bluuebunny/crossref_metadata_2025 huggingface dataset:
Paradox of strategic partnerships for sustainable value chains: Perspectives of not‐for‐profit actors
Authors: Jraisat Luai , Jreissat Mohannad , Upadhyay Arvind , Sajjad Farhana , Balodi Krishna Chandra
Published: May 2022

The study explores strategic partnerships themes for Sustainable Agricultural Value chains (SAVC) dimensions. Acknowledging the role of stakeholders, business and not‐for‐profit actors, and their engagement in such partnerships, this study focuses on the latter's perspective. Literature review followed by five exploratory case studies are used to examine SAVC partnership themes. The study identifies three themes influencing strategic partnerships: the interaction between partners through cooperation, coordination, and collaboration; management of information flow between partners; and product flow management with demand–supply coordination between partners. The level of information sharing between partners also influences SAVC value creation. The findings extend value chain literature by stressing the theoretical association between the identified antecedents and partnership in the sustainability value chain in general and the SAVC in particular. The exploratory case studies provide real‐life perspectives and a practical framework in the context of SAVC. Managers, policymakers and international funded programs can also benefit from the current key findings and the new framework as a referential basis to form a partnership strategy in agricultural sectors. This research suggests a further test for the conceptual framework using large‐scale surveys in diverse geographic contexts and looking at trans‐border value chain partnerships, especially in different country contexts that influence sustainable development and partnerships in SAVC.
A randomized phase II study of SM‐88 plus methoxsalen, phenytoin, and sirolimus in patients with metastatic pancreatic cancer treated in the second line and beyond
Authors: Noel Marcus S. , Kim Semmie , Hartley Marion L. , Wong Steve , Picozzi Vincent J. , Staszewski Harry , Kim Dae Won , Van Tornout Jan M. , Philip Philip Agop , Chung Vincent , Ocean Allyson J. , Wang‐Gillam Andrea
Published: May 2022

Background

This trial explores SM‐88 used with methoxsalen, phenytoin, and sirolimus (MPS) in pretreated metastatic pancreatic ductal adenocarcinoma (mPDAC)

Methods

Forty‐nine patients were randomized to daily 460 or 920 mg oral SM‐88 with MPS (SM‐88 Regimen). The primary endpoint was objective response rate (RECIST 1.1).

Results

Thirty‐seven patients completed ≥ one cycle of SM‐88 Regimen (response evaluable population). Disease control rate (DCR), overall survival (OS), and progression‐free survival (PFS) did not differ significantly between dose levels. Stable disease was achieved in 9/37 patients (DCR, 24.3%); there were no complete or partial responses. Quality‐of‐life (QOL) was maintained and trended in favor of 920 mg. SM‐88 Regimen was well tolerated; a single patient (1/49) had related grade 3 and 4 adverse events, which later resolved. In the intention‐to‐treat population of 49 patients, the median overall survival (mOS) was 3.4 months (95% CI: 2.7–4.9 months). Those treated in the second line had an mOS of 8.1 months and a median PFS of 3.8 months. Survival was higher for patients with stable versus progressive disease (any line; mOS: 10.6 months vs. 3.9 months; p = 0.01).

Conclusions

SM‐88 Regimen has a favorable safety profile with encouraging QOL effects, disease control, and survival trends. This regimen should be explored in the second‐line treatment of patients with mPDAC.

ClinicalTrials.gov Identifier: NCT03512756.
Prediction of lung cancer risk in Chinese population with genetic‐environment factor using extreme gradient boosting
Authors: Li Yutao , Zou Zixiu , Gao Zhunyi , Wang Yi , Xiao Man , Xu Chang , Jiang Gengxi , Wang Haijian , Jin Li , Wang Jiucun , Wang Huai Zhou , Guo Shicheng , Wu Junjie
Published: May 2022

Background

Detecting early‐stage lung cancer is critical to reduce the lung cancer mortality rate; however, existing models based on germline variants perform poorly, and new models are needed. This study aimed to use extreme gradient boosting to develop a predictive model for the early diagnosis of lung cancer in a multicenter case–control study.

