bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrated analysis of how gender and body weight affect the intestinal microbial diversity of Gymnocypris chilianensis
Authors: Zhao Zhongmeng , Zhao Han , Zhang Lu , Huang Zhipeng , Ke Hongyu , Liu Ya , Duan Yuanliang , Li Huadong , Wang Xiongyan , Li Qiang 
Published: May 2023

AbstractIntestinal microorganisms that living in the mucosa and contents of the gastrointestinal tract of animals, have close links with their hosts over a long evolutionary history. The community structure of the fish intestinal microbiota is associated with food, living environment, and the growth stage. To screen for potential probiotics that can be used for regulating breeding behaviors, this study focused on the diversity of fish intestinal microorganisms. This study aimed to investigate the effects of sex and body weight on the intestinal microbial diversity ofGymnocypris chilianensisin the wild. The results showed that the significant high diversity and richness of intestinal microbiota were fould in heavier individuals, and males. The dominant bacterial phyla ofG. chilianensiswere Proteobacteria, Firmicutes, and Bacteroidetes. In addition, the abundance of Firmicutes varied significantly among different body weights. The genus profile revealed that small individuals were dominated byWeissella, while females were dominated byAeromonas, and both large individuals and males were dominated by other genera. Phylogenetic relationships and UPGMA clustering analysis showed significant differences among the groups. In general, the two main factors that have an effect on the intestinal microbiota diversity of wildG. chilianensisare sex and body weight.
Modelling environmental DNA transport in rivers reveals highly resolved spatio-temporal biodiversity patterns
Authors: Carraro Luca , Blackman Rosetta C. , Altermatt Florian 
Published: May 2023

AbstractThe ever-increasing threats to riverine ecosystems call for novel approaches for highly resolved biodiversity assessments across taxonomic groups and spatio-temporal scales. Recent advances in the joint use of environmental DNA (eDNA) data and eDNA transport models in rivers (e.g., eDITH) allow uncovering the full structure of riverine biodiversity, hence elucidating ecosystem processes and supporting conservation measures. We applied eDITH to a metabarcoding dataset covering three taxonomic groups (fish, invertebrates, bacteria) and three seasons for a catchment sampled for eDNA at 73 sites. We upscaled eDNA-based biodiversity predictions to approximately 1900 reaches, and assessed α- and β-diversity patterns across seasons and taxonomic groups over the whole network. Genus richness predicted by eDITH was generally higher than values from direct eDNA analysis. Both predicted α- and β-diversity varied depending on season and taxonomic group. Predicted fish α-diversity increased downstream in all seasons, while invertebrate and bacteria α-diversity either decreased downstream or were unrelated to network position. Spatial β-diversity mostly decreased downstream, especially for bacteria. The eDITH model yielded a more refined assessment of freshwater biodiversity as compared to raw eDNA data, both in terms of spatial coverage, diversity patterns and effect of covariates, thus providing a more complete picture of freshwater biodiversity.
Improving the efficiency of RMSProp optimizer by utilizing Nestrove in deep learning
Authors: Elshamy Reham , Abu-Elnasr Osama , Elhoseny Mohamed , Elmougy Samir 
Published: May 2023

AbstractThere are several methods that have been discovered to improve the performance of Deep Learning (DL). Many of these methods reached the best performance of their models by tuning several parameters such as Transfer Learning, Data augmentation, Dropout, and Batch Normalization, while other selects the best optimizer and the best architecture for their model. This paper is mainly concerned with the optimization algorithms in DL. It proposes a modified version of Root Mean Squared Propagation (RMSProp) algorithm, called NRMSProp, to improve the speed of convergence, and to find the minimum of the loss function quicker than the original RMSProp optimizer. Moreover, NRMSProp takes the original algorithm, RMSProp, a step further by using the advantages of Nesterov Accelerated Gradient (NAG). It also takes in consideration the direction of the gradient at the next step, with respect to the history of the previous gradients, and adapts the value of the learning rate. As a result, this modification helps NRMSProp to convergence quicker than the original RMSProp, without any increase in the complexity of the RMSProp. In this work, many experiments had been conducted to evaluate the performance of NRMSProp with performing several tests with deep Convolution Neural Networks (CNNs) using different datasets on RMSProp, Adam, and NRMSProp optimizers. The experimental results showed that NRMSProp has achieved effective performance, and accuracy up to 0.97 in most cases, in comparison to RMSProp and Adam optimizers, without any increase in the complexity of the algorithm and with fine amount of memory and time.
Feasibility of spinal cord imaging at 7 T using rosette trajectory with magnetization transfer preparation and compressed sensing
Authors: Mahmud Sultan Z. , Denney Thomas S. , Bashir Adil 
Published: May 2023

