Effect of nano-curcumin supplementation on angina status, and traditional and novel cardiovascular risk factors in overweight or obese patients with coronary slow flow phenomenon: a randomized double-blind placebo-controlled clinical trial.

BACKGROUND: Cardiovascular events and poor quality of life are frequently observed in patients with coronary slow flow phenomenon (CSFP). This trial evaluated the effect of nano-curcumin supplement containing curcuminoids, as multifunctional nutraceuticals, on angina status, and some traditional and novel cardiovascular risk factors in overweight or obese patients with CSFP. METHODS: In this double-blind, randomized, placebo-controlled clinical trial, 42 overweight or obese patients with CSFP received either 80 mg/day of nano-curcumin or placebo for 12 weeks. Seattle angina questionnaire (SAQ) as a clinical measure of angina status, circulating endocan, adropin, homocysteine, lipid profile, and the novel scores of visceral adiposity index (VAI) and waist-triglyceride index (WTI) were assessed before and after the intervention. The independent samples t-test, Mann-Whitney test, analysis of covariance, Chi-square, and Fisher's exact tests were used where appropriate. RESULTS: All domains of SAQ including physical limitation, angina stability, angina frequency-severity, treatment satisfaction, and disease perception and quality of life improved significantly in the nano-curcumin compared with the placebo group. No significant changes were observed in serum endocan, adropin, and homocysteine following the intervention. Triglycerides, triglyceride/high-density lipoprotein cholesterol ratio, WTI and VAI values improved significantly only within the nano-curcumin group. CONCLUSIONS: Supplementation with 80 mg/day nano-curcumin (containing curcuminoids) for 12 weeks significantly improved clinically important disease-specific aspects of health in patients with CSFP. Some traditional and novel cardiovascular risk factors improved significantly only compared with the baseline values, which need further investigation. TRIAL REGISTRATION: This study was approved by the Ethics Committee of Tehran University of Medical Sciences (IR.TUMS.VCR.REC.1398.794). The study protocol was registered at Iranian Registry of Clinical Trials by IRCT20131125015536N8 registration ID at 19.06.2019.

Opportunities and challenges of artificial intelligence and distributed systems to improve the quality of healthcare service.

The healthcare sector, characterized by vast datasets and many diseases, is pivotal in shaping community health and overall quality of life. Traditional healthcare methods, often characterized by limitations in disease prevention, predominantly react to illnesses after their onset rather than proactively averting them. The advent of Artificial Intelligence (AI) has ushered in a wave of transformative applications designed to enhance healthcare services, with Machine Learning (ML) as a noteworthy subset of AI. ML empowers computers to analyze extensive datasets, while Deep Learning (DL), a specific ML methodology, excels at extracting meaningful patterns from these data troves. Despite notable technological advancements in recent years, the full potential of these applications within medical contexts remains largely untapped, primarily due to the medical community's cautious stance toward novel technologies. The motivation of this paper lies in recognizing the pivotal role of the healthcare sector in community well-being and the necessity for a shift toward proactive healthcare approaches. To our knowledge, there is a notable absence of a comprehensive published review that delves into ML, DL and distributed systems, all aimed at elevating the Quality of Service (QoS) in healthcare. This study seeks to bridge this gap by presenting a systematic and organized review of prevailing ML, DL, and distributed system algorithms as applied in healthcare settings. Within our work, we outline key challenges that both current and future developers may encounter, with a particular focus on aspects such as approach, data utilization, strategy, and development processes. Our study findings reveal that the Internet of Things (IoT) stands out as the most frequently utilized platform (44.3 %), with disease diagnosis emerging as the predominant healthcare application (47.8 %). Notably, discussions center significantly on the prevention and identification of cardiovascular diseases (29.2 %). The studies under examination employ a diverse range of ML and DL methods, along with distributed systems, with Convolutional Neural Networks (CNNs) being the most commonly used (16.7 %), followed by Long Short-Term Memory (LSTM) networks (14.6 %) and shallow learning networks (12.5 %). In evaluating QoS, the predominant emphasis revolves around the accuracy parameter (80 %). This study highlights how ML, DL, and distributed systems reshape healthcare. It contributes to advancing healthcare quality, bridging the gap between technology and medical adoption, and benefiting practitioners and patients.

Associations between food insecurity and Sleep Duration, Quality, and Disturbance among older adults from six low- and middle-income countries.

