccharide Lyases (PLs) relative to HC. A panel of makers composed of 9 CAZymes mainly belonging to GHs enabled to discriminate the patients with MDD and HC with AUC of 0.824. In addition, this marker panel could classify blinded test samples from the two groups with an AUC of 0.736. Moreover, we found that baseline 4 CAZymes levels also could predict the antidepressant efficacy after adjusted confounding factors and times of depressive episode. Our findings showed that MDD was associated with disturbances of gut CAZymes, which may help to develop diagnostic and predictive tools for depression.
The m6A reader IGF2BP2 regulates glycolytic metabolism and mediates histone lactylation to enhance hepatic stellate cell activation and liver fibrosis
Authors: Zhou Yongqiang , Yan Jiexi , Huang He , Liu Lu , Ren Longfei , Hu Jinjing , Jiang Xiaoxu , Zheng Yan , Xu Lingcong , Zhong Fupeng , Li Xun 
Published: March 2024

AbstractEvidence for the involvement of N6-Methyladenosine (m6A) modification in the etiology and progression of liver fibrosis has emerged and holds promise as a therapeutic target. Insulin-like growth factor 2 (IGF2) mRNA-binding protein 2 (IGF2BP2) is a newly identified m6A-binding protein that functions to enhance mRNA stability and translation. However, its role as an m6A-binding protein in liver fibrosis remains elusive. Here, we observed that IGF2BP2 is highly expressed in liver fibrosis and activated hepatic stellate cells (HSCs), and inhibition of IGF2BP2 protects against HSCs activation and liver fibrogenesis. Mechanistically, as an m6A-binding protein, IGF2BP2 regulates the expression of Aldolase A (ALDOA), a key target in the glycolytic metabolic pathway, which in turn regulates HSCs activation. Furthermore, we observed that active glycolytic metabolism in activated HSCs generates large amounts of lactate as a substrate for histone lactylation. Importantly, histone lactylation transforms the activation phenotype of HSCs. In conclusion, our findings reveal the essential role of IGF2BP2 in liver fibrosis by regulating glycolytic metabolism and highlight the potential of targeting IGF2BP2 as a therapeutic for liver fibrosis.
EMQN best practice guidelines for genetic testing in hereditary breast and ovarian cancer
Authors: McDevitt Trudi , Durkie Miranda , Arnold Norbert , Burghel George J. , Butler Samantha , Claes Kathleen B. M. , Logan Peter , Robinson Rachel , Sheils Katie , Wolstenholme Nicola , Hanson Helen , Turnbull Clare , Hume Stacey 
Published: March 2024

AbstractHereditary Breast and Ovarian Cancer (HBOC) is a genetic condition associated with increased risk of cancers. The past decade has brought about significant changes to hereditary breast and ovarian cancer (HBOC) diagnostic testing with new treatments, testing methods and strategies, and evolving information on genetic associations. These best practice guidelines have been produced to assist clinical laboratories in effectively addressing the complexities of HBOC testing, while taking into account advancements since the last guidelines were published in 2007. These guidelines summarise cancer risk data from recent studies for the most commonly tested high and moderate risk HBOC genes for laboratories to refer to as a guide. Furthermore, recommendations are provided for somatic and germline testing services with regards to clinical referral, laboratory analyses, variant interpretation, and reporting. The guidelines present recommendations where ‘must’ is assigned to advocate that the recommendation is essential; and ‘should’ is assigned to advocate that the recommendation is highly advised but may not be universally applicable. Recommendations are presented in the form of shaded italicised statements throughout the document, and in the form of a table in supplementary materials (Table S4). Finally, for the purposes of encouraging standardisation and aiding implementation of recommendations, example report wording covering the essential points to be included is provided for the most common HBOC referral and reporting scenarios. These guidelines are aimed primarily at genomic scientists working in diagnostic testing laboratories.
Bevacizumab, olaparib, and durvalumab in patients with relapsed ovarian cancer: a phase II clinical trial from the GINECO group
Authors: Freyer Gilles , Floquet Anne , Tredan Olivier , Carrot Aurore , Langlois-Jacques Carole , Lopez Jonathan , Selle Frédéric , Abdeddaim Cyril , Leary Alexandra , Dubot-Poitelon Coraline , Fabbro Michel , Gladieff Laurence , Lamuraglia Michele 
Published: March 2024

