bluuebunny/crossref_metadata_2025 huggingface dataset:
Treatment Efficacy Analysis in Acute Ischemic Stroke Patients Using In Silico Modeling Based on Machine Learning: A Proof-of-Principle
Authors: Winder Anthony , Wilms Matthias , Fiehler Jens , Forkert Nils D.
Published: September 2021

Interventional neuroradiology is characterized by engineering- and experience-driven device development with design improvements every few months. However, clinical validation of these new devices requires lengthy and expensive randomized controlled trials. This contribution proposes a machine learning-based in silico study design to evaluate new devices more quickly with a small sample size. Acute diffusion- and perfusion-weighted MRI, segmented one-week follow-up imaging, and clinical variables were available for 90 acute ischemic stroke patients. Three treatment option-specific random forest models were trained to predict the one-week follow-up lesion segmentation for (1) patients successfully recanalized using intra-arterial mechanical thrombectomy, (2) patients successfully recanalized using intravenous thrombolysis, and (3) non-recanalizing patients as an analogue for conservative treatment for each patient in the sample, independent of the true group membership. A repeated-measures analysis of the three predicted follow-up lesions for each patient revealed significantly larger lesions for the non-recanalizing group compared to the successful intravenous thrombolysis treatment group, which in turn showed significantly larger lesions compared to the successful mechanical thrombectomy treatment group (p < 0.001). A groupwise comparison of the true follow-up lesions for the three treatment options showed the same trend but did not reach statistical significance (p = 0.19). We conclude that the proposed machine learning-based in silico trial design leads to clinically feasible results and can support new efficacy studies by providing additional power and potential early intermediate results.
Genetics Is of the Essence to Face NAFLD
Authors: Meroni Marica , Longo Miriam , Tria Giada , Dongiovanni Paola
Published: September 2021

Nonalcoholic fatty liver disease (NAFLD) is the commonest cause of chronic liver disease worldwide. It is closely related to obesity, insulin resistance (IR) and dyslipidemia so much so it is considered the hepatic manifestation of the Metabolic Syndrome. The NAFLD spectrum extends from simple steatosis to nonalcoholic steatohepatitis (NASH), a clinical condition which may progress up to fibrosis, cirrhosis and hepatocellular carcinoma (HCC). NAFLD is a complex disease whose pathogenesis is shaped by both environmental and genetic factors. In the last two decades, several heritable modifications in genes influencing hepatic lipid remodeling, and mitochondrial oxidative status have been emerged as predictors of progressive hepatic damage. Among them, the patatin-like phospholipase domain-containing 3 (PNPLA3) p.I148M, the Transmembrane 6 superfamily member 2 (TM6SF2) p.E167K and the rs641738 membrane bound-o-acyltransferase domain-containing 7 (MBOAT7) polymorphisms are considered the most robust modifiers of NAFLD. However, a forefront frontier in the study of NAFLD heritability is to postulate score-based strategy, building polygenic risk scores (PRS), which aggregate the most relevant genetic determinants of NAFLD and biochemical parameters, with the purpose to foresee patients with greater risk of severe NAFLD, guaranteeing the most highly predictive value, the best diagnostic accuracy and the more precise individualized therapy.
Perinatal Acetaminophen Exposure and Childhood Attention-Deficit/Hyperactivity Disorder (ADHD): Exploring the Role of Umbilical Cord Plasma Metabolites in Oxidative Stress Pathways
Authors: Anand Neha S. , Raghavan Ramkripa , Wang Guoying , Hong Xiumei , Azuine Romuladus E. , Pearson Colleen , Zuckerman Barry , Xie Hehuang , Wang Xiaobin
Published: September 2021

Oxidative stress mechanisms may explain associations between perinatal acetaminophen exposure and childhood attention-deficit hyperactivity disorder (ADHD). We investigated whether the changes in umbilical cord plasma amino acids needed to synthesize the antioxidant glutathione and in the oxidative stress biomarker 8-hydroxy-deoxyguanosine may explain the association between cord plasma acetaminophen and ADHD in the Boston Birth Cohort (BBC). Mother–child dyads were followed at the Boston Medical Center between 1998 and 2018. Cord plasma analytes were measured from archived samples collected at birth. Physician diagnoses of childhood ADHD were obtained from medical records. The final sample consisted of 568 participants (child mean age [SD]: 9.3 [3.5] years, 315 (52.8%) male, 248 (43.7%) ADHD, 320 (56.3%) neurotypical development). Cord unmetabolized acetaminophen was positively correlated with methionine (R = 0.33, p < 0.001), serine (R = 0.30, p < 0.001), glycine (R = 0.34, p < 0.001), and glutamate (R = 0.16, p < 0.001). Children with cord acetaminophen levels >50th percentile appeared to have higher risk of ADHD for each increase in cord 8-hydroxy-deoxyguanosine level. Adjusting for covariates, increasing cord methionine, glycine, serine, and 8-hydroxy-deoxyguanosine were associated with significantly higher odds for childhood ADHD. Cord methionine statistically mediated 22.1% (natural indirect effect logOR = 0.167, SE = 0.071, p = 0.019) and glycine mediated 22.0% (natural indirect effect logOR = 0.166, SE = 0.078, p = 0.032) of the association between cord acetaminophen >50th percentile with ADHD. Our findings provide some clues, but additional investigation into oxidative stress pathways and the association of acetaminophen exposure and childhood ADHD is warranted.
DJ4 Targets the Rho-Associated Protein Kinase Pathway and Attenuates Disease Progression in Preclinical Murine Models of Acute Myeloid Leukemia
Authors: Golla Upendarrao , Ehudin Melanie A. , Annageldiyev Charyguly , Zeng Zheng , Bastihalli Tukaramrao Diwakar , Tarren Anna , Date Abhijit A. , Elcheva Irina , Berg Arthur , Amin Shantu , Loughran Thomas P. , Kester Mark , Desai Dhimant , Dovat Sinisa , Claxton David , Sharma Arati
Published: September 2021

