Journal Articles, BioMed Central and SpringerOpen

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Elevated EGR1 binding at enhancers in excitatory neurons correlates with neuronal subtype-specific epigenetic regulation
Yin, Liduo; Xu, Xiguang; Conacher, Benjamin; Lin, Yu; Carrillo, Gabriela L.; Cun, Yupeng; Fox, Michael A.; Lu, Xuemei; Xie, Hehuang (2025-08-11)
Background: Brain development and neuronal cell specification are accompanied by epigenetic changes that enable the regulation of diverse gene expression patterns. During these processes, transcription factors interact with cell-type-specific epigenetic marks, binding to unique sets of cis-regulatory elements in different cell types. However, the detailed mechanisms through which cell-type-specific gene regulation is established in neurons remain to be explored. Results: In this study, we conducted a comparative histone modification analysis between excitatory and inhibitory neurons. Our results revealed that neuronal cell-type-specific histone modifications are enriched in super enhancer regions that contain abundant EGR1 motifs. Further CUT&RUN assay confirmed that excitatory neurons exhibit more EGR1 binding sites, primarily located in enhancers. Integrative analysis demonstrated that EGR1 binding is strongly correlated with various epigenetic markers of open chromatin regions and is linked to distinct gene pathways specific to neuronal subtypes. In inhibitory neurons, most genomic regions containing EGR1 binding sites become accessible during early embryonic stages, whereas super enhancers in excitatory neurons, which also host EGR1 binding sites, gain accessibility during postnatal stages. Conclusions: This study highlights the crucial role of transcription factor binding, such as EGR1, to enhancer regions, which may be key to establishing cell-type-specific gene regulation in neurons.
Lifting the profile of deep soil carbon in New Zealand’s managed planted forests
Garrett, Loretta G.; Heckman, Katherine A.; Possinger, Angela R.; Strahm, Brian D.; Hatten, Jeff A.; Fields, Fiona P.; Wakelin, Steve A. (2025-08-14)
Background: Forest soils are a globally significant carbon-store, including in deep layers (> 30 cm depth). However, there is high uncertainty regarding the response of deep soil organic carbon (DSOC) to climate change and the resulting impact on the total OC budget for forest ecosystems. Managed forests have an opportunity to reduce the risk of DSOC loss with climate change, however, the basic understanding of DSOC is lacking. Planted forests in New Zealand are managed with very limited knowledge of DSOC, both in the amount and the capacity of the soil to continue to store carbon with climate change. In this study, we explore DSOC stocks to at least 2 m depth at 15 planted forest sties in New Zealand. We also explore DSOC radiocarbon age and soil mineralogy, then contextualise our results within international SOC datasets and climate change vulnerability frameworks to identify research priorities for New Zealand’s planted forest soils. Results: DSOC stocks and soil mineralogy in New Zealand’s planted forests were diverse both horizontally across soil types and vertically throughout the soil profile. Critically, limiting measurements of SOC to the top 30 cm misses more than half of the SOC stocks present to at least 2 m depth (mean 57%; range 33–72%). At depth, mineral-associated OC was the dominant fraction of DSOC (average > 90%) and was on average much older (> 1000 years) than the current planted forest land use (< 100 years). Conclusions: This small case study highlights that New Zealand’s planted forests contain substantial stocks of DSOC, much of which is older than the current forest land use. The deep soils were dominated by reactive metals, and although the age of DSOC suggest long-term stability, the large contribution of reactive metal-mediated SOC stabilisation may indicate vulnerability to warming soil temperatures relative to other climate change factors. There is a pressing need to expand soil sampling to greater depths and establish a robust SOC baseline for New Zealand’s planted forests. This is essential for enabling spatial predictions of DSOC dynamics under future climate scenarios, identify the key controls on DSOC persistence, and concomitant impacts on forest ecosystem function and resilience.
Clarity through the neutrino fog: constraining new forces in dark matter detectors
Blanco-Mas, Pablo; Coloma, Pilar; Herrera, Gonzalo; Huber, Patrick; Kopp, Joachim; Shoemaker, Ian M.; Tabrizi, Zahra (2025-08-06)
The PandaX-4T and XENONnT experiments present indications of Coherent Elastic Neutrino Nucleus Scattering (CEνNS) from 8B solar neutrinos at 2.6σ and 2.7σ, respectively. This constitutes the first observation of the neutrino “floor” or “fog”, an irreducible background that future dark matter searches in terrestrial detectors will have to contend with. Here, we first discuss the contributions from neutrino–electron scattering and from the Migdal effect in the region of interest of these experiments, and we argue that they are non-negligible. Second, we make use of the recent PandaX-4T and XENONnT data to derive novel constraints on light scalar and vector mediators coupling to neutrinos and quarks. We demonstrate that these experiments already provide world-leading laboratory constraints on new light mediators in some regions of parameter space.