AbstractMRI is a valuable diagnostic tool to investigate spinal cord (SC) pathology. SC MRI can benefit from the increased signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) at ultra-high fields such as 7 T. However, SC MRI acquisitions with routine Cartesian readouts are prone to image artifacts caused by physiological motion. MRI acquisition techniques with non-Cartesian readouts such as rosette can help reduce motion artifacts. The purpose of this study was to demonstrate the feasibility of high-resolution SC imaging using rosette trajectory with magnetization transfer preparation (MT-prep) and compressed sensing (CS) at 7 T. Five healthy volunteers participated in the study. Images acquired with rosette readouts demonstrated reduced motion artifacts compared to the standard Cartesian readouts. The combination of multi-echo rosette-readout images improved the CNR by approximately 50% between the gray matter (GM) and white matter (WM) compared to single-echo images. MT-prep images showed excellent contrast between the GM and WM with magnetization transfer ratio (MTR) and cerebrospinal fluid normalized MT signal (MTCSF) = 0.12 ± 0.017 and 0.74 ± 0.013, respectively, for the GM; and 0.18 ± 0.011 and 0.58 ± 0.009, respectively, for the WM. Under-sampled acquisition using rosette readout with CS reconstruction demonstrated up to 6 times faster scans with comparable image quality as the fully-sampled acquisition.
Proteomics and secreted lipidomics of mouse-derived bone marrow cells exposed to a lethal level of ionizing radiation
Authors: Tatara Yota , Monzen Satoru 
Published: May 2023

AbstractHigh doses of ionizing radiation (IR) exposure can lead to the development of severe acute radiation syndrome with bone marrow failure. Defining risk factors that predict adverse events is a critical mission to guide patient selection for personalized treatment protocols. Since non-hematopoietic stem cells act as feeder cells in the niche and their secreted lipids may regulate hematopoietic stem cells, we focused on non-hematopoietic stem cells and aimed to discover biomarkers that can assess radiation exposure from their secreted lipids. Bone marrow stromal cells (BMSCs) and osteoblast differentiation-inducing cells (ODICs) isolated from mouse femurs were exposed to lethal doses of IR and the proteomic differences between BMSC and ODIC cell layers were compared. We observed an increased Nrf2-mediated oxidative stress response and IL6 expression in ODICs and decreased expression of mitochondrial proteins in BMSCs. To elucidate secreted factors, lipidomics of the cultures were profiled; the relevant lipids distinguishing IR-exposed and control groups of BMSC were acyl-acyl phosphatidylcholine (PC aa C34:1 and PC aa C34:4), lysophosphatidylcholine (lyso-PC a C18:0 and lyso PC a C17:0) and sphingomyelin (SM C20:2). These analyses suggest that certain lipids are candidate markers for the toxic effects of IR.
Necrosulfonamide exerts neuroprotective effect by inhibiting necroptosis, neuroinflammation, and α-synuclein oligomerization in a subacute MPTP mouse model of Parkinson’s disease
Authors: Leem Yea-Hyun , Kim Do-Yeon , Park Jung-Eun , Kim Hee-Sun 
Published: May 2023

AbstractParkinson’s disease (PD) is an incurable movement disorder characterized by dopaminergic cell loss, neuroinflammation, and α-synuclein pathology. Herein, we investigated the therapeutic effects of necrosulfonamide (NSA), a specific inhibitor of mixed lineage kinase domain-like protein (MLKL), in a subacute 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mouse model of PD. MLKL is an executor of necroptosis, a programmed cell death pathway that causes inflammation. Repeated administration of NSA resulted in the recovery of impaired motor performance and dopaminergic degeneration. Furthermore, NSA inhibited the phosphorylation, ubiquitylation, and oligomerization of MLKL, all of which are associated with MLKL cell death-inducing activity in dopaminergic cells in the substantia nigra (SN). NSA also inhibited microglial activation and reactive astrogliosis as well as the MPTP-induced expression of proinflammatory molecules such as tumor necrosis factor-α, interleukin-1β, inducible nitric oxide synthase, and cystatin F. Furthermore, NSA inhibited α-synuclein oligomerization and phosphorylation in the SN of MPTP-treated mice by inhibiting the activity of glycogen synthase kinase 3β and matrix metalloproteinase-3. In conclusion, NSA has anti-necroptotic, anti-inflammatory, and anti-synucleinopathic effects on PD pathology. Therefore, NSA is a potential therapeutic candidate for PD.
GPX4 overexpressed non-small cell lung cancer cells are sensitive to RSL3-induced ferroptosis
Authors: Kim Joo-Won , Min Dong Wha , Kim Dasom , Kim Joohee , Kim Min Jung , Lim Hyangsoon , Lee Ji-Yun 
Published: May 2023

