Suicide gene therapy: a promising approach towards gene delivery

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Microfinanças e empoderamento de mulheres: uma análise de regressão de comutação endógena

Women in Pakistan are suffering from a great social and economic deprivation due to gender discrimination and inequitable distribution of resources. This paper examines the determinants and extent of women empowerment by their participation in microfinance programs. Data for this study were collected from different areas of Faisalabad, Pakistan, where most of the households were poor and had borrowed money from different microfinance institutes. Keeping in view the disguised endogeneity, Endogenous Switching Regression Model was employed which accounts for selection bias because of observable and unobservable factors. The analysis revealed that education level, household size, family system, educational expenditures, income level and the ownership of different assets like sewing machines have the statistically significant impact on the women decision to work and hence promote women empowerment. It is concluded that the government in developing countries should introduce income-generating activities, especially for women by providing them access to financial resources.Las mujeres en Pakistán están sufriendo una gran carencia social y económica debido a la discriminación de género y la distribución desigual de los recursos. Este documento examina los determinantes y el alcance del empoderamiento de las mujeres por su participación en los programas de microfinanzas. Los datos para este estudio fueron recolectados de diferentes áreas de Faisalabad, Pakistán, donde la mayoría de los hogares eran pobres y habían tomado dinero prestado de diferentes institutos de microfinanzas. Teniendo en cuenta la endogeneidad disfrazada, se empleó el Modelo de Regresión de Conmutación Endógena que explica el sesgo debido a factores observables y no observables. El análisis reveló que el nivel educativo, el tamaño del hogar, el sistema familiar, los gastos educativos, el nivel de ingresos y la propiedad de diferentes activos, como las máquinas de coser, tienen un impacto estadísticamente significativo en la decisión de las mujeres de trabajar y, por lo tanto, promover el empoderamiento de las mujeres. Se concluye que el gobierno de los países en desarrollo debe introducir actividades generadoras de ingresos, especialmente para las mujeres, proporcionándoles acceso a recursos financierosAs mulheres no Paquistão sofrem de uma grande privação social e econômica devido à discriminação de gênero e à distribuição desigual de recursos. Este artigo examina os determinantes e a extensão do empoderamento das mulheres pela sua participação em programas de microfinanças. Os dados para este estudo foram coletados em diferentes áreas de Faisalabad, Paquistão, onde a maioria dos domicílios era pobre e tinha tomado dinheiro emprestado de diferentes institutos de microfinanças. Tendo em vista a endogeneidade disfarçada, empregou-se o Modelo de Regressão por Comutação Endógena, que considera o viés de seleção por causa de fatores observáveis e inobserváveis. A análise revelou que o nível de escolaridade, tamanho da família, sistema familiar, gastos com educação, nível de renda e posse de diferentes ativos, como máquinas de costura, têm impacto estatisticamente significativo na decisão das mulheres de trabalhar e, portanto, promovem o empoderamento das mulheres. Conclui-se que o governo dos países em desenvolvimento deve introduzir atividades geradoras de renda, especialmente para as mulheres, proporcionando-lhes acesso a recursos financeiro

Concentration-dependent toxicity of iron oxide nanoparticles mediated by increased oxidative stress

Iron oxide nanoparticles with unique magnetic properties have a high potential for use in several biomedical, bioengineering and in vivo applications, including tissue repair, magnetic resonance imaging, immunoassay, drug delivery, detoxification of biologic fluids, cell sorting, and hyperthermia. Although various surface modifications are being done for making these nonbiodegradable nanoparticles more biocompatible, their toxic potential is still a major concern. The current in vitro study of the interaction of superparamagnetic iron oxide nanoparticles of mean diameter 30 nm coated with Tween 80 and murine macrophage (J774) cells was undertaken to evaluate the dose- and time-dependent toxic potential, as well as investigate the role of oxidative stress in the toxicity. A 15–30 nm size range of spherical nanoparticles were characterized by transmission electron microscopy and zeta sizer. MTT assay showed >95% viability of cells in lower concentrations (25–200 μg/mL) and up to three hours of exposure, whereas at higher concentrations (300–500 μg/mL) and prolonged (six hours) exposure viability reduced to 55%–65%. Necrosis-apoptosis assay by propidium iodide and Hoechst-33342 staining revealed loss of the majority of the cells by apoptosis. H2DCFDDA assay to quantify generation of intracellular reactive oxygen species (ROS) indicated that exposure to a higher concentration of nanoparticles resulted in enhanced ROS generation, leading to cell injury and death. The cell membrane injury induced by nanoparticles studied using the lactate dehydrogenase assay, showed both concentration- and time-dependent damage. Thus, this study concluded that use of a low optimum concentration of superparamagnetic iron oxide nanoparticles is important for avoidance of oxidative stress-induced cell injury and death

