bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep Learning Features Encode Interpretable Morphologies within Histological Images
Authors: pour Ali Foroughi , White Brian , park Jonghanne , Sheridan Todd , Chuang Jeffrey 
Published: February 2022

Abstract
Convolutional neural networks (CNNs) are revolutionizing digital pathology by enabling machine learning-based classification of a variety of phenotypes from hematoxylin and eosin (H&E) whole slide images (WSIs), but the interpretation of CNNs remains difficult. Most studies have considered interpretability in a post hoc fashion, e.g. by presenting example regions with strongly predicted class labels. However, such an approach does not explain the biological features that contribute to correct predictions. To address this problem, here we investigate the interpretability of H&E-derived CNN features (the feature weights in the final layer of a transfer-learning-based architecture). While many studies have incorporated CNN features into predictive models, there has been little empirical study of their properties. We show such features can be construed as abstract morphological genes (“mones”) with strong independent associations to biological phenotypes. Many mones are specific to individual cancer types, while others are found in multiple cancers especially from related tissue types. We also observe that mone-mone correlations are strong and robustly preserved across related cancers. Importantly, linear mone-based classifiers can very accurately separate 38 distinct classes (19 tumor types and their adjacent normals, AUC=97.1% +/- 2.8% for each class prediction), and linear classifiers are also highly effective for universal tumor detection (AUC=99.2% +/- 0.12%). This linearity provides evidence that individual mones or correlated mone clusters may be associated with interpretable histopathological features or other patient characteristics. In particular, the statistical similarity of mones to gene expression values allows integrative mone analysis via expression-based bioinformatics approaches. We observe strong correlations between individual mones and individual gene expression values, notably mones associated with collagen gene expression in ovarian cancer. Mone-expression comparisons also indicate that immunoglobulin expression can be identified using mones in colon adenocarcinoma and that immune activity can be identified across multiple cancer types, and we verify these findings by expert histopathological review. Our work demonstrates that mones provide a morphological H&E decomposition that can be effectively associated with diverse phenotypes, analogous to the interpretability of transcription via gene expression values. Our work also demonstrates mones can be interpreted without using a classifier as a proxy.
Seismic response analysis of tunnel with cavity behind lining
Authors: Wang Dai , Wang Shiyu , Zhang Hai , Liu Zhongxian 
Published: February 2022

For the seismic safety of tunnels with cavity behind lining, based on the finite element method, the viscoelastic artificial boundaries are introduced to study the influence of the location of cavity behind lining on the seismic response of tunnel structure under vertically incident SV wave. The analysis results show that the cavity behind the lining has a significant effect on the seismic response of tunnel structure, and the appearance of cavity behind lining will significantly change the dynamic characteristics of tunnel structure; when the incidence frequency of wave is close to the natural vibration frequency of tunnel structure, the lining stress has the largest amplification when the cavity appears behind the vault; Regardless of the cavity location, the maximum of lining stresses always appears at the arched foot, and the vault stress has the largest amplification; Under the Taft wave, the maximum stress 1.642 MPa of lining without cavity appears at the arched foot, and the minimum 0.118MPa at the arched waist, the stress amplification at the vault can reach about 760 %, which is unfavorable to tunnels. In addition, the soil property also has a great influence on the tunnel; the layered site will lead to the obvious change of the seismic wave, hence the geological data should be collected in detail in the seismic design of tunnel. Meanwhile it is proposed that the PE material can be filled back into the cavities behind the tunnel lining to reduce the earthquake damage of tunnels.
Association of park drinking water source characteristics and water intake in San Francisco Bay Area parks
Authors: Ezennia Jeffery , Schmidt Laura A. , Blacker Lauren S. , Vargas Roberto A. , McCulloch Charles E. , Patel Anisha I. 
Published: February 2022

