Comparison of light microscopy and digital microscopy for learning oral pathology practicals among second year dental students.

Background/purpose: Previous studies have shown that digital microscopy is an indispensable tool for teaching oral pathology laboratory course. Despite this, our institute relies solely on recommended/reference book images for oral pathology practicals, neglecting both light and digital microscopy methods. Gathering students' feedback on these methods is essential before considering digital microscopy as part of the oral pathology curriculum. Therefore, this study aimed to compare the usefulness of light and digital microscopy among second-year dental students. Materials and methods: The study was conducted from December 6 to December 7, 2023, in the Department of Oral Pathology, Dr. Ishrat-ul-Ibad Khan Institute of Oral Health Sciences, Dow University of Health Sciences. The study involved the selection of five cases from the oral pathology course, followed by feedback on students' diagnostic skills, learning impact and acceptance rate of light and digital microscopy using an online questionnaire. Mann-Whitney U test was used to compare students' responses and P-value < 0.05 was set as statistically significant. Results: There was a statistically significant difference in diagnostic scores between light microscopy and digital microscopy (P < 0.05). Statistically significant differences favoring digital microscopy were observed in various aspects, including interpreting variations, diagnosis, time efficiency, and image clarity. Conclusion: Although diagnostic scores were lower, digital microscopy was perceived as a useful method for enhancing diagnostic skills among dental students. Both light microscopy and digital microscopy are viable options for oral pathology practicals, however, digital microscopy was preferred by students due to its time efficiency and clear image quality.

Integrating machine and deep learning technologies in green buildings for enhanced energy efficiency and environmental sustainability.

A green building (GB) is a design idea that integrates environmentally conscious technology and sustainable procedures throughout the building's life cycle. However, because different green requirements and performances are integrated into the building design, the GB design procedure typically takes longer than conventional structures. Machine learning (ML) and other advanced artificial intelligence (AI), such as DL techniques, are frequently utilized to assist designers in completing their work more quickly and precisely. Therefore, this study aims to develop a GB design predictive model utilizing ML and DL techniques to optimize resource consumption, improve occupant comfort, and lessen the environmental effect of the built environment of the GB design process. A dataset ASHARE-884 is applied to the suggested models. An Exploratory Data Analysis (EDA) is applied, which involves cleaning, sorting, and converting the category data into numerical values utilizing label encoding. In data preprocessing, the Z-Score normalization technique is applied to normalize the data. After data analysis and preprocessing, preprocessed data is used as input for Machine learning (ML) such as RF, DT, and Extreme GB, and Stacking and Deep Learning (DL) such as GNN, LSTM, and RNN techniques for green building design to enhance environmental sustainability by addressing different criteria of the GB design process. The performance of the proposed models is assessed using different evaluation metrics such as accuracy, precision, recall and F1-score. The experiment results indicate that the proposed GNN and LSTM models function more accurately and efficiently than conventional DL techniques for environmental sustainability in green buildings.

Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption.

Green building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts for almost 40% of global energy consumption. Despite their importance, challenges such as occupant behavior and energy management gaps often result in GBs consuming up to 2.5 times more energy than intended. To address this, Building Automation Systems (BAS) play a crucial role in enhancing energy efficiency. This research develops a predictive model for GB design using machine learning to minimize energy consumption and improve indoor sustainability. The dataset is utilized to predict cooling and heating individually, with data visualization by graphically illustrating dataset features and preprocessing through Z-Score normalization and dataset splitting. The proposed model, based on active learning and utilizing ML regressors such as Random Forest (RF), Decision Tree (DT), Gradient Boosting (GB), Extreme Gradient Boosting (XGBoost), CatBoost (CB), Light Gradient Boosting Machine (LGBM), K-Nearest Neighbor (KNN), and Logistic Regressor (LR), shows significant performance improvements. The CBR-AL model achieves impressive results with values of 0.9975 for cooling (Y1) and 0.9883 for heating (Y2), indicating a high level of accuracy. The model's success in reducing energy consumption and improving sustainability has potential ripple effects, including substantial cost savings, reduced carbon footprints, and improved operational efficiency in green buildings. This approach not only enhances environmental sustainability but also sets a benchmark for future advancements in predictive modelling for energy management.

