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H syndrome is a rare autosomal recessive genodermatosis characterized by cutaneous manifestations and other systemic involvement. It presents with features like hyperpigmentation, hypertrichosis, hepatosplenomegaly, hearing loss, hallux valgus, hyperglycemia, low height, hypogonadism, and heart anomalies. Without a high index of suspicion, it is often misdiagnosed with other sclerodermatous cutaneous disorders. This case report highlights the clinical variability of H syndrome. An 8-year-old female child presented with hyperpigmented, hypertrichotic indurated patches with hyperglycemia and short stature. Histopathology showed dense lymphohistiocytic infiltrate and fibrosis in the dermis and subcutaneous tissue. The patient lacked features like heart anomalies, hearing loss, and hallux valgus, suggesting forme fruste presentation of H syndrome. An overlap between features of H syndrome and PHID syndrome is also suspected because of atypical presentation.

This review presents an in-depth analysis of the immense potential of CRISPR-Cas9 technology in revolutionizing oral cancer research. It underscores the inherent limitations of conventional treatments while emphasizing the pressing need for groundbreaking approaches. The unparalleled capability of CRISPR-Cas9 to precisely target and modify specific genes involved in cancer progression heralds a new era in therapeutic intervention. Employing genome-wide CRISPR screens, vulnerabilities in oral cancer cells can be identified, thereby unravelling promising targets for therapeutic interventions. In the realm of oral cancer, the disruptive power of CRISPR-Cas9 manifests through its capacity to perturb genes that are intricately associated with drug resistance, consequently augmenting the efficacy of chemotherapy. To address the challenges that arise, this review diligently examines pertinent issues such as off-target effects, efficient delivery mechanisms, and the ethical considerations surrounding germline editing. Through precise gene editing, facilitated by CRISPR/Cas9, it becomes possible to overcome drug resistance by rectifying mutations, thereby enhancing the efficacy of personalized treatment strategies. This review delves into the prospects of CRISPR-Cas9, illuminating its potential applications in the domains of medicine, agriculture, and biotechnology. It is paramount to emphasize the necessity of ongoing research endeavors and the imperative to develop targeted therapies tailored specifically for oral cancer. By embracing this comprehensive overview, we can pave the way for ground-breaking treatments that instill renewed hope for enhanced outcomes in individuals afflicted by oral cancer.

Oral cancer is one of the 19most rapidly progressing cancers associated with significant mortality, owing to its extreme degree of invasiveness and aggressive inclination. The early occurrences of this cancer can be clinically deceiving leading to a poor overall survival rate. The primary concerns from a clinical perspective include delayed diagnosis, rapid disease progression, resistance to various chemotherapeutic regimens, and aggressive metastasis, which collectively pose a substantial threat to prognosis. Conventional clinical practices observed since antiquity no longer offer the best possible options to circumvent these roadblocks. The world of current cancer research has been revolutionized with the advent of state-of-the-art technology-driven strategies that offer a ray of hope in confronting said challenges by highlighting the crucial underlying molecular mechanisms and drivers. In recent years, bioinformatics and Machine Learning (ML) techniques have enhanced the possibility of early detection, evaluation of prognosis, and individualization of therapy. This review elaborates on the application of the aforesaid techniques in unraveling potential hints from omics big data to address the complexities existing in various clinical facets of oral cancer. The first section demonstrates the utilization of omics data and ML to disentangle the impediments related to diagnosis. This includes the application of technology-based strategies to optimize early detection, classification, and staging via uncovering biomarkers and molecular signatures. Furthermore, breakthrough concepts such as salivaomics-driven non-invasive biomarker discovery and omics-complemented surgical interventions are articulated in detail. In the following part, the identification of novel disease-specific targets alongside potential therapeutic agents to confront oral cancer via omics-based methodologies is presented. Additionally, a special emphasis is placed on drug resistance, precision medicine, and drug repurposing. In the final section, we discuss the research approaches oriented toward unveiling the prognostic biomarkers and constructing prediction models to capture the metastatic potential of the tumors. Overall, we intend to provide a bird’s eye view of the various omics, bioinformatics, and ML approaches currently being used in oral cancer research through relevant case studies.

