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Cai C, Ma Y, Zhang L, An Z, Zhou E, Liu X, Li H, Li W, Li Z, Li G, Liu X, Zhang Y, Han R. Genome-wide methylation and transcriptome differential analysis of skeletal muscle in broilers with valgus-varus deformity. Br Poult Sci 2024:1-12. [PMID: 39504239 DOI: 10.1080/00071668.2024.2410368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Accepted: 09/03/2024] [Indexed: 11/08/2024]
Abstract
1. Valgus-varus deformity (VVD) is a disease that severely affects leg function in broilers and for which there is no effective control method current available. Although DNA methylation has an important impact on most physiological and pathological processes, its involvement in skeletal muscle growth and development in VVD broilers is unknown. In this study, genome-wide DNA methylation was analysed in VVD-affected and normal broilers using whole genome resulphite sequencing.2. The results showed that in the cytosine-phosphoric acid-guanine (CG) sequence environment there was a methylation rate of about 55% and 4,265 differentially methylated regions (DMRs) were found in the CG. Of these, 550 were located in the promoter, 547 in the exon region, and 1,718 in the intron region.3. All differentially methylated genes (DMGs) were analysed for enrichment of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The GO was enriched in pathways related to protein degradation such as proteasome complex, endopeptidase complex and extracellular region. The KEGG pathways were enriched in signalling pathways related to protein degradation and catabolism such as proteasome, nitrogen metabolism, adherens junction and alanine.4. Protein interactions analysis revealed that FOS, MYL9, and FRAS1 had a high degree of interactions, in which the DNA methylation level of the MYL9 promoter region was negatively correlated with mRNA expression level. Further studies showed that 5-azacytidine (5-AzaC) inhibited DNMT1 and DNMT3A gene expression and promoted MYL9 expression.5. This study systematically investigated overall DNA methylation patterns in the leg muscle of VVD and normal broilers. It screened common differential genes in conjunction with transcriptomic data to further identify genes associated with muscle growth and development. This study provides new insights to better understand the pathogenesis of VVD from an epigenetic perspective.
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Wang MZ, Jiang HF, Song TY, Xu CL, Li H, Song MH, Fang F. [Clinical characteristics of children with MT-TK gene m.8344A>G variation]. ZHONGHUA ER KE ZA ZHI = CHINESE JOURNAL OF PEDIATRICS 2024; 62:1056-1063. [PMID: 39429077 DOI: 10.3760/cma.j.cn112140-20240516-00337] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/22/2024]
Abstract
Objective: To summarize the clinical characteristics of children carrying the m.8344A>G variant of MT-TK gene. Methods: A case series study was conducted to retrospectively collect data of 22 children with mitochondrial disease caused by MT-TK gene m.8344A>G variation who were treated at the Department of Neurology of Beijing Children's Hospital of Capital Medical University from January 2012 to January 2024. Their clinical data, laboratory tests, muscle pathology, genetic testing, and the follow-up results were analyzed. Pearson correlation analysis was used for correlation analysis. Results: Among the 22 children, there were 13 boys and 9 girls. The age of onset was 5.00 (2.75, 9.00) years. Fifteen children had myoclonic epilepsy with ragged-red fibers (MERRF), 3 had Leigh syndrome (LS), and 4 had LS-MERRF overlap syndrome (LS-MERRF). Myoclonus presented and worsened progressively in all 15 MERRF children, with 10 as the initial symptom and 5 developing progressively during the disease course. Myoclonus was predominantly focal, worsening with fine motor tasks or stress. Electroencephalogram monitoring in the 15 MERRF children revealed myoclonic seizures in 10 children, with 6 classified as myoclonic epilepsy, and 4 as subcortical myoclonus. Two children had generalized myoclonic seizures, and 1 each had absence seizures and generalized seizures. Twelve children had cerebellar ataxia, 10 children exhibited exercise intolerance, and 8 children had muscle weakness. Magnetic resonance imaging (MRI) revealed periventricular white matter involvement in 1 child and bilateral hippocampal involvement in 1 child, likely due to frequent seizures. All 3 children with LS exhibited developmental regressions, accompanied with 2 symptoms include cerebellar ataxia, muscle weakness, and dysphagia. The clinical manifestations of 4 LS-MERRF overlap children presented with combined features of MERRF and LS. Cranial MRI in the 7 LS and LS-MERRF children showed brainstem involvement (all affecting the midbrain) in 6 children and basal ganglia involvement in 4 children. Among the 22 children, 12 had m.8344A>G variant levels >90%, 3 had >80%-90%, 4 had >70%-80%, and 3 had >60%-70%. Higher variant level correlated with the LS phenotype and earlier onset age (r=0.47, -0.50; P=0.018 and 0.029, respectively). Sanger sequencing in 19 mothers revealed m.8344A>G variations in 18, with 4 showing exercise intolerance. Follow-up of 13 children on antimyoclonic treatment showed>75% reduction in seizures with levetiracetam monotherapy in 2 children, with combination therapy required in others. Most achieved >50% seizures reduction within 2 years, but the effectiveness declined with disease progression. Conclusions: The m.8344A>G variant is rare, with MERRF being the most common phenotype, while LS and LS-MERRF are less common. Children with higher ratio of the m.8344A>G variant are more likely to present LS phenotype. Myoclonus, primarily focal, is a key feature, with levetiracetam as the first-line treatment and benzodiazepines recommended for refractory cases.
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Wang S, Lu H, Zhai Y, Tang Y, Su M, Li H, Wang Y, Liu Y, Ge RS. Inhibition of human and rat placental 3β-hydroxysteroid dehydrogenases by bisphenol A analogues depends on their hydrophobicity: In silico docking analysis. Chem Biol Interact 2024; 403:111251. [PMID: 39313105 DOI: 10.1016/j.cbi.2024.111251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/14/2024] [Accepted: 09/20/2024] [Indexed: 09/25/2024]
Abstract
Bisphenol A (BPA) and its analogues are widely used industrial chemicals. Placental 3β-hydroxysteroid dehydrogenases (3β-HSDs) catalyse the conversion of pregnenolone to progesterone. However, the potency of BPA analogues in inhibiting 3β-HSDs activity remains unclear. We investigated the inhibitory effect of 10 BPA analogues on 3β-HSDs activity using an in vitro assay and performed the structure-activity relationship and in silico docking analysis. BPH was the most potent inhibitor of human 3β-HSD1, with an IC50 value of 0.95 μM. BPFL, BPG, DABPA, BPAP, BPZ, DMBPA, and BPB also inhibited human 3β-HSD1 activity, albeit with lower potency. BPG was the most potent inhibitor of rat 3β-HSD4, with an IC50 value of 1.14 μM. BPAP, BPFL, BPG, BPH, BPZ, DABPA, and DMBPA are mixed inhibitors of human 3β-HSD1 and they significantly inhibited human JAr cells to secrete progesterone. The LogP values were inversely correlated with the inhibitory effects. Docking analysis showed that most BPA analogues bind to steroid-binding site of both 3β-HSDs. A pharmacophore containing hydrogen bond donor and hydrophobic region was generated for predicting the inhibitory strength of BPA analogues. In conclusion, this study demonstrates that some BPA analogues are potent inhibitors of 3β-HSDs and lipophilicity determines the inhibitory potency.
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Li H, Zhao J, Jiang Z. Deep learning-based computer-aided detection of ultrasound in breast cancer diagnosis: A systematic review and meta-analysis. Clin Radiol 2024; 79:e1403-e1413. [PMID: 39217049 DOI: 10.1016/j.crad.2024.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 07/05/2024] [Accepted: 08/01/2024] [Indexed: 09/04/2024]
Abstract
PURPOSE The aim of this meta-analysis was to assess the diagnostic performance of deep learning (DL) and ultrasound in breast cancer diagnosis. Additionally, we categorized the included studies into two subgroups: B-mode ultrasound diagnostic subgroup and multimodal ultrasound diagnostic subgroup, and compared the performance differences of DL algorithms in breast cancer diagnosis using only B-mode ultrasound or multimodal ultrasound. METHODS We conducted a comprehensive search for relevant studies published from January 01, 2017 to July 31, 2023 in the MEDLINE and EMBASE databases. The quality of the included studies was evaluated using the QUADAS-2 tool and radiomics quality scores (RQS). Meta-analysis was performed using R software. Inter-study heterogeneity was assessed by I^2 values and Q-test P-values, with sources of heterogeneity analyzed through a random effects model based on test results. Summary receiver operating characteristics (SROC) curves were used for meta-analysis across multiple trials, while combined sensitivity, specificity, and AUC were calculated to quantify prediction accuracy. Subgroup analysis and sensitivity analyses were also conducted to identify potential sources of study heterogeneity. Publication bias was assessed using the funnel plot method. (PROSPERO identifier: CRD42024545758). RESULTS The 20 studies included a total of 14,955 cases, with 4197 cases used for model testing. Among these cases were 1582 breast cancer patients and 2615 benign or other breast lesions. The combined sensitivity, specificity, and AUC values across all studies were found to be 0.93, 0.90, and 0.732, respectively. In subgroup analysis, the multimodal subgroup demonstrated superior performance with combined sensitivity, specificity, and AUC values of 0.93, 0.88, and 0.787, respectively; whereas the combined sensitivity, specificity, and AUC value for the model B subgroup was at a level of 0.92, 0.91, and 0.642, respectively. CONCLUSIONS The integration of DL with ultrasound demonstrates high accuracy in the adjunctive diagnosis of breast cancer, while the fusion of DL and multimodal breast ultrasound exhibits superior diagnostic efficacy compared to B-mode ultrasound alone.
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Li H, Gui Y, Luo Z. Efficacy rigor of neoadjuvant therapy: the role and synthesis of tumor subtype analysis. Letter to the Editor regarding 'Total neoadjuvant therapy with mFOLFIRINOX versus preoperative chemoradiotherapy in patients with locally advanced rectal cancer: long-term results of the UNICANCER-PRODIGE 23 trial' by Conroy T et al. Ann Oncol 2024; 35:1064-1065. [PMID: 39214460 DOI: 10.1016/j.annonc.2024.08.2333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2024] [Accepted: 08/12/2024] [Indexed: 09/04/2024] Open
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Qiao X, Zheng K, Ye L, Yang J, Cui R, Shan Y, Li X, Li H, Zhu Q, Zhao Z, Ge RS, Wang Y. NL13, a novel curcumin analogue and polo like kinase 4 inhibitor, induces cell cycle arrest and apoptosis in prostate cancer models. Br J Pharmacol 2024; 181:4658-4676. [PMID: 39142876 DOI: 10.1111/bph.16501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 05/21/2024] [Accepted: 05/29/2024] [Indexed: 08/16/2024] Open
Abstract
BACKGROUND AND PURPOSE Prostate cancer remains a major public health burden worldwide. Polo like kinase 4 (PLK4) has emerged as a promising therapeutic target in prostate cancer due to its key roles in cell cycle regulation and tumour progression. This study aims to develop and characterize the novel curcumin analogue NL13 as a potential therapeutic agent and PLK4 inhibitor against prostate cancer. EXPERIMENTAL APPROACH NL13 was synthesized and its effects were evaluated in prostate cancer cells and mouse xenograft models. Kinome screening and molecular modelling identified PLK4 as the primary target. Antiproliferative and proapoptotic mechanisms were explored via cell cycle, apoptosis, gene and protein analyses. KEY RESULTS Compared with curcumin, NL13 exhibited much greater potency in inhibiting PC3 (IC50, 3.51 μM vs. 35.45 μM) and DU145 (IC50, 2.53 μM vs. 29.35 μM) prostate cancer cells viability and PLK4 kinase activity (2.32 μM vs. 246.88 μM). NL13 induced G2/M cell cycle arrest through CCNB1/CDK1 down-regulation and triggered apoptosis via caspase-9/caspase-3 cleavage. These effects were mediated by PLK4 inhibition, which led to the inactivation of the AKT signalling pathway. In mice, NL13 significantly inhibited tumour growth and modulated molecular markers consistent with in vitro findings, including decreased p-AKT and increased cleaved caspase-9/3. CONCLUSION AND IMPLICATIONS NL13, a novel PLK4-targeted curcumin analogue, exerts promising anticancer properties against prostate cancer by disrupting the PLK4-AKT-CCNB1/CDK1 and apoptosis pathways. NL13 represents a promising new agent for prostate cancer therapy.
