bluuebunny/crossref_metadata_2025_split huggingface dataset:
MyD88 in Hepatic Stellate Cells Promotes the Development of Alcoholic Fatty Liver via the AKT Pathway
Authors: Li Yukun , Wei Miaomiao , Yuan Qi , Liu Yu , Tian Tian , Hou Lingling , Zhang Jinhua 
Published: November 2021

Abstract
Myeloid differentiation primary response gene 88 (MyD88), an adaptor protein in the TLRs signaling pathway, is expressed in various liver cells including hepatocytes, Kupffer cells and hepatic stellate cells (HSCs). However, the specific role of MyD88 in HSCs in alcoholic fatty liver (AFL) has not been well investigated. Here, to study the role of MyD88 in HSCs in the development of AFL and its related molecular mechanism, chronic-binge ethanol mice models were established in mice with specific MyD88 knockout in quiescent (MyD88GFAP−KO) and activated HSCs (MyD88SMA−KO), respectively. The results showed that the expression of MyD88 in HSCs was significantly increased in ethanol-induced liver tissues of wild-type mice. MyD88 deficiency in quiescent HSCs inhibited inflammation and lipogenesis, but in activated HSCs it only inhibited inflammation under the ethanol feeding condition. Further mechanism studies found that MyD88 promoted the osteopontin (OPN) secretion of HSCs, which further activated the AKT signaling pathway of hepatocytes and upregulated lipogenic gene expression to promote fat accumulation. In addition, OPN also promotes inflammation by activating p-STAT1. Thus, MyD88 may represent a potential candidate target for the prevention and targeted therapy in AFL, and MyD88 inhibitor can be also applied in inhibiting adipogenesis.
Electronic And Nonlinear Optical Features of Inorganic Ga12N12 Nanocage Decorated With Alkali Metals (Li, Na and K)
Authors: Jamshidi Azadeh , Biglari Zeinab 
Published: November 2021

Abstract
The effect of alkali metals (Li, Na and K) interaction on the nonlinear optical response (NLO) of Ga12N12 nanocage has been performed using density functional theory (DFT) calculations. The results show that the exo-M@Ga12N12 structures are energetically favorable with negative interaction energies in the range of ‒1.50 to ‒2.28 eV. The electronic properties of decorated structures are strongly sensitive to interaction with the alkali metals. The HOMO-LUMO gap of Ga12N12 is reduced by about 70% due to the decoration with alkali metals. It is obtained that the adsorption of alkali metals over the tetragonal ring of Ga12N12 nanocage remarkably enhances the first hyperpolarizability up to 6.5×104 au. The results display that decorating Ga12N12 nanocage with alkali metals can be introduced it as a novel inorganic nanomaterial with significant NLO properties.
Mapping the Spatiotemporal Diversity of Precipitation in Iran
Authors: Jamshidi Zahra , Samani Nozar 
Published: November 2021

Abstract
Despite located in a semi-arid and arid part of the world, Iran enjoys a very diverse climate. As a result, water availability in different regions of the country is in a veil of ambiguity. To have a better insight, we investigate the spatiotemporal diversity of precipitation over the country by analyzing the 33-years long monthly precipitation time series (1983-2016) at 461 measuring rain-gauge stations. Cluster Analysis (CA) both hierarchical and non-hierarchical clustering approaches and Principal Component Analysis (PCA) was used to determine the homogeneous precipitation zones at three macro, meso, and micro-scales. First, the country is divided into six precipitation macro-regions using CA. Each region shows a unique mean annual hyetograph and is influenced by a particular air moisture mass entering the country. Then, the six regions were divided into 10 regions of meso-resolution through Hierarchical clustering (HC) and K-Means Clustering. Finally, an optimal number of 24 micro-zones is established that reflect a comprehensive precipitation map over the country, employing PCA, Hierarchical clustering, and K-Means Clustering. The annual hyetograph of each zone showed a unique pattern and distribution with a varying magnitude of monthly precipitation compared to others. The long-term (i.e., 33-years) mean annual rainfall in each region and zone is calculated, and the monthly and annual-precipitation water availability in the country is estimated. The result gives an accurate insight into the amount of precipitation that is expected to fall in each zone during each month of the year, that may be used as the reference for the prediction of the dry and wet seasons and years and also for the allocation of the harvested precipitation water to different consumptive sectors. The result shows that the Hierarchical clustering and PCA have significant classification performance in meso and micro- climatological zoning. Also, it was observed that there are significant similarities between the PCA and Hierarchical clustering (Ward’s method-Pearson correlation) results in micro-climatological zoning.
Diagnostic Performance of Deep LearnIng AlgoriThm for Analysis of Computed Tomography Myocardial PerfusION
Authors: Muscogiuri Giuseppe , Chiesa Mattia , Baggiano Andrea , Spadafora Pierino , De Santis Rossella , Guglielmo Marco , Scafuri Stefano , Fusini Laura , Mushtaq Saima , Conte Edoardo , Annoni Andrea , Formenti Alberto , Mancini Maria Elisabetta , Ricci Francesca , Ariano Francesco Paolo , Spiritigliozzi Luigi , Babbaro Mario , Mollace Rocco , Maragna Riccardo , Giacari Carlo Maria , Andreini Daniele , Guaricci Andrea Igoren , Colombo Gualtiero I. , Rabbat Mark G. , Pepi Mauro , Sardanelli Francesco , Pontone Gianluca 
Published: November 2021