AbstractFerroptosis can be induced by inhibiting antioxidant enzymes GPX4 or system Xc−, increased intracellular iron concentrations, and lipid peroxidation. Recently, it has been suggested that ferroptosis can be an effective way to induce cancer cell death, although the specific relevance and mechanism of ferroptosis have not been fully elucidated. Here, we investigated the anticancer effects of ferroptosis inducers erastin and RSL3 on non-small cell lung cancer (NSCLC) cells. RSL3 induced cell death more effectively in NSCLC cells than erastin, with limited cytotoxicity in BEAS-2B normal bronchial epithelial cells. The sensitivity of NSCLC cells to RSL3 induced death was dependent on GPX4 expression levels; the effect of RSL3 was reversed by ferrostatin-1 (a ferroptosis inhibitor) but not by Z-VAD-FMK, chloroquine, bafilomycin A1, or necrostatin-1. RSL3 induced ferroptosis by promoting lipid peroxidation, elevating intracellular LIP concentration and ROS level, and blocking GSH-to-GSSH conversion through the inhibition of GPX4 and induction of Nrf2/HO1. Furthermore, RSL3 induced autophagosomes but disrupted the formation of autolysosomes with lysosomal membrane destabilization. GPX4 knockdown had a similar effect on ferroptosis phenotypes as RSL3. Taken together, RSL3-induced ferroptosis depends on the regulation of GPX4-Nrf2/HO1 in NSCLC cells. These results may be useful in predicting the ferroptosis response in NSCLC as well as drug resistant cancer cells.
Inferring pseudogene–MiRNA associations based on an ensemble learning framework with similarity kernel fusion
Authors: Fan Chunyan , Ding Mingchao 
Published: May 2023

AbstractAccumulating evidence shows that pseudogenes can function as microRNAs (miRNAs) sponges and regulate gene expression. Mining potential interactions between pseudogenes and miRNAs will facilitate the clinical diagnosis and treatment of complex diseases. However, identifying their interactions through biological experiments is time-consuming and labor intensive. In this study, an ensemble learning framework with similarity kernel fusion is proposed to predict pseudogene–miRNA associations, named ELPMA. First, four pseudogene similarity profiles and five miRNA similarity profiles are measured based on the biological and topology properties. Subsequently, similarity kernel fusion method is used to integrate the similarity profiles. Then, the feature representation for pseudogenes and miRNAs is obtained by combining the pseudogene–pseudogene similarities, miRNA–miRNA similarities. Lastly, individual learners are performed on each training subset, and the soft voting is used to yield final decision based on the prediction results of individual learners. The k-fold cross validation is implemented to evaluate the prediction performance of ELPMA method. Besides, case studies are conducted on three investigated pseudogenes to validate the predict performance of ELPMA method for predicting pseudogene–miRNA interactions. Therefore, all experiment results show that ELPMA model is a feasible and effective tool to predict interactions between pseudogenes and miRNAs.
Selenoprotein P concentrations and risk of progression from mild cognitive impairment to dementia
Authors: Vinceti Marco , Urbano Teresa , Chiari Annalisa , Filippini Tommaso , Wise Lauren A. , Tondelli Manuela , Michalke Bernhard , Shimizu Misaki , Saito Yoshiro 
Published: May 2023

