Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrating Expression Data-Based Deep Neural Network Models with Biological Networks to Identify Regulatory Modules for Lung Adenocarcinoma

Simple Summary The growing evidence suggested that competing endogenous RNAs (ceRNAs) have significant associations with tumor occurrence and progression, yet the regulatory mechanism of them in lung adenocarcinoma remains unclear. Identification of the regulatory modules for lung adenocarcinoma is a critical and fundamental step towards understanding the regulatory mechanisms during carcinogenesis. Deep neural network (DNN) models have become a powerful tool to intelligently recognize the sophisticated relationships of ceRNAs appropriately. In this paper, multiple deep neural network models were constructed using the expression data to identify regulatory modules for lung adenocarcinoma in biological networks. Three identified regulatory modules association with lung adenocarcinoma were validated from three aspects, i.e., literature review, functional enrichment analysis, and an independent dataset. The regulatory relationships between RNAs were validated in various datasets, including CPTAC, TCGA and an expression profile from the GEO database. Our study will contribute to improving the understanding of regulatory mechanisms in the carcinogenesis of lung adenocarcinoma and provide schemes for identifying novel regulatory modules of other cancers. Abstract Lung adenocarcinoma is the most common type of primary lung cancer, but the regulatory mechanisms during carcinogenesis remain unclear. The identification of regulatory modules for lung adenocarcinoma has become one of the hotspots of bioinformatics. In this paper, multiple deep neural network (DNN) models were constructed using the expression data to identify regulatory modules for lung adenocarcinoma in biological networks. First, the mRNAs, lncRNAs and miRNAs with significant differences in the expression levels between tumor and non-tumor tissues were obtained. MRNA DNN models were established and optimized to mine candidate mRNAs that significantly contributed to the DNN models and were in the center of an interaction network. Another DNN model was then constructed and potential ceRNAs were screened out based on the contribution of each RNA to the model. Finally, three modules comprised of miRNAs and their regulated mRNAs and lncRNAs with the same regulation direction were identified as regulatory modules that regulated the initiation of lung adenocarcinoma through ceRNAs relationships. They were validated by literature and functional enrichment analysis. The effectiveness of these regulatory modules was evaluated in an independent lung adenocarcinoma dataset. Regulatory modules for lung adenocarcinoma identified in this study provided a reference for regulatory mechanisms during carcinogenesis.
Three-Dimensional Local MHD Simulations of High States and Low States in Magnetic Accretion Disks

Black hole candidates sometimes show a transition between the high (or soft) state and the low (or hard) state. In the low state, low frequency time variations are much larger than the high state. A possible mechanism of the large-amplitude, sporadic time variabilities in the low-state is the magnetic energy release in low-β (β = P gas /P mag < 1) disks (Mineshige, Kusunose & Matsumoto 1995). It had been thought that low-β disks cannot exist because buoyant escape of magnetic flux due to the Parker instability may set the lower limit for β inside the disk. Shibata, Tajima & Matsumoto (1990), however, pointed out that in accretion disks, once a low-β disk is formed, it can stay in low-β state partly because the growth rate of the Parker instability decreases when β < 1. They suggested that magnetic accretion disks fall into two types; high-β disks and low-β disks.
Inspiral-Merger-Ringdown Models for Spinning Black-Hole Binaries at the Interface between Analytical and Numerical Relativity

