gebhart/patrepeval huggingface dataset:
Characteristics and outcomes of patients undergoing high-dose chemotherapy and autologous stem cell transplantation admitted to the intensive care unit: a single-center retrospective analysis (2022)

High-dose chemotherapy and autologous stem cell transplantation (ASCT) can be associated with adverse events necessitating treatment on the intensive care unit (ICU). Data focusing on patients admitted to the ICU during hospitalization for high-dose chemotherapy and ASCT are scarce. We thus conducted a single-center retrospective analysis comprising 79 individuals who had high-dose chemotherapy and ASCT between 2014 and 2020 and were admitted to the ICU between the initiation of conditioning therapy and day 30 after ASCT. The median age was 57 years (range: 20-82 years); 38% of patients were female. B-cell non-Hodgkin lymphoma (34%) and plasma cell disorders (28%) were the most common indications for high-dose chemotherapy and ASCT. Sepsis represented the major cause for ICU admission (68%). Twenty-nine percent of patients required mechanical ventilation (MV), 5% had renal replacement therapy, and 44% needed vasopressors. The ICU, hospital, 90-day, and 1-year survival rates were 77.2%, 77.2%, 72.2%, and 60.3%, respectively. Stable disease or disease progression prior to the initiation of high-dose chemotherapy (p = 0.0028) and MV (p < 0.0001) were associated with an impaired survival. A total of 36 patients died during observation. The most frequent causes of death were the underlying malignancy (44%) and sepsis (39%). Taken together, the present analysis indicates a favorable overall outcome for patients admitted to the ICU during hospitalization for high-dose chemotherapy and ASCT. Thus, this patient group should not be denied admission and treatment on the ICU.
Transfer Learning to adapt 5G AI-based Fingerprint Localization across Environments (2022)

Fingerprint-based indoor positioning has attracted a lot of interest due to its potential to meet a positional accuracy that enables many location-based 5G indoor services. However, the accuracy of fingerprinting decreases with changes in the environment which prevents positioning in new scenarios. On the other hand, naively acquiring up-to-date training data from the changed environment to retrain the model is often time-consuming. It is unclear whether after a change in the environment, a fingerprint model can be (data-)efficiently updated.This paper examines the generalizability (with respect to accuracy, robustness, and effort in recording data) of state-of-the-art fingerprint models based on a convolutional neural network (CNN) in realistic setups with changes in the environment. We propose a transfer learning (TL) method that exploits realistic synthetic Channel State Information (CSI) obtained with the Quasi Deterministic Radio channel Generator (QuaDRiGa), used to pre-train the CNN-based fingerprint model so that it can be adapted to any real (NLoS) propagation scenario with a low number of real training samples. Our experiments show that the positioning accuracy using fine-tuning improves by 37% in changed and by 19% in new environments.
NCCN Guidelines Insights: Kidney Cancer, Version 1.2021 (2020)

The NCCN Guidelines for Kidney Cancer provide multidisciplinary recommendations for diagnostic workup, staging, and treatment of patients with renal cell carcinoma (RCC). These NCCN Guidelines Insights focus on recent updates to the guidelines, including changes to certain systemic therapy recommendations for patients with relapsed or stage IV RCC. They also discuss the addition of a new section to the guidelines that identifies and describes the most common hereditary RCC syndromes and provides recommendations for genetic testing, surveillance, and/or treatment options for patients who are suspected or confirmed to have one of these syndromes.
The long non-coding RNA SAMMSON is essential for uveal melanoma cell survival (2021)

