First Measurement of η Meson Production in Neutrino Interactions on Argon with MicroBooNE

We present a measurement of η production from neutrino interactions on argon with the MicroBooNE detector. The modeling of resonant neutrino interactions on argon is a critical aspect of the neutrino oscillation physics program being carried out by the DUNE and Short Baseline Neutrino programs. η production in neutrino interactions provides a powerful new probe of resonant interactions, complementary to pion channels, and is particularly suited to the study of higher-order resonances beyond the Δ(1232). We measure a flux-integrated cross section for neutrino-induced η production on argon of 3.22±0.84(stat)±0.86(syst) 10^{-41}  cm^{2}/nucleon. By demonstrating the successful reconstruction of the two photons resulting from η production, this analysis enables a novel calibration technique for electromagnetic showers in GeV accelerator neutrino experiments.

Tissue informative cell-free DNA methylation sites in amyotrophic lateral sclerosis

Cell-free DNA (cfDNA) is increasingly recognized as a promising biomarker candidate for disease monitoring. However, its utility in neurodegenerative diseases, like amyotrophic lateral sclerosis (ALS), remains underexplored. Existing biomarker discovery approaches are tailored to a specific disease context or are too expensive to be clinically practical. Here, we address these challenges through a new approach combining advances in molecular and computational technologies. First, we develop statistical tools to select tissue-informative DNA methylation sites relevant to a disease process of interest. We then employ a capture protocol to select these sites and perform targeted methylation sequencing. Multi-modal information about the DNA methylation patterns are then utilized in machine learning algorithms trained to predict disease status and disease progression. We applied our method to two independent cohorts of ALS patients and controls (n=192). Overall, we found that the targeted sites accurately predicted ALS status and replicated between cohorts. Additionally, we identified epigenetic features associated with ALS phenotypes, including disease severity. These findings highlight the potential of cfDNA as a non-invasive biomarker for ALS.

MRI-based bone marrow radiomics for predicting cytogenetic abnormalities in multiple myeloma

AIM

To develop a radiomics signature applied to magnetic resonance imaging (MRI)-images to predict cytogenetic abnormalities in multiple myeloma (MM).

MATERIALS AND METHODS

Patients with newly diagnosed MM were enrolled retrospectively from March 2019 to September 2022. They were categorised into the high-risk cytogenetics (HRC) group and standard-risk cytogenetics (SRC) group. The patients were allocated randomly at a ratio of 7:3 into training and validation cohorts. Volumes of interest (VOI) was drawn manually on fat suppression T2-weighted imaging (FS-T2WI) and copied to the same location of the T1-weighted imaging (T1WI) sequence. Radiomics features were extracted from two sequences and selected by reproducibility and redundant analysis. The least absolute shrinkage selection operation (LASSO) algorithm was applied to build the radiomics signatures. The performance of the radiomics signatures to distinguish HRC with SRC was evaluated by ROC curves. The area under the curve (AUC), specificity, and sensitivity were also calculated.

RESULTS

A total of 105 MM patients were enrolled in this study. The four and 11 most significant and relevant features were selected separately from T1WI and FS-T2WI sequences to build the radiomics signatures based on the training cohort. Compared to the T1WI sequence, the radiomics signature based on the FS-T2WI sequence achieved better performance with AUCs of 0.896 and 0.729 in the training and validation cohorts respectively. A sensitivity of 0.833, specificity of 0.667, and Youden index of 0.500 were achieved for the FS-T2WI radiomics signature in the validation cohort.

CONCLUSIONS

The radiomics signature based on MRI provides a non-invasive and convenient tool to predict cytogenetic abnormalities in MM patients.

Search for Heavy Neutral Leptons in Electron-Positron and Neutral-Pion Final States with the MicroBooNE Detector

We present the first search for heavy neutral leptons (HNLs) decaying into νe^{+}e^{-} or νπ^{0} final states in a liquid-argon time projection chamber using data collected with the MicroBooNE detector. The data were recorded synchronously with the NuMI neutrino beam from Fermilab's main injector corresponding to a total exposure of 7.01×10^{20} protons on target. We set upper limits at the 90% confidence level on the mixing parameter |U_{μ4}|^{2} in the mass ranges 10≤m_{HNL}≤150  MeV for the νe^{+}e^{-} channel and 150≤m_{HNL}≤245  MeV for the νπ^{0} channel, assuming |U_{e4}|^{2}=|U_{τ4}|^{2}=0. These limits represent the most stringent constraints in the mass range 35 Collapse

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Affiliation(s)

