The Influence of Epilepsy on Oral Health Outcomes: A Retrospective Study in South Indian Adults.

Introduction Epilepsy, a chronic neurological disorder marked by recurrent seizures, affects approximately 50 million people worldwide with a higher prevalence in developing countries. This condition challenges motor skills and coordination, leading to poor oral health maintenance. The study aimed to evaluate the effect of epilepsy on oral health outcomes in adults by contrasting South Indian epileptics with healthy controls. The primary objective was to assess the prevalence of oral health issues in patients with epilepsy compared to healthy individuals and to analyze the types and frequency of dental procedures required in epileptic patients compared to healthy controls in the South Indian population. Materials and methods A retrospective study was conducted in the Department of Oral Medicine and Radiology, Saveetha Dental College and Hospitals, Chennai, India. Approved by the Institutional Human Ethical Committee (Registration ID: IHEC/SDC/OMED-2202/23/106), the study involved 105 epileptic patients and 105 healthy controls from records between January 2021 and December 2023. Both male and female patients within the age limit of 18-55 years were included. Statistical analysis was performed using IBM SPSS Statistics for Windows, Version 29.0 (Released 2022; IBM Corp., Armonk, New York, United States). Results The study involved 210 participants with an equal gender distribution. Valproate was the most common medication used by 39% of epileptic patients. Gingival hyperplasia was significantly more prevalent in the epileptic group (24%). The epileptic group also required more dental procedures, with 32% of teeth needing restoration, 20% root canal treatment, and 20% extraction, compared to 12%, 11%, and 5%, respectively, in the control group. Conclusion Epileptic patients exhibit poorer oral health outcomes, including higher rates of gingival hyperplasia and a greater need for dental procedures compared to healthy controls. These findings highlight the necessity for targeted dental care and regular monitoring for individuals with epilepsy to improve their oral health and overall quality of life.

Effectiveness of Oral Health Education and Interventions in Improving Oral Health Outcomes in Type II Diabetes Mellitus Patients: A Prospective Study.

Introduction Diabetes mellitus (DM) is a group of metabolic diseases characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. The study aimed to evaluate the effectiveness of oral health education and intervention in improving oral health outcomes in type 2 DM (T2DM) patients. Methods The present study was conducted in the Department of Oral Medicine and Radiology between February 2023 and August 2023 at Saveetha Dental College and Hospitals in Chennai, India. All of the patients in the study had T2DM with oral manifestations. This study enrolled 105 participants, of whom 63 were female and 42 were male. A standard pro forma was given to all the participants, and the findings were recorded. The pro forma comprises different oral manifestations, blood glucose levels, the Decayed, Missing, and Filled Teeth (DMFT) index, and Russell's periodontal index. The results were then statistically analyzed. Results This study of 105 individuals with T2DM (60% females and 40% males) revealed significant oral health challenges: 33% had periodontitis, 20% had gingivitis, 5% had lichenoid reactions, 23% had xerostomia, 11% had halitosis, and 8% had candidiasis, illustrating diabetes' impact on dental health. Following appropriate, tailor-made treatment for individual patients, such as scaling, root planning, oral hygiene education, pharmacotherapy, and post-intervention, the prevalence of complications notably decreased by 61%. A total of 7% of patients had gingivitis, 11% had periodontitis, 12% had xerostomia, 4% had halitosis, 2% had candidiasis, and 1% had lichenoid reactions, respectively. This highlights the importance of regular oral care positively impacting diabetes patients, with 61% experiencing improved oral health and 39% experiencing no improvement. Conclusion This study provides compelling evidence for the effectiveness of oral health education and interventions in improving oral health outcomes in T2DM patients. This approach offers a promising strategy for managing the oral health complications associated with diabetes and improving this population's overall health and well-being.

Missed Maxillary Sinus Ostium Syndrome and its Management.