Transcriptome analysis unveils multiple reasons behind delayed and slower deposition of intramuscular fat compared to subcutaneous fat in cattle
Tan, Zhendong; Pokhrel, Binod; Zhou, Ziqi; Jiang, Honglin (2025-07-31)
Background: Intramuscular fat refers to the white adipose tissue deposited between muscle fibers, and its quantity and distribution directly impact the quality and value of beef. Compared to subcutaneous fat, intramuscular fat develops later and accumulates more slowly in cattle. The reasons for the delayed development and slower growth of intramuscular fat in cattle remain unclear. Results: Histological analysis showed that adipocytes in intramuscular fat were smaller than those in subcutaneous fat from the same mature cattle, indicating a delayed development or slower growth of intramuscular fat compared to subcutaneous fat. Intramuscular fat had a lower capacity for retaining or incorporating long-chain fatty acids into triglycerides than subcutaneous fat. Comparing the transcriptomes of intramuscular and subcutaneous fat by RNA sequencing identified more than 1,000 genes differentially expressed (DEGs) between the two adipose depots. Genes upregulated in intramuscular fat included FOXO6, SLC27A1, HDAC9, WWTR1, and PIK3C2A, which are known to inhibit adipose tissue development and growth. Genes downregulated in intramuscular fat included FABP4, AGPAT2, ADIG, ADIRF, and PLIN2, which are known to promote adipose tissue development and growth. Functional enrichment analyses of these DEGs suggested that intramuscular fat may have a lower capacity for fatty acid binding and adipogenesis compared to subcutaneous fat. Furthermore, genes downregulated in intramuscular fat were enriched in signaling pathways such as the PPAR signaling pathway, whereas genes upregulated in intramuscular fat were enriched in pathways including the Wnt signaling pathway. Stromal vascular fraction (SVF) cells from intramuscular fat exhibited a lower adipogenic potential than those from subcutaneous fat. Conclusions: Multiple factors may contribute to the delayed and slower deposition of intramuscular fat compared to subcutaneous fat in cattle, including reduced fatty acid binding capacity, lower triglyceride synthesis, and decreased adipogenesis in intramuscular fat. These differences are possibly driven by lower expressions of genes such as AGPAT2, FABP4, and ADIG, higher expression of genes such as FOXO6, HDAC9, and SLC27A1, reduced activation of the PPAR signaling pathway, and increased activation of the Wnt signaling pathway in intramuscular fat.
Volatile fatty acids recovery from thermophilic acidogenic fermentation using hydrophobic deep eutectic solvents
Liu, Can; Zhang, Xueyao; Qiao, Qi; Wang, Zhiwu; Shao, Qing; Shi, Jian (2025-07-31)
Background: Volatile fatty acids (VFA) derived from acidogenic fermentation can be recovered as precursors for synthesizing value-added chemicals to replace those from fossil fuels. However, separating VFAs from the fermentation broth with complex constituents and a high-water content is an energy-intensive process. Results: This study developed an innovative membrane extraction technology, utilizing hydrophobic deep eutectic solvents (HDESs) as the acceptor phase along with an omniphobic membrane contactor for efficient extraction of anhydrous VFAs. All tested HDESs, three terpene-based type V HDESs and two tetraalkylammonium halide-based type III HDESs, were found to effectively extract VFAs at pH 3, with extraction recovery percentages (ERPs) up to 80% and 92% for 4 C- and 5 C- VFAs, respectively. However, the ERP of type V HDESs decreased significantly when the aqueous phase was adjusted to pH 6. Molecular simulations suggest that the VFA-HDES interactions vary with VFA dissociation, where the ion-dipole interactions between VFA conjugate bases and hydrogen bond donors at near-neutral pH conditions may destabilize the type V HDES structure and lead to reduced extraction efficiency. The temperature increases from 25 °C to 55 °C did not significantly impact VFA distribution, but a higher temperature could enhance cross-membrane mass transfer. Conclusions: This study demonstrated a novel continuous VFA extraction technology based on HDESs and elucidates the impact of temperature, pH, impurities in real fermentate and the applicability of an integrated membrane system through combined experimental and computational approaches.
Direct long-read visualization reveals hidden variation in GCH1 gene copy number and precise expansion steps
Liu, Shiwei; Zulawinska, Julia; Ebel, Emily R.; Luniewski, Aleksander; Danis, Charles; Simpson, Mary L.; Kim, Jane; Ene, Nnenna; Braukmann, Thomas W. A.; Congdon, Molly; Santos, Webster; Yeh, Ellen; Guler, Jennifer L. (2025-07-17)
Background: Increases in the copy number of large genomic regions, termed amplifications, are an important adaptive strategy for many organisms. Numerous amplifications across the AT-rich Plasmodium falciparum genome contribute directly to drug resistance or impact the fitness of this protozoan parasite. During the characterization of malaria parasites selected with a dihydroorotate dehydrogenase (DHODH) inhibitor that targets pyrimidine biosynthesis, we detected increased copies of a genomic region that encompassed 3 genes (~ 5 kb) including GTP cyclohydrolase I (GCH1 amplicon). While amplification of this gene is reported in antifolate-resistant parasites, GCH1 amplicons had not previously been implicated in DHODH inhibitor resistance. Results: Here, we explored the expansion of the GCH1 locus in this family of parasite lines using long-read sequencing and single-read visualization. We directly quantified higher numbers of tandem GCH1 amplicons in selected parasite lines (up to 9 GCH1 amplicons) compared to parental P. falciparum parasites (strictly 3 GCH1 amplicons). Because each read represents DNA from an individual genome, we were able to appreciate hidden variation within a single parasite line (3, to 5, to 7 amplicons) that was not reflected in other DNA-based analysis methods. While all GCH1 amplicons shared a consistent structure, expansions arose in precise 2-unit steps within selected lines. We found conserved AT-rich sequences at amplicon boundaries, which is consistent with the Plasmodium model of CNV formation. Parasite lines with expanded GCH1 also had DHODH amplicons on a separate chromosome. When we evaluated prior DHODH inhibitor selections, we observed that GCH1 amplification was not required for resistance; however, selection outcomes suggest that pre-existing GCH1 amplicons may support amplification at the DHODH locus. Conclusions: We identified previously undetected heterogeneity in gene copy number by viewing long pieces of DNA from individual genomes. This approach was possible due to the amplicon’s tandem orientation and relatively small size that can be spanned by a single long ONT read. The positive association between DHODH and GCH1 copy number, combined with the metabolic connection between P. falciparum pyrimidine and folate biosynthesis, justifies further investigation into the adaptive evolution of these two genomic loci.