Comparison of virtual clinical scenario and role play in learning oral pathology among dental students.

In oral pathology, virtual clinical scenario illustrating dentist-patient interactions can be utilized by both students and health professionals to deliver/gain knowledge and make clinical diagnosis of oral lesions. Role play is also an educational technique which is designed to engage and motivate students in classrooms. This study aimed to compare usefulness of virtual clinical scenario and role play in learning oral pathology among second-year dental students. The students were randomly divided to one of the two groups: virtual clinical scenario group (n = 50) and role play group (n = 50). Virtual clinical scenario group was provided with virtual clinical cases of oral lesions through Google Forms whereas role play group was exposed to virtual clinical cases of oral lesions through role playing activity. Both groups underwent assessments before and after the intervention. Students' perceptions on usefulness of both techniques in terms of diagnosis, visual parameters and impact on learning were evaluated by feedback questionnaire. Data were analyzed using Statistical Package for the Social Sciences version 27.0. Wilcoxon signed-rank test was used to compare pre-test and post-test scores. Additionally, the scores and students' responses from both groups were compared using the Mann-Whitney U test. A P-value of < 0.05 was set as statistically significant. Students in both groups showed significantly higher post-test scores compared to their pre-test scores (P < 0.001). However, the role play group outperformed the virtual clinical scenario group, with a significantly higher post-test score (P = 0.04). Furthermore, feedback concerning role play was significantly higher than that for the virtual clinical scenario across multiple aspects (P < 0.05). Our findings suggest that role play emerges as the preferred method, significantly enhancing dental students' learning experiences in oral pathology.

Exploring the China-Pakistan economic corridor project performance during Covid-19 pandemic.

The outburst of the coronavirus into the global arena, first as a respiratory disease and later as a worldwide pandemic and health emergency, pushed the world economic order into complete turmoil and aftermath, posing severe challenges to the financial stability of developing countries like Pakistan. The temporary suspension of economic activities worldwide has resulted in significant disruptions to international supply chains, leading to substantial delays in implementing infrastructure projects associated with the China-Pakistan Economic Corridor (CPEC). The pandemic has further hindered CPEC progress. Building mega-projects, such as the CPEC, is crucial in determining the economic stability of a nation such as Pakistan. Nevertheless, it is essential to consider that the implementation of infrastructure projects can be subject to delays due to the COVID-19 lockdown and travel restrictions. However, it is worth noting that there needs to be more scholarly research available examining the ongoing progress and performance of CPEC projects from a particular perspective. This study aims to assess the impact of the COVID-19 lockdown policy and travel restrictions on CPEC project performances by highlighting the role of socioeconomic and infrastructure development factors. The study will shed light on numerous causes of concerns in project development phases and provide policy recommendations to help CPEC officials reduce project losses and better survival in the event of extreme uncertainty. The data were collected through an online survey from all over Pakistan using self-administered questionnaires with 570 responses from CPEC employees, officials, and professors from management and economic departments. The structural equation modeling (SEM) technique analyzes the problem mentioned above. As per the results of this study, it is evident that the COVID-19 lockdown policy and travel restrictions have a detrimental effect on the construction of the CPEC project. Moreover, it has been observed that the socioeconomic and infrastructure development associated with the CPEC has a notable impact on the performance of the CPEC projects. This paper aims to provide valuable insights to policymakers by examining the management of the COVID-19 pandemic from the perspective of the CPEC.

Oral Squamous Cell Carcinoma Clinico-pathological features in relation to Tumor Stage; AJCC 2018 perspective.

