Miracle-dz/UniFAR-FTUs huggingface dataset:
The Deacetylase SIRT1 Regulates the Replication Properties of Human Papillomavirus 16 E1 and E2

ABSTRACT Human papillomaviruses (HPV) replicate their genomes in differentiating epithelium using the viral proteins E1 and E2 in association with host proteins. While the roles of E1 and E2 in this process are understood, the host factors involved and how they interact with and regulate E1-E2 are not. Our previous work identified the host replication and repair factor TopBP1 as an E2 partner protein essential for optimal E1-E2 replication and for the viral life cycle. The role of TopBP1 in host DNA replication is regulated by the class III deacetylase SIRT1; activation of the DNA damage response prevents SIRT1 deacetylation of TopBP1, resulting in a switch from DNA replication to repair functions for this protein and cell cycle arrest. Others have demonstrated an essential role for SIRT1 in regulation of the HPV31 life cycle; here, we report that SIRT1 can directly regulate HPV16 E1-E2-mediated DNA replication. SIRT1 is part of the E1-E2 DNA replication complex and is recruited to the viral origin of replication in an E1-E2-dependent manner. CRISPR/Cas9 was used to generate C33a clones with undetectable SIRT1 expression and lack of SIRT1 elevated E1-E2 DNA replication, in part due to increased acetylation and stabilization of the E2 protein in the absence of SIRT1. The results demonstrate that SIRT1 is a member of, and can regulate, the HPV16 replication complex. We discuss the potential role of this protein in the viral life cycle. IMPORTANCE HPV are causative agents in a number of human diseases, and currently only the symptoms of these diseases are treated. To identify novel therapeutic approaches for combating these diseases, the viral life cycle must be understood in more detail. This report demonstrates that a cellular enzyme, SIRT1, is part of the HPV16 DNA replication complex and is brought to the viral genome by the viral proteins E1 and E2. Using gene editing technology (CRISPR/Cas9), the SIRT1 gene was removed from cervical cancer cells. The consequence of this was that viral replication was elevated, probably due to a stabilization of the viral replication factor E2. The overall results demonstrate that an enzyme with known inhibitors, SIRT1, plays an important role in controlling how HPV16 makes copies of itself. Targeting this enzyme could be a new therapeutic approach for combating HPV spread and disease.
A Game-Theoretic Decentralized Model Predictive Control of Thermal Appliances in Discrete-Event Systems Framework

This paper presents a decentralized model predictive control (MPC) scheme for thermal appliances coordination control in smart buildings. The general system structure consists of a set of local MPC controllers and a game-theoretic supervisory control constructed in the framework of discrete-event systems (DES). In this hierarchical control scheme, a set of local controllers work independently to maintain the thermal comfort level in different zones, and a centralized supervisory control is used to coordinate the local controllers according to the power capacity and the current performance. Global optimality is ensured by satisfying the Nash equilibrium at the coordination layer. The validity of the proposed method is assessed by a simulation experiment including two case studies. The results show that the developed control scheme can achieve a significant reduction of the peak power consumption while providing an adequate temperature regulation performance if the system is $\mathcal{P}$-observable.
Long-term outcomes among patients who achieve complete or near-complete responses after the induction phase of bladder-preserving combined modality therapy for muscle-invasive bladder cancer: A pooled analysis of RTOG 9906 and 0233.

284 Background: Bladder preserving combined-modality therapy for muscle-invasive bladder cancer (MIBC) includes transurethral resection and concurrent chemo-RT given in two phases. After the induction phase with chemo-RT to 40 Gy the tumor response is assessed by cystoscopic biopsies and urine cytology. Early salvage cystectomy is promptly offered in case of persistent disease, otherwise patients proceed to consolidation chemo-RT to 64 Gy. The two most recent RTOG protocols 9906 and 0233 allowed patients with near-complete response (Ta or Tis) after the induction phase to proceed to consolidation. Methods: We performed a pooled analysis of 119 eligible patients with MIBC enrolled on RTOG trials 9906 and 0233, who were classified as having a complete (T0) or near-complete (Ta or Tis) response after induction chemo-RT and completed consolidation with a total RT dose of at least 60 Gy. We estimated bladder recurrence, salvage cystectomy rates and disease-specific survival by the cumulative incidence method a.
Automatic Pearl Classification Machine Based on a Multistream Convolutional Neural Network