AbstractMost patients with advanced ovarian cancer (AOC) ultimately relapse after platinum-based chemotherapy. Combining bevacizumab, olaparib, and durvalumab likely drives synergistic activity. This open-label phase 2 study (NCT04015739) aimed to assess activity and safety of this triple combination in female patients with relapsed high-grade AOC following prior platinum-based therapy. Patients were treated with olaparib (300 mg orally, twice daily), the bevacizumab biosimilar FKB238 (15 mg/kg intravenously, once-every-3-weeks), and durvalumab (1.12 g intravenously, once-every-3-weeks) in nine French centers. The primary endpoint was the non-progression rate at 3 months for platinum-resistant relapse or 6 months for platinum-sensitive relapse per RECIST 1.1 and irRECIST. Secondary endpoints were CA-125 decline with CA-125 ELIMination rate constant K (KELIM-B) per CA-125 longitudinal kinetics over 100 days, progression free survival and overall survival, tumor response, and safety. Non-progression rates were 69.8% (90%CI 55.9%-80.0%) at 3 months for platinum-resistant relapse patients (N = 41), meeting the prespecified endpoint, and 43.8% (90%CI 29.0%-57.4%) at 6 months for platinum-sensitive relapse (N = 33), not meeting the prespecified endpoint. Median progression-free survival was 4.1 months (95%CI 3.5–5.9) and 4.9 months (95%CI 2.9–7.0) respectively. Favorable KELIM-B was associated with better survival. No toxic deaths or major safety signals were observed. Here we show that further investigation of this triple combination may be considered in AOC patients with platinum-resistant relapse.
Identification of a potent palladium-aryldiphosphine catalytic system for high-performance carbonylation of alkenes
Authors: Zhao Kang , Wang Hongli , Li Teng , Liu Shujuan , Benassi Enrico , Li Xiao , Yao Yao , Wang Xiaojun , Cui Xinjiang , Shi Feng 
Published: March 2024

AbstractThe development of stable and efficient ligands is of vital significance to enhance the catalytic performance of carbonylation reactions of alkenes. Herein, an aryldiphosphine ligand (L11) bearing the [Ph2P(ortho-C6H4)]2CH2 skeleton is reported for palladium-catalyzed regioselective carbonylation of alkenes. Compared with the industrially successful Pd/1,2-bis(di-tert-butylphosphinomethyl)benzene catalyst, catalytic efficiency catalyzed by Pd/L11 on methoxycarbonylation of ethylene is obtained, exhibiting better catalytic performance (TON: >2,390,000; TOF: 100,000 h−1; selectivity: >99%) and stronger oxygen-resistance stability. Moreover, a substrate compatibility (122 examples) including chiral and bioactive alkenes or alcohols is achieved with up to 99% yield and 99% regioselectivity. Experimental and computational investigations show that the appropriate bite angle of aryldiphosphine ligand and the favorable interaction of 1,4-dioxane with Pd/L11 synergistically contribute to high activity and selectivity while the electron deficient phosphines originated from electron delocalization endow L11 with excellent oxygen-resistance stability.
Strain-release alkylation of Asp12 enables mutant selective targeting of K-Ras-G12D
Authors: Zheng Qinheng , Zhang Ziyang , Guiley Keelan Z. , Shokat Kevan M. 
Published: March 2024

