Circulating tissue factor-positive procoagulant microparticles in patients with type 1 diabetes

Aim: To investigate the count of circulating tissue factor-positive (TF+) procoagulant microparticles (MPs) in patients with type 1 diabetes mellitus (T1DM). Methods: This case-control study included patients with T1DM and age and sex-matched healthy volunteers. The counts of phosphatidylserine-positive (PS+) MPs and TF(+)PS(+)MPs and the subgroups derived from different cell types were measured in the peripheral blood sample of the two groups using multicolor flow cytometric assay. We compared the counts of each MP between groups as well as the ratio of the TF(+)PS(+)MPs and PS(+)MPs (TF(+)PS(+)MPs/PS(+)MPs). Results: We recruited 36 patients with T1DM and 36 matched healthy controls. Compared with healthy volunteers, PS(+)MPs, TF(+)PS(+)MPs and TF(+)PS(+)MPs/PS(+)MPs were elevated in patients with T1DM (PS(+)MPs: 1078.5 +/- 158.08 vs 686.84 +/- 122.04/mu L, P &lt;0.001; TF(+)PS(+)MPs: 202.10 +/- 47.47 vs 108.33 +/- 29.42/mu L, P &lt;0.001; and TF(+)PS(+)MPs/PS(+)MPs: 0.16 +/- 0.04 vs 0.19 +/- 0.05, P = 0.004), mostly derived from platelet, lymphocytes and endothelial cells. In the subgroup analysis, the counts of total and platelet TF(+)PS(+)MPs were increased in patients with diabetic retinopathy (DR) and with higher HbA1c, respectively. Conclusion: Circulating TF(+)PS(+)MPs and those derived from platelet, lymphocytes and endothelial cells were elevated in patients with T1DM.De tre första författarna delar förstaförfattarskapet.</p

Towards Better Dermoscopic Image Feature Representation Learning for Melanoma Classification

Deep learning-based melanoma classification with dermoscopic images has recently shown great potential in automatic early-stage melanoma diagnosis. However, limited by the significant data imbalance and obvious extraneous artifacts, i.e., the hair and ruler markings, discriminative feature extraction from dermoscopic images is very challenging. In this study, we seek to resolve these problems respectively towards better representation learning for lesion features. Specifically, a GAN-based data augmentation (GDA) strategy is adapted to generate synthetic melanoma-positive images, in conjunction with the proposed implicit hair denoising (IHD) strategy. Wherein the hair-related representations are implicitly disentangled via an auxiliary classifier network and reversely sent to the melanoma-feature extraction backbone for better melanoma-specific representation learning. Furthermore, to train the IHD module, the hair noises are additionally labeled on the ISIC2020 dataset, making it the first large-scale dermoscopic dataset with annotation of hair-like artifacts. Extensive experiments demonstrate the superiority of the proposed framework as well as the effectiveness of each component. The improved dataset publicly avaliable at https://github.com/kirtsy/DermoscopicDataset.Comment: ICONIP 2021 conferenc

Genome sequence of the insect pathogenic fungus Cordyceps militaris, a valued traditional chinese medicine

Species in the ascomycete fungal genus Cordyceps have been proposed to be the teleomorphs of Metarhizium species. The latter have been widely used as insect biocontrol agents. Cordyceps species are highly prized for use in traditional Chinese medicines, but the genes responsible for biosynthesis of bioactive components, insect pathogenicity and the control of sexuality and fruiting have not been determined. Here, we report the genome sequence of the type species Cordyceps militaris. Phylogenomic analysis suggests that different species in the Cordyceps/Metarhizium genera have evolved into insect pathogens independently of each other, and that their similar large secretomes and gene family expansions are due to convergent evolution. However, relative to other fungi, including Metarhizium spp., many protein families are reduced in C. militaris, which suggests a more restricted ecology. Consistent with its long track record of safe usage as a medicine, the Cordyceps genome does not contain genes for known human mycotoxins. We establish that C. militaris is sexually heterothallic but, very unusually, fruiting can occur without an opposite mating-type partner. Transcriptional profiling indicates that fruiting involves induction of the Zn2Cys6-type transcription factors and MAPK pathway; unlike other fungi, however, the PKA pathway is not activated.https://doi.org/10.1186/gb-2011-12-11-r11

