Long non-coding RNAs and their targets as potential biomarkers in breast cancer

Breast cancer is among the lethal types of cancer with a high mortality rate, globally. Its high prevalence can be controlled through improved analysis and identification of disease-specific biomarkers. Recently, long non-coding RNAs (lncRNAs) have been reported as key contributors of carcinogenesis and regulate various cellular pathways through post-transcriptional regulatory mechanisms. The specific aim of this study was to identify the novel interactions of aberrantly expressed genetic components in breast cancer by applying integrative analysis of publicly available expression profiles of both lncRNAs and mRNAs. Differential expression patterns were identified by comparing the breast cancer expression profiles of samples with controls. Significant co-expression networks were identified through WGCNA analysis. WGCNA is a systems biology approach used to elucidate the pattern of correlation between genes across microarray samples. It is also used to identify the highly correlated modules. The results obtained from this study revealed significantly differentially expressed and co-expressed lncRNAs and their cis- and trans-regulating mRNA targets which include RP11-108F13.2 targeting TAF5L, RPL23AP2 targeting CYP4F3, CYP4F8 and AL022324.2 targeting LRP5L, AL022324.3, and Z99916.3, respectively. Moreover, pathway analysis revealed the involvement of identified mRNAs and lncRNAs in major cell signalling pathways, and target mRNAs expression is also validated through cohort data. Thus, the identified lncRNAs and their target mRNAs represent novel biomarkers that could serve as potential therapeutics for breast cancer and their roles could also be further validated through wet labs to employ them as potential therapeutic targets in future.

Anti-Neuroinflammatory Potential of Polyphenols by Inhibiting NF-κB to Halt Alzheimer's Disease

Alzheimer's disease (AD) is an irrevocable chronic brain disorder featured by neuronal loss, microglial accumulation, and progressive cognitive impairment. The proper pathophysiology of this life-threatening disorder is not completely understood and no exact remedies have been found yet. Over the last few decades, research on AD has mainly highlighted pathomechanisms linked to a couple of the major pathological hallmarks, including extracellular senile plaques made of amyloid-β (Aβ) peptides, and intracellular neurofibrillary tangles (NFTs) made of tau proteins. Aβ can induce apoptosis, trigger an inflammatory response, and inhibit the synaptic plasticity of the hippocampus, which ultimately contributes to reducing cognitive functions and memory impairment. Recently, a third disease hallmark, the neuroinflammatory reaction that is mediated by cerebral innate immune cells, has become a spotlight in the current research area, assured by pre-clinical, clinical, and genetic investigations. Nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), a cytokine producer, is significantly associated with physiological inflammatory proceedings and thus shows a promising candidate for inflammation- based AD therapy. Recent data reveal that phytochemicals, mainly polyphenol compounds, exhibit potential neuroprotective functions and these may be considered as a vital resource for discovering several drug candidates against AD. Interestingly, phytochemicals can easily interfere with the signaling pathway of NF-κB. This review represents the anti-neuroinflammatory potential of polyphenols as inhibitors of NF-κB to combat AD pathogenesis.

Petri Net modelling approach for analysing the behaviour of [inline-formula removed] and Ca2+ signalling pathways in arrhythmogenic right ventricular cardiomyopathy

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart muscle disease that may result in arrhythmia, heart failure and sudden death. The hallmark pathological findings are progressive myocyte loss and fibro fatty replacement, with a predilection for the right ventricle. This study focuses on the adipose tissue formation in cardiomyocyte by considering the signal transduction pathways including Wnt/[inline-formula removed]-catenin and Wnt/Ca²⁺ regulation system. These pathways are modelled and analysed using stochastic petri nets (SPN) in order to increase our comprehension of ARVC and in turn its treatment regimen. The Wnt/[inline-formula removed]-catenin model predicts that the dysregulation or absence of Wnt signalling, inhibition of dishevelled and elevation of glycogen synthase kinase 3 along with casein kinase I are key cytotoxic events resulting in apoptosis. Moreover, the Wnt/Ca²⁺ SPN model demonstrates that the Bcl2 gene inhibited by c-Jun N-terminal kinase protein in the event of endoplasmic reticulum stress due to action potential and increased amount of intracellular Ca²⁺ which recovers the Ca²⁺ homeostasis by phospholipase C, this event positively regulates the Bcl2 to suppress the mitochondrial apoptosis which causes ARVC.

