bluuebunny/crossref_metadata_2025_split huggingface dataset:
Along‐strike variation in the shear wave crustal structure of the NE Himalayan and Indo‐Burmese arc: Evidence based on surface wave dispersion analysis
Authors: Chanu Nongmaithem Menaka , Kumar Naresh , Kumar Amit , Mukhopadhyay Sagarika , Babu Vivek G. 
Published: May 2022

Surface wave dispersion data is used to infer the shear wave velocity structure variation in the north‐east Himalaya and Indo‐Burmese arc regions. We have used 25 earthquakes data from four groups with a magnitude range of 5.0–6.7, epicentral distance range 368–800 km, and focal depth less than 50 km. Ray paths from the earthquake location to the seismic station are transversely passing different geotectonic units of the Himalayas, Indo‐Gangetic plains, and Indo‐Burma collision zones. The weighted average dispersion curve and the path averaged shear wave velocity models are computed for the four groups located at different azimuths around Shillong seismic station. Non‐linear least‐square inversion is performed to obtain the shear wave velocity structure of the crust and uppermost mantle from joint inversion of Rayleigh and Love waves group velocities. Subsequently, Rayleigh and Love waves group velocities are inverted separately to obtain vertical and horizontal components of S‐wave velocity. Next, using these components anisotropy coefficient values at different depths for each path are also estimated. A high variation of dispersion curves and the shear wave velocity models from one group to another indicates that the region is geotectonically very complex. An approximately 80 km‐thick zone beneath the study region has shear wave velocity as low as 1.7 km/s in the uppermost crust in the southern part and ~4.7 km in the uppermost mantle beneath the Eastern Himalayan Syntaxis (EHS). Inferred velocity is also lower than that of PREM and AK135 global models with a much thicker crust beneath the study region. Radial anisotropy varies even within the northern part from the Indo‐Eurasian collision zone to EHS and northern to southern Indo‐Burma ranges. Anisotropy is comparatively stronger in the deeper part below ~40 km for the three paths, except for the EHS, where the result is contrary.
Deep learning‐based semantic segmentation of interphase cells and debris from metaphase images
Authors: Sathyan Remya Remani , Menon Gopakumar Chandrasekhara , Prasad Hari , Sreedharan Hariharan , Hemanth Duraisamy Jude 
Published: May 2022

AbstractSegmentation plays an essential role in the design of the automated karyotyping system (AKS). It is pivotal to segment interphase cells and other debris usually found in the input G metaphase images. The performance of AKSs is considerably less when interphase cells and debris are present in the input images. In this article, two semantic segmentation models are proposed. For this experiment, an annotated dataset is generated from the G banded metaphase images which are prepared at Regional Cancer Centre (RCC), Thiruvananthapuram, Kerala, India. Inspired by the results of UNet, a lighter version L‐UNet is developed and experimented with. It shows the validation IoU (Intersection over Union) of 0.9809 and F1‐score of 0.9903 on the RCC dataset and the test IoU of 0.9720 and F1‐score of 0.9858 on the CRCN‐NE dataset. As backbone semantic segmentation models are state of the art, an efficient model, Eff‐UNet, is also proposed here. In this model, EfficientNetB03 acts as the backbone that extracts powerful features and UNet acts as the decoder that predicts the segmentation map. It performs with the validation IoU of 0.9842 and F1‐score of 0.9920 on the RCC dataset and the test IoU of 0.7545 and F1‐score of 0.7778 on the CRCN‐NE dataset. To derive this model, 25 encoder–decoder architectures are evaluated with various top‐performing CNNs (convolutional neural networks) as encoders and segmentation networks as decoders. Results are further compared with various segmentation models and the best results are obtained from the proposed model.
Data imputation in deep neural network to enhance breast cancer detection
Authors: Ganesan Kanimozhi , Pichai Shanmugavadivu , Kavitha Muthu Subash , Takahashi Masayoshi 
Published: May 2022

