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This retrospective study is aimed at developing a web‐based artificial intelligence (AI) software (DiagnoCat) for periodontal bone loss detection on panoramic radiographs and evaluating the model's performance by comparing it with clinicians' results. Separate models are trained for tooth and periodontal bone loss detection. The first model's objective was to detect teeth, segmenting their masks, and to define their numbering and developed with Mask R‐CNN using pretrained ResNet‐101 as a backbone. The second model was based on Cascade R‐CNN architecture and used for bone loss prediction. Around 100 radiographs are evaluated by three clinicians regarding tooth identification and periodontal bone loss, separately. Ground truth is determined by the consensus and model's performance is evaluated with kappa, precision, recall, and F‐score statistics. For tooth conditions, the overall F‐score, accuracy, and Cohen's kappa coefficients were found to be 0.948, 0.977, and 0.933 for the binary, and 0.992, 0.988, and 0.961 for the multiclass results. For bone loss detection, the overall F‐score, accuracy, and Cohen's kappa coefficients were found to be 0.985, 0.980, and 0.956 for the binary, and 0.996, 0.993, and 0.974 for the multiclass results. The results of this study suggest that the use of a web‐based AI software (DiagnoCat) can be beneficial in detecting periodontal bone loss on panoramic radiographs. [ABSTRACT FROM AUTHOR]

The current study was undertaken to investigate the macroinvertebrate community and physico-chemical features of Anchar Lake of Kashmir. Sampling of macroinvertebrates was performed using a handmade D-frame net and Ekman dredge, while physico-chemical analysis was conducted according the standards methods of the American Public Health Association. A total of 20 macroinvertebrate taxa were recorded belong to phylum Annelida, Arthropoda and Mollusca, representing six classes, 13 orders and 18 families. The mean value of several biotic indices was computed: 2.31 for Shannon-Wiener index, 0.87 for Simpson's index, 1.58 for Margalef 's index and 0.17 for evenness index. Water analysis revealed that the lake was eutrophic, alkaline, highly productive, and had hard water that was organically polluted. The quality of water, organic rich bottom sediment, density and architecture of macrophytes were found to be vital factors determining the abundance, diversity and patterns in distribution of macroinvertebrate fauna of the lake. Further, anthropogenic pressure in the lake catchment area was observed as potential force behind the current ecological conditions of lake. The study concluded that the lake is under extreme anthropogenic stress and is victim of severe pollution, therefore requiring immediate restoration measures. [ABSTRACT FROM AUTHOR]

Byline: Aditi. Dewan, Anuja. Gupta, Priti. Trivedi, Gaurav. Agrawal, Dipak. Patel, Manoj. Shah Sir, Actinomyces are slow growing, non-spore forming gram-positive, branching bacilli that thrive in anaerobic and microaerophilic conditions [...]

Byline: Priti. Trivedi, Anuja. Gupta, Sunil. Pasricha, Dipak. Patel Pituitary carcinomas are rare adenohypophyseal tumors with cerebrospinal or extracranial metastasis. None of the histologic findings distinguish pituitary adenoma from carcinoma. [...]