bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intracellular pH affects mitochondrial homeostasis in cultured human corneal endothelial cells prepared for cell injection therapy
Authors: Deguchi Hideto , Yamashita Tomoko , Hiramoto Nao , Otsuki Yohei , Mukai Atsushi , Ueno Morio , Sotozono Chie , Kinoshita Shigeru , Hamuro Junji 
Published: April 2022

AbstractThis study aimed to uncover the mechanism responsible for the clinical efficacy of cell injection therapy with fully differentiated cultured cells. Analysis of polarized expression of ion transporters on cultured human corneal endothelial cells (CECs) subpopulations (SPs) was performed. The intracellular pH (pHi) between two CEC SPs, distinct in the proportion of differentiated cells, was measured, and the association with mitochondrial respiration homeostasis was investigated. The effects of the ion transporter inhibition by their selective inhibitors or siRNA transfection were also explored. Na+/K+-ATPase, Aquaporin 1, SLC4A11, NBCe1, NHE1 as transporters, and ZO-1, were all selectively expressed in differentiated SPs, but were almost null in the cell-state-transitioned SPs. We also confirmed that the pHi of CEC SPs affected their mitochondrial respiration by modulating the expression of these ion transporters via inhibitors or siRNA transfection. Ion and water transporters might participate in the maintenance of pHi and mitochondria homeostasis in differentiated SPs, which may contribute, combined with integral barrier functions, to efficient water efflux. The differences in intracellular pH between the two SPs is attributed to variations in the expression profile of specific ion transporters and mitochondrial functions, which may associate with the efficacy of the SPs in cell injection therapy.
Topological magnon modes on honeycomb lattice with coupling textures
Authors: Huang Hong , Kariyado Toshikaze , Hu Xiao 
Published: April 2022

AbstractTopological magnon modes are expected to be useful for novel applications such as robust information propagation, since they are immune to backscattering and robust against disorder. Although there are several theoretical proposals for topological magnon modes and growing experimental efforts for realizing them by now, it is still desirable to add complementary insights on this important phenomenon. Here, we propose a new scheme to achieve topological magnon where only nearest-neighbour exchange couplings on honeycomb lattice are necessary. In both ferromagnets and antiferromagnets, tuning exchange couplings between and inside hexagonal unit cells induces a topological state accompanied by a band inversion between p-orbital and d-orbital like magnon modes. Topological magnon modes appear at the interface between a topological domain and a trivial domain with magnon currents, which counterpropagate depending on pseudospins originated from orbital angular momenta of magnon modes. This mimics the spin-momentum locking phenomenon in the quantum spin Hall effect.
Genetics and immunity of Anopheles response to the entomopathogenic fungus Metarhizium anisopliae overlap with immunity to Plasmodium
Authors: Bukhari Tullu , Aimanianda Vishukumar , Bischoff Emmanuel , Brito-Fravallo Emma , Eiglmeier Karin , Riehle Michelle M. , Vernick Kenneth D. , Mitri Christian 
Published: April 2022

AbstractEntomopathogenic fungi have been explored as a potential biopesticide to counteract the insecticide resistance issue in mosquitoes. However, little is known about the possibility that genetic resistance to fungal biopesticides could evolve in mosquito populations. Here, we detected an important genetic component underlyingAnopheles coluzziisurvival after exposure to the entomopathogenic fungusMetarhizium anisopliae. A familiality study detected variation for survival among wild mosquito isofemale pedigrees, and genetic mapping identified two loci that significantly influence mosquito survival after fungus exposure. One locus overlaps with a previously reported locus forAnophelessusceptibility to the human malaria parasitePlasmodium falciparum. Candidate gene studies revealed that two LRR proteins encoded by APL1C and LRIM1 genes in this newly mapped locus are required for protection of femaleA. coluzziifromM. anisopliae, as is the complement-like factor Tep1. These results indicate that naturalAnophelespopulations already segregate frequent genetic variation for differential mosquito survival after fungal challenge and suggest a similarity inAnophelesprotective responses against fungus andPlasmodium. However, this immune similarity raises the possibility that fungus-resistant mosquitoes could also display enhanced resistance toPlasmodium, suggesting an advantage of selecting for fungus resistance in vector populations to promote naturally diminished malaria vector competence.
Seasonal and sexual variation in mRNA expression of selected adipokine genes affecting fat deposition and metabolism of the emu (Dromaius novaehollandiae)
Authors: Kim Ji Eun , Bennett Darin C. , Wright Kristina , Cheng Kimberly M. 
Published: April 2022