AbstractBreast cancer is one of the most precarious cancers that claims many women's' lives every year. The existing automated systems for mammography datasets are designed to detect the abnormalities and classify them as benign or malignant. However, these systems ignore the incompleteness of data due to missing or irrelevant values in the dataset, which severely impede the automated system's reliability. To enhance the reliability of the decision outcomes, this study proposes a composite imputed multilayer fully connected deep networks (MFCN) that can replace the incomplete values in the dataset to augment the efficient feature learning for breast cancer classification. The data imputation techniques and one‐hot encoding transformation applied to the dataset are proved to improve the feature representation. The imputed features extracted from the instances are fed into the MFCN to classify malignant and benign by utilizing mammographic mass (MM) and INbreast datasets. The performance of the proposed missing data imputation treated MFCN (MdI‐MFCN) is compared with competitive machine learning (ML) classifiers by incorporating stratified 6‐fold cross‐validation. The experimental results of the models are evaluated with and without imputed data using the five performance metrics, namely, accuracy, precision, recall, F1‐score, and specificity. The performance of the proposed MdI‐MFCN has outperformed the competitive classifiers with the highest accuracy of 93% and 98% of the area under the receiver operating characteristic (ROC) curve on MM and INbreast datasets, respectively. The simplicity and reliability of this proposed approach its potential in characterizing mammography datasets during breast cancer diagnosis.
TargetingDNAtopoisomeraseIIα(TOP2A) in the hypoxic tumour microenvironment using unidirectional hypoxia‐activated prodrugs (uHAPs)
Authors: Smith Paul J. , McKeown Stephanie R. , Patterson Laurence H. 
Published: May 2022

AbstractThe hypoxic tumour microenvironment (hTME), arising from inadequate and chaotic vascularity, can present a major obstacle for the treatment of solid tumours. Hypoxic tumour cells compromise responses to treatment since they can generate resistance to radiotherapy, chemotherapy and immunotherapy. The hTME impairs the delivery of a range of anti‐cancer drugs, creates routes for metastasis and exerts selection pressures for aggressive phenotypes; these changes potentially occur within an immunosuppressed environment. Therapeutic strategies aimed at the hTME include targeting the molecular changes associated with hypoxia. An alternative approach is to exploit the prevailing lack of oxygen as a principle for the selective activation of prodrugs to target cellular components within the hTME. This review focuses on the design concepts and rationale for the use of unidirectional Hypoxia‐Activated Prodrugs (uHAPs) to target the hTME as exemplified by the uHAPs AQ4N and OCT1002. These agents undergo irreversible reduction in a hypoxic environment to active forms that target DNA topoisomerase IIα (TOP2A). This nuclear enzyme is essential for cell division and is a recognised chemotherapeutic target. An activated uHAP interacts with the enzyme‐DNA complex to induce DNA damage, cell cycle arrest and tumour cell death. uHAPs are designed to overcome the shortcomings of conventional HAPs and offer unique pharmacodynamic properties for effective targeting of TOP2A in the hTME. uHAP therapy in combination with standard of care treatments has the potential to enhance outcomes by co‐addressing the therapeutic challenge presented by the hTME.
Effects of dexmedetomidine on cognitive dysfunction and neuroinflammation via the HDAC2/HIF‐1α/PFKFB3 axis in a murine model of postoperative cognitive dysfunction
Authors: Liu Yu‐Fang , Hu Rui , Zhang Long‐Fei , Fan Yong , Xiao Ji‐Feng , Liao Xing‐Zhi 
Published: May 2022

AbstractInhibition of histone deacetylase (HDAC) may be a useful approach in the treatment of disorders characterized by cognitive dysfunction. Dexmedetomidine (DEX), an α2‐adrenoceptor (α2‐AR) agonist, has demonstrated neuroprotective effects. Here, we attempted to investigate the protective effects of DEX on postoperative cognitive dysfunction (POCD) involving HDAC2. Male C57BL/6 mice were selected to develop a POCD model, where HDAC2, HIF‐1α, and PFKFB3 expression was quantified. DEX was administered before POCD modeling. Then the cognitive function of POCD mice was evaluated with the open field and Y‐maze tests. Meanwhile, lipopolysaccharide (LPS) was employed to induce BV‐2 microglial cells to simulate the inflammatory response. The contents of TNF‐α, IL‐6, and IL‐10 were measured by enzyme‐linked immunosorbent assay (ELISA) in mouse serum and BV‐2 cell supernatant. Abundant expression of HDAC2, HIF‐1α, and PFKFB3 was confirmed in POCD mice (p < 0.05). Cognitive dysfunction in POCD mice could be alleviated following pharmacological inhibition of HDAC2 by FK228 (p < 0.05). Mechanistically, HDAC2 upregulated HIF‐1α and PFKFB3 and promoted the secretion of inflammatory factors in LPS‐exposed BV‐2 cells (p < 0.05). DEX attenuated neuroinflammation and the resulting cognitive dysfunction by decreasing HDAC2 expression and HIF‐1α‐dependent PFKFB3 upregulation in POCD mice (p < 0.05). In conclusion, DEX‐regulated HDAC2 may play an inhibitory role in mice with POCD through regulation of the HIF‐1α/PFKFB3 axis.
Association of serum hepatoma‐derived growth factor levels with disease activity in rheumatoid arthritis: A pilot study
Authors: Ahn Sung Soo , Kim Hye Min , Park Younhee 
Published: May 2022

