bluuebunny/crossref_metadata_2025 huggingface dataset:
Longitudinal Assessment of Intravoxel Incoherent Motion Diffusion‐Weighted MRI Metrics in Cognitive Decline
Authors: Bergamino Maurizio , Burke Anna , Baxter Leslie C. , Caselli Richard J. , Sabbagh Marwan N. , Talboom Joshua S. , Huentelman Matthew J. , Stokes Ashley M.
Published: March 2022

Background

Advanced diffusion‐based MRI biomarkers may provide insight into microstructural and perfusion changes associated with neurodegeneration and cognitive decline.

Purpose

To assess longitudinal microstructural and perfusion changes using apparent diffusion coefficient (ADC) and intravoxel incoherent motion diffusion‐weighted imaging (IVIM‐DWI) parameters in cognitively impaired (CI) and healthy control (HC) groups.

Study Type

Prospective/longitudinal.

Population

Twelve CI patients (75% female) and 13 HC subjects (69% female).

Field Strength/Sequence

3 T; Spin‐Echo‐IVIM‐DWI.

Assessment

Two MRI scans were performed with a 12‐month interval. ADC and IVIM‐DWI metrics (diffusion coefficient [D] and perfusion fraction [f]) were generated from monoexponential and biexponential fits, respectively. Additionally, voxel‐based correlations were evaluated between change in Montreal Cognitive Assessment (ΔMoCA) and baseline imaging parameters.

Statistical Tests

Analysis of covariance with sex and age as covariates was performed for main effects of group and time (false discovery rate [FDR] corrected) with post hoc comparisons using Bonferroni correction. Partial‐η2 and Hedges' g were used for effect‐size analysis. Spearman's correlations (FDR corrected) were used for the relationship between ΔMoCA score and imaging. P < 0.05 was considered statistically significant.

Results

Significant differences were found for the main effects of group (HC vs. CI) and time. For group effects, higher ADC, IVIM‐D, and IVIM‐f were observed in the CI group compared to HC (ADC: 1.23 ± 0.08.10−3 vs. 1.09 ± 0.07.10−3 mm2/sec; IVIM‐D: 0.82 ± 0.01.10−3 vs. 0.73 ± 0.01.10−3 mm2/sec; and IVIM‐f: 0.317 ± 0.008 vs. 0.253 ± 0.009). Significantly higher ADC, IVIM‐D, and IVIM‐f values were observed in the CI group after 12 months (ADC: 1.45 ± 0.05.10−3 vs. 1.50 ± 0.07.10−3 mm2/sec; IVIM‐D: 0.87 ± 0.01.10−3 vs. 0.94 ± 0.02.10−3 mm2/sec; and IVIM‐f: 0.303 ± 0.007 vs. 0.332 ± 0.008), but not in the HC group at large effect size. ADC, IVIM‐D, and IVIM‐f negatively correlated with ΔMoCA score (ρ = −0.49, −0.51, and −0.50, respectively).

Data Conclusion

These findings demonstrate that longitudinal differences between CI and HC cohorts can be measured using IVIM‐based metrics.

Level of Evidence

2

Technical Efficacy Stage

2
Increased accuracy and precision of hydrometric soil texture measurements (“Pario classic method”) with semi‐empiric correction functions#
Authors: Mátra Zoltán Soma , Heil Bálint , Kovács Gábor , Lang Friederike , Schack‐Kirchner Helmer
Published: March 2022

Background

Though soil texture is one of the most basic soil characteristics its quantification needs still laborious procedures. A commercially available, efficient approach has been introduced as Pario classic method where silt and clay fractions are calculated by inverse fitting of transducer‐measured suspension pressure curves to modeled Stokes’ law of sedimentation. However, comparison of Pario‐measured textures of 64 samples with Köhn method revealed unsatisfactory bias and random error of fractions except for medium silt.

Aims

The goal of our study was to improve precision and accuracy of Pario classic measurements by multiple linear regression models using regressors that were anyway available in the measurement procedure.

Methods

For the model we included two groups of regressors: (1) Pario‐estimated clay, fine, medium, and coarse silt fractions to cover measurement data and dependencies between fractions; (2) parameters assessed during sample preparation including residual moisture of the air‐dried sample (ϴres), soil‐organic carbon (SOC), and pH‐value. The choice of regressors has been optimized according to the Aikaike Information Criterion (AIC).

Results

The final models yielded unbiased estimations and strongly reduced root‐mean square errors below 5 mass‐%. In case of clay and coarse silt, the intrinsic Pario estimated clay and coarse silt contributed strongest to the prediction, but all fractions of the Pario method have been included in the models. The most important external regressor was the residual moisture. It contributed positively to the clay model and negatively to the silt models as expected because it is a known proxy of clay content.

Conclusions

The suggested semi‐empirical correction allows to benefit from the efficient Pario classic method without loss of data quality. We suggest considering ϴres as a standard parameter in soil analysis to improve the quality of texture estimations.
Comparative nutritional and antimicrobial analysis of Himalayan black and yellow soybean and their okara
Authors: Anjum Sofiya , Rana Smita , Dasila Khashti , Agnihotri Vasudha , Pandey Anita , Pande Veena
Published: March 2022

BACKGROUND

Soybean is believed to have good nutraceutical potential which is important for human health. Yellow soybean (YS) is generally used for the production of soymilk and other products, while black soybean (BS) is less explored. During the production of soymilk, residue, called okara is generated which is reported to have a good amount of nutrient content. Studies are generally performed with YS while BS is less explored. The present work is a comparison of the nutraceutical potential of BS and YS and their okara, mainly in terms of proximate, minerals, antinutrients, and isoflavone content and bioactivity of all types of samples in terms of antioxidant and antimicrobial activity.