Abstract
Over half of U.S. adults visit parks regularly. Thus, it is important to understand how park drinking water sources affect visitors’ water consumption. In this cross-sectional study of 30 San Francisco Bay Area parks, 4 day-long direct observations of visitors’ drinking water and other beverages were conducted, along with audits of sugar-sweetened beverage access and drinking water source conditions, including flow, appeal, and obstructions. Outcomes were log-transformed to account for skewness, and results were analyzed using mixed-effects regression models to account for matching and clustering by park and observation day. A greater proportion of water sources in low-income parks were unappealing (57.14 vs. 25.00%, P = 0.01) or in a poor condition (69.70 vs. 43.24%, P = 0.03). A lower proportion of visitors drank water from park fountains that were unappealing (−31%), had poor flow (−22%), or had obstructions (−58%) than those without these conditions. Although only obstructions to the source and water intake were significantly related after adjustment, we observed important effects on water intake by water source appeal and flow. As park water source conditions contribute to water intake, cities should consider installing appealing, functional, and easy to access water sources in parks, particularly those in lower-income neighborhoods.
Statistical tools for water quality assessment and monitoring in river ecosystems – a scoping review and recommendations for data analysis
Authors: Schreiber Stefan G. , Schreiber Sanja , Tanna Rajiv N. , Roberts David R. , Arciszewski Tim J. 
Published: February 2022

Abstract
Robust scientific inference is crucial to ensure evidence-based decision making. Accordingly, the selection of appropriate statistical tools and experimental designs is integral to achieve accuracy from data analytical processes. Environmental monitoring of water quality has become increasingly common and widespread as a result of technological advances, leading to an abundance of datasets. We conducted a scoping review of the water quality literature and found that correlation and linear regression are by far the most used statistical tools. However, the accuracy of inferences drawn from ordinary least squares (OLS) techniques depends on a set of assumptions, most prominently: (a) independence among observations, (b) normally distributed errors, (c) equal variances of errors, and (d) balanced designs. Environmental data, however, are often faced with temporal and spatial dependencies, and unbalanced designs, thus making OLS techniques not suitable to provide valid statistical inferences. Generalized least squares (GLS), linear mixed-effect models (LMMs), and generalized linear mixed-effect models (GLMMs), as well as Bayesian data analyses, have been developed to better tackle these problems. Recent progress in the development of statistical software has made these approaches more accessible and user-friendly. We provide a high-level summary and practical guidance for those statistical techniques.
Selenium-containing Peptides and their Biological Applications
Authors: Ahmed Kainat , Ashraf Delawar , Chotana Ghayoor Abbas , Faisal Amir , Khan Khalid Mohammed , Saleem Rahman Shah Zaib 
Published: February 2022

Abstract:
Selenium (Se) has been known for its beneficial biological roles for several
years, but interest in this trace element has seen a significant increase in the past couple
of decades. It has been reported to be a part of important bioactive organic compounds,
such as selenoproteins and amino acids, including selenocysteine (SeCys), selenomethionine
(SeMet), selenazolidine (SeAzo), and selenoneine. The traditional Se supplementations
(primarily as selenite and selenomethionine), though have been shown to carry
some benefits, also have associated toxicities, thereby paving the way for the organoselenium
compounds, especially the selenoproteins and peptides (SePs/SePPs) that offer several
health benefits beyond fulfilling the elementary nutritional Se needs. This review
aims to showcase the applications of selenium-containing peptides that have been reported
in recent decades. This article summarizes their bioactivities, including neuroprotective,
antiinflammatory, anticancer, antioxidant, hepatoprotective, and immunomodulatory
roles. This will offer the readers a sneak peek into the current advancements to invoke
further developments in this emerging research area.
Extended Double Bond Conjugation in the Chalcone Framework Favours MAO-B Inhibition: A Structural Perspective on Molecular Dynamics
Authors: Abdelgawad Mohamed A. , Soliman Mahmoud E.S. , Mathew Bijo , Agoni Clement , Issahaku Abdul Rashid , Khames Ahmed 
Published: February 2022