Comparison of Different Bat Initialization Techniques for Global Optimization Problems

Bat algorithm (BA) is a population-based stochastic search technique that has been widely used to solve the diverse kind of optimization problems. Population initialization is the current ongoing research problem in evolutionary computing algorithms. Appropriate population initialization assists the algorithm to investigate the swarm search space effectively. BA faces premature convergence problem to find actual global optimization value. Low discrepancy sequences are slightly lesser random number than pseudo-random; however, they are more powerful for computational approaches. In this work, new population initialization approach Halton (BA-HA), Sobol (BA-SO), and Torus (BA-TO) are proposed, which helps bats to avoid from the premature convergence. The proposed approaches are examined on standard benchmark functions, and simulation results are compared with standard BA initialized with uniform distribution. The results depict that substantial enhancement can be attained in the performance of standard BA while varying the random numbers sequences to low discrepancy sequences.

Hot Topics in Breast Surgery

Since the first implant-based breast surgeries were performed nearly 70 years ago, breast augmentation it has changed drastically. As understanding of breast augmentation has advanced, so too have the technologies and techniques used to improve results and minimize the risk of complications in breast implant surgery. This article reviews some of the novel techniques and technologies used today in breast augmentation surgery. How these tools and techniques will withstand the test of time remains to be seen, but they no doubt will add to the fascinating and ever-evolving history of breast augmentation.

Synthesis and characterization of titanium dioxide nanoparticles by chemical and green methods and their antifungal activities against wheat rust

The production of metallic nanoparticles (NPs) by green and ecofriendly methods has received consideration during the recent past. The present study summarized the comparative production of titanium dioxide (TiO₂) NPs by plant extracts of Trianthema portulacastrum (T2) and Chenopodium quinoa (T3) and by conventional chemical (sol-gel) method (T1). Synthesized TiO₂-NPs were examined by high-tech. techniques such as X-Ray Diffraction (XRD), Fourier Transmission Infra-red (FT-IR) spectroscopy, Scanning Electron Microscopy (SEM) with Energy Dispersive X-ray (EDX) spectroscope, SEM-EDS spot analysis and elemental mapping. Synthesized TiO₂-NPs were applied on wheat rust (Ustilago tritici) for the evaluation of their antifungal activity against toxic plant pathogens. XRD results confirmed the (2θ) peak at 25.3 related to 101 anatase form. EDS-spot analysis and elemental mapping confirms the formation of TiO₂-NPs by using these techniques. SEM secondary electrons (SEs) images demonstrated the nano range of particles in cluster form with fewer porous structures. The average size of all three TiO₂-NPs was found less than 15 nm. FT-IR analysis of all three TiO₂-NPs perfectly matched with the standard parameters. The NPs prepared by both sol-gel and green methods have a good antifungal response against U. tritici, and the green prepared TiO₂-NPs were found to have the best antifungal activity against wheat rust especially NPs synthesized with the extract of C. quinoa. Overall, green method can be used for the large scale and less toxic synthesis of TiO₂-NPs because of their wide range of environmental applications.

An Overview of Mutation Strategies in Particle Swarm Optimization

The Particle swarm optimization (PSO) algorithm is a population-based intelligent stochastic search technique encouraged from the intrinsic manner of bee swarm seeking for their food source. With flexibility for numerical experimentation, the PSO algorithm has been mostly used to resolve diverse kind of optimization problems. The PSO algorithm is frequently captured in local optima meanwhile handling the complex real-world problems. Many authors improved the standard PSO algorithm with different mutation strategies but an exhausted comprehensive overview about mutation strategies is still lacking. This article aims to furnish a concise and comprehensive study of problems and challenges that prevent the performance of the PSO algorithm. It has tried to provide guidelines for the researchers who are active in the area of the PSO algorithm and its mutation strategies. The objective of this study is divided into two sections: primarily to display the improvement of the PSO algorithm with mutation strategies that may enhance the performance of the standard PSO algorithm to great extent and secondly, to motivate researchers and developers to use the PSO algorithm to solve the complex real-world problems. This study presents a comprehensive survey of the various PSO algorithms based on mutation strategies. It is anticipated that this survey would be helpful to study the PSO algorithm in detail for researchers.