RESULTS

Compared to raw soybean, protein content decreased significantly in both types of okara. Phytochemicals like ascorbic acid, catechin, quercetin, and gallic acid were significantly (P < 0.05) high in BS residue in comparison to respective raw soybean. Among isoflavones, daidzin and genistin were found significantly varying among all the samples, and glycitin and glycitein were not present in YS.

CONCLUSION

The nutraceutical potential and antimicrobial activity were comparative for both the raw beans and their okara, while the phytochemical contents and antioxidant activity were higher in the case of BS and its okara. © 2022 Society of Chemical Industry.
Investigating readmission rates for patients undergoing oncologic resection and endoprosthetic reconstruction for primary sarcomas and tumors involving bone
Authors: Lazarides Alexander L. , Flamant Etienne M. , Cullen Mark M. , Ferlauto Harrison R. , Cochrane Niall , Gao Junheng , Jung Sin‐Ho , Visgauss Julia D. , Brigman Brian E. , Eward William C.
Published: March 2022

Background

Little is known about the drivers of readmission in patients undergoing Orthopaedic oncologic resection. The goal of this study was to identify factors independently associated with 90‐day readmission for patients undergoing oncologic resection and subsequent prosthetic reconstruction for primary tumors involving bone.

Methods

This was a retrospective comparative cohort study of patients treated from 2008 to 2019 who underwent endoprosthetic reconstruction for a primary bone tumor or soft tissue tumor involving bone, as well as those who underwent a revision endoprosthetic reconstruction if the primary endoprosthetic reconstruction was performed for an oncologic resection. The primary outcome measure was unplanned 90‐day readmission.

Results

A total of 149 patients were identified who underwent 191 surgeries were for a primary bone or soft tissue tumor. The 90‐day readmission rate was 28.3%. Female gender, depression, higher tumor grade, vascular reconstruction, longer procedure duration, longer length of stay (LOS), multiple surgeries during an admission and disposition to a Skilled Nursing Facility were associated with readmission (p < 0.05). In a multivariate analysis, female sex, higher tumor grade and longer procedure duration were independently associated with risk of readmission (p < 0.05).

Conclusions

Readmission rates are high following endoprosthetic reconstruction for Orthopaedic oncologic resections. Further work is necessary to help minimize unplanned readmissions.
Photo‐mediated ultrasound therapy for the treatment of retinal neovascularization in rabbit eyes
Authors: Qin Yu , Yu Yixin , Fu Julia , Wang Mingyang , Yang Xinmai , Wang Xueding , Paulus Yannis M.
Published: March 2022

Objectives

Retinal neovascularization (RNV) is the growth of abnormal microvessels on the retinal surface and into the vitreous, which can lead to severe vision loss. By combining relatively low‐intensity ultrasound and nanosecond‐pulse‐duration laser, we developed a novel treatment method, namely photo‐mediated ultrasound therapy (PUT), which holds a potential to remove RNV with minimal or no damage to the adjacent tissues.

Methods

RNV was created in both albino and pigmented rabbits (n = 10) through a single intravitreal injection with DL‐α‐aminoadipic acid. RNV was treated with PUT 8 weeks postinjection. After PUT treatment, animals were evaluated longitudinally for up to 6 weeks. Treatment outcomes were evaluated through fundus photography, red‐free fundus photography, fluorescein angiography (FA), and histopathology.

Results

In both albino and pigmented rabbits, there were no leakage in the treatment area immediately after PUT treatment as demonstrated by FA, indicating the cessation of blood perfusion of the RNV in the treated area. The fluorescence leakage did not recover in albino rabbits during the 6‐week posttreatment monitoring period, and only 9.9 ± 9.8% of the neovascularization remained at the end of 6 weeks. In the pigmented rabbits, the fluorescence leakage partially returned, but the level of leakage decreased over time during the 6‐week posttreatment monitoring period, and only 10.8 ± 9.8% of the neovascularization remained at the end of 6 weeks. Histology demonstrated removal of vasculature without damage to the surrounding neurosensory retina.

Conclusions

These results demonstrate that PUT could precisely remove RNV without damage to the surrounding neurosensory retina in both rabbit strains.
Transglutaminase 2 enhances hepatocyte growth factor signaling to drive the mesothelioma cancer cell phenotype
Authors: Naselsky Warren , Adhikary Gautam , Shrestha Suruchi , Chen Xi , Ezeka Geraldine , Xu Wen , Friedberg Joseph S , Eckert Richard L.
Published: March 2022