AbstractEmus are farmed for fat production. Oil rendered from their back and abdominal fat pads has good anti-oxidant and anti-inflammatory properties and has ingredients that promote cell growth. Our objective is to examine the mRNA expression of 7 emu adipokine genes (eFABP4,eSCD1,eAdipoQ,eAdipoR1,eAdipoR2,eLEPandeLepR) to identify gene markers that may help improve emu fat production. Back and abdominal fat tissues from 11 adult emus were biopsied at four time points (April, June, August and November). Total RNA was isolated and cDNA was synthesized. Gene specific primers were designed for partial cloning fragments to amplify the open reading frame of the 7 genes. eLEPwas not expressed in emu fat tissue. Nucleotides and amino acids sequences of the 6 expressed gene were compared with homologs from other species and phylogenetic relationships established. Seasonal mRNA expression of each gene was assessed by quantitative RT-PCR and differential expression analysed by the 2−ΔΔCTmethod. The 6 expressed genes showed seasonal variation in expression and showed association of expression level with back fat adiposity. More whole-genome scanning studies are needed to develop novel molecular markers that can be applied to improve fat production in emus.
Population expansion, divergence, and persistence in Western Fence Lizards (Sceloporus occidentalis) at the northern extreme of their distributional range
Authors: Davis Hayden R. , Des Roches Simone , Anderson Roger A. , Leaché Adam D. 
Published: April 2022

AbstractPopulation dynamics within species at the edge of their distributional range, including the formation of genetic structure during range expansion, are difficult to study when they have had limited time to evolve. Western Fence Lizards (Sceloporus occidentalis) have a patchy distribution at the northern edge of their range around the Puget Sound, Washington, where they almost exclusively occur on imperiled coastal habitats. The entire region was covered by Pleistocene glaciation as recently as 16,000 years ago, suggesting that populations must have colonized these habitats relatively recently. We tested for population differentiation across this landscape using genome-wide SNPs and morphological data. A time-calibrated species tree supports the hypothesis of a post-glacial establishment and subsequent population expansion into the region. Despite a strong signal for fine-scale population genetic structure across the Puget Sound with as many as 8–10 distinct subpopulations supported by the SNP data, there is minimal evidence for morphological differentiation at this same spatiotemporal scale. Historical demographic analyses suggest that populations expanded and diverged across the region as the Cordilleran Ice Sheet receded. Population isolation, lack of dispersal corridors, and strict habitat requirements are the key drivers of population divergence in this system. These same factors may prove detrimental to the future persistence of populations as they cope with increasing shoreline development associated with urbanization.
Habitat preferences, estimated abundance and behavior of tree hyrax (Dendrohyrax sp.) in fragmented montane forests of Taita Hills, Kenya
Authors: Rosti Hanna , Heiskanen Janne , Loehr John , Pihlström Henry , Bearder Simon , Mwangala Lucas , Maghenda Marianne , Pellikka Petri , Rikkinen Jouko 
Published: April 2022

AbstractWe studied a previously almost unknown nocturnal mammal, an apparently undescribed species of tree hyrax (Dendrohyrax sp.) in the moist montane forests of Taita Hills, Kenya. We used thermal imaging to locate tree hyraxes, observe their behavior, and to identify woody plants most frequently visited by the selective browsers. We also documented acoustic behavior in forest fragments of different sizes. Data on calling type and frequency were analyzed together with lidar data to estimate population densities and to identify forest stand characteristics associated with large populations. Viable populations were found only in the largest forest fragments (> 90 ha), where tree hyraxes preferred most pristine forest stands with high, multilayered canopies. The estimated population sizes in smaller forest fragments were very limited, and hyraxes were heard to call only during late night and early morning hours, presumably in order to avoid detection. While we frequently recorded tree hyrax songs in the largest forest fragments, we almost never heard songs in the small ones. All remaining subpopulations of the Taita tree hyrax are under threat of human disturbance and further habitat deterioration. Conservation efforts should include protection of all remaining habitat patches, but also reforestation of former habitat is urgently needed.
Aberrant functional connectivity and temporal variability of the dynamic pain connectome in patients with low back related leg pain
Authors: Pei Yixiu , Peng Jidong , Zhang Yong , Huang Muhua , Zhou Fuqing 
Published: April 2022