OBJECTIVES: Although food insecurity has been associated with poor sleep outcomes in young and middle-aged adults, few studies have examined this relationship in older adults. This study aimed to examine the relationship between food insecurity and sleep duration, quality, and disturbance among older adults in six low-income countries (LMICs). DESIGN AND SETTING: We analyzed nationally representative cross-sectional data from 33,460 adults (≥50 years) from the Study on global AGEing and adult health (SAGE). MEASUREMENTS: Food insecurity (FI) was assessed using two questions regarding the frequency of eating less and hunger caused by a lack of food. Sleep outcomes included self-reported sleep duration, sleep quality, and sleep disturbances (difficulty falling asleep, frequent sleep interruptions, and early awakening) assessed based on self-reports over two nights. Multivariable logistic regression was used to assess country-specific relationships between food insecurity and sleep outcomes, and random-effects models were used to estimate pooled associations. RESULTS: The prevalence of FI among older adults in the overall population was 16.2%. In pooled analyses, FI was significantly associated with long sleep duration ≥ 9 h (OR=1.58, 95% CI: 1.30 to 1.93; P=0.001). There were also significant pooled associations between FI and poor sleep quality (OR=1.34, 95% CI: 1.14 to 1.56; P < 0.001) and sleep disturbances (OR=1.44, 95% CI: 1.08 to 1.91; P = 0.014). CONCLUSIONS: In conclusion, the current study found that FI is adversely associated with sleep duration, quality and disturbances in older adults, with some heterogeneity by country. The findings suggest food policies and intervention programs are needed for vulnerable households.

In silico study of the impact of oxidation on pyruvate transmission across the hVDAC1 protein channel.

The overexpression of voltage dependent anion channels (VDACs), particularly VDAC1, in cancer cells compared to normal cells, plays a crucial role in cancer cell metabolism, apoptosis regulation, and energy homeostasis. In this study, we used molecular dynamics (MD) simulations to investigate the effect of a low level of VDAC1 oxidation (induced e.g., by cold atmospheric plasma (CAP)) on the pyruvate (Pyr) uptake by VDAC1. Inhibiting Pyr uptake through VDAC1 can suppress cancer cell proliferation. Our primary target was to study the translocation of Pyr across the native and oxidized forms of hVDAC1, the human VDAC1. Specifically, we employed MD simulations to analyze the hVDAC1 structure by modifying certain cysteine residues to cysteic acids and methionine residues to methionine sulfoxides, which allowed us to investigate the effect of oxidation. Our results showed that the free energy barrier for Pyr translocation through the native and oxidized channel was approximately 4.3 ± 0.7 kJ mol-1 and 10.8 ± 1.8 kJ mol-1, respectively. An increase in barrier results in a decrease in rate of Pyr permeation through the oxidized channel. Thus, our results indicate that low levels of CAP oxidation reduce Pyr translocation, resulting in decreased cancer cell proliferation. Therefore, low levels of oxidation are likely sufficient to treat cancer cells given the inhibition of Pyr uptake.

The applications of machine learning techniques in medical data processing based on distributed computing and the Internet of Things.

Medical data processing has grown into a prominent topic in the latest decades with the primary goal of maintaining patient data via new information technologies, including the Internet of Things (IoT) and sensor technologies, which generate patient indexes in hospital data networks. Innovations like distributed computing, Machine Learning (ML), blockchain, chatbots, wearables, and pattern recognition can adequately enable the collection and processing of medical data for decision-making in the healthcare era. Particularly, to assist experts in the disease diagnostic process, distributed computing is beneficial by digesting huge volumes of data swiftly and producing personalized smart suggestions. On the other side, the current globe is confronting an outbreak of COVID-19, so an early diagnosis technique is crucial to lowering the fatality rate. ML systems are beneficial in aiding radiologists in examining the incredible amount of medical images. Nevertheless, they demand a huge quantity of training data that must be unified for processing. Hence, developing Deep Learning (DL) confronts multiple issues, such as conventional data collection, quality assurance, knowledge exchange, privacy preservation, administrative laws, and ethical considerations. In this research, we intend to convey an inclusive analysis of the most recent studies in distributed computing platform applications based on five categorized platforms, including cloud computing, edge, fog, IoT, and hybrid platforms. So, we evaluated 27 articles regarding the usage of the proposed framework, deployed methods, and applications, noting the advantages, drawbacks, and the applied dataset and screening the security mechanism and the presence of the Transfer Learning (TL) method. As a result, it was proved that most recent research (about 43%) used the IoT platform as the environment for the proposed architecture, and most of the studies (about 46%) were done in 2021. In addition, the most popular utilized DL algorithm was the Convolutional Neural Network (CNN), with a percentage of 19.4%. Hence, despite how technology changes, delivering appropriate therapy for patients is the primary aim of healthcare-associated departments. Therefore, further studies are recommended to develop more functional architectures based on DL and distributed environments and better evaluate the present healthcare data analysis models.