AbstractK-Ras is the most commonly mutated oncogene in human cancer. The recently approved non-small cell lung cancer drugs sotorasib and adagrasib covalently capture an acquired cysteine in K-Ras-G12C mutation and lock it in a signaling-incompetent state. However, covalent inhibition of G12D, the most frequent K-Ras mutation particularly prevalent in pancreatic ductal adenocarcinoma, has remained elusive due to the lack of aspartate-targeting chemistry. Here we present a set of malolactone-based electrophiles that exploit ring strain to crosslink K-Ras-G12D at the mutant aspartate to form stable covalent complexes. Structural insights from X-ray crystallography and exploitation of the stereoelectronic requirements for attack of the electrophile allowed development of a substituted malolactone that resisted attack by aqueous buffer but rapidly crosslinked with the aspartate-12 of K-Ras in both GDP and GTP state. The GTP-state targeting allowed effective suppression of downstream signaling, and selective inhibition of K-Ras-G12D-driven cancer cell proliferation in vitro and xenograft growth in mice.
Real-time detection of 20 amino acids and discrimination of pathologically relevant peptides with functionalized nanopore
Authors: Zhang Ming , Tang Chao , Wang Zichun , Chen Shanchuan , Zhang Dan , Li Kaiju , Sun Ke , Zhao Changjian , Wang Yu , Xu Mengying , Dai Lunzhi , Lu Guangwen , Shi Hubing , Ren Haiyan , Chen Lu , Geng Jia 
Published: March 2024

AbstractPrecise identification and quantification of amino acids is crucial for many biological applications. Here we report a copper(II)-functionalized Mycobacterium smegmatis porin A (MspA) nanopore with the N91H substitution, which enables direct identification of all 20 proteinogenic amino acids when combined with a machine-learning algorithm. The validation accuracy reaches 99.1%, with 30.9% signal recovery. The feasibility of ultrasensitive quantification of amino acids was also demonstrated at the nanomolar range. Furthermore, the capability of this system for real-time analyses of two representative post-translational modifications (PTMs), one unnatural amino acid and ten synthetic peptides using exopeptidases, including clinically relevant peptides associated with Alzheimer’s disease and cancer neoantigens, was demonstrated. Notably, our strategy successfully distinguishes peptides with only one amino acid difference from the hydrolysate and provides the possibility to infer the peptide sequence.
Detecting radioactive particles in complex environmental samples using real-time autoradiography
Authors: Ang Joyce W. L. , Bongrand Arthur , Duval Samuel , Donnard Jérôme , Jolis Ester M. , Utsunomiya Satoshi , Minomo Kenta , Koivula Risto , Siitari-Kauppi Marja , Law Gareth T. W. 
Published: March 2024

AbstractRadioactive particles often contain very high radioactivity concentrations and are widespread. They pose a potential risk to human health and the environment. Their detection, quantification, and characterization are crucial if we are to understand their impact. Here, we present the use of a real-time autoradiography gaseous detector (using parallel ionization multiplier) to expedite and improve the accuracy of radioactive particle screening in complex environmental samples. First, standard particles were used to assess the detector capabilities (spatial resolution, spectrometry, and artefact contributions), then, we applied the technique to more complex and environmentally relevant samples. The real-time autoradiography technique provides data with a spatial resolution (≲100 µm) suitable for particle analysis in complex samples. Further, it can differentiate between particles predominantly emitting alpha and beta radiation. Here, the technique is applied to radioactive cesium-rich microparticles collected from the Fukushima Daiichi nuclear exclusion zone, showing their accurate detection, and demonstrating the viability of real-time autoradiography in environmental scenarios. Indeed, for more complex samples (radioactive particles in a less radioactive heterogeneous background mix of minerals), the technique permits relatively high selectivity for radioactive particle screening (up to 61.2% success rate) with low false positive percentages (~ 1%).
Single-polyp metabolomics for coral health assessment
Authors: Iguchi Akira , Iijima Mariko , Mizusawa Nanami , Ohno Yoshikazu , Yasumoto Ko , Suzuki Atsushi , Suga Shunichi , Tanaka Ken , Zaitsu Kei 
Published: March 2024