P Abratenko Tufts University, Medford, Massachusetts 02155, USA
O Alterkait Tufts University, Medford, Massachusetts 02155, USA
D Andrade Aldana Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
L Arellano The University of Manchester, Manchester M13 9PL, United Kingdom
J Asaadi University of Texas, Arlington, Texas 76019, USA
A Ashkenazi Tel Aviv University, Tel Aviv, Israel, 69978
S Balasubramanian Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
B Baller Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
G Barr University of Oxford, Oxford OX1 3RH, United Kingdom
D Barrow University of Oxford, Oxford OX1 3RH, United Kingdom
J Barrow Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA Tel Aviv University, Tel Aviv, Israel, 69978
V Basque Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
O Benevides Rodrigues Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
S Berkman Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA Michigan State University, East Lansing, Michigan 48824, USA
A Bhanderi The University of Manchester, Manchester M13 9PL, United Kingdom
A Bhat University of Chicago, Chicago, Illinois 60637, USA
M Bhattacharya Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
M Bishai Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
A Blake Lancaster University, Lancaster LA1 4YW, United Kingdom
B Bogart University of Michigan, Ann Arbor, Michigan 48109, USA
T Bolton Kansas State University (KSU), Manhattan, Kansas 66506, USA
J Y Book Harvard University, Cambridge, Massachusetts 02138, USA
M B Brunetti University of Warwick, Coventry CV4 7AL, United Kingdom
L Camilleri Columbia University, New York, New York 10027, USA
Y Cao The University of Manchester, Manchester M13 9PL, United Kingdom
D Caratelli University of California, Santa Barbara, California 93106, USA
F Cavanna Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
G Cerati Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
A Chappell University of Warwick, Coventry CV4 7AL, United Kingdom
Y Chen SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
J M Conrad Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
M Convery SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
L Cooper-Troendle University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
J I Crespo-Anadón Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
R Cross University of Warwick, Coventry CV4 7AL, United Kingdom
M Del Tutto Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
S R Dennis University of Cambridge, Cambridge CB3 0HE, United Kingdom
P Detje University of Cambridge, Cambridge CB3 0HE, United Kingdom
A Devitt Lancaster University, Lancaster LA1 4YW, United Kingdom
R Diurba Universität Bern, Bern CH-3012, Switzerland
Z Djurcic Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
R Dorrill Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
K Duffy University of Oxford, Oxford OX1 3RH, United Kingdom
S Dytman University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
B Eberly University of Southern Maine, Portland, Maine 04104, USA
P Englezos Rutgers University, Piscataway, New Jersey 08854, USA
A Ereditato University of Chicago, Chicago, Illinois 60637, USA Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
J J Evans The University of Manchester, Manchester M13 9PL, United Kingdom
R Fine Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
O G Finnerud The University of Manchester, Manchester M13 9PL, United Kingdom
W Foreman Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
B T Fleming University of Chicago, Chicago, Illinois 60637, USA
D Franco University of Chicago, Chicago, Illinois 60637, USA
A P Furmanski University of Minnesota, Minneapolis, Minnesota 55455, USA
F Gao University of California, Santa Barbara, California 93106, USA
D Garcia-Gamez Universidad de Granada, Granada E-18071, Spain
S Gardiner Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
G Ge Columbia University, New York, New York 10027, USA
S Gollapinni Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
E Gramellini The University of Manchester, Manchester M13 9PL, United Kingdom
P Green University of Oxford, Oxford OX1 3RH, United Kingdom
H Greenlee Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
L Gu Lancaster University, Lancaster LA1 4YW, United Kingdom
W Gu Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
R Guenette The University of Manchester, Manchester M13 9PL, United Kingdom
P Guzowski The University of Manchester, Manchester M13 9PL, United Kingdom
L Hagaman University of Chicago, Chicago, Illinois 60637, USA
O Hen Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
C Hilgenberg University of Minnesota, Minneapolis, Minnesota 55455, USA
G A Horton-Smith Kansas State University (KSU), Manhattan, Kansas 66506, USA
Z Imani Tufts University, Medford, Massachusetts 02155, USA
B Irwin University of Minnesota, Minneapolis, Minnesota 55455, USA
M Ismail University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
C James Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
X Ji Nankai University, Nankai District, Tianjin 300071, China
J H Jo Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
R A Johnson University of Cincinnati, Cincinnati, Ohio 45221, USA
Y-J Jwa Columbia University, New York, New York 10027, USA
D Kalra Columbia University, New York, New York 10027, USA
N Kamp Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
G Karagiorgi Columbia University, New York, New York 10027, USA
W Ketchum Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
M Kirby Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
T Kobilarcik Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
I Kreslo Universität Bern, Bern CH-3012, Switzerland
M B Leibovitch University of California, Santa Barbara, California 93106, USA
I Lepetic Rutgers University, Piscataway, New Jersey 08854, USA
J-Y Li University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
K Li Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
Y Li Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
K Lin Rutgers University, Piscataway, New Jersey 08854, USA
B R Littlejohn Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
H Liu Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
W C Louis Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
X Luo University of California, Santa Barbara, California 93106, USA
C Mariani Center for Neutrino Physics, Virginia Tech, Blacksburg, Viriginia 24061, USA
D Marsden The University of Manchester, Manchester M13 9PL, United Kingdom
J Marshall University of Warwick, Coventry CV4 7AL, United Kingdom
N Martinez Kansas State University (KSU), Manhattan, Kansas 66506, USA
D A Martinez Caicedo South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
S Martynenko Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
A Mastbaum Rutgers University, Piscataway, New Jersey 08854, USA
I Mawby University of Warwick, Coventry CV4 7AL, United Kingdom
N McConkey University College London, London WC1E 6BT, United Kingdom
V Meddage Kansas State University (KSU), Manhattan, Kansas 66506, USA
J Micallef Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA Tufts University, Medford, Massachusetts 02155, USA
K Miller University of Chicago, Chicago, Illinois 60637, USA
A Mogan Colorado State University, Fort Collins, Colorado 80523, USA
T Mohayai Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA Indiana University, Bloomington, Indiana 47405, USA
M Mooney Colorado State University, Fort Collins, Colorado 80523, USA
A F Moor University of Cambridge, Cambridge CB3 0HE, United Kingdom
C D Moore Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
L Mora Lepin The University of Manchester, Manchester M13 9PL, United Kingdom
M M Moudgalya The University of Manchester, Manchester M13 9PL, United Kingdom
S Mulleriababu Universität Bern, Bern CH-3012, Switzerland
D Naples University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
A Navrer-Agasson The University of Manchester, Manchester M13 9PL, United Kingdom
N Nayak Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
M Nebot-Guinot University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
J Nowak Lancaster University, Lancaster LA1 4YW, United Kingdom
N Oza Columbia University, New York, New York 10027, USA
O Palamara Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
N Pallat University of Minnesota, Minneapolis, Minnesota 55455, USA
V Paolone University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
A Papadopoulou Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
V Papavassiliou New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
H B Parkinson University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
S F Pate New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
N Patel Lancaster University, Lancaster LA1 4YW, United Kingdom
Z Pavlovic Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
E Piasetzky Tel Aviv University, Tel Aviv, Israel, 69978
I Pophale Lancaster University, Lancaster LA1 4YW, United Kingdom
X Qian Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
J L Raaf Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
V Radeka Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
A Rafique Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
M Reggiani-Guzzo University of Edinburgh, Edinburgh EH9 3FD, United Kingdom The University of Manchester, Manchester M13 9PL, United Kingdom
L Ren New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
L Rochester SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
J Rodriguez Rondon South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
M Rosenberg Tufts University, Medford, Massachusetts 02155, USA
M Ross-Lonergan Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
C Rudolf von Rohr Universität Bern, Bern CH-3012, Switzerland
I Safa Columbia University, New York, New York 10027, USA
G Scanavini Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
D W Schmitz University of Chicago, Chicago, Illinois 60637, USA
A Schukraft Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
W Seligman Columbia University, New York, New York 10027, USA
M H Shaevitz Columbia University, New York, New York 10027, USA
R Sharankova Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
J Shi University of Cambridge, Cambridge CB3 0HE, United Kingdom
E L Snider Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
M Soderberg Syracuse University, Syracuse, New York 13244, USA
S Söldner-Rembold The University of Manchester, Manchester M13 9PL, United Kingdom
J Spitz University of Michigan, Ann Arbor, Michigan 48109, USA
M Stancari Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
J St John Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
T Strauss Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
A M Szelc University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
W Tang University of Tennessee, Knoxville, Tennessee 37996, USA
N Taniuchi University of Cambridge, Cambridge CB3 0HE, United Kingdom
K Terao SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
C Thorpe Lancaster University, Lancaster LA1 4YW, United Kingdom The University of Manchester, Manchester M13 9PL, United Kingdom
D Torbunov Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
D Totani University of California, Santa Barbara, California 93106, USA
M Toups Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
Y-T Tsai SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
J Tyler Kansas State University (KSU), Manhattan, Kansas 66506, USA
M A Uchida University of Cambridge, Cambridge CB3 0HE, United Kingdom
T Usher SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
B Viren Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
M Weber Universität Bern, Bern CH-3012, Switzerland
H Wei Louisiana State University, Baton Rouge, Louisiana 70803, USA
A J White University of Chicago, Chicago, Illinois 60637, USA
S Wolbers Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
T Wongjirad Tufts University, Medford, Massachusetts 02155, USA
M Wospakrik Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
K Wresilo University of Cambridge, Cambridge CB3 0HE, United Kingdom
W Wu University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
E Yandel University of California, Santa Barbara, California 93106, USA
T Yang Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
L E Yates Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
H W Yu Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
G P Zeller Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
J Zennamo Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
C Zhang Brookhaven National Laboratory (BNL), Upton, New York 11973, USA

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Current status of GABA receptor subtypes in analgesia

