Miracle-dz/UniFAR-FTUs huggingface dataset:
A semi-parametric approach for time-dependent ROC curves with nonignorable missing biomarker

ABSTRACT The main purpose of this paper is to survey the statistical inference for covariate-specific time-dependent receiver operating characteristic (ROC) curves with nonignorable missing continuous biomarker values. To construct time-dependent ROC curves, we consider a joint model which assumes that the failure time depends on the continuous biomarker and the covariates through a Cox proportional hazards model and that the continuous biomarker depends on the covariates through a semiparametric location model. Assuming a purely parametric model on the propensity score, we utilize instrumental variables to deal with the identifiable issue and estimate the unknown parameters of the propensity score by a simple and efficient method. In addition, when the propensity score is estimated, we develop HT and AIPW approaches to estimate our interested quantities. In the presence of nonignorable missing biomarker, our AIPW estimators of the interested quantities are still doubly robust when the true propensity score is a special parametric logistic model. At last, simulation studies are conducted to assess the performance of our proposed approaches, and a real data analysis is also carried out to illustrate its application.
The Presence of Diffuse Interstellar Bands in the Spectra of Cool Stars

Data from the Kitt Peak National Observatory (KPNO) coudé feed telescope were used to analyze the strength of three well-known diffuse interstellar bands (DIBs; 5780, 5797, and 6614 Å). Ten mid-A, mid-F, and mid-G stars with moderate reddening (EB-V = 0.2-1.2) were observed, along with one reddened B0 dwarf for comparison. Synthetic spectra were calculated to remove the interference of stellar features. We report the detection of all three DIBs in A, F, and G stars. We also find the correlation of DIB strengths with E(B-V), in our sight lines, to be consistent with previous results from Herbig (1993), demonstrating that DIB strength is not dependent on the spectral type of the target star.
Comparative Analysis of Transcriptomic Response of Escherichia coli K-12 MG1655 to Nine Representative Classes of Antibiotics

Antibiotics are among the most important inventions in the history of humankind. They are the ultimate reason why bacterial infections are no longer the number one threat to people’s lives. ABSTRACT The use of antibiotics leads to strong stresses to bacteria, leading to profound impact on cellular physiology. Elucidating how bacteria respond to antibiotic stresses not only helps us to decipher bacteria’s strategies to resistant antibiotics but also assists in proposing targets for antibiotic development. In this work, a comprehensive comparative transcriptomic analysis on how Escherichia coli responds to nine representative classes of antibiotics (tetracycline, mitomycin C, imipenem, ceftazidime, kanamycin, ciprofloxacin, polymyxin E, erythromycin, and chloramphenicol) was performed, aimed at determining and comparing the responses of this model organism to antibiotics at the transcriptional level. On average, 39.71% of genes were differentially regulated by antibiotics at concentrations that inhibit 50% growth. Kanamycin leads to the strongest transcriptomic response (76.4% of genes regulated), whereas polymyxin E led to minimal transcriptomic response (4.7% of genes regulated). Further GO, KEGG, and EcoCyc enrichment analysis found significant transcriptomic changes in carbon metabolism, amino acid metabolism, nutrient assimilation, transport, stress response, nucleotide metabolism, protein biosynthesis, cell wall biosynthesis, energy conservation, mobility, and cell-environmental communications. Analysis of coregulated genes led to the finding of significant reduction of sulfur metabolism by all antibiotics, and analysis of transcription factor-coding genes suggested clustered regulatory patterns implying coregulation. In-depth analysis of regulated pathways revealed shared and unique strategies of E. coli resisting antibiotics, leading to the proposal of four different strategies (the pessimistic, the ignorant, the defensive, and the invasive). In conclusion, this work provides a comprehensive analysis of E. coli’s transcriptomic response to antibiotics, which paves the road for further physiological investigation. IMPORTANCE Antibiotics are among the most important inventions in the history of humankind. They are the ultimate reason why bacterial infections are no longer the number one threat to people’s lives. However, the wide application of antibiotics in the last half a century has led to aggravating antibiotic resistance, weakening the efficacy of antibiotics. To better comprehend the ways bacteria deal with antibiotics that may eventually turn into resistance mechanisms, and to identify good targets for potential antibiotics, knowledge on how bacteria regulate their physiology in response to different classes of antibiotics is needed. This work aimed to fill this knowledge gap by identifying changes of bacterial functions at the transcription level and suggesting strategies of bacteria to resist antibiotics.
Homogeneity of XEN Cells Is Critical for Generation of Chemically Induced Pluripotent Stem Cells