Title of dissertation: INSPIRAL-MERGER-RINGDOWN MODELS FOR SPINNING BLACK-HOLE BINARIES AT THE INTERFACE BETWEEN ANALYTICAL AND NUMERICAL RELATIVITY Andrea Taracchini, Doctor of Philosophy, 2014 Dissertation directed by: Professor Alessandra Buonanno Department of Physics The long-sought direct detection of gravitational waves may only be a few years away, as a new generation of interferometric experiments of unprecedented sensitivity will start operating in 2015. These experiments will look for gravitational waves with frequencies from 10 to about 1000 Hz, thus targeting astrophysical sources such as coalescing binaries of compact objects, core collapse supernovae, and spinning neutron stars, among others. The search strategy for gravitational waves emitted by compact-object binaries consists in filtering the output of the detectors with template waveforms that describe plausible signals, as predicted by general relativity, in order to increase the signal-to-noise ratio. In this work, we modeled these systems through the effective-one-body approach to the general-relativistic 2-body problem. This formalism rests on the idea that binary coalescence is universal across different mass ratios, from the testparticle limit to the equal-mass regime. It bridges the gap between post-Newtonian theory (valid in the slow-motion, weak-field limit) and black-hole perturbation theory (valid in the small mass-ratio limit, but not limited to slow motion). The project unfolded along two main avenues of inquiry, with the goal of developing faithful inspiral-merger-ringdown waveforms for generic spinning, stellar-mass blackhole binaries. On the one hand, we studied the motion and gravitational radiation of test masses orbiting Kerr black holes in perturbation theory, with the goal of extracting strong-field information that can be incorporated into effective-one-body models. On the other hand, we worked at the interface between analytical and numerical relativity by calibrating effective-one-body models against numerical solutions of Einstein’s equations, and testing their accuracy when extrapolated to different regions of the parameter space. In the course of this project, we also studied conservative effects of the 2-body dynamics, namely the periastron advance, and devised algorithms for generating realistic initial conditions for spinning, precessing black-hole binaries. The waveform models developed in this project will be employed in dataanalysis pipelines and gravitational-wave searches of advanced LIGO and Virgo. In the near future, natural extensions of this work will be the inclusion of tidal effects in the comparable-mass regime (relevant for neutron-star/black-hole binaries), and spin precession in the test-particle limit. INSPIRAL-MERGER-RINGDOWN MODELS FOR SPINNING BLACK-HOLE BINARIES AT THE INTERFACE BETWEEN ANALYTICAL AND NUMERICAL RELATIVITY
KIFC1: A Reliable Prognostic Biomarker in Rb-positive Triple-negative Breast Cancer Patients Treated With Doxorubicin in Combination With Abemaciclib.

BACKGROUND/AIM Triple-negative breast cancer (TNBC) prevalence and risk of relapse are greatest in African American (AA) patients. Doxorubicin (DOX) and abemaciclib (ABE) synergism in Rb-positive TNBC cells (MDA-MB-231), and antagonism in Rb-negative TNBC cells (MDA-MB-468) have been previously shown. Here, we assessed Kinesin-like protein 1 (KIFC1) as an ethnic-specific prognostic biomarker of the DOX+ABE combination for the Rb-status in TNBC. MATERIALS AND METHODS Literature search for TNBC prognostic biomarkers in the AA population was conducted. MDA-MB-231 and MDA-MB-468 cells were exposed over 72 h to four treatment arms: 1) control (medium without drug), 2) DOX at 50% inhibitory concentration in MDA-MB-231 (0.565 μM) and MDA-MB-468 (0.121 μM), 3) ABE alone (2 μM), and 4) DOX+ABE combination at their corresponding concentrations in each cell-line. KIFC1 protein expression and temporal changes were quantified in MDA-MB-231 cells using western blot. RESULTS KIFC1, Kaiso, and Annexin A2 are literature-identified AA-specific TNBC prognostic biomarkers. KIFC1 was found to be uncorrelated to other proposed biomarkers, suggesting it may predict risk independently of other TNBC biomarkers. In both cell lines, DOX alone did not significantly change KIFC1 expression relative to control. Conversely, ABE reduced KIFC1 expression in MDA-MB-231 but not in MDA-MB-468 cells. The combination DOX+ABE resulted in a greatest reduction in KIFC1 in MDA-MB-231 cells with a more rapid time-to-full inhibition of KIFC1 compared to ABE alone. CONCLUSION Change in KIFC1 expression is primarily driven by ABE in Rb-positive TNBC cells. DOX increases ABE speed to achieve a full inhibition of KIFC1 in Rb-positive, yet, without influencing its expression in Rb-negative TNBC cells.
Miramides A–D: Identification of Detoxin-like Depsipeptides after Heterologous Expression of a Hybrid NRPS-PKS Gene Cluster from Streptomyces mirabilis Lu17588