Experienced poverty stigma is associated with food insecurity, mental health, and resource utilization among Southern US mothers with low income
Liebe, Rachel A.; Khan, Tuba; Azad, Rimsha; Adams, Leah M.; Braun, Ashlea C.; Davis, Heather A.; Misyak, Sarah A. (2025-07-16)
Background: The role of poverty stigma, defined as negative stereotyping based on socioeconomic status, in the relationship between food security and mental health has not been well explored. This study aimed to develop and test a theory to explain the role of internalized and experienced poverty stigma in the relationship between food security and mental health among mothers in the Southern US. Methods: A cross-sectional survey was administered in December 2023. The survey was delivered electronically via Qualtrics to mothers living in the southern US who reported a household income below 185% of the federal poverty level. Food security, stigma, and symptoms of anxiety and depression were assessed using previously validated tools. A path analysis was conducted based on the initial conceptual framework and adapted to remove nonsignificant variables. Linear regression was used to assess stigma by resource utilization. Results: Mean poverty stigma scores among mothers (n = 1,008) were moderate for internalized (3.1 ± 0.8) and experienced stigma (3.1 ± 1.1). Lower food security was associated with higher internalized (β = 0.10, p < 0.001) and experienced stigma (β = 0.34, p < 0.001). Experienced stigma had a small association with both anxiety and depressive symptoms (β = 0.20, 0.23, p < 0.001). Participation in food pantries (+ 0.17) and the Temporary Assistance for Needy Families (TANF) program (+ 0.45) was associated with higher experienced stigma (p < 0.05). Conclusions: Poverty stigma may be a potential area for intervention to address the relationship between food insecurity and mental health among mothers and improve resource utilization.
Efficacy and safety of fecal microbiota transplantation in the management of Parkinson’s disease: a systematic review
Nabil, Yehia; Helal, Mohamed M.; Qutob, Israa A.; Dawoud, Ali I. A.; Allam, Salma; Haddad, Roaa; Manasrah, Ghaida M.; AlEdani, Esraa M.; Sleibi, Wadi; faris, Ayhan; Hassan, Amr K.; Nandwana, Varsha (2025-07-17)
Background: Parkinson’s disease (PD) involves progressive neurodegeneration with motor and non-motor symptoms. Gut microbiota alterations are implicated in PD pathogenesis, leading to interest in fecal microbiota transplantation (FMT) as a therapeutic option. This systematic review assesses the efficacy and safety of FMT in managing PD symptoms. Methods: We conducted a comprehensive search across PubMed, Scopus, Web of Science, and Cochrane Central Controlled trials databases. Studies were screened based on predetermined inclusion criteria, focusing on randomized controlled trials (RCTs) involving FMT in PD patients. Two reviewers independently performed the data extraction and quality assessment. Key outcomes included improvements in motor and non-motor symptoms, quality of life, and adverse effects. Results: Five RCTs involving 157 patients met the inclusion criteria. Some studies reported improvements in motor and non-motor symptoms, particularly with colonic FMT, while others found no significant benefit. One trial observed motor function worsening. FMT was generally well-tolerated, with mild and transient gastrointestinal side effects. Conclusion: FMT may relieve PD symptoms, but findings are inconsistent. Larger trials with standardized protocols are needed to determine its long-term efficacy and safety.
The blueprint for survival: the blue dasher dragonfly as a model for urban adaptation
Tolman, Ethan R.; Gamett, Ellie; Beatty, Christopher D.; Goodman, Aaron; Hahn, Brittney; Benischek, Christian; Castillo, Gracie; Derderian, Ethan; Fernandez-Juarez, Santiago; Gallafent, Ben; Jenson, James; Jordan, Dick; Schneider, Magnolia; Salazar, Roberto; Tamano, Towako; Wei, Maleah; Idec, Jacob; Guralnick, Rob; Ware, Jessica L.; Kohli, Manpreet K. (2025-07-08)
Background: Human alteration of natural environments and habitats is a major driver of species decline. However, a handful of species thrive in human altered environments. The biology, distribution, population structure, and molecular adaptations enabling certain species to thrive in human-altered habitats are not well understood. Here, we evaluate the population and functional genomics, ecological niche and distributions, and geometric morphometrics of the blue dasher (Pachydiplax longipennis), one of the most ubiquitously observed insects in human altered habitats. Results: Using resequencing data we identify a number of genes involved with the success of the blue dasher in human altered habitats, including loci contributing to immune function and response to oxidative stress. Some genes related to these functions are found in regions of strong population structure, while others are not, potentially indicating both regional and widespread adaptations to urban environments within this species. Using one of the most robust locality datasets for any species to date, we also generate habitat suitability predictions which show that P. longipennis has spread with urbanization, suggesting humans have created suitable habitat for this species. These results complement morphological and genomic data showing P. longipennis (particularly East of the Rocky Mountains) has the capacity to rapidly disperse to newly suitable habitats. Conclusions: We confirm that P. longipennis is well equipped to deal with the stress of urban habitats, by observing large swaths of suitable habitat of P. longipennis throughout its range, both within and outside of major cities and towns, and identifying conserved and population specific molecular mechanisms related to urban stress. Furthermore, we observe minor variability in suitable habitat of P. longipennis throughout the years; we do not note any substantial loss or gain in habitat, suggesting its resiliency to fluctuations in temperature and precipitation throughout the United States. Given the shared barriers to colonizing an urban habitat, we expect that many of the molecular adaptations to urban environments we have identified in P. longipennis could be found in other animals that are broadly tied to urban habitats.