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Abdulhamid MI, Aboona BE, Adam J, Adams JR, Agakishiev G, Aggarwal I, Aggarwal MM, Ahammed Z, Aitbaev A, Alekseev I, Alpatov E, Aparin A, Aslam S, Atchison J, Averichev GS, Bairathi V, Cap JGB, Barish K, Bhagat P, Bhasin A, Bhatta S, Bhosale SR, Bordyuzhin IG, Brandenburg JD, Brandin AV, Broodo C, Cai XZ, Caines H, Calderón de la Barca Sánchez M, Cebra D, Ceska J, Chakaberia I, Chan BK, Chang Z, Chatterjee A, Chen D, Chen J, Chen JH, Chen Z, Cheng J, Cheng Y, Christie W, Chu X, Crawford HJ, Csanád M, Dale-Gau G, Das A, Dedovich TG, Deppner IM, Derevschikov AA, Dhamija A, Dixit P, Dong X, Drachenberg JL, Duckworth E, Dunlop JC, Engelage J, Eppley G, Esumi S, Evdokimov O, Eyser O, Fatemi R, Fazio S, Feng CJ, Feng Y, Finch E, Fisyak Y, Flor FA, Fu C, Gao T, Geurts F, Ghimire N, Gibson A, Gopal K, Gou X, Grosnick D, Gupta A, Hamed A, Han Y, Harasty MD, Harris JW, Harrison-Smith H, He W, He XH, He Y, Hu C, Hu Q, Hu Y, Huang H, Huang HZ, Huang SL, Huang T, Huang Y, Huang Y, Humanic TJ, Isshiki M, Jacobs WW, Jalotra A, Jena C, Ji Y, Jia J, Jin C, Ju X, Judd EG, Kabana S, Kalinkin D, Kang K, Kapukchyan D, Kauder K, Keane D, Kechechyan A, Khanal A, Kiselev A, Knospe AG, Ko HS, Kochenda L, Korobitsin AA, Yu. Kraeva A, Kravtsov P, Kumar L, Labonte MC, Lacey R, Landgraf JM, Lebedev A, Lednicky R, Lee JH, Leung YH, Li C, Li D, Li HS, Li H, Li W, Li X, Li Y, Li Y, Li Z, Liang X, Liang Y, Lin T, Lin Y, Liu C, Liu G, Liu H, Liu L, Liu T, Liu X, Liu Y, Liu Z, Ljubicic T, Lomicky O, Longacre RS, Loyd EM, Lu T, Luo J, Luo XF, Luong VB, Ma L, Ma R, Ma YG, Magdy N, Manikandhan R, Margetis S, Matonoha O, McNamara G, Mezhanska O, Mi K, Minaev NG, Mohanty B, Mondal B, Mondal MM, Mooney I, Morozov DA, Mudrokh A, Nagy MI, Nain AS, Nam JD, Nasim M, Nedorezov E, Neff D, Nelson JM, Nie M, Nigmatkulov G, Niida T, Nogach LV, Nonaka T, Odyniec G, Ogawa A, Oh S, Okorokov VA, Okubo K, Page BS, Pal S, Pandav A, Panday A, Panebratsev Y, Pani T, Parfenov P, Paul A, Perkins C, Pokhrel BR, Posik M, Povarov A, Protzman T, Pruthi NK, Putschke J, Qin Z, Qiu H, Racz C, Radhakrishnan SK, Rana A, Ray RL, Robertson CW, Rogachevsky OV, Rosales Aguilar MA, Roy D, Ruan L, Sahoo AK, Sahoo NR, Sako H, Salur S, Samigullin E, Sato S, Schaefer BC, Schmidke WB, Schmitz N, Seger J, Seto R, Seyboth P, Shah N, Shahaliev E, Shanmuganathan PV, Shao T, Sharma M, Sharma N, Sharma R, Sharma SR, Sheikh AI, Shen D, Shen DY, Shen K, Shi SS, Shi Y, Shou QY, Si F, Singh J, Singha S, Sinha P, Skoby MJ, Söhngen Y, Song Y, Srivastava B, Stanislaus TDS, Stewart DJ, Strikhanov M, Su Y, Sun C, Sun X, Sun Y, Sun Y, Surrow B, Svirida DN, Sweger ZW, Tamis AC, Tang AH, Tang Z, Taranenko A, Tarnowsky T, Thomas JH, Tlusty D, Todoroki T, Tokarev MV, Trentalange S, Tribedy P, Tsai OD, Tsang CY, Tu Z, Tyler J, Ullrich T, Underwood DG, Upsal I, Van Buren G, Vasiliev AN, Verkest V, Videbæk F, Vokal S, Voloshin SA, Wang G, Wang JS, Wang J, Wang K, Wang X, Wang Y, Wang Y, Wang Y, Wang Z, Webb JC, Weidenkaff PC, Westfall GD, Wieman H, Wilks G, Wissink SW, Wu J, Wu J, Wu X, Wu X, Xi B, Xiao ZG, Xie G, Xie W, Xu H, Xu N, Xu QH, Xu Y, Xu Y, Xu Z, Xu Z, Yan G, Yan Z, Yang C, Yang Q, Yang S, Yang Y, Ye Z, Ye Z, Yi L, Yu Y, Zha W, Zhang C, Zhang D, Zhang J, Zhang S, Zhang W, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Y, Zhang ZJ, Zhang Z, Zhang Z, Zhao F, Zhao J, Zhao M, Zhou S, Zhou Y, Zhu X, Zurek M, Zyzak M. Imaging shapes of atomic nuclei in high-energy nuclear collisions. Nature 2024; 635:67-72. [PMID: 39506156 DOI: 10.1038/s41586-024-08097-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 09/23/2024] [Indexed: 11/08/2024]
Abstract
Atomic nuclei are self-organized, many-body quantum systems bound by strong nuclear forces within femtometre-scale space. These complex systems manifest a variety of shapes1-3, traditionally explored using non-invasive spectroscopic techniques at low energies4,5. However, at these energies, their instantaneous shapes are obscured by long-timescale quantum fluctuations, making direct observation challenging. Here we introduce the collective-flow-assisted nuclear shape-imaging method, which images the nuclear global shape by colliding them at ultrarelativistic speeds and analysing the collective response of outgoing debris. This technique captures a collision-specific snapshot of the spatial matter distribution within the nuclei, which, through the hydrodynamic expansion, imprints patterns on the particle momentum distribution observed in detectors6,7. We benchmark this method in collisions of ground-state uranium-238 nuclei, known for their elongated, axial-symmetric shape. Our findings show a large deformation with a slight deviation from axial symmetry in the nuclear ground state, aligning broadly with previous low-energy experiments. This approach offers a new method for imaging nuclear shapes, enhances our understanding of the initial conditions in high-energy collisions and addresses the important issue of nuclear structure evolution across energy scales.
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Ding C, Zhu H, Tang Y, Ying Y, Zhu Y, Lin H, Ge RS, Li H. Structural determinants of parabens in inhibiting human and rat gonadal 3β-hydroxysteroid dehydrogenase. Toxicol Appl Pharmacol 2024; 492:117133. [PMID: 39454967 DOI: 10.1016/j.taap.2024.117133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2024] [Revised: 10/18/2024] [Accepted: 10/19/2024] [Indexed: 10/28/2024]
Abstract
This study delved into the impacts of 10 parabens on the activity of human and rat gonadal 3β-hydroxysteroid dehydrogenase (3β-HSD) within human KGN cell and rat testicular microsomes, as well as on the secretion of progesterone in KGN cells and the inhibitory potency was compared between human and rats. Intriguingly, the outcomes revealed that ethyl, propyl, butyl, hexyl, heptyl, nonyl, phenyl, and benzyl parabens displayed varying IC50 values for human 3β-HSD2, from 4.15 to 139.96 μM, demonstrating characteristics of mixed inhibitors. Notably, within KGN cells, all examined parabens, excluding nonyl and phenyl parabens, significantly inhibited progesterone secretion at 5-50 μM. In the case of rats, the IC50 values for these parabens on gonadal 3β-HSD1 fluctuated between 7.15 and 110.76 μM, likewise functioning as mixed inhibitors. Through docking analysis, it was proposed that most parabens effectively bind to NAD+ and/or steroid binding site. Moreover, bivariate correlation analysis unveiled an inverse correlation between IC50 values and structural characteristics such as LogP, molecular weight, heavy atom number, and carbon number within the alcohol moiety of parabens. 3D-QSAR elucidated pivotal regions, comprising hydrogen bond donor, hydrogen bond acceptor, and hydrophobic region, with the most potent inhibitor nonyl paraben engaging with all regions, while the weakest inhibitor ethyl paraben interacted with the regions except for the hydrophobic region. In conclusion, this investigation underscored the inhibitory effects imparted by several parabens on both human and rat gonadal 3β-HSD activity, with their inhibitory potency being modulated by aspects of hydrophobicity and carbon chain length.