The relationship of circulating neuregulin 4 and irisin, and traditional and novel cardiometabolic risk factors with the risk and severity of coronary artery disease.

BACKGROUND AND AIMS: Neuregulin 4 (NRG4) and irisin are adipokines that have been suggested to be associated with cardiometabolic risk factors and coronary artery disease (CAD), but the data are inconclusive. This study aimed to investigate the relationship between circulating NRG4 and irisin and cardiometabolic risk factors with CAD risk and severity. METHODS AND RESULTS: In this cross-sectional study, the presence of CAD and the severity of stenosis (gensini score) were documented based on coronary angiography in 166 adults. Circulating NRG4 and irisin, glucose homeostasis markers, hs-CRP, lipid profiles, blood pressure, and anthropometric measurements were assessed as well. Age (p = 0.005), sex (p = 0.008), SBP (p = 0.033), DBP (p = 0.04), MAP (p = 0.018), FBG (p = 0.012), insulin (p = 0.039) and HOMA-IR (p = 0.01) were significantly associated with odds of having CAD. The final logistic regression model showed that age, sex, HOMA-IR, and MAP were the most important determinants of having CAD. There were no significant associations between circulating irisin and NRG4 with odds of having CAD. The final general linear model showed that being men (ß = 17.303, 95% CI: 7.086-27.52, P = 0.001), age (Aß = 0.712, 95% CI: 0.21-1.214, P = 0.006), HOMA-IR (Aß = 2.168, 95% CI: 0.256 to 4.079, P = 0.027), and NRG4 level (ß = 1.836, 95% CI: 0.119-3.553, P = 0.036) were directly associated with higher gensini score. Participants with the three-vessel disease had a mean increase of about 5 units in circulating irisin compared to those with no clinical CAD (ß = 5.221, 95% CI: 0.454-9.987, p = 0.032). CONCLUSIONS: This study showed that the adipokines NRG4 and Irisin might be associated with the severity of coronary stenosis.

A new lung cancer detection method based on the chest CT images using Federated Learning and blockchain systems.

With an estimated five million fatal cases each year, lung cancer is one of the significant causes of death worldwide. Lung diseases can be diagnosed with a Computed Tomography (CT) scan. The scarcity and trustworthiness of human eyes is the fundamental issue in diagnosing lung cancer patients. The main goal of this study is to detect malignant lung nodules in a CT scan of the lungs and categorize lung cancer according to severity. In this work, cutting-edge Deep Learning (DL) algorithms were used to detect the location of cancerous nodules. Also, the real-life issue is sharing data with hospitals around the world while bearing in mind the organizations' privacy issues. Besides, the main problems for training a global DL model are creating a collaborative model and maintaining privacy. This study presented an approach that takes a modest amount of data from multiple hospitals and uses blockchain-based Federated Learning (FL) to train a global DL model. The data were authenticated using blockchain technology, and FL trained the model internationally while maintaining the organization's anonymity. First, we presented a data normalization approach that addresses the variability of data obtained from various institutions using various CT scanners. Furthermore, using a CapsNets method, we classified lung cancer patients in local mode. Finally, we devised a way to train a global model cooperatively utilizing blockchain technology and FL while maintaining anonymity. We also gathered data from real-life lung cancer patients for testing purposes. The suggested method was trained and tested on the Cancer Imaging Archive (CIA) dataset, Kaggle Data Science Bowl (KDSB), LUNA 16, and the local dataset. Finally, we performed extensive experiments with Python and its well-known libraries, such as Scikit-Learn and TensorFlow, to evaluate the suggested method. The findings showed that the method effectively detects lung cancer patients. The technique delivered 99.69 % accuracy with the smallest possible categorization error.

