bluuebunny/crossref_metadata_2025_split huggingface dataset:
Widespread increasing vegetation sensitivity to soil moisture
Authors: Li Wantong , Migliavacca Mirco , Forkel Matthias , Denissen Jasper M. C. , Reichstein Markus , Yang Hui , Duveiller Gregory , Weber Ulrich , Orth Rene 
Published: July 2022

AbstractGlobal vegetation and associated ecosystem services critically depend on soil moisture availability which has decreased in many regions during the last three decades. While spatial patterns of vegetation sensitivity to global soil water have been recently investigated, long-term changes in vegetation sensitivity to soil water availability are still unclear. Here we assess global vegetation sensitivity to soil moisture during 1982-2017 by applying explainable machine learning with observation-based leaf area index (LAI) and hydro-climate anomaly data. We show that LAI sensitivity to soil moisture significantly increases in many semi-arid and arid regions. LAI sensitivity trends are associated with multiple hydro-climate and ecological variables, and strongest increasing trends occur in the most water-sensitive regions which additionally experience declining precipitation. State-of-the-art land surface models do not reproduce this increasing sensitivity as they misrepresent water-sensitive regions and sensitivity strength. Our sensitivity results imply an increasing ecosystem vulnerability to water availability which can lead to exacerbated reductions in vegetation carbon uptake under future intensified drought, consequently amplifying climate change.
Increased Indian Ocean-North Atlantic Ocean warming chain under greenhouse warming
Authors: Yang Young-Min , Park Jae-Heung , An Soon-Il , Yeh Sang-Wook , Zhu Zhiwei , Liu Fei , Li Juan , Lee June-Yi , Wang Bin 
Published: July 2022

AbstractOver the past half a century, both the Indian Ocean (IO) and the North Atlantic Ocean (NA) exhibit strong warming trends like a global mean surface temperature (SST). Here, we show that not only simply as a result of increased greenhouse gases, but the IO-NA interaction through atmospheric teleconnection boosts up their warming trends. Climate model simulations demonstrate that the IO warming increases the NA SST by enhancing the longwave radiation through atmospheric teleconnection, subsequently, the warmer NA SST-induced atmospheric teleconnection leads to IO warming by reducing evaporative cooling with weakened surface winds. This two-way interaction (i.e., IO-NA warming chain) acts as positive feedback that reinforces warming over both ocean basins. The Pacific Ocean is partly involved in this warming chain as a modulator in an interdecadal timescale. These results highlight the importance of understanding ocean-basin interactions that may provide a more accurate future projection of warming.
GLI3 regulates muscle stem cell entry into GAlert and self-renewal
Authors: Brun Caroline E. , Sincennes Marie-Claude , Lin Alexander Y. T. , Hall Derek , Jarassier William , Feige Peter , Le Grand Fabien , Rudnicki Michael A. 
Published: July 2022

AbstractSatellite cells are required for the growth, maintenance, and regeneration of skeletal muscle. Quiescent satellite cells possess a primary cilium, a structure that regulates the processing of the GLI family of transcription factors. Here we find that GLI3 processing by the primary cilium plays a critical role for satellite cell function. GLI3 is required to maintain satellite cells in a G0 dormant state. Strikingly, satellite cells lacking GLI3 enter the GAlert state in the absence of injury. Furthermore, GLI3 depletion stimulates expansion of the stem cell pool. As a result, satellite cells lacking GLI3 display rapid cell-cycle entry, increased proliferation and augmented self-renewal, and markedly enhanced regenerative capacity. At the molecular level, we establish that the loss of GLI3 induces mTORC1 signaling activation. Therefore, our results provide a mechanism by which GLI3 controls mTORC1 signaling, consequently regulating muscle stem cell activation and fate.
Mast4 determines the cell fate of MSCs for bone and cartilage development
Authors: Kim Pyunggang , Park Jinah , Lee Dong-Joon , Mizuno Seiya , Shinohara Masahiro , Hong Chang Pyo , Jeong Yealeen , Yun Rebecca , Park Hyeyeon , Park Sujin , Yang Kyung-Min , Lee Min-Jung , Jang Seung Pil , Kim Hyun-Yi , Lee Seung-Jun , Song Sun U. , Park Kyung-Soon , Tanaka Mikako , Ohshima Hayato , Cho Jin Won , Sugiyama Fumihiro , Takahashi Satoru , Jung Han-Sung , Kim Seong-Jin 
Published: July 2022