Objective: To investigate the association between clinicopathological findings and tumor stage according to AJCC 2018 guidelines in patients suffering from Oral squamous cell carcinoma (OSCC). Methods: A descriptive study was conducted from January 2019 to January 2020 at King Edward Medical University and University of Health Sciences on a total of 49 patients enrolled after obtaining written informed consent. Clinical and radiographic findings were recorded. Pathological reporting was done using AJCC 2018 cancer staging guidelines. Association between clinicopathological features with tumor stage and grade was assessed using Chi-square and Kruskal-Wallis test. Result: Mean age of the patients was 46.1 ± 10.6 years. Most of the tumors were of well differentiated type (49%) and moderately differentiated (40.8%) with predominant clinical stage III in 42.9% & IV in 44.9 % and primary tumor stage pT2 28.6% & pT3 36.7%. Significant difference was seen for primary tumor stage in relation to age, gender, depth of invasion, primary site, and size of tumor (p < 0.01). For clinical stages, significant difference was observed in the age, gender, size of tumor, nodal metastasis, and anatomical tumor site (p < 0.01). Conclusion: Application of 8th Edition AJCC guidelines identifies the importance of the latest classification with strong association of latest stage criteria with age, gender, site of primary tumor, tumor thickness, depth of invasion, nodal metastasis and size of largest lymph node involved, and Level of Lymph node involved (level III & V) in a subset of patients from a developing country.

Surgical treatment of zygomatic bone fracture using two points fixation versus three point fixation--a randomised prospective clinical trial.

BACKGROUND: The zygoma plays an important role in the facial contour for both cosmetic and functional reasons; therefore zygomatic bone injuries should be properly diagnosed and adequately treated. Comparison of various surgical approaches and their complications can only be done objectively using outcome measurements which in turn require protocol management and long-term follow up. The preference for open reduction and internal fixation of zygomatic fractures at three points has continued to grow in response to observations of inadequate results from two point and one point fixation techniques.The objectives of this study were to compare the efficacy of zygomatic bone after treatment with ORIF using 2 point fixation and ORIF using 3 point fixation and compare the outcome of two procedures. METHODS: 100 patients were randomly divided equally into two groups. In group A, 50 patients were treated by ORIF using two point fixation by miniplates and in group B, 50 patients were treated by ORIF using three point fixation by miniplates. They were evaluated for their complications during and after surgery with their advantages and disadvantages and the difference between the two groups was observed. RESULTS: A total of 100 fractures were sustained. We found that postoperative complication like decreased malar height and vertical dystopia was more common in those patients who were treated by two point fixation than those who were treated with three point fixation. CONCLUSIONS: Based on this study open reduction and internal fixation using three point fixation by miniplates is the best available method for the treatment zygomatic bone fractures.

Modern surgical management of tongue carcinoma - a clinical retrospective research over a 12 years period.

OBJECTIVES: In this retrospective study, we present a clinical review of our experience with tongue cancer in order to obtain valid criteria for therapeutic decision-making. MATERIALS AND METHODS: Between August 1999 and June 2011, a total of 398 patients with squamous cell carcinoma of the tongue were treated at the Department of Oral and Maxillofacial Surgery, King Edward Medical University Lahore Pakistan. Data concerning patient characteristics, clinical and pathologic tumour characteristics and treatment strategies and their results were obtained from a retrospective review of medical records. The average follow-up was 4.6 years. Statistical analysis for survival was calculated by the method of Kaplan and Meier. RESULTS: There were 398 total patients. The mean age at diagnosis was 49.5 years,. 224 (56.3%) were male and 174 (43.7%) female (male/female ratio = 1.3:1).332/398 patients received surgical treatment, whereas 66 patients were excluded from surgical treatment and received primary radio (chemo) therapy after biopsy. Tongue carcinoma patients treated by non surgical treatment modalities had 5 years survival rate of 45.5% and patients with surgical intervention had survival rate of 96.1%. CONCLUSIONS: We recommend categorical bilateral neck dissection in order to reliably remove occult lymph node metastases. Adjuvant treatment modalities should be applied more frequently in controlled clinical trials and should generally be implemented in cases with unclear margins and lymphatic spread. CLINICAL RELEVANCE: This study provides modern treatment strategies for the tongue carcinoma.