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Aad G, Aakvaag E, Abbott B, Abdelhameed S, Abeling K, Abicht NJ, Abidi SH, Aboelela M, Aboulhorma A, Abramowicz H, Abreu H, Abulaiti Y, Acharya BS, Ackermann A, Adam Bourdarios C, Adamczyk L, Addepalli SV, Addison MJ, Adelman J, Adiguzel A, Adye T, Affolder AA, Afik Y, Agaras MN, Agarwala J, Aggarwal A, Agheorghiesei C, Ahmad A, Ahmadov F, Ahmed WS, Ahuja S, Ai X, Aielli G, Aikot A, Ait Tamlihat M, Aitbenchikh B, Akbiyik M, Åkesson TPA, Akimov AV, Akiyama D, Akolkar NN, Aktas S, Al Khoury K, Alberghi GL, Albert J, Albicocco P, Albouy GL, Alderweireldt S, Alegria ZL, Aleksa M, Aleksandrov IN, Alexa C, Alexopoulos T, Alfonsi F, Algren M, Alhroob M, Ali B, Ali HMJ, Ali S, Alibocus SW, Aliev M, Alimonti G, Alkakhi W, Allaire C, Allbrooke BMM, Allen JF, Allendes Flores CA, Allport PP, Aloisio A, Alonso F, Alpigiani C, Alsolami ZMK, Alvarez Estevez M, Alvarez Fernandez A, Alves Cardoso M, Alviggi MG, Aly M, Amaral Coutinho Y, Ambler A, Amelung C, Amerl M, Ames CG, Amidei D, Amirie KJ, Amor Dos Santos SP, Amos KR, An S, Ananiev V, Anastopoulos C, Andeen T, Anders JK, Anderson AC, Andrean SY, Andreazza A, Angelidakis S, Angerami A, Anisenkov AV, Annovi A, Antel C, Antipov E, Antonelli M, Anulli F, Aoki M, Aoki T, Aparo MA, Aperio Bella L, Appelt C, Apyan A, Arbiol Val SJ, Arcangeletti C, Arce ATH, Arena E, Arguin JF, Argyropoulos S, Arling JH, Arnaez O, Arnold H, Artoni G, Asada H, Asai K, Asai S, Asbah NA, Ashby Pickering RA, Assamagan K, Astalos R, Astrand KSV, Atashi S, Atkin RJ, Atkinson M, Atmani H, Atmasiddha PA, Augsten K, Auricchio S, Auriol AD, Austrup VA, Avolio G, Axiotis K, Azuelos G, Babal D, Bachacou H, Bachas K, Bachiu A, Backman F, Badea A, Baer TM, Bagnaia P, Bahmani M, Bahner D, Bai K, Baines JT, Baines L, Baker OK, Bakos E, Bakshi Gupta D, Balabram Filho LE, Balakrishnan V, Balasubramanian R, Baldin EM, Balek P, Ballabene E, Balli F, Baltes LM, Balunas WK, Balz J, Bamwidhi I, Banas E, Bandieramonte M, Bandyopadhyay A, Bansal S, Barak L, Barakat M, Barberio EL, Barberis D, Barbero M, Barel MZ, Barends KN, Barillari T, Barisits MS, Barklow T, Baron P, Baron Moreno DA, Baroncelli A, Barone G, Barr AJ, Barr JD, Barreiro F, Barreiro Guimarães da Costa J, Barron U, Barros Teixeira MG, Barsov S, Bartels F, Bartoldus R, Barton AE, Bartos P, Basan A, Baselga M, Bassalat A, Basso MJ, Bataju S, Bate R, Bates RL, Batlamous S, Batool B, Battaglia M, Battulga D, Bauce M, Bauer M, Bauer P, Bazzano Hurrell LT, Beacham JB, Beau T, Beaucamp JY, Beauchemin PH, Bechtle P, Beck HP, Becker K, Beddall AJ, Bednyakov VA, Bee CP, Beemster LJ, Beermann TA, Begalli M, Begel M, Behera A, Behr JK, Beirer JF, Beisiegel F, Belfkir M, Bella G, Bellagamba L, Bellerive A, Bellos P, Beloborodov K, Benchekroun D, Bendebba F, Benhammou Y, Benkendorfer KC, Beresford L, Beretta M, Bergeaas Kuutmann E, Berger N, Bergmann B, Beringer J, Bernardi G, Bernius C, Bernlochner FU, Bernon F, Berrocal Guardia A, Berry T, Berta P, Berthold A, Bethke S, Betti A, Bevan AJ, Bhalla NK, Bhatta S, Bhattacharya DS, Bhattarai P, Bhide KD, Bhopatkar VS, Bianchi RM, Bianco G, Biebel O, Bielski R, Biglietti M, Billingsley CS, Bindi M, Bingul A, Bini C, Biondini A, Bird GA, Birman M, Biros M, Biryukov S, Bisanz T, Bisceglie E, Biswal JP, Biswas D, Bloch I, Blue A, Blumenschein U, Blumenthal J, Bobrovnikov VS, Boehler M, Boehm B, Bogavac D, Bogdanchikov AG, Bohm C, Boisvert V, Bokan P, Bold T, Bomben M, Bona M, Boonekamp M, Booth CD, Borbély AG, Bordulev IS, Borecka-Bielska HM, Borissov G, Bortoletto D, Boscherini D, Bosman M, Bossio Sola JD, Bouaouda K, Bouchhar N, Boudet L, Boudreau J, Bouhova-Thacker EV, Boumediene D, Bouquet R, Boveia A, Boyd J, Boye D, Boyko IR, Bozianu L, Bracinik J, Brahimi N, Brandt G, Brandt O, Braren F, Brau B, Brau JE, Brener R, Brenner L, Brenner R, Bressler S, Brianti G, Britton D, Britzger D, Brock I, Brooijmans G, Brooks EM, Brost E, Brown LM, Bruce LE, Bruckler TL, Bruckman de Renstrom PA, Brüers B, Bruni A, Bruni G, Bruschi M, Bruscino N, Buanes T, Buat Q, Buchin D, Buckley AG, Bulekov O, Bullard BA, Burdin S, Burgard CD, Burger AM, Burghgrave B, Burlayenko O, Burr JTP, Burzynski JC, Busch EL, Büscher V, Bussey PJ, Butler JM, Buttar CM, Butterworth JM, Buttinger W, Buxo Vazquez CJ, Buzykaev AR, Cabrera Urbán S, Cadamuro L, Caforio D, Cai H, Cai Y, Cai Y, Cairo VMM, Cakir O, Calace N, Calafiura P, Calderini G, Calfayan P, Callea G, Caloba LP, Calvet D, Calvet S, Calvetti M, Camacho Toro R, Camarda S, Camarero Munoz D, Camarri P, Camerlingo MT, Cameron D, Camincher C, Campanelli M, Camplani A, Canale V, Canbay AC, Canonero E, Cantero J, Cao Y, Capocasa F, Capua M, Carbone A, Cardarelli R, Cardenas JCJ, Carducci G, Carli T, Carlino G, Carlotto JI, Carlson BT, Carlson EM, Carmignani J, Carminati L, Carnelli A, Carnesale M, Caron S, Carquin E, Carrá S, Carratta G, Carroll AM, Carter TM, Casado MP, Caspar M, Castillo FL, Castillo Garcia L, Castillo Gimenez V, Castro NF, Catinaccio A, Catmore JR, Cavaliere T, Cavaliere V, 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Search for Light Long-Lived Particles in pp Collisions at sqrt[s]=13 TeV Using Displaced Vertices in the ATLAS Inner Detector. PHYSICAL REVIEW LETTERS 2024; 133:161803. [PMID: 39485965 DOI: 10.1103/physrevlett.133.161803] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 08/29/2024] [Accepted: 09/11/2024] [Indexed: 11/03/2024]
Abstract
A search for long-lived particles (LLPs) using 140 fb^{-1} of pp collision data with sqrt[s]=13 TeV recorded by the ATLAS experiment at the LHC is presented. The search targets LLPs with masses between 5 and 55 GeV that decay hadronically in the ATLAS inner detector. Benchmark models with LLP pair production from exotic decays of the Higgs boson and models featuring long-lived axionlike particles (ALPs) are considered. No significant excess above the expected background is observed. Upper limits are placed on the branching ratio of the Higgs boson to pairs of LLPs, the cross section for ALPs produced in association with a vector boson, and, for the first time, on the branching ratio of the top quark to an ALP and a u/c quark.
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Palacino G, Palazzo A, Palestini S, Pan J, Pan T, Panchal DK, Pandini CE, Panduro Vazquez JG, Pandya HD, Pang H, Pani P, Panizzo G, Paolozzi L, Papadatos C, Parajuli S, Paramonov A, Paraskevopoulos C, Paredes Hernandez D, Park KR, Park TH, Parker MA, Parodi F, Parrish EW, Parrish VA, Parsons JA, Parzefall U, Pascual Dias B, Pascual Dominguez L, Pasqualucci E, Passaggio S, Pastore F, Pasuwan P, Patel P, Patel UM, Pater JR, Pauly T, Pearkes J, Pedersen M, Pedro R, Peleganchuk SV, Penc O, Pender EA, Penski KE, Penzin M, Peralva BS, Peixoto APP, Pereira Sanchez L, Perepelitsa DV, Perez Codina E, Perganti M, Perini L, Pernegger H, Perrin O, Peters K, Peters RFY, Petersen BA, Petersen TC, Petit E, Petousis V, Petridou C, Petrukhin A, Pettee M, Pettersson NE, Petukhov A, Petukhova K, Pezoa R, Pezzotti L, Pezzullo G, Pham TM, Pham T, Phillips PW, Piacquadio G, Pianori E, Piazza F, Piegaia R, Pietreanu D, Pilkington AD, Pinamonti M, Pinfold JL, Pereira BCP, Pinto Pinoargote AE, Pintucci L, Piper KM, Pirttikoski A, Pizzi DA, Pizzimento L, Pizzini A, Pleier MA, Plesanovs V, Pleskot V, Plotnikova E, Poddar G, Poettgen R, Poggioli L, Pokharel I, Polacek S, Polesello G, Poley A, Polifka R, Polini A, Pollard CS, Pollock ZB, Polychronakos V, Pompa Pacchi E, Ponomarenko D, Pontecorvo L, Popa S, Popeneciu GA, Poreba A, Portillo Quintero DM, Pospisil S, Postill MA, Postolache P, Potamianos K, Potepa PA, Potrap IN, Potter CJ, Potti H, Poulsen T, Poveda J, Pozo Astigarraga ME, Prades Ibanez A, Pretel J, Price D, Primavera M, Principe Martin MA, Privara R, Procter T, Proffitt ML, Proklova N, Prokofiev K, Proto G, Protopopescu S, Proudfoot J, Przybycien M, Przygoda WW, Puddefoot JE, Pudzha D, Pyatiizbyantseva D, Qian J, Qichen D, Qin Y, Qiu T, Quadt A, Queitsch-Maitland M, Quetant G, Quinn RP, Rabanal Bolanos G, Rafanoharana D, Ragusa F, Rainbolt JL, Raine JA, Rajagopalan S, Ramakoti E, Ramirez-Berend IA, Ran K, Rapheeha NP, Rasheed H, Raskina V, Rassloff DF, Rastogi A, Rave S, Ravina B, Ravinovich I, Raymond M, Read AL, Readioff NP, Rebuzzi DM, Redlinger G, Reed AS, Reeves K, Reidelsturz JA, Reikher D, Rej A, Rembser C, Renardi A, Renda M, Rendel MB, Renner F, Rennie AG, Rescia AL, Resconi S, Ressegotti M, Rettie S, Reyes Rivera JG, Reynolds E, Rezanova OL, Reznicek P, Ribaric N, Ricci E, Richter R, Richter S, Richter-Was E, Ridel M, Ridouani S, Rieck P, Riedler P, Riefel EM, Rieger JO, Rijssenbeek M, Rimoldi A, Rimoldi M, Rinaldi L, Rinn TT, Rinnagel MP, Ripellino G, Riu I, Rivadeneira P, Rivera Vergara JC, Rizatdinova F, Rizvi E, Roberts BA, Roberts BR, Robertson SH, Robinson D, Robles Gajardo CM, Robles Manzano M, Robson A, Rocchi A, Roda C, Rodriguez Bosca S, Rodriguez Garcia Y, Rodriguez Rodriguez A, Rodríguez Vera AM, Roe S, Roemer JT, Roepe-Gier AR, Roggel J, Røhne O, Rojas RA, Roland CPA, Roloff J, Romaniouk A, Romano E, Romano M, Romero Hernandez AC, Rompotis N, Roos L, Rosati S, Rosser BJ, Rossi E, Rossi E, Rossi LP, Rossini L, Rosten R, Rotaru M, Rottler B, Rougier C, Rousseau D, Rousso D, Roy A, Roy-Garand S, Rozanov A, Rozario ZMA, Rozen Y, Ruan X, Rubio Jimenez A, Ruby AJ, Ruelas Rivera VH, Ruggeri TA, Ruggiero A, Ruiz-Martinez A, Rummler A, Rurikova Z, Rusakovich NA, Russell HL, Russo G, Rutherfoord JP, Rutherford Colmenares S, Rybacki