CRISPR-Cas genome editing technologies have revolutionized the fields of functional genetics and genome engineering, but with the recent discovery and optimization of RNA-targeting Cas ribonucleases, we may soon see a similar revolution in the study of RNA function and transcriptome engineering. However, to date, successful proof of principle for Cas ribonuclease RNA targeting in eukaryotic systems has been limited. Only recently has successful modification of RNA expression by a Cas ribonuclease been demonstrated in animal embryos. This previous work, however, did not evaluate endogenous expression of Cas ribonucleases and only focused on function in early developmental stages. A more comprehensive evaluation of this technology is needed to assess its potential impact. Here we report on our efforts to develop a programmable platform for RNA targeting using a Cas ribonuclease, CasRx, in the model organism Drosophila melanogaster. By genetically encoding CasRx in flies, we demonstrate moderate transcript targeting of known phenotypic genes in addition to unexpected toxicity and lethality. We also report on the off-target effects following on-target transcript cleavage by CasRx. Taken together, our results present the current state and limitations of a genetically encoded programmable RNA-targeting Cas system in Drosophila melanogaster, paving the way for future optimization of the system.

CRISPR-Cas genome editing technologies have revolutionized the fields of functional genetics and genome engineering, but with the recent discovery and optimization of RNA-targeting Cas ribonucleases, we may soon see a similar revolution in the study of RNA function and transcriptome engineering. However, to date, successful proof-of-principle for Cas ribonuclease RNA targeting in eukaryotic systems has been limited. Only recently has successful modification of RNA expression by a Cas ribonuclease been demonstrated in animal embryos. This previous work, however, did not evaluate endogenous expression of Cas ribonucleases and only focused on Cas ribonuclease function in early developmental stages. A more comprehensive evaluation of this technology is needed to assess its potential impact in the field. Here we report on our efforts to develop a programmable platform for RNA-targeting using a Cas ribonuclease, CasRx, in the model organism Drosophila melanogaster. By genetically encoding CasRx in flies, we demonstrate moderate transcript targeting of known phenotypic genes in addition to unexpected toxicity and lethality. We also report on the off-target effects following on-target transcript cleavage by CasRx. Taken together, our results present the current state and limitations of a genetically encoded programmable RNA-targeting Cas system in Drosophila melanogaster, paving the way for future optimization of the system.

Calcium-dependent calpains are a family of cysteine proteases that have been demonstrated to play key roles in both platelet glycoprotein Ibα shedding and platelet activation and altered calpain activity is associated with thrombotic thrombocytopenic purpura. Calpain activators induce apoptosis in several types of nucleated cells. However, it is not clear whether calpain activators induce platelet apoptosis. Here we show that the calpain activator dibucaine induced several platelet apoptotic events including depolarization of the mitochondrial inner transmembrane potential, up-regulation of Bax and Bak, down-regulation of Bcl-2 and Bcl-XL, caspase-3 activation and phosphatidylserine exposure. Platelet apoptosis elicited by dibucaine was not affected by the broad spectrum metalloproteinase inhibitor GM6001. Furthermore, dibucaine did not induce platelet activation as detected by P-selectin expression and PAC-1 binding. However, platelet aggregation induced by ristocetin or α-thrombin, platelet adhesion and spreading on von Willebrand factor were significantly inhibited in platelets treated with dibucaine. Taken together, these data indicate that dibucaine induces platelet apoptosis and platelet dysfunction.

The current study provides preliminary evidence documenting the limited use of complementary therapies in rehabilitation settings and highlights the opportunity for further research, particularly regarding pain-related outcomes.

CasRx, a member of the RNA-targeting Cas13 family, is a promising new addition of the CRISPR/Cas technologies in efficient gene transcript reduction with an attractive off-target profile at both cellular and organismal levels. It is recently reported that the CRISPR/CasRx system can be used to achieve ubiquitous and tissue-specific gene transcript reduction in Drosophila melanogaster. This paper details the methods from the recent work, consisting of three parts: 1) ubiquitous in vivo endogenous RNA targeting using a two-component CasRx system; 2) ubiquitous in vivo exogenous RNA targeting using a three-component CasRx system; and 3) tissue-specific in vivo RNA targeting using a three-component CasRx system. The effects of RNA targeting observed include targeted gene specific phenotypic changes, targeted RNA transcript reduction, and occasional lethality phenotypes associated with high expression of CasRx protein and collateral activity. Overall, these results showed that the CasRx system is capable of target RNA transcript reduction at the organismal level in a programmable and efficient manner, demonstrating that in vivo transcriptome targeting, and engineering is feasible and lays the foundation for future in vivo CRISPR-based RNA targeting technologies.

Long non-coding RNAs (lncRNAs) play important roles in hematological malignancies. We have previously identified several differentially expressed lncRNAs in myelodysplastic syndromes (MDS) by microarray analysis. In the present study, we explored the regulatory circuitry, potential functions, clinical and prognostic relevance of these lncRNAs in MDS by developing a lncRNA regulation network. We identified a novel lncRNA, LOC101928834, which was significantly up-regulated in the bone marrow of patients with MDS and acute myeloid leukemia (AML). We further evaluated the clinical relevance of LOC101928834 in 89 MDS and 110 AML patients and found that higher level of LOC101928834 expression was associated with higher white blood cell count, higher blast percentage, the subtype of refractory cytopenia with excess blasts (RAEB) and shorter overall survival in MDS patients. Receiver operating characteristic (ROC) curve analysis showed that LOC101928834 expression could discriminate MDS-RAEB patients from control with an area under the receiver-operating curve (AUC) of 0.9048. Moreover, functional analysis showed that LOC101928834 promoted cell proliferation and cell cycle progression, and activated Wnt/β-catenin signaling pathway in vitro. In conclusion, LOC101928834 expression is correlated with clinical and biological features of MDS and may serve as a novel diagnostic and prognostic biomarker.

Anti-instinctive learning, an ability to modify an animal's innate behaviors in ways that go against one's innate tendency, can confer great evolutionary advantages to animals and enable them to better adapt to the changing environment. Yet, our understanding of anti-instinctive learning and its underlying mechanisms is still limited. In this work, we describe a new anti-instinctive learning behavior of fruit flies. This learning paradigm requires the fruit fly to respond to a recurring, aversive, mild heat stress by modifying its innate locomotion behavior. We found that experiencing movement-triggered mild heat stress repeatedly significantly reduced walking activity in wild type fruit flies, indicating that fruit flies are capable of anti-instinctive learning. We also report that such learning ability is reduced in dopamine 1-like receptor 1 (Dop1R1) null mutant and dopamine 2-like receptor (Dop2R) null mutant flies, suggesting that these two dopamine receptors are involved in mediating anti-instinctive learning in flies.

Non-intrusive Load Monitoring (NILM) is a critical technology that enables detailed analysis of household energy consumption without requiring individual metering of every appliance, and has the capability to provide valuable insights into energy usage behavior, facilitate energy conservation, and optimize load management. Currently, deep learning models have been widely adopted as state-of-the-art approaches for NILM. In this study, we introduce DiffNILM, a novel energy disaggregation framework that utilizes diffusion probabilistic models to distinguish power consumption patterns of individual appliances from aggregated power. Starting from a random Gaussian noise, the target waveform is iteratively reconstructed via a sampler conditioned on the total active power and encoded temporal features. The proposed method is evaluated on two public datasets, REDD and UKDALE. The results demonstrated that DiffNILM outperforms baseline models on several key metrics on both datasets and shows a remarkable ability to effectively recreate complex load signatures. The study highlights the potential of diffusion models to advance the field of NILM and presents a promising approach for future energy disaggregation research.