LLukas22/scidocs huggingface dataset:
Cell-penetrating peptides and their therapeutic applications

The process of introducing drugs into cells has always proved a major challenge for research scientists and for the pharmaceutical industry. The cell membrane is selectively permeable and supports no generic mechanism for their uptake. A drug must be either highly lipophilic or very small to stand a chance of cellular internalization. These restrictions mean that the repertoire of possible drug molecules is limited. Similarly, novel therapeutic approaches such as gene and protein therapy also have limited potential due to the cell-impermeable nature of peptides and oligonucleotides. The existing methods for delivery of macromolecules, such as viral vectors and membrane perturbation techniques, can result in high toxicity, immunogenicity and low delivery yield. However, in 1988 the remarkable ability of a peptide to traverse a cell’s plasma membrane independent of a membrane receptor was revealed. Known as Tat, the transcription activator of the human immunodeficiency virus type 1 (HIV-1) viral genome was shown to enter cells in a non-toxic and highly efficient manner. In light of such properties Tat became known as the first ‘cell-penetrating peptide’ (CPP). CPPs have demonstrated themselves to be capable of delivering biologically active cargo to the cell interior and the vehicular capabilities of CPPs have already been harnessed for use as laboratory tools. However, it is believed that their true potential lies within the field of therapeutics. Attached to a CPP, therapeutic cargo could be delivered to an intracellular target, thus overcoming the entry restrictions set by the plasma membrane. Since the discovery of Tat, the number of known peptides with cell-penetrating capabilities has grown and in 2003, the first CPP-based drug reached phase II clinical trials. This review discusses the controversial mechanism of entry employed by CPPs, their potential applications in vitro and in vivo, and the ways in which CPP properties have been optimized to maximize their potential as future therapeutics.
Dietary total antioxidant capacity: a novel indicator of diet quality in healthy young adults.

BACKGROUND
Overall diet quality measurements have been suggested as a useful tool to assess diet-disease relationships. Oxidative stress has been related to the development of obesity and other chronic diseases. Furthermore, antioxidant intake is being considered as protective against cell oxidative damage and related metabolic complications.


OBJECTIVE
To evaluate potential associations between the dietary total antioxidant capacity of foods (TAC), the energy density of the diet, and other relevant nutritional quality indexes in healthy young adults.


METHODS
Several anthropometric variables from 153 healthy participants (20.8 +/- 2.7 years) included in this study were measured. Dietary intake was assessed by a validated food-frequency questionnaire, which was also used to calculate the dietary TAC and for daily energy intake adjustment.


RESULTS
Positive significant associations were found between dietary TAC and Mediterranean energy density hypothesis-oriented dietary scores (Mediterranean Diet Score, Alternate Mediterranean Diet Score, Modified Mediterranean Diet Score), non-Mediterranean hypothesis-oriented dietary scores (Healthy Eating Index, Alternate Healthy Eating Index, Diet Quality Index-International, Diet Quality Index-Revised), and diversity of food intake indicators (Recommended Food Score, Quantitative Index for Dietary Diversity in terms of total energy intake). The Mediterranean Diet Quality Index and Diet Quality Index scores (a Mediterranean and a non-Mediterranean hypothesis-oriented dietary score, respectively), whose lower values refer to a higher diet quality, decreased with higher values of dietary TAC. Energy density was also inversely associated with dietary TAC.


CONCLUSION
These data suggest that dietary TAC, as a measure of antioxidant intake, may also be a potential marker of diet quality in healthy subjects, providing a novel approach to assess the role of antioxidant intake on health promotion and diet-based therapies.
A lightweight BFT consensus protocol for blockchains

We present a general consensus framework that allows to easily introduce a customizable Byzantine fault tolerant consensus algorithm to an existing (delegated) proof-of-stake blockchain. We prove the safety of the protocol under the assumption that less than 1/3 of the block proposers are Byzantine. The framework further allows for consensus participants to choose subjective decision thresholds in order to obtain safety even in the case of a larger proportion of Byzantine block proposers. Moreover, the liveness of the protocol is shown if less than 1/3 of the block proposers crash. Based on the framework, we introduce Lisk-Bft, a Byzantine fault tolerant consensus algorithm for the Lisk blockchain. Lisk-Bft integrates with the existing block proposal, requires only two additional integers in block headers and no additional messages. The protocol is simple and provides safety in the case of static proposers if less than 1/3 of the block proposers are Byzantine. For the case of dynamically changing proposers, we proof the safety of the protocol assuming a bound on the number of Byzantine proposers and the number of honest proposers that can change at one time. We further show the liveness of the Lisk-Bft protocol for less than 1/3 crashing block proposers.
Adherence is not a barrier to successful antiretroviral therapy in South Africa.

