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BackgroundThe treatment of preterm and low birth weight (LBW) neonates born with congenital heart disease (CHD) requiring early cardiac intervention remains challenging. We aimed to analyze morbidity and mortality in this combined high-risk patient group.MethodsA retrospective cohort study was conducted of preterm [ more...

Fruit crops under soil conservational management might sequester carbon (C) in soils and mitigate greenhouse gases emissions. Using grape pomace residues as soil amendment holds promise for sustainable viticulture. However, its actual capability to increase soil organic carbon (SOC) and nitrogen (N) is unknown, especially in subtropical climates. This research aims to investigate whether grape pomace compost and vermicompost can increase SOC, total N (TN), and C and N stocks in subtropical vineyards. Two vineyards located in Veranópolis, in South Brazil, one cultivated with ‘Isabella’ and the other with ‘Chardonnay’ varieties, were annually amended with these residues for three years. We quantified SOC and TN in each condition in different soil layers, as well as C and N content in two different granulometric fractions: mineral-associated organic matter (MAOM) and particulate organic matter (POM). C and N stocks were also calculated. Despite potential benefits, neither treatment enhanced SOC, its fractions, or C stocks. In fact, vermicompost was rapidly mineralized and depleted SOC and its fractions in the 0.0 to 0.05 m layers of the ‘Isabella’ vineyard. Our findings indicate that the tested grape pomace residues were unable to promote C sequestration in subtropical vineyards after a three-year period. more...

BackgroundCritical congenital heart disease (cCHD)—requiring cardiac intervention in the first year of life for survival—occurs globally in 2-3 of every 1000 live births. In the critical perioperative period, intensive multimodal monitoring at a pediatric intensive care unit (PICU) is warranted, as their organs—especially the brain—may be severely injured due to hemodynamic and respiratory events. These 24/7 clinical data streams yield large quantities of high-frequency data, which are challenging in terms of interpretation due to the varying and dynamic physiology innate to cCHD. Through advanced data science algorithms, these dynamic data can be condensed into comprehensible information, reducing the cognitive load on the medical team and providing data-driven monitoring support through automated detection of clinical deterioration, which may facilitate timely intervention. ObjectiveThis study aimed to develop a clinical deterioration detection algorithm for PICU patients with cCHD. MethodsRetrospectively, synchronous per-second data of cerebral regional oxygen saturation (rSO2) and 4 vital parameters (respiratory rate, heart rate, oxygen saturation, and invasive mean blood pressure) in neonates with cCHD admitted to the University Medical Center Utrecht, the Netherlands, between 2002 and 2018 were extracted. Patients were stratified based on mean oxygen saturation during admission to account for physiological differences between acyanotic and cyanotic cCHD. Each subset was used to train our algorithm in classifying data as either stable, unstable, or sensor dysfunction. The algorithm was designed to detect combinations of parameters abnormal to the stratified subpopulation and significant deviations from the patient’s unique baseline, which were further analyzed to distinguish clinical improvement from deterioration. Novel data were used for testing, visualized in detail, and internally validated by pediatric intensivists. ResultsA retrospective query yielded 4600 hours and 209 hours of per-second data in 78 and 10 neonates for, respectively, training and testing purposes. During testing, stable episodes occurred 153 times, of which 134 (88%) were correctly detected. Unstable episodes were correctly noted in 46 of 57 (81%) observed episodes. Twelve expert-confirmed unstable episodes were missed in testing. Time-percentual accuracy was 93% and 77% for, respectively, stable and unstable episodes. A total of 138 sensorial dysfunctions were detected, of which 130 (94%) were correct. ConclusionsIn this proof-of-concept study, a clinical deterioration detection algorithm was developed and retrospectively evaluated to classify clinical stability and instability, achieving reasonable performance considering the heterogeneous population of neonates with cCHD. Combined analysis of baseline (ie, patient-specific) deviations and simultaneous parameter-shifting (ie, population-specific) proofs would be promising with respect to enhancing applicability to heterogeneous critically ill pediatric populations. After prospective validation, the current—and comparable—models may, in the future, be used in the automated detection of clinical deterioration and eventually provide data-driven monitoring support to the medical team, allowing for timely intervention. more...

Understanding and predicting fluctuations of the neutron population within a nuclear reactor is of fundamental importance for nuclear safety, especially in connection with reactor control at startup and shutdown. The study presents experiments and Monte Carlo simulations of persistent neutron fluctuations and correlations (stochastic noise and neutron clustering) in nuclear reactors which are interpreted by stochastic modelling based on branching random walks. more...