Background:The monotropic membrane protein monoamine oxidase B (MAO-B) has been shown to be a crucial drug target for the treatment of neurodegenerative diseases. The design of recent inhibitor therapeutic agents of MAO-B involves conjugation and modification of a chalcone scaffold comprising two aryl or heteroaryl rings connected via a short spacer unit with rotatable bonds. Supported by experimental data, these modifications often result in high potent inhibitor compounds.Method:In this study, we employ molecular dynamics simulations to unravel the impact of extended double bond conjugation in two novel compounds, F1 and MO10, toward the inhibition of the MAO-B protein. It was revealed that extended double bond conjugation induced a unidirectional orientation and motion of F1 and MO10, suggesting a stable binding pocket anchorage favouring high-affinity pocket interactions.Discussion:Real-time structural dynamics also revealed that the extended double bond conjugation mediated peculiar interactions with MAO-B binding pocket residues characterized by π-alkyl, π-π stacking, and π-sulphur interactions which buried both compounds into the hydrophobic core of MAO-B and ultimately induced higher binding affinities of both F1 and MO10.Result::Conformational analyses also revealed that the incorporated double bond extension impeded the motion of individual binding pocket residues, which subsequently disrupted the functionality of MAO-B.Conclusion:These insights present useful structural perspectives of the extended double bond conjugation associated with the experimentally reported enhanced inhibitory activity of F1 and MO10 against MAO-B.
Integrating LASSO Feature Selection and Soft Voting Classifier to Identify
Origins of Replication Sites
Authors: Zhang Shengli , Yao Yingying , Xue Tian 
Published: February 2022

Background:
DNA replication plays an indispensable role in the transmission of genetic
information. It is considered to be the basis of biological inheritance and the most fundamental process
in all biological life. Considering that DNA replication initiates with a special location, namely the
origin of replication, a better and accurate prediction of the origins of replication sites (ORIs) is essential
to gain insight into the relationship with gene expression.

Objective:
In this study, we have developed an efficient predictor called iORI-LAVT for ORIs identification.

Methods::
This work focuses on extracting feature information from three aspects, including mononucleotide
encoding, k-mer and ring-function-hydrogen-chemical properties. Subsequently, least absolute
shrinkage and selection operator (LASSO) as a feature selection is applied to select the optimal
features. Comparing the different combined soft voting classifiers results, the soft voting classifier
based on GaussianNB and Logistic Regression is employed as the final classifier.

Results:
Based on 10-fold cross-validation test, the prediction accuracies of two benchmark datasets
are 90.39% and 95.96%, respectively. As for the independent dataset, our method achieves high accuracy
of 91.3%.

Conclusion:
Compared with previous predictors, iORI-LAVT outperforms the existing methods. It is
believed that iORI-LAVT predictor is a promising alternative for further research on identifying ORIs.
Biological Activities, Pharmacokinetics and Toxicity of Nootkatone: A Review
Authors: Sahu Bidya Dhar , Jha Ankush Kumar , Gairola Shobhit , Kundu Sourav , Doye Pakpi , Syed Abu Mohammad , Ram Chetan , Kulhari Uttam , Kumar Naresh , Murty Upadhyayula Suryanarayana 
Published: February 2022

Abstract:
Plant-based drugs have a significant impact on modern therapeutics due to their vast array of pharmacological activities. The integration of herbal plants in the current healthcare system has emerged as a new field of research. It can be used for the identification of novel lead compound candidates for future drug development. Nootkatone is a sesquiterpene derivative and an isolate of grapefruit. Shreds of evidence illustrate that nootkatone targets few molecular mechanisms to exhibit its pharmacological activity and yet needs more exploration to be established. The current review is related to nootkatone, drafted through a literature search using research articles and books from different sources, including Science Direct, Google Scholar, Elsevier, PubMed, and Scopus. It has been reported to possess a wide range of pharmacological activities such as anti-inflammatory, anticancer, antibacterial, hepatoprotective, neuroprotective, and cardioprotective. Although preclinical studies in experimental animal models suggest that nootkatone has therapeutic potential, it is further warranted to evaluate its toxicity and pharmacokinetic parameters before being applied to humans. Hence in the present review, we have summarized the scientific knowledge on nootkatone with a particular emphasis on its pharmacological properties to encourage researchers for further exploration in preclinical and clinical settings.
The Medicinal Chemistry of Chalcones as Anti-Mycobacterium tuberculosis Agents
Authors: Dos Santos Jean Leandro , Rodríguez-Silva Cristhian N. , Prokopczyk Igor Muccilo 
Published: February 2022