In induced pluripotent stem cells (iPSCs), pluripotency is induced artificially by introducing the transcription factors Oct4, Sox2, Klf4, and c-Myc. When a transgene is introduced using a viral vector, the transgene may be integrated into the host genome and cause a mutation and cancer. No integration occurs when an episomal vector is used, but this method has a limitation in that remnants of the virus or vector remain in the cell, which limits the use of such iPSCs in therapeutic applications. Chemical reprogramming, which relies on treatment with small-molecule compounds to induce pluripotency, can overcome this problem. In this method, reprogramming is induced according to the gene expression pattern of extra-embryonic endoderm (XEN) cells, which are used as an intermediate stage in pluripotency induction. Therefore, iPSCs can be induced only from established XEN cells. We induced XEN cells using small molecules that modulate a signaling pathway and affect epigenetic modifications, and devised a culture method which can produce homogeneous XEN cells. At least 4 passages were required to establish morphologically homogeneous chemically induced XEN (CiXEN) cells, whose properties were similar to those of XEN cells, as revealed through cellular and molecular characterization. Chemically iPSCs derived from CiXEN cells showed characteristics similar to those of mouse embryonic stem cells. Our results show that the homogeneity of CiXEN cells is critical for the efficient induction of pluripotency by chemicals.
Diffusion Coefficients of CdSe/CdS Quantum Rods in Water Measured Using Polarized Fluorescence Correlation Spectroscopy

A polarization fluorescence correlation spectroscopy system based on a confocal microscope was built to study the rotational and translational diffusion of CdSe/CdS quantum rods (Q-rods), with the same and different polarization states between the polarizer and the analyzer (i.e. the XXX and XYY states). The rotational diffusion amplitude showed the dependences on polarization of $0.75{\pm}0.05$ in the XXX state and $0.26{\pm}0.03$ in the XYY state, when the translational diffusion amplitude was 1. The diffusion coefficients of the Q-rods were found based on their translational and rotational diffusion times in the two polarization states, in solutions with viscosity ranging from 0.9 to 6.9 cP. The translational and rotational diffusion coefficients ranged from $1.5{\times}10^{-11}$ to $2.6{\times}10^{-12}m^2s^{-1}$ and from $2.9{\times}10^5$ to $5.6{\times}10^4s^{-1}$ , respectively.
Convolution Neural Network for Breast Cancer Detection and Classification Using Deep Learning

Objective: Early detection and precise diagnosis of breast cancer (BC) plays an essential part in enhancing the diagnosis and improving the breast cancer survival rate of patients from 30 to 50%. Through the advances of technology in healthcare, deep learning takes a significant role in handling and inspecting a great number of X-ray, MRI, CTR images. The aim of this study is to propose a deep learning model (BCCNN) to detect and classify breast cancers into eight classes: benign adenosis (BA), benign fibroadenoma (BF), benign phyllodes tumor (BPT), benign tubular adenoma (BTA), malignant ductal carcinoma (MDC), malignant lobular carcinoma (MLC), malignant mucinous carcinoma (MMC), and malignant papillary carcinoma (MPC). Methods: Breast cancer MRI images were classified into BA, BF, BPT, BTA, MDC, MLC, MMC, and MPC using a proposed Deep Learning model with additional 5 fine-tuned Deep learning models consisting of Xception, InceptionV3, VGG16, MobileNet and ResNet50 trained on ImageNet database. The dataset was collected from Kaggle depository for breast cancer detection and classification. That Dataset was boosted using GAN technique. The images in the dataset have 4 magnifications (40X, 100X, 200X, 400X, and Complete Dataset). Thus we evaluated the proposed Deep Learning model and 5 pre-trained models using each dataset individually. That means we carried out a total of 30 experiments. The measurement that was used in the evaluation of all models includes: F1-score, recall, precision, accuracy. Results: The classification F1-score accuracies of Xception, InceptionV3, ResNet50, VGG16, MobileNet, and Proposed Model (BCCNN) were 97.54%, 95.33%, 98.14%, 97.67%, 93.98%, and 98.28%, respectively. Conclusion: Dataset Boosting, preprocessing and balancing played a good role in enhancing the detection and classification of breast cancer of the proposed model (BCCNN) and the fine-tuned pre-trained models’ accuracies greatly. The best accuracies were attained when the 400X magnification of the MRI images due to their high images resolution.
A small change approach on adiposity, lean mass and bone mineral density in adults with overweight and obesity: A randomized controlled trial