Transglutaminase 2 (TG2) is an important mesothelioma cancer cell survival protein. However, the mechanism whereby TG2 maintains mesothelioma cell survival is not well understood. We present studies showing that TG2 drives hepatocyte growth factor (HGF)‐dependent MET receptor signaling to maintain the aggressive mesothelioma cancer phenotype. TG2 increases HGF and MET messenger RNA and protein levels to enhance MET signaling. TG2 inactivation reduces MET tyrosine kinase activity to reduce cancer cell spheroid formation, invasion and migration. We also confirm that HGF/MET signaling is a biologically important mediator of TG2 action. Reducing MET level using genetic methods or treatment with MET inhibitors reduces spheroid formation, invasion and migration and this is associated with reduced MEK1/2 and ERK1/2. In addition, MEK1/2 and ERK1/2 inhibitors suppress the cancer phenotype. Moreover, MET knockout mesothelioma cells form 10‐fold smaller tumors compared to wild‐type cells and these tumors display reduced MET, MEK1/2, and ERK1/2 activity. These findings suggest that TG2 maintains HGF and MET levels in cultured mesothelioma cells and tumors to drive HGF/MET, MEK1/2, and ERK1/2 signaling to maintain the aggressive mesothelioma cancer phenotype.
The pancreatic cancer immune tumor microenvironment is negatively remodeled by gemcitabine while TGF‐β receptor plus dual checkpoint inhibition maintains antitumor immune cells
Authors: Rana Manjul , Kansal Rita , Chaib Mehdi , Teng Bin , Morrrison Michelle , Hayes David Neil , Stanfill Ansley G. , Shibata David , Carson James A. , Makowski Liza , Glazer Evan S.
Published: March 2022

Pancreatic ductal adenocarcinoma (PDA) tumors have a highly immunosuppressive desmoplastic tumor microenvironment (TME) where immune checkpoint inhibition (ICI) therapy has been exceptionally ineffective. Transforming growth factor‐β (TGF‐β) receptor activation leads to cancer and immune cell proliferation and phenotype, and cytokine production leading to tumor progression and worse overall survival in PDA patients. We hypothesized that TGF‐β receptor inhibition may alter PDA progression and antitumor immunity in the TME. Here, we used a syngeneic preclinical murine model of PDA to explore the impact of TGF‐β pathway inhibitor galunisertib (GAL), dual checkpoint immunotherapy (anti‐PD‐L1 and CTLA‐4), the chemotherapy gemcitabine (GEM), and their combinations on antitumor immune responses. Blockade of TGF‐β and ICI in immune‐competent mice bearing orthotopically injected murine PDA cells significantly inhibited tumor growth and was accompanied by antitumor M1 macrophage infiltration. In contrast, GEM treatment resulted in increased PDA tumor growth, decreased antitumor M1 macrophages, and decreased cytotoxic CD8+ T cell subpopulation compared to control mice. Together, these findings demonstrate the ability of TGF‐β inhibition with GAL to prime antitumor immunity in the TME and the curative potential of combining GAL with dual ICI. These preclinical results indicate that targeted inhibition of TGF‐β may enhance the efficacy of dual immunotherapy in PDA. Optimal manipulation of the immune TME with non‐ICI therapy may enhance therapeutic efficacy.
STAT3 pathway in cancers: Past, present, and future
Authors: Wang Han‐Qi , Man Qi‐Wen , Huo Fang‐Yi , Gao Xin , Lin Hao , Li Su‐Ran , Wang Jing , Su Fu‐Chuan , Cai, Lulu , Shi Yi , Liu, Bing , Bu Lin‐Lin
Published: March 2022

Signal transducer and activator of transcription 3 (STAT3), a member of the STAT family, discovered in the cytoplasm of almost all types of mammalian cells, plays a significant role in biological functions. The duration of STAT3 activation in normal tissues is a transient event and is strictly regulated. However, in cancer tissues, STAT3 is activated in an aberrant manner and is induced by certain cytokines. The continuous activation of STAT3 regulates the expression of downstream proteins associated with the formation, progression, and metastasis of cancers. Thus, elucidating the mechanisms of STAT3 regulation and designing inhibitors targeting the STAT3 pathway are considered promising strategies for cancer treatment. This review aims to introduce the history, research advances, and prospects concerning the STAT3 pathway in cancer. We review the mechanisms of STAT3 pathway regulation and the consequent cancer hallmarks associated with tumor biology that are induced by the STAT3 pathway. Moreover, we summarize the emerging development of inhibitors that target the STAT3 pathway and novel drug delivery systems for delivering these inhibitors. The barriers against targeting the STAT3 pathway, the focus of future research on promising targets in the STAT3 pathway, and our perspective on the overall utility of STAT3 pathway inhibitors in cancer treatment are also discussed.
A Longitudinal Study of Plasma pTau181 in Mild Cognitive Impairment with Lewy Bodies and Alzheimer's Disease
Authors: Thomas Alan J. , Hamilton Calum A. , Heslegrave Amanda , Barker Sally , Durcan Rory , Lawley Sarah , Barnett Nicola , Lett Debbie , Firbank Michael , Roberts Gemma , Taylor John‐Paul , Donaghy Paul C. , Zetterberg Henrik , O'Brien John
Published: March 2022

Background

Alzheimer's disease (AD) co‐pathology is common in dementia with Lewy bodies and is associated with increased decline. Plasma pTau181 is a blood‐based biomarker that can detect AD co‐pathology.

Objectives

We investigated whether pTau181 was associated with cognitive decline in mild cognitive impairment with Lewy bodies (MCI‐LB) and MCI with AD (MCI‐AD).

Methods

We assessed plasma pTau181 using a single‐molecule array (Simoa) immunoassay at baseline and follow‐up in a longitudinal cohort of MCI‐LB, MCI‐AD, and controls.