The poor prognosis of acute myeloid leukemia (AML) and the highly heterogenous nature of the disease motivates targeted gene therapeutic investigations. Rho-associated protein kinases (ROCKs) are crucial for various actin cytoskeletal changes, which have established malignant consequences in various cancers, yet are still not being successfully utilized clinically towards cancer treatment. This work establishes the therapeutic activity of ROCK inhibitor (5Z)-2–5-(1H-pyrrolo[2,3-b]pyridine-3-ylmethylene)-1,3-thiazol-4(5H)-one (DJ4) in both in vitro and in vivo preclinical models of AML to highlight the potential of this class of inhibitors. Herein, DJ4 induced cytotoxic and proapoptotic effects in a dose-dependent manner in human AML cell lines (IC50: 0.05–1.68 μM) and primary patient cells (IC50: 0.264–13.43 μM); however, normal hematopoietic cells were largely spared. ROCK inhibition by DJ4 disrupts the phosphorylation of downstream targets, myosin light chain (MLC2) and myosin-binding subunit of MLC phosphatase (MYPT), yielding a potent yet selective treatment response at micromolar concentrations, from 0.02 to 1 μM. Murine models injected with luciferase-expressing leukemia cell lines subcutaneously or intravenously and treated with DJ4 exhibited an increase in overall survival and reduction in disease progression relative to the vehicle-treated control mice. Overall, DJ4 is a promising candidate to utilize in future investigations to advance the current AML therapy.
Biologically Targeted Radiation Therapy: Incorporating Patient-Specific Hypoxia Data Derived from Quantitative Magnetic Resonance Imaging
Authors: Her Emily J. , Haworth Annette , Sun Yu , Williams Scott , Reynolds Hayley M. , Kennedy Angel , Ebert Martin A.
Published: September 2021

Purpose: Hypoxia has been linked to radioresistance. Strategies to safely dose escalate dominant intraprostatic lesions have shown promising results, but further dose escalation to overcome the effects of hypoxia require a novel approach to constrain the dose in normal tissue.to safe levels. In this study, we demonstrate a biologically targeted radiotherapy (BiRT) approach that can utilise multiparametric magnetic resonance imaging (mpMRI) to target hypoxia for favourable treatment outcomes. Methods: mpMRI-derived tumour biology maps, developed via a radiogenomics study, were used to generate individualised, hypoxia-targeting prostate IMRT plans using an ultra- hypofractionation schedule. The spatial distribution of mpMRI textural features associated with hypoxia-related genetic profiles was used as a surrogate of tumour hypoxia. The effectiveness of the proposed approach was assessed by quantifying the potential benefit of a general focal boost approach on tumour control probability, and also by comparing the dose to organs at risk (OARs) with hypoxia-guided focal dose escalation (DE) plans generated for five patients. Results: Applying an appropriately guided focal boost can greatly mitigate the impact of hypoxia. Statistically significant reductions in rectal and bladder dose were observed for hypoxia-targeting, biologically optimised plans compared to isoeffective focal DE plans. Conclusion: Results of this study suggest the use of mpMRI for voxel-level targeting of hypoxia, along with biological optimisation, can provide a mechanism for guiding focal DE that is considerably more efficient than application of a general, dose-based optimisation, focal boost.
Transcriptomic Analysis in Multiple Myeloma and Primary Plasma Cell Leukemia with t(11;14) Reveals Different Expression Patterns with Biological Implications in Venetoclax Sensitivity
Authors: Todoerti Katia , Taiana Elisa , Puccio Noemi , Favasuli Vanessa , Lionetti Marta , Silvestris Ilaria , Gentile Massimo , Musto Pellegrino , Morabito Fortunato , Gianelli Umberto , Bolli Niccolò , Baldini Luca , Neri Antonino , Ronchetti Domenica
Published: September 2021

Mechanisms underlying the pathophysiology of primary Plasma Cell Leukemia (pPCL) and intramedullary multiple myeloma (MM) need to be further elucidated, being potentially relevant for improving therapeutic approaches. In such a context, the MM and pPCL subgroups characterized by t(11;14) deserve a focused investigation, as the presence of the translocation is mainly associated with sensitivity to venetoclax. Herein, we investigated a proprietary cohort of MM and pPCL patients, focusing on the transcriptional signature of samples carrying t(11;14), whose incidence increases in pPCL in association with an unfavorable outcome. In addition, we evaluated the expression levels of the BCL2-gene family members and of a panel of B-cell genes recently reported to be associated with sensitivity to venetoclax in MM. Moreover, transcriptional analysis of lncRNAs in the two clinical settings led to the identification of several differentially expressed transcripts, among which the SNGH6 deregulated lncRNA might be relevant in the pathogenesis and prognosis of pPCL with t(11;14). Overall, our data suggest that MMs and pPCLs with t(11;14) might be responsive to venetoclax based on different molecular programs, prompting further studies to elucidate better novel potential predictive biomarkers.
The Impact of Different Timing Schedules on Prostate HDR-Mono-Brachytherapy. A TCP Modeling Investigation
Authors: Stavrev Pavel , Stavreva Nadejda , Genova Boriana , Ruggieri Ruggero , Alongi Filippo , Nahum Alan E. , Pressyanov Dobromir
Published: September 2021