Abstract
Purpose: Artificial intelligence could play a key role in cardiac imaging analysis. To evaluate the diagnostic accuracy of a deep learning (DL) algorithm predicting hemodynamically significant coronary artery disease (CAD) by using a rest dataset of myocardial computed tomography perfusion (CTP) as compared to invasive evaluation. Methods: One hundred and twelve consecutive symptomatic patients scheduled for clinically indicated invasive coronary angiography (ICA) underwent CCTA plus static stress CTP and ICA with invasive fractional flow reserve (FFR) for stenoses ranging between 30% and 80%. Subsequently, a DL algorithm for the prediction of significant CAD by using the rest dataset (CTP-DLrest) and stress dataset (CTP-DLstress) was developed. The diagnostic accuracy for identification of significant CAD using CCTA, CCTA+CTPStress, CCTA+CTP-DLrest, and CCTA+CTP-DLstress were measured and compared. The time of analysis for CTPStress, CTP-DLrest and CTP-DLStress were recorded. Results: Patient-specific sensitivity, specificity, NPV, PPV, accuracy and area under the curve (AUC) of CCTA alone and CCTA+CTPStress were 100%, 33%, 100%, 54%, 63%, 67% and 86%, 89%, 89%, 86%, 88%, 87%, respectively. Patient-specific sensitivity, specificity, NPV, PPV, accuracy and AUC of CCTA+DLrest and CCTA+DLstress were 100%, 72%, 100%, 74%, 84%, 96% and 93%, 83%, 94%, 81%,88%,98%, respectively. All CCTA+CTPStress, CCTA+CTP-DLRest and CCTA+CTP-DLStress significantly improved detection of hemodynamically significant CAD (p<0.01).Time of CTP-DL was significantly lower as compared to human analysis (39.2±3.2 vs. 379.6±68.0 seconds, p<0.001).Conclusion: Evaluation of myocardial ischemia using a DL approach on rest CTP datasets is feasible and accurate. This approach may be a useful gatekeeper prior to CTPStress.
The K Nearest Neighbor Algorithm for Imputation of Missing Longitudinal Prenatal Alcohol Data
Authors: Sania Ayesha , Pini Nicolò , Nelson Morgan E. , Myers Michael M. , Shuffrey Lauren C. , Lucchini Maristella , Elliott Amy J. , Odendaal Hein J. , Fifer William P. 
Published: November 2021