Abstract There is a growing literature investigating the effects of selenium on the central nervous system and cognitive function. However, little is known about the role of selenoprotein P, the main selenium transporter, which can also have adverse biological effects. We conducted a prospective cohort study of individuals aged 42–81 years who received a clinical diagnosis of mild cognitive impairment. Using sandwich ELISA methods, we measured full-length selenoprotein P concentrations in serum and cerebrospinal fluid to assess the relation with dementia incidence during a median follow-up of 47.3 months. We used Cox proportional hazards regression and restricted cubic splines to model such relation. Of the 54 participants, 35 developed dementia during follow-up (including 26 cases of Alzheimer’s dementia). Selenoprotein P concentrations in serum and cerebrospinal fluid were highly correlated, and in spline regression analyses they each showed a positive non-linear association with dementia risk, particularly after excluding dementia cases diagnosed within 24 months of follow-up. We also observed differences in association according to the dementia subtypes considered. Risk ratios of dementia peaked at 2–6 at the highest levels of selenoprotein P, when compared to its median level, also depending on matrix, analytical methodology and dementia subtype. Findings of this study, the first to assess selenoprotein P levels in the central nervous system in vivo and the first to use a prospective study design to evaluate associations with dementia, suggest that higher circulating concentrations of selenoprotein P, both in serum and cerebrospinal fluid, predict progression of MCI to dementia. However, further confirmation of these findings is required, given the limited statistical precision of the associations and the potential for residual confounding.
High-throughput proteomics profiling-derived signature associated with chemotherapy response and survival for stage II/III colorectal cancer
Authors: Ye Shu-Biao , Cheng Yi-Kan , Li Pei-Si , Zhang Lin , Zhang Lian-Hai , Huang Yan , Chen Ping , Wang Yi , Wang Chao , Peng Jian-Hong , Shi Li-Shuo , Ling Li , Wu Xiao-Jian , Qin Jun , Yang Zi-Huan , Lan Ping 
Published: May 2023

AbstractAdjuvant chemotherapy (ACT) is usually used to reduce the risk of disease relapse and improve survival for stage II/III colorectal cancer (CRC). However, only a subset of patients could benefit from ACT. Thus, there is an urgent need to identify improved biomarkers to predict survival and stratify patients to refine the selection of ACT. We used high-throughput proteomics to analyze tumor and adjacent normal tissues of stage II/III CRC patients with /without relapse to identify potential markers for predicting prognosis and benefit from ACT. The machine learning approach was applied to identify relapse-specific markers. Then the artificial intelligence (AI)-assisted multiplex IHC was performed to validate the prognostic value of the relapse-specific markers and construct a proteomic-derived classifier for stage II/III CRC using 3 markers, including FHL3, GGA1, TGFBI. The proteomics profiling-derived signature for stage II/III CRC (PS) not only shows good accuracy to classify patients into high and low risk of relapse and mortality in all three cohorts, but also works independently of clinicopathologic features. ACT was associated with improved disease-free survival (DFS) and overall survival (OS) in stage II (pN0) patients with high PS and pN2 patients with high PS. This study demonstrated the clinical significance of proteomic features, which serve as a valuable source for potential biomarkers. The PS classifier provides prognostic value for identifying patients at high risk of relapse and mortality and optimizes individualized treatment strategy by detecting patients who may benefit from ACT for survival.
HRD effects on first-line adjuvant chemotherapy and PARPi maintenance therapy in Chinese ovarian cancer patients
Authors: Li Lei , Gu Yu , Zhang Mengpei , Shi Xiaohua , Li Zhe , Xu Xinyun , Sun Tianqi , Dong Yu , Xue Chao , Zhu Xiaoru , Lv Ran , Jiao Kai , Ji Xuwo , Wang Li-juan , Zhang Yang , Liang Zhiyong , Jin Ying , Yin Rutie , Wu Ming , Liang Han 
Published: May 2023

AbstractHomologous recombination deficiency (HRD) testing has been approved by FDA for selecting epithelial ovarian cancer (EOC) patients who may benefit from the first-line poly (ADP-ribose) polymerase inhibitor (PARPi) maintenance therapy. However, the effects of HRD on the clinical outcomes of first-line chemotherapy and first-line PARPi maintenance therapy have not been rigorously evaluated in Chinese EOC patients. Here, we developed an HRD assay and applied it to two large retrospectively collected Chinese EOC patient cohorts. In the first-line adjuvant chemotherapy cohort (FACT, N = 380), HRD status significantly improved PFS (median, 15.6 months vs. 9.4 months; HR, 0.688; 95% CI, 0.526–0.899; P = 0.003) and OS (median, 89.5 months vs. 60.9 months; HR, 0.636; 95% CI, 0.423–0.955; P = 0.008). In the first-line PARPi maintenance therapy cohort (FPMT, N = 83), HRD status significantly improved PFS (median, NA vs. 12 months; HR, 0.438; 95% CI, 0.201–0.957; P = 0.033) and OS (median, NA vs. NA months; HR, 0.12; 95% CI, 0.029–0.505; P = 0.001). Our results demonstrate that HRD status is a significant predictor for PFS and OS in both first-line chemotherapy and first-line PARPi maintenance therapy, providing strong real-world evidence for conducting genetic testing and improving clinical recommendations for Chinese EOC patients.
Label-free nanoscale mapping of intracellular organelle chemistry
Authors: Greaves George E. , Kiryushko Darya , Auner Holger W. , Porter Alexandra E. , Phillips Chris C. 
Published: May 2023