Results

One hundred forty‐six subjects (56 probable MCI‐LB, 22 possible MCI‐LB, 44 MCI‐AD, and 24 controls) were reviewed for up to 5.7 years. Probable MCI‐LB had significantly higher pTau181 (22.2% mean increase) compared with controls and significantly lower (24.4% mean decrease) levels compared with MCI‐AD. Receiver operating characteristic analyses of pTau181 in discriminating probable MCI‐LB from controls showed an area under the curve (AUC) of 0.68 (83% specificity, 57% sensitivity); for discriminating MCI‐AD from healthy controls, AUC was 0.8 (83.3% specificity, 72.7% sensitivity). pTau181 concentration was less useful in discriminating between probable MCI‐LB and MCI‐AD: AUC of 0.64 (71.4% specificity, 52.3% sensitivity).

There was an association between pTau181 and cognitive decline in MCI‐AD but not in MCI‐LB. In a subset with repeat samples there was a nonsignificant 3% increase per follow‐up year in plasma pTau181. The rate of change in pTau181 was not significantly different in different diagnostic subgroups.

Conclusions

pTau181 was not associated with an increased decline assessed using either baseline or repeat pTau181. pTau181 partially discriminated probable MCI‐LB from controls and MCI‐AD from controls but was not useful in distinguishing probable MCI‐LB from MCI‐AD. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
A novel fusion between CDC42BPB and ALK in a patient with quadruple wild‐type gastrointestinal stromal tumor
Authors: Huang Wen , Yuan Wei , Ren Lei , Xu Chen , Luo Rongkui , Zhou Yuhong , Lu Weiqi , Hao Qing , Xu Mian , Hou Yingyong
Published: March 2022

Background

Gastrointestinal stromal tumors (GISTs) are the most common type of mesenchymal tumor in gastrointestinal tract, with striking features of morphology and immunohistochemistry. But GISTs in pregnancy could seldom be found. Pathogenic activating mutations of the proto‐oncogene KIT and PDGFRA are detected in majority GISTs, and adjuvant imatinib therapy targeting KIT and PDGFRA mutations is recommended for patients with high‐risk GIST. However, some rare subgroups with distinct molecular features remain uncovered and more therapeutic targets need to be revealed.

Methods

The DNA/RNA samples were detected using the NGS‐based YuanSu450 gene panel. After identifying the CDC42BPB‐ALK fusion by NGS, this novel fusion was further confirmed by Sanger sequencing. Subsequently, FISH analysis was performed using the Vysis ALK Break Apart FISH Probe kit to testify the ALK status. ALK protein expression was confirmed by IHC (D5F3 and 5A4).

Results

Herein, we reported the first case of quadruple wild‐type (WT) GIST with ALK‐CDC42BPB fusion and ALK (D5F3) overexpression. In this study, we described a 33‐year‐old pregnant patient in lactation who had a massive space occupying lesion (with the maximum diameter of 22 cm) in the stomach and was eventually diagnosed as quadruple WT GIST (KITWT/PDGFRAWT/SDHWT/RAS‐PWT).

Conclusion

We unexpectedly found that this GIST patient showed ALK (D5F3) overexpression and harbored a novel fusion CDC42BPB exon 24‐ALK in exon 20.
The linear stability for a free boundary problem modeling multilayer tumor growth with time delay
Authors: He Wenhua , Xing Ruixiang , Hu Bei
Published: March 2022

We study a free boundary problem modeling multilayer tumor growth with a small time delay
, representing the time needed for the cell to complete the replication process. The model consists of two elliptic equations which describe the concentration of nutrient and the tumor tissue pressure, respectively, an ordinary differential equation describing the cell location characterizing the time delay and a partial differential equation for the free boundary. In this paper, we establish the well‐posedness of the problem; namely, first, we prove that there exists a unique flat stationary solution
for all
. The stability of this stationary solution should depend on the tumor aggressiveness constant
. It is also unrealistic to expect the perturbation to be flat. We show that, under non‐flat perturbations, there exists a threshold
such that
is linearly stable if
and linearly unstable if
. Furthermore, the time delay increases the stationary tumor size. These are interesting results with mathematical and biological implications.
The effects of unexpected changes to content delivery on student learning outcomes: A psychological contract perspective during the COVID‐19 era
Authors: Gazica Michele W. , Leto Grace D. , Irish Andrea L.
Published: March 2022

Meta‐analyses suggest that student learning outcomes (SLOs) are comparable across modalities of instruction. None of these studies examined how unmet student expectations (here, unexpected changes in course delivery) might increase perceptions of student–instructor‐university psychological contract breaches (PCBs) and, ultimately, perceived SLOs within and across modalities. The COVID‐19 pandemic provided an opportunity to study these potential relationships because many residential institutions of higher education opted into, or were required to, offer distance and/or blended learning to accommodate COVID‐19 safety mandates. This study sampled undergraduate students (n = 155) from a university, which, before the pandemic, offered exclusively face‐to‐face classroom instruction. During the Fall 2020 semester, however, this university offered three modalities of instruction: (1) face‐to‐face; (2) blended learning; and (3) distance education. The results of this study suggest that perceived PCBs by instructors and universities negatively influence underling indices of student achievement in terms of motivation, engagement, and learning within and across modalities of instruction. Given this and near universal decrements in student enrollment and retention in institutions of higher education, it is important for universities and instructors to understand, explicitly and transparently negotiate, and meet student expectations to improve student progression to graduation and maintain competitiveness among similar institutions.
Social media and politics on the local level
Authors: Datts Mario , Schultze Martin
Published: March 2022