Natural products derived from plants, fungi or bacteria have been used for years in the medicine, agriculture and food industries as they exhibit a variety of beneficial properties, such as antibiotic, antifungal, anticancer, herbicidal and immunosuppressive activities. Compared to synthetic compounds, natural products possess a greater chemical diversity, which is a reason why they are profitable templates for developing pharmaceutical drug candidates and ongoing research on them is inevitable. Performing heterologous expression with unknown gene clusters is the preferred method to activate gene clusters that are not expressed in the wild-type strain under laboratory conditions; thus, this method offers a way to discover new interesting metabolites. Here, we report the gene cluster assembly of a hybrid NRPS-PKS gene cluster from Streptomyces mirabilis Lu17588, which was heterologously expressed in Streptomyces albus Del14. Four new compounds were produced by the obtained strain, which were named miramides A–D. Isolation and structure elucidation revealed similarity of the isolated compounds to the known depsipeptides rimosamides/detoxins.
Final Height in GnRH Analogue Treatment in Girls Diagnosed with Early Puberty: Comparison with Untreated Controls

Introduction: In this retrospective study, it was aimed to examine the effect of gonadotropin-releasing hormone (GnRH) analogue treatment on final height in girls diagnosed with early puberty (EP) between the ages of 8 and 10. Materials and Methods: In the study, 87 girls who were diagnosed with EP and reached the final height were included. Two groups, those who received GnRH analogue treatment and those who did not, were formed. The average age, bone age, average height, height standard deviation score (SDS), body mass index SDS, target height, predicted adult height of the groups at the time of admission were calculated. The final height they reached and their menarche ages were noted. Results: No difference was found between the groups in terms of average age, average height, height SDS, bone age, body mass index SDS at the time of admission. The target height, predicted adult height, final height and the SDS of these were similar in both groups. All cases in both groups reached the target height. Conclusion: It was determined that the GnRH analogue treatment did not make a positive contribution to the final height in the EP group,
Prevalence, Clinical Pattern and Presentations of Psoriasis in A Tertiary Care Hospital of Bangladesh

To find out different presentations of Psoriasis in Bangladesh. Material and Methods: This is a cross sectional study of all dermatology patients with features of psoriasis who attended the dermatology outpatient clinic of the hospital between July 2016 and June 2017. Data was collected on a perform questionnaire. Age, gender and clinical presentations were recorded and analyzed using SPSS version 16. Results: Psoriasis was found in 1.13% (60/5505) of the study population. There was a male preponderance with a male to female ratio of 1.34:1. The majority of patients seen were in the fourth decade of life. Stress, alcohol, and drugs were the most reported predisposing factors to psoriasis. All types of psoriasis were found, and plaque psoriasis was the most common. Conclusion: Psoriasis is a one of the common skin diseases with wide range of clinical variation and predisposing factors. The current trend in the management of psoriasis is focused on treating the inflammatory process as well as managing the modifiable environmental triggers. Central Medical College Journal Vol 5 No 2 Jul 2021 PP 102-105
LMI-based impedance control synthesis: a case study on fixed-stiffness actuators (FSAs)

Impedance control is frequency-dependent in the twofold sense: (1) the impedance matching error can only be attenuated arbitrarily small over a low-frequency range due to the water bed effect (Freudenberg et al., 2003), and (2) the impedance matching error always diverges to infinity as the frequency tends to infinity since no causal controller can track arbitrarily fast signals. To sum up, we can only shape the robot impedance over some low-frequency range which may be very small due to the limitation resulting from the robot's inherent high-frequency characteristics. Unfortunately, this fact was underestimated in the existing impedance control schemes. In this paper, a frequency-aware linear impedance control synthesis technique is developed for FSAs based on control theory, which is also suitable for the general robot system in the condition that the robot dynamics is linearised around an equilibrium configuration or compensated with its inverse dynamics model to form an exact-linearised system a priori. With the powerful tool, we study the impedance shaping technique and address the two long-standing issues: (1) Under what conditions, an impedance-controlled FSA can exceed its physical stiffness? (2) Can a stiff FSA render a wider stiffness range than its softer counterparts?
Synthetic gRNA/Cas9 Ribonucleoprotein Inhibits HIV Reactivation and Replication