AbstractThe ability to image cell chemistry at the nanoscale is key for understanding cell biology, but many optical microscopies are restricted by the ~(200–250)nm diffraction limit. Electron microscopy and super-resolution fluorescence techniques beat this limit, but rely on staining and specialised labelling to generate image contrast. It is challenging, therefore, to obtain information about the functional chemistry of intracellular components. Here we demonstrate a technique for intracellular label-free chemical mapping with nanoscale (~30 nm) resolution. We use a probe-based optical microscope illuminated with a mid-infrared laser whose wavelengths excite vibrational modes of functional groups occurring within biological molecules. As a demonstration, we chemically map intracellular structures in human multiple myeloma cells and compare the morphologies with electron micrographs of the same cell line. We also demonstrate label-free mapping at wavelengths chosen to target the chemical signatures of proteins and nucleic acids, in a way that can be used to identify biochemical markers in the study of disease and pharmacology.
Rat hippocampal CA1 region represents learning-related action and reward events with shorter latency than the lateral entorhinal cortex
Authors: Soma Shogo , Ohara Shinya , Nonomura Satoshi , Suematsu Naofumi , Yoshida Junichi , Pastalkova Eva , Sakai Yutaka , Tsutsui Ken-Ichiro , Isomura Yoshikazu 
Published: May 2023

AbstractThe hippocampus and entorhinal cortex are deeply involved in learning and memory. However, little is known how ongoing events are processed in the hippocampal-entorhinal circuit. By recording from head-fixed rats during action-reward learning, here we show that the action and reward events are represented differently in the hippocampal CA1 region and lateral entorhinal cortex (LEC). Although diverse task-related activities developed after learning in both CA1 and LEC, phasic activities related to action and reward events differed in the timing of behavioral event representation. CA1 represented action and reward events almost instantaneously, whereas the superficial and deep layers of the LEC showed a delayed representation of the same events. Interestingly, we also found that ramping activity towards spontaneous action was correlated with waiting time in both regions and exceeded that in the motor cortex. Such functional activities observed in the entorhinal-hippocampal circuits may play a crucial role for animals in utilizing ongoing information to dynamically optimize their behaviors.
Impact of the metal core on the electrochemiluminescence of a pair of atomically precise Au20 nanocluster isomers
Authors: Chen Shuang , Liu Ying , Kuang Kaiyang , Yin Bing , Wang Xiaojian , Jiang Lirong , Wang Pu , Pei Yong , Zhu Manzhou 
Published: May 2023

AbstractAlthough the electrochemiluminescence (ECL) of metal nanoclusters has been reported, revealing the correlation between structure and ECL at an atomic level is highly challenging. Here, we reported the impact of the metal core of Au20(SAdm)12(CHT)4 (Au20-AC for short; SAdm = 1-adamantanethiolate; CHT= cyclohexanethiol) and its isomer Au20(TBBT)16 (TBBT = 4-tert-butylthiophenol) on their solution-state and solid-state electrochemiluminescence. In self-annihilation ECL experiments, Au20-AC showed a strong cathodic ECL but a weak anodic ECL, while the ECL signal of Au20(TBBT)16 was weak and barely detectable. Density functional theory (DFT) calculations showed that the Au7 kernel of [Au20-AC]- is metastable, weakening its anodic ECL. Au20-AC in solution-state displayed an intense co-reactant ECL in the near-infrared region, which is 7 times higher than that of standard Ru(bpy)32+. The strongest solid-state ECL emissions of Au20-AC and Au20(TBBT)16 were at 860 and 770 nm, respectively — 15 nm red-shifted for Au20-AC and 20 nm blue-shifted for Au20(TBBT)16, compared to their corresponding solid-state photoluminescence (PL) emissions. This work shows that ECL is significantly affected by the subtle differences of the metal core, and offers a potential basis for sensing and immunoassay platforms based on atomically precise emissive metal nanoclusters.