Additional Samples Research Articles

Using resiliency, redundancy, and representation in a Bayesian belief network to assess imperilment of riverine fishes

AbstractConservation prioritization frameworks are used worldwide to identify species at greatest risk of extinction and to allocate limited resources across regions, species, and populations. Conservation prioritization can be impeded by ecological knowledge gaps and data deficiency, especially in freshwater species inhabiting highly complex aquatic ecosystems. Therefore, we developed a flexible approach that calculates a species' imperilment risk based on the conservation principles of resiliency, redundancy, and representation (i.e., the “three R's”). Our approach organizes data on species traits, distributions, population connectivity, and threats within a Bayesian belief network capable of predicting resiliency and redundancy within representative ecological settings. Empirical data and expert judgment inform the model to provide robust and repeatable risk assessments for rare and data‐deficient species. The model calculates resiliency at hierarchical spatial scales from distributional trends and population strength. Redundancy is estimated from the connectivity and quantities of extant populations. Resiliency, redundancy, and species' inherent vulnerability based on species traits collectively estimate extirpation risk within each unique ecological setting. Extirpation risks across ecological settings characterize representation and are aggregated to estimate global imperilment risk. We demonstrate the model's utility with Piebald Madtom (Noturus gladiator), a species petitioned for listing under the U.S. Endangered Species Act. Our results revealed that resiliency, redundancy, and extirpation risks can vary spatially across the species' range while identifying populations where additional sampling could disproportionally reduce uncertainty in estimated global imperilment risk. Our approach could standardize and expedite conservation status assessments, identify opportunities for early management intervention of at‐risk species and populations, and strategically reduce uncertainty by focusing monitoring and research on priority information gaps.

Speech enhancement augmentation for robust speech recognition in noisy environments

Abstract. The use of augmentations as a data enrichment method has become an important element in improving the performance of speech recognition systems. To work effectively in noisy conditions, augmentation is usually used to simulate the presence of background noise. However, the quality of speech recognition on samples pre-processed by noise reduction models does not increase. This paper proposes a new approach to speech data augmentation when training ASR systems, intended for their joint use with models for speech enhancement. It was based on the creation of several additional data samples containing speech samples processed by the enhancement model. The proposed approach was tested on the E-Branchformer neural network model using data from the Librispeech set. The quality of speech samples was assessed using the DNSMOS metric. By means of a 100-hour sample of clean speech samples it was shown that the proposed augmentation allows for an improvement in the WER metric of more than 4% in absolute value compared to the generally accepted approach based on adding noisy speech samples. Experiments on 960-hour data demonstrated the robustness of this approach as the training set size increased.

Deep Metric Learning Based on Meta-Mining Strategy With Semiglobal Information.

Recently, deep metric learning (DML) has achieved great success. Some existing DML methods propose adaptive sample mining strategies, which learn to weight the samples, leading to interesting performance. However, these methods suffer from a small memory (e.g., one training batch), limiting their efficacy. In this work, we introduce a data-driven method, meta-mining strategy with semiglobal information (MMSI), to apply meta-learning to learn to weight samples during the whole training, leading to an adaptive mining strategy. To introduce richer information than one training batch only, we elaborately take advantage of the validation set of meta-learning by implicitly adding additional validation sample information to training. Furthermore, motivated by the latest self-supervised learning, we introduce a dictionary (memory) that maintains very large and diverse information. Together with the validation set, this dictionary presents much richer information to the training, leading to promising performance. In addition, we propose a new theoretical framework that can formulate pairwise and tripletwise metric learning loss functions in a unified framework. This framework brings new insights to society and facilitates us to generalize our MMSI to many existing DML methods. We conduct extensive experiments on three public datasets, CUB200-2011, Cars-196, and Stanford Online Products (SOP). Results show that our method can achieve the state of the art or very competitive performance. Our source codes have been made available at https://github.com/NUST-Machine-Intelligence-Laboratory/MMSI.