We sought to determine whether small changes in physical activity and diet could prevent adverse changes in body composition over 2 years in adults with overweight and obesity. Previously inactive adults (N = 289) were included in a secondary analysis of data derived from a 3‐year, single‐centre, two‐arm, longitudinal randomized controlled trial. Participants were randomized to a small change approach (N = 144, body mass index: 32.4 ± 4.2 [mean ± standard deviation], age: 52.3 ±. 10.6 years) or usual care (N = 145, body mass index: 32.4 ± 4.2, age: 53.1 ± 10.6 years). Small change approach participants were counselled to make small changes in diet and physical activity, while usual care participants were asked to maintain their usual lifestyle. Adiposity, lean mass and bone mineral density were measured by dual‐x‐ray absorptiometry. The change in total adiposity was significantly greater in the small change approach group than usual care at 6 and 12 months but did not remain significant at 24 months (mean change [standard error] −0.8 [0.4] vs. −0.7 [0.4] kg; difference 0.6, 95% confidence interval [CI] −1.2 to 1.1). Changes in visceral fat were significantly greater in the small change approach than usual care at 6 and 12 months but did not remain significant at 24 months (−0.04 [0.03] vs. 0.02 [0.03] kg; difference 0.06, 95% CI: −1.5 to 0.3). Changes in lean mass or bone mineral density were not significantly different between groups at any time point (all p > 0.1). The small change approach did not prevent gains in adiposity or losses in lean mass compared to usual care at 2 years in adults with overweight or obesity. No difference from baseline in adiposity, lean mass or bone mineral density was observed in either arm of the trial.
Estimates for the Syracuse Problem via a Probabilistic Model

We employ a simple stochastic model for the Syracuse problem (also known as the 3x+1 problem) to get estimates for the average behavior of the trajectories of the original deterministic dynamical system. The use of the model is supported not only by certain similarities between the governing rules in the systems, but also by a qualitative estimate of the rate of approximation. From the model, we derive explicit formulae for the asymptotic densities of some sets of interest for the original sequence. We also approximate the asymptotic distributions for the stopping times (times until absorption in the only known cycle {1,2}) of the original system and give numerical illustrations of our results.
Metagenome based analysis of groundwater from arsenic contaminated sites of West Bengal revealed community diversity and their metabolic potential

Abstract The study of microbial community in groundwater systems is considered to be essential to improve our understanding of arsenic (As) biogeochemical cycling in aquifers, mainly as it relates to the fate and transport of As. The present study was conducted to determine the microbial community composition and its functional potential using As-contaminated groundwater from part of the Bengal Delta Plain (BDP) in West Bengal, India. Geochemical analyses indicated low to moderate dissolved oxygen (0.42-3.02 mg/L), varying As (2.5-311 µg/L) and Fe (0.19-1.2 mg/L) content, while low concentrations of total organic carbon (TOC), total inorganic carbon (TIC), nitrate, and sulfate were detected. Proteobacteria was the most abundant phylum, while the indiscriminate presence of an array of archaeal phyla, Euryarchaeota, Crenarchaeota, Nanoarchaeota, etc., was noteworthy. The core community members were affiliated to Sideroxydans, Acidovorax, Pseudoxanthomonas, Brevundimonas, etc. However, diversity assessed over multiple seasons indicated a shift from Sideroxydans to Pseudomonas or Brevundimonas dominant community, suggestive of microbial response to seasonally fluctuating geochemical stimuli. Taxonomy-based functional potential showed prospects for As biotransformation, methanogenesis, sulfate respiration, denitrification, etc. Thus, this study strengthened existing reports from this region by capturing the less abundant or difficult-to-culture taxa collectively forming a major fraction of the microbial community.
Metformin counters oxidative stress and mitigates adverse effects of radiation exposure: An overview

Metformin (1,1‐dimethylbiguanidine hydrochloride) (MF) is a drug that has long been in use for the treatment of type 2 diabetes mellitus and recently is coming into use in the radiation therapy of cancer and other conditions. Exposure to ionizing radiation disturbs the redox homeostasis of cells and causes damage to proteins, membranes, and mitochondria, destroying a number of biological processes. After irradiation, MF activates cellular antioxidant and repair systems by signaling to eliminate the harmful consequences of disruption of redox homeostasis. The use of MF in the treatment of the negative effects of irradiation has great potential in medical patients after radiotherapy and in victims of nuclear accidents or radiologic terrorism.
DNA methylation profile of single in vitro matured bovine oocytes