In this paper, we design an automatic pearl classification machine, composed of four parts: feeding mechanism, delivering mechanism, vision-based detection device, and classification mechanism. Pearls can be delivered to the detection device one by one, where multiview images of each pearl can be collected. A novel multistream convolutional neural network (MS-CNN) is developed to cope with these multiview images, with each stream processing an image of particular viewing angle and different streams sharing part of weights to fuse high-order features without losing too much diversity. Using the machine, we collect 52 500 multiview images for 10 500 pearls, i.e., each pearl has five images of top, left, right, main, and rear views. These pearls were labeled by the experienced professionals in advance, and grouped into two classes with rough rules and seven classes with fine rules. Experimental results show that, compared with the support vector machine and backpropagation neural network, our MS-CNN behaves much better in both classification tasks, obtaining 92.14% and 91.24% accuracies. Moreover, the visualization of activations of convolutional kernels suggests that MS-CNN, imitating the manual process, can indeed recognize relatively complex features. These results indicate the potential value of our machine in the pearl industry.
Influence of knitted orthopaedic support construction on compression generated by the support

This study attempts to investigate the influence of the inlay-yarn insertion density into a knitted structure and of the area of a rigid element integrated into a knitted orthopaedic support on a compression generated by the support. The samples were made on a flat double needle-bed knitting machine with a laid-in structure knitted on a rib 1 × 1 pattern base, differing in the inlay-yarn insertion density. In general, research studies analyse compression and other properties of compressive stockings and do not investigate the influence of non-textile parts usually used in the knitted orthopaedic support. It was established that the linear density of the inlay-yarn has a visible influence on the compression generated by knitted support when inlay-yarn insertion density is every other course and less. When inlay-yarn is inserted into every course, the generated compression is the highest and the influence of inlay-yarn linear density on the generated compression is significant. It was found that compression of the support increases depending on the area of the rigid element in the knitted support. The rate of influence of the rigid area on compression rises with an increase in the inlay-yarn insertion density and in the elongation value. By designing a knitted compressive orthopaedic support, it is necessary to find an optimal ratio between an inlay-yarn insertion density and an area of a rigid element, thereby achieving the best compressive, wear comfort and economical result.
Sensitive Next-Generation Sequencing Method Reveals Deep Genetic Diversity of HIV-1 in the Democratic Republic of the Congo

ABSTRACT As the epidemiological epicenter of the human immunodeficiency virus (HIV) pandemic, the Democratic Republic of the Congo (DRC) is a reservoir of circulating HIV strains exhibiting high levels of diversity and recombination. In this study, we characterized HIV specimens collected in two rural areas of the DRC between 2001 and 2003 to identify rare strains of HIV. The env gp41 region was sequenced and characterized for 172 HIV-positive specimens. The env sequences were predominantly subtype A (43.02%), but 7 other subtypes (33.14%), 20 circulating recombinant forms (CRFs; 11.63%), and 20 unclassified (11.63%) sequences were also found. Of the rare and unclassified subtypes, 18 specimens were selected for next-generation sequencing (NGS) by a modified HIV-switching mechanism at the 5′ end of the RNA template (SMART) method to obtain full-genome sequences. NGS produced 14 new complete genomes, which included pure subtype C (n = 2), D (n = 1), F1 (n = 1), H (n = 3), and J (n = 1) genomes. The two subtype C genomes and one of the subtype H genomes branched basal to their respective subtype branches but had no evidence of recombination. The remaining 6 genomes were complex recombinants of 2 or more subtypes, including subtypes A1, F, G, H, J, and K and unclassified fragments, including one subtype CRF25 isolate, which branched basal to all CRF25 references. Notably, all recombinant subtype H fragments branched basal to the H clade. Spatial-geographical analysis indicated that the diverse sequences identified here did not expand globally. The full-genome and subgenomic sequences identified in our study population significantly increase the documented diversity of the strains involved in the continually evolving HIV-1 pandemic. IMPORTANCE Very little is known about the ancestral HIV-1 strains that founded the global pandemic, and very few complete genome sequences are available from patients in the Congo Basin, where HIV-1 expanded early in the global pandemic. By sequencing a subgenomic fragment of the HIV-1 envelope from study participants in the DRC, we identified rare variants for complete genome sequencing. The basal branching of some of the complete genome sequences that we recovered suggests that these strains are more closely related to ancestral HIV-1 strains than to previously reported strains and is evidence that the local diversification of HIV in the DRC continues to outpace the diversity of global strains decades after the emergence of the pandemic.
Nut Consumption and Lung Cancer Risk: Results from Two Large Observational Studies