A Novel Two-Stage Framework for Mid-Term Electric Load Forecasting

Electric utilities and planners rely heavily on accurate mid-term load projections to effectively schedule maintenance, coordinate load dispatch, and manage fuel reserves. Current approaches that attempt to forecast electric load for multiple horizons in a single stage, however, often result in inaccurate forecasts due to the lack of information for predicting the data at the farthest horizon and propagation of large errors. To address this issue, this paper presents a two-step mechanism for forecasting electric load that utilizes the benefits of both Backpropagation Neural Networks (BPNNs) and Radial Basis Function Neural Networks (RBFNNs). The first stage utilizes a pool of BPNNs to make partial predictions. BPNNs are used as they are well known for their capability of fast and accurate predictions. In the second stage, RBFNNs are used to make complete forecasts. RBFNNs are known for their ability to model non-linear relationships in the data which is crucial in this stage of the forecast process. Additionally, this paper also proposes a unique method for generating additional training samples by incorporating stacking noise, which adds more variability to the data, increasing the generalization capability of the models, resulting in better forecasting performance. The performance of the proposed framework has been investigated with simulation studies and has been validated on actual load data of Madhya Pradesh Power Transmission System, India. The performance comparison with the existing methods in terms of both accuracy and reliability shows that the proposed forecasting framework provides more accurate results.

Inadequate (Ax) Transbronchial Lung Transplant Biopsies—Scope and the Potential Contributing Factors

Transbronchial biopsy is the cornerstone for the evaluation of graft function after lung transplant and a standard of care to diagnose acute cellular rejection. However, the yield from these biopsies is variable, with about 15% to 50% of samples being judged as nondiagnostic, leading to additional procedures. The factors contributing to the nondiagnostic sampling have not been delineated, and the discordance in sample assessment between the bronchoscopist and pathologist has not been quantified. A retrospective cohort of patients who had bronchoscopies with biopsies for surveillance and graft assessment at a large-volume transplant center was studied. The occurrence of nondiagnostic alveolar sampling was assessed, and the patient demographics and procedural characteristics were compared with the diagnostic group. We included 128 patients in our study and found the inadequacy rate for alveolar tissue sampling to be 15.5%. The median number of passes made by the bronchoscopist was 9, and the number of samples assessed by the bronchoscopist was 8, with a median of 6 adequate samples identified by the pathologist. The frequency of previous biopsies, history of prior inadequate samples, need for a higher number of pass attempts, presence of airway abnormalities, and the use of general anesthesia increased the odds of inadequate sampling. Patients with the identified factors may be at risk of inadequate sampling on transbronchial biopsies. The bronchoscopist could consider getting additional samples to avoid a nondiagnostic alveolar sample. Further multicenter studies would help to elucidate other contributing factors.

Higher or Lower? - The Resolution of Analytical Pipelines for the Evaluation of Lipid Nanoparticle Critical Quality Attributes

Dynamic light scattering (DLS) is a routinely used analytical technique to measure the size distribution of a colloidal sample. Nanoparticle tracking analysis (NTA) has more recently emerged as an orthogonal technique to determine particle size and estimated concentration, although widespread use of NTA for lipid nanoparticle (LNP) analysis is not reported. Here, we use DLS and NTA to screen the stability of oligonucleotide drug loaded lipid nanoparticles (oligo-LNPs) at ultra low storage temperatures (-80 °C) in the presence and absence of a cryoprotectant (20 % sucrose, w/v) as a case study to highlight differences in technique resolution. NTA was able to detect additional LNP subpopulations samples for all measured samples, whereas DLS was unable to detect these subpopulations. Our study conveys that the use of orthogonal sizing techniques can support early stage product development, where a more in-depth analysis of formulation and process parameters on LNP stability would support comprehensive understanding of variable defining product stability.