Abstract:
Tuberculosis (TB), a highly fatal infectious disease, is caused by Mycobacterium tuberculosis (Mtb) that has inflicted mankind for several centuries. In 2019, the staggering number of new cases reached 10 million resulting in 1.2 million deaths. The emergence of multidrug-resistance- Mycobacterium tuberculosis (MDR-TB) and extensively drug-resistant-Mycobacterium tuberculosis (XDR-TB) is a global concern that requires the search for novel, effective, and safer short-term therapies. Nowadays, among the few alternatives available to treat resistant-Mtb strains, the majority have limitations, which include drug-drug interactions, long-term treatment, and chronic induced toxicities. Therefore, it is mandatory to develop new anti-Mtb agents to achieve health policy goals to mitigate the disease by 2035. Among the several bioactive anti-Mtb compounds, chalcones have been described as the privileged scaffold useful for drug design. Overall, this review explores and analyzes 37 chalcones that exhibited anti-Mtb activity described in the literature up to April 2021 with minimum inhibitory concentration (MIC90) values inferior to 20 μM and selective index superior to 10. In addition, the correlation of some properties for most active compounds was evaluated, and the main targets for these compounds were discussed.
MCM3AP-AS1: A LncRNA Participating in the Tumorigenesis of Cancer Through Multiple Pathways
Authors: Yuan Chengfu , Wang Bei , Chen Jinlan , Lin Chen , Liu Ru , Wang Lu 
Published: February 2022

Background:
More and more shreds of evidence show that the occurrence and development of tumors are closely related to the abnormal expression of LncRNA. A large number of experiments have found that overexpression or under-expression of MCM3AP-AS1 can affect the occurrence and development of cancer cells in varying degrees, such as proliferation, invasion, and translocation. Besides, MCM3AP-AS1 may become a promising target for many tumor biotherapies. This article reviews the pathophysiological functions and molecular mechanisms of MCM3AP-AS1 in various tumors.

Methods:
This paper systematically summarizes the published literatures in PubMed. The molecular mechanism of MCM3AP-AS1 in a variety of tumors is reviewed.

Results:
The abnormal expression of MCM3AP-AS1 in different tumors is closely related to tumor proliferation, invasion, and migration. MCM3AP-AS1 mediates or participates in related signaling pathways to regulate the expression of targeted miRNAs and proteins. MCM3AP-AS1 plays a vital role in tumor diagnosis and treatment.

Conclusion:
LncRNA MCM3AP-AS1 is a feasible tumor marker and a potential therapeutic target for many kinds of tumors.
Durable Disease-free Survival in a Patient with Metastatic Triple-negative
Breast Cancer Treated with Olaparib Monotherapy
Authors: Wang Xue , Hu Nanlin , Cui Lina , Si Yiran , Yue Jian , Zheng Fangchao , Kang Yikun , Yuan Peng 
Published: February 2022

Background:
Metastatic triple-negative breast cancer (mTNBC) has a poor prognosis and
few effective targeted therapy options. Olaparib, a poly (ADP-ribose) polymerase (PARP) inhibitor,
has been granted accelerated approval by FDA for patients with deleterious BRCA-mutated human
epidermal growth factor receptor 2 (HER2)-negative advanced/metastatic breast cancer. However,
there is little data demonstrating that patients with particular forms of germline and/or somatic
BRCA1/2, such as large fragment variation, can benefit from PARP inhibitors.

Case Presentation:
In 2011, a 40-year-old woman was diagnosed with TNBC having pT2N0M0 in the
right breast, and a new irregular lesser tubercle in the left breast appeared after approximately 3 years,
which was also diagnosed as TNBC. In 2017, computed tomography (CT) showed TNBC metastases
to the lung and brain. A next-generation sequencing (NGS) was performed with a lung metastasis sample,
and results showed a homologous recombination deficiency (HRD) score of 67, a germline large
deletion of exon 2 in BRCA1, a novel somatic BRCA2-STARD13 rearrangement and copy number
loss of RAD51. Since September 2017, the patient was treated with olaparib. Till the report date of this
case, the patient underwent regular follow-up without disease recurrence.

