Learning and forecasting open quantum dynamics with correlated noise

The development of practical quantum processors relies on the ability to control and predict their functioning despite the presence of noise. This is particularly challenging for temporarily correlated noise. Here we propose a physics-inspired supervised machine learning approach to efficiently and accurately predict the functioning of quantum processors in the presence of correlated noise, which only requires data from randomized benchmarking experiments. To demonstrate the efficacy of our technique, we analyze the data from a superconducting quantum processor with tunable correlated noise. We produce training data by evolving the system for a number of time steps, and with this, we fully quantify the correlated noise and accurately predict the dynamics of the system for times beyond the training data. This approach shows a path towards efficient and effective learning of noisy quantum dynamics and optimally control quantum processors over long and complex computations even in the presence of correlated noise

Contextualizing the Revised Patient Perception of Patient-Centeredness (Pppc-R) Scale in Primary Healthcare Settings: a Validity and Reliability Evaluation Study

BACKGROUND: An English version of the Patient Perception of Patient-Centeredness (PPPC) scale was recently revised, and it is necessary to test this instrument in different primary care populations. AIM: This study aimed to assess the validity and reliability of a Chinese version of the PPPC scale. DESIGN: A mixed method was used in this study. The Delphi method was used to collect qualitative and quantitative data to address the content validity of the PPPC scale by calculating the Content Validity Index, Content Validity Ratio, the adjusted Kappa, and the Item Impact Score. Confirmatory factor analysis (CFA) and exploratory factor analysis (EFA) were used to assess the construct validity of the PPPC scale through a cross-sectional survey. The internal consistency was also assessed. SETTING/PARTICIPANTS: In the Delphi consultation, seven experts were consulted through a questionnaire sent by email. The cross-sectional survey interviewed 188 outpatients in Guangzhou city and 108 outpatients in Hohhot City from community health service centers or stations face-to-face. RESULTS: The 21 items in the scale were relevant to their component. The Item-level Content Validity Index for each item was higher than 0.79, and the average Scale-level content validity index was 0.97 in each evaluation round. The initial proposed 4-factor CFA model did not fit adequately. Still, we found a 3-factor solution based on our EFA model and the validation via the CFA model (model fit: [Formula: see text], P \u3c 0.001, RMSEA = 0.044, CFI = 0.981; factor loadings: 0.553 to 0.888). Cronbach\u27s α also indicated good internal consistency reliability: The overall Cronbach\u27s α was 0.922, and the Cronbach\u27s α for each factor was 0.851, 0.872, and 0.717, respectively. CONCLUSIONS: The Chinese version of the PPPC scale provides a valuable tool for evaluating patient-centered medical service quality

Preliminary clinical study of left ventricular myocardial strain in patients with non-ischemic dilated cardiomyopathy by three-dimensional speckle tracking imaging

<p>Abstract</p> <p>Background</p> <p>Non-ischemic dilated cardiomyopathy (DCM) is the most common cardiomyopathy worldwide, with significant mortality. Correct evaluation of the patient's myocardial function has important clinical significance in the diagnosis, therapeutic effect assessment and prognosis in non-ischemic DCM patients. This study evaluated the feasibility of three-dimensional speckle tracking imaging (3D-STE) for assessment of the left ventricular myocardial strain in patients with non-ischemic dilated cardiomyopathy (DCM).</p> <p>Methods</p> <p>Apical full-volume images were acquired from 65 patients with non-ischemic DCM (DCM group) and 59 age-matched normal controls (NC group), respectively. The following parameters were measured by 3D-STE: the peak systolic radial strain (RS), circumferential strain (CS), longitudinal strain (LS) of each segment. Then all the parameters were compared between the two groups.</p> <p>Results</p> <p>The peak systolic strain in different planes had certain regularities in normal groups, radial strain (RS) was the largest in the mid region, the smallest in the apical region, while circumferential strain (CS) and longitudinal strain (LS) increased from the basal to the apical region. In contrast, the regularity could not be applied to the DCM group. RS, CS, LS were significantly decreased in DCM group as compared with NC group (<it>P </it>< 0.001 for all). The interobserver, intraobserver and test-retest reliability were acceptable.</p> <p>Conclusions</p> <p>3D-STE is a reliable tool for evaluation of left ventricular myocardial strain in patients with non-ischemic DCM, with huge advantage in clinical application.</p

Prognostic gene expression and microRNA profiling signatures and genetic alterations in primary testicular diffuse large B-cell lymphoma