Extremely tortuous sound absorbers with labyrinthine channels in non-porous and microporous solid skeletons

An assembly of additively-manufactured modules to form two-dimensional networks of labyrinthine slits results in a sound absorber with extremely high tortuosity and thereby a relatively low-frequency quarter wavelength resonance. Fully analytical modelling is developed for the generic design of such composite acoustic panels, allowing rapid exploration of various specific designs. In addition to labyrinthine channels in a non-porous solid skeleton, a case is also considered where the skeleton has microporosity such that its permeability is very much lower than that due to the labyrinthine channels alone. The analytical modelling is verified by numerical calculations as well as sound absorption measurements performed on several 3D printed samples of modular composite panels. The experimental validation required overcoming the non-trivial difficulties related to additive manufacturing and testing samples of extreme tortuosity. However, due to the two-dimensionality and modularity of the proposed design, such absorbers can possibly be produced without 3D printing by assembling simple, identical modules produced separately. The experimental results fully confirmed the theoretical predictions that significant sound absorption, almost perfect at the peak, can be achieved at relatively low frequencies using very thin panels, especially those with double porosity.

Transcriptome network analysis of inflammation and fibrosis in keloids

BackgroundKeloid (KL) is a common benign skin tumor. KL is typically characterized by significant fibrosis and an intensive inflammatory response. Therefore, a comprehensive understanding of the interactions between cellular inflammation and fibrotic cells is essential to elucidate the mechanisms driving the progression of KL and to develop therapeutics. ObjectiveInvestigate the transcriptome landscape of inflammation and fibrosis in keloid scars. MethodsIn this paper, we performed transcriptome sequencing and microRNA (miRNA) sequencing on unselected live cells from six human keloid tissues and normal skin tissues to elucidate a comprehensive transcriptome landscape. In addition, we used single-cell RNA sequencing (scRNA-seq) analysis to analyze intercellular communication networks and enrich fibroblast populations in two additional keloid and normal skin samples to study fibroblast diversity. ResultsBy RNA sequencing and a miRNA-mRNA-PPI network analysis, we identified miR-615–5p and miR-122b-3p as possible miRNAs associated with keloids, as they differed most significantly in keloids. Similarly, COL3A1, COL1A2, THBS2, TNC, IGTA, THBS4, TGFB3 as genes with significant differences in keloid may be associated with keloid development. Using single-cell RNA sequencing data from 24,086 cells collected from normal or keloid, we report reconstructed intercellular signaling network analysis and aggregation to modules associated with specific cell subpopulations at the cellular level for keloid alterations. ConclusionsOur multitranscriptomic dataset delineates inflammatory and fibro heterogeneity of human keloids, underlining the importance of intercellular crosstalk between inflammatory cells and fibro cells and revealing potential therapeutic targets.

Potency and Powder X-ray Diffraction (PXRD) Evaluation of Levothyroxine Sodium Tablets under Ambient, Accelerated, and Stressed Conditions.

Levothyroxine tablets, although highly prescribed in the United States, have been one of the most frequently recalled products. Because of the importance of the medication, several efforts have been put in place by the United States Food and Drug Administration (US FDA) to control the quality of levothyroxine tablets available to patients using the drug. The choice of excipients used in the formulation has been shown to impact the hygroscopicity and microenvironment, and ultimately the stability of the levothyroxine tablets formulations. Based on information generated from the US FDA Enforcement Report database, one of the main reasons for recalls is the low potency of different batches of the product. The yearly product recall trends for levothyroxine formulations were determined using the FDA Enforcement Report database. Three brands of levothyroxine tablets were selected with excipient lists similar to those products that have been historically recalled. The samples were placed at ambient (~23 °C), accelerated stability (40 °C/75% RH), and stress (50 °C/75% RH) conditions for up to 6 months. Sample potencies were determined at 0, 1.5, 3, and 6 months using the methods for assay and impurities in the United States Pharmacopeia (USP) monograph for levothyroxine tablets. Additional sample monitoring was conducted by overlaying the initial powder X-ray diffractograms (PXRD) of the samples from 0 months with the patterns generated thereafter. There has been a decline in the number of levothyroxine tablets recalled over the years. The highest numbers of recalls were recorded in the years 2013 [33] and 2020 [23]; no recalls occurred in the years 2019 and 2022. All of the brands evaluated met the USP 95.0-105.0% assay requirements at 1.5 months under accelerated conditions; only one of the brands complied at 3 months. Under ambient conditions, two brands were stable at 6 months, with borderline assay results. For stability, levothyroxine was found in microgram quantities in the formulations and PXRD could not detect changes at these low levels. However, we found some distinguishing data for samples under stress conditions.