Gamma-aminobutyric acid (GABA), a non-protein-producing amino acid synthesized from the excitatory amino acid glutamate via the enzyme glutamic acid decarboxylase, is extensively found in microorganisms, plants and vertebrates, and is abundantly expressed in the spinal cord and brain. It is the major inhibitory neurotransmitter in the mammalian nervous system. GABA plays crucial roles in the regulation of synaptic transmission, the promotion of neuronal development and relaxation, and the prevention of insomnia and depression. As the major inhibitory neurotransmitter, GABA plays pivotal roles in the regulation of pain sensation, which is initiated by the activation of peripheral nociceptors and transmitted to the spinal cord and brain along nerves. GABA exerts these roles by directly acting on three types of receptors: ionotropic GABAA and GABAC receptors and G protein-coupled GABAB receptor. The chloride-permeable ion channel receptors GABAA and GABAC mediate fast neurotransmission, while the metabotropic GABAB receptor mediates slow effect. Different GABA receptors regulate pain sensation via different signaling pathways. Here we highlight recent updates on the involvement of specific GABA receptors and their subtypes in the process of pain sensation. Further understanding of different GABA receptors and signaling pathways in pain sensation will benefit the development of novel analgesics for pain management by targeting specific GABA receptor subtypes and signaling pathways.

Discriminating minimal residual disease status in multiple myeloma based on MRI: utility of radiomics and comparison of machine-learning methods

AIM

To explore the possibility of discriminating minimal residual disease (MRD) status in multiple myeloma (MM) based on magnetic resonance imaging (MRI) and identify optimal machine-learning methods to optimise the clinical treatment regimen.

MATERIALS AND METHODS

A total of 83 patients were analysed retrospectively. They were divided randomly into training and validation cohorts. The regions of interest were segmented and radiomics features were extracted and analysed on two sequences, including T1-weighted imaging (WI) and fat saturated (FS)-T2WI, and then radiomics models were built in the training cohort and evaluated in the validation cohort. Clinical characteristics were calculated to build a traditional model. A combined model was also built using the clinical characteristics and radiomics features. Classification accuracy was assessed using area under the curve (AUC) and F1 score.

RESULTS

In the training cohort, only the bone marrow (BM) infiltrate ratio (p=0.005) was retained after univariate and multivariable logistic regression analysis. In T1WI, the linear support vector machine (SVM) achieved the best performance compared to other classifiers, with AUCs of 0.811 and 0.708 and F1 scores of 0.792 and 0.696 in the training and validation cohorts, respectively. Similarly, in FS-T2WI sequence, linear SVM achieved the best performance with AUCs of 0.833 and 0.800 and F1 score of 0.833 and 0.800. The combined model constructed by the FS-T2WI-linear SVM and BM infiltrate ratio outperformed the traditional model (p=0.050 and 0.012, Delong test), but showed no significant difference compared with the radiomics model (p=0.798 and 0.855).

CONCLUSION

The linear SVM-based machine-learning method can offer a non-invasive tool for discriminating MRD status in MM.

First Double-Differential Measurement of Kinematic Imbalance in Neutrino Interactions with the MicroBooNE Detector

We report the first measurement of flux-integrated double-differential quasielasticlike neutrino-argon cross sections, which have been made using the Booster Neutrino Beam and the MicroBooNE detector at Fermi National Accelerator Laboratory. The data are presented as a function of kinematic imbalance variables which are sensitive to nuclear ground-state distributions and hadronic reinteraction processes. We find that the measured cross sections in different phase-space regions are sensitive to different nuclear effects. Therefore, they enable the impact of specific nuclear effects on the neutrino-nucleus interaction to be isolated more completely than was possible using previous single-differential cross section measurements. Our results provide precision data to help test and improve neutrino-nucleus interaction models. They further support ongoing neutrino-oscillation studies by establishing phase-space regions where precise reaction modeling has already been achieved.

Final Measurement of the ^{235}U Antineutrino Energy Spectrum with the PROSPECT-I Detector at HFIR

This Letter reports one of the most precise measurements to date of the antineutrino spectrum from a purely ^{235}U-fueled reactor, made with the final dataset from the PROSPECT-I detector at the High Flux Isotope Reactor. By extracting information from previously unused detector segments, this analysis effectively doubles the statistics of the previous PROSPECT measurement. The reconstructed energy spectrum is unfolded into antineutrino energy and compared with both the Huber-Mueller model and a spectrum from a commercial reactor burning multiple fuel isotopes. A local excess over the model is observed in the 5-7 MeV energy region. Comparison of the PROSPECT results with those from commercial reactors provides new constraints on the origin of this excess, disfavoring at 2.0 and 3.7 standard deviations the hypotheses that antineutrinos from ^{235}U are solely responsible and noncontributors to the excess observed at commercial reactors, respectively.

Investigation of preclinical pharmacokinetics of N-demethylsinomenine, a potential novel analgesic candidate, using an UPLC-MS/MS quantification method

N- Demethylsinomenine (NDSM), the in vivo demethylated metabolite of sinomenine, has exhibited antinociceptive efficacy against various pain models and may become a novel drug candidate for pain management. However, no reported analytical method for quantification of N- Demethylsinomenine in a biological matrix is currently available, and the pharmacokinetic properties of N- Demethylsinomenine are unknown. In the present study, an ultra-high performance liquid chromatography with tandem mass spectrometry (UPLC-MS/MS) method for quantification of N- Demethylsinomenine in rat plasma was developed and utilized to examine the preclinical pharmacokinetic profiles of N- Demethylsinomenine. The liquid-liquid extraction using ethyl acetate as the extractant was selected to treat rat plasma samples. The mixture of 25% aqueous phase (0.35% acetic acid-10 mM ammonium acetate buffer) and 75% organic phase (acetonitrile) was chosen as the mobile phases flowing on a ZORBAX C18 column to perform the chromatographic separation. After a 6-min rapid elution, NDSM and its internal standard (IS), metronidazole, were separated successfully. The ion pairs of 316/239 and 172/128 were captured for detecting N- Demethylsinomenine and IS, respectively, using multiple reaction monitoring (MRM) under a positive electrospray ionization (ESI) mode in this mass spectrometry analysis. The standard curve met linear requirements within the concentration range from 3 to 1000 ng/mL, and the lower limit of quantification (LLOQ) was 3 ng/mL. The method was evaluated regarding precision, accuracy, recovery, matrix effect, and stability, and all the results met the criteria presented in the guidelines for validation of biological analysis method. Then the pharmacokinetic profiles of N- Demethylsinomenine in rat plasma were characterized using this validated UPLC-MS/MS method. N- Demethylsinomenine exhibited the feature of linear pharmacokinetics after intravenous (i.v.) or intragastric (i.g.) administration in rats. After i. v. bolus at three dosage levels (0.5, 1, and 2 mg/kg), N- Demethylsinomenine showed the profiles of rapid elimination with mean half-life (T_1/2Z) of 1.55-1.73 h, and extensive tissue distribution with volume of distribution (V_Z) of 5.62-8.07 L/kg. After i. g. administration at three dosage levels (10, 20, and 40 mg/kg), N- Demethylsinomenine showed the consistent peak time (T_max) of 3 h and the mean absolute bioavailability of N- Demethylsinomenine was 30.46%. These pharmacokinetics findings will aid in future drug development decisions of N- Demethylsinomenine as a potential candidate for pain analgesia.