The local level is highly important for political engagement, as political issues that are relevant to citizens' daily lives are discussed at this level. Therefore, political parties are especially interested in organizing a strong local basis. Yet, empirical research on the local party units is rather scarce, particularly with respect to their social media activities. We do not know whether the local units of political parties are nowadays active players in the most important communication sphere, and nor do we know anything about potential driving forces of their activities on social media. Using big data, we are able to demonstrate that local party units in Germany are especially active on Facebook during a heated election campaign. Interestingly, we also confirm this observation with regard to user activities. Furthermore, our results reveal that the local basis of the German right‐wing populist party Alternative for Germany has an insurmountable lead on Facebook—in terms of both published posts and user response. This finding supports the thesis that a right‐wing ecosystem on Facebook has been established in Germany. Besides election and party effects, we find that urbanized areas provide better opportunities for the social media usage of political parties and citizens.
Caffeine and bronchopulmonary dysplasia: Clinical benefits and the mechanisms involved
Authors: Yuan Yuan , Yang Yang , Lei Xiaoping , Dong Wenbin
Published: March 2022

Bronchopulmonary dysplasia (BPD) is a chronic respiratory disease that occurs during the neonatal period and is commonly associated with prematurity. This condition results in a severe economic burden on society and the families involved. Caffeine is used not only for the treatment of apnea in prematurity, but also for the prevention of BPD. There are multiple clinical benefits of caffeine treatment, including improved extubation success, a reduced duration of mechanical ventilation, improved lung function, and a reduction of patent ductus arteriosus requiring treatment. These clinical benefits of caffeine for the treatment of BPD are supported by both clinical trials and evidence from animal models. However, the mechanism by which caffeine protects against BPD remains unclear. Here, we review the clinical value of caffeine in the prevention of BPD and its potential mechanisms of action, including anti‐inflammatory, antioxidant, antifibrotic, and antiapoptotic properties, the regulation of angiogenesis, and diuretic effects. Our aim is to provide a new theoretical basis for the clinical treatment of BPD.
Using tank‐mix adjuvant improves the physicochemical properties and dosage delivery to reduce the use of pesticides in unmanned aerial vehicles for plant protection in wheat
Authors: Zhao Rui , Yu Meng , Sun Zhe , Li Lin‐jie , Shang Hong‐Yi , Xi Wan‐jiang , Li Biao , Li Yang‐yang , Xu Yong , Wu Xue‐Min
Published: March 2022

BACKGROUND

Unmanned aerial vehicles (UAVs) are widely used to improve the efficiency of pesticide applications. Low‐volume spraying operations require more efficient deposition of droplets on the target surface. Therefore, pesticide deposition and retention on plant surfaces is a serious challenge for modern precision agriculture. Tank‐mix adjuvants have been used to improve spray dilutions performance; however, their effects on the physicochemical properties of spray dilutions, dosage delivery, and pesticide dosage are unclear.

RESULTS

Tank‐mix adjuvant 8860 significantly improved the physicochemical properties of spray dilutions, inhibited spray droplets rebound, improved the wetting and spreading performance of spray dilutions on wheat leaves, and increased the effective deposition of tebuconazole on wheat leaves. Even when its dosage was reduced by one‐third, the spray solution still showed excellent disease control and effective deposition of the active ingredient on wheat leaves.

CONCLUSION

The use of appropriate tank‐mix adjuvants in UAV‐based plant protection for wheat can significantly improve the performance of spray dilutions, increase the efficiency of pesticide dosage delivery, and improve disease control. These adjuvants can also help reduce the pesticide use while ensuring their effectiveness. © 2022 Society of Chemical Industry.
Switchable Phase Transition from Crystalline to Amorphous States of Cadmium Sulfate Octahydrate Single Crystals by Shock Waves
Authors: Sivakumar Aswathappa , Dhas Sathiyadhas Sahaya Jude , Showrilu Kondaveeti , Sivaprakash Paramasiva , Kumar Raju Suresh , Almansour Abdulrahman I. , Chakraborty Shubhadip , Arumugam Sonachalam , Dhas Sathiyadhas Amalapushpam Martin Britto
Published: March 2022

Even slight changes occurring in the lattice positions of solid materials enforced by the external forces may give rise to remarkable results in the crystallographic nature. The materials which undergo phase‐change without modifying their overall chemistry are the prominent candidates to be the driving forces for the applications involving phase transitions. In the present context, the authors present and demonstrate the switchable phase transition occurring between crystalline and amorphous nature of cadmium sulfate octahydrate single crystals (3CdSO4·8H2O) impacted by shock waves with which the transition is authenticated via diffraction, vibrational and optical spectroscopic techniques such as powder X‐ray diffractometry, Raman and UV‐Vis spectral analyses. Based on the results attained from diffraction and spectroscopic analyses, it is observed that the switchable phase transition sequence is crystalline–crystalline–amorphous–crystalline–crystalline with respect to the control, one, two, three, and four shock‐wave‐loaded conditions, respectively. Due to the outstanding switching behavior, the title material is strongly suggested for the applications of molecular switching and optical data storage systems.
Noniterative tensor network‐based algorithm for Volterra system identification
Authors: Hu Yangsheng , Tan Li , de Callafon Raymond A.
Published: March 2022