Compassionate Use Narsoplimab for Severe Refractory Transplantation-Associated Thrombotic Microangiopathy in Children

Transplant-associated thrombotic microangiopathy (TA-TMA) is a common and potentially severe complication of hematopoietic cell transplantation. TA-TMA-directed therapy with eculizumab, a complement C5 inhibitor, has resulted in a survival benefit in some studies. However, children with TA-TMA refractory to C5 inhibition with eculizumab (rTA-TMA) have mortality rates exceeding 80%, and there are no other known therapies. Narsoplimab, an inhibitor of the MASP-2 effector enzyme of the lectin pathway, has been studied in adults with TA-TMA as first-line therapy with a response rate of 61%. Although there are limited data on narsoplimab use as a second-line agent in children, we hypothesized, that complement pathways proximal to C5 are activated in rTA-TMA, and that narsoplimab may ameliorate rTA-TMA in children. In this single-center study, children were enrolled on single-patient, Institutional Review Board-approved compassionate use protocols for narsoplimab treatment. Clinical complement lab tests were obtained at the discretion of the treating physician, although all patients were also offered participation in a companion biomarker study. Research blood samples were obtained at the time of TA-TMA diagnosis, prior to eculizumab treatment, at the time of refractory TA-TMA diagnosis prior to the first narsoplimab dose, and 2 weeks after the first narsoplimab dose. Single ELISA kits were used to measure markers of complement activation according to the manufacture's instructions. Five children with rTA-TMA received narsoplimab; 3 were in multiorgan failure and 2 had worsening multiorgan dysfunction at the time of treatment. Additional comorbidities at the time of treatment included sinusoidal obstructive syndrome (SOS; n = 3), viral infection (n = 3), and steroid-refractory stage 4 lower gut grade IV acute graft-versus-host disease (aGVHD, n = 3). Two infants with concurrent SOS and no aGVHD had resolution of organ dysfunction; 1 also developed transfusion-independence (complete response), and the other's hematologic response was not assessable in the setting of leukemia and chemotherapy (partial response). One additional patient achieved transfusion independence but had no improvement in organ manifestations (partial response), and 2 patients treated late in the course of disease had no response. Narsoplimab was well tolerated without any attributed adverse effects. Three patients consented to provide additional research blood samples. One patient with resolution of organ failure demonstrated evidence of proximal pathway activation prior to narsoplimab treatment with subsequent declines in Ba, Bb, C3a, and C5a and increases in C3 in both clinical and research lab tests. Otherwise, there was no clear pattern of other complement markers, including MASP-2 levels, after therapy. In this cohort of ill children with rTA-TMA and multiple comorbidities, 3 patients benefited from narsoplimab. Notably, the 2 patients with resolution of organ involvement did not have steroid-refractory aGVHD, which is thought to be a critical driver of TA-TMA. Additional studies are needed to determine which patients are most likely to benefit from narsoplimab and which markers may be most helpful for monitoring lectin pathway activation and inhibition.

Switching Style towards Ease in a Medieval Textbook of Medicine: Revison of Constantine the African’s Pantegni, Theorica in Twelfth-Century Manuscripts

Abstract The Pantegni of Constantine the African (d. by 1098/9) was the first ever comprehensive medical textbook written in Latin. It was translated and modified from an Arabic original in Salerno and in the monastery of Monte Cassino in south Italy. This article demonstrates that a large-scale stylistic revision of the Pantegni, or more precisely of its section Theorica, was carried out in the first half of the twelfth century at the latest. The existence of the revised version suggests there was a desire for Constantine’s translation to meet altered expectations and practical needs. Based on collation of a chapter from Book V and additional sample passages in both the standard version and the revised version of the Theorica, it is argued that the latter was compiled in order to simplify and clarify Constantine’s expression and make his train of thought as lucid as possible.