K, Rybar M, Rye EB, Ryzhov A, Sabater Iglesias JA, Sabatini P, Sadrozinski HFW, Safai Tehrani F, Safarzadeh Samani B, Safdari M, Saha S, Sahinsoy M, Saibel A, Saimpert M, Saito M, Saito T, Salamani D, Salnikov A, Salt J, Salvador Salas A, Salvatore D, Salvatore F, Salzburger A, Sammel D, Sampsonidis D, Sampsonidou D, Sánchez J, Sanchez Pineda A, Sanchez Sebastian V, Sandaker H, Sander CO, Sandesara JA, Sandhoff M, Sandoval C, Sankey DPC, Sano T, Sansoni A, Santi L, Santoni C, Santos H, Santpur SN, Santra A, Saoucha KA, Saraiva JG, Sardain J, Sasaki O, Sato K, Sauer C, Sauerburger F, Sauvan E, Savard P, Sawada R, Sawyer C, Sawyer L, Sayago Galvan I, Sbarra C, Sbrizzi A, Scanlon T, Schaarschmidt J, Schacht P, Schäfer U, Schaffer AC, Schaile D, Schamberger RD, Scharf C, Schefer MM, Schegelsky VA, Scheirich D, Schenck F, Schernau M, Scheulen C, Schiavi C, Schioppa EJ, Schioppa M, Schlag B, Schleicher KE, Schlenker S, Schmeing J, Schmidt MA, Schmieden K, Schmitt C, Schmitt N, Schmitt S, Schoeffel L, Schoening A, Scholer PG, Schopf E, Schott M, Schovancova J, Schramm S, Schroeder F, Schroer T, Schultz-Coulon HC, Schumacher M, Schumm BA, Schune P, Schuy AJ, Schwartz HR, Schwartzman A, Schwarz TA, Schwemling P, Schwienhorst R, Sciandra A, Sciolla G, Scuri F, Sebastiani CD, Sedlaczek K, Seema P, Seidel SC, Seiden A, Seidlitz BD, Seitz C, Seixas JM, Sekhniaidze G, Sekula SJ, Selem L, Semprini-Cesari N, Sengupta D, Senthilkumar V, Serin L, Serkin L, Sessa M, Severini H, Sforza F, Sfyrla A, Shabalina E, Shaheen R, Shahinian JD, Shaked Renous D, Shan LY, Shapiro M, Sharma A, Sharma AS, Sharma P, Sharma S, Shatalov PB, Shaw K, Shaw SM, Shcherbakova A, Shen Q, Sheppard DJ, Sherwood P, Shi L, Shi X, Shimmin CO, Shinner JD, Shipsey IPJ, Shirabe S, Shiyakova M, Shlomi J, Shochet MJ, Shojaii J, Shope DR, Shrestha B, Shrestha S, Shrif EM, Shroff MJ, Sicho P, Sickles AM, Sideras Haddad E, Sidoti A, Siegert F, Sijacki D, Sili F, Silva JM, Silva Oliveira MV, Silverstein SB, Simion S, Simoniello R, Simpson EL, Simpson H, Simpson LR, Simpson ND, Simsek S, Sindhu S, Sinervo P, Singh S, Sinha S, Sinha S, Sioli M, Siral I, Sitnikova E, Sivoklokov SY, Sjölin J, Skaf A, Skorda E, Skubic P, Slawinska M, Smakhtin V, Smart BH, Smiesko J, Smirnov SY, Smirnov Y, Smirnova LN, Smirnova O, Smith AC, Smith EA, Smith HA, Smith JL, Smith R, Smizanska M, Smolek K, Snesarev AA, Snider SR, Snoek HL, Snyder S, Sobie R, Soffer A, Solans Sanchez CA, Soldatov EY, Soldevila U, Solodkov AA, Solomon S, Soloshenko A, Solovieva K, Solovyanov OV, Solovyev V, Sommer P, Sonay A, Song WY, Sonneveld JM, Sopczak A, Sopio AL, Sopkova F, Sotarriva Alvarez IR, Sothilingam V, Soto Sandoval OJ, Sottocornola S, Soualah R, Soumaimi Z, South D, Soybelman N, Spagnolo S, Spalla M, Sperlich D, Spigo G, Spinali S, Spiteri DP, Spousta M, Staats EJ, Stabile A, Stamen R, Stampekis A, Standke M, Stanecka E, Stange MV, Stanislaus B, Stanitzki MM, Stapf B, Starchenko EA, Stark GH, Stark J, Starko DM, Staroba P, Starovoitov P, Stärz S, Staszewski R, Stavropoulos G, Steentoft J, Steinberg P, Stelzer B, Stelzer HJ, Stelzer-Chilton O, Stenzel H, Stevenson TJ, Stewart GA, Stewart JR, Stockton MC, Stoicea G, Stolarski M, Stonjek S, Straessner A, Strandberg J, Strandberg S, Stratmann M, Strauss M, Strebler T, Strizenec P, Ströhmer R, Strom DM, Stroynowski R, Strubig A, Stucci SA, Stugu B, Stupak J, Styles NA, Su D, Su S, Su W, Su X, Sugizaki K, Sulin VV, Sullivan MJ, Sultan DMS, Sultanaliyeva L, Sultansoy S, Sumida T, Sun S, Sun S, Gudnadottir OS, Sur N, Sutton MR, Suzuki H, Svatos M, Swiatlowski M, Swirski T, Sykora I, Sykora M, Sykora T, Ta D, Tackmann K, Taffard A, Tafirout R, Tafoya Vargas JS, Takeva EP, Takubo Y, Talby M, Talyshev AA, Tam KC, Tamir NM, Tanaka A, Tanaka J, Tanaka R, Tanasini M, Tao Z, Tapia Araya S, Tapprogge S, Tarek Abouelfadl Mohamed A, Tarem S, Tariq K, Tarna G, Tartarelli GF, Tas P, Tasevsky M, Tassi E, Tate AC, Tateno G, Tayalati Y, Taylor GN, Taylor W, Tee AS, Teixeira De Lima R, Teixeira-Dias P, Teoh JJ, Terashi K, Terron J, Terzo S, Testa M, Teuscher RJ, Thaler A, Theiner O, Themistokleous N, Theveneaux-Pelzer T, Thielmann O, Thomas DW, Thomas JP, Thompson EA, Thompson PD, Thomson E, Tian Y, Tikhomirov V, Tikhonov YA, Timoshenko S, Timoshyn D, Ting EXL, Tipton P, Tlou SH, Tnourji A, Todome K, Todorova-Nova S, Todt S, Togawa M, Tojo J, Tokár S, Tokushuku K, Toldaiev O, Tombs R, Tomoto M, Tompkins L, Topolnicki KW, Torrence E, Torres H, Torró Pastor E, Toscani M, Tosciri C, Tost M, Tovey DR, Traeet A, Trandafir IS, Trefzger T, Tricoli A, Trigger IM, Trincaz-Duvoid S, Trischuk DA, Trocmé B, Troncon C, Truong L, Trzebinski M, Trzupek A, Tsai F, Tsai M, Tsiamis A, Tsiareshka PV, Tsigaridas S, Tsirigotis A, Tsiskaridze V, Tskhadadze EG, Tsopoulou M, Tsujikawa Y, Tsukerman II, Tsulaia V, Tsuno S, Tsuri K, Tsybychev D, Tu Y, Tudorache A, Tudorache V, Tuna AN, Turchikhin S, Turk Cakir I, Turra R, Turtuvshin T, Tuts PM, Tzamarias S, Tzanis P, Tzovara E, Ukegawa F, Ulloa Poblete PA, Umaka EN, Unal G, Unal M, Undrus A, Unel G, Urban J, Urquijo P, Urrejola P, Usai G, Ushioda R, Usman M, Uysal Z, Vacek V, Vachon B, Vadla KOH, Vafeiadis T, Vaitkus A, Valderanis C, Valdes Santurio E, Valente M, Valentinetti S, Valero A, Valiente Moreno E, Vallier A, Valls Ferrer JA, Van Arneman DR, Van Daalen TR, Van Der Graaf A, Van Gemmeren P, Van Rijnbach M, Van Stroud S, Van Vulpen I, Vanadia M, Vandelli W, Vandenbroucke M, Vandewall ER, Vannicola D, Vannoli L, Vari R, Varnes EW, Varni C, Varol T, Varouchas D, Varriale L, Varvell KE, Vasile ME, Vaslin L, Vasquez GA, Vasyukov A, Vazeille F, Vazquez Schroeder T, Veatch J, Vecchio V, Veen MJ, Veliscek I, Veloce LM, Veloso F, Veneziano S, Ventura A, Ventura Gonzalez S, Verbytskyi A, Verducci M, Vergis C, Verissimo De Araujo M, Verkerke W, Vermeulen JC, Vernieri C, Vessella M, Vetterli MC, Vgenopoulos A, Viaux Maira N, Vickey T, Vickey Boeriu OE, Viehhauser GHA, Vigani L, Villa M, Villaplana Perez M, Villhauer EM, Vilucchi E, Vincter MG, Virdee GS, Vishwakarma A, Visibile A, Vittori C, Vivarelli I, Voevodina E, Vogel F, Voigt JC, Vokac P, Volkotrub Y, Von Ahnen J, Von Toerne E, Vormwald B, Vorobel V, Vorobev K, Vos M, Voss K, Vossebeld JH, Vozak M, Vozdecky L, Vranjes N, Vranjes Milosavljevic M, Vreeswijk M, Vu NK, Vuillermet R, Vujinovic O, Vukotic I, Wada S, Wagner C, Wagner JM, Wagner W, Wahdan S, Wahlberg H, Wakida M, Walder J, Walker R, Walkowiak W, Wall A, Wamorkar T, Wang AZ, Wang C, Wang C, Wang H, Wang J, Wang RJ, Wang R, Wang R, Wang SM, Wang S, Wang T, Wang WT, Wang W, Wang X, Wang X, Wang X, Wang Y, Wang Y, Wang Z, Wang Z, Wang Z, Warburton A, Ward RJ, Warrack N, Watson AT, Watson H, Watson MF, Watton E, Watts G, Waugh BM, Weber C, Weber HA, Weber MS, Weber SM, Wei C, Wei Y, Weidberg AR, Weik EJ, Weingarten J, Weirich M, Weiser C, Wells CJ, Wenaus T, Wendland B, Wengler T, Wenke NS, Wermes N, Wessels M, Wharton AM, White AS, White A, White MJ, Whiteson D, Wickremasinghe L, Wiedenmann W, Wiel C, Wielers M, Wiglesworth C, Wilbern DJ, Wilkens HG, Williams DM, Williams HH, Williams S, Willocq S, Wilson BJ, Windischhofer PJ, Winkel FI, Winklmeier F, Winter BT, Winter JK, Wittgen M, Wobisch M, Wolffs Z, Wollrath J, Wolter MW, Wolters H, Wongel AF, Woodward EL, Worm SD, Wosiek BK, Woźniak KW, Wozniewski S, Wraight K, Wu C, Wu J, Wu M, Wu M, Wu SL, Wu X, Wu Y, Wu Z, Wuerzinger J, Wyatt TR, Wynne BM, Xella S, Xia L, Xia M, Xiang J, Xie M, Xie X, Xin S, Xiong A, Xiong J, Xu D, Xu H, Xu L, Xu R, Xu T, Xu Y, Xu Z, Xu Z, Yabsley B, Yacoob S, Yamaguchi Y, Yamashita E, Yamauchi H, Yamazaki T, Yamazaki Y, Yan J, Yan S, Yan Z, Yang HJ, Yang HT, Yang S, Yang T, Yang X, Yang X, Yang Y, Yang Y, Yang Z, Yao WM, Yap YC, Ye H, Ye H, Ye J, Ye S, Ye X, Yeh Y, Yeletskikh I, Yeo B, Yexley MR, Yin P, Yorita K, Younas S, Young CJS, Young C, Yu C, Yu Y, Yuan M, Yuan R, Yue L, Zaazoua M, Zabinski B, Zaid E, Zak ZK, Zakareishvili T, Zakharchuk N, Zambito S, Zamora Saa JA, Zang J, Zanzi D, Zaplatilek O, Zeitnitz C, Zeng H, Zeng JC, Zenger DT, Zenin O, Ženiš T, Zenz S, Zerradi S, Zerwas D, Zhai M, Zhang B, Zhang DF, Zhang J, Zhang J, Zhang K, Zhang L, Zhang P, Zhang R, Zhang S, Zhang S, Zhang T, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng J, Zheng K, Zheng X, Zheng Z, Zhong D, Zhou B, Zhou H, Zhou N, Zhou Y, Zhu CG, Zhu J, Zhu Y, Zhu Y, Zhuang X, Zhukov K, Zhulanov V, Zimine NI, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L. Search for the Exclusive W Boson Hadronic Decays W^{±}→π^{±}γ, W^{±}→K^{±}γ and W^{±}→ρ^{±}γ with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2024; 133:161804. [PMID: 39485985 DOI: 10.1103/physrevlett.133.161804] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 07/15/2024] [Indexed: 11/03/2024]
Abstract
A search for the exclusive hadronic decays W^{±}→π^{±}γ, W^{±}→K^{±}γ, and W^{±}→ρ^{±}γ is performed using up to 140 fb^{-1} of proton-proton collisions recorded with the ATLAS detector at a center-of-mass energy of sqrt[s]=13 TeV. If observed, these rare processes would provide a unique test bench for the quantum chromodynamics factorization formalism used to calculate cross sections at colliders. Additionally, at future colliders, these decays could offer a new way to measure the W boson mass through fully reconstructed decay products. The search results in the most stringent upper limits to date on the branching fractions B(W^{±}→π^{±}γ)<1.9×10^{-6}, B(W^{±}→K^{±}γ)<1.7×10^{-6}, B(W^{±}→ρ^{±}γ)<5.2×10^{-6} at 95% confidence level.