The current antiretroviral therapy (ART) for human immunodeficiency virus (HIV) can halt viral replication but cannot eradicate HIV infection because proviral DNA integrated into the host genome remains genetically silent in reservoir cells and is replication-competent upon interruption or cessation of ART. CRISPR/Cas9-based technology is widely used to edit target genes via mutagenesis (i.e., nucleotide insertion/deletion and/or substitution) and thus can inactivate integrated proviral DNA. However, CRISPR/Cas9 delivery systems often require viral vectors, which pose safety concerns for therapeutic applications in humans. In this study, we used synthetic guide RNA (gRNA)/Cas9-ribonucleoprotein (RNP) as a non-viral formulation to develop a novel HIV gene therapy. We designed a series of gRNAs targeting different HIV genes crucial for HIV replication and tested their antiviral efficacy and cellular cytotoxicity in lymphoid and monocytic latent HIV cell lines. Compared with the scramble gRNA control, HIV-gRNA/Cas9 RNP-treated cells exhibited efficient viral suppression with no apparent cytotoxicity, as evidenced by the significant inhibition of latent HIV DNA reactivation and RNA replication. Moreover, HIV-gRNA/Cas9 RNP inhibited p24 antigen expression, suppressed infectious viral particle production, and generated specific DNA cleavages in the targeted HIV genes that are confirmed by DNA sequencing. Because of its rapid DNA cleavage, low off-target effects, low risk of insertional mutagenesis, easy production, and readiness for use in clinical application, this study provides a proof-of-concept that synthetic gRNA/Cas9 RNP drugs can be utilized as a novel therapeutic approach for HIV eradication.
Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions

Endoscopic ultrasonography (EUS) is the most accurate imaging modality for the evaluation of different types of pancreatic cystic lesions. Our aim was to analyze EUS images of pancreatic cystic lesions using an image processing software. We specified the echogenicity of the lesions by measuring the gray value of pixels inside the selected areas. The images were divided into groups (serous cystic neoplasm /SCN/, intraductal papillary mucinous neoplasms and mucinous cystic neoplasms /Non-SCN/ and Pseudocyst) according to the pathology results of the lesions. Overall, 170 images were processed by the software: 81 in Non-SCN, 30 in SCN and 59 in Pseudocyst group. The mean gray value of the entire lesion in the Non-SCN group was significantly higher than in the SCN group (27.8 vs. 18.8; p < 0.0005). The area ratio in the SCN, Non-SCN and Pseudocyst groups was 57%, 39% and 61%, respectively; significantly lower in the Non-SCN group than in the SCN or Pseudocyst groups (p < 0.0005 and p < 0.0005, respectively). The lesion density was also significantly higher in the Non-SCN group compared to the SCN or Pseudocyst groups (4186.6/mm2 vs. 2833.8/mm2 vs. 2981.6/mm2; p < 0.0005 and p < 0.0005, respectively). The EUS image analysis process may have the potential to be a diagnostic tool for the evaluation and differentiation of pancreatic cystic lesions.
GENERALIZED METHODS FOR RESTRICTED MARKOV-SWITCHING MODELS WITH INDEPENDENT STATE VARIABLES

We generalize the existing Bayesian method for estimating Markov-switching models by allowing for independent Markov processes and various restrictions on transition matrices. This generalized method is used to develop tools for estimating both identified and reduced-form multivariate dynamic models. Moreover, we develop (1) an efficient block-wise optimization algorithm for obtaining the maximum likelihood or posterior es- timates, (2) a new modified harmonic means method to deal with the common situation in which the likelihood is zero and a Gaussian approximation is inadequate, and (3) an es- timation method for Markov-switching VARs with restrictions on both time variation and the lag structure.
Human Adipose-Derived Stromal Cells Delivered on Decellularized Muscle Improve Muscle Regeneration and Regulate RAGE and P38 MAPK

Volumetric muscle loss (VML) is the acute loss of muscle mass due to trauma. Such injuries occur primarily in the extremities and are debilitating, as there is no clinical treatment to restore muscle function. Pro-inflammatory advanced glycation end-products (AGEs) and the soluble receptor for advanced glycation end-products (RAGE) are known to increase in acute trauma patient’s serum and are correlated with increased injury severity. However, it is unclear whether AGEs and RAGE increase in muscle post-trauma. To test this, we used decellularized muscle matrix (DMM), a pro-myogenic, non-immunogenic extracellular matrix biomaterial derived from skeletal muscle. We delivered adipose-derived stromal cells (ASCs) and primary myoblasts to support myogenesis and immunomodulation (N = 8 rats/group). DMM non-seeded and seeded grafts were compared to empty defect and sham controls. Then, 56 days after surgery muscle force was assessed, histology characterized, and protein levels for AGEs, RAGE, p38 MAPK, and myosin heavy chains were measured. Overall, our data showed improved muscle regeneration in ASC-treated injury sites and a regulation of RAGE and p38 MAPK signaling, while myoblast-treated injuries resulted in minor improvements. Taken together, these results suggested that ASCs combined with DMM provides a pro-myogenic microenvironment with immunomodulatory capabilities and indicates further exploration of RAGE signaling in VML.
Multisource Heterogeneous Data-Based Behavior Excavation of Investors and Financial Risk Prediction