AbstractMesenchymal stromal cells (MSCs) differentiation into different lineages is precisely controlled by signaling pathways. Given that protein kinases play a crucial role in signal transduction, here we show that Microtubule Associated Serine/Threonine Kinase Family Member 4 (Mast4) serves as an important mediator of TGF-β and Wnt signal transduction in regulating chondro-osteogenic differentiation of MSCs. Suppression of Mast4 by TGF-β1 led to increased Sox9 stability by blocking Mast4-induced Sox9 serine 494 phosphorylation and subsequent proteasomal degradation, ultimately enhancing chondrogenesis of MSCs. On the other hand, Mast4 protein, which stability was enhanced by Wnt-mediated inhibition of GSK-3β and subsequent Smurf1 recruitment, promoted β-catenin nuclear localization and Runx2 activity, increasing osteogenesis of MSCs. Consistently,Mast4−/−mice demonstrated excessive cartilage synthesis, while exhibiting osteoporotic phenotype. Interestingly, Mast4 depletion in MSCs facilitated cartilage formation and regeneration in vivo. Altogether, our findings uncover essential roles of Mast4 in determining the fate of MSC development into cartilage or bone.
TRIM24 is an insulin-responsive regulator of P-bodies
Authors: Wei Wen , Chen Qiaoli , Liu Minjun , Sheng Yang , OuYang Qian , Feng Weikuan , Yang Xinyu , Ding Longfei , Su Shu , Zhang Jingzi , Fang Lei , Vidal-Puig Antonio , Wang Hong-Yu , Chen Shuai 
Published: July 2022

AbstractInsulin is a potent inducer of mRNA transcription and translation, contributing to metabolic regulation. Insulin has also been suggested to regulate mRNA stability through the processing body (P-body) molecular machinery. However, whether and how insulin regulates mRNA stability via P-bodies is not clear. Here we show that the E3-ligase TRIM24 is a critical factor linking insulin signalling to P-bodies. Upon insulin stimulation, protein kinase B (PKB, also known as Akt) phosphorylates TRIM24 and stimulates its shuttling from the nucleus into the cytoplasm. TRIM24 interacts with several critical components of P-bodies in the cytoplasm, promoting their polyubiquitylation, which consequently stabilises Pparγ mRNA. Inactivation of TRIM24 E3-ligase activity or prevention of its phosphorylation via knockin mutations in mice promotes hepatic Pparγ degradation via P-bodies. Consequently, both knockin mutations alleviate hepatosteatosis in mice fed on a high-fat diet. Our results demonstrate the critical role of TRIM24 in linking insulin signalling to P-bodies and have therapeutic implications for the treatment of hepatosteatosis.
Melatonin ameliorates Parkinson’s disease via regulating microglia polarization in a RORα‐dependent pathway
Authors: Li Jingwen , Liu Hanshu , Wang Xinyi , Xia Yun , Huang Jinsha , Wang Tao , Lin Zhicheng , Xiong Nian 
Published: July 2022

AbstractAn important pathophysiological component of Parkinson’s Disease (PD) is circadian rhythm disorder, closely related to a decrease in circulated melatonin (MLT) level. It has been reported recently that retinoic acid-associated orphan nuclear receptor (RORα), for the potentiallyendogenous ligand MLT, plays an important role in various diseases. However, the function of RORα in the pathogenesis of neurodegenerative diseases remains much unclear. Here, we showed in a cellular PD model that RORα expression was down-regulated in 1 methyl 4 phenyl pyridinium ion (MPP+)-treated BV2 cells but up-regulated by MLT. Of a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) - induced mouse model with RORα levels reduced in the midbrain tissue, MLT treatment (intraperitoneal 20 mg/kg/d for 7 days) significantly increased the RORα levels and protected dopamine neurons, with decreased inflammation and increased anti-inflammatory M2-like phenotype in the microglia. Furthermore, siRNA-mediated knockdown implied the involvement of signal transducer and activator of transcription (STAT) pathway. In conclusion, MLT ameliorates neuroinflammation by inhibiting STAT-related pro-inflammatory (M1-like) polarization of microglia, revealing alternative options for neuroprotective treatment of PD.
HistoML, a markup language for representation and exchange of histopathological features in pathology images
Authors: Lou Peiliang , Wang Chunbao , Guo Ruifeng , Yao Lixia , Zhang Guanjun , Yang Jun , Yuan Yong , Dong Yuxin , Gao Zeyu , Gong Tieliang , Li Chen 
Published: July 2022