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Wang S, Lu H, Su M, He J, Tang Y, Ying Y, Chen Z, Zhu Q, Ge RS, Li H, Li X. Bisphenol H exposure disrupts Leydig cell function in adult rats via oxidative stress-mediated m6A modifications: Implications for reproductive toxicity. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 285:117061. [PMID: 39303633 DOI: 10.1016/j.ecoenv.2024.117061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2024] [Revised: 09/13/2024] [Accepted: 09/14/2024] [Indexed: 09/22/2024]
Abstract
Bisphenol H (BPH) has emerged as a potential alternative to bisphenol A (BPA), which has been curtailed for use due to concerns over its reproductive and endocrine toxicity. This study investigates whether BPH exerts antiandrogenic effects by impairing Leydig cell function, a critical component in testosterone production. We administered orally BPH to adult male rats at doses of 0, 1, 10, and 100 mg/kg/day for 7 days. Notably, BPH treatment resulted in a dose-dependent reduction in testicular testosterone levels, with significant decreases observed at ≥ 1 mg/kg/day. Additionally, BPH affected the expression of key genes involved in steroidogenesis and cholesterol metabolism, including Nr5a1, Nr3c4, Lhcgr, Scarb1, and Star, at higher doses (10 and/or 100 mg/kg/day). The study also revealed alterations in antioxidant gene expression (Sod2 and Cat) and modulation of m6A-related genes (Ythdf1-3 and Foxo3) and their proteins. Through MeRIP-qPCR analysis, we identified increased m6A modifications in Scarb1 and Star genes following BPH exposure. In vitro experiments with primary Leydig cells confirmed that BPH enhanced oxidative stress and diminished testosterone production, which were partially mitigated by antioxidant vitamin E supplementation and Ythdf3 knockdown. Meanwhile, simultaneous administration of BPH and vitamin E to primary Leydig cells partially counteracted BPH-induced alterations in the Ythdf3 expression. Our findings underscore a novel mechanism by which BPH disrupts Leydig cell function through the oxidative stress-m6A modification-autophagy pathway, raising concerns about its potential reproductive toxicity.
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Zhao YA, Li WC, Wei PJ, Yan YM, Li H, Chang JK, Cui JN, Zhang FW, Fang F, Li SG, Dong J, Zhao GZ, Ouyang WB, Pan XB. [Mid- and long-term outcomes of percutaneous balloon mitral valvuloplasty guided solely by echocardiography]. ZHONGHUA YI XUE ZA ZHI 2024; 104:3575-3579. [PMID: 39414585 DOI: 10.3760/cma.j.cn112137-20240429-01005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 10/18/2024]
Abstract
Objective: To evaluate the mid-and long-term clinical outcomes of percutaneous balloon mitral valvuloplasty (PBMV) guided solely by echocardiography. Methods: A total of 71 patients with moderate to severe mitral stenosis who underwent PBMV guided solely by echocardiography at Fuwai Hospital, Chinese Academy of Medical Sciences, from January 2016 to December 2022 were retrospectively included. The clinical data and follow-up information were collected and analyzed. Results: Finally, 71 patients (11 males and 60 females) aged (48.6±12.4) years, including 3 pregnant women were included. One patient required surgical intervention due to moderate to severe mitral regurgitation, resulting in a procedure success rate of 98.6% (70/71). The procedural duration was (84.1±40.2) minutes, with the balloon diameter of (26.5±1.1) mm and number of dilatations of 2.9±0.7. The mean mitral transvalvular pressure gradient decreased from (12.6±6.1) mmHg (1 mmHg=0.133 kPa) preoperatively to (5.4±2.4) mmHg postoperatively, while the mitral valve orifice area increased from (0.9±0.2) cm² to (1.7±0.3) cm² (both P<0.001). Before discharge, 16 patients developed new mild mitral regurgitation, five developed new moderate mitral regurgitation, and one patient had a small amount of pericardial effusion absorbed by herself. No severe complications such as death, pericardial tamponade, or thromboembolism occurred during the perioperative period. The average follow-up duration was 12-84 (49.7±21.4) months. At two years postoperatively, the mean mitral transvalvular pressure gradient was (6.2±2.5) mmHg, and the mitral valve orifice area was (1.6±0.3) cm². Eight patients underwent surgical mitral valve replacement at an median of [M(Q1, Q3)] 18 (5, 53) months postoperatively, and one patient died during the follow-up period due to non-cardiac reasons. Conclusion: The mid-and long-term outcomes of PBMV guided solely by echocardiography are favorable.
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Kim J, Kim J, Seo KH, Lee KH, Park YH, Lin CH, Lu YS, Ueno T, Yap YS, Wong FY, Tan VKM, Lim GH, Tan SM, Yeo W, Liu Q, Leung R, Naito Y, Li H, Lee HB, Han W, Im SA. Survival outcomes of young-age female patients with early breast cancer: an international multicenter cohort study. ESMO Open 2024; 9:103732. [PMID: 39413678 PMCID: PMC11530587 DOI: 10.1016/j.esmoop.2024.103732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 08/05/2024] [Accepted: 08/29/2024] [Indexed: 10/18/2024] Open
Abstract
BACKGROUND The incidence of breast cancer among young Asian women is increasing, yet they remain underrepresented in global data. We analyzed the epidemiology and outcomes of Asian patients with breast cancer <40 years old across different subtypes to identify their clinical unmet needs. PATIENTS AND METHODS Female patients aged ≥20 years diagnosed with early breast cancer were analyzed from the prospective cohort of the Asian Breast Cancer Cooperative Group (ABCCG). For comparison, data from the Surveillance, Epidemiology, and End Results Program (SEER) cancer registry were used. Patients were categorized into three age groups: young (<40 years), alleged premenopausal mid-age (40-49 years), and alleged postmenopausal (aged ≥50 years). Multivariable Cox proportional hazards models for survival were adjusted for subtypes, histologic grade, T stage, nodal status, and study centers. RESULTS A total of 45 021 patients with breast cancer from Asian study centers, 496 332 SEER-White patients, and 18 279 SEER-Asian patients were included in the analysis. The median age at diagnosis was younger in the Asian cohort (51 years) compared with SEER-Whites (62 years) and SEER-Asians (58 years; P < 0.0001). In the young-age group, hormone receptor-positive/human epidermal growth factor receptor 2 negative (HR+/HER2-) breast cancer was more prevalent among Asians and SEER-Asians compared with SEER-Whites (61.2% and 59.8% versus 54.7%). In the Asian population, young patients with HR+/HER2- breast cancer exhibited significantly inferior overall survival than the mid-age group (6-year overall survival 94.4% versus 96.6%; mid-age to young-age group hazard ratio 0.62; P < 0.001). Similarly, young patients in SEER-Whites showed an earlier decline in survival compared with the mid-age group (89.1% versus 94.0%; P < 0.001). CONCLUSION ABCCG-Asian patients with breast cancer <40 years old with HR+/HER2- subtypes were more likely to have worse survival outcomes than their mid-age counterparts. Our study highlights the poorer prognosis of young patients and underscores the need for a tailored therapeutic approach, such as ovarian function suppression, particularly considering ethnic factors.
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Combination and summary of ATLAS dark matter searches interpreted in a 2HDM with a pseudo-scalar mediator using 139 fb -1 of s=13 TeV pp collision data. Sci Bull (Beijing) 2024; 69:3005-3035. [PMID: 39179456 DOI: 10.1016/j.scib.2024.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/03/2023] [Accepted: 05/27/2024] [Indexed: 08/26/2024]
Abstract
Results from a wide range of searches targeting different experimental signatures with and without missing transverse momentum (ETmiss) are used to constrain a Two-Higgs-Doublet Model (2HDM) with an additional pseudo-scalar mediating the interaction between ordinary and dark matter (2HDM+a). The analyses use up to 139 fb-1 of proton-proton collision data at a centre-of-mass energy s=13 TeV recorded with the ATLAS detector at the Large Hadron Collider during 2015-2018. The results from three of the most sensitive searches are combined statistically. These searches target signatures with large ETmiss and a leptonically decaying Z boson; large ETmiss and a Higgs boson decaying to bottom quarks; and production of charged Higgs bosons in final states with top and bottom quarks, respectively. Constraints are derived for several common and new benchmark scenarios in the 2HDM+a.
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XS, Qin ZH, Qiu JF, Qu SQ, Rashid KH, Redmer CF, Ren KJ, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Ruan SN, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan KY, Shan W, Shan XY, Shangguan JF, Shao LG, Shao M, Shen CP, Shen HF, Shen WH, Shen XY, Shi BA, Shi HC, Shi JY, Shi QQ, Shi RS, Shi X, Song JJ, Song WM, Song YX, Sosio S, Spataro S, Stieler F, Su PP, Su YJ, Sun GX, Sun H, Sun HK, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YZ, Sun ZT, Tan YX, Tang CJ, Tang GY, Tang J, Tao LY, Tao QT, Tat M, Teng JX, Thoren V, Tian WH, Tian Y, Uman I, Wang B, Wang B, Wang BL, Wang CW, Wang DY, Wang F, Wang HJ, Wang HP, Wang K, Wang LL, Wang M, Wang MZ, Wang M, Wang S, Wang S, Wang T, Wang TJ, Wang W, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YH, Wang YQ, Wang Y, Wang Z, Wang ZY, Wang Z, Wei DH, Weidner F, Wen SP, White DJ, Wiedner U, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu XH, Wu Y, Wu YJ, Wu Z, Xia L, Xiang T, Xiao D, Xiao GY, Xiao H, Xiao SY, Xiao YL, Xiao ZJ, Xie C, Xie XH, Xie Y, Xie YG, Xie YH, Xie ZP, Xing TY, Xu CF, Xu CJ, Xu GF, Xu HY, Xu QJ, Xu XP, Xu YC, Xu ZP, Yan F, Yan L, Yan WB, Yan WC, Yang HJ, Yang HL, Yang HX, Yang SL, Yang T, Yang YF, Yang YX, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu T, Yu XD, Yuan CZ, Yuan L, Yuan SC, Yuan XQ, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng FR, Zeng X, Zeng Y, Zhai XY, Zhan YH, Zhang AQ, Zhang BL, Zhang BX, Zhang DH, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HQ, Zhang HY, Zhang JL, Zhang JQ, Zhang JW, Zhang JX, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang LM, Zhang LQ, Zhang L, Zhang P, Zhang QY, Zhang S, Zhang S, Zhang XD, Zhang XM, Zhang XY, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZH, Zhang ZL, Zhang ZY, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng WJ, Zheng YH, Zhong B, Zhong C, Zhong X, Zhou H, Zhou LP, Zhou X, Zhou XK, Zhou XR, Zhou XY, Zhou YZ, Zhu J, Zhu K, Zhu KJ, Zhu LX, Zhu SH, Zhu SQ, Zhu TJ, Zhu WJ, Zhu YC, Zhu ZA, Zou JH, Zu J. Extracting the femtometer structure of strange baryons using the vacuum polarization effect. Nat Commun 2024; 15:8812. [PMID: 39394218 PMCID: PMC11470094 DOI: 10.1038/s41467-024-51802-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 08/19/2024] [Indexed: 10/13/2024] Open
Abstract
One of the fundamental goals of particle physics is to gain a microscopic understanding of the strong interaction. Electromagnetic form factors quantify the structure of hadrons in terms of charge and magnetization distributions. While the nucleon structure has been investigated extensively, data on hyperons are still scarce. It has recently been demonstrated that electron-positron annihilations into hyperon-antihyperon pairs provide a powerful tool to investigate their inner structure. We present a method useful for hyperon-antihyperon pairs of different types which exploits the cross section enhancement due to the effect of vacuum polarization at the J/ψ resonance. Using the 10 billion J/ψ events collected with the BESIII detector, this allows a precise determination of the hyperon structure function. The result is essentially a precise snapshot of theΛ ¯ Σ 0 ( Λ Σ ¯ 0 ) transition process, encoded in the transition form factor ratio and phase. Their values are measured to be R = 0.860 ± 0.029(stat.) ± 0.015(syst.), Δ Φ Λ ¯ Σ 0 = ( 1.011 ± 0.094 ( stat. ) ± 0.010 ( syst. ) ) r a d and Δ Φ Λ Σ ¯ 0 = ( 2.128 ± 0.094 ( stat. ) ± 0.010 ( syst. ) ) r a d . Furthermore, charge-parity (CP) breaking is investigated in this reaction and found to be consistent with CP symmetry.