AbstractCoral reef ecosystems supported by environmentally sensitive reef-building corals face serious threats from human activities. Our understanding of these reef threats is hampered by the lack of sufficiently sensitive coral environmental impact assessment systems. In this study, we established a platform for metabolomic analysis at the single-coral-polyp level using state-of-the-art mass spectrometry (probe electrospray ionization/tandem mass spectrometry; PESI/MS/MS) capable of fine-scale analysis. We analyzed the impact of the organic UV filter, benzophenone (BP), which has a negative impact on corals. We also analyzed ammonium and nitrate samples, which affect the environmental sensitivity of coral-zooxanthella (Symbiodiniaceae) holobionts, to provide new insights into coral biology with a focus on metabolites. The method established in this study breaks new ground by combining PESI/MS/MS with a technique for coral polyps that can control the presence or absence of zooxanthellae in corals, enabling functions of zooxanthellae to be assessed on a polyp-by-polyp basis for the first time. This system will clarify biological mechanisms of corals and will become an important model system for environmental impact assessment using marine organisms.
A publicly available deep learning model and dataset for segmentation of breast, fibroglandular tissue, and vessels in breast MRI
Authors: Lew Christopher O. , Harouni Majid , Kirksey Ella R. , Kang Elianne J. , Dong Haoyu , Gu Hanxue , Grimm Lars J. , Walsh Ruth , Lowell Dorothy A. , Mazurowski Maciej A. 
Published: March 2024

AbstractBreast density, or the amount of fibroglandular tissue (FGT) relative to the overall breast volume, increases the risk of developing breast cancer. Although previous studies have utilized deep learning to assess breast density, the limited public availability of data and quantitative tools hinders the development of better assessment tools. Our objective was to (1) create and share a large dataset of pixel-wise annotations according to well-defined criteria, and (2) develop, evaluate, and share an automated segmentation method for breast, FGT, and blood vessels using convolutional neural networks. We used the Duke Breast Cancer MRI dataset to randomly select 100 MRI studies and manually annotated the breast, FGT, and blood vessels for each study. Model performance was evaluated using the Dice similarity coefficient (DSC). The model achieved DSC values of 0.92 for breast, 0.86 for FGT, and 0.65 for blood vessels on the test set. The correlation between our model’s predicted breast density and the manually generated masks was 0.95. The correlation between the predicted breast density and qualitative radiologist assessment was 0.75. Our automated models can accurately segment breast, FGT, and blood vessels using pre-contrast breast MRI data. The data and the models were made publicly available.
The use of wearable resistance and weighted vest for sprint performance and kinematics: a systematic review and meta-analysis
Authors: Bertochi Gabriel Felipe Arantes , Tasinafo Júnior Márcio Fernando , Santos Izabela A. , Sasaki Jeffer Eidi , Mota Gustavo R. , Jordão Gabriela Gregorutti , Puggina Enrico Fuini 
Published: March 2024

AbstractWearable resistance (WR) and weighted vests (WV) can be used in almost all training conditions to enhance sprint performance; however, positioning and additional mass are different in WV and WR strategies, affecting performance and kinematics differently. We aimed to systematically review the literature, searching for intervention studies that reported the acute or chronic kinematic and performance impact of WV and WR and comparing them. We analyzed Pubmed, Embase, Scopus, and SPORTDiscuss databases for longitudinal and cross-over studies investigating sprint performance or kinematics using an inverse-variance with a random-effect method for meta-analysis. After the eligibility assessment, 25 studies were included in the meta-analysis. Cross-over WR and WV studies found significantly higher sprint times and higher ground contact times (CT) compared to unloaded (UL) conditions. However, WR presented a lower step frequency (SF) compared to UL, whereas WV presented a lower step length (SL). Only one study investigated the chronic adaptations for WR, indicating a superiority of the WR group on sprint time compared to the control group. However, no difference was found chronically for WV regarding sprint time, CT, and flight time (FT). Our findings suggest that using WV and WR in field sports demonstrates overload sprint gesture through kinematic changes, however, WR can be more suitable for SF-reliant athletes and WV for SL-reliant athletes. Although promising for chronic performance improvement, coaches and athletes should carefully consider WV and WR use since there is no supporting evidence that WV or WR will impact sprint performance, CT, and FT.
Optimization design of brushless DC motor based on improved JAYA algorithm
Authors: Cheng Yuan , Lyu Xueli , Mao Shasha 
Published: March 2024