AbstractNeuroimaging studies have suggested a link between the intensity of chronic low back pain intensity and structural and functional brain alterations. However, chronic pain results from the coordination and dynamics among several brain networks that comprise the dynamic pain connectome. Here, we use resting-state functional magnetic resonance imaging and measures of static (sFC) and dynamic functional connectivity (dFC) variability in the typical (0.01–0.1 Hz) and five specific (slow-6 to slow-2) frequency bands to test hypotheses regarding disruption in this variability in low back-related leg pain (LBLP) patients who experience chronic pain and numbness. Twenty-four LBLP patients and 23 healthy controls completed clinical assessments, and partial correlational analyses between altered sFC and dFC variability and clinical measures were conducted. We found a lower within-network sFC in the ascending nociceptive pathway (Asc) and a lower cross-network sFC between nodes of the salience network and the Asc in the typical frequency band. In the slow-5 frequency band, a lower within-network sFC was found in the Asc. Abnormal cross-network sFC was found between nodes of the salience network-Asc (slow-5 and slow-6) and the default mode network-Asc (slow-4 and slow-6). Furthermore, cross-network abnormalities in the typical and certain specific frequency bands were linked to clinical assessments. These findings indicate that frequency-related within- and cross-network communication among the nodes in the dynamic pain connectome is dysfunctional in LBLP patients and that selecting specific frequencies may be potentially useful for detecting LBLP-related brain activity.
Decoding personalized motor cortical excitability states from human electroencephalography
Authors: Hussain Sara J. , Quentin Romain 
Published: April 2022

AbstractBrain state-dependent transcranial magnetic stimulation (TMS) requires real-time identification of cortical excitability states. Current approaches deliver TMS during brain states that correlate with motor cortex (M1) excitability at the group level. Here, we hypothesized that machine learning classifiers could successfully discriminate between high and low M1 excitability states in individual participants using information obtained from low-density electroencephalography (EEG) signals. To test this, we analyzed a publicly available dataset that delivered 600 single TMS pulses to the right M1 during EEG and electromyography (EMG) recordings in 20 healthy adults. Multivariate pattern classification was used to discriminate between brain states during which TMS evoked small and large motor-evoked potentials (MEPs). Results show that personalized classifiers successfully discriminated between low and high M1 excitability states in 80% of tested participants. MEPs elicited during classifier-predicted high excitability states were significantly larger than those elicited during classifier-predicted low excitability states in 90% of tested participants. Personalized classifiers did not generalize across participants. Overall, results show that individual participants exhibit unique brain activity patterns which predict low and high M1 excitability states and that these patterns can be efficiently captured using low-density EEG signals. Our findings suggest that deploying individualized classifiers during brain state-dependent TMS may enable fully personalized neuromodulation in the future.
Non-invasive sampling of water-borne hormones demonstrates individual consistency of the cortisol response to stress in laboratory zebrafish (Danio rerio)
Authors: Midttun H. L. E. , Øverli Ø. , Tudorache C. , Mayer I , Johansen I. B. 
Published: April 2022

AbstractGlucocorticoid (GC) stress hormones are well-known for their impact on phenotypic traits ranging from immune function to behaviour and cognition. For that reason, consistent aspects of an individual’s physiological stress response (i.e. GC responsiveness) can predict major elements of life-history trajectory. Zebrafish (Danio rerio) emerge as a promising model to study such consistent trait correlations, including the development of individual stress coping styles, i.e. consistent associations between physiological and behavioral traits. However, consistency in GC responsiveness of this popular animal model remains to be confirmed. Such a study has so far been hampered by the small-bodied nature and insufficient blood volume of this species to provide repeated measurements of circulating GCs. Here, we adopted a technique that allows for repeated, non-invasive sampling of individual zebrafish by quantifying GCs from holding water. Our findings indicate consistency of the magnitude of post-stress GC production over several consecutive stress events in zebrafish. Moreover, water-borne GCs reflect individual variation in GC responsiveness with the strongest consistency seen in males.
Cross subkey side channel analysis based on small samples
Authors: Hu Fanliang , Wang Huanyu , Wang Junnian 
Published: April 2022