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Grants
- The BESIII collaboration thanks the staff of BEPCII and the IHEP computing center for their strong support. This work is supported in part by National Key R&D Program of China under Contracts Nos. 2020YFA0406300, 2020YFA0406400; National Natural Science Foundation of China (NSFC) under Contracts Nos. 11635010, 11735014, 11835012, 11875115, 11935015, 11935016, 11935018, 11961141012, 12022510, 12025502, 12035009, 12035013, 12075250, 12165022, 12192260, 12192261, 12192262, 12192263, 12192264, 12192265, 12225509; the Chinese Academy of Sciences (CAS) Large-Scale Scientific Facility Program; Joint Large-Scale Scientific Facility Funds of the NSFC and CAS under Contract No. U1832207; the CAS Center for Excellence in Particle Physics (CCEPP); 100 Talents Program of CAS; The Institute of Nuclear and Particle Physics (INPAC) and Shanghai Key Laboratory for Particle Physics and Cosmology; Yunnan Fundamental Research Project under Contract No. 202301AT070162; ERC under Contract No. 758462; European Union's Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement under Contract No. 894790; German Research Foundation DFG under Contracts Nos. 443159800, 455635585, Collaborative Research Center CRC 1044, FOR5327, GRK 2149; Istituto Nazionale di Fisica Nucleare, Italy; Ministry of Development of Turkey under Contract No. DPT2006K-120470; National Science and Technology fund; National Science Research and Innovation Fund (NSRF) via the Program Management Unit for Human Resources & Institutional Development, Research and Innovation under Contract No. B16F640076; Olle Engkvist Foundation under Contract No. 200-0605; STFC (United Kingdom); Suranaree University of Technology (SUT), Thailand Science Research and Innovation (TSRI), and National Science Research and Innovation Fund (NSRF) under Contract No. 160355; Polish National Science Centre under Contract 2019/35/O/ST2/02907; The Royal Society, UK under Contracts Nos. DH140054, DH160214; The Knut and Alice Wallenberg Foundation (Sweden); The Swedish Research Council; The Swedish Foundation for International Cooperation in Research and Higher Education (STINT); U. S. Department of Energy under Contract No. DE-FG02-05ER41374.
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Li H, Oliver A, Shields RK, Kamat S, Stone G, Estabrook M. Molecular characterization of clinically isolated Pseudomonas aeruginosa with varying resistance to ceftazidime-avibactam and ceftolozane-tazobactam collected as a part of the ATLAS global surveillance program from 2020 to 2021. Antimicrob Agents Chemother 2024; 68:e0067024. [PMID: 39254297 PMCID: PMC11459925 DOI: 10.1128/aac.00670-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Accepted: 08/08/2024] [Indexed: 09/11/2024] Open
Abstract
Ceftazidime-avibactam (CZA) and ceftolozane-tazobactam (C/T) are important agents for treating multidrug-resistant P. aeruginosa infections. In this study, we evaluated the molecular characteristics of 300 globally collected clinical P. aeruginosa isolates non-susceptible (NS) to CZA, C/T, or both agents. Isolates were CZA-NS and C/T-NS (n = 57), CZA-susceptible (S) and C/T-NS (n = 145), or CZA-NS and C/T-S (n = 98) selected from the Antimicrobial Testing Leadership and Surveillance (ATLAS) surveillance program from 2020 to 2021. Characterization was by whole-genome sequencing. Analysis was performed to identify β-lactamase genes and mutations that impact efflux regulation, AmpC regulation, and target binding (PBP3). Of the 57 CZA-NS+C/T-NS isolates, 64.9% carried a metallo-β-lactamase (MBL), and a cumulative 84.2% carried any non-intrinsic β-lactamase [i.e., not Pseudomonas-derived cephalosporinase (PDC) or OXA-50-like]. Of the 145 CZA-S+C/T-NS isolates, 26.2% carried an extended-spectrum β-lactamase (ESBL) and no carbapenemase, 17.9% carried a serine-carbapenemase, and 42.1% were negative for non-intrinsic β-lactamases. Of 98 CZA-NS+C/T-S isolates, 34.7% carried mutations previously described as causing an upregulation of the MexAB-OprM efflux pump, while only 9.2% carried a non-intrinsic β-lactamase, and no resistance mechanism was identified in 29.6% of these isolates. MBLs were present in most isolates NS to both agents. More than half of the CZA-S+C/T-NS isolates carried serine β-lactamases. The most frequently identified resistance mechanism identified in CZA-NS+C/T-S isolates was a marker indicating the upregulation of MexAB-OprM. No mechanism was identified that is thought to support resistance to these agents in numerous isolates. This may be due in part to the fact that whole genome sequencing (WGS) cannot directly measure gene expression of chromosomal resistance mechanisms.
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Ruby AJ, Ruelas Rivera VH, Ruggeri TA, Ruggiero A, Ruiz-Martinez A, Rummler A, Rurikova Z, Rusakovich NA, Russell HL, Russo G, Rutherfoord JP, Rutherford Colmenares S, Rybacki K, Rybar M, Rye EB, Ryzhov A, Sabater Iglesias JA, Sabatini P, Sadrozinski HFW, Safai Tehrani F, Safarzadeh Samani B, Safdari M, Saha S, Sahinsoy M, Saibel A, Saimpert M, Saito M, Saito T, Salamani D, Salnikov A, Salt J, Salvador Salas A, Salvatore D, Salvatore F, Salzburger A, Sammel D, Sampsonidis D, Sampsonidou D, Sánchez J, Sanchez Pineda A, Sanchez Sebastian V, Sandaker H, Sander CO, Sandesara JA, Sandhoff M, Sandoval C, Sankey DPC, Sano T, Sansoni A, Santi L, Santoni C, Santos H, Santra A, Saoucha KA, Saraiva JG, Sardain J, Sasaki O, Sato K, Sauer C, Sauerburger F, Sauvan E, Savard P, Sawada R, Sawyer C, Sawyer L, Sayago Galvan I, Sbarra C, Sbrizzi A, Scanlon T, Schaarschmidt J, Schacht P, Schäfer U, Schaffer AC, Schaile D, Schamberger RD, Scharf C, Schefer MM, Schegelsky VA, Scheirich D, Schenck F, Schernau M, Scheulen C, Schiavi C, Schioppa EJ, Schioppa M, Schlag B, Schleicher KE, Schlenker S, Schmeing J, Schmidt MA, Schmieden K, Schmitt C, Schmitt N, Schmitt S, Schoeffel L, Schoening A, Scholer PG, Schopf E, Schott M, Schovancova J, Schramm S, Schroeder F, Schroer T, Schultz-Coulon HC, Schumacher M, Schumm BA, Schune P, Schuy AJ, Schwartz HR, Schwartzman A, Schwarz TA, Schwemling P, Schwienhorst R, Sciandra A, Sciolla G, Scuri F, Sebastiani CD, Sedlaczek K, Seema P, Seidel SC, Seiden A, Seidlitz BD, Seitz C, Seixas JM, Sekhniaidze G, Selem L, Semprini-Cesari N, Sengupta D, Senthilkumar V, Serin L, Serkin L, Sessa M, Severini H, Sforza F, Sfyrla A, Shabalina E, Shaheen R, Shahinian JD, Shaked Renous D, Shan LY, Shapiro M, Sharma A, Sharma AS, Sharma P, Sharma S, Shatalov PB, Shaw K, Shaw SM, Shcherbakova A, Shen Q, Sheppard DJ, Sherwood P, Shi L, Shi X, Shimmin CO, Shinner JD, Shipsey IPJ, Shirabe S, Shiyakova M, Shlomi J, Shochet MJ, Shojaii J, Shope DR, Shrestha B, Shrestha S, Shrif EM, Shroff MJ, Sicho P, Sickles AM, Sideras Haddad E, Sidoti A, Siegert F, Sijacki D, Sili F, Silva JM, Silva Oliveira MV, Silverstein SB, Simion S, Simoniello R, Simpson EL, Simpson H, Simpson LR, Simpson ND, Simsek S, Sindhu S, Sinervo P, Singh S, Sinha S, Sinha S, Sioli M, Siral I, Sitnikova E, Sivoklokov SY, Sjölin J, Skaf A, Skorda E, Skubic P, Slawinska M, Smakhtin V, Smart BH, Smirnov SY, Smirnov Y, Smirnova LN, Smirnova O, Smith AC, Smith EA, Smith HA, Smith JL, Smith R, Smizanska M, Smolek K, Snesarev AA, Snider SR, Snoek HL, Snyder S, Sobie R, Soffer A, Solans Sanchez CA, Soldatov EY, Soldevila U, Solodkov AA, Solomon S, Soloshenko A, Solovieva K, Solovyanov OV, Solovyev V, Sommer P, Sonay A, Song WY, Sonneveld JM, Sopczak A, Sopio AL, Sopkova F, Sorenson JD, Sotarriva Alvarez IR, Sothilingam V, Soto Sandoval OJ, Sottocornola S, Soualah R, Soumaimi Z, South D, Soybelman N, Spagnolo S, Spalla M, Sperlich D, Spigo G, Spinali S, Spiteri DP, Spousta M, Staats EJ, Stabile A, Stamen R, Stampekis A, Standke M, Stanecka E, Stange MV, Stanislaus B, Stanitzki MM, Stapf B, Starchenko EA, Stark GH, Stark J, Starko DM, Staroba P, Starovoitov P, Stärz S, Staszewski R, Stavropoulos G, Steentoft J, Steinberg P, Stelzer B, Stelzer HJ, Stelzer-Chilton O, Stenzel H, Stevenson TJ, Stewart GA, Stewart JR, Stockton MC, Stoicea G, Stolarski M, Stonjek S, Straessner A, Strandberg J, Strandberg S, Stratmann M, Strauss M, Strebler T, Strizenec P, Ströhmer R, Strom DM, Stroynowski R, Strubig A, Stucci SA, Stugu B, Stupak J, Styles NA, Su D, Su S, Su W, Su X, Sugizaki K, Sulin VV, Sullivan MJ, Sultan DMS, Sultanaliyeva L, Sultansoy S, Sumida T, Sun S, Sun S, Gudnadottir OS, Sur N, Sutton MR, Suzuki H, Svatos M, Swiatlowski M, Swirski T, Sykora I, Sykora M, Sykora T, Ta D, Tackmann K, Taffard A, Tafirout R, Tafoya Vargas JS, Takeva EP, Takubo Y, Talby M, Talyshev AA, Tam KC, Tamir NM, Tanaka A, Tanaka J, Tanaka R, Tanasini M, Tao Z, Tapia Araya S, Tapprogge S, Tarek Abouelfadl Mohamed A, Tarem S, Tariq K, Tarna G, Tartarelli GF, Tas P, Tasevsky M, Tassi E, Tate AC, Tateno G, Tayalati Y, Taylor GN, Taylor W, Tee AS, Teixeira De Lima R, Teixeira-Dias P, Teoh JJ, Terashi K, Terron J, Terzo S, Testa M, Teuscher RJ, Thaler A, Theiner O, Themistokleous N, Theveneaux-Pelzer T, Thielmann O, Thomas DW, Thomas JP, Thompson EA, Thompson PD, Thomson E, Tian Y, Tikhomirov V, Tikhonov YA, Timoshenko S, Timoshyn D, Ting EXL, Tipton P, Tlou SH, Tnourji A, Todome K, Todorova-Nova S, Todt S, Togawa M, Tojo J, Tokár S, Tokushuku K, Toldaiev O, Tombs R, Tomoto M, Tompkins L, Topolnicki KW, Torrence E, Torres H, Torró Pastor E, Toscani M, Tosciri C, Tost M, Tovey DR, Traeet A, Trandafir IS, Trefzger T, Tricoli A, Trigger IM, Trincaz-Duvoid S, Trischuk DA, Trocmé B, Troncon C, Truong L, Trzebinski M, Trzupek A, Tsai F, Tsai M, Tsiamis A, Tsiareshka