The inflammatory process involving the maxillary sinus is often exacerbated by a functional obstruction due to laterally displaced uncinate process which obstructs the infundibulum and the natural ostium. Physiologically the drainage pathway may be adequate but during periods of inflammation resulting in nasal oedema, the ostium/infundibulum interface is inadequate, preventing adequate ventilation and drainage of the maxillary sinus. Incomplete removal of the uncinate process without including the natural ostium may result in failure and recurrence. This method of Middle meatal antrostomy that does not include the natural ostium of the maxillary sinus, leads to the missed ostium sequence and continued sinus disease. Here a case of missed maxillary sinus syndrome and its management is presented. A 28-year-old man with complaints of post nasal drip and Left facial pain for 4 months. 3 years prior the patient underwent functional endoscopic sinus surgery (FESS), following surgery patient had recurrent episode of sinusitis. Diagnostic nasal endoscopy revealed presence of mucopurulent discharge in left middle meatus, CT scan Paranasal sinus was suggestive of opacity in left maxillary sinuses and in left middle meatus with wide maxillary antrostomy. Revision FESS surgery was performed, where two ostia were present was converted into single wide middle meatal antrostomy using a back bitting forceps and microdebrider to avoid maxillary sinus mucus recirculation phenomenon. On follow up 1 year later, patient had no symptoms of repeated sinusitis. Missed maxillary sinus ostium syndrome has to be recognized and timely addressed by joining the natural and surgically created ostia as single wide middle meatal antrostomy window. Supplementary Information: The online version contains supplementary material available at 10.1007/s12070-023-04385-x.

Comprehending interaction mechanism of natural actives of Colchicum autumnale L. for rheumatoid arthritis using integrative chemoinformatic approaches.

This research delves into the realm of therapeutic potential within natural compounds derived from Colchicum autumnale L., emphasizing a holistic perspective on medications used in human therapy. Rather than confining the study to their primary actions, the research endeavors to unveil molecular targets for these natural compounds, with a specific focus on their potential applicability in the treatment of rheumatoid arthritis (RA). The study focuses on understanding interactions between specific natural actives that target RA. Fifteen RA target proteins were identified from OMIM, GeneScan and PharmaGKB. Their structures were downloaded from RCSB PDB. Two active components of C. autumnale L. were chosen for mass spectrometry investigation. Ligand characteristics were determined using the ADMETlab and SwissADME software tools. Molecular docking was performed, and the top three complexes were simulated for 200 ns, along with identification of free binding energies. The compounds ß-sitosterol-IL-10 (-6.50 kcal/mol), colchicine-IL-10 (-6.01 kcal/mol), linoleic acid-IL-10 (-7.22 kcal/mol) and linoleic acid-IL-10 (-7.22 kcal/mol) exhibited best binding energies. ß-Sitosterol and colchicine showed the highest stability in simulations, confirmed by molecular mechanics free energy binding calculations. This work provides insights into the molecular interaction of natural compounds against RA targets, offering potential therapeutic anti-RA medications.Communicated by Ramaswamy H. Sarma.

Dendritic Cell Activation in Leprosy Using CD1a and Factor XIIIa Markers.

BACKGROUND: Leprosy is manifested in varied forms based on the immune status of the patient giving rise to the polar and borderline spectrum of tuberculoid (TT) and lepromatous leprosy (LL). The present study was conducted to assess the macrophage activation in the spectrum of leprosy using CD1a and Factor XIIIa immunohistochemical markers and to correlate the macrophage expression with the morphological spectrum and bacillary index. METHODOLOGY: The present study was an observational study. RESULTS: The present study consisted of 40 biopsy-proven leprosy cases, in which a majority were males, and the most common age group was 20-40 years. The most common type encountered was borderline tuberculoid (BT) leprosy. Expression of epidermal dendritic cells and intensity of staining by CD1a was higher in TT (seven of 10 cases (70%)) when compared to LL (one of three cases (33%)). Similarly, Factor XIIIa showed higher expression of dermal dendritic cells in 90% of TT when compared to LL which was seen in 66%. CONCLUSION: The increased number and strong intensity of dendritic cells in the tuberculoid spectrum may indirectly indicate macrophage activation and possibly account for the low bacillary index.

An empirical study of preprocessing techniques with convolutional neural networks for accurate detection of chronic ocular diseases using fundus images.