Genesis of the Abunabu antimony deposits in the Tethys Himalayan metallogenic belt: Evidence from He–Ar and S isotopes of stibnite

Introduction: The Abunabu antimony mining area is located between the Indus–Yarlung Tsangpo suture and the southern Tibetan detachment system. Ore deposits in the mining area provide an excellent opportunity to understand the nature and genesis of antimony mineralisation in the Tethys Himalayan metallogenic belt.Methods: In this study, we analysed the He–Ar and S isotopic compositions of stibnite-hosted fluid inclusions as a basis for investigating the sources of ore-forming fluids in the Abunabu mining area and the Tethys Himalayan metallogenic belt.Results: The analysed stibnites have 4He contents of 0.016 × 10−7–1.584 × 10–7 cm3 STP/g, 40Ar contents of 1.37 × 10−7–2.94 × 10–7 cm3 STP/g, 40Ar/36Ar ratios of 303.8–320.7, and 3He/4He (Ra) ratios of 0.021–0.351. These isotopic features indicate that the ore-forming fluids were primarily metamorphic fluids of crustal origin, with small amounts of magmatic-derived materials and modified air-saturated water with low 40Ar*/4He ratios. The δ34S values of stibnite vary within a narrow range of −4.9‰ to −3.5‰, with a mean value of −4.31‰, indicating a deep magmatic origin.Discussion: On the basis of these results and a compilation of data for sulphide deposits in the metallogenic belt, we infer that compositional variations in the He and Ar isotopes of the ore-forming fluids of each antimony deposit in the Tethys Himalayan metallogenic belt are independent of each other. This suggests that antimony deposits in the belt had similar ore-forming fluid sources and mixing processes and that differences in the metallogenic tectonic setting within the belt emerged only in the later stages of deposit evolution. Our new results and compiled data also show that antimony–gold deposits and lead–zinc–antimony polymetallic deposits in the Tethys Himalayan metallogenic belt differ in their sulphur isotopic compositions and that multiple sulphur sources were involved in each of these types of deposit

Preliminary Evidence of Sex Differences in Cortical Thickness Following Acute Mild Traumatic Brain Injury

The main objective of this study was to evaluate sex differences in cortical thickness after acute mild traumatic brain injury (mTBI) and its associations with clinical outcomes. Thirty-two patients with mTBI at acute phase (2.4 ± 1.3 days post-injury) and 30 healthy controls were enrolled. All the participants underwent comprehensive neurocognitive assessments and MRI to assess cortical thickness. Significant sex differences were determined by using variance analysis of factorial design. Relations between the cortical thickness and clinical assessments were measured with the Spearman Correlation. Results revealed that patients with mTBI had significantly reduced cortical thickness in the left entorhinal cortex while increased cortical thickness in the left precuneus cortex and right lateral occipital cortex, compared with healthy controls. The interaction effect of the group × sex on cortical thickness was significant. Female patients had significant thicker cortical thickness in the left caudal anterior cingulate cortex (ACC) than male patients and had higher scores on Posttraumatic stress disorder Checklist—Civilian Version (PCL-C). Spearman correlational analysis showed a significantly positive correlations between the cortical thickness of the left caudal ACC and PCL-C ratings in female patients. Sex differences in cortical thickness support its potential as a neuroimaging phenotype for investigating the differences in clinical profiles of mild TBI between women and men

Assessing generalisability of deep learning-based polyp detection and segmentation methods through a computer vision challenge

Polyps are well-known cancer precursors identified by colonoscopy. However, variability in their size, appearance, and location makes the detection of polyps challenging. Moreover, colonoscopy surveillance and removal of polyps are highly operator-dependent procedures and occur in a highly complex organ topology. There exists a high missed detection rate and incomplete removal of colonic polyps. To assist in clinical procedures and reduce missed rates, automated methods for detecting and segmenting polyps using machine learning have been achieved in past years. However, the major drawback in most of these methods is their ability to generalise to out-of-sample unseen datasets from different centres, populations, modalities, and acquisition systems. To test this hypothesis rigorously, we, together with expert gastroenterologists, curated a multi-centre and multi-population dataset acquired from six different colonoscopy systems and challenged the computational expert teams to develop robust automated detection and segmentation methods in a crowd-sourcing Endoscopic computer vision challenge. This work put forward rigorous generalisability tests and assesses the usability of devised deep learning methods in dynamic and actual clinical colonoscopy procedures. We analyse the results of four top performing teams for the detection task and five top performing teams for the segmentation task. Our analyses demonstrate that the top-ranking teams concentrated mainly on accuracy over the real-time performance required for clinical applicability. We further dissect the devised methods and provide an experiment-based hypothesis that reveals the need for improved generalisability to tackle diversity present in multi-centre datasets and routine clinical procedures