Effects of Calorie Restricted Diet on Oxidative/Antioxidative Status Biomarkers and Serum Fibroblast Growth Factor 21 Levels in Nonalcoholic Fatty Liver Disease Patients: A Randomized, Controlled Clinical Trial.

Oxidative stress plays a fundamental role in the development and progression of nonalcoholic fatty liver disease (NAFLD). This study aimed to investigate the effects of a calorie-restricted (CR) diet on oxidative/anti-oxidative status in patients with NAFLD and the potential mediating role of fibroblast growth factor 21 (FGF-21) in this regard. This randomized, controlled clinical trial was carried out on sixty patients with NAFLD aged 20 to 60 years with body mass index (BMI) ranging from 25 to 35 kg/m2. Participants were randomly assigned to either the CR diet group (received a prescribed low-calorie diet for twelve weeks, n = 30) or the control group (n = 30). Fasting blood samples, anthropometric measurements, dietary intake, and physical activity data were collected for all participants at baseline and at the end of the trial. Significant reductions in weight, BMI, waist circumference, and serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were observed in the CR diet group compared to the control group (all p < 0.05). Liver steatosis grade, serum levels of malondialdehyde (MDA), total antioxidant capacity (TAC), and FGF-21, as well as erythrocyte superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities did not show significant changes in the CR group when compared to the controls at the end of the study (p > 0.05). CR diet with moderate weight loss has some favorable effects on NAFLD but was not able to modify oxidative/anti-oxidative status in these patients. Future studies are warranted to target the effects of long-term interventions with a greater weight loss in this patient population.

Porous nanoparticles with engineered shells release their drug cargo in cancer cells.

Highly porous nanoscale metal-organic frameworks (nanoMOFs) attract growing interest as drug nanocarriers. However, engineering "stealth" nanoMOFs with poly(ethylene glycol) (PEG) coatings remains a main challenge. Here we address the goal of coating nanoMOFs with biodegradable shells using novel cyclodextrin (CD)-based oligomers with a bulky structure to avoid their penetration inside the open nanoMOF porosity. The PEG chains were grafted by click chemistry onto the CDs which were further crosslinked by citric acid. Advantageously, the oligomers' free citrate units allowed their spontaneous anchoring onto the nanoMOFs by complexation with the iron sites in the top layers. Up to 31 wt% oligomers could be firmly attached by simple incubation with the nanoMOFs in an aqueous medium. Moreover, the anticancer drug doxorubicin (DOX) was successfully entrapped in the core-shell nanoMOFs with loadings up to 41 wt%. High resolution STEM (HR-STEM) showed that the organized crystalline structures were preserved. Remarkably, at the highest loadings, DOX was poorly released out of the nanoMOFs at pH 7.4 (<2% in 2 days). In contrast, around 80% of DOX was released out at pH 4.5 of artificial lysosomal fluid in 24 h. Confocal microscopy investigations showed that the DOX-loaded nanoMOFs penetrated inside Hela cancer cell together with their PEG shells. There, they released the DOX cargo which further diffused inside the nucleus to eradicate the cancer cells.

Fast antibody responses by immuno-targeting and nanotechnology strategies versus HBsAg vaccine.

OBJECTIVES: Though immunization with HBsAg has been routine since the 1980s, it has numerous limitations such as low or none humoral immune responses. Today, nanotechnology is used in vaccinology to achieve higher potency. The present study deals with the achievement of fast antibody response of humoral immune responses using immune-targeting through mannosylated nanocarriers of the vaccine. MATERIALS AND METHODS: Mannose sugar and HBsAg were attached to the surface of iron oxide nanoparticles. Mannosylated iron oxide nanoparticles conjugated HBsAg (HBsAg +MLCMNP), iron oxide nanoparticles conjugated HBsAg (HBsAg +LCMNP), hepatitis B vaccine, and mere HBsAg were injected twice to BALB/c mice subcutaneously, while suitable control groups were considered. Specific total IgG antibodies were evaluated on the 7th and 14th days after the final immunization. The avidity maturation of the humoral immune response was assessed with an optimized ELISA. Graph pad prism software was used to analyze statistical data. RESULTS: Results showed that on the seventh day of the final shooting, the mannosylated nano-vaccine caused higher antibody response induction than nano-vaccine without mannose and commercial vaccine groups. After 14 days of the second injection, a significant difference was seen versus the nano-vaccine without mannose but not the commercial vaccine group. In addition, the avidity index in mannosylated nano-vaccine showed a significant increase compared with the nano-vaccine without mannose and mere HBsAg group but not compared with the commercial vaccine. CONCLUSION: It seems that mannosylated nano-vaccine has more potency to achieve fast antibody responses and also higher quality of humoral immune response.