An Automated Capillary Electrophoresis Based Method for Drug Release Profiling of Liposomal Doxorubicin

Liposomal doxorubicin hydrochloride is an antineoplastic agent widely used against human cancers. The data from in vitro drug release test (IVRT) is essential for quality and/or bioequivalence evaluation in drug approval and post-approval regulation of liposomal drug products. However, most of the currently available IVRT methods for liposomal doxorubicin hydrochloride have experimental deficiencies associated with liposomal rupture during the separation process which is needed for selective quantification of released drug from liposomal-bound drug. In addition, many of the methods are time consuming, requiring bulk quantities of liposomal drug product, and lack of automation. We have developed a selective, sensitive, and automated capillary electrophoresis (CE)-based IVRT method, measuring released doxorubicin without additional sampling and separation steps. This method requires a small volume of sample compared to currently available methods. The IVRT release study with liposomal doxorubicin was conducted at different temperatures and pH conditions. It was observed that the release profiles obtained for five formulations including the reference listed drug were similar at pH 6.50 and 47.0 °C. The drug release increased with the increase of media pH and temperature. Complete doxorubicin release (100 %) was obtained in 7 h at pH 6.50 and 47.0 °C, and in less than 3 h at pH 6.50 and 52.0 °C. This CE-based method can be extended for determination of the IVRT profiling of other liposomal drug products.

Streptomyces Diversity Maps Reveal Distinct High-Specificity Biogeographical and Environmental Patterns Compared to the Overall Bacterial Diversity.

Despite their enormous impact on the environment and humans, the distribution and variety of the biggest natural secondary metabolite producers, the genus Streptomyces, have not been adequately investigated. We developed representative maps from public EMP 16S rRNA amplicon sequences microbiomics data. Streptomyces ASVs were extracted from the EMP overall bacterial community, demonstrating Streptomyces diversity and identifying crucial diversity patterns. Our findings revealed that while the EMP primarily distinguished bacterial communities as host-associated or free-living (EMPO level 1), the Streptomyces community showed no significant difference but exhibited distinctions between categories in EMPO level 2 (animal, plant, non-saline, and saline). Multiple linear regression analysis demonstrated that pH, temperature, and salinity significantly predicted Streptomyces richness, with richness decreasing as these factors increased. However, latitude and longitude do not predict Streptomyces richness. Our Streptomyces maps revealed that additional samplings in Africa and Southeast Asia are needed. Additionally, our findings indicated that a greater number of samples did not always result in greater Streptomyces richness; future surveys may not necessitate extensive sampling from a single location. Broader sampling, rather than local/regional sampling, may be more critical in answering microbial biogeograph questions. Lastly, using 16S rRNA gene sequencing data has some limitations, which should be interpreted cautiously.

Heritability and genetic correlations for sleep apnea, insomnia, and hypersomnia in a large clinical biobank

RationaleComorbid insomnia and sleep apnea is reported to have worse outcomes than either condition alone. The local genetic correlations of these disorders are unknown. ObjectivesTo identify local genomic regions with heritability for clinically diagnosed sleep apnea and insomnia, and to identify local genetic correlations between these disorders and/or hypersomnia. MethodsFifty thousand two hundred seventeen patients of European ancestry were examined. Global and local heritability and genetic correlations for independent regions were calculated, adjusting for obesity and other covariates. ResultsSleep apnea and insomnia were significantly globally heritable and had 118 and 168 genetic regions with local heritability p-values <.05, respectively. One region had a significant genetic correlation for sleep apnea and hypersomnia (p-value = 9.85 × 10−4). ConclusionsClinically diagnosed sleep apnea and insomnia have minimal shared genetic architecture, supporting genetically distinct comorbid insomnia and sleep apnea components. However, additional correlated regions may be identified with additional sample size and methodological improvements.

Collision-Induced Unfolding, Tandem MS, Bottom-up Proteomics, and Interactomics for Identification of Protein Complexes in Native Surface Mass Spectrometry.