Materials and Methods

A total of 974 cases and 1005 controls in Shanghai and Taizhou were recruited, and 61 single nucleotide polymorphisms (SNPs) were genotyped. Multivariate logistic regression was used to calculate the association between signal SNPs and lung cancer risk. Logistic regression (LR) and extreme gradient boosting (XGBoost) algorithms, a large‐scale machine learning algorithm, were adopted to build the lung cancer risk model. In both models, 10‐fold cross‐validation was performed, and model predictive performance was evaluated by the area under the curve (AUC).

Results

After FDR adjustment, TYMS rs3819102 and BAG6 rs1077393 were significantly associated with lung cancer risk (p < 0.05). For lung cancer risk prediction, the model predicted only with epidemiology attained an AUC of 0.703 for LR and 0.744 for XGBoost. Compared with the LR model predicted only with epidemiology, further adding SNPs and applying XGBoost increased the AUC to 0.759 (p < 0.001) in the XGBoost model. BAG6 rs1077393 was the most important predictor among all SNPs in the lung cancer prediction XGBoost model, followed by TERT rs2735845 and CAMKK1 rs7214723. Further stratification in lung adenocarcinoma (ADC) showed a significantly elevated performance from 0.639 to 0.699 (p = 0.009) when applying XGBoost and adding SNPs to the model, while the best model for lung squamous cell carcinoma (SCC) prediction was the LR model predicted with epidemiology and SNPs (AUC = 0.833), compared with the XGBoost model (AUC = 0.816).

Conclusion

Our lung cancer risk prediction models in the Chinese population have a strong predictive ability, especially for SCC. Adding SNPs and applying the XGBoost algorithm to the epidemiologic‐based logistic regression risk prediction model significantly improves model performance.
In Situ Cofactor Regeneration Using NAD(P)H Oxidase: Enzyme Stability in a Bubble Column
Authors: Wang Jingyu , Woodley John M.
Published: May 2022

NAD(P)H and NAD(P)+ are important cofactors and currently receiving great interest in biocatalytic synthesis (e. g. the resolution of chiral alcohols and the synthesis of keto chemicals with high selectivity), where their regeneration is necessary in order to ensure the economic sustainability of syntheses based on NAD(P)H or NAD(P)+ dependent enzymes. This paper reports new details on the kinetic stability of a water‐forming NAD(P)H oxidase (NOX) for in‐situ cofactor regeneration in a bubble column. Two‐stage deactivation kinetics of NOX was observed at gas flowrates of 0.25 vvm and 0.50 vvm with half‐life of 29 h and 32 h, respectively. Single‐stage deactivation kinetics occurred at a higher gas flowrate of 0.75 vvm, while the half‐life of NOX was longer (40 h) because of the shorter residence time of the gas‐liquid interface. Finally, results from SDS‐PAGE suggest that there is no dissociation of NOX into its subunits but rather that NOX unfolding (and aggregation) at the interface led to the observed deactivation.
Online prediction based on the Copula function for the intrinsic viscosity of polyester fibre
Authors: Shi Jintao , Gao Jinchen , Chen Lei , Hao Kuangrong
Published: May 2022

The polymerization process, as the starting point of polyester fibre production, directly affects the fibre properties. However, the polymerization process has complex reaction mechanisms and involves many variables, making online modelling more challenging. In this paper, we introduce the Copula function into the modelling of the polymerization process. First, a feature selection method based on kernel principal component analysis (KPCA)‐Copula is proposed, and then, the Copula function to obtain the nonlinear characteristics among the variables is used. On this basis, an online prediction model of intrinsic viscosity based on just‐in‐time learning (JITL) was established, that is, empirical Copula‐JITL. In order to improve the computational efficiency of the empirical Copula‐JITL, the t‐Copula function is introduced. Furthermore, by combining the t‐Copula function with the empirical Copula function, we get a JITL model based on the hybrid Copula function, that is, hybrid Copula‐JITL. Finally, actual polymerization process data collected from fibre production are provided to demonstrate the effectiveness of the proposed algorithms.
Pd‐Catalyzed Cross‐Coupling of Alkylzirconocenes and Aryl Chlorides
Authors: Jiang Binyang , Shi Shi‐Liang
Published: May 2022