Background: Mechanistic TCP (tumor control probability) models exist that account for possible re-sensitization of an initially hypoxic tumor during treatment. This phenomenon potentially explains the better outcome of a 28-day vs 14-day treatment schedule of HDR (high dose rate) brachytherapy of low- to intermediate-risk prostate cancer as recently reported. Methods: A TCP model accounting for tumor re-sensitization developed earlier is used to analyze the reported clinical data. In order to analyze clinical data using individual TCP model, TCP distributions are constructed assuming inter-individual spread in radio-sensitivity. Results: Population radio-sensitivity parameter values are found that result in TCP population values which are close to the reported ones. Using the estimated population parameters, two hypothetical regimens are investigated that are shorter than the ones used clinically. The impact of the re-sensitization rate on the calculated treatment outcome is also investigated as is the anti-hypothesis that there is no re-sensitization during treatment. Conclusions: The carried out investigation shows that the observed clinical data cannot be described without assuming an initially hypoxic state of the tumor followed by re-oxygenation and, hence, re-sensitization. This phenomenon explains the better outcome of the prolonged treatment schedule compared to shorter regimens based on the fact that prostate cancer is a slowly repopulating tumor.
Comparing the Effect of Multiple Histone Deacetylase Inhibitors on SSTR2 Expression and [111In]In-DOTATATE Uptake in NET Cells
Authors: Klomp Maria J. , Dalm Simone U. , van Koetsveld Peter M. , Dogan Fadime , de Jong Marion , Hofland Leo J.
Published: September 2021

The aim of this study was to increase somatostatin type-2 receptor (SSTR2) expression on neuroendocrine tumor (NET) cells using histone deacetylase inhibitors (HDACis), potentially increasing the uptake of SSTR2-targeted radiopharmaceuticals and subsequently improving treatment efficacy of peptide receptor radionuclide therapy (PRRT). Human NET cell lines BON-1, NCI-H727, and GOT1 were treated with HDACis (i.e., CI-994, entinostat, LMK-235, mocetinostat, panobinostat, or valproic acid (VPA); entinostat and VPA were the HDACis tested in GOT1 cells) to examine SSTR2 mRNA expression levels and uptake of SSTR2-targeting radiotracer [111In]In-DOTATATE. Reversibility of the induced effects was examined after drug-withdrawal. Finally, the effect of VPA on radiosensitivity was investigated. A strong stimulatory effect in BON-1, NCI-H727, and GOT1 cells was observed after HDACi treatment, both on SSTR2 mRNA expression levels and [111In]In-DOTATATE uptake. The effects of the HDACis were largely reversible over a period of seven days, demonstrating largest reductions within the first day. The reversibility profile of the induced effects suggests that proper timing of HDACi treatment is most likely essential for a beneficial outcome. In addition to increasing SSTR2 expression levels, VPA enhanced the radiosensitivity of all cell lines. In conclusion, HDACi treatment increased SSTR2 expression, and radiosensitivity was also enhanced upon VPA treatment.
The Role of Monoclonal Antibodies in the Era of Bi-Specifics Antibodies and CAR T Cell Therapy in Multiple Myeloma
Authors: Mohan Meera , Maatman Theresa Camille , Schinke Carolina
Published: September 2021

Multiple myeloma (MM) remains largely incurable despite enormous improvement in the outcome of patients. Over the past decade, we have witnessed the “era of monoclonal antibody (moAb)”, setting new benchmarks in clinical outcomes for relapsed and newly diagnosed MM. Due to their excellent efficacy and relative safe toxicity profile, moAbs in combination with immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs) have become the new backbone of upfront anti-MM therapy. Yet, most patients will eventually relapse and patients who become refractory to IMiDs, PIs and moAbs have a dismal outcome. Emerging T-cell directing therapies, such as bispecific antibody (bsAb) and chimeric antigen receptor T cells (CAR T) have shown unprecedented responses and outcomes in these heavily pretreated and treatment-refractory patients. Their clinical efficacy combined with high tolerability will likely lead to the use of these agents earlier in the treatment course and there is great enthusiasm that a combination of T cell directed therapy with moAbs can lead to long duration remission in the near future, possibly even without the need of high dose chemotherapy and stem cell transplantation. Herein, we summarize the role of naked moAbs in MM in the context of newer immunotherapeutic agents like bsAb and CAR T therapy.
An Updated Review on Head and Neck Cancer Treatment with Radiation Therapy
Authors: Anderson Garrett , Ebadi Maryam , Vo Kim , Novak Jennifer , Govindarajan Ameish , Amini Arya
Published: September 2021

The complexity of head and neck cancers (HNC) mandates a multidisciplinary approach and radiation therapy (RT) plays a critical role in the optimal management of patients with HNC, either as frontline or adjuvant treatment postoperatively. The advent of both definitive and post-operative RT has significantly improved the outcomes of patients with HNC. Herein, we discuss the role of postoperative RT in different subtypes of HNC, its side effects, and the importance of surveillance. The treatment regions discussed in this paper are the oral cavity, nasopharynx, paranasal sinus cavity, oropharynx, larynx and hypopharynx. Multiple studies that demonstrate the importance of definitive and/or postoperative RT, which led to an improved outlook of survival for HNC patients will be discussed.
Remodeling the ECM: Implications for Metastasis and Tumor Dormancy
Authors: Di Martino Julie S. , Akhter Tasmiah , Bravo-Cordero Jose Javier
Published: September 2021