The clinical management of oral cancer is often frequented with challenges that arise from relapse, recurrence, invasion and resistance towards the cornerstone chemo and radiation therapies. The recent conceptual advancement in oncology has substantiated the role of cancer stem cells (CSC) as a predominant player of these intricacies. CSC are a sub-group of tumor population with inherent adroitness to self-renew with high plasticity. During tumor evolution, the structural and functional reprogramming persuades the cancer cells to acquire stem-cell like properties, thus presenting them with higher survival abilities and treatment resistance. An appraisal on key features that govern the stemness is of prime importance to confront the current challenges encountered in oral cancer. The nurturing niche of CSC for maintaining its stemness characteristics is thought to be modulated by complex multi-layered components encompassing neoplastic cells, extracellular matrix, acellular components, circulatory vessels, various cascading signaling molecules and stromal cells. This review focuses on recapitulating both intrinsic and extrinsic mechanisms that impart the stemness. There are contemplating evidences that demonstrate the role of transcription factors (TF) in sustaining the neoplastic stem cell’s pluripotency and plasticity alongside the miRNA in regulation of crucial genes involved in the transformation of normal oral mucosa to malignancy. This review illustrates the interplay between miRNA and various known TF of oral cancer such as c-Myc, SOX, STAT, NANOG and OCT in orchestrating the stemness and resistance features. Further, the cross-talks involved in tumor micro-environment inclusive of cytokines, macrophages, extra cellular matrix, angiogenesis leading pathways and influential factors of hypoxia on tumorigenesis and CSC survival have been elucidated. Finally, external factorial influence of oral microbiome gained due to the dysbiosis is also emphasized. There are growing confirmations of the possible roles of microbiomes in the progression of oral cancer. Given this, an attempt has been made to explore the potential links including EMT and signaling pathways towards resistance and stemness. This review provides a spectrum of understanding on stemness and progression of oral cancers at various regulatory levels along with their current therapeutic knowledge. These mechanisms could be exploited for future research to expand potential treatment strategies.

Introduction: Atopic Dermatitis (AD) is a common relapsing inflammatory disorder, among the paediatric population clinically, characterised by pruritus and recurring eczematous skin lesions and a host of other cutaneous changes. Diagnosis is done on the basis of clinical findings with the usage of Hanifin and Rajka’s criteria which includes 4 major and 23 minor criteria. Geographical, climatic factors and other population factors have been reported to influence the occurrence of minor criteria. Aim: To estimate the frequency of Minor criteria among paediatric atopic dermatitis in Western Tamil Nadu, India. Materials and Methods: This cross-sectional observational study was done by including 110 atopic children attending Paediatric and Dermatology Outpatient Departments (OPD) of KMCH IHSR, Coimbatore, Western Tamil Nadu, India, between March 2022 to August 2022. The clinical and ophthalmological findings were documented. Categorical variables were presented as frequency and percentages, Continuous variables were presented as Mean±Standard deviation. The data was entered in excel and was analysed using statistical package for social sciences (SPSS) version 27. Results: Among the total study population of 110, 53 (48.2%) were males and the rest 57 (51.8%) were females. The mean age was 24.73±5.18 years with a range of 2-15 years. Early age of onset was seen in 73.6% of study population. Hyperlinear palms were found in 70% of the study patients. 68.2% had Dennie Morgan infraorbital fold, 64.5% had xerosis, 61% had pityriasis alba and 60% had a family history of atopy. Conclusion: Certain minor manifestations of AD like xerosis, icthyosis, hyprerlinear palms, and perifollicular accentuation were more common in the present study. Western Tamil Nadu having a tropical semi-arid climate tempered by higher altitude could explain the differences noted in the frequency of certain minor criteria.

Over the past decade, numerous gene-editing platforms which alter host DNA in a highly specific and targeted fashion have been described. Two notable examples are zinc finger nucleases (ZFNs), the first gene-editing platform to be tested in clinical trials, and more recently, CRISPR/Cas9. Although CRISPR/Cas9 approaches have become arguably the most popular platform in the field, the therapeutic advantages and disadvantages of each strategy are only beginning to emerge. We have established a nonhuman primate (NHP) model that serves as a strong predictor of successful gene therapy and gene-editing approaches in humans; our recent work shows that ZFN-edited hematopoietic stem and progenitor cells (HSPCs) engraft at lower levels than CRISPR/Cas9-edited cells. Here, we investigate the mechanisms underlying this difference. We show that optimized culture conditions, including defined serum-free media, augment engraftment of gene-edited NHP HSPCs in a mouse xenograft model. Furthermore, we identify intracellular RNases as major barriers for mRNA-encoded nucleases relative to preformed enzymatically active CRISPR/Cas9 ribonucleoprotein (RNP) complexes. We conclude that CRISPR/Cas9 RNP gene editing is more stable and efficient than ZFN mRNA-based delivery and identify co-delivered RNase inhibitors as a strategy to enhance the expression of gene-editing proteins from mRNA intermediates.