OBJECTIVE
To determine adherence of an indigent African HIV-infected cohort initiating antiretroviral therapy (ART); to identify predictors of incomplete adherence (< 95%) and virologic failure (> 400 HIV RNA copies/ml).


DESIGN
Prospective monitoring of adherence in a poor HIV-positive cohort, attending a public sector hospital and receiving ART through phase III studies.


METHODS
Adherence to ART was determined over 48 weeks by counting tablet-returns. Logistic regression models including age, WHO HIV stage, home language, socio-economic status, complexity and type of regimen were fitted to determine predictors of incomplete adherence and virologic failure at 48 weeks.


RESULTS
289 patients were recruited between January 1996 and May 2001. Median (mean) adherence of the cohort was 93.5% (87.2%). Three times daily dosing [risk ratio (RR), 3.07; 95% confidence interval (CI), 1.40-6.74], speaking English (RR, 0.41; 95% CI, 0.21-0.80) and age (RR, 0.97; 95% CI, 0.94-0.99) were independent predictors of incomplete adherence. Socio-economic status, sex and HIV stage did not predict adherence. Independent predictors of virologic failure included baseline viral load (RR, 2.57; 95% CI, 1.57-4.22) and three times daily dosing (RR, 2.64; 95% CI, 1.23-5.66), incomplete adherence (RR, 1.92; 95% CI, 1.10-3.57), age (RR, 0.96; 95% CI, 0.92-0.99) and dual nucleoside therapy (RR, 2.69; 95% CI, 1.17-6.15).


CONCLUSION
The proportion of individuals achieving viral suppression matched results from the developing world. Speaking the same language as site staff and simplified dosing frequency were beneficial. Socio-economic status had no impact on adherence and should not be used as a limitation to ART access.
PLATELET COUNT IN WOMEN WITH PREGNANCY INDUCED HYPERTENSION IN UNIVERSITY HOSPITAL CENTER OF MOTHER AND CHILD HEALTHCARE “KOçO GLIOZHENI”, TIRANA, ALBANIA

INTRODUCTION
One of the most common and potential life threatening complications of pregnancy is pregnancy induced hypertension. This cross-sectional study aimed to investigate the relationship between platelet count and pregnancy induced hypertension.


MATERIAL AND METHODS
Twenty (20) patients (subjects) and twenty (20) healthy pregnant women (control) visiting the Obstetrics and Gynecology Hospital University of "Koço Gliozheni" Tirana Albania were registered in the study and followed during their pregnancy. Both, subjects and control participants were subject to platelet count manually performed using standard methods on.


RESULTS
The mean platelet count of the control group (38448±235500) was significantly higher than that of the subject group (217050±50780.7) (p<0.03). In the first and second trimester was more prevalent low platelet counting with the mean platelet count (107 ±57.3) and (101 ±63.4), respectively. The mean age at marriage in subjects with PIH was found to be with low platelet count. Regular monitoring of platelet counts in women with Pregnancy Induced Hypertension must be subject of the management protocols.
Projector Calibration using Arbitrary Planes and Calibrated Camera

In this paper, an easy calibration method for projector is proposed. The calibration handled in this paper is projective relation between 3D space and 2D pattern, and is not correction of trapezoid distortion in projected pattern. In projector-camera systems, especially for 3D measurement, such calibration is the basis of process. The projection from projector can be modeled as inverse projection of the pinhole camera, which is generally considered as perspective projection. In the existing systems, some special objects or devices are often used to calibrate projector, so that 3D-2D projection map can be measured for typical camera calibration methods. The proposed method utilizes projective geometry between camera and projector, so that it requires only pre-calibrated camera and a plane. It is easy to practice, easy to calculate, and reasonably accurate.
South Africa’s readiness to integrate ICT into mathematics and science pedagogy in secondary schools

One of South Africa’s identified priorities is the implementation of ICT in education. To this end a phased implementation plan was initiated in 2004 for ICT to be implemented into schools across the country over eight years. During this time South Africa also participated in three international studies undertaken by the International Association for the Evaluation of Educational Achievement (IEA) focusing on ICT in Education. Each of these permitted the country to benchmark its progress in terms of other countries and their implementation of ICT in education. The latest study, SITES 2006 provides a useful set of indicators against which South Africa can evaluate its progress with regard to its implementation of ICT. This paper seeks to evaluate South Africa’s readiness to integrate ICT into mathematics and science classrooms. This was done using a number of indicators of “sustainable change” derived from SITES 2006 and then comparing these to countries such as Chile, Thailand and Norway, the former two with similar context and conditions and the latter with contrasting conditions. The findings reveal that whilst South Africa has made some progress since 1998 in terms of the implementation of ICT in education, that the majority of schools are still in their infancy regarding the acquisition of ICT and most of those who have access are still in the process of trying to integrate the ICT into their teaching and learning. It would appear that more fundamental needs in South Africa’s education system have dominated its priorities.
Learning conditional preference networks