Primary progressive aphasia (PPA) is a clinical syndrome in which patients progressively lose speech and language abilities. Three variants are recognized: logopenic (lvPPA), associated with phonology and/or short-term verbal memory deficits accompanied by left temporo-parietal atrophy; semantic (svPPA), associated with semantic deficits and anterior temporal lobe (ATL) atrophy; non-fluent (nfvPPA) associated with grammar and/or speech-motor deficits and inferior frontal gyrus (IFG) atrophy. Here, we set out to investigate whether the three variants of PPA can be dissociated based on error patterns in a single language task. We recruited 21 lvPPA, 28 svPPA, and 24 nfvPPA patients, together with 31 healthy controls, and analyzed their performance on an auditory noun-to-verb generation task, which requires auditory analysis of the input, access to and selection of relevant lexical and semantic knowledge, as well as preparation and execution of speech. Task accuracy differed across the three variants and controls, with lvPPA and nfvPPA having the lowest and highest accuracy, respectively. Critically, machine learning analysis of the different error types yielded above-chance classification of patients into their corresponding group. An analysis of the error types revealed clear variant-specific effects: lvPPA patients produced the highest percentage of “not-a-verb” responses and the highest number of semantically related nouns (production of baseball instead of throw to noun ball); in contrast, svPPA patients produced the highest percentage of “unrelated verb” responses and the highest number of light verbs (production of take instead of throw to noun ball). Taken together, our findings indicate that error patterns in an auditory verb generation task are associated with the breakdown of different neurocognitive mechanisms across PPA variants. Specifically, they corroborate the link between temporo-parietal regions with lexical processing, as well as ATL with semantic processes. These findings illustrate how the analysis of pattern of responses can help PPA phenotyping and heighten diagnostic sensitivity, while providing insights on the neural correlates of different components of language. more...

As an indispensable module of computer-aided pronunciation training (CAPT) systems, mispronunciation detection and diagnosis (MDD) techniques have attracted a lot of attention from academia and industry over the past decade. To train robust MDD models, this technique requires massive human-annotated speech recordings which are usually expensive and even hard to acquire. In this study, we propose to use transfer learning to tackle the problem of data scarcity from two aspects. First, from audio modality, we explore the use of the pretrained model wav2vec2.0 for MDD tasks by learning robust general acoustic representation. Second, from text modality, we explore transferring prior texts into MDD by learning associations between acoustic and textual modalities. We propose textual modulation gates that assign more importance to the relevant text information while suppressing irrelevant text information. Moreover, given the transcriptions, we propose an extra contrastive loss to reduce the difference of learning objectives between the phoneme recognition and MDD tasks. Conducting experiments on the L2-Arctic dataset showed that our wav2vec2.0 based models outperformed the conventional methods. The proposed textual modulation gate and contrastive loss further improved the F1-score by more than 2.88% and our best model achieved an F1-score of 61.75%. more...

Since HA-1-specific T cells have been shown to make a significant contribution to the clinical responses in patients with relapsed leukemia, we investigated the feasibility of adoptive transfer of in vitro induced HA-1-specific CD8 positive T cells to patients with relapsed leukemia after allogeneic stem cell transplantation. The in vitro generation of clinical grade HA-1-specific T-cell lines from HA-1 negative donors was seen to be feasible and 3 patients were treated with HA-1-specific T-cell lines. No toxicity after infusion was observed. Although in one patient, during a period of stable disease, HA-1-specific T cells could be detected in the peripheral blood and bone marrow, these patients had no clear clinical response. more...

Background and Objectives Graft-versus-host-disease may be avoided and the likelihood of a graft-versus-leukemia reaction increased by infusion of in vitro-generated, leukemia-reactive, cytotoxic T lymphocyte (CTL) lines as treatment for patients with relapsed leukemia after allogeneic stem cell transplantation, instead of donor lymphocyte infusion. The aim of this phase I/II study was to assess the feasibility of large-scale in vitro generation of leukemia-reactive CTL for clinical use.Design and Methods Using a modified limiting dilution culture system donor T cells were stimulated with HLA-identical leukemic antigen-presenting cells. Feasibility experiments demonstrated that in 16 of 27 donor-recipient pairs tested a CTL line could be generated. Twelve of these 16 patients developed a relapse and for 11 of these 12 patients a CTL line was generated under Good Manufacturing Practice conditions.Results The CTL lines showed moderate to high cytotoxic activity against original recipient leukemic cells in vitro. Eight patients with a relapse received from one to seven CTL lines. One patient entered a complete remission after CTL infusion only, one entered a complete remission after combined CTL infusion and donor lymphocyte infusion, two patients had temporarily stable disease, and in four patients no response was observed.Interpretation and Conclusions Although the current procedure to generate these CTL lines is feasible, the strategy is logistically complex and time-consuming, and needs further improvement. more...