Efficacy of Ozone, UV Radiation, Herbal and Glutaraldehyde Method for Sterilisation of Elastomeric Impression Materials for Orthodontic and Prosthodontic procedures.

Objectives: The objectives of the current study was to evaluate the disinfection efficacy of ozone, ultraviolet (UV) radiation, herbal and glutaraldehyde method for sterilization of elastomeric impression materials. Materials and Methods: Disinfection of elastomeric impression material was performed with each of the disinfection methods: ozone, UV radiation, herbal, and glutaraldehyde. Later microbiological analysis was performed and the colony-forming units were evaluated and compared. Results: The highest disinfection efficacy was found with glutaraldehyde, followed by ozone and UV radiation, and the least with neem herbal rinse. Intergroup comparison was highly significant. Conclusion: Dry gaseous ozone and UV radiation can be used effectively for the disinfection of impressions.

A CBCT Assessment of Orthodontic Mini-Implant Placement.

Objectives: This study compares the precision of cone beam computed tomography (CBCT) and two-dimensional radiography for mini-implant implantation. Materials and Method: For 30 sites (in 15 patients between the ages of 13 and 26 years), the buccal interradicular region among the 2nd premolar and 1st molar was found to be the best location for mini-implants. Next, two groups of the mini-implant implantation process were created. Mini-implants were positioned at the CBCT data-identified sites in the CBCT group. Mini-implants were inserted in the RVG group by using two-dimensional digital radiography and a specially constructed guide. To assess the precision of the mini-implant implantation, post-placement CBCT images were acquired. The obtained data were statistically analyzed. Result: The two groups showed a statistically considerable variation in the mini-implant placement's departure from the optimal height. Due to the smaller interradicular space and decreased convenience in the posterior mandibular area, two out of 15 mini-implants in the RVG group demonstrated root contact in the mandibular jaw. Conclusion: The two-dimensional intraoral radiograph of the interradicular area provides sufficient information for mini-implant placement even though CBCT accurately visualizes the interradicular space in three dimensions.

Neuronal Vulnerability to Degeneration in Parkinson's Disease and Therapeutic Approaches.

Parkinson's disease is the second most common neurodegenerative disease affecting millions of people worldwide. Despite the crucial threat it poses, currently, no specific therapy exists that can completely reverse or halt the progression of the disease. Parkinson's disease pathology is driven by neurodegeneration caused by the intraneuronal accumulation of alpha-synuclein (α-syn) aggregates in Lewy bodies in the substantia nigra region of the brain. Parkinson's disease is a multiorgan disease affecting the central nervous system (CNS) as well as the autonomic nervous system. A bidirectional route of spreading α-syn from the gut to CNS through the vagus nerve and vice versa has also been reported. Despite our understanding of the molecular and pathophysiological aspects of Parkinson's disease, many questions remain unanswered regarding the selective vulnerability of neuronal populations, the neuromodulatory role of the locus coeruleus, and alpha-synuclein aggregation. This review article aims to describe the probable factors that contribute to selective neuronal vulnerability in Parkinson's disease, such as genetic predisposition, bioenergetics, and the physiology of neurons, as well as the interplay of environmental and exogenous modulators. This review also highlights various therapeutic strategies with cell transplants, through viral gene delivery, by targeting α -synuclein and aquaporin protein or epidermal growth factor receptors for the treatment of Parkinson's disease. The application of regenerative medicine and patient-specific personalized approaches have also been explored as promising strategies in the treatment of Parkinson's disease.

DEGREE AND FACTORS OF BURNOUT AMONG EMERGENCY HEALTHCARE WORKERS IN INDIA.

OBJECTIVE: 'Burnout' among emergency healthcare workers needs focus as they make crucial life changing decisions every day and thus, their state of physical and mental wellbeing is an absolute necessity. We aimed to find the level and factors contributing to burnout among the healthcare workers in the busiest Emergency Department of Northeast India. This is the first study done in this department to assess burnout. METHOD: This cross-sectional, questionnaire-based study assessed burnout of the doctors, nurses, and paramedics working in an emergency department of a busy tertiary care teaching institute. Association of demographic variables and factors influencing burnout was explored. Results were analyzed by descriptive and inferential statistics. RESULTS: Low level in emotional exhaustion, moderate level in depersonalization, and moderate level in the lack of personal accomplishment was reported by participants. Children and partner were found to be protective factors. Working hours, duration and status (permanent/contractual) of service influenced burnout. CONCLUSION: Knowing the level of burnout and their determinants can help in formulating measures of improving the work environment. A healthy workforce ensures high quality of healthcare and patient satisfaction.

A new method for QRS detection in ECG signals using QRS-preserving filtering techniques.

Detection of QRS complexes in ECG signals is required for various purposes such as determination of heart rate, feature extraction and classification. The problem of automatic QRS detection in ECG signals is complicated by the presence of noise spectrally overlapping with the QRS frequency range. As a solution to this problem, we propose the use of least-squares-optimisation-based smoothing techniques that suppress the noise peaks in the ECG while preserving the QRS complexes. We also propose a novel nonlinear transformation technique that is applied after the smoothing operations, which equalises the QRS amplitudes without boosting the supressed noise peaks. After these preprocessing operations, the R-peaks can finally be detected with high accuracy. The proposed technique has a low computational load and, therefore, it can be used for real-time QRS detection in a wearable device such as a Holter monitor or for fast offline QRS detection. The offline and real-time versions of the proposed technique have been evaluated on the standard MIT-BIH database. The offline implementation is found to perform better than state-of-the-art techniques based on wavelet transforms, empirical mode decomposition, etc. and the real-time implementation also shows improved performance over existing real-time QRS detection techniques.

QRS complex detection in ECG signals using locally adaptive weighted total variation denoising.

The QRS complex is the most prominent feature in the electrocardiogram (ECG), therefore, its detection is required for delineation of other waves and segments in the ECG and derivation of additional clinically useful information. QRS detection is complicated by factors like varying QRS morphologies, noise, artefacts and interference from tall and pointed P- and T-waves. In this paper, we propose a novel technique for QRS detection by preprocessing the ECG using weighted total variation (WTV) denoising. A local estimate of noise in the signal block under consideration is used to determine the regularization parameter in WTV minimization, which determines the amount of smoothing applied. This makes the denoising locally adaptive. The weights are chosen so as to give preference to preservation of QRS complexes over P- and T-waves while smoothing. Thus, the technique can simultaneously reduce the higher frequency noise as well as the lower frequency interference from P- and T-waves, in spite of the fact that they have overlapping spectra with the QRS complexes. The proposed method is evaluated on the MIT-BIH arrhythmia database and gives improved detection accuracy over established and state-of-the-art techniques. The technique has low computational load, therefore, it can be used for fast offline QRS detection in long duration ECG records, as well as real-time QRS detection in block-by-block processing mode. The average values of sensitivity, positive predictivity and detection error rate are 99.90%, 99.88% and 0.23%, for the offline implementation, respectively, and 99.86%, 99.85% and 0.29%, for the real-time mode, respectively.