AbstractThe majority of recently demonstrated Deep-Learning Side-Channel Analysis (DLSCA) use neural networks trained on a segment of traces containing operations only related to the target subkey. However, when the size of the training set is limited, as in this paper with only 5K power traces, the deep learning (DL) model cannot effectively learn the internal features of the data due to insufficient training data. In this paper, we propose a cross-subkey training approach that acts as a trace augmentation. We train deep-learning models not only on a segment of traces containing the SBox operation of the target subkey of AES-128 but also on segments for other 15 subkeys. Experimental results show that the accuracy of the subkey combination training model is $$28.20\%$$

28.20
%

higher than that of the individual subkey training model on traces captured in the microcontroller implementation of the STM32F3 with AES-128. And validation is performed on two additional publicly available datasets. At the same time, the number of traces that need to be captured when the model is trained is greatly reduced, demonstrating the effectiveness and practicality of the method.
Loss of microbiota-derived protective metabolites after neutropenic fever
Authors: Rashidi Armin , Ebadi Maryam , Rehman Tauseef Ur , Elhusseini Heba , Halaweish Hossam , Holtan Shernan G. , Ramamoorthy Sivapriya , Weisdorf Daniel J. , Khoruts Alexander , Staley Christopher 
Published: April 2022

AbstractNeutropenic fever (NF) is a common complication of chemotherapy in patients with cancer which often prolongs hospitalization and worsens the quality of life. Although an empiric antimicrobial approach is used to prevent and treat NF, a clear etiology cannot be found in most cases. Emerging data suggest an altered microbiota-host crosstalk leading to NF. We profiled the serum metabolome and gut microbiome in longitudinal samples before and after NF in patients with acute myeloid leukemia, a prototype setting with a high incidence of NF. We identified a circulating metabolomic shift after NF, with a minimal signature containing 18 metabolites, 13 of which were associated with the gut microbiota. Among these metabolites were markers of intestinal epithelial health and bacterial metabolites of dietary tryptophan with known anti-inflammatory and gut-protective effects. The level of these metabolites decreased after NF, in parallel with biologically consistent changes in the abundance of mucolytic and butyrogenic bacteria with known effects on the intestinal epithelium. Together, our findings indicate a metabolomic shift with NF which is primarily characterized by a loss of microbiota-derived protective metabolites rather than an increase in detrimental metabolites. This analysis suggests that the current antimicrobial approach to NF may need a revision to protect the commensal microbiota.
Deep learning model for tongue cancer diagnosis using endoscopic images
Authors: Heo Jaesung , Lim June Hyuck , Lee Hye Ran , Jang Jeon Yeob , Shin Yoo Seob , Kim Dahee , Lim Jae Yol , Park Young Min , Koh Yoon Woo , Ahn Soon-Hyun , Chung Eun-Jae , Lee Doh Young , Seok Jungirl , Kim Chul-Ho 
Published: April 2022

AbstractIn this study, we developed a deep learning model to identify patients with tongue cancer based on a validated dataset comprising oral endoscopic images. We retrospectively constructed a dataset of 12,400 verified endoscopic images from five university hospitals in South Korea, collected between 2010 and 2020 with the participation of otolaryngologists. To calculate the probability of malignancy using various convolutional neural network (CNN) architectures, several deep learning models were developed. Of the 12,400 total images, 5576 images related to the tongue were extracted. The CNN models showed a mean area under the receiver operating characteristic curve (AUROC) of 0.845 and a mean area under the precision-recall curve (AUPRC) of 0.892. The results indicate that the best model was DenseNet169 (AUROC 0.895 and AUPRC 0.918). The deep learning model, general physicians, and oncology specialists had sensitivities of 81.1%, 77.3%, and 91.7%; specificities of 86.8%, 75.0%, and 90.9%; and accuracies of 84.7%, 75.9%, and 91.2%, respectively. Meanwhile, fair agreement between the oncologist and the developed model was shown for cancer diagnosis (kappa value = 0.685). The deep learning model developed based on the verified endoscopic image dataset showed acceptable performance in tongue cancer diagnosis.
The effect of preoperative patient-reported anxiety on morbidity and mortality outcomes in patients undergoing major general surgery
Authors: Kassahun Woubet Tefera , Mehdorn Matthias , Wagner Tristan Cedric , Babel Jonas , Danker Helge , Gockel Ines 
Published: April 2022