Somatic cell nuclear transfer (SCNT) is commercially used despite incomplete nuclear reprogramming of the somatic cell nucleus by the enucleated oocyte compromising its efficiency. Oocyte selection is a key factor in increasing this efficiency as its cytoplasm reprograms the differentiated cell. In this study, we adapted a methodology to characterize epialleles in potential epigenetic markers in single in vitro matured oocytes. Characterization of the regions that control the expression of imprinted genes, X‐chromosome inactivation, and satellite I DNA (IGF2, ICR‐H19, XIST, RepA, and SAT1) showed methylated and unmethylated alleles in the imprinted genes IGF2 and ICR‐H19 while XIST‐DMR1 and RepA showed hypermethylated alleles. There was great variation in methylation patterns for candidate regions which may be related to oocyte quality. Moreover, the identification of different epialleles in the same oocyte suggests that, at least for those loci, the epigenome of the metaphase plate and polar body is different. The single‐cell bisulfite polymerase chain reaction technique can be used to improve the precision of selecting the best oocytes for SCNT procedures, thereby increasing its efficiency.
Neutrophil-to-Lymphocyte Ratio (NLR) for Preoperative Differentiation between Uterine Leiomyosarcoma (LMS) and Uterine Leiomyoma: A Case-Controlled Study

Background: Differentiating uterine LMS from uterine leiomyoma is difficult. Therefore, this study aimed to compare preoperative NLR of uterine leiomyosarcoma (LMS) with leiomyoma and secondary objective aimed to identify the clinical characteristics to distinguish between uterine LMS and uterine leiomyoma including the appropriate NLR cut off value to differentiate LMS from leiomyoma. Methods: This was a matched case-controlled study with 1:4 ratio. We collected data of patients with uterine LMS and leiomyoma from 2011 to 2020 at King Chulalongkorn Memorial Hospital. Patients with uterine LMS (case group) and leiomyoma (control group) were matched in terms of year of the surgery and size of the uterine mass. Statistical analysis was conducted using SPSS version 22.0 and STATA version 17. Conditional logistic regression analysis with a p-value of <0.05 was used. Results: Twenty-seven patients who were diagnosed with uterine LMS met the inclusion criteria; 13 patients who had incomplete data and one patient who was had concurrent breast cancer were excluded. Thirteen patients were included in the final analysis. From 2,587 patients in control group; 52 patients were matched. The baseline characteristics in both groups were comparable except for menopausal status Women with uterine LMS had a higher NLR than those with leiomyoma (mean, 4.56 ± 2.5 and 2.4 ± 1.15 in the case and control groups, respectively). Conditional logistic regression determined that the NLR cut-off value of 2.8 was a statistically significant factor for determining uterine LMS (OR = 3.24; 95% CI 1.01–10.43). No significant difference was found in the other factors. Conclusions: Patients who were diagnosed with uterine LMS had a significantly higher NLR than those diagnosed with leiomyoma. The NLR is a simple and effective method for predicting the presence of a uterine LMS in patients who are pre-operatively diagnosed with a uterine mass.
MAML1‐induced HPV E6 oncoprotein stability is required for cellular proliferation and migration of cervical tumor‐derived cells