AbstractBackgroundHepatoma‐derived growth factor (HDGF) is reported to play an important role in tumorigenesis and cancer progression. However, growing evidence indicates its participation in immune system activation. This study analyzed the relationship among serum HDGF levels, disease activity, and laboratory markers in patients with rheumatoid arthritis (RA).MethodsBlood samples from 165 patients with RA, 42 with osteoarthritis (OA), and 28 healthy controls, were used to evaluate the serum HDGF levels. Correlations of serum HDGF levels with age, 28‐joint count disease activity score (DAS28), and laboratory findings were assessed by Pearson correlation and receiver operator characteristic (ROC) curve analyses to obtain HDGF optimal cutoffs according to the disease status. Immunohistochemical staining was performed on the knee synovial tissue samples from patients with RA and OA (n = 10 each) to investigate HDGF joint expression.ResultsSerum HDGF levels were significantly correlated with DAS28 erythrocyte sedimentation rate (r = 0.412, p < 0.001) and C‐reactive protein values (r = 0.376, p < 0.001). The optimal cutoffs of serum HDGF levels from the ROC analysis were 5.79 and 5.14 for the differentiation of active/inactive disease and remission/non‐remission, respectively. The ideal cutoff of serum HDGF levels to differentiate RA and OA was determined as 5.47. Serial serum HDGF level analyses in 21 patients with RA revealed that serum HDGF levels significantly decreased after improvement in disease activity (p = 0.046). HDGF expression was not observed in the synovial tissues of the patients with RA and OA.ConclusionSerum HDGF level could be a potential laboratory biomarker for the severity of RA.
Quantitative Apparent Diffusion Coefficients From Peritumoral Regions as Early Predictors of Response to Neoadjuvant Systemic Therapy in Triple‐Negative Breast Cancer
Authors: Musall Benjamin C. , Adrada Beatriz E. , Candelaria Rosalind P. , Mohamed Rania M. M. , Abdelhafez Abeer H. , Son Jong Bum , Sun Jia , Santiago Lumarie , Whitman Gary J. , Moseley Tanya W. , Scoggins Marion E. , Mahmoud Hagar S. , White Jason B. , Hwang Ken‐Pin , Elshafeey Nabil A. , Boge Medine , Zhang Shu , Litton Jennifer K. , Valero Vicente , Tripathy Debu , Thompson Alastair M. , Yam Clinton , Wei Peng , Moulder Stacy L. , Pagel Mark D. , Yang Wei T. , Ma Jingfei , Rauch Gaiane M. 
Published: May 2022

BackgroundPathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in triple‐negative breast cancer (TNBC) is a strong predictor of patient survival. Edema in the peritumoral region (PTR) has been reported to be a negative prognostic factor in TNBC.PurposeTo determine whether quantitative apparent diffusion coefficient (ADC) features from PTRs on reduced field‐of‐view (rFOV) diffusion‐weighted imaging (DWI) predict the response to NAST in TNBC.Study TypeProspective.Population/SubjectsA total of 108 patients with biopsy‐proven TNBC who underwent NAST and definitive surgery during 2015–2020.Field Strength/SequenceA 3.0 T/rFOV single‐shot diffusion‐weighted echo‐planar imaging sequence (DWI).AssessmentThree scans were acquired longitudinally (pretreatment, after two cycles of NAST, and after four cycles of NAST). For each scan, 11 ADC histogram features (minimum, maximum, mean, median, standard deviation, kurtosis, skewness and 10th, 25th, 75th, and 90th percentiles) were extracted from tumors and from PTRs of 5 mm, 10 mm, 15 mm, and 20 mm in thickness with inclusion and exclusion of fat‐dominant pixels.Statistical TestsADC features were tested for prediction of pCR, both individually using Mann–Whitney U test and area under the receiver operating characteristic curve (AUC), and in combination in multivariable models with k‐fold cross‐validation. A P value < 0.05 was considered statistically significant.ResultsFifty‐one patients (47%) had pCR. Maximum ADC from PTR, measured after two and four cycles of NAST, was significantly higher in pCR patients (2.8 ± 0.69 vs 3.5 ± 0.94 mm2/sec). The top‐performing feature for prediction of pCR was the maximum ADC from the 5‐mm fat‐inclusive PTR after cycle 4 of NAST (AUC: 0.74; 95% confidence interval: 0.64, 0.84). Multivariable models of ADC features performed similarly for fat‐inclusive and fat‐exclusive PTRs, with AUCs ranging from 0.68 to 0.72 for the cycle 2 and cycle 4 scans.Data ConclusionQuantitative ADC features from PTRs may serve as early predictors of the response to NAST in TNBC.Evidence Level1Technical EfficacyStage 4
Assessing the changes of precipitation extremes in Peninsular Malaysia
Authors: Ng Cia Yik , Wan Jaafar Wan Zurina , Mei Yiwen , Othman Faridah , Lai Sai Hin , Liew Juneng 
Published: May 2022