Background: Epidemiologic evidence on the association between nut consumption and lung cancer risk is limited. Methods: We investigated this relationship in the Environment and Genetics in Lung Cancer Etiology (EAGLE) study, a population-based case–control study, and the National Institutes of Health (NIH) American Association of Retired Persons (AARP) Diet and Health Study, a prospective cohort. We identified 2,098 lung cases for EAGLE and 18,533 incident cases in AARP. Diet was assessed by food frequency questionnaire for both studies. Multivariable ORs and HRs and respective 95% confidence intervals (CI) were calculated using unconditional logistic regression and Cox proportional hazards regression for EAGLE and AARP, respectively. Results: Higher frequency of intake of nut consumption was inversely associated with overall lung cancer risk (highest vs. lowest quintile, OREAGLE = 0.74; 95% CI, 0.57–0.95; HRAARP = 0.86; 95% CI, 0.81–0.91), regardless of smoking status. Results from the prospective cohort showed similar associations across histologic subtypes and a more pronounced benefits from nut consumption for those who smoked 1 to 20 cigarettes/day (OREAGLE = 0.61; 95% CI, 0.39–0.95; HRAARP = 0.83; 95% CI, 0.74–0.94). Conclusions: Nut consumption was inversely associated with lung cancer in two large population-based studies, and associations were independent of cigarette smoking and other known risk factors. Impact: To our knowledge, this is the first study that examined the association between nut consumption and lung cancer risk by histologic subtypes and smoking intensity. Cancer Epidemiol Biomarkers Prev; 26(6); 826–36. ©2017 AACR.
Using Incompletely Cooperative Game Theory in Mobile Ad Hoc Networks

Recently, game theory becomes a useful and powerful tool to research mobile ad hoc networks (MANETs). Wireless LANs (WLANs) can work under both infrastructure and ad hoc modes, and are the most widely used MANETs. In this paper, we propose a novel concept of incompletely cooperative game theory and use it to improve the performance of WLANs. In this game, firstly, each node estimates the current state of the game (i.e., the number of competing nodes) by detecting the channel. Secondly, each node changes its equilibrium strategy by tuning its local contention parameters based on the estimated game state. Finally, the game is repeated finitely to get the optimal performance. Our simulation results show that the incompletely cooperative game can increase system throughput, and decrease delay, jitter and packet-loss-rate.
Sparse Representation-Based Radiomics for the Diagnosis of Brain Tumors

Brain tumors are the most common malignant neurologic tumors with the highest mortality and disability rate. Because of the delicate structure of the brain, the clinical use of several commonly used biopsy diagnosis is limited for brain tumors. Radiomics is an emerging technique for noninvasive diagnosis based on quantitative medical image analyses. However, current radiomics techniques are not standardized regarding feature extraction, feature selection, and decision making. In this paper, we propose a sparse representation-based radiomics (SRR) system for the diagnosis of brain tumors. First, we developed a dictionary learning- and sparse representation-based feature extraction method that exploits the statistical characteristics of the lesion area, leading to fine and more effective feature extraction compared with the traditional explicitly calculation-based methods. Then, we set up an iterative sparse representation method to solve the redundancy problem of the extracted features. Finally, we proposed a novel multi-feature collaborative sparse representation classification framework that introduces a new coefficient of regularization term to combine features from multi-modal images at the sparse representation coefficient level. Two clinical problems were used to validate the performance and usefulness of the proposed SRR system. One was the differential diagnosis between primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM), and the other was isocitrate dehydrogenase 1 estimation for gliomas. The SRR system had superior PCNSL and GBM differentiation performance compared with some advanced imaging techniques and yielded 11% better performance for estimating IDH1 compared with the traditional radiomics methods.
Comparison of monitor unit calculations performed with a 3D computerized planning system and independent “hand” calculations: Results of three years clinical experience

A comparison of the monitor unit calculations of a commercial 3D computerized treatment planning system (TPS) with “hand” calculations from lookup tables was made for a large number of clinical cases (greater than 13 500 treatment fields). Differences were analyzed by treatment site for prostate, rectum, cranium, and breast. The 3D TPS monitor unit calculation was systematically higher than the “hand” calculation by an amount that depended on the complexity of the treatment geometry. For simple geometries the mean difference was 1% and was as high as 3% for more complicated geometries. The higher value was attributed to an accumulation of differences introduced by multiple factors in the monitor unit calculation. Careful attention to factors such as patient contour could reduce the mean difference. “Hand” calculations were shown to be an accurate and useful tool for verification of TPS monitor unit calculations. PACS number(s): 87.53. ‐j, 87.52. ‐g
R 1 R 2 R 3 S 4 a S 4 b I 1 I

We propose deceptive secret sharing, which is a novel approach to provide both confidentiality and deception in distributed storage systems. The motivation for this is to protect confidentiality as far as possible while acknowledging that no confidentiality scheme provides perfect protection. If confidentiality is breached and information is accessed by unauthorized individuals, our deceptive secret sharing techniques will reveal, with high probability, only false information. This provides an added deception layer on top of the confidentiality provided by basic secret sharing. We present deceptive techniques that work with both XOR secret sharing and Shamir’s polynomialbased threshold secret sharing. We provide extensive analyses of both overhead and security of our techniques and we show how they provide tunable security that can trade off security and overhead by varying a single parameter of the schemes. The proposed techniques were also implemented in CloudLab, where experimental evaluations showed that, with appropriate parameter choices, they can provide both reasonable performance and high availability.
Dark Image Enhancement Using Perceptual Color Transfer