Arbitrage Price Theory (APT) and Karachi Stock Exchange (KSE)

The intention of this study is to analyze the variability of Arbitrage price theory (APT) in case of KSE. The data from Jan 1985 to Dec 2008 is monthly based has been considered and two econometric methodologies, Johanson co integration and Error correction model are used to checkout the validity of APT in this study. The conclusion of this study illustrates that Quasi money responds negatively with KSE 100 index return while IIP (industrial index of production), exchange rate, petroleum price, domestic interest responds negatively with KSE 100 index return. On the Contrary bullion price and inflation rate are insignificant regarding to KSE 100 index return

Named Entity Recognition for Urdu Language: The UNER System, A Hybrid Approach

NER is a natural language processing technique that primarily classifies parts of parsed text into well-known named entities. In the domain of natural language processing, the recognition of name entities is used to classify nouns that appear in bulk text data and place these nouns into predefined groups, such as names of people, places, times, dates, organizations, etc. There is a lot of fragmented material and data on the Cyberspace, therefore scholars are working on several languages (i.e: Sindhi, English, etc.), by working on various approaches and techniques depending on their locations, to improve accessibility of filtered information for online users. The NER enhance the quality of NLP in applications including automated summarization, semantic web search, information extraction and retrieval machine translation and question answering, chatbots and others. This study designs an efficient framework to extract noun entities in Urdu using a hybrid approach. The UNER system not only extracts entities by searching through a list of names, but also extracts named entities by recognizing phrases in a given text. The UNER system is designed to recognize Urdu noun entities in pre-defined categories such as places, personal names, titled personal names, organizations, object names, trade names, abbreviations, dates and times, measurements, and text names in Urdu

Estimation of protein requirements in Indian pregnant women using a whole-body potassium counter

Background: The 2007 World Health Organization/Food and Agriculture Organization/United Nations University (WHO/FAO/UNU) recommendation for the Estimated Average Requirement (EAR) of additional protein during pregnancy for a gestational weight gain (GWG) of 12 kg (recalculated from a GWG of 13.8 kg) is 6.7 and 21.7 g/d in the second and the third trimester, respectively. This EAR is based on measurements of potassium accretion in high-income country (HIC) pregnant women. It is not known if low- to middle-income country, but well-nourished, pregnant women have comparable requirements. Objective: We aimed to estimate total body potassium (TBK) accretion during pregnancy in Indian pregnant women, using a whole-body potassium counter (WBKC), to measure their additional protein EAR. Methods: Well-nourished pregnant women (20–40 y, n = 38, middle socioeconomic stratum) were recruited in the first trimester of pregnancy. Anthropometric, dietary, and physical activity measurements, and measurements of TBK using a WBKC, were performed at each trimester and at birth. Results: The mid-trimester weight gain was 2.7 kg and 8.0 kg in the second and the third trimester, respectively, for an average 37-wk GWG of 10.7 kg and a mean birth weight of 3.0 kg. Protein accretion was 2.7 and 5.7 g/d, for an EAR of 8.2 and 18.9 g/d in the second and the third trimester, respectively. The additional protein EAR, calculated for a GWG of 12 kg, was 9.1 and 21.2 g/d in the second and the third trimester, respectively. Conclusion: The additional protein requirements of well-nourished Indian pregnant women for a GWG of 12 kg in the second and third trimesters were similar to the recalculated 2007 WHO/FAO/UNU requirements for 12 kg

Automatic image annotation based on deep learning models: A systematic review and future challenges

Recently, much attention has been given to image annotation due to the massive increase in image data volume. One of the image retrieval methods which guarantees the retrieval of images in the same way as texts are automatic image annotation (AIA). Consequently, numerous studies have been conducted on AIA, particularly on the classification-based and probabilistic modeling techniques. Several image annotation techniques that performed reasonably on standard datasets have been developed over the last decade. In this paper, a review of the image annotation method was conducted, focusing more on deep learning models. Automatic image annotation (AIA) methods were also classified into five categories, including i) Convolutional Neural Network (CNN) based on AIA, ii) Recurrent Neural Network (RNN) based on AIA, iii) Deep Neural Networks (DNN) based on AIA, iv) Long-Short-Term Memory (LSTM) based on AIA, and v) Stacked auto-encoder (SAE) based on AIA. An assessment of the five varieties of AIA methods was also offered based on their principal notion, feature mining technique, explanation precision, computational density, and examined aggregated data. Moreover, the evaluation metrics used to evaluate AIA methods were reviewed and discussed. The need for careful consideration of methods throughout the improvement of novel procedures and datasets for image annotation assignment was highly demanded. From the analysis of the achievements so far, it is certain that more attention should be paid to automatic image annotation

FTIR spectra of (a) Nic@Chi Np’s, (b) Chitosan nanoparticles (void), (c) Niclosamide drug alone.