GPS-based street-view greenspace exposure and wearable assessed physical activity in a prospective cohort of US women
Yi, Li; Hart, Jaime E.; Wilt, Grete; Hu, Cindy R.; Jimenez, Marcia P.; Lin, Pi-I D.; Suel, Esra; Hystad, Perry; Hankey, Steven C.; Zhang, Wenwen; Chavarro, Jorge E.; Laden, Francine; James, Peter (2025-07-06)
Background: Increasing evidence positively links greenspace and physical activity (PA). However, most studies use measures of greenspace, such as satellite-based vegetation indices around the residence, which fail to capture ground-level views and day-to-day dynamic exposures, potentially misclassifying greenspace and limiting policy relevance. Methods: We analyzed data from the US-based Nurses’ Health Study 3 Mobile Health Substudy (2018–2020). Participants wore Fitbits™ and provided smartphone global positioning system (GPS) for four 7-day periods throughout the year. Street-view greenspace (%trees, %grass, %other greenspace [flowers/plants/fields]) were derived from 2019 street-view imagery using deep-learning algorithms at a 100-meter resolution and linked to 10-minute GPS observations. Average steps-per-minute for were calculated for each 10-minute period following each GPS observation. Generalized Additive Mixed Models examined associations of street-view greenspace exposure with PA, adjusting for individual and area-level covariates. We considered effect modification by region, season, neighborhood walkability and socioeconomic status (SES), temperature, and precipitation. Results: Our sample included 335 participants (meanage= 39.4 years, n = 304,394 observations). Mean steps-per-minute per 10-minutes were 6.9 (SD = 14.6). An IQR increase (18.7%) in street-view trees was associated with a 0.36 steps-per-minute decrease (95%CI: -0.71, -0.01). In addition, an IQR increase (10.6%) in grass exposure was associated with a 0.59 steps-per-minute decrease (95% CI: -0.79, -0.40); however, the association was non-linear and flattened out after the 75th percentile of street-view grass. Conversely, an IQR increase (1.2%) in other greenspace was associated with a 1.99 steps-per-minute increase (95%CI: 0.01, 3.97). Associations were stronger in the spring and in higher SES neighborhoods, and among residents of the Northeast. Conclusions: In this prospective cohort, momentary street-view exposure to trees and grass was inversely associated with PA, while exposure to other greenspace was positively associated. Future research should confirm these results in other populations and explore the mechanisms through which specific greenspace components influence PA.
Neutrino interaction vertex reconstruction in DUNE with Pandora deep learning
Abud, A. A.; Acciarri, R.; Acero, M. A.; Adames, M. R.; Adamov, G.; Adamowski, M.; Adams, D.; Adinolfi, M.; Adriano, C.; Aduszkiewicz, A.; Aguilar, J.; Akbar, F.; Alemanno, F.; Alex, N. S.; Allison, K.; Alrashed, M.; Alton, A.; Alvarez, R.; Alves, T.; Aman, A.; Amar, H.; Amedo, P.; Anderson, J.; Andreopoulos, C.; Andreotti, M.; Andrews, M. P.; Andrianala, F.; Andringa, S.; Anjarazafy, F.; Antic, D.; Antoniassi, M.; Antonova, M.; Aranda-Fernandez, A.; Arellano, L.; Arrieta Diaz, E.; Arroyave, M. A.; Asaadi, J.; Ashkenazi, A.; Asner, D.; Asquith, L.; Atkin, E.; Auguste, D.; Aurisano, A.; Aushev, V.; Autiero, D.; Ávila Gómez, D.; Azam, M. B.; Azfar, F.; Back, A.; Back, H.; Back, J. J.; Bagaturia, I.; Bagby, L.; Baigarashev, D.; Balasubramanian, S.; Balboni, A.; Baldi, P.; Baldini, W.; Baldonedo, J.; Baller, B.; Bambah, B.; Banerjee, R.; Barao, F.; Barbu, D.; Barenboim, G.; Barham Alzás, P.; Barker, G. J.; Barkhouse, W.; Barr, G.; Barranco Monarca, J.; Barros, A.; Barros, N.; Barrow, D.; Barrow, J. L.; Basharina-Freshville, A.; Bashyal, A.; Basque, V.; Basu, D.; Batchelor, C.; Bathe-Peters, L.; Battat, J. B. R.; Battisti, F.; Bay, F.; Bazetto, M. C. Q.; Bazo Alba, J. L. L.; Beacom, J. F.; Bechetoille, E.; Behera, B.; Belchior, E.; Bell, B.; Bell, G.; Bellantoni, L.; Bellettini, G.; Bellini, V.; Beltramello, O.; Benitez Montiel, C.; Benjamin, D.; Bento Neves, F.; Berger, J.; Berkman, S.; Bernal, J.; Bernardini, P.; Bersani, A.; Bertolini, E.; Bertolucci, S.; Betancourt, M.; Betancur Rodríguez, A.; Bezawada, Y.; Bezerra, A. T.; Bhat, A.; Bhatnagar, V.; Bhatt, J.; Bhattacharjee, M.; Bhattacharya, M.; Bhuller, S.; Bhuyan, B.; Biagi, S.; Bian, J.; Biery, K.; Bilki, B.; Bishai, M.; Blake, A.; Blaszczyk, F. D.; Blazey, G. C.; Blucher, E.; Bogart, B.; Bogenschuetz, J.; Boissevain, J.; Bolognesi, S.; Bolton, T.; Bomben, L.; Bonesini, M.; Bonilla-Diaz, C.; Booth, A.; Boran, F.; Borges Merlo, R.; Bostan, N.; Botogoske, G.; Bottino, B.; Bouet, R.; Boza, J.; Bracinik, J.; Brahma, B.; Brailsford, D.; Bramati, F.; Branca, A.; Brandt, A.; Bremer, J.; Brew, C.; Brice, S. J.; Brio, V.; Brizzolari, C.; Bromberg, C.; Brooke, J.; Bross, A.; Brunetti, G.; Brunetti, M. B.; Buchanan, N.; Budd, H.; Buergi, J.; Bundock, A.; Burgardt, D.; Butchart, S.; Caceres V., G.; Cai, T.; Calabrese, R.; Calabrese, R.; Calcutt, J.; Calivers, L.; Calvo, E.; Caminata, A.; Camino, A. F.; Campanelli, W.; Campani, A.; Campos Benitez, A.; Canci, N.; Capó, J.; Caracas, I.; Caratelli, D.; Carber, D.; Carceller, J. M.; Carini, G.; Carlus, B.; Carneiro, M. F.; Carniti, P.; Caro Terrazas, I.; Carranza, H.; Carrara, N.; Carroll, L.; Carroll, T.; Carter, A.; Casarejos, E.; Casazza, D.; Castaño Forero, J. F.; Castaño, F. A.; Castillo, A.; Castromonte, C.; Catano-Mur, E.; Cattadori, C.; Cavalier, F.; Cavanna, F.; Centro, S.; Cerati, G.; Cerna, C.; Cervelli, A.; Cervera Villanueva, A.; Chalifour, M.; Chappell, A.; Chatterjee, A.; Chauhan, B.; Chen, H.; Chen, M.; Chen, W. C.; Chen, Y.; Chen, Z.; Cherdack, D.; Chhibra, S. S.; Chi, C.; Chiapponi, F.; Chirco, R.; Chitirasreemadam, N.; Cho, K.; Choate, S.; Choi, G.; Chokheli, D.; Chong, P. S.; Chowdhury, B.; Christian, D.; Chung, M.; Church, E.; Cicala, M. F.; Cicerchia, M.; Cicero, V.; Ciolini, R.; Clarke, P.; Cline, G.; Cocco, A. G.; Coelho, J. A. B.; Cohen, A.; Collazo, J.; Collot, J.; Conrad, J. M.; Convery, M.; Conway, K.; Copello, S.; Cova, P.; Cox, C.; Cremonesi, L.; Crespo-Anadón, J. I.; Crisler, M.; Cristaldo, E.; Crnkovic, J.; Crone, G.; Cross, R.; Cudd, A.; Cuesta, C.; Cui, Y.; Curciarello, F.; Cussans, D.; Dai, J.; Dalager, O.; Dallaway, W.; D’Amico, R.; da Motta, H.; Dar, Z. A.; Darby, R.; Da Silva Peres, L.; David, Q.; Davies, G. S.; Davini, S.; Dawson, J.; De Aguiar, R.; De Almeida, P.; Debbins, P.; Decowski, M. P.; de Gouvêa, A.; De Holanda, P. C.; De Jong, P.; Del Amo Sanchez, P.; De Lauretis, G.; Delbart, A.; Delepine, D.; Delgado, M.; Dell’Acqua, A.; Delle Monache, G.; Delmonte, N.; De Lurgio, P.; Demario, R.; De Matteis, G.; de Mello Neto, J. R. T.; DeMuth, D. M.; Dennis, S.; Densham, C.; Denton, P.; Deptuch, G. W.; De Roeck, A.; De Romeri, V.; Detje, J. P.; Devine, J.; Dharmapalan, R.; Dias, M.; Diaz, A.; Díaz, J. S.; Díaz, F.; Di Capua, F.; Di Domenico, A.; Di Domizio, S.; Di Falco, S.; Di Giulio, L.; Ding, P.; Di Noto, L.; Diociaiuti, E.; Di Silvestre, V.; Distefano, C.; Diurba, R.; Diwan, M.; Djurcic, Z.; Dolan, S.; Dolce, M.; Dolek, F.; Dolinski, M. J.; Domenici, D.; Donati, S.; Donon, Y.; Doran, S.; Douglas, D.; Doyle, T. A.; Drielsma, F.; Duarte, L.; Duchesneau, D.; Duffy, K.; Dugas, K.; Dunne, P.; Dutta, B.; Duyang, H.; Dwyer, D. A.; Dyshkant, A. S.; Dytman, S.; Eads, M.; Earle, A.; Edayath, S.; Edmunds, D.; Eisch, J.; Emark, W.; Englezos, P.; Ereditato, A.; Erjavec, T.; Escobar, C. O.; Evans, J. J.; Ewart, E.; Ezeribe, A. C.; Fahey, K.; Falcone, A.; Fani’, M.; Farnese, C.; Farrell, S.; Farzan, Y.; Felix, J.; Feng, Y.; Fernandez-Martinez, E.; da