AbstractThe rise of global surface temperature due to warming climate is expected to increase the intensity and occurrence of extreme precipitation events. Previous studies in Southeast Asia revealed complex variations in changes of precipitation extremes. This study presents a spatial–temporal analysis on changes of precipitation extremes in Peninsular Malaysia by utilizing long‐term daily rainfall records at 64 observed stations during 1989–2018. The modified Mann–Kendall and Sen's slope tests were performed to detect the significance and magnitude of trends in eight extreme precipitation indices recommended by the Expert Team on Climate Change Detection and Indices. Statistically significant increasing trends are observed for four of these extreme indices in the annual assessment. Spatial analysis demonstrates an obvious contrast between wet and dry regions in patterns of precipitation extremes. Seasonal analysis reveals the intensity and frequency of wet extremes are enhanced significantly during the northeast monsoon season. Significant correlations are found between precipitation extremes and El Niño–Southern Oscillation, particularly in the northern, eastern and southwest regions. Collectively, the evidence presented suggests that the occurrence of precipitation extremes in Peninsular Malaysia tends to be more frequent and intense over the year and is closely associated with the combined effects of tropical monsoon cycles and El Niño–Southern Oscillation.
Preageing of the skin among Asian populations
Authors: Anwar Siti S. , Smith Saxon D. , Pongprutthipan Marisa , Kim Ji Young , Yuan Chao , van Steensel Maurice 
Published: May 2022

AbstractSkin ageing is a complex process. Both intrinsic and extrinsic factors have a role in determining the speed, progression and phenotypic outcomes of the process. Typical clinical signs of ageing, such as wrinkles, thinning and sagging of the skin, are usually first noticed in the mid‐20s to early 30s. However, real‐world studies report that younger Asian women between the ages of 18 and 24 years are perceiving emerging signs of ageing, including dull skin, uneven skin tone, dryness, transient wrinkles, and a lack of skin firmness. These observations have led to a hypothesis that a phase of preageing may exist, where clinical signs of ageing are not yet present, but an individual starts to notice subtle changes in their skin's appearance. This paper discusses the concept of preageing in Asian populations and provides recommendations for recognising and managing the preageing process in clinical practice.
Tannic acid‐copper metal‐organic frameworks decorated graphene oxide for reinforcement of the corrosion protection of waterborne epoxy coatings
Authors: Cheng Li , Hou Peimin , Liu Chengbao 
Published: May 2022

AbstractWaterborne anticorrosion coatings have aroused tremendous attention in the metal protection field due to their environmentally friendly properties. However, the limited barrier performance and poor resistance to corrosive species severely impede its practical applications. Herein, tannic acid‐copper metal‐organic framework (TA‐Cu) was first synthesized via oxidative coordination and then assembled with graphene oxide to obtain TA‐Cu‐decorated graphene oxide (TAG), which was utilized to improve the anticorrosion performance of waterborne epoxy (WEP) coatings. Electrochemical measurements demonstrated that the impermeability of WEP has been significantly enhanced with the incorporation of TAG. Meanwhile, local electrochemical impedance spectroscopy tests indicated that the corrosion reaction at defected region can be effectively suppressed, presenting an active anticorrosion function. The protection mechanisms are attributed to (1) TA‐Cu contributed to the dispersion of graphene oxide in WEP and impeded the intrusion of aggressive ions and (2) the coordination and adsorption of TA on steel inhibited the redox process and corrosion extension.
Disordered Decision Making: A Cognitive Framework for Apathy and Impulsivity in Huntington's Disease
Authors: Morris Lee‐Anne , O'Callaghan Claire , Le Heron Campbell 
Published: May 2022

