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Abstract Background Cleft lip and palate (CLP) are among the most common congenital anomaly that affects up to 33,000 newborns in India every year. Nasoalveolar moulding (NAM) is a non-surgical treatment performed between 0 and 6 months of age to reduce the cleft and improve nasal aesthetics prior to lip surgery. The NAM treatment has been a controversial treatment option with 51% of the cleft teams in Europe, 37% of teams in the USA and 25 of cleft teams in India adopting this methodology. This treatment adds to the already existing high burden of care for these patients. Furthermore, the supporting evidence for this technique is limited with no high-quality long-term clinical trials available on the effectiveness of this treatment. Method The NAMUC study is an investigator-initiated, multi-centre, single-blinded randomized controlled trial with a parallel group design. The study will compare the effectiveness of NAM treatment provided prior to lip surgery against the no-treatment control group in 274 patients with non-syndromic unilateral complete cleft lip and palate. The primary endpoint of the trial is the nasolabial aesthetics measured using the Asher McDade index at 5 years of age. The secondary outcomes include dentofacial development, speech, hearing, cost-effectiveness, quality of life, patient perception, feeding and intangible benefits. Randomization will be carried out via central online system and stratified based on cleft width, birth weight and clinical trial site. Discussion We expect the results from this study on the effectiveness of treatment with NAM appliance in the long term along with the cost-effectiveness evaluation can eliminate the dilemma and differences in clinical care across the globe. Trial registration ClinicalTrials.gov CTRI/2022/11/047426 (Clinical Trials Registry India). Registered on 18 November 2022. The first patient was recruited on 11 December 2022. CTR India does not pick up on Google search with just the trial number. The following steps have to be carried out to pick up. How to search: ( https://ctri.nic.in/Clinicaltrials/advsearch.php —use the search boxes by entering the following details: Interventional trial > November 2022 > NAMUC).

The role of plasticity and epigenetics in shaping cancer evolution and response to therapy has taken center stage with recent technological advances including single cell sequencing. This roadmap article is focused on state-of-the-art mathematical and experimental approaches to interrogate plasticity in cancer, and addresses the following themes and questions: is there a formal overarching framework that encompasses both non-genetic plasticity and mutation-driven somatic evolution? How do we measure and model the role of the microenvironment in influencing/controlling non-genetic plasticity? How can we experimentally study non-genetic plasticity? Which mathematical techniques are required or best suited? What are the clinical and practical applications and implications of these concepts?

Abstract Retraction: [Aryan Marwaha, Rami Qays Malik, Shehab Mohamed Beram, Ali Rizwan, Hari Kishore Kakarla, Deepak Thakur, Tanya Gera, Mohammad Shabaz, Visualisation‐based binary classification of android malware using vgg16, IET Software 2023 (https://doi.org/10.1049/sfw2.12094)]. The above article from IET Software, published online on 23 January 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor‐in‐Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.

When using a Wireless Sensor Network (WSN) for target tracking applications, optimum selection of right functioning nodes can reduce the number of active nodes and also ensuring tracking reliability requirement. Due to the limitations of the WSN's sensing range, it is crucial to create a mechanism that allows nodes to coordinate in order to follow the target reliably and with a high probability. By doing this, the network's overall energy consumption can be decreased, resulting in a longer network lifetime. Target tracking (TT) is a well observed and significant application of WSNs. In simple words, it maintains a proper trade-off between tracking quality and energy consumption. In the proposed work, Particle Filter (PF) with a machine learning technique called Support Vector Machine (SVM) based energy efficient target tracking used in WSN's. PF is considered to be the most accepted filtering algorithm in various tracking and localization problems. Simulation results show greater performance in determining the target location and maintain lower energy consumption.

Wireless Sensor Networks (WSN) has a wide range of opportunities and can be applied to almost every part of our life. Intrusion detection and monitoring across disputed areas and on army bases are two of the most important uses of WSN. An innovative method that precisely calculates many barriers involved in the process for quick identification and prevention of intrusions. The relevance and risk level of the chosen characteristics were assessed in this paper using feature importance and feature sensitivity metrics. This paper develops a deep learning-based feed-forward artificial neural network model that enables precise estimates of the k-barrier count for effective intrusion detection and mitigation. The area of the region of interest, sensor sensing area, sensing transmission area, and many sensors are the four potential characteristics that were used to learn and assess the feed-forward ANN model. The various attributes are extracted via Monte Carlo simulation. This research found that the method correctly forecasts the number of barriers with Root Mean Square Error and correlation coefficient. The proposed methodology is more efficient than the other standard methods.

Objectives: The excellent resolution offered by magnetic resonance imaging (MRI) has a trade-off in the form of scan duration. The purpose of the present study was to assess the clinical utility of echo-planar imaging mix (EPIMix), an echo-planar imaging-based MRI sequence for the brain with a short acquisition time. Materials and Methods: This was a retrospective observational study of 50 patients, who could benefit from faster MRI brain scans. The T1, T2, fluid attenuated inversion recovery, diffusion-weighted imaging (DWI), and T2*/susceptibility-weighted imaging sequences were acquired, conventionally and with EPIMix. Conventional and EPIMix images were assessed by two radiologists for overall quality, motion, and susceptibility artifacts and scored on a Likert scale. The scores given for conventional and EPIMix images were compared. The diagnostic performance of EPIMix was also assessed by the ability to detect clinically relevant findings. Results: The acquisition time for conventional MRI was 11 min and 45 s and for EPIMix 1 min and 15 s. All EPIMix images were sufficient for diagnostic use. On assessment of the diagnostic performance, it was excellent for ischemic and hemorrhagic strokes. Smaller lesions, lesions adjacent to bone, and post-operative tumors were difficult to identify. Moderate to perfect agreement (Kappa values 0.41-1) was seen between radiologists for all categories except skull base, calvarial, and orbital lesions. Image quality, artifact assessment showed excellent interobserver agreement (>90%) for the scores. All EPIMix images showed reduced motion artifacts. The EPIMix-DWI was comparable to conventional-DWI in terms of quality and artifacts. The remaining sequences showed reduced quality and increased susceptibility. Conclusion: The EPIMix has a significantly reduced acquisition time than conventional MRI and could be used instead of conventional MRI in situations demanding faster scans such as suspected acute ischemic or hemorrhagic stroke. In other clinical scenarios, it could help tailor the MRI examination for each patient. [ABSTRACT FROM AUTHOR]

Background: The smile is one of the most fundamental facial expressions, used to convey friendship, agreement, and admiration. There are various smile analysis method available. Objective: The aim of this scoping review to find most reliable smile analysis method. Which smile analysis method is most reliable and accurate while assessing the smile of patients undergoing orthodontic treatment? Design: An electronic search was executed on PUBMED, Cochrane, SCOPUS, hand search was made on google scholar and references of the articles selected. Keyword used while searching the databases as "((smile analysis) AND methods) AND comparison." Results: A preliminary search of databases and grey literature yielded 525 articles. Following the application of the eligibility criteria, 16 articles were included. Conclusion: With the use of latest technologies and knowledge in literature, a clinician can correctly identify the problem, assess the treatment need and give a satisfactory outcome to the patient. [ABSTRACT FROM AUTHOR]