Long non-coding RNAs (lncRNAs) can exhibit cell-type and cancer-type specific expression profiles, making them highly attractive as therapeutic targets. Pan-cancer RNA sequencing data revealed broad expression of the SAMMSON lncRNA in uveal melanoma (UM), the most common primary intraocular malignancy in adults. Currently, there are no effective treatments for UM patients with metastatic disease, resulting in a median survival time of 6-12 months. We aimed to investigate the therapeutic potential of SAMMSON inhibition in UM. Antisense oligonucleotide (ASO)-mediated SAMMSON inhibition impaired the growth and viability of a genetically diverse panel of uveal melanoma cell lines. These effects were accompanied by an induction of apoptosis and were recapitulated in two uveal melanoma patient derived xenograft (PDX) models through subcutaneous ASO delivery. SAMMSON pulldown revealed several candidate interaction partners, including various proteins involved in mitochondrial translation. Consequently, inhibition of SAMMSON impaired global, mitochondrial and cytosolic protein translation levels and mitochondrial function in uveal melanoma cells. The present study demonstrates that SAMMSON expression is essential for uveal melanoma cell survival. ASO-mediated silencing of SAMMSON may provide an effective treatment strategy to treat primary and metastatic uveal melanoma patients.
Evaluation of survival and recovery characteristics of bifidobacteria as indicators of fecal pollution of water (2000)

The examination of aquatic environments for bacterial indicator organisms has proven to be a useful and well-established practice for the purpose of monitoring microbiological water quality. An ideal indicator of fecal pollution should be present in sufficient density to allow detection, present simultaneous with pathogen(s), incapable of aftergrowth in external aquatic environments, easy to enumerate, and exclusively of fecal origin. Unfortunately, none of the indicator organisms presently in use today meet all of these requirements. Bifidobacteria show promise as indicators of fecal pollution in water with the additional ability of potentially distinguishing between fecal pollution of human and animal origin. In laboratory microcosm experiments, the survival of the bifidobacteria population was indirectly proportional to the temperature at which the microcosm was stored. In mixed microcosm studies with E. coli, the survival of the bifidobacteria population was considerably less than the E. coli population. The recovery of bifidobacteria from constructed wetlands receiving primary treated sewage was monitored using published selective media (YN6, BIM25, and BIM50 agar). In the influent and wetland samples, there was approximately a 2 to 3 log reduction of bifidobacteria, while fecal coliforms exhibited a 4 to 5 log reduction. Results indicate the YN6 medium lacks the desired sensitivity and selectivity to effectively enumerate bifidobacteria. Studies addressing the recovery of bifidobacteria from the wetlands with modified bifidobacteria enumeration media were mixed to unsuccessful.
Distinguishing the Direct and Indirect Products of a Gas-Surface Reaction (1994)

It has long been postulated that gas-surface chemical reactions can occur by means of two distinct mechanisms: direct reaction on a single gas-surface encounter or reaction between two adsorbed species. It is shown here that these mechanisms have distinct dynamical signatures, as illustrated by the reaction of hydrogen with chlorine on gold(111). The direct reaction product leaves the surface with a high kinetic energy in a narrow angular distribution that displays a "memory" of the direction and energy of the incident hydrogen atom. The indirect reaction product has a near-thermal energy distribution and an angular distribution that is close to that of a cosine function.
Immune-focused multi-omics analysis of prostate cancer: leukocyte Ig-Like receptors are associated with disease progression (2020)