Chronic Ocular Diseases (COD) such as myopia, diabetic retinopathy, age-related macular degeneration, glaucoma, and cataract can affect the eye and may even lead to severe vision impairment or blindness. According to a recent World Health Organization (WHO) report on vision, at least 2.2 billion individuals worldwide suffer from vision impairment. Often, overt signs indicative of COD do not manifest until the disease has progressed to an advanced stage. However, if COD is detected early, vision impairment can be avoided by early intervention and cost-effective treatment. Ophthalmologists are trained to detect COD by examining certain minute changes in the retina, such as microaneurysms, macular edema, hemorrhages, and alterations in the blood vessels. The range of eye conditions is diverse, and each of these conditions requires a unique patient-specific treatment. Convolutional neural networks (CNNs) have demonstrated significant potential in multi-disciplinary fields, including the detection of a variety of eye diseases. In this study, we combined several preprocessing approaches with convolutional neural networks to accurately detect COD in eye fundus images. To the best of our knowledge, this is the first work that provides a qualitative analysis of preprocessing approaches for COD classification using CNN models. Experimental results demonstrate that CNNs trained on the region of interest segmented images outperform the models trained on the original input images by a substantial margin. Additionally, an ensemble of three preprocessing techniques outperformed other state-of-the-art approaches by 30% and 3%, in terms of Kappa and F 1 scores, respectively. The developed prototype has been extensively tested and can be evaluated on more comprehensive COD datasets for deployment in the clinical setup.

Prevalence of Oral Submucous Fibrosis With Other Oral Potentially Malignant Disorders: A Clinical Retrospective Study.

Background  Oral submucous fibrosis (OSMF) is a chronic, progressive, and potentially malignant oral disorder that causes scarring of the oral cavity, pharynx, and upper oesophagus. It is most common in Southeast Asia, but it is also found in other parts of the world. Oral potentially malignant disorders (OPMDs) are a group of oral lesions that have an increased risk of developing into oral cancer. The study aimed to evaluate the prevalence of OSMF associated with other OPMDs. The presence of multiple OPMDs existing in one patient is a significant finding, as it is associated with an elevated risk of developing malignancy. The risk of malignant transformation increases with the number of OPMDs present in a patient; patients with two OPMDs have a three to four times higher risk of developing malignancy than those with a single OPMD. Patients with three or more OPMDs have a 7-10 times higher risk and the risk of malignant transformation depends on the type of OPMD. Materials and methods The study was conducted in the Department of Oral Medicine and Radiology, Saveetha Dental College and Hospitals, Chennai, India, to investigate the prevalence of OSMF with other OPMDs. The study team retrieved 630 case records of patients with OSMF from the electronic database between January 2018 and March 2023. All of the patients in the study had OSMF, as well as other OPMDs such as leukoplakia, candidiasis, actinic cheilitis, dyskeratosis congenita, erythroplakia, lichen planus, sideropenic dysphagia (Plummer-Vinson syndrome), and discoid lupus erythematosus. Both clinical and histopathological examinations confirmed these diagnoses. Oral mucosal lesions without coexisting OSMF were excluded. The study was done on the basis of age group, habits, type of habits, associated coexisting lesions, and systemic condition. Results The patients were clinically examined and diagnosed. Of the 630 cases, 10% had OSMF with OPMDs. The most common OPMDs associated with OSMF were leukoplakia (86%), followed by candidiasis (12%) and both leukoplakia and candidiasis (2%). Based on gender, the incidence of OSMF was higher in males compared to females with 67% and 33%, respectively. Conclusion OSMF is more likely to develop into malignancy; the widespread use of areca nut products in India has contributed to the rising incidence of OSMF. Accumulating epidemiological data can help to identify high-risk populations for prevention and control measures. Earlier oral cancer diagnosis and treatment can increase the likelihood of a favourable outcome.

Content-based medical image retrieval system for lung diseases using deep CNNs.