Silva, M. F.; Ferry, G.; Fialova, E.; Fields, L.; Filip, P.; Filkins, A.; Filthaut, F.; Fiorillo, G.; Fiorini, M.; Fogarty, S.; Foreman, W.; Fowler, J.; Franc, J.; Francis, K.; Franco, D.; Franklin, J.; Freeman, J.; Fried, J.; Friedland, A.; Fucci, M.; Fuess, S.; Furic, I. K.; Furman, K.; Furmanski, A. P.; Gaba, R.; Gabrielli, A.; Gago, A. M.; Galizzi, F.; Gallagher, H.; Galli, M.; Gallice, N.; Galymov, V.; Gamberini, E.; Gamble, T.; Gandhi, R.; Ganguly, S.; Gao, F.; Gao, S.; Garcia-Gamez, D.; García-Peris, M. Á.; Gardim, F.; Gardiner, S.; Gastler, D.; Gauch, A.; Gauzzi, P.; Gazzana, S.; Ge, G.; Geffroy, N.; Gelli, B.; Gent, S.; Gerlach, L.; Ghosh, A.; Giammaria, T.; Gibin, D.; Gil-Botella, I.; Gilligan, S.; Gioiosa, A.; Giovannella, S.; Giri, A. K.; Giugliano, C.; Giusti, V.; Gnani, D.; Gogota, O.; Gollapinni, S.; Gollwitzer, K.; Gomes, R. A.; Gomez Bermeo, L. V.; Gomez Fajardo, L. S.; Gonzalez-Diaz, D.; Goodman, M. C.; Goswami, S.; Gotti, C.; Goudeau, J.; Goudzovski, E.; Grace, C.; Gramellini, E.; Gran, R.; Granados, E.; Granger, P.; Grant, C.; Gratieri, D. R.; Grauso, G.; Green, P.; Greenberg, S.; Greer, J.; Griffith, W. C.; Grzelak, K.; Gu, L.; Gu, W.; Guarino, V.; Guarise, M.; Guenette, R.; Guerzoni, M.; Guffanti, D.; Guglielmi, A.; Guo, B.; Guo, F. Y.; Gupta, V.; Gurung, G.; Gutierrez, D.; Guzowski, P.; Guzzo, M. M.; Gwon, S.; Habig, A.; Haegel, L.; Hagaman, L.; Hahn, A.; Hakenmüller, J.; Hamernik, T.; Hamilton, P.; Hancock, J.; Handley, M.; Happacher, F.; Harris, D. A.; Hart, A. L.; Hartnell, J.; Hartnett, T.; Harton, J.; Hasegawa, T.; Hasnip, C. M.; Hatcher, R.; Hawkins, S.; Hays, J.; He, M.; Heavey, A.; Heeger, K. M.; Heindel, A.; Heise, J.; Hellmuth, P.; Henderson, L.; Herner, K.; Hewes, V.; Higuera, A.; Hilgenberg, C.; Himmel, A.; Hinkle, E.; Hirsch, L. R.; Ho, J.; Hoefken Zink, J.; Hoff, J.; Holin, A.; Holvey, T.; Hong, C.; Hoppe, E.; Horiuchi, S.; Horton-Smith, G. A.; Hosokawa, R.; Houdy, T.; Howard, B.; Howell, R.; Hristova, I.; Hronek, M. S.; Huang, J.; Huang, R. G.; Huang, X.; Hulcher, Z.; Iles, G.; Ilic, N.; Iliescu, A. M.; Illingworth, R.; Ingratta, G.; Ioannisian, A.; Irwin, B.; Ismerio Oliveira, M.; Jackson, C. M.; Jain, V.; James, E.; Jang, W.; Jargowsky, B.; Jena, D.; Jentz, I.; Ji, X.; Jiang, C.; Jiang, J.; Jipa, A.; Jo, J. H.; Joaquim, F. R.; Johnson, W.; Jollet, C.; Jones, R.; Jovancevic, N.; Judah, M.; Jung, C. K.; Jung, K. Y.; Junk, T.; Jwa, Y.; Kabirnezhad, M.; Kaboth, A. C.; Kadenko, I.; Kalikulov, O.; Kalra, D.; Kandemir, M.; Kaplan, D. M.; Karagiorgi, G.; Karaman, G.; Karcher, A.; Karyotakis, Y.; Kasetti, S. P.; Kashur, L.; Kauther, A.; Kazaryan, N.; Ke, L.; Kearns, E.; Keener, P. T.; Kelly, K. J.; Keloth, R.; Kemp, E.; Kemularia, O.; Kermaidic, Y.; Ketchum, W.; Kettell, S. H.; Khan, N.; Khvedelidze, A.; Kim, D.; Kim, J.; Kim, M. J.; Kim, S.; King, B.; King, M.; Kirby, M.; Kish, A.; Klein, J.; Kleykamp, J.; Klustova, A.; Kobilarcik, T.; Koch, L.; Koehler, K.; Koerner, L. W.; Koh, D. H.; Kordosky, M.; Kosc, T.; Kostelecký, V. A.; Kothekar, K.; Kotler, I.; Kovalcuk, M.; Krah, W.; Kralik, R.; Kramer, M.; Kreczko, L.; Krennrich, F.; Kroupova, T.; Kubota, S.; Kubu, M.; Kudryavtsev, V. A.; Kufatty, G.; Kuhlmann, S.; Kumar, J.; Kumar, P.; Kumar, P.; Kumaran, S.; Kunzmann, J.; Kuravi, R.; Kus, V.; Kutter, T.; Kvasnicka, J.; Labree, T.; Lackey, T.; Lalău, I.; Lambert, A.; Land, B. J.; Lane, C. E.; Lane, N.; Lang, K.; Langford, T.; Langstaff, M.; Lanni, F.; Larkin, J.; Lasorak, P.; Last, D.; Laundrie, A.; Laurenti, G.; Lavaut, E.; Laycock, P.; Lazanu, I.; LaZur, R.; Lazzaroni, M.; Le, T.; Leardini, S.; Learned, J.; LeCompte, T.; Lehmann Miotto, G.; Lehnert, R.; Leitner, M.; Lemoine, H.; Leon Silverio, D.; Lepin, L. M.; Li, J.