AbstractExcessive levels of anxiety may negatively influence treatment outcomes and likely increase patient suffering. We designed a prospective observational study to assess whether preoperative patient-reported anxiety affects major general surgery outcomes. We prospectively administered the State-Trait Anxiety Inventory (STAI) to measure preoperative anxiety in patients awaiting major general surgical procedures. Patients were grouped by STAI scores according to established cutoffs: no anxiety (STAI < 40) and anxiety (STAI ≥ 40). Four hundred patients completed the questionnaires and underwent surgery, with an average interval from questionnaire completion to surgery of 4 days. Applying a state anxiety (STAI-S) score ≥ 40 as a reference point, the prevalence of patient-reported anxiety was 60.5% (241 of 400). The mean STAI-S score for these patients was 50.48 ± 7.77. The mean age of the entire cohort was 58.5 ± 14.12 years. The majority of participants were male (53.8%). The distribution of sex by anxiety status showed that 53.5% of women and 46.5% of men had anxiety (p = 0.003). In the entire cohort, postoperative complications occurred in 23.9% and 28.6% of the no anxiety and anxiety groups, respectively. The difference was nonsignificant. In a subgroup of patients who underwent high-risk complex procedures (N = 221), however, postoperative complications occurred in 31.4% and 45.2% of the no anxiety and anxiety groups, respectively. This difference was significant atp = 0.004. Of the patients who were anxious, 3.3% (8 of 241) died during hospitalization following surgery, compared with 4.4% of the patients (7 of 159) who were not anxious (p = 0.577). In the multivariable analysis adjusted for covariates and based on the results of subgroup analysis, preoperative anxiety assessed by the STAIS score was associated with morbidity (OR 2.12, CI 1.14–3.96;p = 0.018) but not mortality. The majority of enrolled patients in this study were classified as having high- to very high-level preoperative clinical anxiety, and we found a significant quantitative effect of patient-reported anxiety on morbidity but not mortality after surgery.
Culture and multiomic analysis of lung cancer patient-derived pleural effusions revealed distinct druggable molecular types
Authors: Seo Ha-Young , Kim Soon-Chan , Roh Woo-lee , Shin Young-Kyoung , Kim Soyeon , Kim Dong-Wan , Kim Tae Min , Ku Ja-Lok 
Published: April 2022

AbstractMalignant pleural effusion (MPE) is an independent determinant of poor prognostic factor of non-small cell lung cancer (NSCLC). The course of anchorage independent growth within the pleural cavity likely reforms the innate molecular characteristics of malignant cells, which largely accounts for resistance to chemotherapy and poor prognosis after the surgical resection. Nevertheless, the genetic and transcriptomic features with respect to various drug responses of MPE-complicated NSCLC remain poorly understood. To obtain a clearer overview of the MPE-complicated NSCLC, we established 28 MPE-derived lung cancer cell lines which were subjected to genomic, transcriptomic and pharmacological analysis. Our results demonstrated MPE-derived NSCLC cell lines recapitulated representative driver mutations generally found in the primary NSCLC. It also exhibited the presence of distinct translational subtypes in accordance with the mutational profiles. The drug responses of several targeted chemotherapies accords with both genomic and transcriptomic characteristics of MPE-derived NSCLC cell lines. Our data also suggest that the impending drawback of mutation-based clinical diagnosis in evaluating MPE-complicated NSCLS patient responses. As a potential solution, our work showed the importance of comprehending transcriptomic characteristics in order to defy potential drug resistance caused by MPE.