A Comparative Analysis of U-Net and Vision Transformer Architectures in Semi-Supervised Prostate Zonal Segmentation

The precise segmentation of different regions of the prostate is crucial in the diagnosis and treatment of prostate-related diseases. However, the scarcity of labeled prostate data poses a challenge for the accurate segmentation of its different regions. We perform the segmentation of different regions of the prostate using U-Net- and Vision Transformer (ViT)-based architectures. We use five semi-supervised learning methods, including entropy minimization, cross pseudo-supervision, mean teacher, uncertainty-aware mean teacher (UAMT), and interpolation consistency training (ICT) to compare the results with the state-of-the-art prostate semi-supervised segmentation network uncertainty-aware temporal self-learning (UATS). The UAMT method improves the prostate segmentation accuracy and provides stable prostate region segmentation results. ICT plays a more stable role in the prostate region segmentation results, which provides strong support for the medical image segmentation task, and demonstrates the robustness of U-Net for medical image segmentation. UATS is still more applicable to the U-Net backbone and has a very significant effect on a positive prediction rate. However, the performance of ViT in combination with semi-supervision still requires further optimization. This comparative analysis applies various semi-supervised learning methods to prostate zonal segmentation. It guides future prostate segmentation developments and offers insights into utilizing limited labeled data in medical imaging

Graph Reasoning for Question Answering with Triplet Retrieval

Answering complex questions often requires reasoning over knowledge graphs (KGs). State-of-the-art methods often utilize entities in questions to retrieve local subgraphs, which are then fed into KG encoder, e.g. graph neural networks (GNNs), to model their local structures and integrated into language models for question answering. However, this paradigm constrains retrieved knowledge in local subgraphs and discards more diverse triplets buried in KGs that are disconnected but useful for question answering. In this paper, we propose a simple yet effective method to first retrieve the most relevant triplets from KGs and then rerank them, which are then concatenated with questions to be fed into language models. Extensive results on both CommonsenseQA and OpenbookQA datasets show that our method can outperform state-of-the-art up to 4.6% absolute accuracy.Comment: Findings of ACL 202

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

Guideline adherence of β-blocker initiating dose and its consequence in hospitalized patients with heart failure with reduced ejection fraction

Background: We aim to investigate the guideline adherence of β-blocker (BB) initiating dose in Chinese hospitalized patients with heart failure with reduced ejection fraction (HFrEF) and whether the adherence affected the in-hospital outcomes.Methods: This was a retrospective study of patients hospitalized with HFrEF who had initiated BBs during their hospitalization. We defined adherence to clinical practice guidelines as initiating BB with standard dose and non-adherence to guidelines if otherwise, and examined the association between adherence to guidelines and in-hospital BB-related adverse events. Subgroup analyses based on sex, age, coronary heart disease, and hypertension were performed.Results: Among 1,104 patients with HFrEF initiating BBs during hospitalization (median length of hospitalization, 12 days), 304 (27.5%) patients received BB with non-adherent initiating dose. This non-adherence was related to a higher risk (hazard ratio [95% confidence interval]) of BB dose reduction or withdrawal (1.78 [1.42 to 2.22], P &lt; 0.001), but not significantly associated with risks of profound bradycardia, hypotension, cardiogenic shock requiring intravenous inotropes, and severe bronchospasm requiring intravenous steroid during hospitalization.Conclusion: This study identified that over a fourth of patients had received BBs with an initiating dose that was not adherent to guidelines in Chinese hospitalized patients with HFrEF, and this non-adherence was associated with BB dose reduction or withdrawal during hospitalization

A unified neurocognitive model of semantics language social behaviour and face recognition in semantic dementia