AbstractA caregiver's all‐too‐familiar narrative ‐ “He doesn't think through what he does, but mostly he does nothing.” Apathy and impulsivity, debilitating and poorly understood, commonly co‐occur in Huntington's disease (HD). HD is a neurodegenerative disease with manifestations bridging clinical neurology and psychiatry. In addition to movement and cognitive symptoms, neurobehavioral disturbances, particularly apathy and impulsivity, are prevalent features of HD, occurring early in the disease course, often worsening with disease progression, and substantially reducing quality of life. Treatments remain limited, in part because of limited mechanistic understanding of these behavioral disturbances. However, emerging work within the field of decision‐making neuroscience and beyond points to common neurobiological mechanisms underpinning these seemingly disparate problems. These insights bridge the gap between underlying disease pathology and clinical phenotype, offering new treatment strategies, novel behavioral and physiological biomarkers of HD, and deeper understanding of human behavior. In this review, we apply the neurobiological framework of cost‐benefit decision making to the problems of apathy and impulsivity in HD. Through this decision‐making lens, we develop a mechanistic model that elucidates the occurrence of these behavioral disturbances and points to potential treatment strategies and crucial research priorities. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson Movement Disorder Society.
Anthropometric evaluation of a 3D scanning mobile application
Authors: Smith Brooke , McCarthy Cassidy , Dechenaud Marcelline E. , Wong Michael C. , Shepherd John , Heymsfield Steven B. 
Published: May 2022

AbstractObjectiveThree‐dimensional (3D) imaging systems are increasingly being used in health care settings for quantifying body size and shape. The potential exists to provide similar phenotyping capabilities outside of professional settings using smartphone applications (apps). The current study aim was to compare waist, hip, upper arm, and midthigh circumference measurements acquired by a free downloadable app (MeThreeSixty; Size Stream, Cary, North Carolina) and a conventional 20‐camera 3D system (SS20; Size Stream) with those measured with a flexible tape at the same anatomic sites.MethodsFifty‐nine adults were scanned with the app and SS20; the same software was used to generate circumference estimates from device‐acquired object files that were then compared with reference tape measurements.ResultsThe app and SS20 had similar coefficients of variation that were minimally larger than those by the tape (e.g., waist, 0.93%, 0.87%, and 0.06%). Correlations of the app and of SS20 with tape circumferences were all strong (p < 0.001) and similar in magnitude (R2s: 0.72‐0.93 and 0.78‐0.95, respectively); minimally significant (p < 0.05 to p < 0.01) bias was present between both imaging approaches and some tape measurements.ConclusionThese proof‐of‐concept observations combined with ubiquitous smartphone availability create the possibility of phenotyping adult body size and shape, with important clinical and research implications, on a global scale.
A new type of unsaturated polyester resin with epoxy functionalized nano‐silica and dimer fatty acid: Preparation and property
Authors: Huang Xue , Guo Yan‐ting , Yan Xu‐ming , Yin Guo‐qiang , Feng Guang‐zhu 
Published: May 2022

AbstractThe surface of reactive nano‐silica coated with a silage coupling agent containing the epoxy group (denoted as E‐SiO2) and dimer fatty acids (DFA) were allowed to participate in the in‐situ polycondensation reaction of unsaturated polyester resin (UPR), thus obtaining E‐SiO2/DFA/UPR hybrid material. Fourier transform infrared spectrometer, scanning electron microscope, and X‐ray energy dispersive spectrometer were used to analyze the structure of the material, morphology of tensile section, and the element composition of the section. It was found that E‐SiO2 grafted onto the DFA/UPR backbone by chemical bonds, and the material exhibited ductile fracture with Si element on the fracture surface. Thermogravimetric analysis, differential scanning calorimetry, stress–strain test, tensile test, bending test, hardness test, and water resistance test, the influence of the content of E‐SiO2 on the thermal stability, mechanical properties, and water resistance of the materials was studied. The results show that E‐SiO2 has a good reinforcing and toughening effect for the in‐situ polymerized E‐SiO2/DFA/UPR composite due to the chemical reaction between the epoxy group of E‐SiO2 and the hydroxyl group (carboxyl group) of DFA/UPR. A heterogeneous network structure was formed in the cured E‐SiO2/DFA/UPR composites. The mechanical properties and thermal properties of E‐SiO2 nanocomposites were improved. When 0.8 wt% E‐SiO2 was added, the tensile strength, Young's modulus, flexural strength, flexural stress, elongation at break, and Shore A hardness increased by 37.03%, 69.18%, 86.81%, 86.80%, 14.0%, and 14.71%, respectively, compared to DFA/UPR. At the same time, the addition of E‐SiO2 also improved the water resistance of hybrid materials.