Primary testicular (PT) diffuse large B-cell lymphoma (DLBCL) is a rare and aggressive lymphoma with distinct clinical and molecular characteristics. To identify prognostic biomarkers in PT-DLBCL, in this study we analyzed DNA and RNA samples of PT-DLBCL tumors from 206 patients using next-generation sequencing platforms and assays. Genetic alteration analysis found that multiple chromosomal copy number variations (CNVs), TP53 transcript mutations with high variant allele frequency, and MCD subtype had significantly adverse prognostic effects, whereas elevated microsatellite instability had a significantly favorable prognostic effect in PT-DLBCL. Targeted RNA-seq analysis identified a PTL gene expression signature by comparing PT-DLBCL with systemic DLBCL and revealed the heterogeneity within PT-DLBCL by unsupervised clustering, which classified PT-DLBCLs into a testicular lymphoma tumor (TLT) subtype and a microenvironment (ME) subtype. The TLT subtype featured upregulation of genes functioning in DNA damage response, DNA repair, chromatin remodeling, the cell cycle, and the nucleus, and was associated with significantly poorer patient survival and higher frequencies of MYD88 mutations, multiple CNVs, MCD subtype, bulk tumors, and elderly patients in the PT-DLBCL cohort. In contrast, the ME subtype distinctively featured upregulation of various signaling pathway genes involving the tumor microenvironment and downregulation of BTK and B-cell receptor signaling genes, and was associated with significantly better clinical outcome than the TLT subtype of PT-DLBCL independently of CNVs, MCD and MYD88 mutation and than systemic DLBCL. Moreover, genomic microRNA profiling analysis identified a PTL microRNA signature significantly differentially expressed between PT-DLBCL and systemic DLBCL patients and within the PT-DLBCL cohort, and PT-DLBCL patients with higher expression of 16 PTL microRNAs (14 are testicular tissue-specific) had significantly better survival. In summary, this study revealed the molecular heterogeneity in genetic abnormalities and expression profiles of coding genes and microRNAs within the PT-DLBCL entity, and identified significant prognostic biomarkers and PTL signatures. (Figure presented.)</p

Multidimensional Single Cell Based STAT Phosphorylation Profiling Identifies a Novel Biosignature for Evaluation of Systemic Lupus Erythematosus Activity

INTRODUCTION: Dysregulated cytokine action on immune cells plays an important role in the initiation and progress of systemic lupus erythematosus (SLE), a complex autoimmune disease. Comprehensively quantifying basal STATs phosphorylation and their signaling response to cytokines should help us to better understand the etiology of SLE. METHODS: Phospho-specific flow cytometry was used to measure the basal STAT signaling activation in three immune cell types of peripheral-blood mononuclear cells from 20 lupus patients, 9 rheumatoid arthritis (RA) patients and 13 healthy donors (HDs). A panel of 27 cytokines, including inflammatory cytokines, was measured with Bio-Plex™ Human Cytokine Assays. Serum Prolactin levels were measured with an immunoradiometric assay. STAT signaling responses to inflammatory cytokines (interferon α [IFNα], IFNγ, interleukin 2 [IL2], IL6, and IL10) were also monitored. RESULTS: We observed the basal activation of STAT3 in SLE T cells and monocytes, and the basal activation of STAT5 in SLE T cells and B cells. The SLE samples clustered into two main groups, which were associated with the SLE Disease Activity Index 2000, their erythrocyte sedimentation rate, and their hydroxychloroquine use. The phosphorylation of STAT5 in B cells was associated with cytokines IL2, granulocyte colony-stimulating factor (G-CSF), and IFNγ, whereas serum prolactin affected STAT5 activation in T cells. The responses of STAT1, STAT3, and STAT5 to IFNα were greatly reduced in SLE T cells, B cells, and monocytes, except for the STAT1 response to IFNα in monocytes. The response of STAT3 to IL6 was reduced in SLE T cells. CONCLUSIONS: The basal activation of STATs signaling and reduced response to cytokines may be helpful us to identify the activity and severity of SLE

Review of thermo-physical properties, wetting and heat transfer characteristics of nanofluids and their applicability in industrial quench heat treatment

The success of quenching process during industrial heat treatment mainly depends on the heat transfer characteristics of the quenching medium. In the case of quenching, the scope for redesigning the system or operational parameters for enhancing the heat transfer is very much limited and the emphasis should be on designing quench media with enhanced heat transfer characteristics. Recent studies on nanofluids have shown that these fluids offer improved wetting and heat transfer characteristics. Further water-based nanofluids are environment friendly as compared to mineral oil quench media. These potential advantages have led to the development of nanofluid-based quench media for heat treatment practices. In this article, thermo-physical properties, wetting and boiling heat transfer characteristics of nanofluids are reviewed and discussed. The unique thermal and heat transfer characteristics of nanofluids would be extremely useful for exploiting them as quench media for industrial heat treatment

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery