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Objectives: This study investigates the dual role of ALKBH5, an eraser enzyme, in colorectal cancer (CRC), focusing on how N6-methyladenosine (m6A) mutations influence CRC development and progression., Methods: We reviewed various studies that highlighted the role of ALKBH5 in colorectal cancer (CRC). This includes the impact of ALKBH5 on tumor cell behavior including immune system interactions, invasion, and proliferation in CRC. We also looked into how ALKBH5 acts as a tumor suppressor under different conditions analyzed clinical data to assess the impact of ALKBH5 expression on outcomes in colorectal cancer patients., Key Findings: In CRC, ALKBH5 plays a dual role. In certain situations, it inhibits the progression of the tumor, but in other circumstances, it promotes tumor growth and immunosuppression. The interaction with RABA5 plays a role in the development of CRC. Having elevated levels of ALKBH5 has been associated with unfavorable patient outcomes, such as reduced survival rates and more advanced cancer stages. Various factors, including tumor differentiation, TNM stages, and carcinoembryonic antigen (CEA) levels, be linked to ALKBH5 expression., Conclusions: ALKBH5 plays a complicated and situation-specific role in colorectal cancer (CRC). Targeting ALKBH5 could result in novel therapy options that balance its tumor-promoting and tumor-fighting properties in CRC. Further research into m6A alterations and ALKBH5 could enhance CRC treatment approaches and patient outcomes., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Royal Pharmaceutical Society. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

The Zigzag ladybird beetle, Cheilomenes sexmaculata (Fabricius) (Coleoptera: Coccinellidae), is a biological control agent that feeds on a variety of aphid species. Life table and predation data of C. sexmaculata were collected under laboratory conditions at 25±2⁰C, 60±5% RH and L14: D10 h in connection with feeding on four different aphid species; Lipaphis erysimi (Kaltenbach), Myzus persicae (Sulzer), Aphis nerii (Boyer de Fonscolombe) and Diuraphis noxia (Mordvilko). Larval development of C. sexmaculata was long when fed on M. persicae (12.18 days) and shorter on D. noxia (10.64 days). The male's lifespan was longer on M. persicae (26.70 days) and shorter on L. erysimi (23.67 days). Fecundity was maximum when the beetle was fed D. noxia (316.8 eggs/female) and minimum on M. persicae (199.1 eggs/female). Net reproductive rate, intrinsic rate of increase and finite rate of increase were highest on D. noxia with values of 158.4 (offspring individual-1), 0.22 d-1, and 1.24 d-1, respectively whereas the respective parameters were lowest on L. erysimi (99.5 offspring individual-1, 0.19 d-1, and 1.20 d-1, respectively). However, the mean of the generation (T) was shorter on A. nerii (22.48 d-1) and longer on M. persicae (24.68 d-1). Based on life table parameters obtained under laboratory conditions, the most appropriate host of C. sexmaculata was D. noxia. This study should help us to improve mass rearing and use of C. sexmaculata in the biological control of aphids on field and horticultural crops., Competing Interests: The authors have declared that no competing interests exist.

Feeding potential and foraging behavior are complimentary to determine the efficiency of a predator. The predatory potential of both grub and adult stages of Cheilomenes sexmaculata (F.) (Coleoptera: Coccinellidae) was investigated against different developmental stages of cotton whitefly, Bemisia tabaci Gennadius (Aleyrodidae: Hemiptera), under laboratory conditions (27 ± 2 °C; 70 ± 5% RH; 14 h L: 10 h D). Fourth instar grub of C. sexmaculata exhibited the highest feeding potential against the whitefly stages (41.74 adults, 33.41 pupae and 31.33 nymphs), whereas first instar grub exhibited the lowest feeding potential (10.15 adults, 9.15 pupae and 7.00 whitefly nymphs). The female beetle consumed the highest number of prey (1445.29 adults, 1364.88 pupae, and 1374.35 whitefly nymphs) followed by male beetle (1390.12 adults, 1308.18 pupae and 1325.35 whitefly nymphs). Both Roger's and Holling's models indicated a type II functional response curve for all the grub and adult stages of C. sexmaculata. Cheilomenes sexmaculata female showed the highest attack rate (4.65 h-1), and the maximum rate of predation 37.5 insects/day, whereas the male beetle recorded the lowest handling time (0.02 h). The fourth instar grub showed the highest attack rate (1.30 h-1) against the B. tabaci pupae, whereas the female beetle showed the maximum rate of predation 38.18 insects/day, with the lowest handling time (0.04 h). Female beetle showed the highest attack rate (6.87 h-1), whereas the fourth instar grub showed the maximum rate of predation 41.7 insects/day with the lowest handling time (0.01 h). Hence, it is advocated to release the fourth instar grubs and adult females of C. sexmaculata collectively for the augmentative biological control of B. tabaci in the IPM program. [ABSTRACT FROM AUTHOR]

Introduction: Medical image processing aimed at reducing human error rates attracted many researchers. The Segmentation of magnetic resonance image for tumor detection is one of the recognized challenges in the treatment of the disease. Considering the importance of this issue in the present study, the diagnosis of brain tumor is considered. Material and Methods: One of the most popular and most widely used methods in the field of segmentation of images of resonance imaging of the brain is the kmeans clustering algorithm, which, despite the diagnosis of a tumor, fall in to local optimum problem, followed by a reduction in the accuracy of the diagnosis tumors are malignant. In this study, we aimed to solve this problem and subsequently increase the accuracy of diagnosis of malignant tumors, a GAclustering combination of clustering based on k-means and genetic algorithms. Results: How to combine in the way that the genetic algorithm is applied to each repetition of the K-means algorithm and, by scanning more in the space of the answer, is trying to find higher quality cluster centers. The effectiveness of the proposed method has been investigated on a number of images of BRATS standard collections. It is also compared with the K-means algorithm. Conclusion: The results show that the proposed algorithm provides better results than the K-means algorithm. [ABSTRACT FROM AUTHOR]