First Measurement of Quasielastic Λ Baryon Production in Muon Antineutrino Interactions in the MicroBooNE Detector

We present the first measurement of the cross section of Cabibbo-suppressed Λ baryon production, using data collected with the MicroBooNE detector when exposed to the neutrinos from the main injector beam at the Fermi National Accelerator Laboratory. The data analyzed correspond to 2.2×10^{20} protons on target running in neutrino mode, and 4.9×10^{20} protons on target running in anti-neutrino mode. An automated selection is combined with hand scanning, with the former identifying five candidate Λ production events when the signal was unblinded, consistent with the GENIE prediction of 5.3±1.1 events. Several scanners were employed, selecting between three and five events, compared with a prediction from a blinded Monte Carlo simulation study of 3.7±1.0 events. Restricting the phase space to only include Λ baryons that decay above MicroBooNE's detection thresholds, we obtain a flux averaged cross section of 2.0_{-1.7}^{+2.2}×10^{-40}  cm^{2}/Ar, where statistical and systematic uncertainties are combined.

ICARUS at the Fermilab Short-Baseline Neutrino program: initial operation

The ICARUS collaboration employed the 760-ton T600 detector in a successful 3-year physics run at the underground LNGS laboratory, performing a sensitive search for LSND-like anomalous ν e appearance in the CERN Neutrino to Gran Sasso beam, which contributed to the constraints on the allowed neutrino oscillation parameters to a narrow region around 1 eV2 . After a significant overhaul at CERN, the T600 detector has been installed at Fermilab. In 2020 the cryogenic commissioning began with detector cool down, liquid argon filling and recirculation. ICARUS then started its operations collecting the first neutrino events from the booster neutrino beam (BNB) and the Neutrinos at the Main Injector (NuMI) beam off-axis, which were used to test the ICARUS event selection, reconstruction and analysis algorithms. ICARUS successfully completed its commissioning phase in June 2022. The first goal of the ICARUS data taking will be a study to either confirm or refute the claim by Neutrino-4 short-baseline reactor experiment. ICARUS will also perform measurement of neutrino cross sections with the NuMI beam and several Beyond Standard Model searches. After the first year of operations, ICARUS will search for evidence of sterile neutrinos jointly with the Short-Baseline Near Detector, within the Short-Baseline Neutrino program. In this paper, the main activities carried out during the overhauling and installation phases are highlighted. Preliminary technical results from the ICARUS commissioning data with the BNB and NuMI beams are presented both in terms of performance of all ICARUS subsystems and of capability to select and reconstruct neutrino events.

Improved Measurement of the Evolution of the Reactor Antineutrino Flux and Spectrum at Daya Bay

Reactor neutrino experiments play a crucial role in advancing our knowledge of neutrinos. In this Letter, the evolution of the flux and spectrum as a function of the reactor isotopic content is reported in terms of the inverse-beta-decay yield at Daya Bay with 1958 days of data and improved systematic uncertainties. These measurements are compared with two signature model predictions: the Huber-Mueller model based on the conversion method and the SM2018 model based on the summation method. The measured average flux and spectrum, as well as the flux evolution with the ^{239}Pu isotopic fraction, are inconsistent with the predictions of the Huber-Mueller model. In contrast, the SM2018 model is shown to agree with the average flux and its evolution but fails to describe the energy spectrum. Altering the predicted inverse-beta-decay spectrum from ^{239}Pu fission does not improve the agreement with the measurement for either model. The models can be brought into better agreement with the measurements if either the predicted spectrum due to ^{235}U fission is changed or the predicted ^{235}U, ^{238}U, ^{239}Pu, and ^{241}Pu spectra are changed in equal measure.

Modifiable predictors of type 2 diabetes mellitus and roles of insulin resistance and β-cell function over a 6-year study and 30-year follow-up

PURPOSE

This study aimed to examine the modifiable predictors of T2DM and the roles of insulin resistance (IR) and β-cell function over a 6-year study and 30-year follow-up.

METHODS

A total of 462 non-diabetic participants, 282 with impaired glucose tolerance (IGT), and 180 with normal glucose tolerance (NGT) were enrolled in this analysis. The Matsuda IR index and area under the curve of insulin-to-glucose ratio (AUCI/G-R) were used as IR and β-cell function indices in the analysis.

RESULTS

In all participants, multivariable analysis showed that BMI, glucose status, Matsuda IR index and systolic blood pressure (SBP) at baseline were independently associated with an increased risk of T2DM over 30 years, whereas lifestyle intervention and AUCI/G-R were inversely associated with this risk. The predictive effect of the Matsuda IR index and AUCI/G-R in participants with IGT was consistent with the results of all participants, whereas in those with NGT, only the Matsuda IR index, not the AUCI/G-R, predicted the development of T2DM (HR = 1.42, 95% CI 1.07-1.89 vs HR = 1.09, 95% CI 0.76-1.56). The predictive effect of the Matsuda IR index on T2DM existed even in participants with BMI < 25 (p = 0.049).

CONCLUSION

The modifiable predictors of T2DM in Chinese adults were high BMI, hypertension, mild hyperglycaemia, IR, and β-cell dysfunction. Both IR and β-cell function contributed to the development of T2DM in the long term; however, IR remains the initial and long-standing key risk factor for T2DM.

Precision Measurement of Reactor Antineutrino Oscillation at Kilometer-Scale Baselines by Daya Bay

We present a new determination of the smallest neutrino mixing angle θ_{13} and the mass-squared difference Δm_{32}^{2} using a final sample of 5.55×10^{6} inverse beta-decay (IBD) candidates with the final-state neutron captured on gadolinium. This sample is selected from the complete dataset obtained by the Daya Bay reactor neutrino experiment in 3158 days of operation. Compared to the previous Daya Bay results, selection of IBD candidates has been optimized, energy calibration refined, and treatment of backgrounds further improved. The resulting oscillation parameters are sin^{2}2θ_{13}=0.0851±0.0024, Δm_{32}^{2}=(2.466±0.060)×10^{-3}  eV^{2} for the normal mass ordering or Δm_{32}^{2}=-(2.571±0.060)×10^{-3}  eV^{2} for the inverted mass ordering.

Juglans mandshurica Maximowicz as a traditional medicine: review of its phytochemistry and pharmacological activity in East Asia

OBJECTIVES

The conducted search reveals that Juglans mandshurica Maximowicz, called Manchuria walnuts, had many local uses that can be categorized into cancer, dermatosis and acesodyne.

KEY FINDINGS

Various metabolites including diarylheptanoids, naphthoquinones, and flavonoids (also their glycosides) were reported as bioactive metabolites. The isolated metabolites and extracts from J. mandshurica showed different biological activity including cytotoxicity, anti-inflammation, antimelanotic, anticomplement, anti-HIV, antimicrobial and anti-obesity activity.

SUMMARY

It is indicated that this review will add value to more scientific research on J. mandshurica and enhance the increased interest in the sustainable commercialization of J. mandshurica. It also leads to the validation of unverified ethnobotanical claims. Future studies on J. mandshurica would be focused to establish the links between the pharmacological activity, bioactive metabolites, and traditional uses.

First Constraints on Light Sterile Neutrino Oscillations from Combined Appearance and Disappearance Searches with the MicroBooNE Detector

We present a search for eV-scale sterile neutrino oscillations in the MicroBooNE liquid argon detector, simultaneously considering all possible appearance and disappearance effects within the 3+1 active-to-sterile neutrino oscillation framework. We analyze the neutrino candidate events for the recent measurements of charged-current ν_{e} and ν_{μ} interactions in the MicroBooNE detector, using data corresponding to an exposure of 6.37×10^{20} protons on target from the Fermilab booster neutrino beam. We observe no evidence of light sterile neutrino oscillations and derive exclusion contours at the 95% confidence level in the plane of the mass-squared splitting Δm_{41}^{2} and the sterile neutrino mixing angles θ_{μe} and θ_{ee}, excluding part of the parameter space allowed by experimental anomalies. Cancellation of ν_{e} appearance and ν_{e} disappearance effects due to the full 3+1 treatment of the analysis leads to a degeneracy when determining the oscillation parameters, which is discussed in this Letter and will be addressed by future analyses.

The J-shape Association between Total Bilirubin and Stroke in Older Patients with Obstructive Sleep Apnea Syndrome: A Multicenter Study

OBJECTIVES

To explore the relationship between total bilirubin (TBil) and stroke risk in older patients with obstructive sleep apnea syndrome (OSAS).

METHODS

A total of 1,007 patients with OSAS without stroke history aged ≥ 60 years and with complete serum TBil records were enrolled in this study. The median follow-up was 42 months. Participants were divided into four groups based on the quartile of the baseline serum TBil concentration. Multivariate Cox proportional hazards analysis and restricted cubic spline (RCS) were used to investigate the association of TBil with the incidence of new-onset stroke.

RESULTS

The PRIMARY part: the third quantile TBil level group had the lowest prevalence of stroke among the four groups. The RCS functions depicted a J-type curve relationship between TBil (3.3-33.3 µmol/L) and stroke (nonlinear P < 0.05). When the TBil level was in the range of 3.3 to 11.5 µmol/L, the possible protective influence of bilirubin against stroke in patients with OSAS enhanced with an increasing TBil level. However, when the TBil level exceeded 11.5 µmol/L and gradually increased, the effect of TBil on stroke risk became more and more pronounced. The SECONDARY part: for every 1 µmol/L increase in TBil levels in the range of 11.5 to 33.3 µmol/L, the risk of stroke in patients with OSAS increased by 16.2% (P < 0.001). In addition, there was a higher risk in women with OSAS (hazard ratio (HR)=1.292, 95% confidence interval (95%CI): 1.093-1.528; P = 0.003). Moreover, an increased TBil level alone was significantly associated with stroke in subjects aged < 75 years (HR: 1.190, 95%CI: 1.069-1.324), patients with mild-to-moderate OSAS (HR: 1.215, 95%CI: 1.083-1.364), and individuals without atrial fibrillation (AF) (HR: 1.179, 95%CI: 1.083-1.285) within a TBil level in the range of 11.5 to 33.3 µmol/L.

CONCLUSIONS

Both lower and higher bilirubin levels may increase the risk of stroke in older persons with OSAS, and there was a J-type dose-response relationship. The risk of stroke was lowest when the TBil level was approximately 11.5 µmol/L.

Investigation of the protective mechanism of leonurine against acute myocardial ischemia by an integrated metabolomics and network pharmacology strategy

Background

Leonurus japonicus Houtt has an obvious efficacy on cardiovascular diseases. As the most representative component in the herb, leonurine has attracted increasing attention for its potential in myocardial ischemia. However, its protective mechanism against myocardial ischemia remains incompletely elucidated.

Objectives

The present study aimed to reveal the potential mechanism of leonurine in acute myocardial ischemia using a strategy combining metabolomics and network pharmacology.

Methods

First, a metabolomics method was proposed to identify the differential metabolites of plasma in rats. Then, network pharmacology was performed to screen candidate targets of leonurine against acute myocardial ischemia. A compound-reaction-enzyme-gene network was thus constructed with the differential metabolites and targets. Finally, molecular docking was carried out to predict the binding capability of leonurine with key targets.

Results

A total of 32 differential metabolites were identified in rat plasma, and 16 hub genes were detected through network pharmacology. According to the results of compound-reaction-enzyme-gene network and molecular docking, what was screened included six key targets (GSR, CYP2C9, BCHE, GSTP1, TGM2, and PLA2G2A) and seven differential metabolites (glycerylphosphorylcholine, lysophosphatidylcholine, choline phosphate, linoleic acid, 13-HpODE, tryptophan and glutamate) with four important metabolic pathways involved: glycerophospholopid metabolism, linoleic acid metabolism, tryptophan metabolism and glutamate metabolism. Among them, glycerophospholipid and tryptophan metabolism were shown to be important, since the regulation of leonurine on these two pathways was also observed in our previous metabolomics study conducted on clinical hyperlipidemia patients.

Conclusion

This is the first study of its kind to reveal the underlying mechanism of leonurine against acute myocardial ischemia through a strategy combining metabolomics and network pharmacology, which provides a valuable reference for the research on its future application.

First Measurement of High-Energy Reactor Antineutrinos at Daya Bay

This Letter reports the first measurement of high-energy reactor antineutrinos at Daya Bay, with nearly 9000 inverse beta decay candidates in the prompt energy region of 8-12 MeV observed over 1958 days of data collection. A multivariate analysis is used to separate 2500 signal events from background statistically. The hypothesis of no reactor antineutrinos with neutrino energy above 10 MeV is rejected with a significance of 6.2 standard deviations. A 29% antineutrino flux deficit in the prompt energy region of 8-11 MeV is observed compared to a recent model prediction. We provide the unfolded antineutrino spectrum above 7 MeV as a data-based reference for other experiments. This result provides the first direct observation of the production of antineutrinos from several high-Q_{β} isotopes in commercial reactors.

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties.

Search for an Excess of Electron Neutrino Interactions in MicroBooNE Using Multiple Final-State Topologies

We present a measurement of ν_{e} interactions from the Fermilab Booster Neutrino Beam using the MicroBooNE liquid argon time projection chamber to address the nature of the excess of low energy interactions observed by the MiniBooNE Collaboration. Three independent ν_{e} searches are performed across multiple single electron final states, including an exclusive search for two-body scattering events with a single proton, a semi-inclusive search for pionless events, and a fully inclusive search for events containing all hadronic final states. With differing signal topologies, statistics, backgrounds, reconstruction algorithms, and analysis approaches, the results are found to be either consistent with or modestly lower than the nominal ν_{e} rate expectations from the Booster Neutrino Beam and no excess of ν_{e} events is observed.