Keystone island flaps have a growing array of applications in reconstructive surgeries for the closure of simple and complex defects following the excision of skin tumors. It is a trapezoidal-shaped flap based on fasciocutaneous perforators. We share our experience with a 79-year-old man, who underwent keystone island flap reconstruction after the excision of biopsy-proven Bowen’s disease. A good aesthetic and functional outcome was obtained. With an ever expanding repertoire of reconstructive surgical techniques, the individualization of defect closure is of paramount importance in ensuring good cosmesis.

From the latter half of the last decade, there has been a growing interest in developing algorithms for automatically solving mathematical word problems (MWP). It is a challenging and unique task that demands blending surface level text pattern recognition with mathematical reasoning. In spite of extensive research, we still have a lot to explore for building robust representations of elementary math word problems and effective solutions for the general task. In this paper, we critically examine the various models that have been developed for solving word problems, their pros and cons and the challenges ahead. In the last 2 years, a lot of deep learning models have recorded competing results on benchmark datasets, making a critical and conceptual analysis of literature highly useful at this juncture. We take a step back and analyze why, in spite of this abundance in scholarly interest, the predominantly used experiment and dataset designs continue to be a stumbling block. From the vantage point of having analyzed the literature closely, we also endeavor to provide a road‐map for future math word problem research. This article is categorized under:Technologies > Machine LearningTechnologies > Artificial IntelligenceFundamental Concepts of Data and Knowledge > Knowledge Representation [ABSTRACT FROM AUTHOR]

Foam concrete is one of the light weight concrete which contains cement, filler, water and foaming agent. Nowadays, this foam concrete has very useful characteristics for building construction. It requires no compaction and can easily fill the irregular cavities. In construction industry, various types of industrial waste materials was used to improve the strength and durability properties of the concrete. The endeavours to improve the strength properties such as cement, silica fume, fly ash, foaming Agent, Poly Vinyl Alcohol (PVA) fiber and carbon fiber were used. The combination of two fibers were added in the foam concrete with the different proportion of 0.3%, 0.4% and 0.5%. This paper describes the strength properties such as compressive strength, split tensile strength, water absorption characteristics and prediction of compressive strength of the fibre reinforced foam concrete using python. The targeted design density of foam concrete is 1650 kg/m3. All the specimens were tested and determined the strength at the age of 7 days, 14 days and 28 days.

Context: Cervical lymph node metastasis is the most important prognostic factor in Squamous Cell Carcinoma of Head and Neck (SCCHN). Detection and evaluation of micro-metastasis forms the basis for diagnosis, staging, treatment options and prognosis. Lymph node prognostic factors are extremely important for the survival and recurrence in the patient. Assessing lymph node metastasis in the absence of clinical enlargement is challenging. Aim: To evaluate micrometastasis and individual tumor cells (ITC) in regional lymph nodes of oral squamous cell carcinoma (OSCC) by modified papanicolaou (PAP) stain and re-evaluate the tumor staging. Settings and Design: The retrospective study was executed at MS Ramaiah University of Applied Sciences. Methods and Materials: The current study constituted a total of 40 lymph nodes from OSCC patients, metastatic (n=20) and non-metastatic lymph nodes (n=20). All sections were stained with H & E followed by modified PAP stain. Modified PAP was used for identification of micrometastasis deposits. Statistical Analysis Used: The Chi square test was employed to analyze significance. Results: Modified PAP stain proved to be more accurate (p = 0.006) than H and E stain in detecting micrometastasis which accounted for 15% of non-metastatic lymph node sections used in our study. Conclusion: Special stain like modified PAP stain is valuable and sensitive in detecting micro-metastasis over H and E stain. Detection of micrometastasis in OSCC patients is advantageous for the patient as it influences staging, it modifies the treatment plan in terms of both radiotherapy and chemotherapy. [ABSTRACT FROM AUTHOR]

In order to assess the fetus health and make timely decisions throughout pregnancy, Fetal Electrocardiography (FECG) monitoring is essential. Huge datasets for electrocardiograms are freely accessible from Physionet ATM Dataset1- Abdominal and Direct Fetal ECG Database (adfecgdb), Dataset2- Fetal ECG Synthetic Database (fecgsyndb), Dataset3- Non-Invasive Fetal ECG Database(nifecgdb). In this study, categorization is done based on normal and abnormal (Atrial fibrillation) FECG from three online dataset which contains FECG recordings as major details. Deep learning models like Transfer Learning (TL) and Convolutional Neural Networks (CNN) are being investigated. The composite abdominal signal and the FECG are separated using a wavelet transform approach. The best model for categorizing the parameters of the FECG is determined through a comparative analysis and performance is improved using Continuous Wavelet Transform (CWT). The accuracy of the CNN-based technique is found to be 98.59%, whereas the accuracy of the transfer learning model is 99.01% for FECG classification. The computation of metric parameters for all the datasets is done. The classification of normal and abnormal (Atrial fibrillation) is best performed in TL model compared to CNN. Real-time data analysis is done for PQRST plotting and comparative study is done using Net Reclassification Improvement (NRI) and obtained NRI = 13%, z static 0f 3.7641, p-Value of 0.00016721. Acute Myocardial Infraction (AMI) identification is done based on ST segment of Maternal ECG (MECG) images to analyze the heart attack risk. The proposed work can be utilized to track FECG waveforms in real-time for wearable technology because of its end-to-end properties and expandable intrinsic for diagnosing multi-lead heart disorders. [ABSTRACT FROM AUTHOR]

