• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.2
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• pp.79-85
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• 2023

The Tibetan Plateau is home to the only alpine crane species, the black-necked crane (Grus nigricollis). Conservation efforts are severely hampered by a lack of knowledge on the spatial distribution and breeding habitats of this species. The ecological niche modeling framework used to predict the spatial distribution of this species, based on the maximum entropy and occurrence record data, allowed us to generate a species-specific spatial distribution map in Ladakh, Trans-Himalaya, India. The model was created by assimilating species occurrence data from 486 geographical sites with 24 topographic and bioclimatic variables. Fourteen variables helped forecast the distribution of black-necked cranes by 96.2%. The area under the curve score for the model training data was high (0.98), indicating the accuracy and predictive performance of the model. Of the total study area, the areas with high and moderate habitat suitability for black-necked cranes were anticipated to be 8,156 km² and 6,759 km², respectively. The area with high habitat suitability within the protected areas was 5,335 km². The spatial distribution predicted using our model showed that the majority of speculated conservation areas bordered the existing protected areas of the Changthang Wildlife Sanctuary. Hence, we believe, that by increasing the current study area, we can account for these gaps in conservation areas, more effectively.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.12
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• pp.4957-4961
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• 2014

Background: Head and neck cancer without distant metastases is amenable to various modalities of treatment. However, the stage at presentation is a very important determinant for treatment success. The present study was conducted to determine the stage-wise presentation of non-metastatic head and neck cancer patients from the hilly regions in Kumaon division of Uttarakhand, India. Materials and Methods: The hospital records for non-metastatic head and neck cancer patients from the only functional cancer centre of the region for the period of two-years (January 2012-December 2013) were included. Nasopharyngeal carcinoma was excluded due to its staging system being different. Non-squamous histopathologies were also excluded. Patients hailing from nearby regions of Uttar Pradesh and Nepal were excluded, as were patients from non-hilly regions of Kumaon. Results: Of the 271 patients of head and neck cancer, 27 with distant metastases at diagnosis were excluded from the analysis. Of the 244 eligible patient records, 90.1% (n=222) were male, and 9.9% (n=22) were female. The proportions of patients with carcinoma of the larynx, oropharynx, oral cavity, hypopharynx and maxillary antrum were 31.9% (n=78), 27.9% (n=68), 20.5% (n=50), 12.7% (n=31) and 1.2% (n=3). A further 5.7% (n=14) were diagnosed as having secondary involvement of neck nodes with unknown primaries. The proportion of patients presenting in stages I, II, III, IVA and IVB were 0.8% (n=2), 2.5% (n=6), 9.4% (n=23), 51.6% (n=126) and 35.7% (n=87) respectively. Conclusions: An abysmally low proportion (3.3%) of non-metastatic head and neck cancer patients presented in the early stages (I and II). A vast majority of the patients (88.1%) presented with stages IVA and IVB. Not only does this reflect a poor therapeutic outlook, but also exposes the dire need for programmes focusing on cancer awareness and early detection in the region.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.12
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• pp.4981-4985
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• 2015

Background: Colorectal cancer (CRC) is a leading cause of morbidity and mortality worldwide. Targeting autophagic cell death is emerging as a novel strategy in cancer chemotherapy. Aldose reductase (AR) catalyzes the rate limiting step of the polyol pathway of glucose metabolism; besides reducing glucose to sorbitol, AR reduces lipid peroxidation-derived aldehydes and their glutathione conjugates. A complex interplay between autophagic cell death and/or survival may in turn govern tumor metastasis. This exploratory study aimed to investigate the potential role of AR inhibition using a novel inhibitor Fidarestat in the regulation of autophagy in CRC cells. Materials and Methods: For glucose depletion (GD), HT-29 and SW480 CRC cells were rinsed with glucose-free RPMI-1640, followed by incubation in GD medium +/- Fidarestat ($10{\mu}M$). Proteins were extracted by a RIPA-method followed by Western blotting ($35-50{\mu}g$ of protein; n=3). Results: Autophagic regulatory markers, primarily, microtubule associated protein light chain (LC) 3, autophagy-related gene (ATG) 5, ATG 7 and Beclin-1 were expressed in CRC cells; glyceraldehyde-3 phosphate dehydrogenase (GAPDH) was used as an internal reference. LC3 II (14 kDa) expression was relatively high compared to LC3A/B I levels in both CRC cell lines, suggesting occurrence of autophagy. Expression of non-autophagic markers, high mobility group box (HMG)-1 and Bcl-2, was comparatively low. Conclusions: GD +/- ARI induced autophagy in HT-29 and SW-480 cells, thereby implicating Fidarestat as a promising therapeutic agent for colorectal cancer; future studies with more potent ARIs are warranted to fully dissect the molecular regulatory networks for autophagy in colorectal carcinoma.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.10
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• pp.5195-5199
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• 2012

Objectives: Global cancer statistical data show that India has one of the highest incidence rates of oral cancer worldwide. Early detection is extremely important as it results in lower morbidity and death rates. The present study was undertaken to assess awareness of oral cancer and knowledge of its early signs and risk factors in the general public of the semi-urban Gorakhpur area of Uttar Pradesh (India). It was also intended to educate the same population for early detection by increasing their ability to recognize signs and risk factors. Method: A questionnaire-based household survey was conducted over a period of one month in different parts of Gorakhpur district, a region where tobacco use is apparently very high. A total of 2,093 persons participated in the survey. The collected data were analyzed using SPSS software to assess and associate oral cancer awareness with the prevalence, and abstract risk factors, as well as other confounding variables. Results: The general awareness, knowledge of signs and risk factors of oral cancer were found to be proportionate to the literacy level with the highest rate of awareness being among high school and graduates and lowest among illiterates. It was also observed that on most of these dimensions the younger age groups (<30 years) were significantly more knowledgeable. Conclusion: Overall, the awareness of oral cancer in the high-risk population of Gorakhpur was not satisfactory, pointing to a need for further dissemination of information on this issue and its associated risks. This is especially important for the youngsters, as this may possibly help them keep away from the deleterious habit of tobacco indulgence in any form. If necessary risk factor cessation counselling should be provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.1
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• pp.46-63
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• 2024

One of the biggest dangers in the globe is water contamination. Water is a necessity for human survival. In most cities, the digging of borewells is restricted. In some cities, the borewell is allowed for only drinking water. Hence, the scarcity of drinking water is a vital issue for industries and villas. Most of the water sources in and around the cities are also polluted, and it will cause significant health issues. Real-time quality observation is necessary to guarantee a secure supply of drinking water. We offer a model of a low-cost system of monitoring real-time water quality using IoT to address this issue. The potential for supporting the real world has expanded with the introduction of IoT and other sensors. Multiple sensors make up the suggested system, which is utilized to identify the physical and chemical features of the water. Various sensors can measure the parameters such as temperature, pH, and turbidity. The core controller can process the values measured by sensors. An Arduino model is implemented in the core controller. The sensor data is forwarded to the cloud database using a WI-FI setup. The observed data will be transferred and stored in a cloud-based database for further processing. It wasn't easy to analyze the water quality every time. Hence, an Optimized Neural Network-based automation system identifies water quality from remote locations. The performance of the feed-forward neural network classifier is further enhanced with a hybrid GA- PSO algorithm. The optimized neural network outperforms water quality prediction applications and yields 91% accuracy. The accuracy of the developed model is increased by 20% because of optimizing network parameters compared to the traditional feed-forward neural network. Significant improvement in precision and recall is also evidenced in the proposed work.