Figure S6. FTIR spectra of (a) Nic@Chi Np’s, (b) Chitosan nanoparticles (void), (c) Niclosamide drug alone

Enhanced antineoplastic/therapeutic efficacy using 5-fluorouracil-loaded calcium phosphate nanoparticles

In the past few decades, the successful theranostic application of nanomaterials in drug delivery systems has significantly improved the antineoplastic potency of conventional anticancer therapy. Several mechanistic advantages of nanomaterials, such as enhanced permeability, retention, and low toxicity, as well as surface engineering with targeting moieties, can be used as a tool in enhancing the therapeutic efficacy of current approaches. Inorganic calcium phosphate nanoparticles have the potential to increase the therapeutic potential of antiproliferative drugs due to their excellent loading efficiency, biodegradable nature and controlled-release behaviour. Herein, we report a novel system of 5-fluorouracil (5-FU)-loaded calcium phosphate nanoparticles (CaP@5-FU NPs) synthesized via a reverse micelle method. The formation of monodispersed, spherical, crystalline nanoparticles with an approximate diameter of 160–180 nm was confirmed by different methods. The physicochemical characterization of the synthesized CaP@5-FU NPs was done with transmission electron microscopy (TEM), dynamic light scattering (DLS), field emission scanning electron microscopy (FE-SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). The antineoplastic potential of the CaP@5-FU NPs against colorectal and lung cancer cells was reported. The CaP@5-FU NPs were found to inhibit half the population (IC50) of lung adenocarcinoma (A549) cells at 32 μg/mL and colorectal (HCT-15) cancer cells at 48.5 μg/mL treatment. The apoptotic induction of CaP@5-FU NPs was confirmed with acridine orange/ethidium bromide (AO/EB) staining and by examining the morphological changes with Hoechst and rhodamine B staining in a time-dependent manner. The apparent membrane bleb formation was observed in FE-SEM micrographs. The up-regulated proapoptotic and down-regulated antiapoptotic gene expressions were further confirmed with semiquantitative reverse transcriptase polymerase chain reaction (PCR). The increased intracellular reactive oxygen species (ROS) were quantified via flow cytometry upon CaP@5-FU NP treatment. Likewise, the cell cycle analysis was performed to confirm the enhanced apoptotic induction. Our study concludes that the calcium phosphate nanocarriers system, i.e. CaP@5-FU NPs, has higher antineoplastic potential as compared to 5-FU alone and can be used as an improved alternative to the antimitotic drug, which causes severe side effects when administrated alone

Data from: Niclosamide loaded biodegradable chitosan nanocargoes: an in vitro study for potential application in cancer therapy

Chitosan nanoparticles can advance the pharmacological and therapeutic properties of chemotherapeutic agents by controlling release rates and targeted delivery process, which eliminates the limitations of conventional anti-cancer therapies and they are also safe as well as cost-effective. The aim of present study is to explore the anti-tumour effect of niclosamide in lung and breast cancer cell lines using biocompatible and biodegradable carrier where nanoparticles loaded with hydrophobic drug (niclosamide) were synthesized, characterized and applied as a stable anti-cancer agent. Niclosamide loaded chitosan nanoparticles (Nic-Chi Np's) of size approximately 100–120 nm in diameter containing hydrophobic anti-cancer drug, i.e. niclosamide, were prepared. Physico-chemical characterization confirms that the prepared nanoparticles are spherical, monodispersed and stable in aqueous systems. The therapeutic efficacy of Nic-Chi Np's was evaluated against breast cancer cell line (MCF-7) and human lung cancer cell line (A549). MTT assay reveals the cell viability of the prepared Nic-Chi Np's against A549 and MCF-7 cells and obtained an IC50 value of 8.75 µM and 7.5 µM, respectively. Acridine orange/ethidium bromide dual staining results verified the loss of the majority of the cells by apoptosis. Flow cytometer analysis quantified the generation of intracellular reactive oxygen species (ROS) and signified that exposure to a higher concentration (2 × IC50) of Nic-Chi Np's resulted in elevated ROS generation. Notably, Nic-Chi Np treatment showed more apoptosis and cell death in MCF-7 as compared to A549. Further, the remarkable induction of apoptosis by Nic-Chi Np's was confirmed by semi-quantitative reverse transcription polymerase chain reaction, scanning electron microscopy and cell-cycle analysis. Thus, Nic-Chi Np's may have a great potential even at low concentration for anti-cancer therapy and may replace or substitute more toxic anti-mitotic drugs in the near future