PV, Tsigaridas S, Tsirigotis A, Tsiskaridze V, Tskhadadze EG, Tsopoulou M, Tsujikawa Y, Tsukerman II, Tsulaia V, Tsuno S, Tsuri K, Tsybychev D, Tu Y, Tudorache A, Tudorache V, Tuna AN, Turchikhin S, Turk Cakir I, Turra R, Turtuvshin T, Tuts PM, Tzamarias S, Tzanis P, Tzovara E, Ukegawa F, Ulloa Poblete PA, Umaka EN, Unal G, Unal M, Undrus A, Unel G, Urban J, Urquijo P, Urrejola P, Usai G, Ushioda R, Usman M, Uysal Z, Vacek V, Vachon B, Vadla KOH, Vafeiadis T, Vaitkus A, Valderanis C, Valdes Santurio E, Valente M, Valentinetti S, Valero A, Valiente Moreno E, Vallier A, Valls Ferrer JA, Van Arneman DR, Van Daalen TR, Van Der Graaf A, Van Gemmeren P, Van Rijnbach M, Van Stroud S, Van Vulpen I, Vanadia M, Vandelli W, Vandenbroucke M, Vandewall ER, Vannicola D, Vannoli L, Vari R, Varnes EW, Varni C, Varol T, Varouchas D, Varriale L, Varvell KE, Vasile ME, Vaslin L, Vasquez GA, Vasyukov A, Vazeille F, Vazquez Schroeder T, Veatch J, Vecchio V, Veen MJ, Veliscek I, Veloce LM, Veloso F, Veneziano S, Ventura A, Ventura Gonzalez S, Verbytskyi A, Verducci M, Vergis C, Verissimo De Araujo M, Verkerke W, Vermeulen JC, Vernieri C, Vessella M, Vetterli MC, Vgenopoulos A, Viaux Maira N, Vickey T, Vickey Boeriu OE, Viehhauser GHA, Vigani L, Villa M, Villaplana Perez M, Villhauer EM, Vilucchi E, Vincter MG, Virdee GS, Vishwakarma A, Visibile A, Vittori C, Vivarelli I, Voevodina E, Vogel F, Voigt JC, Vokac P, Volkotrub Y, Von Ahnen J, Von Toerne E, Vormwald B, Vorobel V, Vorobev K, Vos M, Voss K, Vossebeld JH, Vozak M, Vozdecky L, Vranjes N, Vranjes Milosavljevic M, Vreeswijk M, Vu NK, Vuillermet R, Vujinovic O, Vukotic I, Wada S, Wagner C, Wagner JM, Wagner W, Wahdan S, Wahlberg H, Wakida M, Walder J, Walker R, Walkowiak W, Wall A, Wamorkar T, Wang AZ, Wang C, Wang C, Wang H, Wang J, Wang RJ, Wang R, Wang R, Wang SM, Wang S, Wang T, Wang WT, Wang W, Wang X, Wang X, Wang X, Wang Y, Wang Y, Wang Z, Wang Z, Wang Z, Warburton A, Ward RJ, Warrack N, Watson AT, Watson H, Watson MF, Watton E, Watts G, Waugh BM, Weber C, Weber HA, Weber MS, Weber SM, Wei C, Wei Y, Weidberg AR, Weik EJ, Weingarten J, Weirich M, Weiser C, Wells CJ, Wenaus T, Wendland B, Wengler T, Wenke NS, Wermes N, Wessels M, Wharton AM, White AS, White A, White MJ, Whiteson D, Wickremasinghe L, Wiedenmann W, Wielers M, Wiglesworth C, Wilbern DJ, Wilkens HG, Williams DM, Williams HH, Williams S, Willocq S, Wilson BJ, Windischhofer PJ, Winkel FI, Winklmeier F, Winter BT, Winter JK, Wittgen M, Wobisch M, Wolffs Z, Wollrath J, Wolter MW, Wolters H, Wongel AF, Woodward EL, Worm SD, Wosiek BK, Woźniak KW, Wozniewski S, Wraight K, Wu C, Wu J, Wu M, Wu M, Wu SL, Wu X, Wu Y, Wu Z, Wuerzinger J, Wyatt TR, Wynne BM, Xella S, Xia L, Xia M, Xiang J, Xie M, Xie X, Xin S, Xiong A, Xiong J, Xu D, Xu H, Xu L, Xu R, Xu T, Xu Y, Xu Z, Xu Z, Yabsley B, Yacoob S, Yamaguchi Y, Yamashita E, Yamauchi H, Yamazaki T, Yamazaki Y, Yan J, Yan S, Yan Z, Yang HJ, Yang HT, Yang S, Yang T, Yang X, Yang X, Yang Y, Yang Y, Yang Z, Yao WM, Yap YC, Ye H, Ye H, Ye J, Ye S, Ye X, Yeh Y, Yeletskikh I, Yeo BK, Yexley MR, Yin P, Yorita K, Younas S, Young CJS, Young C, Yu C, Yu Y, Yuan M, Yuan R, Yue L, Zaazoua M, Zabinski B, Zaid E, Zak ZK, Zakareishvili T, Zakharchuk N, Zambito S, Zamora Saa JA, Zang J, Zanzi D, Zaplatilek O, Zeitnitz C, Zeng H, Zeng JC, Zenger DT, Zenin O, Ženiš T, Zenz S, Zerradi S, Zerwas D, Zhai M, Zhang DF, Zhang J, Zhang J, Zhang K, Zhang L, Zhang P, Zhang R, Zhang S, Zhang S, Zhang T, Zhang X, Zhang X, Zhang Y, Zhang Y, Zhang Y, Zhang Z, Zhang Z, Zhao H, Zhao T, Zhao Y, Zhao Z, Zhemchugov A, Zheng J, Zheng K, Zheng X, Zheng Z, Zhong D, Zhou B, Zhou H, Zhou N, Zhou Y, Zhu CG, Zhu J, Zhu Y, Zhu Y, Zhuang X, Zhukov K, Zhulanov V, Zimine NI, Zinsser J, Ziolkowski M, Živković L, Zoccoli A, Zoch K, Zorbas TG, Zormpa O, Zou W, Zwalinski L. Determination of the Relative Sign of the Higgs Boson Couplings to W and Z Bosons Using WH Production via Vector-Boson Fusion with the ATLAS Detector. PHYSICAL REVIEW LETTERS 2024; 133:141801. [PMID: 39423379 DOI: 10.1103/physrevlett.133.141801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 07/09/2024] [Accepted: 08/22/2024] [Indexed: 10/21/2024]
Abstract
The associated production of Higgs and W bosons via vector-boson fusion is highly sensitive to the relative sign of the Higgs boson couplings to W and Z bosons. In this Letter, two searches for this process are presented, using 140 fb^{-1} of proton-proton collision data at sqrt[s]=13 TeV recorded by the ATLAS detector at the LHC. The first search targets scenarios with opposite-sign couplings of the W and Z bosons to the Higgs boson, while the second targets standard model-like scenarios with same-sign couplings. Both analyses consider Higgs boson decays into a pair of b quarks and W boson decays with an electron or muon. The data exclude the opposite-sign coupling hypothesis with a significance beyond 5σ, and the observed (expected) upper limit set on the cross section for vector-boson fusion WH production is 9.0 (8.7) times the standard model value at 95% confidence level.
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Li H, Li S, Zhang H, Gu J, Dai Y, Wu R, Wang Y, Han R, Sun G, Zhang Y, Li H, Zhao Y, Li G. Integrated GWAS and transcriptome analysis reveals key genes associated with muscle fibre and fat traits in Gushi chicken. Br Poult Sci 2024:1-11. [PMID: 39364777 DOI: 10.1080/00071668.2024.2400685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 05/13/2024] [Indexed: 10/05/2024]
Abstract
1. In the following experiment meat quality traits of a Gushi-Anka F2 resource population were measured, and their heritability estimated. Intramuscular fat (IMF) had medium heritability (0.35) but leg muscle fibre density (LMD), leg muscle fibre diameter (LMF), breast muscle fibre density (BMD), fresh fat content (FFA), and absolute dry fat content (AFC) had low heritability (0-0.2). The IMF presented the most important genetic additive effect among the poultry meat quality-related traits studied.2. The phenotypic data of meat quality traits in the Gushi-Anka F2 resource population were combined with genotyping by sequencing (GBS) data to obtain genotype data. Six meat quality traits in 734 birds were analysed by GWAS. Based on these variants, 83 significant (-log10(p) > 4.42) single nucleotide polymorphisms and four quantitative trait loci (QTL) regions corresponding to 175 genes were identified. Further linkage disequilibrium (LD) analysis was conducted on chromosome 13 (Chr13) and chromosome 27 (Chr27) QTL regions.3. Based on the transcriptome data and GWAS results, 12 shared genes - ITGB3, DNAJC27, ETV4, C7orf50, FKBP1B, G3BP1, IGF2BP1, KCNH6, LOC416263, SCARA5, SMIM5 and TBL1XR1 were identified as candidate genes influencing muscle fibre and fat traits.
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Sandalova E, Li H, Guan L, Raj SD, Lim TG, Tian E, Kennedy BK, Maier AB. Testing the amount of nicotinamide mononucleotide and urolithin A as compared to the label claim. GeroScience 2024; 46:5075-5083. [PMID: 38935229 PMCID: PMC11335992 DOI: 10.1007/s11357-024-01257-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Accepted: 06/12/2024] [Indexed: 06/28/2024] Open
Abstract
Healthy Longevity Medicine aims to optimize health by targeting aging processes across the lifespan. Addressing accelerated aging involves adaptation of lifestyle and the use of geroprotective drugs and supplements, including nutritional supplements and bioactive compounds. The Food and Drug Administration, under the Dietary Supplement Health and Education Act, categorizes bioactive compounds and medicinal products as dietary supplements. While numerous companies sell ingredients that can be deemed geroprotectors, there's limited oversight in their quality control. Governmental safety authorities only verify the presence of prohibited compounds, not the accuracy of ingredients listed on labels.Here, Nicotinamide mononucleotide and Urolithin A supplements, easily accessible online or in pharmacies, were tested for their active ingredient content. Results showed a significant deviation from the labeled amounts, ranging from + 28.6% to -100%. This indicates a considerable disparity in the quality of geroprotective supplements.To address this variability, collaboration between and within societies representing healthcare professionals, industry and regulatory bodies is imperative to ensure the quality of geroprotective supplements.
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Song W, Liu L, Liang H, Cheng H, He W, Yin Q, Zhang Z, Lin W, Li H, Li Q, Liu W, Zhang D, Chen D, Yuan Q. m 6Am Methyltransferase PCIF1 Regulates Periodontal Inflammation. J Dent Res 2024; 103:1130-1140. [PMID: 39290151 DOI: 10.1177/00220345241271078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/19/2024] Open
Abstract
N6,2'-O-dimethyladenosine (m6Am), a common mRNA modification in eukaryotic capped mRNAs, plays a pivotal role in cellular functions and disease progression. However, its involvement in host inflammation remains elusive. Here, we demonstrate that loss of m6Am methyltransferase phosphorylated CTD interacting factor 1 (PCIF1) attenuates periodontal inflammation in whole-body and myeloid lineage-specific knockout mouse models. Pcif1 deletion inhibits macrophage phagocytosis and migration through m6Am-Csf1r signaling. In addition, colony-stimulating factor-1 receptor (CSF1R) is identified as a potential target for the treatment of periodontitis. We thus reveal a previously unrecognized role for PCIF1-mediated m6Am modification in governing macrophage responses and periodontal inflammation.