[The relationship between insulin resistance and risk of long-term mortality in people without diabetes: a 30-year follow-up of the Daqing Diabetes Study]

Objective: To determine whether insulin resistance is associated with all-cause mortality in subjects without diabetes. Methods: A total of 505 participants without diabetes, 198 with normal glucose tolerance (NGT) and 307 with impaired glucose tolerance (IGT), were recruited from the Daqing Diabetes Study. The participants were followed up for 30 years. They were stratified into three groups (tertiles) according to baseline homeostasis model assessment of insulin resistance(HOMA-IR) levels, as the HOMA-IR 0, the HOMA-IR 1 and the HOMA-IR 2 groups, to assess the predictive effect of insulin resistance on risk of all-cause mortality. Results: During the 30-year follow-up, 52, 56 and 78 participants died across the three HOMA-IR groups, respectively. The corresponding mortality per 1 000 person-years (95%CI) were 12.12 (9.56-15.01), 13.10 (10.46-16.03) and 19.91 (16.73-23.15), respectively. Participants in the HOMA-IR 2 group had a significantly higher risk of death than those in the HOMA-IR 0 group after adjustment of age, sex and smoking status (HR=1.97,95%CI 1.38-2.81, P<0.001). Cox analyses showed that a one standard deviation increase in HOMA-IR was associated with a 22% increase in the mortality after adjustment of potential confounders (HR=1.22, 95%CI 1.08-1.39, P=0.002). Conclusions: Insulin resistance is associated with increased risk of all-cause death in Chinese people without diabetes, suggesting that improving insulin resistance could be beneficial for people without diabetic in reducing risk of long-term all-cause mortality.

First Measurement of Energy-Dependent Inclusive Muon Neutrino Charged-Current Cross Sections on Argon with the MicroBooNE Detector

We report a measurement of the energy-dependent total charged-current cross section σ(E_{ν}) for inclusive muon neutrinos scattering on argon, as well as measurements of flux-averaged differential cross sections as a function of muon energy and hadronic energy transfer (ν). Data corresponding to 5.3×10^{19} protons on target of exposure were collected using the MicroBooNE liquid argon time projection chamber located in the Fermilab booster neutrino beam with a mean neutrino energy of approximately 0.8 GeV. The mapping between the true neutrino energy E_{ν} and reconstructed neutrino energy E_{ν}^{rec} and between the energy transfer ν and reconstructed hadronic energy E_{had}^{rec} are validated by comparing the data and Monte Carlo (MC) predictions. In particular, the modeling of the missing hadronic energy and its associated uncertainties are verified by a new method that compares the E_{had}^{rec} distributions between data and a MC prediction after constraining the reconstructed muon kinematic distributions, energy, and polar angle to those of data. The success of this validation gives confidence that the missing energy in the MicroBooNE detector is well modeled and underpins first-time measurements of both the total cross section σ(E_{ν}) and the differential cross section dσ/dν on argon.

Brain charts for the human lifespan

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Search for Neutrino-Induced Neutral-Current Δ Radiative Decay in MicroBooNE and a First Test of the MiniBooNE Low Energy Excess under a Single-Photon Hypothesis

We report results from a search for neutrino-induced neutral current (NC) resonant Δ(1232) baryon production followed by Δ radiative decay, with a ⟨0.8⟩  GeV neutrino beam. Data corresponding to MicroBooNE's first three years of operations (6.80×10^{20} protons on target) are used to select single-photon events with one or zero protons and without charged leptons in the final state (1γ1p and 1γ0p, respectively). The background is constrained via an in situ high-purity measurement of NC π^{0} events, made possible via dedicated 2γ1p and 2γ0p selections. A total of 16 and 153 events are observed for the 1γ1p and 1γ0p selections, respectively, compared to a constrained background prediction of 20.5±3.65(syst) and 145.1±13.8(syst) events. The data lead to a bound on an anomalous enhancement of the normalization of NC Δ radiative decay of less than 2.3 times the predicted nominal rate for this process at the 90% confidence level (C.L.). The measurement disfavors a candidate photon interpretation of the MiniBooNE low-energy excess as a factor of 3.18 times the nominal NC Δ radiative decay rate at the 94.8% C.L., in favor of the nominal prediction, and represents a greater than 50-fold improvement over the world's best limit on single-photon production in NC interactions in the sub-GeV neutrino energy range.

Joint Determination of Reactor Antineutrino Spectra from ^{235}U and ^{239}Pu Fission by Daya Bay and PROSPECT

A joint determination of the reactor antineutrino spectra resulting from the fission of ^{235}U and ^{239}Pu has been carried out by the Daya Bay and PROSPECT Collaborations. This Letter reports the level of consistency of ^{235}U spectrum measurements from the two experiments and presents new results from a joint analysis of both data sets. The measurements are found to be consistent. The combined analysis reduces the degeneracy between the dominant ^{235}U and ^{239}Pu isotopes and improves the uncertainty of the ^{235}U spectral shape to about 3%. The ^{235}U and ^{239}Pu antineutrino energy spectra are unfolded from the jointly deconvolved reactor spectra using the Wiener-SVD unfolding method, providing a data-based reference for other reactor antineutrino experiments and other applications. This is the first measurement of the ^{235}U and ^{239}Pu spectra based on the combination of experiments at low- and highly enriched uranium reactors.

Joint Measurement of the ^{235}U Antineutrino Spectrum by PROSPECT and STEREO

The PROSPECT and STEREO collaborations present a combined measurement of the pure ^{235}U antineutrino spectrum, without site specific corrections or detector-dependent effects. The spectral measurements of the two highest precision experiments at research reactors are found to be compatible with χ^{2}/ndf=24.1/21, allowing a joint unfolding of the prompt energy measurements into antineutrino energy. This ν[over ¯]_{e} energy spectrum is provided to the community, and an excess of events relative to the Huber model is found in the 5-6 MeV region. When a Gaussian bump is fitted to the excess, the data-model χ^{2} value is improved, corresponding to a 2.4σ significance.

[Clinical value of tumor-associated autoantibodies in diagnosis of early non-small cell lung cancer]