AbstractThe study of histopathological phenotypes is vital for cancer research and medicine as it links molecular mechanisms to disease prognosis. It typically involves integration of heterogenous histopathological features in whole-slide images (WSI) to objectively characterize a histopathological phenotype. However, the large-scale implementation of phenotype characterization has been hindered by the fragmentation of histopathological features, resulting from the lack of a standardized format and a controlled vocabulary for structured and unambiguous representation of semantics in WSIs. To fill this gap, we propose the Histopathology Markup Language (HistoML), a representation language along with a controlled vocabulary (Histopathology Ontology) based on Semantic Web technologies. Multiscale features within a WSI, from single-cell features to mesoscopic features, could be represented using HistoML which is a crucial step towards the goal of making WSIs findable, accessible, interoperable and reusable (FAIR). We pilot HistoML in representing WSIs of kidney cancer as well as thyroid carcinoma and exemplify the uses of HistoML representations in semantic queries to demonstrate the potential of HistoML-powered applications for phenotype characterization.
Anesthetic modulations dissociate neuroelectric characteristics between sensory-evoked and spontaneous activities across bilateral rat somatosensory cortical laminae
Authors: Baek Kwangyeol , Park Chae Ri , Jang Siwan , Shim Woo Hyun , Kim Young Ro 
Published: July 2022

AbstractSpontaneous neural activity has been widely adopted to construct functional connectivity (FC) amongst distant brain regions. Although informative, the functional role and signaling mechanism of the resting state FC are not intuitive as those in stimulus/task-evoked activity. In order to bridge the gap, we investigated anesthetic modulation of both resting-state and sensory-evoked activities. We used two well-studied GABAergic anesthetics of varying dose (isoflurane: 0.5–2.0% and α-chloralose: 30 and 60 mg/kg∙h) and recorded changes in electrophysiology using a pair of laminar electrode arrays that encompass the entire depth of the bilateral somatosensory cortices (S1fl) in rats. Specifically, the study focused to describe how varying anesthesia conditions affect the resting state activities and resultant FC between bilateral hemispheres in comparison to those obtained by evoked responses. As results, isoflurane decreased the amplitude of evoked responses in a dose-dependent manner mostly due to the habituation of repetitive responses. However, α-chloralose rather intensified the amplitude without exhibiting habituation. No such diverging trend was observed for the spontaneous activity, in which both anesthetics increased the signal power. For α-chloralose, overall FC was similar to that obtained with the lowest dose of isoflurane at 0.5% while higher doses of isoflurane displayed increased FC. Interestingly, only α-chloralose elicited relatively much greater increases in the ipsi-stimulus evoked response (i.e., in S1fl ipsilateral to the stimulated forelimb) than those associated with the contra-stimulus response, suggesting enhanced neuronal excitability. Taken together, the findings demonstrate modulation of the FC profiles by anesthesia is highly non-linear, possibly with a distinct underlying mechanism that affects either resting state or evoked activities differently. Further, the current study warrants thorough investigation of the basal neuronal states prior to the interpretation of resting state FC and evoked activities for accurate understanding of neural signal processing and circuitry.
Long-term posterolateral spinal fusion in rabbits induced by rhBMP6 applied in autologous blood coagulum with synthetic ceramics
Authors: Stokovic Nikola , Ivanjko Natalia , Pecin Marko , Erjavec Igor , Smajlović Ana , Milesevic Marina , Karlovic Sven , Capak Hrvoje , Vrbanac Zoran , Maticic Drazen , Vukicevic Slobodan 
Published: July 2022