SN38 loaded nanostructured lipid carriers (NLCs); preparation and in vitro evaluations against glioblastoma.

SN38 is the active metabolite of irinotecan with 1000-fold greater cytotoxicity compared to the parent drug. Despite the potential, its application as a drug is still seriously limited due to its stability concerns and low solubility in acceptable pharmaceutical solvents. To address these drawbacks here nanostructured lipid carrier (NLC) containing SN38 was prepared and its cytotoxicity against U87MG glioblastoma cell line was investigated. The formulations were prepared using hot ultrasonication and solvent evaporation/emulsification methods. NLCs with a mean size of 140 nm and particle size distribution (PDI) of 0.25 were obtained. The average loading efficiency was 9.5% and its entrapment efficiency was 81%. In order to obtain an accurate determination of released amount of SN38 a novel medium and extraction method was designed, which lead to an appropriate in vitro release profile of the drug from the prepared NLCs. The MTT test results revealed the significant higher cytotoxicity of NLCs on U87MG human glioblastoma cell line compared with the free drug. The confocal microscopy images confirmed the proper penetration of the nanostructures into the cells within the first 4 h. Consequently, the results indicated promising potentials of the prepared NLCs as a novel treatment for glioblastoma.

White adipose tissue browning in critical illness: A review of the evidence, mechanisms and future perspectives.

Observational studies suggest better clinical outcomes following critical illness in patients with overweight and obesity (obesity paradox). An understanding of the morphologic, physiologic and metabolic changes in adipose tissue in critical illness may provide an explanation. Recent studies have demonstrated the transformation of white to brown-like adipocytes due to the "browning process," which has been of interest as a potential novel therapy in obesity during the last decade. The characteristics of the browning of white adipose tissue (WAT) include the appearance of smaller, multilocular adipocytes, increased UCP1 mRNA expression, mitochondrial density and respiratory capacity. These changes have been identified in some critical illnesses, which specifically refers to burns, sepsis and cancer cachexia in this study. The pathophysiological nature of WAT browning, underlying mechanisms, main regulators and potential benefits and harms of this process are interesting new areas that warrants further investigations. In this review, we discuss emerging scientific discipline of adipose tissue physiology in metabolic stress, available data, gaps of knowledge and future perspectives. Future investigations in this field may provide insights into the underlying mechanisms and clinical aspects of browning that may further our understanding of the proposed obesity paradox following critical illness, which may in turn open up opportunities for novel therapies to save lives and improve recovery.

Evaluating pre- and post-operation plasma miRNAs of papillary thyroid carcinoma (PTC) patients in comparison to benign nodules.

BACKGROUND: Thyroid cancer is the most common endocrinology cancer that its incidence has increased in recent decades. miRNAs are new biomarkers in recent studies in the diagnosis and follow-up of these patients. METHODS: Blood and thyroid tissue samples were obtained from two groups of included patients (PTC and benign nodules), pre- and post-operation. miRNAs were extracted from these plasma samples and were measured quantitatively. After cDNA synthesis, qPCR was carried out. Then tissue samples were investigated, and their relation to miR expression was studied. These results were analyzed by paired- and independent samples t-test, and non-parametric tests. RESULTS: miR-222 and miR-181a declined in PTC patients before and after surgery, significantly (P < 0.001 for both groups), with no significant difference in control group before and after surgery (P = 0.61 for miR-222 and P = 0.06 for miR-181a). The difference between the two groups, pre-and post-operation, was statistically significant (P = 0.01 for miR-222 and P < 0.001 for miR-181a). Comparing case and control groups, pre- and post-operatively, yielded no significant difference, in miR-155-5p levels (P = 0.61 and P = 0.53, respectively). Comparing PTC and control groups before surgery showed a significant difference (P = 0.01), while no significant difference was observed comparing them after surgery, in miR146-a (P = 0.27). Our results depicted a higher miR-155-5p and miR-146a expression before surgery than after it (P < 0.001 in both groups, for both miRs). We found a significant relationship between miR-222 and BRAFV600E mutation and significantly higher levels of miR-181a with increasing tumor size in PTC patients. CONCLUSION: miR-222 showed overexpression in all PTC cases, which is indicative of a relation between miRNA and PTC. Also, comparing miR-181 and miR-146a showed a significant difference between cancerous and benign cases. miR-155-5p as an inflammatory factor, showed no significant changes, comparing two groups.