Objective: To investigate the auxiliary diagnostic value of seven tumor-associated autoantibodies (AABs) P53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE in early non-small cell lung cancer (NSCLC). Methods: The case-control study enrolled 195 patients with early NSCLC [71 males and 124 females, aged (55.70±11.78) years old], 114 patients with benign lung disease [44 males and 70 females, aged (52.85±12.31) years old] and 100 healthy subjects [39 males and 61 females, aged (53.62±9.97) years old] from the First Affiliate Hospital of Nanjing Medical University from June 2020 to December 2020. AABs were detected by enzyme-linked-immunosorbent serologic assay (ELISA), and carcinoembryonic antigen (CEA),cytokeratin 19-fragments (CYFRA21-1) and neuron specific enolase (NSE) were detected by electrochemiluminescence. The levels of AABs,CEA,CYFRA21-1 and NSE in the 3 groups were compared. Patients with benign lung diseases and healthy subjects were combined into the control group, and the positive rate of each indicator in the NSCLC group and the control group was compared. The diagnostic efficacy of single and combined tests for NSCLC were obtained using receiver operating characteristic (ROC) curves. Besides, the relationship between the levels of AABs, CEA, CYFRA21-1 and NSE and their clinicopathological features and preoperative imaging parameters in NSCLC patients was assessed. Results: The levels of SOX2 [0.70 (0.10, 2.40) U/mL] and GBU4-5 [1.30 (0.30, 8.90) U/mL] in NSCLC group were higher than those in benign disease group [SOX2: 0.50 (0.10, 1.60) U/mL, GBU4-5: 0.80 (0.10, 2.30) U/mL, Z values were 27.258 and 45.797; P values were all<0.05] and health control group [SOX2: 0.45 (0.10, 1.08) U/mL, GBU4-5: 0.75 (0.20, 1.78) U/mL, Z values were 32.551 and 40.456; P values were all<0.05], and there was no significant difference between benign disease group and health control group (Z values were 5.293 and 5.340, P values were all>0.05). The levels of CEA [1.75 (1.08, 2.72) U/mL] and CYFRA21-1 [1.81 (1.41, 2.36) U/mL] in NSCLC group were higher than those in healthy control group [CEA: 1.22 (0.68, 1.81) U/mL, CYFRA21-1: 1.43 (1.14, 1.74) U/mL, Z values were 64.100 and 37.597; P values were all<0.05], but there was no significant difference between NSCLC group and benign group [CEA: 1.74 (1.01, 2.51) U/mL, CYFRA21-1: 1.82 (1.45, 2.46) U/mL, Z values were 7.275 and 10.621; P values were all>0.05]. The positive rates of P53, SOX2, GAGE7, GBU4-5 and CEA in NSCLC group were higher than those in the control group [P53: 10.3% vs 0.9%, SOX2: 11.3% vs 2.3%, GAGE7: 11.3% vs 0.5%, GBU4-5: 30.1% vs 5.6%, CEA: 9.7% vs 0.9%, χ² values were 17.420, 13.242, 22.485, 43.211, 16.255, respectively; P values were all<0.05]. The diagnostic efficiency of the combined detection of seven AABs was better than that of single detection. Seven AABs combined with CEA [area under curve (AUC): 0.732, sensitivity: 64.10%] and with CYFRA21-1 (AUC: 0.737, sensitivity: 58.97%) greatly improved the diagnostic efficiency and sensitivity of CEA (AUC: 0.583, sensitivity: 50.77%) and CYFRA21-1 (AUC: 0.552, sensitivity: 44.10%). The levels of SOX2 and CEA in NSCLC patients were correlated with the degree of tumor invasion (H values were 6.436 and 14.071; P values were all<0.05); the levels of GAGE7 and CEA were correlated with the nodule density (H values were 7.643 and 12.268; P values were all<0.05); and the levels of SOX2, GAGE7, CEA and CYFRA21-1 were all correlated with the nodule size (H values were 10.837, 11.528, 31.835, 20.338; P values were all<0.05). Conclusion: The detection of AABs combined with CEA and CYFRA21-1 is helpful for the early auxiliary diagnosis of NSCLC, and plays an important role in prevention and screening for early lung cancer.

Search for a Higgs Portal Scalar Decaying to Electron-Positron Pairs in the MicroBooNE Detector

We present a search for the decays of a neutral scalar boson produced by kaons decaying at rest, in the context of the Higgs portal model, using the MicroBooNE detector. We analyze data triggered in time with the Fermilab NuMI neutrino beam spill, with an exposure of 1.93×10^{20} protons on target. We look for monoenergetic scalars that come from the direction of the NuMI hadron absorber, at a distance of 100 m from the detector, and decay to electron-positron pairs. We observe one candidate event, with a standard model background prediction of 1.9±0.8. We set an upper limit on the scalar-Higgs mixing angle of θ<(3.3-4.6)×10^{-4} at the 95% confidence level for scalar boson masses in the range (100-200)  MeV/c^{2}. We exclude, at the 95% confidence level, the remaining model parameters required to explain the central value of a possible excess of K_{L}^{0}→π^{0}νν[over ¯] decays reported by the KOTO collaboration. We also provide a model-independent limit on a new boson X produced in K→πX decays and decaying to e^{+}e^{-}.

Cosmic Ray Background Removal With Deep Neural Networks in SBND

In liquid argon time projection chambers exposed to neutrino beams and running on or near surface levels, cosmic muons, and other cosmic particles are incident on the detectors while a single neutrino-induced event is being recorded. In practice, this means that data from surface liquid argon time projection chambers will be dominated by cosmic particles, both as a source of event triggers and as the majority of the particle count in true neutrino-triggered events. In this work, we demonstrate a novel application of deep learning techniques to remove these background particles by applying deep learning on full detector images from the SBND detector, the near detector in the Fermilab Short-Baseline Neutrino Program. We use this technique to identify, on a pixel-by-pixel level, whether recorded activity originated from cosmic particles or neutrino interactions.

[Risk factors and risk model of lymph node metastasis in early gastric cancer]

To investigate the risk factors of lymph node metastasis in early gastric cancer (EGC) and to develop a risk model for the presence of lymph node metastasis. A total of 172 EGC patients, with a median age of 62(52, 68) years, who underwent gastric cancer resection in the First Affiliated Hospital of Nanjing Medical University from January 2017 to June 2019 were selected. Clinical data of the patients were collected through the case system. Logistic regression analysis was used to determine the variables significantly related to lymph node metastasis. ROC curve and calibration curve were used to evaluate the risk model. The results showed that the lymph node metastasis rate of 172 EGC patients was 19.19% (33/172). Tumor size, depth of invasion, degree of differentiation and vascular tumor thrombus were associated with lymph node metastasis (P<0.05), but age ≥ 60 years (OR=5.556, 95%CI: 1.757-17.569, P=0.004), invasion depth (OR=4.218,95%CI:1.418-12.548, P=0.010) and vascular cancer embolus (OR=13.878,95%CI:4.081-47.196,P<0.001) were independent risk factors for lymph node metastasis of EGC. The consistency index of the risk model based on the above risk factors was 0.8835 (95%CI: 0.818 8-0.948 2). The calibration curve shows that the risk assessment model is in good agreement with the actual results, indicating that the model has high accuracy and discrimination.The most common site of metastasis was group 3, followed by group 4. Therefore, patients over 60 years old with submucosal invasion and vascular tumor thrombus may have a higher risk of lymph node metastasis.

Gamma-Ray Observation of the Cygnus Region in the 100-TeV Energy Region

We report observations of gamma-ray emissions with energies in the 100-TeV energy region from the Cygnus region in our Galaxy. Two sources are significantly detected in the directions of the Cygnus OB1 and OB2 associations. Based on their positional coincidences, we associate one with a pulsar PSR J2032+4127 and the other mainly with a pulsar wind nebula PWN G75.2+0.1, with the pulsar moving away from its original birthplace situated around the centroid of the observed gamma-ray emission. This work would stimulate further studies of particle acceleration mechanisms at these gamma-ray sources.

Imaging the Néel vector switching in the monolayer antiferromagnet MnPSe3 with strain-controlled Ising order

Antiferromagnets are interesting materials for spintronics because of their faster dynamics and robustness against perturbations from magnetic fields. Control of the antiferromagnetic order constitutes an important step towards applications, but has been limited to bulk materials so far. Here, using spatially resolved second-harmonic generation, we show direct evidence of long-range antiferromagnetic order and Ising-type Néel vector switching in monolayer MnPSe₃ with large XY anisotropy. In additional to thermally induced switching, uniaxial strain can rotate the Néel vector, aligning it to a general in-plane direction irrespective of the crystal axes. A change of the universality class of the phase transition in the XY model under uniaxial strain causes this emergence of strain-controlled Ising order in the XY magnet MnPSe₃. Our discovery is a further ingredient for compact antiferromagnetic spintronic devices in the two-dimensional limit.

