ChromoLogic (United States)

Background: Preeclampsia, which is a leading cause of maternal and perinatal mortality and morbidity, represents a biologically heterogeneous syndrome. First-trimester screening with the Fetal Medicine Foundation competing-risks model enables prevention of preterm preeclampsia through aspirin prophylaxis but depends on Doppler velocimetry and biochemical measurements that limit scalability and offer limited discrimination for term disease. A unified, molecular first trimester test capable of stratifying risk across the full clinical spectrum of preeclampsia has not been established. Objective: To determine whether multi-modal, tissue-resolved analysis of first trimester circulating cell-free DNA (cfDNA), obtained during routine non-invasive prenatal testing (NIPT), enables early prediction of both preterm and term preeclampsia. Study Design: This nested case-control study included 125 singleton pregnancies sampled at 11-14 weeks' gestation after quality control (48 controls, 30 preterm preeclampsia, 47 term preeclampsia). For 80 pregnancies, matched placental villi and maternal buffy coat samples were available to derive tissue reference profiles. Plasma cfDNA underwent multi-modal sequencing using Oxford Nanopore Technologies, enabling tissue-resolved analysis of fragmentomic and epigenetic signatures. Separate ensemble machine-learning classifiers were developed for preterm (<37 weeks) and term (>=37 weeks) preeclampsia using stratified 10-fold cross-validation. Model discrimination was evaluated using area under the receiver operating characteristic curve (AUROC), sensitivity at predefined specificity thresholds, and comparison with the FMF first-trimester risk score. A population-level simulation of 100,000 pregnancies, applying incidence point estimates of 2.5% for preterm and 7.5% for term PE, was used to derive predictive values and likelihood ratios. Results: The multi-modal cfDNA classifier achieved an AUROC (95% CI) of 0.85 (0.77-0.91) for preterm preeclampsia and 0.84 (0.76-0.91) for term preeclampsia. The FMF score yielded an AUROC of 0.80 (0.70-0.89) for preterm and 0.53 (0.43-0.63) for term PE. At 80% specificity, cfDNA sensitivity was 70.5% for preterm and 72.1% for term preeclampsia, demonstrating improved discrimination for term disease compared with FMF screening. In simulated population-level analysis, positive likelihood ratios were 4.25 (preterm) and 3.83 (term), with negative likelihood ratios of 0.21 and 0.34, respectively, supporting meaningful post-test risk stratification and strong rule-out performance. Conclusion: First-trimester multi-modal, tissue-resolved cfDNA analysis enables early risk stratification across the full clinical spectrum of preeclampsia from a single routine blood sample. Compared with FMF screening, this approach can potentially improve discrimination for term preeclampsia while providing incremental improvement for preterm disease. The potential for integration into existing NIPT workflows offers a scalable pathway toward unified precision prevention, supporting timely aspirin prophylaxis for preterm preeclampsia and risk-adapted surveillance strategies for term disease.

The present research shows several features of Lukan Christology along a journey through Lk-Acts, taking into account some of its exclusive notes distributed in the different stages of the Way of the Word. It begins by showing the narrative itinerary of Lk-Acts and the importance of these stages. Next, an exegetical-theological journey is made in ten steps through different texts of or about Luke’s Jesus, highlighting a series of Christological keys or notes. Finally, by way of conclusion, some ways opened by the research are shown.

Artykuł jest przyczynkiem do badań hagiologicznych w zakresie poszukiwania odpo­wiedzi na pytanie o specyfikę doświadczenia mistycznego. Jest opracowaniem teologiczno-hagiograficznym, dostarcza bowiem danych biograficznych, które stanowią źródło do dalszych badań hagiologicznych w różnych aspektach. Źródła franciszkańskie ukazują Świętą Klarę jako „kobietę eucharystyczną”, której życie można nazwać egzystencją paschalną. Tym obrazem jest ukazany charyzmat franciszkański, skupiony na misterium Wcielenia i Zmartwychwstania. Osiągnięciem badań przyczynkowych, ukazanych w artykule, jest wskazanie korelacji między dziejami życia człowieka świątobliwego a teologią będącą refleksją nad ogółem wydarzeń i sytuacji, w których Bóg objawia swoje misterium i wprowadza w nie człowieka.