Content-based image retrieval (CBIR) systems are designed to retrieve images that are relevant, based on detailed analysis of latent image characteristics, thus eliminating the dependency of natural language tags, text descriptions, or keywords associated with the images. A CBIR system maintains high-level image visuals in the form of feature vectors, which the retrieval engine leverages for similarity-based matching and ranking for a given query image. In this paper, a CBIR system is proposed for the retrieval of medical images (CBMIR) for enabling the early detection and classification of lung diseases based on lung X-ray images. The proposed CBMIR system is built on the predictive power of deep neural models for the identification and classification of disease-specific features using transfer learning based models trained on standard COVID-19 Chest X-ray image datasets. Experimental evaluation on the standard dataset revealed that the proposed approach achieved an improvement of 49.71% in terms of precision, averaging across various distance metrics. Also, an improvement of 26.55% was observed in the area under precision-recall curve (AUPRC) values across all subclasses.

Deep neural models for automated multi-task diagnostic scan management-quality enhancement, view classification and report generation.

The detailed physiological perspectives captured by medical imaging provides actionable insights to doctors to manage comprehensive care of patients. However, the quality of such diagnostic image modalities is often affected by mismanagement of the image capturing process by poorly trained technicians and older/poorly maintained imaging equipment. Further, a patient is often subjected to scanning at different orientations to capture the frontal, lateral and sagittal views of the affected areas. Due to the large volume of diagnostic scans performed at a modern hospital, adequate documentation of such additional perspectives is mostly overlooked, which is also an essential key element of quality diagnostic systems and predictive analytics systems. Another crucial challenge affecting effective medical image data management is that the diagnostic scans are essentially stored as unstructured data, lacking a well-defined processing methodology for enabling intelligent image data management for supporting applications like similar patient retrieval , automated disease prediction etc. One solution is to incorporate automated diagnostic image descriptions of the observation/findings by leveraging computer vision and natural language processing. In this work, we present multi-task neural models capable of addressing these critical challenges. We propose ESRGAN, an image enhancement technique for improving the quality and visualization of medical chest x-ray images, thereby substantially improving the potential for accurate diagnosis, automatic detection and region-of-interest segmentation. We also propose a CNN-based model called ViewNet for predicting the view orientation of the x-ray image and generating a medical report using Xception net, thus facilitating a robust medical image management system for intelligent diagnosis applications. Experimental results are demonstrated using standard metrics like BRISQUE, PIQE and BLEU scores, indicating that the proposed models achieved excellent performance. Further, the proposed deep learning approaches enable diagnosis in a lesser time and their hybrid architecture shows significant potential for supporting many intelligent diagnosis applications.

A rare case of round ligament leiomyoma: an inguinal mass.

Tumours of round ligament of uterus are rare. Leiomyoma of the round ligament can present as inguinal swelling mimicking an incarcerated/irreducible hernia / inguinal secondaries / lymph node. It arises from smooth muscle of round ligament. It can be diagnosed preoperatively by CT scan or following exploration. Surgery is the treatment of choice for this condition.

A Population based Study on Alcoholism among Adult Males in a Rural Area, Tamil Nadu, India.

BACKGROUND: India's reputation as a country with a culture of abstinence especially in matters regarding alcohol is underserved. There has been a rapid proliferation of city bars and nightclubs in recent years and people are fast shedding its inhibitions about alcohol as a lifestyle choice. This scenario has led to fears of an undocumented rise in alcohol abuse among all sections of society. Policies by the government has been laid down to regulate sales and pricing of alcohol, but not well improvised. Our aim was to find out the prevalence of alcoholism among adult males in a rural population and also to analyze its association between various factors. MATERIALS AND METHODS: A cross sectional study in a rural population at Kuthampakkam village, in Poonamallee block of Tiruvallur district in Tamil Nadu, India. The study population included adult male population. Simple random sampling method was adopted. A structured questionnaire was used to collect information regarding the background characteristics, history of alcoholism and certain social factors. STATISTICAL ANALYSIS: Data entry and analysis was done using Statistical Package for Social Sciences (SPSS) version 15 software. Descriptive statistics were calculated for background variables and the prevalence of the alcoholism. Chi-square test and p-value were calculated to see the association between alcoholism and social factors. RESULTS: A total of 157 adult male were enrolled in the study. The mean age of the study participants was 37.20 years. The prevalence of alcoholism among the study participants was 35.7%. Among them only 4.5% who presented with symptoms of chronic alcoholism had taken treatment. Reasons for not taking treatment for alcoholism among study population were mainly due to their family problems (55.2%). CONCLUSION: Although alcohol consumption has existed for many centuries, the quantity, usage pattern, and resultant problems have undergone substantial changes over the past 20 years. These developments have raised concerns about the public health and social consequences. Awareness among the population and necessary rehabilitation and self-help programs will help in bringing down the prevalence of alcoholism.