In this paper, we introduce an image enhancing approach for transforming dark images into lightened scenes, and we evaluate such method in different perceptual color spaces, in order to find the best-suited for this particular task. Specifically, we use a classical color transfer method where we obtain first-order statistics from a target image and transfer them to a dark input, modifying its hue and brightness. Two aspects are particular to this paper, the application of color transfer on dark imagery and in the search for the best color space for the application. In this regard, the tests performed show an accurate transference of colors when using perceptual color spaces, being RLAB the best color space for the procedure. Our results show that the methodology presented in this paper can be a good alternative to low-light or night vision processing techniques. Besides, the proposed method has a low computational complexity, property that is important for real time applications or for low-resource systems. This method can be used as a preprocessing step in order to improve the recognition and interpretation of dark imagery in a wide range of applications.
Evaluation of digital radiography practice using exposure index tracking

Some digital radiography (DR) detectors and software allow for remote download of exam statistics, including image reject status, body part, projection, and exposure index (EI). The ability to have automated data collection from multiple DR units is conducive to a quality control (QC) program monitoring institutional radiographic exposures. We have implemented such a QC program with the goal to identify outliers in machine radiation output and opportunities for improvement in radiation dose levels. We studied the QC records of four digital detectors in greater detail on a monthly basis for one year. Although individual patient entrance skin exposure varied, the radiation dose levels to the detectors were made to be consistent via phototimer recalibration. The exposure data stored on each digital detector were periodically downloaded in a spreadsheet format for analysis. EI median and standard deviation were calculated for each protocol (by body part) and EI histograms were created for torso protocols. When histograms of EI values for different units were compared, we observed differences up to 400 in average EI (representing 60% difference in radiation levels to the detector) between units nominally calibrated to the same EI. We identified distinct components of the EI distributions, which in some cases, had mean EI values 300 apart. Peaks were observed at the current calibrated EI, a previously calibrated EI, and an EI representing computed radiography (CR) techniques. Our findings in this ongoing project have allowed us to make useful interventions, from emphasizing the use of phototimers instead of institutional memory of manual techniques to improvements in our phototimer calibration. We believe that this QC program can be implemented at other sites and can reveal problems with radiation levels in the aggregate that are difficult to identify on a case‐by‐case basis. PACS number(s): 87.59. bf
Strong Tracking Current Statistical Model Based on Mixed Bayesian-Fisher Model

The current statistical (CS) model has poor performance on tracking weak and sudden maneuvering targets due to non-adaptively adjusting the maneuvering parameters. To solve this problem, a new method based on mixed Bayesian-Fisher model is proposed. By introducing the mixed Bayesian-Fisher model and fusing input estimation (IE) theory, the maneuvering acceleration is adaptive estimated as an additional input term in the corresponding state equation. Then, a multiple fading factor is introduced to enhance the stability and robustness of the algorithm. The simulation results show that the strong tracking current statistical model based on mixed Bayesian-Fisher model (BF-STFCS) eliminates the dependence on initial maneuvering parameters, the tracking accuracy is significantly improved compared with the current statistical model, and the algorithm proposed performs even better than the interacting multiple model (IMMCVCACT). While the complexity of the proposed is only one-third of that of IMMCVCACT, slightly higher than the CS model.
Identification and Characterization of a Cis-Encoded Antisense RNA Associated with the Replication Process of Salmonella enterica Serovar Typhi

Antisense RNAs that originate from the complementary strand of protein coding genes are involved in the regulation of gene expression in all domains of life. In bacteria, some of these antisense RNAs are transcriptional noise whiles others play a vital role to adapt the cell to changing environmental conditions. By deep sequencing analysis of transcriptome of Salmonella enterica serovar Typhi, a partial RNA sequence encoded in-cis to the dnaA gene was revealed. Northern blot and RACE analysis confirmed the transcription of this antisense RNA which was expressed mostly in the stationary phase of the bacterial growth and also under iron limitation and osmotic stress. Pulse expression analysis showed that overexpression of the antisense RNA resulted in a significant increase in the mRNA levels of dnaA, which will ultimately enhance their translation. Our findings have revealed that antisense RNA of dnaA is indeed transcribed not merely as a by-product of the cell's transcription machinery but plays a vital role as far as stability of dnaA mRNA is concerned.