Disease Detection in Plum Using Convolutional Neural Network under True Field Conditions

The agriculture sector faces crop losses every year due to diseases around the globe, which adversely affect food productivity and quality. Detecting and identifying plant diseases at an early stage is still a challenge for farmers, particularly in developing countries. Widespread use of mobile computing devices and the advancements in artificial intelligence have created opportunities for developing technologies to assist farmers in plant disease detection and treatment. To this end, deep learning has been widely used for disease detection in plants with highly favorable outcomes. In this paper, we propose an efficient convolutional neural network-based disease detection framework in plum under true field conditions for resource-constrained devices. As opposed to the publicly available datasets, images used in this study were collected in the field by considering important parameters of image-capturing devices such as angle, scale, orientation, and environmental conditions. Furthermore, extensive data augmentation was used to expand the dataset and make it more challenging to enable robust training. Investigations of recent architectures revealed that transfer learning of scale-sensitive models like Inception yield results much better with such challenging datasets with extensive data augmentation. Through parameter quantization, we optimized the Inception-v3 model for deployment on resource-constrained devices. The optimized model successfully classified healthy and diseased fruits and leaves with more than 92% accuracy on mobile devices.

Occupancy detection in non-residential buildings – A survey and novel privacy preserved occupancy monitoring solution

Buildings use approximately 40% of global energy and are responsible for almost a third of the worldwide greenhouse gas emissions. They also utilise about 60% of the world’s electricity. In the last decade, stringent building regulations have led to significant improvements in the quality of the thermal characteristics of many building envelopes. However, similar considerations have not been paid to the number and activities of occupants in a building, which play an increasingly important role in energy consumption, optimisation processes, and indoor air quality. More than 50% of the energy consumption could be saved in Demand Controlled Ventilation (DCV) if accurate information about the number of occupants is readily available (Mysen et al., 2005). But due to privacy concerns, designing a precise occupancy sensing/counting system is a highly challenging task. While several studies count the number of occupants in rooms/zones for the optimisation of energy consumption, insufficient information is available on the comparison, analysis and pros and cons of these occupancy estimation techniques. This paper provides a review of occupancy measurement techniques and also discusses research trends and challenges. Additionally, a novel privacy preserved occupancy monitoring solution is also proposed in this paper. Security analyses of the proposed scheme reveal that the new occupancy monitoring system is privacy preserved compared to other traditional schemes.

The role of continuous trust in usage of online product recommendations

Purpose

This study examines the role of continuous trust (i.e., a trust that develops over time as a result of continuous usage interactions) in determining customers' intention to continue using online product recommendations (OPRs).

Design/methodology/approach

Based on information system (IS), continuance model, and continuous trust, we propose that continuous trust will influence customers’ intention to continue OPRs’ use directly and indirectly via their satisfaction and usefulness of the OPRs. The research model is tested using data collected via an online survey from 626 existing users of OPRs in 15 different countries.

Findings

The empirical results revealed that continuous trust is shown to be a significant predictor of customers’ intention to continue OPRs use for future purchases. Additionally, the customers’ perceived confirmation and continuous trust positively influence their perceived usefulness and satisfaction with the OPRs, which subsequently influence customers’ OPRs continuous usage intention.

Research limitations/implications

The saliency of continuous trust and usefulness of OPRs present e-retailers with potential fruitful areas to shape future usage of OPRs. In addition, e-retailers must understand that improving the OPR usefulness on its own may not lead to OPRs continuous usage until OPRs trustworthiness is not continually improved. OPRs itself may be convenient and useful, but trustworthy OPRs will pay stronger dividends for customer satisfaction and OPRs’ continuous usage.