-Y.; Li, S. W.; Li, Y.; Liao, H.; Lima, R.; Lin, C. S.; Lindebaum, D.; Linden, S.; Lineros, R. A.; Lister, A.; Littlejohn, B. R.; Liu, H.; Liu, J.; Liu, Y.; Lockwitz, S.; Lomidze, I.; Long, K.; Lopes, T. V.; Lopez, J.; López de Rego, I.; López-March, N.; LoSecco, J. M.; Louis, W. C.; Lozano Sanchez, A.; Lu, X.-G.; Luk, K. B.; Luo, X.; Luppi, E.; Machado, A. A.; Machado, P.; Macias, C. T.; Macier, J. R.; MacMahon, M.; Magill, S.; Magueur, C.; Mahn, K.; Maio, A.; Major, A.; Majumdar, K.; Malige, A.; Mameli, S.; Man, M.; Mandujano, R. C.; Maneira, J.; Manly, S.; Mann, A.; Manolopoulos, K.; Manrique Plata, M.; Manthey Corchado, S.; Manyam, V. N.; Manzanillas-Velez, L.; Marchan, M.; Marchionni, A.; Marciano, W.; Marfatia, D.; Mariani, C.; Maricic, J.; Marinho, F.; Marino, A. D.; Markiewicz, T.; Das Chagas Marques, F.; Marquet, C.; Marshak, M.; Marshall, C. M.; Marshall, J.; Martina, L.; Martín-Albo, J.; Martinez, N.; Martinez Caicedo, D. A.; Martinez-Casales, M.; Martínez López, F.; Martínez Miravé, P.; Martynenko, S.; Mascagna, V.; Mastbaum, A.; Masud, M.; Matichard, F.; Matteucci, G.; Matthews, J.; Mauger, C.; Mauri, N.; Mavrokoridis, K.; Mawby, I.; Mayhew, F.; Mazza, R.; McAskill, T.; McConkey, N.; McFarland, K. S.; McGrew, C.; McNab, A.; McNulty, C.; Meazza, L.; Meddage, V. C. N.; Mehmood, M.; Mehta, B.; Mehta, P.; Mei, F.; Melas, P.; Mellet, L.; Mena, O.; Mendez, H.; Méndez, D. P.; Mendonca, A. P.; Menegolli, A.; Meng, G.; Mercuri, A. C. E. A.; Meregaglia, A.; Messier, M. D.; Metallo, S.; Metcalf, W.; Mewes, M.; Meyer, H.; Miao, T.; Micallef, J.; Miccoli, A.; Michna, G.; Milincic, R.; Miller, F.; Miller, G.; Miller, W.; Minotti, A.; Miralles, L.; Mironov, C.; Miryala, S.; Miscetti, S.; Mishra, C. S.; Mishra, P.; Mishra, S. R.; Mislivec, A.; Mladenov, D.; Mocioiu, I.; Mogan, A.; Mohanta, R.; Mohayai, T. A.; Mokhov, N.; Molina, J.; Molina Bueno, L.; Montagna, E.; Montanari, A.; Montanari, C.; Montanari, D.; Montanino, D.; Montaño Zetina, L. M.; Mooney, M.; Moor, A. F.; Moore, M.; Moore, Z.; Moreno, D.; Moreno-Granados, G.; Moreno-Palacios, O.; Morescalchi, L.; Moretti, R.; Morris, C.; Mossey, C.; Moura, C. A.; Mouster, G.; Mu, W.; Mualem, L.; Mueller, J.; Muether, M.; Muheim, F.; Muir, A.; Mukhamejanov, Y.; Mukhamejanova, A.; Mulhearn, M.; Munford, D.; Munteanu, L. J.; Muramatsu, H.; Muraz, J.; Murphy, M.; Murphy, T.; Muse, J.; Mytilinaki, A.; Nachtman, J.; Nagai, Y.; Nagu, S.; Naples, D.; Narita, S.; Nava, J.; Navrer-Agasson, A.; Nayak, N.; Nebot-Guinot, M.; Nehm, A.; Nelson, J. K.; Neogi, O.; Nesbit, J.; Nessi, M.; Newbold, D.; Newcomer, M.; Nichol, R.; Nicolas-Arnaldos, F.; Nielsen, A.; Nikolica, A.; Nikolov, J.; Niner, E.; Nishimura, K.; Norman, A.; Norrick, A.; Novella, P.; Nowak, A.; Nowak, J. A.; Oberling, M.; Ochoa-Ricoux, J. P.; Oh, S.; Oh, S. B.; Olivier, A.; Olson, T.; Onel, Y.; Onishchuk, Y.; Oranday, A.; Osbiston, M.; Osorio Vélez, J. A.; O’Sullivan, L.; Otiniano Ormachea, L.; Pagani, L.; Palacio, G.; Palamara, O.; Palestini, S.; Paley, J. M.; Pallavicini, M.; Palomares, C.; Pan, S.; Panareo, M.; Panda, P.; Pandey, V.; Panduro Vazquez, W.; Pantic, E.; Paolone, V.; Papadopoulou, A.; Papaleo, R.; Papoulias, D.; Paramesvaran, S.; Parke, S.; Parsa, S.; Parsa, Z.; Parveen, S.; Parvu, M.; Pasciuto, D.; Pascoli, S.; Pasqualini, L.; Pasternak, J.; Patiño Camargo, G.; Paton, J. L.; Patrick, C.; Patrizii, L.; Patterson, R. B.; Patzak, T.; Paudel, A.; Paul, J.; Paulucci, L.; Pavlovic, Z.; Pawloski, G.; Payne, D.; Peake, A.; Pec, V.; Pedreschi, E.; Peeters, S. J. M.; Pellico, W.; Pennacchio, E.; Penzo, A.; Peres, O. L. G.; Perez