AbstractAutologous bone graft substitute (ABGS) containing rhBMP6 in autologous blood coagulum (Osteogrow) is a novel therapeutic solution for bone regeneration. This study is aimed to investigate the long-term outcome of ABGS with synthetic ceramics (Osteogrow-C) in rabbit posterolateral spinal fusion (PLF) model. Osteogrow-C implants were implanted bilaterally between rabbit lumbar transverse processes. We compared the outcome following implantation of ABGS with ceramic particles of different chemical composition (TCP and biphasic ceramics containing both TCP and HA) and size (500–1700 µm and 74–420 µm). Outcome was analyzed after 14 and 27 weeks by microCT, histology, and biomechanical analyses. Successful bilateral spinal fusion was observed in all animals at the end of observation period. Chemical composition of ceramic particles has impact on the PLF outcome via resorption of TCP ceramics, while ceramics containing HA were only partially resorbed. Moreover, persistence of ceramic particles subsequently resulted with an increased bone volume in implants with small particles containing high proportion of HA. ABGS (rhBMP6/ABC) with various synthetic ceramic particles promoted spinal fusion in rabbits. This is the first presentation of BMP-mediated ectopic bone formation in rabbit PLF model with radiological, histological, and biomechanical features over a time course of up to 27 weeks.
Ultra-high resolution, multi-scale, context-aware approach for detection of small cancers on mammography
Authors: Rangarajan Krithika , Gupta Aman , Dasgupta Saptarshi , Marri Uday , Gupta Arun Kumar , Hari Smriti , Banerjee Subhashis , Arora Chetan 
Published: July 2022

AbstractWhile detection of malignancies on mammography has received a boost with the use of Convolutional Neural Networks (CNN), detection of cancers of very small size remains challenging. This is however clinically significant as the purpose of mammography is early detection of cancer, making it imperative to pick them up when they are still very small. Mammography has the highest spatial resolution (image sizes as high as 3328 × 4096 pixels) out of all imaging modalities, a requirement that stems from the need to detect fine features of the smallest cancers on screening. However due to computational constraints, most state of the art CNNs work on reduced resolution images. Those that work on higher resolutions, compromise on global context and work at single scale. In this work, we show that resolution, scale and image-context are all important independent factors in detection of small masses. We thereby use a fully convolutional network, with the ability to take any input size. In addition, we incorporate a systematic multi-scale, multi-resolution approach, and encode image context, which we show are critical factors to detection of small masses. We show that this approach improves the detection of cancer, particularly for small masses in comparison to the baseline model. We perform a single institution multicentre study, and show the performance of the model on a diagnostic mammography dataset, a screening mammography dataset, as well as a curated dataset of small cancers < 1 cm in size. We show that our approach improves the sensitivity from 61.53 to 87.18% at 0.3 False Positives per Image (FPI) on this small cancer dataset. Model and code are available from https://github.com/amangupt01/Small_Cancer_Detection
Interconnectedness between periodontitis stage, oral hygiene habits, adherence to the Mediterranean diet and nutritional status in Dalmatian kidney transplant recipients: a cross-sectional study
Authors: Radić Josipa , Vučković Marijana , Gelemanović Andrea , Roguljić Marija , Orešković Josip , Kovačević Katja , Kolak Ela , Nenadić Dora Bučan , Radić Mislav 
Published: July 2022

AbstractThe aim of this cross-sectional study was to determine the associations between the Mediterranean diet (MeDi), nutritional status parameters, muscle strength, and periodontal status in Dalmatian kidney transplant recipients (KTRs). 89 KTRs were included in this analysis, 40 (45%) women, with a mean age of 61 years (IQR = 13) and a mean time since kidney transplantation of 5 years (IQR = 6.6). An OHIP-14 questionnaire and questionnaire-based periodontal history were obtained from all participants, a comprehensive periodontal examination was performed. Body composition data, anthropometric and clinical parameters were collected for each study participant. The Mediterranean Diet Serving Score (MDSS) was used to assess MeDi adherence, and handgrip strength was measured with a hand dynamometer. Our results showed low adherence to MeDi in KTRs (28%) and almost 50% of KTRs suffer from severe forms of periodontitis. We also found a low OHIP-14 score and poor oral hygiene habits. KTRs with a less severe form of periodontitis had higher muscle mass and handgrip strength. MDSS score was associated with a higher number of teeth, and everyday cereal intake was inversely associated with the periodontitis stage. Our results demonstrate the associations between nutritional status, muscle strength, dietary habits, and periodontal health in Dalmatian KTRs.
A comparison of explainable artificial intelligence methods in the phase classification of multi-principal element alloys
Authors: Lee Kyungtae , Ayyasamy Mukil V. , Ji Yangfeng , Balachandran Prasanna V. 
Published: July 2022