Utility of S100A12 as an Early Biomarker in Patients With ST-Segment Elevation Myocardial Infarction

Importance: S100A12 is a calcium binding protein which is involved in inflammation and progression of atherosclerosis. Objective: We sought to investigate the utility of S100A12 as a biomarker for the early diagnosis and prognostication of patients presenting with ST-segment elevation myocardial infarction (STEMI). Design, Setting, and Participants: S100A12 was measured in 1023 patients presenting to the emergency department with acute chest pain between June 2012 and November 2015. An independent cohort of 398 patients enrolled at 3 different hospitals served as a validation cohort. Main Outcomes and Measures: The primary clinical endpoint of interest was major adverse cardiac and cerebral events (MACCE) defined as a composite of all-cause death, MI, stroke, or hospitalization for heart failure. Results: A total of 438/1023 patients (42.8%) in the diagnosis cohort were adjudicated as STEMI, among whom plasma S100A12 levels increased within 30 min and peaked 1–2 h after symptom onset. Compared with high-sensitivity cardiac troponin T and creatine kinase-MB isoenzyme, S100A12 more accurately identified STEMI, especially within the first 2 h after symptom onset (area under the curve 0.963 compared with 0.860 for hscTnT and 0.711 for CK-MB, both P \u3c 0.05). These results were consistent in the 243-patient validation cohort. The 1-year rate of MACCE was greatest in patients in the highest peak S100A12 tertile, intermediate in the middle tertile and least in the lowest tertile (9.3 vs. 5.7 vs. 3.0% respectively, Ptrend = 0.0006). By multivariable analysis the peak plasma concentration of S100A12 was an independent predictor of MACCE within 1 year after STEMI (HR, 1.001, 95%CI, 1.000–1.002; P = 0.0104). Zhang et al. S100A12 as a STEMI Biomarker Conclusions and Relevance: S100A12 rapidly identified patients with STEMI, more accurately than other cardiac biomarkers, especially within the first 2 h after symptom onset. The peak plasma S100A12 level was a strong predictor of 1-year prognosis after STEMI

Acoustic sequences in non-human animals: a tutorial review and prospectus.

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise - let alone understand - the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, 'Analysing vocal sequences in animals'. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.This review was developed at an investigative workshop, “Analyzing Animal Vocal Communication Sequences” that took place on October 21–23 2013 in Knoxville, Tennessee, sponsored by the National Institute for Mathematical and Biological Synthesis (NIMBioS). NIMBioS is an Institute sponsored by the National Science Foundation, the U.S. Department of Homeland Security, and the U.S. Department of Agriculture through NSF Awards #EF-0832858 and #DBI-1300426, with additional support from The University of Tennessee, Knoxville. In addition to the authors, Vincent Janik participated in the workshop. D.T.B.’s research is currently supported by NSF DEB-1119660. M.A.B.’s research is currently supported by NSF IOS-0842759 and NIH R01DC009582. M.A.R.’s research is supported by ONR N0001411IP20086 and NOPP (ONR/BOEM) N00014-11-1-0697. S.L.DeR.’s research is supported by the U.S. Office of Naval Research. R.F.-i-C.’s research was supported by the grant BASMATI (TIN2011-27479-C04-03) from the Spanish Ministry of Science and Innovation. E.C.G.’s research is currently supported by a National Research Council postdoctoral fellowship. E.E.V.’s research is supported by CONACYT, Mexico, award number I010/214/2012.This is the accepted manuscript. The final version is available at http://dx.doi.org/10.1111/brv.1216