No abstract

The diagnosis of heart failure can be difficult, even for heart failure specialists. Artificial Intelligence-Clinical Decision Support System (AI-CDSS) has the potential to assist physicians in heart failure diagnosis. The aim of this work was to evaluate the diagnostic accuracy of an AI-CDSS for heart failure. AI-CDSS for cardiology was developed with a hybrid (expert-driven and machine-learningdriven) approach of knowledge acquisition to evolve the knowledge base with heart failure diagnosis. A retrospective cohort of 1198 patients with and without heart failure was used for the development of AI-CDSS (training dataset, n = 600) and to test the performance (test dataset, n = 598). A prospective clinical pilot study of 97 patients with dyspnea was used to assess the diagnostic accuracy of AI-CDSS compared with that of non-heart failure specialists. The concordance rate between AI-CDSS and heart failure specialists was evaluated. In retrospective cohort, the concordance rate was 98.3% in the test dataset. The concordance rate for patients with heart failure with reduced ejection fraction, heart failure with mid-range ejection fraction, heart failure with preserved ejection fraction, and no heart failure was 100%, 100%, 99.6%, and 91.7%, respectively. In a prospective pilot study of 97 patients presenting with dyspnea to the outpatient clinic, 44% had heart failure. The concordance rate between AI-CDSS and heart failure specialists was 98%, whereas that between non-heart failure specialists and heart failure specialists was 76%. In conclusion, AI-CDSS showed a high diagnostic accuracy for heart failure. Therefore, AI-CDSS may be useful for the diagnosis of heart failure, especially when heart failure specialists are not available.npj Digital Medicine (2020) 3:54 ; https://doi.

Autism spectrum disorder (ASD) is a neurodevelopmental impairment characterized by deficits in social interaction skills, impaired communication, and repetitive and restricted behaviors that are thought to be due to altered neurotransmission processes. The amino acid glutamate is an essential excitatory neurotransmitter in the human brain that regulates cognitive functions such as learning and memory, which are usually impaired in ASD. Over the last several years, increasing evidence from genetics, neuroimaging, protein expression, and animal model studies supporting the notion of altered glutamate metabolism has heightened the interest in evaluating glutamatergic dysfunction in ASD. Numerous pharmacological, behavioral, and imaging studies have demonstrated the imbalance in excitatory and inhibitory neurotransmitters, thus revealing the involvement of the glutamatergic system in ASD pathology. Here, we review the effects of genetic alterations on glutamate and its receptors in ASD and the role of non-invasive imaging modalities in detecting these changes. We also highlight the potential therapeutic targets associated with impaired glutamatergic pathways.

Data-driven knowledge acquisition and validation against published guidelines were used to help a team of physicians and knowledge engineers create executable clinical knowledge. The advantages of the R-CKM are twofold: it reflects real practices and conforms to standard guidelines, while providing optimal accuracy comparable to that of a PM. The proposed approach yields better insight into the steps of knowledge acquisition and enhances collaboration efforts of the team of physicians and knowledge engineers.

Acute lymphoblastic leukemia (ALL) is a significant cancer of children resulting from the clonal proliferation of lymphoid precursors with arrested maturation. Although chemotherapeutic approaches have been achieving successful remission for the majority of cases of childhood ALL, development of resistance to chemotherapy has been observed. Thus, new therapeutic approaches are required to improve patient's prognosis. Therefore, we investigated the anticancer potential of curcumin in ALL. We tested a panel of B-precursor ALL (B-Pre-ALL) cell lines with various translocations after treatment with different doses of curcumin. Curcumin suppresses the viability in a concentration-dependent manner in 697, REH, SupB15, and RS4;11 cells (doses from 0 to 80 μM). Curcumin induces apoptosis in B-Pre-ALL cell lines via activation of caspase-8 and truncation of BID. Curcumin treatment increased the ratio of Bax/Bcl-2 and resulted in a leaky mitochondrial membrane that led to the discharge of cytochrome c from the mitochondria to the cytoplasm, the activation of caspase 3 and the cleavage of PARP. Curcumin treatment of B-Pre-ALL cell lines induced a dephosphorylation of the constitutive phosphorylated AKT/PKB and a down-regulation of the expression of cIAP1, and XIAP. Moreover, curcumin mediates its anticancer activity by the generation of reactive oxygen species. Finally, the suboptimal doses of curcumin potentiated the anticancer activity of cisplatin. Altogether, these results suggest an important therapeutic role of curcumin, acting as a growth suppressor of B-Pre-ALL by apoptosis via inactivation of AKT/PKB and down-regulation of IAPs and activation of intrinsic apoptotic pathway via generation of Reactive Oxygen Species (ROS). Our interesting findings raise the possibility of considering curcumin as a potential therapeutic agent for the treatment of B-Pre-ALL.