AbstractBrushless direct current motor is widely used in industrial production because of its simple structure, wide speed range and low noise. To improve the operation efficiency of brushless DC motor and reduce the production and application costs, the optimization of brushless DC motor is analyzed by introducing the JAYA algorithm. This method determines the optimal parameters of a brushless DC motor using the theory of electromagnetic structure parameter selection and efficiency calculation. The population diversity of the JAYA algorithm is improved through an empirical learning strategy, and an adaptive strategy is introduced to balance the development ability and search performance of the algorithm. This ensures population diversity and improves convergence speed. The experiment showcases that the improved JAYA algorithm has a lower rank average in unimodal function operations, demonstrating stronger local development ability and better stability. It exhibits strong search ability in many local optima of multimodal functions. Moreover, the motor's average efficiency after optimization is 94.48%. The algorithm reaches the global optimum after approximately 40 iterations and offers faster convergence speed and higher accuracy. The adaptive JAYA algorithm is stable at around 93% when the number of iterations reaches 90, with a maximum efficiency of 95.3%. It is 5–12 percentage points higher than the other three comparison algorithms. The optimal solution of the motor parameters in the adaptive JAYA algorithm is closest to the theoretical parameter optimization value, meeting both the constraints of variables and the constraints of the model. The stator diameter, tooth magnetic induction, winding current density, air gap magnetic induction, and stator yoke magnetic induction values are 201.5 mm, 1.8 T, 2.049 A/mm2, 0.63 T, and 0.91 T, respectively. The research overcomes the problem of parameter optimization in the optimization design of brushless DC motor, improving their economic value of brushless DC motor in industrial production and application.
New oxadiazole and pyrazoline derivatives as anti-proliferative agents targeting EGFR-TK: design, synthesis, biological evaluation and molecular docking study
Authors: Serag Marwa I. , Tawfik Samar S. , Badr Sahar M. I. , Eisa Hassan M. 
Published: March 2024

AbstractTwo new series of oxadiazole and pyrazoline derivatives were designed and synthesized as promising EGFR-TK inhibitors. The in vitro antiproliferative activity was studied against three human cancer cell lines; HCT116, HepG-2 and MCF7 using MTT assay. Compound 10c showed the most potent anticancer activity against all cancer cell lines, with IC50 range of 1.82 to 5.55 μM, while proving safe towards normal cells WI-38 (IC50 = 41.17 μM) compared to the reference drug doxorubicin (IC50 = 6.72 μM). The most active candidates 5a, 9b, 10a, 10b and 10c were further assessed for their EGFR-TK inhibition. The best of which, compounds 5a and 10b showed IC50 of 0.09 and 0.16 μM respectively compared to gefitinib (IC50 = 0.04 μM). Further investigation against other EGFR family members, showed that 5a displayed good activities against HER3 and HER4 with IC50 values 0.18 and 0.37 µM, respectively compared to gefitinib (IC50 = 0.35 and 0.58 µM, respectively). Furthermore, 5a was evaluated for cell cycle distribution and apoptotic induction on HepG-2 cells. It induced mitochondrial apoptotic pathway and increased accumulation of ROS. Molecular docking study came in agreement with the biological results. Compounds 5a and 10b showed promising drug-likeness with good physicochemical properties.