Comprehensive Summary

Alkylzirconocenes, readily prepared by hydrozirconation of alkenes with Schwartz's reagent, are perspective yet rarely exploited partners in transition‐metal catalyzed cross‐coupling reaction. The notoriously low nucleophilicity of alkylzirconocenes and the potential β‐H elimination restrict their application in cross‐coupling. Herein, we report the first Pd‐catalyzed aryl‐alkyl cross‐coupling of alkylzirconocenes and aryl halides. A commercially available N‐heterocyclic carbene (IPr) as the ligand for palladium catalyst is critical to enable the challenging process. This mild protocol does not require base additives and tolerates a broad scope of both coupling partners bearing various functional groups and heterocycles. Moreover, both terminal and internal alkenes are applicable, and the latter undergo “chain walking”, giving the terminal coupling product exclusively. Preliminary mechanistic studies reveal a precatalyst activation pathway and inhibited β‐H elimination due to steric bulk of NHC ligand.
PHRONESIS: A One‐Shot Approach for Sequential Assignment of Protein Resonances by Ultrafast MAS Solid‐State NMR Spectroscopy
Authors: Gopinath Tata , Manu Veliparambil S. , Weber Daniel K. , Veglia Gianluigi
Published: May 2022

Solid‐state NMR (ssNMR) spectroscopy has emerged as the method of choice to analyze the structural dynamics of fibrillar, membrane‐bound, and crystalline proteins that are recalcitrant to other structural techniques. Recently, 1H detection under fast magic angle spinning and multiple acquisition ssNMR techniques have propelled the structural analysis of complex biomacromolecules. However, data acquisition and resonance‐specific assignments remain a bottleneck for this technique. Here, we present a comprehensive multi‐acquisition experiment (PHRONESIS) that simultaneously generates up to ten 3D 1H‐detected ssNMR spectra. PHRONESIS utilizes broadband transfer and selective pulses to drive multiple independent polarization pathways. High selectivity excitation and de‐excitation of specific resonances were achieved by high‐fidelity selective pulses that were designed using a combination of an evolutionary algorithm and artificial intelligence. We demonstrated the power of this approach with microcrystalline U‐13C,15N GB1 protein, reaching 100 % of the resonance assignments using one data set of ten 3D experiments. The strategy outlined in this work opens up new avenues for implementing novel 1H‐detected multi‐acquisition ssNMR experiments to speed up and expand the application to larger biomolecular systems.
Use interactive process to determine if accommodations for Long COVID create fundamental alterations
Authors: Masinter Michael R.
Published: May 2022

Although the worst of the COVID pandemic appears to be over, its impact on disability services providers will continue through the effects of Long COVID and through continued fear of illness. Recent guidance from the Office for Civil Rights and the Department of Justice (https://bit.ly/3IPSbYh, which I previously discussed here: February 2022, https://bit.ly/3IPSbYh) notes that Long COVID, an occasional consequence of even mild COVID infections, can be a disability if it substantially limits a major life activity, and therefore can be expected to trigger requests for academic adjustments and reasonable accommodations. The guidance notes that common symptoms associated with Long COVID include but are not limited to fatigue; difficulty thinking or concentrating, sometimes referred to as brain fog; depression; anxiety; and heart palpitations, all of which may directly interfere with the ability to think and learn.
Review study results showing differences in experiences of disabled, nondisabled students during COVID‐19
Authors: Hope Joan
Published: May 2022

Compared with their nondisabled peers, students with disabilities were more likely to experience “compounded stressors during the COVID‐19 pandemic that affected their overall well‐being.” That's one result of a study reported in “COVID‐19 Related Experiences Among College Students With and Without Disabilities: Psychosocial Impacts, Supports, and Virtual Learning Environments,” published in Frontiers in Public Health.
ICAP‐1 loss impairs CD8+ thymocyte development and leads to reduced marginal zone B cells in mice
Authors: Sevilla‐Movilla Silvia , Fuentes Patricia , Rodríguez‐García Yaiza , Arellano‐Sánchez Nohemi , Krenn Peter W. , de Val Soledad Isern , Montero‐Herradón Sara , García‐Ceca Javier , Burdiel‐Herencia Valeria , Gardeta Sofía R. , Aguilera‐Montilla Noemí , Barrio‐Alonso Celia , Crainiciuc Georgiana , Bouvard Daniel , García‐Pardo Angeles , Zapata Agustin G. , Hidalgo Andrés , Fässler Reinhard , Carrasco Yolanda R. , Toribio Maria L. , Teixidó Joaquin
Published: May 2022