Context: Spindle cell lesions comprise a vast plethora of benign and malignant lesions with similar clinical and radiographic features. Their overlapping histopathologic features ensure a diagnostic dilemma. Aim: The current multicentric study aims to delineate fibroblastic and myofibroblastic oral spindle cell lesions based on cytomorphology and comprehensive immunohistochemical analysis. Settings and Design: The experimental study was conducted at MS Ramaiah University of Applied Sciences, Bangalore, and All India Institute of Applied Sciences, Delhi. Methods and Material: A comprehensive histological scoring criteria and panel of immunohistochemical makers (STAT6, CD31, CD34, S100, SMA, vimentin, pan-CK, HHF-35, Ki67, ALK, desmin, HMB-45, SATB2, ERG, EMA and CD99) were employed concurrently for the first time for fibroblastic and myofibroblastic oral spindle cell lesions. The data obtained was tabulated and studied. Statistical Analysis Used: NA. Results: Using cytological scoring criteria and panel of immunohistochemical makers, the cases analysed and characterized were desmoplastic fibroma, fibrosarcoma, leiomyosarcoma, nodular fasciitis, neurofibroma and epithelioid inflammatory myofibroblastic sarcoma (EIMS). Conclusions: The diagnostic strategies need to be upgraded for the diagnosis of spindle cell lesions. Emphasis must be placed on cytomorphology, an immunohistochemistry (IHC) panel of markers is imperative for the accurate diagnosis of fibroblastic and myofibroblastic oral spindle cell lesions. [ABSTRACT FROM AUTHOR]

In the past three decades, many types of electrospun fibers have been developed and utilized for innumerable tissue engineering applications. Precisely, in the area of bone tissue engineering, composite bone grafts are being employed to overcome the limitations associated with autografts, allografts, and xenografts. A composite bone graft comprises a polymeric osteoconductive matrix and an osteoinductive or osteogenic material. Moreover, polymeric and ceramic-based engineered nanocomposite fibers developed through electrospinning are relatively similar to composite bone grafts. The polymers offer biocompatibility, resorbability, and flexibility to the nanocomposite fibers. In addition, polymeric matrices provide structural support for cell adhesion and subsequent cellular processes leading to tissue formation, whereas bioactive ceramics provide strength and osteoconductivity to the nanocomposite fibers. An array of ceramic particles such as bioactive glasses, wollastonite, hydroxyapatite, tricalcium phosphate, tetracalcium phosphate, octacalcium phosphate, magnesium silicate, whitlockite, akermanite, carbon nitride, calcium sulfate, and alumina have been explored in bone-specific applications to gain successful outcomes. The current chapter emphasizes the properties, cytocompatibility, and in vivo performance of ceramic-incorporated nanocomposite fibers and fibrous scaffolds in bone tissue engineering applications. [ABSTRACT FROM AUTHOR]

In the recent years, multiscale fibres have gained widespread attention for use in diverse biomedical applications. With the technological advancements in electrospinning technique, the dimensions of the multiscale fibres can be tailored to match the desired requirements of the target tissues and organs. These fibres combining the unique properties of nano- and microfibres can be fabricated several techniques. The engineered multiscale fibrous scaffolds are being utilised to deliver growth factors and cells of interest, thereby, aid in tissue regeneration. The elastic modulus of the multiscale fibrous scaffolds can be enhanced by introducing biomaterials like multilayer carbon nanotubes (MCNT), nanoclay, nanohydroxyapatite (n-HAp), and graphene oxide (GO). Moreover, studies on bone, cartilage, cardiovascular and liver tissue engineering have revealed that the multiscale fibrous scaffolds are capable of restoring the microarchitecture of the extracellular matrix (ECM). The current chapter focuses on some of the fabrication techniques which include coaxial, emulsion & co-electrospinning, edge electrospinning, gap electrospinning, 3D jet writing, and caged collector electrospinning & moving spinneret. Further, the application of multiscale fibrous scaffolds with respect to bone, cartilage, cardiovascular, liver, neural, skin and tendon tissue engineering has been discussed. [ABSTRACT FROM AUTHOR]