Abstract
Background — Missing data are a source of bias in epidemiologic studies. This is problematic in alcohol research where data missingness is linked to drinking behavior. Methods — The Safe Passage study was a prospective investigation of prenatal drinking and fetal/infant outcomes (n=11,083). Daily alcohol consumption for last reported drinking day and 30 days prior was recorded using Timeline Follow-back method. Of 3.2 million person-days, data were missing for 0.36 million. We imputed missing data using a machine learning algorithm; “k-Nearest Neighbor” (k-NN). k-NN imputes missing values for a participant using data of participants closest to it. Imputed values were weighted for the distances from nearest neighbors and matched for day of week. Validation was done on 500 iterations after randomly deleting data for 5-15 consecutive days. Results — Data from 5 nearest neighbors and segments of 55 days provided imputed values with least imputation error. After deleting data segments from with no missing days from first trimester, there was no difference between actual and predicted values for 64% of deleted segments. For 31% of the segments, imputed data were within +/-1 drink/day of the actual. Conclusions — k-NN can be used to impute missing data from longitudinal studies of alcohol during pregnancy with high accuracy.
Metadichol®, a Novel Nano Lipid Formulation that Inhibits SARS-COV-2 and a Multitude of Pathological Viruses in vitro
Authors: Raghavan Palayakotai 
Published: November 2021

Abstract

Increasing outbreaks of new pathogenic viruses have promoted the exploration of novel alternatives to time-consuming vaccines. Thus, it is necessary to develop a universal approach to halt the spread of new and unknown viruses as they are discovered. One such promising approach is to target lipid membranes, which are common to all viruses and bacteria. The ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has reaffirmed the importance of interactions between the virus envelope and the host cell plasma membrane as a critical mechanism of infection. Metadichol®, a nano lipid emulsion of long chain alcohols, has been demonstrated as a strong candidate that inhibits the proliferation of SARS-CoV-2. Naturally derived substances, such as long-chain saturated lipid alcohols, reduce viral infectivity, including that of coronaviruses (such as SARS-CoV-2) by modifying their lipid-dependent attachment mechanism to human host cells. The receptor ACE2 mediates the entry of SARS-CoV-2 into the host cells, whereas the serine protease TMPRSS2 primes the viral S protein. In this study, Metadichol® was found to be 270 times more potent an inhibitor of TMPRSS2 (EC50 = 96 ng/ml) than Camostat mesylate (EC50 = 26000 ng/mL). Additionally, it inhibits ACE with an EC50 of 71 ng/mL, but very weak inhibitor of ACE2 at an EC50 of 31 µg/ml. Furthermore, the live viral assay performed in Caco-2 cells revealed that Metadichol® inhibits SARS-CoV-2 replication at an EC90 of 0.16 µg/ml. Moreover, Metadichol® had an EC90 of 0.00037 µM, making it 2081 and 3371 times more potent than Remdesivir (EC50 = 0.77 µM) and chloroquine (EC50 = 1.14 µM), respectively.
Universe: the dynamics of the minimum and maximum expansion states
Authors: Petrakis Sócrates 
Published: November 2021

Abstract
Two hypotheses stand out in describing the evolution of the Universe. The predominant one predicts that the current expansion began at a certain instant and will not preserve any variation of energy that performs work; apparent flat Universe (Ω = 1) is advocated by relativistic calculations and observational data, with an end or thermal death at its maximum expansion (3D Space). The other hypothesis considers that the Universe is cyclical (always alternating phases of expansion and contraction). This proposal aims to demonstrate that both hypotheses can be correct by not being distinct, but complementary. Supported by the immutability of physical laws, analyses of concepts such as space, mass, energy, gravity, spin, and entropy define an exclusive presence of 1D Space in the minimum and maximum expansion states of the Universe. With our 3D Space Universe created and existing between these extreme states, every dynamic is outlined and completes the usual relativity. The concept of complete rest energy (1D Space) was able to be applied, demonstrating that the complete evolution of the Universe is spatially dynamic in a perpetual time dimension, always recreating our Universe.
A Linear Dynamical Perspective on Epidemiology: Interplay Between Early COVID-19 Outbreak and Human Mobility
Authors: Mustavee Shakib , Agarwal Shaurya , Das Suddhasattwa , Enyioha Chinwendu 
Published: November 2021