Monocular depth estimation is a crucial task in many embedded vision systems with numerous applications in autonomous driving, robotics and augmented reality. Traditional methods often rely only on frame-based approaches, which struggle in dynamic scenes due to their limitations, while event-based cameras offer complementary high temporal resolution, though they lack spatial resolution and context. We propose a novel embedded multimodal monocular depth estimation framework using a hybrid spiking neural network (SNN) and artificial neural network (ANN) architecture. This framework leverages a custom accelerator, TransPIM for efficient transformer deployment, enabling real-time depth estimation on embedded systems. Our approach leverages the advantages of both frame-based and event-based cameras, where SNN extracts low-level features and generates sparse representations from events, which are then fed into an ANN with frame-based input for estimating depth. The SNN-ANN hybrid architecture allows for efficient processing of both RGB and event data showing competitive performance across different accuracy metrics in depth estimation with standard benchmark MVSEC and DENSE dataset. To make it accessible to embedded system we deploy it on TransPIM enabling 9x speedup and 183× lower energy consumption compared to standard GPUs opening up new possibilities for various embedded system applications.

The Ebola virus glycoprotein (GP) gene templates several mRNAs that produce either the virion-associated transmembrane protein or one of two secreted glycoproteins. Soluble glycoprotein (sGP) is the predominant product. GP1 and sGP share an amino terminal sequence of 295 amino acids but differ in quaternary structure, with GP1 being a heterohexamer with GP2 and sGP a homodimer. Two structurally different DNA aptamers were selected against sGP that also bound GP1,2. These DNA aptamers were compared with a 2′FY-RNA aptamer for their interactions with the Ebola GP gene products. The three aptamers have almost identical binding isotherms for sGP and GP1,2 in solution and on the virion. They demonstrated high affinity and selectivity for sGP and GP1,2. Furthermore, one aptamer, used as a sensing element in an electrochemical format, detected GP1,2 on pseudotyped virions and sGP with high sensitivity in the presence of serum, including from an Ebola-virus-infected monkey. Our results suggest that the aptamers interact with sGP across the interface between the monomers, which is different from the sites on the protein bound by most antibodies. The remarkable similarity in functional features of three structurally distinct aptamers suggests that aptamers, like antibodies, have preferred binding sites on proteins.

Multiparameter flow cytometry (MFC) is one of the essential ancillary methods in bone marrow (BM) investigation of patients with cytopenia and suspected myelodysplastic syndrome (MDS). MFC can also be applied in the follow‐up of MDS patients undergoing treatment. This document summarizes recommendations from the International/European Leukemia Net Working Group for Flow Cytometry in Myelodysplastic Syndromes (ELN iMDS Flow) on the analytical issues in MFC for the diagnostic work‐up of MDS. Recommendations for the analysis of several BM cell subsets such as myeloid precursors, maturing granulocytic and monocytic components and erythropoiesis are given. A core set of 17 markers identified as independently related to a cytomorphologic diagnosis of myelodysplasia is suggested as mandatory for MFC evaluation of BM in a patient with cytopenia. A myeloid precursor cell (CD34+CD19−) count >3% should be considered immunophenotypically indicative of myelodysplasia. However, MFC results should always be evaluated as part of an integrated hematopathology work‐up. Looking forward, several machine‐learning‐based analytical tools of interest should be applied in parallel to conventional analytical methods to investigate their usefulness in integrated diagnostics, risk stratification, and potentially even in the evaluation of response to therapy, based on MFC data. In addition, compiling large uniform datasets is desirable, as most of the machine‐learning‐based methods tend to perform better with larger numbers of investigated samples, especially in such a heterogeneous disease as MDS.