Volterra model serves as one of the powerful alternatives to approximate nonlinear dynamics on the basis of input/output observations. The kernel representation of a Volterra model is attractive since it is linear in the kernel coefficients and always stable. Although the kernel representation suffers from the curse of dimensionality, the demand for storage requirements can be relieved via a tensor network (TN) technique. This allows one to approximate complicated coupled nonlinear dynamics with high degree and even multi‐input multi‐output (MIMO) Volterra models. The iterative feature of existing TN‐based algorithms poses challenges for the algorithms to converge to an appropriate solution with both good prediction accuracy and minor overfitting problems. In this article, noniterative TN‐based algorithms with two tuning factors to solve either a linear or ridge regression are proposed for MIMO Volterra system identification. The proposed algorithms do not suffer convergence problems due to its noniterative feature and perform active low‐rank approximations to reduce overfitting problems. Simulations compare different algorithms and investigate the effects for different excitation signals.
Electrochemical Strategy for High‐Resolution Nanostructures in Laser‐Heat‐Mode Resist Toward Next Generation Diffractive Optical Elements
Authors: Wang Zhengwei , Chen Guodong , Wen Ming , Hu Xutao , Liu Xing , Wei Jingsong , Wu Qingsheng , Fu YongQing
Published: March 2022

For achieving high‐resolution nanostructures for next‐generation diffractive optical elements (DOEs) using an environmentally friendly process, an electrochemical development strategy is proposed and developed using AgInSbTe‐based laser heat‐mode resist (AIST‐LHR). Based on the electrical resistivity difference of amorphous and crystalline phases for this resist, an etching selectivity ratio of ≈30:1 (i.e., the etch ratio between the amorphous and crystalline ones) is achieved through the oxidation of Fe3+ ions with the assisted pitting activation etching using Cl− ions in an acid medium. Nanostructures with a minimum feature size down to 41 nm are successfully generated, including grating patterns, meta‐surface optical structures, gears, and English characters. Using a post‐plasma etching process, the nanostructures are successfully transferred from the AIST‐HLR onto silica substrate, and X‐ray grating patterns with a line space of 80 nm are created as a demonstration for its potential applications in DOEs.
Fundamental Understanding and Construction of Solid‐State Li−Air Batteries
Authors: Wang Huan-Feng , Wang Xiao-Xue , Li Fei , Xu Ji-Jing
Published: March 2022

Nonaqueous Li−air batteries with ultrahigh theoretical energy density have attracted much attention in the development of clean energy technology. However, a series of safety challenges including the flammable, volatile organic liquid electrolyte, together with the electrolyte decomposition have greatly hindered their practical development. Solid‐state electrolytes with superior mechanical strength, good chemical stability under open‐air system, wide electrochemical window, nonflammable properties provide a feasible strategy to overcome the safety issues and achieve a stable, applicable Li−air battery system. In this article, a comprehensive review of solid‐state Li−air batteries is provided. Based on the overall understanding of the necessity of developing a solid‐state Li−air battery and ion migration mechanism in solid electrolytes, the construction strategies of solid‐state Li−air battery including cathode fabrication, Li anode optimization, electrolyte design, and the interface regulation between electrodes and electrolyte are presented. The prospects of solid‐state Li−air batteries are also proposed at the end. It is expected that this review would provide a systematic understanding and theoretical guidance in designing and developing safe, stable, applicable solid‐state Li−air batteries.
Critical roles of the activation of ethylene pathway genes mediated by DNA demethylation in Arabidopsis hyperhydricity
Authors: Gao Hongyang , Xia Xiuying , An Lijia
Published: March 2022

Hyperhydricity (HH) often occurs in plant tissue culture, seriously influencing the commercial micropropagation and genetic improvement. DNA methylation has been studied for its function in plant development and stress responses. However, its potential role in HH is unknown. In this study, we report the first comparative DNA methylome analysis of normal and hyperhydric Arabidopsis thaliana (L.) Heynh. seedlings using whole‐genome bisulfite sequencing (BS‐seq). We found that the global methylation level decreased in hyperhydric seedlings, and most of the differentially methylated genes were CHH hypomethylated genes. Moreover, the bisulfite sequencing results showed that hyperhydric seedlings displayed CHH demethylation patterns in the promoter of the ACS1 and ETR1 genes, resulting in upregulated expression of both genes and increased ethylene accumulation. Furthermore, hyperhydric seedling displayed reduced stomatal aperture accompanied by decreased water loss and increased phosphorylation of aquaporins accompanied by increased water uptake. While silver nitrate (AgNO3) prevented HH by maintained the degree of methylation in the promoter regions of ACS1 and ETR1 and downregulated the transcription of both genes. AgNO3 also reduced the content of ethylene together with the phosphorylation of aquaporins and water uptake. Taken together, this study suggested that DNA demethylation is a key switch that activates ethylene pathway genes to enable ethylene synthesis and signal transduction, which may subsequently influence aquaporin phosphorylation and stomatal aperture, eventually causing HH; thus, DNA demethylation plays a crucial role in HH. These results provide insights into the epigenetic regulation mechanism of HH and confirm the role of ethylene and AgNO3 in hyperhydricity control.
Bioinspired soft nanovesicles for site‐selective cancer imaging and targeted therapies
Authors: Prasad Rajendra , Conde João
Published: March 2022