Abstract
This paper investigates the impact of human activity and mobility (HAM) in the spreading dynamics of an epidemic. Specifically, it explores the interconnections between HAM and its effect on the early spread of the COVID-19 virus. During the early stages of the pandemic, effective reproduction numbers exhibited a high correlation with human mobility patterns, leading to a hypothesis that the HAM system can be studied as a coupled system with disease spread dynamics. This study applies the generalized Koopman framework with control inputs to determine the nonlinear disease spread dynamics and the input-output characteristics as a locally linear controlled dynamical system. The approach solely relies on the snapshots of spatiotemporal data and does not require any knowledge of the system’s physical laws. We exploit the Koopman operator framework by utilizing the Hankel Dynamic Mode Decomposition with Control (HDMDc) algorithm to obtain a linear disease spread model incorporating human mobility as a control input. The study demonstrated that the proposed methodology could capture the impact of local mobility on the early dynamics of the ongoing global pandemic. The obtained locally linear model can accurately forecast the number of new infections for various prediction windows ranging from two to four weeks. The study corroborates a leader-follower relationship between mobility and disease spread dynam-
Collectivism in a Replication Network of Minimal Nucleobase Sequences
Authors: Vela-Gallego Sonia , Pardo-Botero Zulay , Moya-Álamo Cristian , Escosura Andrés de la 
Published: November 2021

Abstract
A major challenge for understanding the origins of life is to explore how replication networks can engage in an evolutionary process. Herein, we shed light on this problem by implementing a network constituted by two different types of extremely simple biological components: the amino acid cysteine and the canonical nucleobases adenine and thymine, connected through amide bonds to the cysteine amino group and oxidation of its thiol into three possible disulfides. Supramolecular and kinetic analyses revealed that both self- and mutual interactions between such dinucleobase compounds drive their assembly and replication pathways. Those pathways involving sequence complementarity led to enhanced replication rates, suggesting a potential bias for selection. The interplay of synergistic dynamics and competition between replicators was then simulated in an open reactor with experimental kinetic data, showing the selective amplification of different species depending on the initial mixture composition. Overall, this network configuration can favor a collective adaptability to changes in the availability of feedstock molecules, with disulfide exchange reactions serving as 'wires' that connect the different individual auto- and cross-catalytic pathways.
Metformin Intake Suppresses The Degree of Liver Metastasis From Colorectal Cancer In Diabetic Patients But Does Not Improve Their Prognosis
Authors: Saito Akira , Kitayama Joji , Horie Hisanaga , Koinuma Koji , Ohzawa Hideyuki , Yamaguchi Hironori , Kawahira Hiroshi , Mimura Toshiki , Lefor Alan Kawarai , Sata Naohiro 
Published: November 2021

Abstract
Background: Metformin reduces the risk of, and mortality from, colorectal cancer in patients with diabetes mellitus. However, the effect of metformin on patients with stage IV disease is unknown. In the present study we reviewed the clinical features and outcomes of patients with diabetes mellitus and stage IV colorectal cancer (M1, liver metastases) treated with or without metformin.Methods: The 202 patients with colorectal cancer and macroscopic liver metastasis who were treated in the Department of Surgery or Department of Clinical Oncology at Jichi Medical University Hospital from January 2006 through June 2019 were surveyed treatment of diabetes, clinical and pathological factor and prognosis of these patients. Results: We retrospectively examined the effect of metformin use on outcomes in 32 patients with liver metastases from colorectal cancer. Hepatic metastases were stage H1 in 8/8 patients taking metformin and stage H2-3 in 17/24 non-users. Of 22 patients who underwent colectomy, colorectal tumors were pT4 in 5 metformin users, and pT2-3 in 10/17 non-users. The mean survival of metformin users and non-users was equal (28.0 mo vs 29.3 mo, p>.05). No significant difference was detected when survival was compared between 6 metformin users and 19 non-users who received systemic chemotherapy. Conclusion: These results suggest that metformin has less potent anti-tumor effects in patients with advanced stage disease. Metformin for the treatment of patients with metastatic colorectal cancer requires further study.
The Impact of Exogenous Tetrodotoxin on the piRNAs and mRNAs Profiles of Gonads in Pufferfish Takifugu Flavidus
Authors: He Xue , Wu Hexing , Ye Yaping , Gong Xiaolin , Bao Baolong 
Published: November 2021

