Lysosomal cation channel TRPML1 suppression sensitizes acute myeloid leukemia cells to chemotherapeutics by inhibiting autophagy.

Despite the implementation of novel therapeutic regimens and extensive research efforts, chemoresistance remains a formidable challenge in the treatment of acute myeloid leukemia (AML). Notably, the involvement of lysosomes in chemoresistance has sparked interest in developing lysosome-targeted therapies to sensitize tumor cells to currently approved chemotherapy or as innovative pharmacological approaches. Moreover, as ion channels on the lysosomal membrane are critical regulators of lysosomal function, they present potential as novel targets for enhancing chemosensitivity. Here, we discovered that the expression of a lysosomal cation channel, namely transient receptor potential mucolipin 1 (TRPML1), was elevated in AML cells. Inhibiting TRPML1 individually does not impact the proliferation and apoptosis of AML cells. Importantly, inhibition of TRPML1 demonstrated the potential to modulate the sensitivity of AML cells to chemotherapeutic agents. Exploration of the underlying mechanisms revealed that suppression of TRPML1 impaired autophagy while concurrently increasing the production of reactive oxygen species (ROS) and ROS-mediated lipid peroxidation (Lipid-ROS) in AML cells. Finally, the knockdown of TRPML1 significantly reduced OCI-AML3 tumor growth following chemotherapy in a mouse model of human leukemia. In summary, targeting TRPML1 represents a promising approach for combination therapy aimed at enhancing chemosensitivity in treating AML.

A scoping review on the epidemiology and public significance of Brucella abortus in Chinese dairy cattle and humans.

Brucellosis, caused by Brucella spp., is a re-emerging One Health disease with increased prevalence and incidence in Chinese dairy cattle and humans, severely affecting animal productivity and public health. In dairy cattle, B. abortus is the primary causative agent although infections with other Brucella species occur occasionally. However, the epidemiological and comparative importance of B. abortus in dairy cattle and humans remains inadequately understood throughout China due to the heterogeneity in locations, quality, and study methods. This scoping review aims to describe the changing status of B. abortus infection in dairy cattle and humans, investigate the circulating Brucella species and biovars, and identify factors driving the disease transmission by retrieving publicly accessible literature from four databases. After passing the prespecified inclusion criteria, 60 original articles were included in the final synthesis. Although the reported animal-level and farm-level prevalence of brucellosis in dairy cattle was lower compared to other endemic countries (e.g. Iran and India), it has been reported to increase over the last decade. The incidence of brucellosis in humans displayed seasonal increases. The Rose Bengal Test and Serum Agglutination Test, interpreted in series, were the most used serological test to diagnose Brucella spp. in dairy cattle and humans. B. abortus biovar 3 was the predominant species (81.9%) and biovar (70.3%) in dairy cattle, and B. melitensis biovar 3 was identified as the most commonly detected strain in human brucellosis cases. These strains were mainly clustered in Inner Mongolia and Shannxi Province (75.7%), limiting the generalizability of the results to other provinces. Live cattle movement or trade was identified as the key factor driving brucellosis transmission, but its transmission pattern remains unknown within the Chinese dairy sector. These knowledge gaps require a more effective One Health approach to be bridged. A coordinated and evidence-based research program is essential to inform regional or national control strategies that are both feasible and economical in the Chinese context.

A novel Bayesian Latent Class Model (BLCM) evaluates multiple continuous and binary tests: A case study for Brucella abortus in dairy cattle.

Bovine brucellosis, primarily caused by Brucella abortus, severely affects both animal health and human well-being. Accurate diagnosis is crucial for designing informed control and prevention measures. Lacking a gold standard test makes it challenging to determine optimal cut-off values and evaluate the diagnostic performance of tests. In this study, we developed a novel Bayesian Latent Class Model that integrates both binary and continuous testing outcomes, incorporating additional fixed (parity) and random (farm) effects, to calibrate optimal cut-off values by maximizing Youden Index. We tested 651 serum samples collected from six dairy farms in two regions of Henan Province, China with four serological tests: Rose Bengal Test, Serum Agglutination Test, Fluorescence Polarization Assay, and Competitive Enzyme-Linked Immunosorbent Assay. Our analysis revealed that the optimal cut-off values for FPA and C-ELISA were 94.2 mP and 0.403 PI, respectively. Sensitivity estimates for the four tests ranged from 69.7% to 89.9%, while specificity estimates varied between 97.1% and 99.6%. The true prevalences in the two study regions in Henan province were 4.7% and 30.3%. Parity-specific odds ratios for positive serological status ranged from 1.2 to 2.2 for different parity groups compared to primiparous cows. This approach provides a robust framework for validating diagnostic tests for both continuous and discrete tests in the absence of a gold standard test. Our findings can enhance our ability to design targeted disease detection strategies and implement effective control measures for brucellosis in Chinese dairy farms.