Cell‐to‐cell communication within the heterogeneous solid tumor environment plays a significant role in the uncontrolled metastasis of cancer. To inhibit the metastasis and growth of cancer cells, various chemically designed and biologically derived nanosized biomaterials have been applied for targeted cancer therapeutics applications. Over the years, bioinspired soft nanovesicles have gained tremendous attention for targeted cancer therapeutics due to their easy binding with tumor microenvironment, natural targeting ability, bio‐responsive nature, better biocompatibility, high cargo capacity for multiple therapeutics agents, and long circulation time. These cell‐derived nanovesicles guard their loaded cargo molecules from immune clearance and make them site‐selective to cancer cells due to their natural binding and delivery abilities. Furthermore, bioinspired soft nanovesicles prevent cell‐to‐cell communication and secretion of cancer cell markers by delivering the therapeutics agents predominantly. Cell‐derived vesicles, namely, exosomes, extracellular vesicles, and so forth have been recognized as versatile carriers for therapeutic biomolecules. However, low product yield, poor reproducibility, and uncontrolled particle size distribution have remained as major challenges of these soft nanovesicles. Furthermore, the surface biomarkers and molecular contents of these vesicles change with respect to the stage of disease and types. Here in this review, we have discussed numerous examples of bioinspired soft vesicles for targeted imaging and cancer therapeutic applications with their advantages and limitations. Importance of bioengineered soft nanovesicles for localized therapies with their clinical relevance has also been addressed in this article. Overall, cell‐derived nanovesicles could be considered as clinically relevant platforms for cancer therapeutics.

This article is categorized under:

Biology‐Inspired Nanomaterials > Nucleic Acid‐Based Structures

Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease
Rethinking the Input for Process Mining: Insights from the XES Survey and Workshop
Authors: Wynn Moe Thandar , Lebherz Julian , van der Aalst Wil M. P. , Accorsi Rafael , Di Ciccio Claudio , Jayarathna Lakmali , Verbeek H. M. W.
Published: March 2022

Although the popularity and adoption of process mining techniques grew rapidly in recent years, a large portion of effort invested in process mining initiatives is still consumed by event data extraction and transformation rather than process analysis. The IEEE Task Force on Process Mining conducted a study focused on the challenges faced during event data preparation (from source data to event log). This paper presents findings from the online survey with 289 participants spanning the roles of practitioners, researchers, software vendors, and end-users. These findings were presented at the XES 2.0 workshop co-located with the 3rd International Conference on Process Mining. The workshop also hosted presentations from various stakeholder groups and a discussion panel on the future of XES and the input needed for process mining. This paper summarises the main findings of both the survey and the workshop. These outcomes help us to accelerate and improve the standardisation process, hopefully leading to a new standard widely adopted by both academia and industry.
Can Deep Neural Networks Learn Process Model Structure? An Assessment Framework and Analysis
Authors: Peeperkorn Jari , vanden Broucke Seppe , De Weerdt Jochen
Published: March 2022

Predictive process monitoring concerns itself with the prediction of ongoing cases in (business) processes. Prediction tasks typically focus on remaining time, outcome, next event or full case suffix prediction. Various methods using machine and deep learning have been proposed for these tasks in recent years. Especially recurrent neural networks (RNNs) such as long short-term memory nets (LSTMs) have gained in popularity. However, no research focuses on whether such neural network-based models can truly learn the structure of underlying process models. For instance, can such neural networks effectively learn parallel behaviour or loops? Therefore, in this work, we propose an evaluation scheme complemented with new fitness, precision, and generalisation metrics, specifically tailored towards measuring the capacity of deep learning models to learn process model structure. We apply this framework to several process models with simple control-flow behaviour, on the task of next-event prediction. Our results show that, even for such simplistic models, careful tuning of overfitting countermeasures is required to allow these models to learn process model structure.
Remaining Time Prediction for Processes with Inter-case Dynamics
Authors: Pourbafrani Mahsa , Kar Shreya , Kaiser Sebastian , van der Aalst Wil M. P.
Published: March 2022

Process mining techniques use event data to describe business processes, where the provided insights are used for predicting processes’ future states (Predictive Process Monitoring). Remaining Time Prediction of process instances is an important task in the field of Predictive Process Monitoring (PPM). Existing approaches have two key limitations in developing Remaining Time Prediction Models (RTM): (1) The features used for predictions lack process context, and the created models are black-boxes. (2) The process instances are considered to be in isolation, despite the fact that process states, e.g., the number of running instances, influence the remaining time of a single process instance. Recent approaches improve the quality of RTMs by utilizing process context related to batching-at-end inter-case dynamics in the process, e.g., using the time to batching as a feature. We propose an approach that decreases the previous approaches’ reliance on user knowledge for discovering fine-grained process behavior. Furthermore, we enrich our RTMs with the extracted features for multiple performance patterns (caused by inter-case dynamics), which increases the interpretability of models. We assess our proposed remaining time prediction method using two real-world event logs. Incorporating the created inter-case features into RTMs results in more accurate and interpretable predictions.
Active Anomaly Detection for Key Item Selection in Process Auditing
Authors: Post Ruben , Beerepoot Iris , Lu Xixi , Kas Stijn , Wiewel Sebastiaan , Koopman Angelique , Reijers Hajo
Published: March 2022