Prostate cancer (PCa) immunotherapy has shown limited efficacy so far, even in advanced-stage cancers. The success rate of PCa immunotherapy might be improved by approaches more adapted to the immunobiology of the disease. The objective of this study was to perform a multi-omics analysis to identify immune genes associated with PCa progression to better characterize PCa immunobiology and propose new immunotherapeutic targets. mRNA, miRNA, methylation, copy number aberration, and single nucleotide variant datasets from The Cancer Genome Atlas PRAD cohort were analyzed after filtering for genes associated with immunity. Sparse partial least squares-discriminant analyses were performed to identify features associated with biochemical recurrence (BCR) in each type of omics data. Selected features predicted BCR with a balanced error rate (BER) of 0.20 to 0.51 in single-omics and of 0.05 in multi-omics analyses. Amongst features associated with BCR were genes from the Immunoglobulin Ig-like Receptor (LILR) family which are immune checkpoints with immunotherapeutic potential. Using Multivariate INTegrative (MINT) analysis, the association of five <i>LILR</i> genes with BCR was quantified in a combination of three RNA-seq datasets and confirmed with Kaplan-Meier analysis in both these and in an independent RNA-seq dataset. Finally, immunohistochemistry showed that a high number of LILRB1 positive cells within the tumors predicted long-term adverse outcomes. Thus, tumors characterized by abnormal expression of <i>LILR</i> genes have an elevated risk of recurring after definitive local therapy. The immunotherapeutic potential of these regulators to stimulate the immune response against PCa should be evaluated in pre-clinical models.
Monoclonal Antibodies Reveal Additional Epitopes of Serotype D Cryptococcus neoformans Capsular Glucuronoxylomannan that Elicit Protective Antibodies (1998)

Epitope specificity and isotype influence mAb efficacy against Cryptococcus neoformans; however, the relative contribution of each attribute is poorly understood. To date, only mAbs that recognize two epitopes of capsular glucuronoxylomannan (GXM), defined by the IgG1 mAbs 2H1 and E1, consistently mediate protection against C. neoformans. The role of epitope specificity was further examined using six additional IgG1 mAbs and serotype D C. neoformans ATCC 24067. mAbs 3C2, 439, and 471 recognize the 2H1 epitope, whereas mAbs 339, 1255, and 302 recognize two separate epitopes. mAbs 3C2, 439, and 471 competed for GXM with the IgA mAb 18G9, a 2H1 mAb family member, whereas mAbs 302, 339, and 1255 did not. Each mAb bound GXM similarly, as determined by agglutination, direct Ag binding, Ag inhibition, and indirect capsular immunofluorescence assays. mAb apparent affinity constants for GXM ranged from 5 to 26 x 10(7) M(-1) with mAb 1255 > 3C2 > 339 > 439 > 471 > 302. Each mAb significantly prolonged survival (p < 0.05); the average survival times of control and mice passively immunized with mAbs 3C2, 302, 339, 439, 471, and 1255 were 10.8, 36.6, 33, 25.5, 24.9, 17, and 22.6 days, respectively. Although each mAb enhanced J774.16 cell fungicidal activity, differences were observed in the ability of each mAb to facilitate attachment and ingestion of cryptococci. These results indicate 1) two additional epitope specificities associated with mAb efficacy, 2) differences in opsonic and protective efficacy for IgG1 anti-GXM mAbs, 3) an association between affinity and protective efficacy, and 4) additional support for association between an annular indirect capsular immunofluorescence pattern and mAb efficacy.
Electronic Structure, Molecular Geometry, and Bonding Energetics in Zerovalent Yttrium and Gadolinium Bis(arene) Sandwich Complexes. A Theoretical ab Initio Study (1996)

The first ab initio study of bonding and bonding energetics in zerovalent rare earth bis(arene) sandwich complexes is presented. The d3 ground state and d2s1 first excited state [(e2g)3 and (e2g)2(a1g1) configurations, respectively] electronic structures and geometries of the M(η6-C6H6)2 complexes, where M = Y and Gd, have been investigated by using relativistic effective core potentials with MP2, MP4, and coupled-cluster ab initio wave functions. The two electronic states lie close in energy but exhibit significant differences in bonding interactions and geometries. The greater stabilities found in the ground states of both complexes are associated with greater metal → ligand back-bonding interactions and, hence, shorter M−C bond lengths. Computed ground state electronic configurations agree well with experimental EPR and magnetic susceptibility data, while metrical parameters are in very good agreement with diffraction data. The metal−arene interactions, both ligand-to-metal donation and metal-to-ligand back-donation, are similar in both complexes. The role of electron correlation appears crucial to correctly predicting the metal−arene dissociation energies. The Hartree−Fock energy is actually repulsive compared to that of the ground state fragments, while the inclusion of correlation effects through perturbative and coupled-cluster procedures predicts bound molecules, even though the binding energies remain underestimated.
CTNI-37. EFFICACY OF ONC201 IN PATIENTS WITH ONC201 FOR RECURRENT H3 K27M-MUTANT DIFFUSE MIDLINE GLIOMA (2020)