HBs antigen and mannose loading on the surface of iron oxide nanoparticles in order to immuno-targeting: fabrication, characterization, cellular and humoral immunoassay.

Mannosylation of nanovaccine is an appropriate strategy for targeting the mannose receptors on DCs. Here, HBsAg and mannose loaded on the surface of iron oxide nanoparticles to increases HBsAg vaccine potency. Nanoparticles are made by co-precipitation method and bonded to the HBsAg and mannose by chemical bonding. The physicochemical properties of nano-vaccines, their toxicity and antigenicity were determined. The synthesized nano-vaccine showed spherical shape with a mean particle size of 60 nm, a zeta potential of -44 mV, an antigen-binding efficiency of around 100% and for mannose 78%. In vitro release of nanoparticles exhibited about 30% at the first day and about 60% until the third day. SDSPAGE analysis confirmed structural integrity of HBsAg loaded on nanoparticles. The HBsAg-loaded LCMNP and MLCMNP nanoparticles had no toxic effects on HEK293 cell line. The quantification of the intracellular Fe by ICP-OES as a criterion of nano-vaccine uptake revealed mannose intensify uptake of MLCMNP. In addition, mannose in the structure of MLCMNP improved IL-6, TNF-α and IFN-γ (>16 fold) cytokines genes expression by macrophage/dendritic cells after exposure in 12 h. Immunization of experimental mice (subcutaneously, two times with 2-week intervals) with 5 µg of HBsAg loaded on MLCMNP nanoparticles increased specific total IgG and IgG2a/IgG1 ratio. In addition, TNF-α, IL-12, IL-2 and IL-4 cytokines in mannosylated nano-vaccine increased versus nano-vaccine group while lymphocyte proliferation and IFN-γ responses in the targeted nano-vaccine group show a tiny increase versus the nano-vaccine group. The results show that mannosylated nano-vaccine promotes higher level of cellular and humoural immune responses against HBsAg nano-vaccine.

Design and Synthesis of a Biocompatible 1D Coordination Polymer as Anti-Breast Cancer Drug Carrier, 5-Fu: In Vitro and in Vivo Studies.

Designable coordination polymers with suitable chemical diversities and biocompatible structures have been proposed as a promising class of vehicles for drug delivery systems. Here, we hydrothermally synthesized a novel one-dimensional (1D) coordination polymer, [Zn(H2O)6K2(H2BTC)2(H2O)4](H2BTC)2·2H2O, where H3BTC = benzene-1,3,5-tricarboxylic acid (trimesic acid), cp.1. As the hydrogen bonds stabilized 1D chains in three dimensions, the cp.1 could be a good candidate for delivering small-molecule chemotherapeutics such as 5-fluorouracil (5-Fu). The synthesized cp.1 showed a remarkable 5-Fu loading of 66% with encapsulation efficiency of 98% and almost complete release process. The 5-Fu-loaded cp.1 displayed a time-dependent cytotoxicity effect against breast cancer cell lines MCF-7 and 4T1. The cellular uptake of cp.1 particles was investigated via confocal laser scanning microscopy using fluorescein isothiocyanate and LysoTracker Red staining. Furthermore, the in vivo antitumor impact of 5-Fu-loaded cp.1 was studied on 4T1 breast cancer BALB/c mice model. The intratumor treatment of 5-Fu-loaded cp.1 demonstrated beneficial antitumor efficacy by postponing tumor growth. These results suggest that the 5-Fu-loaded cp.1 microparticles with a great locoregional delivery can be efficient anticancer drug carriers for further clinical treatments.

Global spectral graph wavelet signature for surface analysis of carpal bones.

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

NanoMIL-100(Fe) containing docetaxel for breast cancer therapy.