Comparative Study to Assess the Effectiveness of Various Disinfecta- nts on two Microorganisms and the effect of same on Flexural Strength of Acrylic Denture Base Resin - An In Vitro Study.

BACKGROUND: To evaluate and compare the effectiveness of various disinfectants on Candida albicans (C.albicans) and Staphylococcus aureus (Staph.aureus) inoculated on acrylic denture base resin and effect of disinfectants on flexural strength of denture base resin. MATERIALS & METHODS: A total of 130 acrylic denture base resin specimens were fabricated and processed according to manufacturer instructions. 82 sterile specimens were used for microbiological study. 2 specimens were cultured for organism growth to ensure sterility. 40 sterile specimens each were inoculated by immersing in Sabouraud & Nutrient broth containing microorganisms for 45 minutes each. Then the specimens were immersed in chlorhexidine, glutaraldehyde & distilled water (control) for 4 & 8 minutes. Then the specimens were neutralized. After neutralization the specimens were cultured onto Sabouraud's broth for C.albicans and Nutrient broth for Staph.aureus incubated for 72 h and observed for turbidity. At the end of 72 h subculture were made onto Sabourads dextrose agar media for C.albicans, Blood agar media for Staph.aureus and incubated for 48 h to observe growth. For flexural strength testing, 8 specimens each was immersed in the above mentioned disinfectants and distilled water for 8 & 16 minutes. Each of which was then subjected to 3 point flexural load in Lloyd's Universal testing machine. The peak load was recorded and flexural strength values were calculated. RESULTS: The microbiological study revealed that both disinfectants were equally effective at 4 minutes against C.albicans & Staph.aureus microorganisms. Flexural strength test revealed no significant difference between test and control groups. CONCLUSION: Chlorhexdine and Glutaraldehyde disinfectans are equally effective against C.albicans and Staph.aureus microorganisms. Heat polymerized acrylic denture base resin did not demonstrate any significant change in flexural strength between control and test specimens. How to cite this article: Ganesh S, Gujjari A K, Shylesh K B S, Ravi M B, Sowmya S, Meenakshi S.Comparative Study to Assess the Effectiveness of Various Disinfectants on two Microorganisms and the effect of same on Flexural Strength of Acrylic Denture Base Resin - An In Vitro Study. J Int Oral Health 2013; 5(3):55-62.

Intraoperative high-dose-rate 192Ir radical implant in early breast cancer: a quality assurance and dosimetry study.

PURPOSE: To evaluate the variability in catheter length, geometry, and dosimetric parameters of radical intraoperative high-dose-rate breasts implant during 7-11 days. METHODS AND MATERIALS: Simulator X-rays, CT scans, and dosimetric studies were repeated on alternate days in 14 consecutive patients treated with radical intraoperative two- or three-plane nylon catheter high-dose-rate implant (34 Gy in 10 fractions within 5 days). RESULTS: Significant variation was found in catheter length, but no major change was noted in implant geometry, homogeneity, or inhomogeneity indexes. A variation in length of >5 mm in one or more catheters was seen in all patients and >10 mm in 11 patients at any time during the implant. Of the 171 catheters in 14 patients, 100 (58%) and 38 (22%) showed a variation of >5 mm or >10 mm, respectively. The variation of >10 mm was reduced from 32% of catheters in the first 5 patients to 17% in the subsequent 9 patients (p = 0.028). Rigid catheter fixation might reduce length variation but may cause skin necrosis if the expanding cavity indents the skin for a long period against the fixation device. A dose homogeneity index of 0.90 (range 0.85-0.92) and dose nonuniformity ratio of 0.20 (range 0.12-0.25) were satisfactory. CONCLUSION: The catheter fixation and exit catheter length should be measured daily and if the implant is in situ for more than a few days, orthogonal X-rays and, if indicated, dosimetry should be repeated at least once.