Abstract H3 K27M-mutant diffuse midline gliomas (DMG) have a dismal prognosis. We report an integrated analysis for ONC201, a DRD2 antagonist and ClpP agonist, in patients with recurrent H3 K27M DMG administered as monotherapy in 3 clinical studies (NCT03295396, n=20; NCT02525692, n=6; or expanded access, n=4) by independent, central radiology review among 30 patients. At baseline, patients had measurable contrast-enhancing disease by RANO criteria, KPS&amp;gt;60, and were &amp;gt;90 days from prior radiation. Patients with primary lesions that involved the pons or spinal cord or had evidence of leptomeningeal or cerebrospinal fluid dissemination were excluded. ONC201 was orally administered at 625 mg (scaled by body weight for patients &amp;lt; 18 years old) weekly in 29 patients and every 3 weeks in 1 patient. Median age was 31 years (range 8–70; two patients &amp;lt; 18). There were 16 women and 14 men. Tumors were predominantly thalamic (73%), with other locations including the cerebellum (5%), brainstem (non-pontine) (3%), basal ganglia (3%), and midbrain (3%). Median time from prior radiation was 7.5 months. The most frequent drug-related adverse events were low grade nausea (10%) and fatigue (10%). Nine patients (30%) had &amp;gt;50% regression of T1 contrast enhancement and 11 (36.7%) patients had regression of T2/FLAIR. Objective response rate and progression-free survival by RANO criteria, as well overall survival will be reported. Among 8 patients with sustained radiographic regressions, 6 were tapered off dexamethasone and 4 had improvement in KPS. Five patients (16.7%) remain on treatment with a median of 9.5 months (range 7.3–12). In conclusion, single agent ONC201 is well tolerated and clinically active in recurrent H3 K27M DMG patients.
154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction (2007)

You have accessJournal of UrologyModerated Poster 6, Sunday, May 20, 2007, 8:00 - 10:00 am1 Apr 2007154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction Stefano Ongarello, Eberhard Steiner, Regina Achleitner, Isabel Feuerstein, Birgit Stenzel, Christian Fuchsberger, Claudio Cobelli, Gianna Toffolo, Wolfgang Horninger, Georg Bartsch, Günther K. Bonn, Helmut Klocker, and Alexandre E. Pelzer Stefano OngarelloStefano Ongarello More articles by this author , Eberhard SteinerEberhard Steiner More articles by this author , Regina AchleitnerRegina Achleitner More articles by this author , Isabel FeuersteinIsabel Feuerstein More articles by this author , Birgit StenzelBirgit Stenzel More articles by this author , Christian FuchsbergerChristian Fuchsberger More articles by this author , Claudio CobelliClaudio Cobelli More articles by this author , Gianna ToffoloGianna Toffolo More articles by this author , Wolfgang HorningerWolfgang Horninger More articles by this author , Georg BartschGeorg Bartsch More articles by this author , Günther K. BonnGünther K. Bonn More articles by this author , Helmut KlockerHelmut Klocker More articles by this author , and Alexandre E. PelzerAlexandre E. Pelzer More articles by this author View All Author Informationhttps://doi.org/10.1016/S0022-5347(18)30419-1AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail "154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction." The Journal of Urology, 177(4S), pp. 52–53 © 2016 by American Urological AssociationFiguresReferencesRelatedDetails Volume 177Issue 4SApril 2007Page: 52-53 Advertisement Copyright & Permissions© 2016 by American Urological AssociationMetricsAuthor Information Stefano Ongarello More articles by this author Eberhard Steiner More articles by this author Regina Achleitner More articles by this author Isabel Feuerstein More articles by this author Birgit Stenzel More articles by this author Christian Fuchsberger More articles by this author Claudio Cobelli More articles by this author Gianna Toffolo More articles by this author Wolfgang Horninger More articles by this author Georg Bartsch More articles by this author Günther K. Bonn More articles by this author Helmut Klocker More articles by this author Alexandre E. Pelzer More articles by this author Expand All Advertisement PDF downloadLoading ...
Laser Spike Annealing for Shallow Junctions in Ge CMOS (2016)