Conditional preference networks (CP-nets) have recently emerged as a popular language capable of representing ordinal preference relations in a compact and structured manner. In this paper, we investigate the problem of learning CP-nets in the well-known model of exact identification with equivalence and membership queries. The goal is to identify a target preference ordering with a binary-valued CP-net by interacting with the user through a small number of queries. Each example supplied by the user or the learner is a preference statement on a pair of outcomes. In this model, we show that acyclic CP-nets are not learnable with equivalence queries alone, even if the examples are restricted to swaps for which dominance testing takes linear time. By contrast, acyclic CP-nets are what is called attribute-efficiently learnable when both equivalence queries and membership queries are available: we indeed provide a learning algorithm whose query complexity is linear in the description size of the target concept, but only logarithmic in the total number of attributes. Interestingly, similar properties are derived for tree-structured CPnets in the presence of arbitrary examples. Our learning algorithms are shown to be quasi-optimal by deriving lower bounds on the VC-dimension of CP-nets. In a nutshell, our results reveal that active queries are required for efficiently learning CP-nets in large multi-attribute domains.
The metabolic syndrome and its components in patients with prostate cancer on androgen deprivation therapy.

PURPOSE
Androgen deprivation therapy may promote the development of the metabolic syndrome in patients with prostate cancer. We assessed the prevalence of the full metabolic syndrome and its components during the first year of androgen deprivation therapy.


MATERIALS AND METHODS
This observational, multicenter, prospective study included 539 patients with prostate cancer scheduled to receive 3-month depot luteinizing hormone-releasing hormone analogs for more than 12 months. Waist circumference, body mass index, lipid profile, blood pressure and fasting glucose were evaluated at baseline and after 6 and 12 months. The metabolic syndrome was assessed according to NCEP ATP III criteria (2001) and 4 other definitions (WHO 1998, AACE 2003, AHA/NHLBI 2005 and IDF 2005).


RESULTS
At 6 and 12 months after the initiation of androgen deprivation therapy, significant increases were observed in waist circumference, body mass index, fasting glucose, triglycerides, total cholesterol, and high-density and low-density lipoprotein cholesterol. No significant changes in blood pressure 130/85 or greater were detected. A nonsignificant increase of 3.9% in the prevalence of the full metabolic syndrome (ATP III) was observed (22.9% at baseline vs 25.5% and 26.8% at 6 and 12 months, respectively). The prevalence of the metabolic syndrome at baseline varied according to the definition used, ranging from 9.4% (WHO) to 50% (IDF). At 12 months significant increases in prevalence were observed with the WHO (4.1%) and AHA/NHLBI (8.1%) definitions.


CONCLUSIONS
Androgen deprivation therapy produces significant early effects on waist circumference, body mass index, fasting glucose, triglycerides and cholesterol. The prevalence of and increase in the metabolic syndrome depend on the defining criteria. Counseling patients on the prevention, early detection and treatment of specific metabolic alterations is recommended.
Biologically inspired robots using Smart Composite Microstructures

Various biologically inspired small scale robots are built with endoskeleton structures. Generally, endoskeletons consist of rotational joints and rigid links. For millimeter scale robots, endoskeletons should be scalable and easy to manufacture. Layers of composite materials and polymer film can be fabricated into small scale joints and link structures as seen in fig. 1. The structures are called SCM (Smart Composite Microstructures) [1]. These structures have many advantages in small scale robot structures in aspect of friction and manufacturing simplicity. We expand the structure with SMA spring actuator for actuation of small components. In this video, we show three robot prototypes using SCM. The first robot is a fully foldable robot using torsional spring type SMA actuator. As seen in fig. 2, three segments of plate structures can be folded into a compact cube shape. The Second robot is Omegabot: Inchworm inspired robot [3]. It crawls with two anchors gripping the ground alternatively by making its body into an omega shape. This simple locomotion is a suitable moving mechanism for small scale robots. The Omegabot produces motions of crawling, climbing, and steering with tethered power and control. The third robot is a flea inspired robot. The flea can jump more than 130 times of its body length with its body length just below 1mm. The flea uses a torque reversal mechanism which enables storing large amount of energy and releasing it with a small amount of force. This mechanism is simple and efficient, which makes it a good mechanism for small jumping robots. The current prototype of the flea inspired robot jumps 64cm high, which is about 30 times of the robot body length. The SCM enabled these novel small scale robots, and has a potential to enable various small scale robots.
Turing Test Considered Harmful