Endogenously occurring salts and nonvolatile matrix components in untreated biological surfaces can suppress protein ionization and promote adduct formation, challenging protein identification. Characterization of labile proteins within biological specimens is particularly demanding because additional purification or sample treatment steps can be time-intensive and can disrupt noncovalent interactions. It is demonstrated that the combined use of collision-induced unfolding, tandem mass spectrometry, and bottom-up proteomics improves protein characterization in native surface mass spectrometry (NSMS). This multiprong analysis is achieved by acquiring NSMS, MS/MS, ion mobility (IM), and bottom-up proteomics data from a single surface extracted sample. The validity of this multiprong approach was confirmed by the successful characterization of nine surface-deposited proteins, with molecular weights ranging from 8 to 147 kDa, in two separate mixtures. Bottom-up proteomics provided a list of proteins to match against observed proteins in NSMS and their detected subunits in tandem MS. The method was applied to characterize endogenous proteins from untreated chicken liver samples. The subcapsular liver sampling for NSMS analysis allowed for the detection of endogenous proteins with molecular weights of up to ∼220 kDa. Moreover, using IM-MS, collision cross sections and collision-induced unfolding pathways of enzymatic proteins and protein complexes of up to 145 kDa were obtained.

НОВАЯ ПРОТИВОКОРРОЗИОННАЯ ПРИСАДКА «РОСОЙЛ-АКОР»

The paper contains the results of laboratory tests of a new Rosoil-Akor anticorrosive additive, designed to improve the protective properties of oils for various purposes and fuels in comparison with the similar AKOR-1 additive from two Russian manufacturers. The physicochemical characteristics of the additives are defined. The effect of additives on the protective and anti-wear properties of transformer oils, motor oils and diesel fuel are studied. It is shown that the physico-chemical parameters of Rosoil-Akor additive meets the requirements of GOST 15171-78 Additive AKOP-I. Specifications. It is found that when exposed to salt fog, the protective ability of oils and diesel fuel with Rosoil-Akor additive is 3-10 times higher than with AKOR-1 additives. At higher values of relative humidity and air temperature, the protective ability of oils and diesel fuel with Rosoil-Akor additive is up to 25 times better than with AKOR-1 additives. All the additives under study increase the anti-wear properties of transformer oils, while the diameter of the wear spot of oil with Rosoil-Akor additive is 1.2-1.4 times smaller than oils with AKOR-1 additives. The addition of the studied additives to engine oils does not significantly affect the anti-wear properties of oils. The wear index of diesel fuel decreases with the addition of Rosoil-Akor and AKOR-1 additives (sample No. 1), but increases with the addition of AKOR-1 additive (sample No. 2). Test results show that the new Rosoil-Akor additive has high anticorrosive and anti-wear properties and can be used to improve the protective properties of oils for various purposes and diesel fuel instead of AKOR-1 additive.

Co-Pyrolysis of walnut shell and waste tire with a focus on bio-oil yield quantity and quality

In this study, a series of pyrolysis and co-pyrolysis experiments on waste tires and walnut shells were conducted under ideal conditions of 500 °C, 10 °C/min heating rate, and 60 min of retention time. Mixture samples with WS/WT: 3/1, 2/2, and 1/3 additive ratios were utilized in co-pyrolysis experiments. The results of the experiments showed that the WS/WT: 3/1 additive ratio samples were necessary to achieve the positive synergistic effect. A 52.57 ± 0.28 % efficient liquid product by mass was produced under these conditions on a dry, ashless basis, which has a significant production potential for the production of high pyrolytic oil. The co-pyrolytic organic phase of the fuel contains around 40 % light naphtha, 10 % heavy naphtha, and 30 % medium distillate by volume, according to atmospheric distillation experiments. Furthermore, it has been discovered that this product can be utilized as a gasoline or gasoline additive due to its IBP-72 °C boiling point range, 20 % distillate percentage, and immediate or inexpensive improvement. When these observations are taken into consideration, it is clear that the co-pyrolytic liquid can be utilized as a raw material input in the production of various of commercial liquid fuels as well as a variety of chemicals with high added value.