The investment decision-making behavior of investors refers to the capital purchase behavior of investors in order to achieve a certain purpose or goal. As an individual decision-maker, investors will be affected by various factors when making investment decisions, and the influencing factors may be caused by the outside or generated by themselves. The focus of this paper is to analyze the impact of investors’ past returns on investors’ decision-making based on multisource heterogeneous data. Multisource heterogeneous data can show the results of investors’ behavior evaluation at multiscale and multilevel. Using conceptual deduction and empirical research methods, based on the analysis of investors’ behavior, the financial risk prediction results are proposed. Financial risk prediction mainly analyzes the impact of investment returns on investors’ decision-making from two aspects: individual returns and overall returns. The measurement indicators of investment decisions use investors’ transaction frequency and asset size.
Bacterial Contamination Level of Indoor Air and Surface of Equipment in the Operation Room in Dil-Chora Referral Hospital, Dire Dawa, Eastern Ethiopia

Purpose This study investigated the bacterial contamination level of the indoor air and surface of the operation room, surgical, and gynecology wards of Dilchora Referral hospitals between January and August 2020. Methods A laboratory based cross-sectional study was carried out on the OR and wards of Dilchora referral hospital in Eastern Ethiopia. A passive air sampling method was used to collect 128 indoor air samples; the bacterial load was enumerated and the result was expressed as colony forming units (CFU/m3). Additional qualitative analysis was carried out to identify particular bacterial species that were isolated from the indoor air and swabs taken from the surface of the equipment using conventional techniques. All laboratory data were entered and analyzed using MS Excel 2007 and SPSS version 20. Results The mean bacterial counts of 94.63 CFU/dm/hr in major OR during active time as well as 509.75 and 509.38 CFU/dm/hr in male and female clothing rooms during the afternoon were unacceptable (>450 CFU/dm2). Similarly, 43.75% of the bacterial counts found in the afternoon samples fell short of Fisher’s criterion. The difference between the bacterial counts recorded in the morning and afternoon was significant (p=0.000). A total of 54 (42.2%) indoor air samples and 28 (93.3%) cotton swabs were positive for bacterial growth, with S. aureus (51.04%) and Bacillus sp (55%) being the dominant bacteria isolated from indoor air and the surface of equipment, respectively. Conclusion The bacterial load of investigated wards is considerably “high” to “very high”, which implies a significant risk of hospital acquired infections. Therefore, devising effective control strategies targeted on surface cleansing and sterilizing of the air environment and practicing periodic microbial surveillance of the hospital environment is a paramant.
Field-driven hysteretic and reversible resistive switch at the Ag–Pr0.7Ca0.3MnO3 interface

The hysteretic and reversible polarity-dependent resistive switch driven by electric pulses is studied in both Ag/Pr0.7Ca0. 3MnO3/YBa2Cu3O7 sandwiches and single-layer Pr0.7Ca0. 3MnO3 strips. The data demonstrate that the switch takes place at the Ag–Pr0.7Ca0. 3MnO3 interface. A model, which describes the data well, is proposed. We further suggest that electrochemical migration is the cause for the switch.
Applying Block Bootstrap Methods in Silver Prices Forecasting

Abstract This article focuses on the presentation of the forecasting possibilities of bootstrap methods used to predict prices based on time series. The aim of the paper was to examine the quality of the forecasts made with the methods for silver futures contracts. In order to achieve the intended goal, ex-post and ex-ante errors for the forecasts prepared by applying bootstrap methods were analysed. The forecasts were calculated using the daily closing prices of the silver futures contracts for the period from 01/07/2020 to 27/03/2022 The analysis showed that the quality of forecasts for each of the presented methods is at a satisfactory level. Moreover, the forecasts calculated using the bootstrap methods were closer to the real performance of the silver futures contracts than the forecasts obtained using the ARMA model (1,1). In addition, it was shown that the forecasts made with the tapered block bootstrap method are less affected by forecast errors than the other analysed methods.