Funder: Chinese Scholarship CouncilFunder: National Key R&D Program of China (2016YFC1306305)Funder: ERC grant (GAP: 670428 - BRAIN2MIND_NEUROCOMP)Abstract: The anterior temporal lobes (ATL) have become a key brain region of interest in cognitive neuroscience founded upon neuropsychological investigations of semantic dementia (SD). The purposes of this investigation are to generate a single unified model that captures the known cognitive-behavioural variations in SD and map these to the patients’ distribution of frontotemporal atrophy. Here we show that the degree of generalised semantic impairment is related to the patients’ total, bilateral ATL atrophy. Verbal production ability is related to total ATL atrophy as well as to the balance of left > right ATL atrophy. Apathy is found to relate positively to the degree of orbitofrontal atrophy. Disinhibition is related to right ATL and orbitofrontal atrophy, and face recognition to right ATL volumes. Rather than positing mutually-exclusive sub-categories, the data-driven model repositions semantics, language, social behaviour and face recognition into a continuous frontotemporal neurocognitive space

Glycated Haemoglobin A1c Variability Score Elicits Kidney Function Decline in Chinese People Living with Type 2 Diabetes

Our aim was to investigate the association of glycated haemoglobin A1c (HbA1c) variability score (HVS) with estimated glomerular filtration rate (eGFR) slope in Chinese adults living with type 2 diabetes. This cohort study included adults with type 2 diabetes attending outpatient clinics between 2011 and 2019 from a large electronic medical record-based database of diabetes in China (WECODe). We estimated the individual-level visit-to-visit HbA1c variability using HVS, a proportion of changes in HbA1c of ≥0.5% (5.5 mmol/mol). We estimated the odds of people experiencing a rapid eGFR annual decline using a logistic regression and differences across HVS categories in the mean eGFR slope using a mixed-effect model. The analysis involved 2397 individuals and a median follow-up of 4.7 years. Compared with people with HVS ≤ 20%, those with HVS of 60% to 80% had 11% higher odds of experiencing rapid eGFR annual decline, with an extra eGFR decline of 0.93 mL/min/1.73 m(2) per year on average; those with HVS > 80% showed 26% higher odds of experiencing a rapid eGFR annual decline, with an extra decline of 1.83 mL/min/1.73 m(2) per year on average. Chinese adults with type 2 diabetes and HVS > 60% could experience a more rapid eGFR decline

Multifunctional ytterbium oxide buffer for perovskite solar cells

Perovskite solar cells (PSCs) comprise a solid perovskite absorber sandwiched between several layers of different charge-selective materials, ensuring unidirectional current flow and high voltage output of the devices. A ‘buffer material’ between the electron-selective layer and the metal electrode in p-type/intrinsic/n-type (p-i-n) PSCs (also known as inverted PSCs) enables electrons to flow from the electron-selective layer to the electrode. Furthermore, it acts as a barrier inhibiting the inter-diffusion of harmful species into or degradation products out of the perovskite absorber. Thus far, evaporable organic molecules and atomic-layer-deposited metal oxides have been successful, but each has specific imperfections. Here we report a chemically stable and multifunctional buffer material, ytterbium oxide (YbOx), for p-i-n PSCs by scalable thermal evaporation deposition. We used this YbOx buffer in the p-i-n PSCs with a narrow-bandgap perovskite absorber, yielding a certified power conversion efficiency of more than 25%. We also demonstrate the broad applicability of YbOx in enabling highly efficient PSCs from various types of perovskite absorber layer, delivering state-of-the-art efficiencies of 20.1% for the wide-bandgap perovskite absorber and 22.1% for the mid-bandgap perovskite absorber, respectively. Moreover, when subjected to ISOS-L-3 accelerated ageing, encapsulated devices with YbOx exhibit markedly enhanced device stability

Uncertainty analysis of atmospheric friction torque on the solid Earth

The wind stress acquired from European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP) climate models and QSCAT satellite observations are analyzed by using frequency-wavenumber spectrum method. The spectrum of two climate models, i.e., ECMWF and NCEP, is similar for both 10 m wind data and model output wind stress data, which indicates that both the climate models capture the key feature of wind stress. While the QSCAT wind stress data shows the similar characteristics with the two climate models in both spectrum domain and the spatial distribution, but with a factor of approximately 1.25 times larger than that of climate models in energy. These differences show the uncertainty in the different wind stress products, which inevitably cause the atmospheric friction torque uncertainties on solid Earth with a 60% departure in annual amplitude, and furtherly affect the precise estimation of the Earth's rotation