Conclusion:
To our knowledge, this is the first case describing a patient with lung- and brainmetastatic
TNBC with combined germline and somatic large rearrangement and a high HRD score
who achieved a long-term benefit from olaparib monotherapy. The use of NGS is promising in the
treatment of TNBC in clinical practice.
Cancer Vaccine in Cold Tumors: Clinical Landscape, Challenges, and
Opportunities
Authors: Rezaei Mahnaz , Danilova Natalia D. , Soltani Mojdeh , Savvateeva Lyudmila V. , Tarasov Vadim V. , Ganjalikhani-Hakemi Mazdak , Bazhin Alexandr V. , Zamyatnin Andrey A. 
Published: February 2022

Abstract:
The idea of cancer immunotherapy is to stimulate the immune system to fight tumors
without destroying normal cells. One of the anticancer therapy methods, among many, is based on
the use of cancer vaccines that contain tumor antigens in order to induce immune responses against
tumors. However, clinical trials have shown that the use of such vaccines as monotherapy is ineffective
in many cases since they do not cause a strong immune response. Particular tumors are resistant
to immunotherapy due to the absence or insufficient infiltration of tumors with CD8+ T cells, and
hence, they are called cold or non-inflamed tumors. Cold tumors are characterized by a lack of CD8+
T cell infiltration, the presence of anti-inflammatory myeloid cells, tumor-associated M2 macrophages,
and regulatory T cells. It is very important to determine the stage of the antitumor response that
does not work properly in order to use the right strategy. Applying other therapeutic methods alongside
cancer vaccines can be more rational for cold tumors, which do not provoke the immune system
strongly. Herein, we indicate some combinational therapies that have been used or are in progress for
cold tumor treatment alongside vaccines.
Targeting G-Quadruplex DNA for Cancer Chemotherapy
Authors: Acharya Pratap Chandra , Debbarma Sumanta 
Published: February 2022

Abstract:
The self-association of DNA formed by Hoogsteen hydrogen bonding comprises several
layers of four guanine or G-tetrads or G4s. The distinct feature of G4s, such as the G-tetrads and
loops, qualify structure-selective recognition by small molecules and various ligands and can act as
potential anticancer therapeutic molecules. The G4 selective ligands can influence gene expression by
targeting a nucleic acid structure rather than sequence. Telomere G4 can be targeted for cancer treatment
by small molecules inhibiting the telomerase activity, whereas c-MYC is capable of controlling
transcription and can be targeted to influence transcription. The k-RAS is one of the most frequently
encountered oncogenic driver mutations in pancreatic, colorectal, and lung cancers. The k-RAS oncogene
plays an important role in acquiring and increasing drug resistance and can also be directly targeted
by small molecules to combat k-RAS mutant tumors. Modular G4 ligands with different functional
groups, side chains, and rotatable bonds, as well as conformation, affect the binding affinity/
selectivity in cancer chemotherapeutic interventions. These modular G4 ligands act by targeting the
diversity of G4 loops and groves and assist in developing more drug-like compounds with selectivity.
In this review, we present the recent research on synthetic G4 DNA-interacting ligands as an approach
towards the discovery of target-specific anticancer chemotherapeutic agents.
Recent Development in Small Molecules for SARS-CoV-2 and the Opportunity for Fragment-Based Drug Discovery
Authors: Mahato Sujit 
Published: February 2022

Abstract:The ongoing pandemic of Covid-19 caused by SARS-CoV-2 is a major threat to global public health, drawing attention to develop new therapeutics for treatment. Much research work is focused on identifying or repurposing new small molecules to serve as potential inhibitors by interacting with viral or host-cell molecular targets and understanding the nature of the virus in the host cells. Identifying small molecules as potent inhibitors at an early stage is advantageous in developing a molecule with higher potency and then finding a lead compound for the development of drug discovery. Small molecules can show their inhibition property by targeting either the SARS-CoV-2 main protease (Mpro) enzyme, papain-like protease (PLpro) enzyme, or helicase (Hel), or blocking the spike (S) protein angiotensin-converting enzyme 2 (ACE2) receptor. A very recent outbreak of a new variant (B.1.617.2—termed as Delta variant) of SARS-CoV-2 worldwide posed a greater challenge as it is resistant to clinically undergoing vaccine trials. Thus, the development of new drug molecules is of potential interest to combat SARS-CoV-2 disease, and for that, the fragment-based drug discovery (FBDD) approach could be one of the ways to bring out an effective solution. Two cysteine protease enzymes would be an attractive choice of target for fragment-based drug discovery to tune the molecular structure at an early stage with suitable functionality. In this short review, the recent development in small molecules as inhibitors against Covid-19 is discussed, and the opportunity for FBDD is envisioned optimistically to provide an outlook regarding Covid-19 that may pave the way in the direction of the Covid-19 drug development paradigm.