[The value of NLR, FIB, CEA and CA19-9 in colorectal cancer]

Objective: To investigate the clinical value of neutrophil-lymphocyte ratio (NLR), fibrinogen (FIB), carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) in the diagnosis and prognosis of colorectal cancer. Methods: A case-control study design was used to select 155 patients with colorectal cancer[98 males and 57 females, aged (63.12±13.99)years old], 90 patients with colorectal polyps[62 males and 28 females, aged (56.86±12.74)years old] and 150 healthy subjects[93 males and 57 females, aged (57.02±10.91)years old] from the First Affiliated Hospital of Nanjing Medical University from October 2017 to March 2018. Blood routine tests were detected by instrument method, FIB was detected by Clauss method, and CEA and CA19-9 were detected by electrochemiluminescence method. The levels of the NLR, FIB, CEA and CA19-9 in the 3 groups were compared. The diagnostic efficacy of NLR, FIB, CEA and CA19-9 of colorectal cancer was compared according to the ROC curve. The relationship between the level of NLR, FIB, CEA and CA19-9 and their clinicopathological features in colorectal cancer patients was assessed. According to the median levels of NLR, FIB, CEA and CA19-9, 112 follow-up of colorectal cancer patients could be divided into the high-value group and the low-value group. Kaplan-Meier, log-rank test and Cox regression analysis were used to analyze the relationship between the levels of the four indicators and the prognosis of colorectal cancer. Results: The levels of NLR, FIB, CEA and CA19-9 in colorectal cancer group were 2.11(1.52, 2.86), 3.21(2.58, 3.86)g/L, 3.93(2.27, 8.78)μg/L, 15.11(9.10, 25.73)U/ml. The levels of NLR, FIB, CEA and CA19-9 in colorectal polyp group were 1.74(1.39, 2.17), 2.54(2.26, 3.03)g/L, 1.99(1.18, 2.70)μg/L, 9.83(6.13, 15.68)U/ml. The levels of NLR, FIB, CEA and CA19-9 in healthy control group were 1.68(1.33, 2.28), 2.56(2.30, 2.82)g/L, 1.85(1.28, 2.59)μg/L, 10.03(6.86, 13.26)U/ml. The levels of NLR, FIB, CEA and CA19-9 in colorectal cancer group were significantly higher than those in colorectal polyp group (Z values were 3.568, 5.913, 6.880 and 4.022,P values were all<0.05) and healthy control group(Z values were 3.916, 7.381, 9.131 and 5.251,P values were all<0.05). The levels of NLR, FIB, CEA and CA19-9 in colorectal polyp group were not remarkably different from those in healthy control group (Z values were 0.217, 0.179, 0.320 and 0.061,P values were all>0.05). The diagnostic performance of CEA was the best in single test, followed by FIB, CA19-9 and NLR. The sensitivity of combined NLR+FIB+CEA or NLR+FIB+CEA+CA19-9 was the highest with 72.3%. NLR and FIB levels were associated with tumor sites (Z values were 3.587 and 7.089,P values were both<0.05). FIB and CEA levels were correlated with the depth of tumor invasion (Z values were 3.250 and 3.245, P values were both <0.05). NLR, FIB, CEA and CA19-9 levels were both associated with lymph node metastasis (Z values were 2.010, 3.276, 3.312 and 2.921, P values were all<0.05). The prognosis of patients in the high-value NLR, FIB, CEA and CA19-9 groups was significantly worse than that in the low-value group (χ² values were 5.744, 6.048, 4.389 and 6.942,P values were all<0.05).Cox multivariate regression analysis showed lymph node metastasis, NLR >2.15 and CA19-9 >15.47 U/ml are independent factors affecting the prognosis of colorectal cancer. Conclusion: NLR, FIB, CEA and CA19-9 can be applied in the auxiliary diagnosis and prognosis of colorectal cancer.

Prospects for beyond the Standard Model physics searches at the Deep Underground Neutrino Experiment: DUNE Collaboration

The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool for a variety of physics topics. The high-intensity proton beams provide a large neutrino flux, sampled by a near detector system consisting of a combination of capable precision detectors, and by the massive far detector system located deep underground. This configuration sets up DUNE as a machine for discovery, as it enables opportunities not only to perform precision neutrino measurements that may uncover deviations from the present three-flavor mixing paradigm, but also to discover new particles and unveil new interactions and symmetries beyond those predicted in the Standard Model (SM). Of the many potential beyond the Standard Model (BSM) topics DUNE will probe, this paper presents a selection of studies quantifying DUNE's sensitivities to sterile neutrino mixing, heavy neutral leptons, non-standard interactions, CPT symmetry violation, Lorentz invariance violation, neutrino trident production, dark matter from both beam induced and cosmogenic sources, baryon number violation, and other new physics topics that complement those at high-energy colliders and significantly extend the present reach.

Nonfuel Antineutrino Contributions in the High Flux Isotope Reactor

Reactor neutrino experiments have seen major improvements in precision in recent years. With the experimental uncertainties becoming lower than those from theory, carefully considering all sources of ν ¯ e is important when making theoretical predictions. One source of ν ¯ e that is often neglected arises from the irradiation of the nonfuel materials in reactors. The ν ¯ e rates and energies from these sources vary widely based on the reactor type, configuration, and sampling stage during the reactor cycle and have to be carefully considered for each experiment independently. In this article, we present a formalism for selecting the possible ν ¯ e sources arising from the neutron captures on reactor and target materials. We apply this formalism to the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory, the ν ¯ e source for the the Precision Reactor Oscillation and Spectrum Measurement (PROSPECT) experiment. Overall, we observe that the nonfuel ν ¯ e contributions from HFIR to PROSPECT amount to 1% above the inverse beta decay threshold with a maximum contribution of 9% in the 1.8-2.0 MeV range. Nonfuel contributions can be particularly high for research reactors like HFIR because of the choice of structural and reflector material in addition to the intentional irradiation of target material for isotope production. We show that typical commercial pressurized water reactors fueled with low-enriched uranium will have significantly smaller nonfuel ν ¯ e contribution.

First Measurement of Differential Charged Current Quasielasticlike ν_{μ}-Argon Scattering Cross Sections with the MicroBooNE Detector

We report on the first measurement of flux-integrated single differential cross sections for charged-current (CC) muon neutrino (ν_{μ}) scattering on argon with a muon and a proton in the final state, ^{40}Ar (ν_{μ},μp)X. The measurement was carried out using the Booster Neutrino Beam at Fermi National Accelerator Laboratory and the MicroBooNE liquid argon time projection chamber detector with an exposure of 4.59×10^{19} protons on target. Events are selected to enhance the contribution of CC quasielastic (CCQE) interactions. The data are reported in terms of a total cross section as well as single differential cross sections in final state muon and proton kinematics. We measure the integrated per-nucleus CCQE-like cross section (i.e., for interactions leading to a muon, one proton, and no pions above detection threshold) of (4.93±0.76_{stat}±1.29_{sys})×10^{-38}  cm^{2}, in good agreement with theoretical calculations. The single differential cross sections are also in overall good agreement with theoretical predictions, except at very forward muon scattering angles that correspond to low-momentum-transfer events.