While most primary tumors can be effectively treated, therapeutics fail to efficiently eliminate metastases. Metastases arise from cancer cells that leave the primary tumor and seed distant sites. Recent studies have shown that cancer cells disseminate early during tumor progression and can remain dormant for years before they resume growth. In these metastatic organs, cancer cells reside in microenvironments where they interact with other cells, but also with the extracellular matrix (ECM). The ECM was long considered to be an inert, non-cellular component of tissues, providing their architecture. However, in recent years, a growing body of evidence has shown that the ECM is a key driver of cancer progression, and it can exert effects on tumor cells, regulating their metastatic fate. ECM remodeling and degradation is required for the early steps of the metastatic cascade: invasion, tumor intravasation, and extravasation. Similarly, ECM molecules have been shown to be important for metastatic outgrowth. However, the role of ECM molecules on tumor dormancy and their contribution to the dormancy-supportive niches is not well understood. In this perspective article, we will summarize the current knowledge of ECM and its role in tumor metastasis and dormancy. We will discuss how a better understanding of the individual components of the ECM niche and their roles mediating the dormant state of disseminated tumor cells (DTCs) will advance the development of new therapies to target dormant cells and prevent metastasis outgrowth.
Targeting Nanomaterials to Head and Neck Cancer Cells Using a Fragment of the Shiga Toxin as a Potent Natural Ligand
Authors: Navarro-Palomares Elena , García-Hevia Lorena , Padín-González Esperanza , Bañobre-López Manuel , Villegas Juan C. , Valiente Rafael , Fanarraga Mónica L.
Published: September 2021

Head and Neck Cancer (HNC) is the seventh most common cancer worldwide with a 5-year survival from diagnosis of 50%. Currently, HNC is diagnosed by a physical examination followed by an histological biopsy, with surgery being the primary treatment. Here, we propose the use of targeted nanotechnology in support of existing diagnostic and therapeutic tools to prevent recurrences of tumors with poorly defined or surgically inaccessible margins. We have designed an innocuous ligand-protein, based on the receptor-binding domain of the Shiga toxin (ShTxB), that specifically drives nanoparticles to HNC cells bearing the globotriaosylceramide receptor on their surfaces. Microscopy images show how, upon binding to the receptor, the ShTxB-coated nanoparticles cause the clustering of the globotriaosylceramide receptors, the protrusion of filopodia, and rippling of the membrane, ultimately allowing the penetration of the ShTxB nanoparticles directly into the cell cytoplasm, thus triggering a biomimetic cellular response indistinguishable from that triggered by the full-length Shiga toxin. This functionalization strategy is a clear example of how some toxin fragments can be used as natural biosensors for the detection of some localized cancers and to target nanomedicines to HNC lesions.
Towards a Better Characterisation of Leukemic Cells in Chronic Lymphocytic Leukaemia: Cell-Size Heterogeneity Reflects Their Activation Status and Migratory Abilities
Authors: Manukyan Gayane , Mikulkova Zuzana , Turcsanyi Peter , Savara Jakub , Trajerová Markéta , Kubova Zuzana , Papajik Tomas , Kriegova Eva
Published: September 2021

Chronic lymphocytic leukaemia (CLL) is a genetically, morphologically and phenotypically heterogeneous chronic disease with clinical variability between patients. Whether the significant heterogeneity of cell size within the CLL population contributes to the heterogeneous features of this disease has not been investigated. The present study aimed to characterise the phenotypic and functional properties of two subpopulations of typical CLL cells that differ in cell size: small (s-CLL) and large (l-CLL) CLL cells delineated by forward scatter cytometry. The s-CLL cells were characterised by the CD5lowCXCR4hi phenotype, while the l-CLL cells were characterised by the CD5hiCXCR4dim phenotype and indicated a higher expression of CXCR3, CD20, CD38 and HLA-DR. The l-CLL cells displayed higher migration activity towards CXCL12, a tendency towards a higher proliferation rate and an increased capacity to produce IgM in the presence of CpG compared with s-CLL cells. When stimulated with CpG and CXCL12, l-CLL cells were characterised by a higher polarisation phenotype and motility than s-CLL cells. Our study revealed that the differences in CLL cell size reflected their activation status, polarisation and migratory abilities. Our data provide evidence of the importance of cell-size heterogeneity within a CLL pool and the dynamics of cell-size changes for disease pathogenesis, thus deserving further investigation.
Implications of Intratumor Heterogeneity on Consensus Molecular Subtype (CMS) in Colorectal Cancer
Authors: Chowdhury Saikat , Hofree Matan , Lin Kangyu , Maru Dipen , Kopetz Scott , Shen John Paul
Published: September 2021