ICAP‐1 regulates β1‐integrin activation and cell adhesion. Here, we used ICAP‐1‐null mice to study ICAP‐1 potential involvement during immune cell development and function. Integrin α4β1‐dependent adhesion was comparable between ICAP‐1‐null and control thymocytes, but lack of ICAP‐1 caused a defective single‐positive (SP) CD8+ cell generation, thus, unveiling an ICAP‐1 involvement in SP thymocyte development. ICAP‐1 bears a nuclear localization signal and we found it displayed a strong nuclear distribution in thymocytes. Interestingly, there was a direct correlation between the lack of ICAP‐1 and reduced levels in SP CD8+ thymocytes of Runx3, a transcription factor required for CD8+ thymocyte generation. In the spleen, ICAP‐1 was found evenly distributed between cytoplasm and nuclear fractions, and ICAP‐1–/– spleen T and B cells displayed upregulation of α4β1‐mediated adhesion, indicating that ICAP‐1 negatively controls their attachment. Furthermore, CD3+‐ and CD19+‐selected spleen cells from ICAP‐1‐null mice showed reduced proliferation in response to T‐ and B‐cell stimuli, respectively. Finally, loss of ICAP‐1 caused a remarkable decrease in marginal zone B‐ cell frequencies and a moderate increase in follicular B cells. Together, these data unravel an ICAP‐1 involvement in the generation of SP CD8+ thymocytes and in the control of marginal zone B‐cell numbers.
Alterations of blood monocyte subset distribution and surface phenotype are linked to infection severity in COVID‐19 inpatients
Authors: Haschka David , Petzer Verena , Burkert Francesco Robert , Fritsche Gernot , Wildner Sophie , Bellmann‐Weiler Rosa , Tymoszuk Piotr , Weiss Guenter
Published: May 2022

Severe coronavirus disease 19 (COVID‐19) manifests with systemic immediate proinflammatory innate immune activation and altered iron turnover. Iron homeostasis, differentiation, and function of myeloid leukocytes are interconnected. Therefore, we characterized the cellularity, surface marker expression, and iron transporter phenotype of neutrophils and monocyte subsets in COVID‐19 patients within 72 h from hospital admission, and analyzed how these parameters relate to infection severity. Between March and November 2020, blood leukocyte samples from hospitalized COVID‐19 patients (n = 48) and healthy individuals (n = 7) were analyzed by flow cytometry enabling comparative analysis of 40 features. Inflammation‐driven neutrophil expansion, depletion of CD16+ nonclassical monocytes, and changes in surface expression of neutrophil and monocyte CD64 and CD86 were associated with COVID‐19 severity. By unsupervised self‐organizing map clustering, four patterns of innate myeloid response were identified and linked to varying levels of systemic inflammation, altered cellular iron trafficking and the severity of disease. These alterations of the myeloid leukocyte compartment during acute COVID‐19 may be hallmarks of inefficient viral control and immune hyperactivation and may help at risk prediction and treatment optimization.
Seismic fragility analysis of railway reinforced concrete bridges considering real‐time vehicle‐bridge interaction with the aid of co‐simulation techniques
Authors: Stefanidou Sotiria P. , Paraskevopoulos Elias A.
Published: May 2022