Abstract
Tetrodotoxin (TTX) is a deadly neurotoxin and usually accumulates in large amounts in the ovaries but is non-toxic or low toxic in the testis of pufferfish. The molecular mechanism underlying sexual dimorphism of TTX accumulation in gonads is complex and unclear. Piwi/piRNA complexes are essential for germline specification, gametogenesis, and gonadal development, they also demonstrate sexual dimorphism in teleosts. Hence, the present study investigated the expression of piRNAs and mRNAs by transcriptomics in cultured pufferfish Takifugu flavidus after intramuscular administration of exogenous TTX. The results showed 80 piRNAs were down-regulated and 223 genes were up-regulated in the ovary after TTX administration. By contrast, 286 piRNAs were down-regulated and 445 genes were up-regulated after TTX administration in testis. Functional and pathway analyses indicated that the TTX up-regulated genes were enriched in the Wnt, ErbB and GnRH signaling pathways in ovary, while were enriched in the oocyte meiosis, estrogenesis biosynthesis and cell apoptosis-related pathways in testis. Interestingly, these genes were also the potential target genes of TTX downregulated piRNAs. Amhr2 and cyp19a were also identified as sex-related genes, involved in TTX administration. These results showed a certain level of consistency with the enrichment pathway analysis, which indicated that the TTX could affect the expression of sex-related genes, and work as an inhibitor for the testicular meiosis, but as a promoting factor for ovary development through piRNAs in pufferfish. In addition, TUNEL staining showed that significant apoptosis was detected in the TTX treated testis, and the role of the cell apoptotic pathway was further confirmed. Overall, this research will contribute to an understanding of the piwi function in TTX sexual dimorphism accumulation in pufferfish and provide a basis for further studies.
Time to First Optimal Glycemic Control and its Predictors Among Type 1 Diabetic Children&lt;15 Years in Bahir Dar City Public Referral Hospitals, North West Ethiopia: A Retrospective Follow Up Study
Authors: Meseret Fentahun , Belachew Amare , Tesfa Getasew , Mengesh Teshale , Embiale Tsegasew , Alemu Ayichew , Dagne Melsew 
Published: November 2021

Abstract
Background: Recognizing the level of glycemic control of a client is an important predictor of the development of complication and risk of death from diabetes. However, the other most important predictor which is the time that the patient stayed in that poor glycemic level before reaching optimal glycemic control has not been studied so far. Objective: The aim of this study was to estimate time to first optimal glycemic control and identify predictors among type 1 diabetic children<15 years in Bahir Dar city public referral hospitals, Northwest, Ethiopia, 2021Methods: Retrospective cohort study was conducted at Bahir Dar city public referral hospitals among randomly selected sample of 385 patients with type 1 diabetes who were on follow up from January1, 2016 to February30, 2021.Data were collected by using data abstraction tool and then entered into Epi-data version 4.2 and exported into STATA 14.0 statistical software. Descriptive statistics, Kaplan Meier plots and median survival times, Log-rank test and Cox-proportional hazard regression were used for analysis. After performing Cox-proportional hazard regression, model goodness-of-fit and assumptions were checked. Finally, association between independent variables and time to first optimal glycemic control in months were assessed using multivariable Cox Proportional Hazard model and Variables with p-value < 0.05 were considered as statistically significant.Result: Median survival time to first optimal glycemic control among type 1 diabetic client was 8 months (95%CI: 6.9-8.9).First optimal glycemic achievement rate was 8.2(95%CI: 7.2-9.2) per 100 person/month observation. Factors that affect time to first optimal glycemic control were age (AHR=0.32;95%CI=0.19-0.55),weight(AHR=0.96;95%CI=0.94-0.99),primary care giver(AHR=2.09;95%CI=1.39-3.13), insulin dose (AHR=1.05;95%CI=1.03-1.08),duration of diabetes (AHR=0.64;95%CI=0.44-0.94), adherence (AHR=9.72;95%CI=6.09-15.51),carbohydrate counting(AHR=2.43;95%CI=1.12-5.26),and comorbidity (AHR=0.72;95%CI=0.53-0.98).Conclusion and Recommendation: The median survival time to first optimal glycemic control in this study was long. Age, weight, primary care giver, insulin dose, duration of diabetes, adherence, and carbohydrate counting including history of comorbidity were determinant factors. Therefore, clinicians should advice weight reduction, increase the dose of insulin during initial treatment, counsel their parents about adherence of insulin drug and auditing their children diet as prescription helps to reduce the length of glycemic control.