The implications of intratumor heterogeneity on the four consensus molecular subtypes (CMS) of colorectal cancer (CRC) are not well known. Here, we use single-cell RNA sequencing (scRNASeq) to build an algorithm to assign CMS classification to individual cells, which we use to explore the distributions of CMSs in tumor and non-tumor cells. A dataset of colorectal tumors with bulk RNAseq (n = 3232) was used to identify CMS specific-marker gene sets. These gene sets were then applied to a discovery dataset of scRNASeq profiles (n = 10) to develop an algorithm for single-cell CMS (scCMS) assignment, which recapitulated the intrinsic biology of all four CMSs. The single-cell CMS assignment algorithm was used to explore the scRNASeq profiles of two prospective CRC tumors with mixed CMS via bulk sequencing. We find that every CRC tumor contains individual cells of each scCMS, as well as many individual cells that have enrichment for features of more than one scCMS (called mixed cells). scCMS4 and scCMS1 cells dominate stroma and immune cell clusters, respectively, but account for less than 3% epithelial cells. These data imply that CMS1 and CMS4 are driven by the transcriptomic contribution of immune and stromal cells, respectively, not tumor cells.
Enhanced Thermostability of Pseudomonas nitroreducens Isoeugenol Monooxygenase by the Combinatorial Strategy of Surface Residue Replacement and Consensus Mutagenesis
Authors: Lu Xin-Yi , Wu Xiao-Mei , Ma Bao-Di , Xu Yi
Published: September 2021

Vanillin has many applications in industries. Isoeugenol monooxygenase (IEM) can catalyze the oxidation of isoeugenol to vanillin in the presence of oxygen under mild conditions. However, the low thermal stability of IEM limits its practical application in the biosynthesis of natural vanillin. Herein, two rational strategies were combined to improve the thermostability of IEM from Pseudomonas nitroreducens Jin1. Two variants (K83R and K95R) with better thermostability and one mutant (G398A) with higher activity were identified from twenty candidates based on the Surface Residue Replacement method. According to the Consensus Mutagenesis method, one mutant (I352R) with better thermostability and another mutant (L273F) with higher activity were also identified from nine candidates. After combinatorial mutation, a triple mutant K83R/K95R/L273F with the best thermostability and catalytic efficiency was generated. Compared with the wild-type IEM, the thermal inactivation half-lives (t1/2) of K83R/K95R/L273F at 25 °C, 30 °C, and 35 °C increased 2.9-fold, 11.9-fold, and 24.7-fold, respectively. Simultaneously, it also exhibited a 4.8-fold increase in kcat, leading to a 1.2-fold increase in catalytic efficiency (kcat/Km). When the whole cell of K83R/K95R/L273F was applied to the biotransformation of isoeugenol on preparative scale, the vanillin concentration reached 240.1 mM with space-time yield of 109.6 g/L/d, and vanillin was achieved in 77.6% isolated yield and >99% purity.
The Intersection of Purine and Mitochondrial Metabolism in Cancer
Authors: De Vitto Humberto , Arachchige Danushka , Richardson Brian , French Jarrod
Published: September 2021

Nucleotides are essential to cell growth and survival, providing cells with building blocks for DNA and RNA, energy carriers, and cofactors. Mitochondria have a critical role in the production of intracellular ATP and participate in the generation of intermediates necessary for biosynthesis of macromolecules such as purines and pyrimidines. In this review, we highlight the role of purine and mitochondrial metabolism in cancer and how their intersection influences cancer progression, especially in ovarian cancer. Additionally, we address the importance of metabolic rewiring in cancer and how the evolving landscape of purine synthesis and mitochondria inhibitors can be potentially exploited for cancer treatment.
Advances in Chirality Sensing with Macrocyclic Molecules
Authors: Liang Xiaotong , Liang Wenting , Jin Pengyue , Wang Hongtao , Wu Wanhua , Yang Cheng
Published: September 2021

The construction of chemical sensors that can distinguish molecular chirality has attracted increasing attention in recent years due to the significance of chiral organic molecules and the importance of detecting their absolute configuration and chiroptical purity. The supramolecular chirality sensing strategy has shown promising potential due to its advantages of high throughput, sensitivity, and fast chirality detection. This review focuses on chirality sensors based on macrocyclic compounds. Macrocyclic chirality sensors usually have inherent complexing ability towards certain chiral guests, which combined with the signal output components, could offer many unique advantages/properties compared to traditional chiral sensors. Chirality sensing based on macrocyclic sensors has shown rapid progress in recent years. This review summarizes recent advances in chirality sensing based on both achiral and chiral macrocyclic compounds, especially newly emerged macrocyclic molecules.
Management of Advanced Heart Failure in Children with Cancer Therapy-Related Cardiac Dysfunction
Authors: Tunuguntla Hari P. , Puri Kriti , Denfield Susan W.
Published: September 2021

The evolution of cancer therapies has led to marked improvement in survival of those affected by childhood malignancies, while also increasing the recognition of early and late toxicities associated with cancer therapies. Cardiotoxicity can include cardiomyopathy/heart failure, coronary artery disease, stroke, pericardial disease, arrhythmias, and valvular and vascular dysfunction as a result of exposure to chemotherapy and/or radiation. Anthracyclines remain the most common cause of chemotherapy-induced cardiomyopathy (CCM) with varying clinical presentations including: acute, early onset, and late-onset. Many individuals develop cardiac dysfunction over the long-term, ranging from subclinical cardiac dysfunction to end-stage symptomatic heart failure. The focus of this review is on characterization of symptomatic heart failure in children with cancer therapy-related cardiac dysfunction (CTRCD) primarily due to CCM and utilization of advanced heart failure therapies, including ventricular assist device (VAD) support and heart transplantation, with consideration of unique patient-related factors.
Mothers’ Use of Regulatory Talk with Toddlers in Chile and the US: How Do Cultural Values and Children’s Gender Affect Mothers’ Regulatory Talk at 12 and 30 Months?
Authors: Santelices María Pía , Vallotton Claire De Ann , Farkas Chamarrita , Chang Tzu-Fen , Franco Eduardo , Gallardo Ana María
Published: September 2021