An annealing method capable of forming highly activated shallow junctions in Ge CMOS is still lacking. For the first time, nonmelt submillisecond laser spike annealing (LSA) is demonstrated to achieve high activation level, excellent diffusion control, and resulting low contact resistivity for both n-type and p-type Ge junctions when using P and B as the dopants, respectively. The thermal stability of the junctions activated by LSA is investigated. In addition, our results on Ge junctions and contacts are benchmarked systematically against published results using sheet resistance-junction depth (R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> -X <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> ) plots and contact resistivity-dopant concentration (ρ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">c</sub> - N) plots.
Privacy-preserving big data publishing (2015)

The problem of privacy-preserving data mining has been studied extensively in recent years because of its importance as a key enabler in the sharing of massive data sets. Most of the work in privacy has focussed on issues involving the quality of privacy preservation and utility, though there has been little focus on the issue of scalability in privacy preservation. The reason for this is that anonymization has generally been seen as a batch and one-time process in the context of data sharing. However, in recent years, the sizes of data sets have grown tremendously to a point where the effective application of the current algorithms is becoming increasingly difficult. Furthermore, the transient nature of recent data sets has resulted in an increased need for the repeated application of such methods on the newer data sets which have been collected. Repeated application demands even greater computational efficiency in order to be practical. For example, an algorithm with quadratic complexity is unlikely to be implementable in reasonable time over terabyte scale data sets. A bigger issue is that larger data sets are likely to be addressed by distributed frameworks such as MapReduce. In such frameworks, one has to address the additional issue of minimizing data transfer across different nodes, which is the bottleneck. In this paper, we discuss the first approach towards privacy-preserving data mining of very massive data sets using MapReduce. We study two most widely-used privacy models k-anonymity and l-diversity for anonymization, and present experimental results illustrating the effectiveness of the approach.
An Intelligent Classification Framework for Complex PQDs Using Optimized KS-Transform and Multiple Fusion CNN (2023)

Intelligent classification of multiple power quality disturbances (PQDs) is a top priority in pollution control of the power grid. However, the large-scale application of renewable energy introduces lots of nonlinear and impact loads, which makes the PQDs more complex and challenges the effectiveness of conventional detection frameworks. In this article, a novel framework based on optimized Kaiser-window-based <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$S$</tex-math></inline-formula> -transform (OKST) and multiple fusion convolutional neural network (MFCNN) is proposed to identify multiple complex PQDs. First, the OKST is used for the time–frequency positioning of PQDs, where an improved control function is proposed to meet different detection requirements of time–frequency. Additionally, the parameters of the control function are adjusted automatically using maximum energy concentration. Then, the MFCNN based on residual networks (ResNets) is further proposed to extract and classify these time–frequency features automatically. In MFCNN, feature information is fused using different convolution kernels at a two-dimensional level, which can effectively reduce information loss and improve classification performance. The network model is set up using the Pytorch platform, and the dataset containing 28 types of PQDs and 2 types of nonlinearly mixed PQDs is built to test our framework. The result shows that the proposed OKST-MFCNN obtains an average accuracy of 99.38% under the 20-dB noise level, which is more accurate and robust than some advanced PQDs detection frameworks. Moreover, the accuracy of 97.94% is achieved with satisfactory real-time performance in hardware platform experiments, proving its superior identification performance for complex PQDs.