AbstractWe demonstrate the capabilities of two model-agnostic local post-hoc model interpretability methods, namely breakDown (BD) and shapley (SHAP), to explain the predictions of a black-box classification learning model that establishes a quantitative relationship between chemical composition and multi-principal element alloys (MPEA) phase formation. We trained an ensemble of support vector machines using a dataset with 1,821 instances, 12 features with low pair-wise correlation, and seven phase labels. Feature contributions to the model prediction are computed by BD and SHAP for each composition. The resulting BD and SHAP transformed data are then used as inputs to identify similar composition groups using k-means clustering. Explanation-of-clusters by features reveal that the results from SHAP agree more closely with the literature. Visualization of compositions within a cluster using Ceteris-Paribus (CP) profile plots show the functional dependencies between the feature values and predicted response. Despite the differences between BD and SHAP in variable attribution, only minor changes were observed in the CP profile plots. Explanation-of-clusters by examples show that the clusters that share a common phase label contain similar compositions, which clarifies the similar-looking CP profile trends. Two plausible reasons are identified to describe this observation: (1) In the limits of a dataset with independent and non-interacting features, BD and SHAP show promise in recognizing MPEA composition clusters with similar phase labels. (2) There is more than one explanation for the MPEA phase formation rules with respect to the set of features considered in this work.
Identification of the major photodegradant in metronidazole by LC-PDA-MS and its reveal in compendial methods
Authors: Chen Mei-Ling , Xu Hong-Xia , Yuan Wei-Feng , Zhao Sui-Hong , Li Xue , Zhu Lan-Xin , Shen Zong-Yong , Liu Yu-Jing , Wang Ming-Juan , Ma Ang , Hoogmartens Jos , Adams Erwin 
Published: July 2022

AbstractMetronidazole in aqueous solution is sensitive to light and UV irradiation, leading to the formation of N-(2-hydroxyethyl)-5-methyl-l,2,4-oxadiazole-3-carboxamide. This is revealed here by liquid chromatography with tandem photo diode array detection and mass spectrometry (LC-PDA-MS) and further verified by comparison with the corresponding reference substance and proton nuclear magnetic resonance (1H-NMR). However, in current compendial tests for related substances/organic impurities of metronidazole, the above photolytic degradant could not be detected. Thus, when photodegradation of metronidazole occurs, it could not be demonstrated. In our study, an improved LC method was developed and validated, which includes a detection at a wavelength of 230 nm and optimization of mobile phase composition thereby a better separation was obtained.
Coverage optimization of soil moisture wireless sensor networks based on adaptive Cauchy variant butterfly optimization algorithm
Authors: Liang Jinyan , Tian Min , Liu Yang , Zhou Jie 
Published: July 2022

AbstractSoil moisture wireless sensor networks (SMWSNs) are used in the field of information monitoring for precision farm irrigation, which monitors the soil moisture content and changes during crop growth and development through sensor nodes at the end. The control terminal adjusts the irrigation water volume according to the transmitted information, which is significant for increasing the crop yield. One of the main challenges of SMWSNs in practical applications is to maximize the coverage area under certain conditions of monitoring area and to minimize the number of nodes used. Therefore, a new adaptive Cauchy variant butterfly optimization algorithm (ACBOA) has been designed to effectively improve the network coverage. More importantly, new Cauchy variants and adaptive factors for improving the global and local search ability of ACBOA, respectively, are designed. In addition, a new coverage optimization model for SMWSNs that integrates node coverage and network quality of service is developed. Subsequently, the proposed algorithm is compared with other swarm intelligence algorithms, namely, butterfly optimization algorithm (BOA), artificial bee colony algorithm (ABC), fruit fly optimization algorithm (FOA), and particle swarm optimization algorithm (PSO), under the conditions of a certain initial population size and number of iterations for the fairness and objectivity of simulation experiments. The simulation results show that the coverage rate of SMWSNs after ACBOA optimization increases by 9.09%, 13.78%, 2.57%, and 11.11% over BOA, ABC, FOA, and PSO optimization, respectively.