Passing the Turing Test is not a sensible goal for Artificial Intelligence. Adherence to Turing's vision from 1950 is now actively harmful to our field. We review problems with Turing's idea, and suggest that, ironically, the very cognitive science that he tried to create must reject his research goal.
A hybrid learning algorithm for text classification

Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify text need sufficient documents to learn accurately. This paper presents a new algorithm for text classification that requires fewer documents for training. Instead of using words, word relation i.e association rules from these words is used to derive feature set from preclassified text documents. The concept of Naïve Bayes classifier is then used on derived features and finally only a single concept of Genetic Algorithm has been added for final classification. Experimental results show that the classifier build this way is more accurate than the existing text classification systems.
Active tamoxifen metabolite plasma concentrations after coadministration of tamoxifen and the selective serotonin reuptake inhibitor paroxetine.

BACKGROUND
Tamoxifen, a selective estrogen receptor modulator (SERM), is converted to 4-hydroxy-tamoxifen and other active metabolites by cytochrome P450 (CYP) enzymes. Selective serotonin reuptake inhibitors (SSRIs), which are often prescribed to alleviate tamoxifen-associated hot flashes, can inhibit CYPs. In a prospective clinical trial, we tested the effects of coadministration of tamoxifen and the SSRI paroxetine, an inhibitor of CYP2D6, on tamoxifen metabolism.


METHODS
Tamoxifen and its metabolites were measured in the plasma of 12 women of known CYP2D6 genotype with breast cancer who were taking adjuvant tamoxifen before and after 4 weeks of coadministered paroxetine. We assessed the inhibitory activity of pure tamoxifen metabolites in an estradiol-stimulated MCF7 cell proliferation assay. To determine which CYP isoforms were involved in the metabolism of tamoxifen to specific metabolites, we used CYP isoform-specific inhibitors. All statistical tests were two-sided.


RESULTS
We separated, purified, and identified the metabolite 4-hydroxy-N-desmethyl-tamoxifen, which we named endoxifen. Plasma concentrations of endoxifen statistically significantly decreased from a mean of 12.4 ng/mL before paroxetine coadministration to 5.5 ng/mL afterward (difference = 6.9 ng/mL, 95% confidence interval [CI] = 2.7 to 11.2 ng/mL) (P =.004). Endoxifen concentrations decreased by 64% (95% CI = 39% to 89%) in women with a wild-type CYP2D6 genotype but by only 24% (95% CI = 23% to 71%) in women with a variant CYP2D6 genotype (P =.03). Endoxifen and 4-hydroxy-tamoxifen inhibited estradiol-stimulated MCF7 cell proliferation with equal potency. In vitro, troleandomycin, an inhibitor of CYP3A4, inhibited the demethylation of tamoxifen to N-desmethyl-tamoxifen by 78% (95% CI = 65% to 91%), and quinidine, an inhibitor of CYP2D6, reduced the subsequent hydroxylation of N-desmethyl-tamoxifen to endoxifen by 79% (95% CI = 50% to 108%).


CONCLUSIONS
Endoxifen is an active tamoxifen metabolite that is generated via CYP3A4-mediated N-demethylation and CYP2D6-mediated hydroxylation. Coadministration of paroxetine decreased the plasma concentration of endoxifen. Our data suggest that CYP2D6 genotype and drug interactions should be considered in women treated with tamoxifen.
Detection of Violations in Credit Cards of Banks and Financial Institutions based on Artificial Neural Network and Metaheuristic Optimization Algorithm

Due to popularity of the World Wide Web and ecommerce, electronic communications between people and different organizations through virtual world of the Internet have provided a good basis for commercial and economic relations. These developments, although occurring for less than a century, electronic communications have always been subject to interference, cheating, fraud, and other acts of sabotage. Along with this increase in trading volume, there is a huge increase in the number of online fraud which results in billions of dollars of losses annually worldwide; this has a direct effect on customer service of banking systems, particularly electronic banking systems, and survival as a reliable financial service provider. Therefore, attention to fraud detection techniques is essential to prevent fraudulent acts and is the motive for many scientific researches. For this reason, business intelligence is used to identify financial violations in various economic, banking and other fields. Here, the focus is on algorithms and methods presented in data mining to deal with fraud by using neural networks. The main objective is to improve these methods or present new algorithms by studying the behavioral patterns of customers and the combined use of genetic algorithm to improve the performance of neural network and find the appropriate models for better decision making by implementing and testing the performance of the suggested algorithms. The results show that more strength was given to neural network by using genetic algorithm. In fact, genetic algorithm can raise our ability to control the training process. Moreover, it was concluded that criteria such as age, gender, marital status were not effective on detection; in fact, the most important effective criteria are information related to transaction. Keywords—Financial fraud detection; neural networks; data mining; genetic algorithm