Studies have shown that Chilean and US infants differ in their levels of self-regulation. One of the mechanisms of early socializing is the use of language, particularly mental state language. The current study seeks to deepen our knowledge of the ways in which mental state language is related to socialization processes in early childhood, including the ways both culture and children’s gender influence a mothers’ use of mental state talk. We used a quantitative and descriptive approach with 109 mothers and their children (64 Chilean and 45 US dyads), measured twice, at 12 and 30 months old. Mental state references related to regulation were coded during a story-sharing task, including positive (calm and patient) and negative (messy and impatient) references to regulating behavior. Chilean mothers generally showed more regulatory references than US mothers, especially if the children were at a younger age (12 month). Frequencies of regulatory references increased in US mothers at 30 months but were still less than in Chilean mothers. At the 12-month measuring point, Chilean mothers showed more negative regulatory attributes than positive regulatory attributes. Finally, US mothers mainly used references to secondary emotions (e.g., pride) and positive regulatory attributes (being obedient, mature and patient) at both ages.
Quantitative Analysis of Positive-Bias-Stress-Induced Electron Trapping in the Gate Insulator in the Self-Aligned Top Gate Coplanar Indium–Gallium–Zinc Oxide Thin-Film Transistors
Authors: Kim Dae-Hwan , Jeong Hwan-Seok , Lee Dong-Ho , Bae Kang-Hwan , Lee Sunhee , Kim Myeong-Ho , Lim Jun-Hyung , Kwon Hyuck-In
Published: September 2021

We experimentally extracted the positive bias temperature stress (PBTS)-induced trapped electron distribution within the gate dielectric in self-aligned top-gate (SA-TG) coplanar indium–gallium–zinc oxide (IGZO) thin-film transistors (TFTs) using the analytical threshold voltage shift model. First, we carefully examined the effects of PBTS on the subgap density of states in IGZO TFTs to exclude the effects of defect creation on the threshold voltage shift due to PBTS. We assumed that the accumulated electrons were injected into the gate dielectric trap states near the interface through trap-assisted tunneling and were consequently moved to the trap states, which were located further away from the interface, through the Poole–Frenkel effect. Accordingly, we quantitatively analyzed the PBTS-induced electron trapping. The experimental results showed that, in the fabricated IGZO TFTs, the electrons were trapped in the shallow and deep trap states simultaneously owing to PBTS. Electrons trapped in the shallow state were easily detrapped after PBTS termination; however, those trapped in the deep state were not. We successfully extracted the PBTS-induced trapped electron data within the gate dielectric in the fabricated SA-TG coplanar IGZO TFTs by using the proposed method.
Coralline Hydroxyapatite Coated with a Layer Biomimetic Calcium Phosphate Containing BMP-2 Induces Dose-Related Ectopic Bone Formation in Wistar Rats
Authors: Uijlenbroek Henri , Lin Xingnan , Zhang Xin , Deng Liquan , Wismeijer Daniel , Wang Mingjie , Wei Lingfei , Zheng Yuanna , Liu Yuelian
Published: September 2021

In order to evaluate loading methods and the dose dependency of bone morphogenetic protein 2 (BMP-2) in ectopic bone formation, an osteoinductive material consisting of commercially available coralline hydroxyapatite (CHA) was coated with a layer of biomimetic calcium phosphate (BioCaP) containing BMP-2 in different ways. Eight groups—each containing samples of 0.25 g CHA—were formed and coated with, respectively, BioCaP with internally incorporated BMP-2 in concentrations of 1, 5, 10, 20, 40 and 60 µg per sample, and the two control groups with BioCaP only and BioCaP with 20 µg of adsorbed BMP-2 per sample. The samples were implanted subcutaneously in 27 male Wistar rats. The histological results show that there is no bone formation in the group in which no BMP-2 was included. All samples with BioCaP containing BMP-2 show bone formation. The group with 20 µg of adsorbed BMP-2 per sample shows the least bone formation. Coating-incorporated BMP-2 is more efficient in inducing bone formation than adsorbed BMP-2. The group with 5 µg of coating-incorporated BMP-2 per sample shows the most bone formation. Increasing the amount of coating-incorporated BMP-2 up to 60 µg does not improve ectopic bone formation.
Effect of Loading Direction on the Tensile Properties and Texture Evolution of AZ31 Magnesium Alloy
Authors: Li Yuyu , Han Tingzhuang , Chu Zhibing , Xue Chun , Yang Qianhua , Zhao Xiaodong , Gao Hong
Published: September 2021

Samples were cut from an extruded AZ31 magnesium alloy bar for uniaxial tensile and EBSD characterization tests. The long axis and bar extrusion directions were 0° (T0 sample), 45° (T45 sample), and 90° (T90 sample). The effects of loading direction on the tensile behavior, microstructure, and texture evolution of the magnesium alloy were studied. Results show that the obvious mechanical anisotropy of tensile behavior is affected by the loading direction, and the T0 sample with a grain c-axis perpendicular to the extrusion direction has a strong basal texture and high flow stress and yield strength. The loading direction has a significant influence on the microstructure characteristics of different samples, especially the number of {10–12} tensile twins and {10–11} compression twins. Texture evolution results show that the loading direction and the effect of deformation mode on the deformation mechanism lead to variations in texture evolution: the basal slip and prismatic slip during the plastic deformation of the T0 specimen, the compression twin of the T45 specimen, and the tensile twin of the T90 specimen.
Experimental Data of Bottom Pressure and Free Surface Elevation including Wave and Current Interactions
Authors: Gabl Roman , Draycott Samuel , Pillai Ajit C. , Davey Thomas
Published: September 2021