Process mining allows auditors to retrieve crucial information about transactions by analysing the process data of a client. We propose an approach that supports the identification of unusual or unexpected transactions, also referred to as exceptions. These exceptions can be selected by auditors as “key items”, meaning the auditors wants to look further into the underlying documentation of the transaction. The approach encodes the traces, assigns an anomaly score to each trace, and uses the domain knowledge of auditors to update the assigned anomaly scores through active anomaly detection. The approach is evaluated with three groups of auditors over three cycles. The results of the evaluation indicate that the approach has the potential to support the decision-making process of auditors. Although auditors still need to make a manual selection of key items, they are able to better substantiate this selection. As such, our research can be seen as a step forward with respect to the usage of anomaly detection and data analysis in process auditing.
An Event Data Extraction Approach from SAP ERP for Process Mining
Authors: Berti Alessandro , Park Gyunam , Rafiei Majid , van der Aalst Wil M. P.
Published: March 2022

The extraction, transformation, and loading of event logs from information systems is the first and the most expensive step in process mining. In particular, extracting event logs from popular ERP systems such as SAP poses major challenges, given the size and the structure of the data. Open-source support for ETL is scarce, while commercial process mining vendors maintain connectors to ERP systems supporting ETL of a limited number of business processes in an ad-hoc manner. In this paper, we propose an approach to facilitate event data extraction from SAP ERP systems. In the proposed approach, we store event data in the format of object-centric event logs that efficiently describe executions of business processes supported by ERP systems. To evaluate the feasibility of the proposed approach, we have developed a tool implementing it and conducted case studies with a real-life SAP ERP system.
Verifying Guideline Compliance in Clinical Treatment Using Multi-perspective Conformance Checking: A Case Study
Authors: Grüger Joscha , Geyer Tobias , Kuhn Martin , Braun StephanA. , Bergmann Ralph
Published: March 2022

Clinical guidelines support physicians in the evidence-based treatment of patients. The technical verification of guideline compliance is not trivial, since guideline knowledge is usually represented textually and none of the approaches to computer-interpretable guideline representation has yet been able to establish itself. Due to the procedural nature of treatment sequences, this case study examines the applicability of a guideline process model to real hospital data for verification of guideline compliance. For this purpose, the limitations and challenges in the transformation of clinical data into an event log and in the application of conformance checking to align the data with the guideline reference model are investigated. As a data set, we use treatment data of skin tumor patients from a cancer registry enriched by hospital information system data. The results show the difficulty of applying process mining to medically complex and heterogeneous data and the need for complex preprocessing. The variability of clinical processes makes the application of global conformance checking algorithms challenging. In addition, the work shows the semantic weakness of the alignments and the need for new semantically sensitive approaches.
Root Cause Analysis in Process Mining with Probabilistic Temporal Logic
Authors: Van Houdt Greg , Depaire Benoît , Martin Niels
Published: March 2022

Process mining is a research domain that enables businesses to analyse and improve their processes by extracting insights from event logs. While determining the root causes of, for example, a negative case outcome can provide valuable insights for business users, only limited research has been conducted to uncover true causal relations within the process mining field. Therefore, this paper proposes AITIA-PM, a novel technique to measure cause-effect relations in event logs based on causality theory. The AITIA-PM algorithm employs probabilistic temporal logic to formally yet flexibly define hypotheses and then automatically tests them for causal relations from data. We demonstrate this by applying AITIA-PM on a real-life dataset. The case study shows that, after a well-thought-out hypotheses definition and information extraction, the AITIA-PM algorithm can be applied on rich event logs, expanding the possibilities of meaningful root cause analysis in a process mining context.
Articulations of Ethics: Energy Worlds and Moral Selves
Authors: High Mette M.
Published: March 2022

This chapter introduces the notion of ‘regimes of ethics’ to explore the diverse ways that ethics is articulated in corporate capitalism, particularly in industries that are involved in the extraction of natural resources such as oil and gas. I show how companies draw on corporate social responsibility frameworks as public-facing demonstrations of ethics for stakeholder engagement, while also generating greater company loyalty and pride among employees. While corporate social responsibility (CSR) provides an explicit corporate strategy, the professional codes of ethics that apply to engineering practices in the USA specifically anchor ethics in individual decision-making. Animated by a generally conservative, if not stultifying, ethos, engineering ethics sees practices such as whistleblowing and breaking ranks as epitomising individual ethical action. Co-existing with and sometimes challenging these two formal regimes of ethics are also industry actors’ own moral convictions. This third regime of ethics draws on my ethnographic research in the oil and gas industry in Colorado, USA. By discussing these various articulations of ethics, my aim is to take seriously formal rules and codes as well as industry actors’ own ethical sensibilities. I suggest that rather than existing as entrenched hardened moral worlds, these multiple and competing regimes of ethics indicate the underdetermined nature of ethical life.
Challenging the Transition of Civilization: Theory and Practice of “Energy Democracy”
Authors: Sasaki Hiroshi
Published: March 2022

Today, wind powers and solar powers have become the main stream of energies. Everyone, from major electric power utilities to mega capital investors, has entered the renewable energy sector, increasingly and rapidly expanding the mass capital investment projects in the world. It is not rare to find cases of such mega projects developing confrontations with local communities. Since 1990s, the privatization of energy sector has been significant, with Nordic countries and Germany seeing the advancement of privatizations among community-operated energy utilities. Recently, however, there has been the movement to re-review such trend “to revive public utilities”. The recent reversal of privatization trend means that the conventional way of decision-making participated by local governments and handful corporations is no longer appropriate, and there is a rise of common understanding that the decision-making and governance method of local communities must be open and distributed horizontally. The rapid progress of ICT in recent years has raised awareness of risks in the governance system dominated by private companies, while raising technical capabilities to realize new and open decision-making and governance in local communities.