Originality/value

The incorporation of continuous trust into the IS continuance model offers a new theoretical lens and an alternative explanation for the OPR continuous usage intention. This study stands in contrast to the large majority of research concerning initial trust and OPRs adoption, in that it focuses on continuous trust (as opposed to initial trust) and on a customers’ OPRs continuous usage intention as opposed to the initial adoption decision.

Does Implant Surface Texture Affect the Risk of Capsular Contracture in Subglandular Breast Augmentation and Breast Augmentation-Mastopexy?

BACKGROUND

Previous studies have reported decreased rates of capsular contracture associated with the use of textured surface breast implants placed in the subglandular plane during breast augmentation. However, since the publication of these studies, our understanding of the pathophysiology of capsular contracture, as well as the surgical techniques utilized to minimize bacterial contamination of the implant, have advanced considerably.

OBJECTIVES

The purpose of this study was to re-evaluate the relation between implant surface texturization and capsular contracture rates for breast implants placed in the subglandular plane during primary breast augmentation.

METHODS

Retrospective chart review was performed of all primary subglandular breast augmentation procedures involving the use of either smooth or textured round silicone gel implants, with or without simultaneous mastopexy. The primary outcome measures included clinically significant capsular contracture (Baker grade III/IV) and revision surgery for capsular contracture.

RESULTS

Between 2010 and 2017, 526 patients underwent primary subglandular breast augmentation with either smooth (n = 212) or textured (n = 314) round silicone gel implants; 248 patients underwent breast augmentation, whereas 278 underwent breast augmentation-mastopexy. Average follow-up was 756 days in the textured group and 461 days in the smooth group. Five cases of capsular contracture were observed in the textured group, and 7 cases of capsular contracture were observed in the smooth group (P = 0.20).

CONCLUSIONS

Smooth surface implants placed in the subglandular plane were not at a significantly increased risk of capsular contracture compared with textured surface implants. We suggest that adherence to a surgical technique focused on minimizing bacterial contamination of the implant is of greater clinical significance than implant surface characteristics when discussing capsular contracture.

LEVEL OF EVIDENCE: 4

Deciphering the expression dynamics of ANGPTL8 associated regulatory network in insulin resistance using formal modelling approaches

ANGPTL8 is a recently identified novel hormone which regulates both glucose and lipid metabolism. The increase in ANGPTL8 during compensatory insulin resistance has been recently reported to improve glucose tolerance and a part of cytoprotective metabolic circuit. However, the exact signalling entities and dynamics involved in this process have remained elusive. Therefore, the current study was conducted with a specific aim to model the regulation of ANGPTL8 with emphasis on its role in improving glucose tolerance during insulin resistance. The main contribution of this study is the construction of a discrete model (based on kinetic logic of René Thomas) and its equivalent Stochastic Petri Net model of ANGPTL8 associated Biological Regulatory Network (BRN) which can predict its dynamic behaviours. The predicted results of these models are in‐line with the previous experimental observations and provide comprehensive insights into the signalling dynamics of ANGPTL8 associated BRN. The authors’ results support the hypothesis that ANGPTL8 plays an important role in supplementing the insulin signalling pathway during insulin resistance and its loss can aggravate the pathogenic process by quickly leading towards Diabetes Mellitus. The results of this study have potential therapeutic implications for treatment of Diabetes Mellitus and are suggestive of its potential as a glucose‐lowering agent.

Emerging promise of sulforaphane-mediated Nrf2 signaling cascade against neurological disorders

Neurological disorders represent a great challenge and are the leading cause of death and disability globally. Although numerous complicated mechanisms are involved in the progressions of chronic and acute neurodegenerative disorders, most of the diseases share mutual pathogenic features such as oxidative stress, mitochondrial dysfunction, neuroinflammation, protein misfolding, excitotoxicity, and neuronal damage, all of these are the common targets of nuclear factor erythroid 2 related factor 2 (Nrf2) signaling cascade. No cure has yet been discovered to tackle these disorders, so, intervention approaches targeting phytochemicals have been recommended as an alternative form of treatment. Sulforaphane is a sulfur-rich dietary phytochemical which has several activities such as antioxidant, anti-inflammatory, and anti-tumor via multiple targets and various mechanisms. Given its numerous actions, sulforaphane has drawn considerable attention for neurological disorders in recent years. Nrf2 is one of the most crucial targets of sulforaphane which has potential in regulating the series of cytoprotective enzyme expressions that have neuroprotective, antioxidative, and detoxification actions. Neurological disorders are auspicious candidates for Nrf2-targeted treatment strategy. Sulforaphane protects various neurological disorders by regulating the Nrf2 pathway. In this article, we recapitulate current studies of sulforaphane-mediated Nrf2 activation in the treatment of various neurological disorders.