Force plates are commonly used in tank testing to measure loads acting on the foundation of a structure. These targeted measurements are overlaid by the hydrostatic and dynamic pressure acting on the force plate induced by the waves and currents. This paper presents a dataset of bottom force measurement with a six degree-of-freedom force plate (AMTI OR6-7 1000, surface area 0.464 m × 0.508 m) combined with synchronised measurements of surface elevation and current velocity. The data cover wave frequencies between 0.2 to 0.7 Hz and wave directions between 0∘ and 180∘. These variations are provided for current speeds of 0 and 0.2 m/s and a variation of the current in the absence of waves covering 0 to 0.45 m/s. The dataset can be utilised as a validation dataset for models predicting bottom pressure based on free surface elevation. Additionally, the dataset provides the wave- and current-induced load acting on the specific load cell at a fixed water depth of 2 m, which can subsequently be removed to obtain the often-desired measurement of structural loads.
Predicting Mechanical Ventilation and Mortality in COVID-19 Using Radiomics and Deep Learning on Chest Radiographs: A Multi-Institutional Study
Authors: Bae Joseph , Kapse Saarthak , Singh Gagandeep , Gattu Rishabh , Ali Syed , Shah Neal , Marshall Colin , Pierce Jonathan , Phatak Tej , Gupta Amit , Green Jeremy , Madan Nikhil , Prasanna Prateek
Published: September 2021

In this study, we aimed to predict mechanical ventilation requirement and mortality using computational modeling of chest radiographs (CXRs) for coronavirus disease 2019 (COVID-19) patients. This two-center, retrospective study analyzed 530 deidentified CXRs from 515 COVID-19 patients treated at Stony Brook University Hospital and Newark Beth Israel Medical Center between March and August 2020. Linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and random forest (RF) machine learning classifiers to predict mechanical ventilation requirement and mortality were trained and evaluated using radiomic features extracted from patients’ CXRs. Deep learning (DL) approaches were also explored for the clinical outcome prediction task and a novel radiomic embedding framework was introduced. All results are compared against radiologist grading of CXRs (zone-wise expert severity scores). Radiomic classification models had mean area under the receiver operating characteristic curve (mAUCs) of 0.78 ± 0.05 (sensitivity = 0.72 ± 0.07, specificity = 0.72 ± 0.06) and 0.78 ± 0.06 (sensitivity = 0.70 ± 0.09, specificity = 0.73 ± 0.09), compared with expert scores mAUCs of 0.75 ± 0.02 (sensitivity = 0.67 ± 0.08, specificity = 0.69 ± 0.07) and 0.79 ± 0.05 (sensitivity = 0.69 ± 0.08, specificity = 0.76 ± 0.08) for mechanical ventilation requirement and mortality prediction, respectively. Classifiers using both expert severity scores and radiomic features for mechanical ventilation (mAUC = 0.79 ± 0.04, sensitivity = 0.71 ± 0.06, specificity = 0.71 ± 0.08) and mortality (mAUC = 0.83 ± 0.04, sensitivity = 0.79 ± 0.07, specificity = 0.74 ± 0.09) demonstrated improvement over either artificial intelligence or radiologist interpretation alone. Our results also suggest instances in which the inclusion of radiomic features in DL improves model predictions over DL alone. The models proposed in this study and the prognostic information they provide might aid physician decision making and efficient resource allocation during the COVID-19 pandemic.
Confocal Laser Endomicroscopy in Oncological Surgery
Authors: Charalampaki Patra , Kakaletri Irini
Published: September 2021

The therapy of choice in the treatment of abnormalities in the human body, is to attempt a personalized diagnosis and with minimal invasiveness, ideally resulting in total resection (surgery) or turning off (intervention) of the pathology with preservation of normal functional tissue, followed by additional treatments, e [...]
A Transformer-Based Hierarchical Variational AutoEncoder Combined Hidden Markov Model for Long Text Generation
Authors: Zhao Kun , Ding Hongwei , Ye Kai , Cui Xiaohui
Published: September 2021

The Variational AutoEncoder (VAE) has made significant progress in text generation, but it focused on short text (always a sentence). Long texts consist of multiple sentences. There is a particular relationship between each sentence, especially between the latent variables that control the generation of the sentences. The relationships between these latent variables help in generating continuous and logically connected long texts. There exist very few studies on the relationships between these latent variables. We proposed a method for combining the Transformer-Based Hierarchical Variational AutoEncoder and Hidden Markov Model (HT-HVAE) to learn multiple hierarchical latent variables and their relationships. This application improves long text generation. We use a hierarchical Transformer encoder to encode the long texts in order to obtain better hierarchical information of the long text. HT-HVAE’s generation network uses HMM to learn the relationship between latent variables. We also proposed a method for calculating the perplexity for the multiple hierarchical latent variable structure. The experimental results show that our model is more effective in the dataset with strong logic, alleviates the notorious posterior collapse problem, and generates more continuous and logically connected long text.
Joint User Scheduling, Relay Selection, and Power Allocation for Multi-Antenna Opportunistic Beamforming Systems
Authors: Sun Wenbin , Tao Mingliang , Yang Xin , Zhang Tao , Han Chuang , Wang Ling
Published: September 2021