Based on past earthquake events, bridges are the most critical and most vulnerable component of road and rail transport systems, while bridge damage is related to substantial direct and indirect losses. For the case of railway bridges, the estimation of seismic fragility is a rather complex and computationally demanding procedure given the real‐time interaction of the train movement and the bridge and the different failure modes of subsystems. Considering vehicle‐bridge interaction (VBI) in the frame of railway bridge fragility analysis is rather challenging, requiring analysis of the bridge and the vehicle at every time step. Partitioning of the coupled VBI problem proposing a weak formulation scheme and a set of second‐order ordinary differential equations (ODEs) is performed in a way that allows for independent subsystem (vehicle and bridge) analysis. Several methodologies are available in the literature to estimate the seismic fragility of train‐bridge systems that ignore the nonlinear behavior of the bridge during earthquake loading, the step‐by‐step VBI, and the different failure modes of critical components. The scope of this research paper is to propose a real‐time component‐based methodology for estimating bridge fragility curves, considering all critical components and failure modes of subsystems. The two subsystems are incorporated in a uniform software platform using the co‐simulation approach and a Gauss‐Seidel communication pattern. The vehicle‐rail system is solved using a C++ tailor‐made code, including a mathematical formulation that is based on the description of the constrained problem with a set of pure ODEs, avoiding issues related to differential‐algebraic equations, constraint violation, drifts, energy loss, stability, and convergence. The vehicle subsystem is solved using multibody dynamics (MBD), while the bridge subsystem is modeled and solved using OpenSees.py. An ad‐hoc software for the implementation of the probabilistic framework and the derivation of fragility curves is developed in Python. A novel methodological procedure is proposed, dully tailored to the demanding estimation of fragility curves of the coupled vehicle‐bridge problem. The step‐by‐step solution of subsystems is performed using the co‐simulation technique. Real‐time interaction is allowed, considering a rational transfer of force, velocity, and displacement between subsystems. The methodology along with the software developed is described and applied to two representative reinforced concrete (RC) bridges of the Greek railway network (v≤200 m/sec), providing fragility curves (i.e., the seismic performance for various levels of earthquake intensity) for the coupled system. The results are discussed and assessed.
Safety distance for pressure‐resistance tests of cylindrical pressure vessels in the industrial field
Authors: Shin Seolin , Kim Eui Soo , Kang Chankyu , Jung Seungho
Published: May 2022

The number of pressure vessel bursts (PVBs) has reduced since the 1990s due to the introduction of many rules and regulations. However, accidents frequently occur during pressure resistance tests (pneumatics) and there are scant safety guidelines for examining pressure vessels. Thus, this study proposes a safe distance to prevent accidents during a test, based on the explosion energy and vessel shape. First, the maximum explosion energy was computed using Brode's equation and the distance and overpressure were nondimensionalized via Sachs' scaling. Next, the overpressure ratio of the spherical tank (opsphere) was calculated based on the overpressure ratio of the cylindrical tank (opcylinder), considering the length to diameter ratio of the cylindrical vessel. Finally, the function of the safety distance was obtained. The result was validated by comparing it with data from the catastrophic failure that occurred at D. D. Williamson & Co. Inc. in 2003. This study could help establish safety guidelines and the prevention of PVB damage.
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

Segmentation 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

Breast 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

The 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

Inhibition 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

Background

Hepatoma‐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).

Methods

Blood 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.

Results

Serum 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.

Conclusion

Serum 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

Background

Pathologic 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.

Purpose

To 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 Type

Prospective.

Population/Subjects

A total of 108 patients with biopsy‐proven TNBC who underwent NAST and definitive surgery during 2015–2020.

Field Strength/Sequence

A 3.0 T/rFOV single‐shot diffusion‐weighted echo‐planar imaging sequence (DWI).

Assessment

Three 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 Tests

ADC 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.

Results

Fifty‐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 Conclusion

Quantitative ADC features from PTRs may serve as early predictors of the response to NAST in TNBC.

Evidence Level

1

Technical Efficacy

Stage 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

The 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

Skin 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

Waterborne 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

A 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

Objective

Three‐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.

Methods

Fifty‐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.

Results

The 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.