While a small proportion of high‐risk (HR) alpha (α) human papillomaviruses (HPVs) is associated with numerous human malignancies, of which cervical cancer is the most prevalent, beta (β) HPVs predominantly act as co‐factors in skin carcinogenesis. A characteristic feature of both α‐ and β‐E6 oncoproteins is the presence of the LXXLL binding motif, which α‐E6s utilize to form a complex with E6AP and which enables β‐E6s to interact with MAML1. Here we show that multiple α‐E6 oncoproteins bind to MAML1 via the LXXLL binding motif and that this results in increased protein stability. Moreover, β‐E6 oncoprotein stability is also dependent on the interaction with MAML1. Additionally, in the absence of MAML1, endogenous HPV‐8 E6 and HPV‐18 E6 are rapidly degraded at the proteasome. Ablation of both E6AP and MAML1 leads to an even more profound downregulation of α‐E6 protein expression, whereas this is not observed with β‐E6. This highly suggests that there is one cellular pool for most of β‐E6 that interacts solely with MAML1, whereas there are two cellular pools of HR α‐E6, one forming a complex with MAML1 and the other interacting with E6AP. Furthermore, MAML1 induces HPV‐8 E6 shuttling from the nucleus to the cytosolic fraction, while MAML1 interaction with HR E6 induces a drastic nuclear and membrane upregulation of E6. Interestingly, the HR α‐E6/MAML1 complex does not affect targeting of some of the known HR E6 cellular substrates such as p53 and DLG1. However, MAML1 and E6AP joint co‐expression with HR α‐E6 leads to a significant increase in cellular proliferation, whereas silencing MAML1 decreases wound closure in HeLa cells. These results demonstrate that HR α‐E6 interaction with MAML1 results in a stable form of E6, which likely modulates MAML1's normal cellular activities, one consequence of which being an increased proliferative capacity of HPV‐transformed cancer cells. Thus, this study shows a novel function of the α‐E6 oncoprotein and how it's activity might affect HPV‐induced pathogenesis.
The Associations of Dietary Vitamin K Intake and Circulating Vitamin 25(OH)D with Serum Lipoprotein Levels: The Vitamin Deficiency Matters

Abstract A synergistic interplay between vitamins K and D appears to exist. We aimed to investigate for the first time whether the associations of dietary vitamin K intake and circulating 25(OH)D with serum lipoprotein levels are influenced by the existence of deficiency of either or both vitamins K and D. Sixty individuals [24 males, 36(18–79) years old] were examined. Vitamin deficiency of K1 and D were defined as vitamin K1 intake/body weight (BW)<1.00 μg/kg/day and circulating 25(OH)D<20 ng/ml, respectively. In individuals with vitamin K1 deficiency, the vitamin K1 intake/BW correlated positively with high density lipoprotein-cholesterol (HDL-C) (r=0.509, p=0.008) and negatively with serum triglycerides (TG) (r=–0.638, p=0.001), whereas circulating 25(OH)D correlated negatively with TG (r=–0.609, p=0.001). In individuals with vitamin D deficiency, the vitamin K1 intake/BW correlated positively with HDL-C (r=0.533, p=0.001) and negatively with TG (r=–0.421, p=0.009), while circulating 25(OH)D correlated negatively with TG (r=–0.458, p=0.004). The above-mentioned associations of vitamin K1 intake/BW and circulating 25(OH)D with serum lipoproteins were not detected in individuals without vitamin K1 deficiency or the ones without vitamin D deficiency. The vitamin K2 intake/BW correlated negatively with low density lipoprotein-cholesterol (LDL-C) (r=–0.404, p=0.001). In conclusion, the associations of vitamin K1 intake with TG and HDL-C and of circulating 25(OH)D with TG were more pronounced in individuals with deficiency of either or both vitamins K1 and D. Increased dietary vitamin K2 intake was associated with decreased LDL-C.
In vitro and ex vivo antibiofilm activity of riparin 1, and its nor and dinor homologs, against dermatophytes

ABSTRACT Dermatophytosis is one of the most frequent superficial mycoses in the world. They are mainly caused by the dermatophytes Trichophyton rubrum and Microsporum canis. Biofilm production is an essential factor in the pathogenesis of dermatophytes; it confers drug resistance and significantly impairs antifungal effectiveness. Therefore, we evaluated the antibiofilm activity of an alkamide-type alkaloid called riparin 1 (RIP1) against clinically relevant dermatophytes. We also produced synthetic nor (NOR1) and dinor (DINOR1) homologs for pharmacological evaluation, with a 61–70% yield. We used in vitro (96-well polystyrene plates) and ex vivo (hair fragments) models to verify the effects of these compounds on the formation and viability of biofilms. RIP1 and NOR1 showed antifungal activity against strains of T. rubrum and M. canis, but DINOR1 showed no significant antifungal activity against the dermatophytes. Furthermore, RIP1 and NOR1 significantly reduced the viability of biofilms in vitro and ex vivo (P < 0.05). RIP1 was more potent than NOR1, possibly due to the distance between the p-methoxyphenyl and the phenylamide moieties in these compounds. Due to the significant antifungal and antibiofilm activities observed for RIP1 and NOR1, we suggest that they could be useful in the treatment of dermatophytosis.