Opportunistic beamforming (OBF) is a potential technique in the fifth generation (5G) and beyond 5G (B5G) that can boost the performance of communication systems and encourage high user quality of service (QoS) through multi-user selection gain. However, the achievable rate tends to be saturated with the increased number of users, when the number of users is large. To further improve the achievable rate, we proposed a multi-antenna opportunistic beamforming-based relay (MOBR) system, which can achieve both multi-user and multi-relay selection gains. Then, an optimization problem is formulated to maximize the achievable rate. Nevertheless, the optimization problem is a non-deterministic polynomial (NP)-hard problem, and it is difficult to obtain an optimal solution. In order to solve the proposed optimization problem, we divide it into two suboptimal issues and apply a joint iterative algorithm to consider both the suboptimal issues. Our simulation results indicate that the proposed system achieved a higher achievable rate than the conventional OBF systems and outperformed other beamforming schemes with low feedback information.
Constrained Adjusted Maximum a Posteriori Estimation of Bayesian Network Parameters
Authors: Di Ruohai , Wang Peng , He Chuchao , Guo Zhigao
Published: September 2021

Maximum a posteriori estimation (MAP) with Dirichlet prior has been shown to be effective in improving the parameter learning of Bayesian networks when the available data are insufficient. Given no extra domain knowledge, uniform prior is often considered for regularization. However, when the underlying parameter distribution is non-uniform or skewed, uniform prior does not work well, and a more informative prior is required. In reality, unless the domain experts are extremely unfamiliar with the network, they would be able to provide some reliable knowledge on the studied network. With that knowledge, we can automatically refine informative priors and select reasonable equivalent sample size (ESS). In this paper, considering the parameter constraints that are transformed from the domain knowledge, we propose a Constrained adjusted Maximum a Posteriori (CaMAP) estimation method, which is featured by two novel techniques. First, to draw an informative prior distribution (or prior shape), we present a novel sampling method that can construct the prior distribution from the constraints. Then, to find the optimal ESS (or prior strength), we derive constraints on the ESS from the parameter constraints and select the optimal ESS by cross-validation. Numerical experiments show that the proposed method is superior to other learning algorithms.
Econophysics and the Entropic Foundations of Economics
Authors: Rosser J. Barkley
Published: September 2021

This paper examines relations between econophysics and the law of entropy as foundations of economic phenomena. Ontological entropy, where actual thermodynamic processes are involved in the flow of energy from the Sun through the biosphere and economy, is distinguished from metaphorical entropy, where similar mathematics used for modeling entropy is employed to model economic phenomena. Areas considered include general equilibrium theory, growth theory, business cycles, ecological economics, urban–regional economics, income and wealth distribution, and financial market dynamics. The power-law distributions studied by econophysicists can reflect anti-entropic forces is emphasized to show how entropic and anti-entropic forces can interact to drive economic dynamics, such as in the interaction between business cycles, financial markets, and income distributions.
Bibliometric Analysis on Supercritical CO2 Power Cycles for Concentrating Solar Power Applications
Authors: Reyes-Belmonte Miguel Angel , Guédez Rafael , Montes Maria José
Published: September 2021

In recent years, supercritical CO2 power cycles have received a large amount of interest due to their exceptional theoretical conversion efficiency above 50%, which is leading a revolution in power cycle research. Furthermore, this high efficiency can be achieved at a moderate temperature level, thus suiting concentrating solar power (CSP) applications, which are seen as a core business within supercritical technologies. In this context, numerous studies have been published, creating the need for a thorough analysis to identify research areas of interest and the main researchers in the field. In this work, a bibliometric analysis of supercritical CO2 for CSP applications was undertaken considering all indexed publications within the Web of Science between 1990 and 2020. The main researchers and areas of interest were identified through network mapping and text mining techniques, thus providing the reader with an unbiased overview of sCO2 research activities. The results of the review were compared with the most recent research projects and programs on sCO2 for CSP applications. It was found that popular research areas in this topic are related to optimization and thermodynamics analysis, which reflects the significance of power cycle configuration and working conditions. Growing interest in medium temperature applications and the design of sCO2 heat exchangers was also identified through density visualization maps and confirmed by a review of research projects.
Variational Beta Process Hidden Markov Models with Shared Hidden States for Trajectory Recognition
Authors: Zhao Jing , Zhang Yi , Sun Shiliang , Dai Haiwei
Published: September 2021

Hidden Markov model (HMM) is a vital model for trajectory recognition. As the number of hidden states in HMM is important and hard to be determined, many nonparametric methods like hierarchical Dirichlet process HMMs and Beta process HMMs (BP-HMMs) have been proposed to determine it automatically. Among these methods, the sampled BP-HMM models the shared information among different classes, which has been proved to be effective in several trajectory recognition scenes. However, the existing BP-HMM maintains a state transition probability matrix for each trajectory, which is inconvenient for classification. Furthermore, the approximate inference of the BP-HMM is based on sampling methods, which usually takes a long time to converge. To develop an efficient nonparametric sequential model that can capture cross-class shared information for trajectory recognition, we propose a novel variational BP-HMM model, in which the hidden states can be shared among different classes and each class chooses its own hidden states and maintains a unified transition probability matrix. In addition, we derive a variational inference method for the proposed model, which is more efficient than sampling-based methods. Experimental results on a synthetic dataset and two real-world datasets show that compared with the sampled BP-HMM and other related models, the variational BP-HMM has better performance in trajectory recognition.