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Li H, La SK, Zhang LY, Li S, Yu ZB, Ao LM, Gao TY, Huang HT. Metabolomics and amino acid profiling of plasma reveals the metabolite profiles associated with nitrogen utilisation efficiency in primiparous dairy cows. Animal 2024; 18:101202. [PMID: 39270357 DOI: 10.1016/j.animal.2024.101202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Revised: 05/14/2024] [Accepted: 05/17/2024] [Indexed: 09/15/2024] Open
Abstract
Nitrogen (N) utilisation efficiency (NUE, milk N yield [g/d]/N intake [g/d]) is an important performance indicator in dairy farming. Determining the NUE-associated blood metabolite profile will contribute to the optimisation of nutritional strategies to further improve NUE among dairy cows. Here, 20 primiparous lactating cows with days in milk ranging from 95 to 115 days were selected from a total of 1 221 cows. Each cow's N intake and milk N yield were measured for 7 days. Subsequently, blood samples were collected before morning feeding. Based on analysis and calculations, cows were retrospectively classified into two groups based on their NUE values, namely, a low NUE group (LNUE, NUE = 24.8 ± 1.6%, n = 10, mean ± SD) and a high NUE group (HNUE, NUE = 35.2 ± 1.7%, n = 10, mean ± SD). Plasma samples were selected from six cows in each group for metabolomics and amino acid profiling. Among the 41 differential metabolites (DMs) identified in the metabolomic analysis, sucrose, MG(0:0/22:1(13Z)/0:0), 2-amino-6-hydroxyhexanoic acid, and L-glutamine exhibited significant correlations with NUE, milk yield, and BW (P < 0.05). Moreover, the five differential amino acids and amino acid metabolites (DAAs) identified in the amino acid profiling and 5 of the 6 differential amino acids and amino acid conjugates identified by plasma metabolomics were found to be less abundant in the HNUE group (P < 0.05). Specifically, there was a 39.4% decrease in L-arginine content and a 29.2% decrease in L-glutamine content (P < 0.05). Pathway analysis indicated that the DMs and DAAs were mainly involved in arginine biosynthesis, glutathione metabolism, arginine and proline metabolism, and tryptophan metabolism (pathway impact > 0.1). These results provided new insights into the new blood metabolite profile associated with NUE in dairy cows. These new insights can provide foundational information for the formulation of new strategies to further enhance NUE in dairy cows.
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Zheng Y, Li H, Zhang K, Luo Q, Ding C, Han X, Shi H. Dual-energy CT-based radiomics for predicting pathological grading of invasive lung adenocarcinoma. Clin Radiol 2024; 79:e1226-e1234. [PMID: 39098469 DOI: 10.1016/j.crad.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 06/04/2024] [Accepted: 07/09/2024] [Indexed: 08/06/2024]
Abstract
AIMS The purpose of the study was to build a radiomics model using Dual-energy CT (DECT) to predict pathological grading of invasive lung adenocarcinoma. MATERIALS AND METHODS The retrospective study enrolled 107 patients (80 low-grade and 27 high-grade) with invasive lung adenocarcinoma before surgery. Clinical features, radiographic characteristics, and quantitative parameters were measured. Virtual monoenergetic images at 50kev and 150kev were reconstructed for extracting DECT radiomics features. To select features for constructing models, Pearson's correlation analysis, intraclass correlation coefficients, and least absolute shrinkage and selection operator penalized logistic regression were performed. Four models, including the DECT radiomics model, the clinical-DECT model, the conventional CT radiomics model, and the mixed model, were established. Area under the curve (AUC) and decision curve analysis were used to measure the performance and the clinical value of the models. RESULTS The radiomics model based on DECT exhibited outstanding performance in predicting tumor differentiation, with an AUC of 0.997 and 0.743 in the training and testing sets, respectively. Incorporating tumor density, lobulation, and effective atomic number at AP, the clinical-DECT model showed a comparable performance with an AUC of 0.836 in both the training and testing sets. In comparison to the conventional CT radiomics model (AUC of 0.998 in the training and 0.529 in the testing set) and the mixed model (AUC of 0.988 in the training and 0.707 in the testing set), the DECT radiomics model demonstrated a greater AUC value and provided patients with a more significant net benefit in the testing set. CONCLUSIONS In contrast to the conventional CT radiomics model, the DECT radiomics model produced greater predictive performance in pathological grading of invasive lung adenocarcinoma.
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Mao BP, Pan M, Shan Y, Wang YN, Li H, Wu J, Zhu X, Hu E, Cheng CY, Shangguan W. Katanin regulatory subunit B1 (KATNB1) regulates BTB dynamics through changes in cytoskeletal organization. FASEB J 2024; 38:e70049. [PMID: 39275889 DOI: 10.1096/fj.202400966r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 07/31/2024] [Accepted: 08/29/2024] [Indexed: 09/16/2024]
Abstract
In this study, we have explored the role of the KATNB1 gene, a microtubule-severing protein, in the seminiferous epithelium of the rat testis. Our data have shown that KATNB1 expressed in rat brain, testes, and Sertoli cells. KATNB1 was found to co-localize with α-tubulin showing a unique stage-specific distribution across the seminiferous epithelium. Knockdown of KATNB1 by RNAi led to significant disruption of the tight junction (TJ) permeability barrier function in primary Sertoli cells cultured in vitro with an established functional TJ-barrier, as well as perturbations in the microtubule and actin cytoskeleton organization. The disruption in these cytoskeletal structures, in turn, led to improper distribution of TJ and basal ES proteins essential for maintaining the Sertoli TJ function. More importantly, overexpression of KATNB1 in the testis in vivo was found to block cadmium-induced blood-testis barrier (BTB) disruption and testis injury. KATNB1 exerted its promoting effects on BTB and spermatogenesis through corrective spatiotemporal expression of actin- and microtubule-based regulatory proteins by maintaining the proper organization of cytoskeletons in the testis, illustrating its plausible therapeutic implication. In summary, Katanin regulatory subunit B1 (KATNB1) plays a crucial role in BTB and spermatogenesis through its effects on the actin- and microtubule-based cytoskeletons in Sertoli cells and testis, providing important insights into male reproductive biology.
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Aaij R, Abdelmotteleb ASW, Abellan Beteta C, Abudinén F, Ackernley T, Adefisoye AA, Adeva B, Adinolfi M, Adlarson P, Agapopoulou C, Aidala CA, Ajaltouni Z, Akar S, Akiba K, Albicocco P, Albrecht J, Alessio F, Alexander M, Aliouche Z, Alvarez Cartelle P, Amalric R, Amato S, Amey JL, Amhis Y, An L, Anderlini L, Andersson M, Andreianov A, Andreola P, Andreotti M, Andreou D, Anelli A, Ao D, Archilli F, Argenton M, Arguedas Cuendis S, Artamonov A, Artuso M, Aslanides E, Atzeni M, Audurier B, Bacher D, Bachiller Perea I, Bachmann S, Bachmayer M, Back JJ, Baladron Rodriguez P, Balagura V, Baldini W, Baptista de Souza Leite J, Barbetti M, Barbosa IR, Barlow RJ, Barsuk S, Barter W, Bartolini M, Bartz J, Baryshnikov F, Basels JM, Bassi G, Batsukh B, Battig A, Bay A, Beck A, Becker M, Bedeschi F, Bediaga IB, Beiter A, Belin S, Bellee V, Belous K, Belov I, Belyaev I, Benane G, Bencivenni G, Ben-Haim E, Berezhnoy A, Bernet R, Bernet Andres S, Bertella C, Bertolin A, Betancourt C, Betti F, Bex J, Bezshyiko I, Bhom J, Bieker MS, Biesuz NV, Billoir P, Biolchini A, Birch M, Bishop FCR, Bitadze A, Bizzeti A, Blake T, Blanc F, Blank JE, Blusk S, Bocharnikov V, Boelhauve JA, Boente Garcia O, Boettcher T, Bohare A, Boldyrev A, Bolognani CS, Bolzonella R, Bondar N, Borgato F, Borghi S, Borsato M, Borsuk JT, Bouchiba SA, Bowcock TJV, Boyer A, Bozzi C, Bradley MJ, Brea Rodriguez A, Breer N, Brodzicka J, Brossa Gonzalo A, Brown J, Brundu D, Buchanan E, Buonaura A, Buonincontri L, Burke AT, Burr C, Bursche A, Butkevich A, Butter JS, Buytaert J, Byczynski W, Cadeddu S, Cai H, Calabrese R, Calefice L, Cali S, Calvi M, Calvo Gomez M, Cambon Bouzas JI, Campana P, Campora Perez DH, Campoverde Quezada AF, Capelli S, Capriotti L, Caravaca-Mora R, Carbone A, Carcedo Salgado L, Cardinale R, Cardini A, Carniti P, Carus L, Casais Vidal A, Caspary R, Casse G, Castro Godinez J, Cattaneo M, Cavallero G, Cavallini V, Celani S, Cerasoli J, Cervenkov D, Cesare S, Chadwick AJ, Chahrour I, Charles M, 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Wu Y, Wyllie K, Xian S, Xiang Z, Xie Y, Xu A, Xu J, Xu L, Xu L, Xu M, Xu Z, Xu Z, Xu Z, Yang D, Yang S, Yang X, Yang Y, Yang Z, Yang Z, Yeroshenko V, Yeung H, Yin H, Yu CY, Yu J, Yuan X, Zaffaroni E, Zavertyaev M, Zdybal M, Zeng M, Zhang C, Zhang D, Zhang J, Zhang L, Zhang S, Zhang S, Zhang Y, Zhang YZ, Zhao Y, Zharkova A, Zhelezov A, Zheng XZ, Zheng Y, Zhou T, Zhou X, Zhou Y, Zhovkovska V, Zhu LZ, Zhu X, Zhu X, Zhukov V, Zhuo J, Zou Q, Zuliani D, Zunica G. Observation of New Charmonium or Charmoniumlike States in B^{+}→D^{*±}D^{∓}K^{+} Decays. PHYSICAL REVIEW LETTERS 2024; 133:131902. [PMID: 39392986 DOI: 10.1103/physrevlett.133.131902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Accepted: 08/13/2024] [Indexed: 10/13/2024]
Abstract
A study of resonant structures in B^{+}→D^{*+}D^{-}K^{+} and B^{+}→D^{*-}D^{+}K^{+} decays is performed, using proton-proton collision data at center-of-mass energies of sqrt[s]=7, 8, and 13 TeV recorded by the LHCb experiment, corresponding to an integrated luminosity of 9 fb^{-1}. A simultaneous amplitude fit is performed to the two channels with contributions from resonances decaying to D^{*-}D^{+} and D^{*+}D^{-} states linked by C parity. This procedure allows the C parities of resonances in the D^{*±}D^{∓} mass spectra to be determined. Four charmonium or charmoniumlike states are observed decaying into D^{*±}D^{∓}: η_{c}(3945), h_{c}(4000), χ_{c1}(4010), and h_{c}(4300), with quantum numbers J^{PC} equal to 0^{-+}, 1^{+-}, 1^{++}, and 1^{+-}, respectively. At least three of these states have not been observed previously. In addition, the existence of the T_{c[over ¯]s[over ¯]0}^{*}(2870)^{0} and T_{c[over ¯]s[over ¯]1}^{*}(2900)^{0} resonances in the D^{-}K^{+} mass spectrum, already observed in the B^{+}→D^{+}D^{-}K^{+} decay, is confirmed in a different production channel.
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Search for Rare Decays of D_{s}^{+} to Final States π^{+}e^{+}e^{-}, ρ^{+}e^{+}e^{-}, π^{+}π^{0}e^{+}e^{-}, K^{+}π^{0}e^{+}e^{-}, and K_{S}^{0}π^{+}e^{+}e^{-}. PHYSICAL REVIEW LETTERS 2024; 133:121801. [PMID: 39373421 DOI: 10.1103/physrevlett.133.121801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 06/21/2024] [Indexed: 10/08/2024]
Abstract
Using 7.33 fb^{-1} of e^{+}e^{-} collision data collected by the BESIII detector at center-of-mass energies in the range of sqrt[s]=4.128-4.226 GeV, we search for the rare decays D_{s}^{+}→h^{+}(h^{0})e^{+}e^{-}, where h represents a kaon or pion. By requiring the e^{+}e^{-} invariant mass to be consistent with a ϕ(1020), 0.98
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