Circulating Factor Seven Activating Protease (FSAP) in the Hyperacute Phase of Stroke

Background. Factor VII activating protease (FSAP) is a circulating serine protease that could be involved in the pathophysiology of stroke. We analyzed the temporal changes in FSAP antigen and FSAP activity after acute cerebral ischemia (ACI) and tested if FSAP could be used to differentiate between stroke subtypes in the hyperacute phase (&lt;4.5 hours after symptom onset). Methods. Of the 118 suspected stroke patients enrolled, 76 had ACI; of which 20 suffered from large vessel occlusion (LVO), 19 had intracerebral hemorrhage (ICH), and 23 had stroke mimics. Median time from symptom onset to the two plasma sample collections, &lt;4.5 hours, were 66 and 107 minutes for the entire study population. Additional samples were collected up to 90 days post stroke in a subset of ACI patients ( n = 19 ). FSAP antigen, FSAP activity, FSAP-α2-antiplasmin-complex (FSAP-AP complex), and nucleosomes were measured by activity assays or ELISA. Results. ACI patients treated with tissue plasminogen activator (tPA) had elevated FSAP activity &lt; 4.5 hours ( p = 0.016 ) that subsequently normalized after 6 hours. FSAP-AP complex levels decreased significantly from &lt;4.5 hours ( p = 0.015 ) to 6 hours after symptom onset. tPA did not increase FSAP activity significantly in plasma in vitro. FSAP antigen significantly decreased &lt; 4.5 hours after symptom onset in LVO ( p = 0.008 ) and ICH ( p = 0.017 ) patients. FSAP could not differentiate ACI from ICH or strokes (ACI and ICH) from stroke mimics. FSAP did not correlate with stroke severity. Conclusion. LVO and ICH seem to influence FSAP levels in the hyperacute phase of stroke, but FSAP does not differentiate between stroke subtypes in a hyperacute setting.

10214-COT-24 A RARE CLINICAL CASE OF LUMBAR METASTASIS FROM GLIOSARCOMA

Abstract Gliosarcoma (GS) is a variant of glioblastoma (GBM) and has been shown to be prone to extracranial metastasis. We report a rare case of lumbar metastasis of Gliosarcoma (GS) based on histopathological findings.37-year-old male.He underwent emergency surgery for a left frontal subcortical hemorrhage. Pathological diagnosis confirmed GS. Postoperatively, the patient underwent conventional radiation chemotherapy. Later, in conjunction with cranioplasty, the remaining lesion was additionally excised and maintenance therapy was administered for 9 months. Subsequently, a follow-up MRI revealed an intracranial disseminated lesion, although the primary site was not affected. At the same time, he had difficulty moving due to back pain, and MRI revealed extracranial metastases in the second lumbar vertebra and retroperitoneum. Lumbar biopsy confirmed the diagnosis of metastasis. Pathological findings at the initial surgery showed that the tumor consisted of GS and gemistocyte-like components, and immunostaining and genetic findings showed IDH wild type GBM. Additional tissue samples showed predominantly gemistocyte-like components and no GS component, and the genetic profile was similar.Lumbar biopsies showed predominantly GS and no gemistocyte-like components. MGMT methylation changed from methylation-negative to positive and then negative by immunostaining and MS-PCR. In a previous report, Feldheim et al. performed a meta-analysis of MGMT methylation changes in relapsing GBM and reported increased methylation after relapse. In addition, Jimenez et al. quantitatively analyzed MGMT methylation in recurrent GBM by pyrosequencing and found an increased rate of methylation in about half of the cases. These reports indicate that MGMT methylation is altered following therapeutic intervention. In the present case, it was hypothesized that an intracranial lesion that was initially unmethylated was methylated by the intervention, but an unmethylated, treatment-resistant GS component metastasized to the extracranial space. The clinical course of this case was a rare example of evidence of a change in MGMT methylation due to therapeutic intervention.

Testable likelihoods for beyond-the-standard model fits

Studying potential BSM effects at the precision frontier requires accurate transfer of information from low-energy measurements to high-energy BSM models. We propose to use normalising flows to construct likelihood functions that achieve this transfer. Likelihood functions constructed in this way provide the means to generate additional samples and admit a “trivial” goodness-of-fit test in form of a χ2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\chi ^2$$\\end{document} test statistic. Here, we study a particular form of normalising flow, apply it to a multi-modal and non-Gaussian example, and quantify the accuracy of the likelihood function and its test statistic.