Conclusion

These 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

The 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.
Doppelpack für genauere Wetterdaten
Authors: Asmus Jörg
Published: May 2022

Ab 1977 brachten die Europäer ihre erste Generation von Meteosat‐Wettersatelliten (Meteosat First Generation, MFG) in eine geostationäre Bahn. MFG war ein zylinderförmiger Satellit, der durch Rotation um seine Längsachse lagestabilisiert wurde. Dabei scannte er mit seinem Beobachtungsinstrument im infraroten und sichtbaren Spektralbereich die Erde ab. Das gleiche Grundprinzip nutzt die ab 2004 in Betrieb gegangene zweite Generation, Meteosat Second Generation (MSG). Allerdings besitzt ihr Hauptinstrument zur Beobachtung wesentlich mehr Spektralkanäle und kann schneller Bilder liefern. Die dritte Generation, Meteosat Third Generation (MTG), besteht hingegen aus nicht rotierenden Doppelsatelliten, die durch Gyroskope lagestabilisiert werden. Dadurch können sie permanent ihre verbesserten Instrumente auf die Erde ausrichten, ihre Solarzellen zur Sonne. Die Doppelsatelliten beobachten auch mehr Phänomene als MFG, zum Beispiel Blitze. Sie sollen wesentlich genauere Wettervorhersagen und Warnungen vor Wetterereignissen ermöglichen. Im Dezember 2022 soll der erste MTG starten.
Produktives Klangchaos
Authors: Mathelitsch Leopold , Verovnik Ivo
Published: May 2022

Bei Musik und Sprache denkt man automatisch an harmonische Klänge. Rauschen ist jedoch ebenfalls ein essentieller Bestandteil. Jedes Instrument hat ein charakteristisches Rauschverhalten im Klang. Noch wichtiger ist Rauschen beim Sprechen, ohne es könnte man keine Konsonanten bilden. Es gibt verschiedene Arten von Rauschen, in der Akustik dominiert weißes, rosa und braunes Rauschen. Rauschen wird aber auch medizinisch genutzt, zum Beispiel zur Tinnitus‐Behandlung.
Auf dem Weg zum Replikator
Authors: Regehly Martin , Hecht Stefan
Published: May 2022

Konventionelle 3D‐Druckverfahren erzeugen Objekte Schicht für Schicht. Sie sind weit entwickelt, benötigen jedoch lange Druckzeiten. Die Xolographie ist eine neue volumetrische Technologie, die unter Nutzung von photoschaltbaren Molekülen und einem Lichtschnitt‐basierten Schreibprozess das Ausgangsmaterial im freien Volumen prozessiert. Angewendet auf den 3D‐Druck macht das hohe Auflösungen, isotrope Materialeigenschaften und hohe Geschwindigkeiten möglich. Mit dem Einsatz mehrerer Lichtwellenlängen bietet der Ansatz in Zukunft noch vielfältige Entwicklungsmöglichkeiten.
Die diskrete Wissenschaft vom Magneten
Authors: Loos Andreas
Published: May 2022

Sein Modell des Magnetismus wird zu einer wissenschaftlichen Erfolgsgeschichte, ohne dass er dies über viele Jahre lang mitbekommt.
Adsorption and Sensing for SF6 Decomposition Products by Ru–MoTe2 Monolayer
Authors: Jiang Keruo , Yue Long , Xu Xin , Qian Xiying , Yan Ling , Zhao Luzhen , Shen Tao
Published: May 2022

In this work, the adsorption of SF6 decomposition products (SO2, SOF2, and SO2F2) on Ru–MoTe2 monolayer is investigated based on density‐functional theory (DFT) calculations. The doping structure, band structure, adsorption structure, adsorption energy, charge transfer, density of states (DOS), and molecular orbital are analyzed to better analyze the interaction mechanism between gas molecules and Ru–MoTe2 system. In the results, it is shown that the conductivity of MoTe2 monolayer can be greatly increased by doping Ru atom. Pristine MoTe2 shows a weak adsorption capacity for SO2, SOF2, and SO2F2 gases, which belongs to physical adsorption. When Ru atom is doped on MoTe2, the adsorption capacity of the doping system for these three gases is obviously improved. The adsorption capacity of Ru–MoTe2 monolayer to the gases is ranked as SO2F2 > SOF2 > SO2. Moreover, the strong interaction between gas molecules and Ru–MoTe2 surfaces leads to the rise of the conductivity of all adsorption systems to varying degrees, and the degree of the rise of conductivity influenced by gas molecules is ranked as SO2F2 > SO2 > SOF2. Herein, a theoretical basis for the preparation of gas sensors or adsorbers based on Ru–MoTe2 is provided for detecting and absorbing SF6 decomposition products.