The Impact of Skin Care Product Sales in an Aesthetic Plastic Surgery Practice

BACKGROUND

Despite significant growth of the global skin care market, many plastic surgeons do not offer skin care products through their aesthetic practice. However, skin care products represent a significant potential revenue stream for plastic surgeons, not only by generating revenue from product sales but by improving patient retention over time and, in turn, generating additional surgical and nonsurgical revenue.

OBJECTIVES

The purpose of this study was to determine the financial implications that skin care sales can have for an aesthetic surgery practice. Our hypothesis was that patients making skin care purchases would generate higher non-skin care revenue than patients not purchasing skin care products.

METHODS

A retrospective chart review was performed of all purchases made within a single aesthetic surgery practice during a 6-year period (2012-2017). Pre-tax revenue ($CAD) from each category was recorded for any patient who made a purchase during the study period.

RESULTS

A total 3785 patients purchased skin care products, 5088 patients purchased nonsurgical treatments, and 3504 patients underwent surgery. Average patient spending was $720.73 (skin care), $1272.63 (nonsurgical), and $10,048.34 (surgery), respectively. Overall, patients who purchased skin care generated more revenue from the purchases of nonsurgical treatments and surgery than patients who did not purchase skin care products.

CONCLUSIONS

Skin care sales not only generate revenue, but over time these patients spend more on nonsurgical and surgical treatments than patients who do not purchase skin care. Skin care is an important adjuvant to nonsurgical and surgical treatments that should be considered by all aesthetic surgeons.

INTESTINAL MALROTATION IN 35 YEAR OLD WOMEN FROM PESHAWAR, PAKISTAN

Thirty five years old women presented to the Accident and Emergency Department with acute onset right upper quadrant abdominal pain with normal vitals. CT images revealed a malrotation causing midgut volvulus and intestinal obstruction. On emergency exploratory laparotomy, the gut loops showed partial ischemia due to a double twist at the root of mesentery and malrotation of the gut along with the caecum which was mobile coming from left iliac fossa and lying in the right iliac fossa. Duodeno-jejunal junction was identified. The coils of the intestine were untwisted and rotation was corrected. The gut color changed back to normal. She was discharged painless after routine post-operative care.

Barriers to implementation of emergency obstetric and neonatal care in rural Pakistan

BACKGROUND

Recognizing the need for improving maternal and newborn care, the Punjab public health department (Pakistan) launched emergency obstetric neonatal care (EmONC) services under WHO guideline. Unfortunately, the program implementation is facing some serious problems. The purpose of this study was to identify barriers to implementation of EmONC in district Bahawalnagar (Pakistan).

METHODS

This study used sequential exploratory design. Specifically, a qualitative study was conducted to identify barriers to EmONC. Subsequently, the relative importance of these barriers was determined in a quantitative study. Participants were health service providers involved in 24-hours basic EmONC services in the basic health units of district Bahawalnagar (Pakistan). Qualitative data were gathered by interviewing the participants using key informant guide. Quantitative data were collected in a rank order survey of the same participants. The methodological quality was assessed using mixed methods appraisal tool (MMAT) version 2011.

RESULTS

The results indicate that lack of teamwork, conflict management, communication, and improper power distribution are important interpersonal barriers. The significant organizational-level barriers include job insecurity, lack of organizational culture, human resource deployment issues, and lack of role clarity. Lack of target management, lack of resource availability, house job requirement, and dual practice issues were identified as major system-level barriers.

CONCLUSION

Barriers to EmONC implementation must be addressed for improving maternal and neonatal care in district Bahawalnagar.