Metal-organic frameworks, such as MIL-100, have been recently introduced as promising drug carriers due to their notable characteristics such as stability, biocompatibility and owning large porosity which may admit a broad range of drugs with different molecular sizes. In this study, we firstly proposed an accessible top-down approach using ultrasound method to prepare nanoMIL-100 and secondly, evaluated its potentials as an anticancer nanocarrier. This is the first report that docetaxel (DTX) as a highly hydrophobic anticancer drug was encapsulated in nanoMIL-100 with the drug payload of 57.2 wt%. Characterizations of the prepared nanoMIL-100 and DTX-loaded nanoMIL-100 were performed by PXRD, FT-IR, N2 adsorption, DLS and FE-SEM. Moreover, the drug loading and release processes were quantified by HPLC. The in vitro release of DTX from the prepared nanocarrier was investigated in two pH values, 7.4 and 5.5. The toxic effect of DTX-loaded nanoMIL-100 was examined on human breast cancer cell line, MCF-7, and a significant decrease was observed in IC50 value (0.198 µg/mL) at the first 24 h in comparison with the free drug (4.9908 µg/mL). This nanocarrier may, thus offer promising potentials as a novel cytotoxic drug delivery system.

Stroke subtypes, risk factors and mortality rate in northwest of Iran.

Background: Stroke is the second most common cause of death and first cause of disability in adults in the world. About 80% of all stroke deaths occur in developing countries. So far, the data on stroke epidemiology have been limited in Iran. Therefore, this study was focused on stroke demographic data, risk factors, types and mortality. Methods: A retrospective study was done in two university tertiary referral hospitals in Tabriz, northwest of Iran, from March 2008 to April 2013. Patients diagnosed with stroke were enrolled in the study. Demographic data, stroke subtypes, duration of hospitalization, stroke risk factors and hospital mortality rate were recorded for all the patients. Results: A total number of 5355 patients were evaluated in the present study. Mean age of the patients was 67.5 ± 13.8 years, and 50.6% were men. Final diagnosis of ischemic stroke was made in 76.5% of the patients, intra-cerebral hemorrhage (ICH) with or without intra-ventricular hemorrhage (IVH) in 14.3% and subarachnoid hemorrhage (SAH) in 9.2%. Stroke risk factors among the patients were hypertension in 68.8% of the patients, diabetes mellitus (DM) in 23.9%, smoking in 12.6% and ischemic heart diseases (IHD) in 17.1%. Mean hospital stay was 17.3 days. Overall, the in-hospital mortality was 20.5%. Conclusion: Compared to other studies, duration of hospital stay was longer and mortality rate was higher in this study. Hypertension was the most common risk factor and cardiac risk factors and DM had relatively lower rate in comparison to other studies. Because of insufficient data on the epidemiology, patterns, and risk factors of stroke in Iran, there is a necessity to develop and implement a national registry system.

In Silico Analysis of L1/L2 Sequences of Human Papillomaviruses: Implication for Universal Vaccine Design.

The aim of this study was to design a multiepitope universal vaccine for major human papillomavirus (HPV) structural proteins, L1/L2, by bioinformatics models. For this purpose, we predicted the most probable immunogenic epitopes of L1 and L2 from common high-risk HPV 16, 18, 31, and 45 beside high prevalent type 6 and 11 based on BCPREDS defaulted model, while solvent accessibility of structure was extrapolated. The three-dimensional molecular model of L1 protein was constructed by Swiss Model server, whereas sequence alignment provided model for prediction of L2 protein epitopes. After that, N-glycosylation sites were excluded from estimated epitope regions. Then, by other bioinformatics analyses, 20 epitopes were selected and fused in tandem repeats, reverse translated, and codon optimized to relevant sequence. The final protein parameters such as antigenicity were analyzed by protean program. Evaluation of new recombinant protein sequence indicated a molecular weight of 41.8 kDa with 400 amino acids beside positive charge. The computed isoelectric point (pI) value indicated the acidic nature of final product. The aliphatic index showed low thermal stability of this construct and the Grand Average Hydropathicity value was negative (-0.494). Analyzed plot showed that major parts of new protein construct had hydrophilic property, thus harboring antigenic potency. After all, sequence of final construct reverse translated to DNA and this codon-optimized sequence showed Codon Adaptation Index (CAI) of >0.8 for expression in Escherichia coli. Finally, this sequence ligated into pET28a bacterial expression vector. The new recombinant proteins harboring 20 B cell epitope seem to be suitable antigens based on computational methods as a universal vaccine candidate for HPVs.