Gonzalez, Y. F.; Pérez-Molina, L.; Pernas, C.; Perry, J.; Pershey, D.; Pessina, G.; Petrillo, G.; Petta, C.; Petti, R.; Pfaff, M.; Pia, V.; Pickering, L.; Pierini, L.; Pietropaolo, F.; Pimentel, V. L.; Pinaroli, G.; Pincha, S.; Pinchault, J.; Pitts, K.; Pletcher, K.; Plows, K.; Pollack, C.; Pollmann, T.; Pompa, F.; Pons, X.; Poonthottathil, N.; Popov, V.; Poppi, F.; Porter, J.; Porto Paixão, L. G.; Potekhin, M.; Pozzato, M.; Pradhan, R.; Prakash, T.; Prest, M.; Psihas, F.; Pugnere, D.; Pullia, D.; Qian, X.; Queen, J.; Raaf, J. L.; Rabelhofer, M.; Radeka, V.; Rademacker, J.; Radics, B.; Raffaelli, F.; Rafique, A.; Raguzin, E.; Rahe, A.; Rajagopalan, S.; Rajaoalisoa, M.; Rakhno, I.; Rakotondravohitra, L.; Ralaikoto, M. A.; Ralte, L.; Ramirez Delgado, M. A.; Ramson, B.; Randriamanampisoa, S. S.; Rappoldi, A.; Raselli, G.; Rath, T.; Ratoff, P.; Ray, R.; Razafinime, H.; Razakamiandra, R. F.; Rea, E. M.; Real, J. S.; Rebel, B.; Rechenmacher, R.; Reichenbacher, J.; Reitzner, S. D.; Renner, E.; Repetto, S.; Rescia, S.; Resnati, F.; Restrepo, Diego; Reynolds, C.; Ribas, M.; Riboldi, S.; Riccio, C.; Riccobene, G.; Ricol, J. S.; Rigan, M.; Rikalo, A.; Rincón, E. V.; Ritchie-Yates, A.; Ritter, S.; Rivera, D.; Robert, A.; Roberts, A.; Robles, E.; Rocabado Rocha, J. L.; Roda, M.; Rodrigues, M. J. O.; Rondon, J. R.; Rosauro-Alcaraz, S.; Rosier, P.; Ross, D.; Rossella, M.; Rossi, M.; Roy, N.; Roy, P.; Roy, P.; Rubbia, C.; Rudik, D.; Ruggeri, A.; Ruiz Ferreira, G.; Rushiya, K.; Russell, B.; Sacerdoti, S.; Saduyev, N.; Sahoo, S. K.; Sahu, N.; Sakhiyev, S.; Sala, P.; Salmoria, G.; Samanta, S.; Samios, N.; Sanchez, M. C.; Sánchez Bravo, A.; Sánchez-Castillo, A.; Sanchez-Lucas, P.; Sanders, D. A.; Sanfilippo, S.; Santoro, D.; Saoulidou, N.; Sapienza, P.; Sarcevic, I.; Sarra, I.; Savage, G.; Savinov, V.; Scanavini, G.; Scaramelli, A.; Scarff, A.; Schefke, T.; Schellman, H.; Schifano, S.; Schlabach, P.; Schmitz, D.; Schneider, A. W.; Scholberg, K.; Schukraft, A.; Schuld, B.; Schwartz, S.; Segade, A.; Segreto, E.; Senise, C. R.; Sensenig, J.; Seppela, D.; Shaevitz, M. H.; Shanahan, P.; Sharma, P.; Kumar, R.; Sharma Poudel, S.; Shaw, K.; Shaw, T.; Shchablo, K.; Shen, J.; Shepherd-Themistocleous, C.; Shi, J.; Shi, W.; Shin, S.; Shivakoti, S.; Shmakov, A.; Shoemaker, I.; Shooltz, D.; Shrock, R.; Siden, M.; Silber, J.; Simard, L.; Sinclair, J.; Sinev, G.; Singh, Jaydip; Singh, J.; Singh, L.; Singh, P.; Singh, V.; Singh Chauhan, S.; Sipos, R.; Sironneau, C.; Sirri, G.; Siyeon, K.; Skarpaas, K.; Smedley, J.; Smith, J.; Smith, P.; Smolik, J.; Smy, M.; Snape, M.; Snider, E. L.; Snopok, P.; Soares Nunes, M.; Sobel, H.; Soderberg, M.; Solano Salinas, C. J.; Söldner-Rembold, S.; Solomey, N.; Solovov, V.; Sondheim, W. E.; Sorel, M.; Soto-Oton, J.; Sousa, A.; Soustruznik, K.; Souza Correia, D.; Spinella, F.; Spitz, J.; Spooner, N. J. C.; Stalder, D.; Stancari, M.; Stanco, L.; Steenis, J.; Stein, R.; Steiner, H. M.; Steklain Lisbôa, A. F.; Stewart, J.; Stillwell, B.; Stock, J.; Stokes, T.; Strait, M.; Strauss, T.; Strigari, L.; Stuart, A.; Suarez, J. G.; Subash, J.; Surdo, A.; Suter, L.; Sutton, K.; Suvorov, Y.; Svoboda, R.; Swain, S. K.; Sweeney, C.; Szczerbinska, B.; Szelc, A. M.; Sztuc, A.; Taffara, A.; Talukdar, N.; Tamara, J.; Tanaka, H. A.; Tang, S.; Taniuchi, N.; Tapia Casanova, A. M.; Tapper, A.; Tariq, S.; Tarpara, E.; Tatar, E.; Tayloe, R.; Tedeschi, D.; Teklu, A. M.; Tena Vidal, J.; Tennessen, P.; Tenti, M.; Terao, K.; Terranova, F.; Testera, G.; Thakore, T.; Thea, A.; Thomas, S.; Thompson, A.; Thorn, C.; Thorpe, C.; Timm, S. C.; Tiras, E.; Tishchenko, V.; Tiwari, S.; Todorović, N.; Tomassetti, L.; Tonazzo, A.; Torbunov, D.; Torres Muñoz, D.; Torti, M.; Tortola, M.; Torun, Y.; Tosi, N.; Totani, D.; Toups, M.; Touramanis, C.; Tran, D.; Travaglini, R.; Trevor, J.; Triller, E.; Trilov, S.; Truchon, J.; Truncali, D.; Trzaska, W. H.; Tsai, Y.; Tsai, Y.-T.; Tsamalaidze, Z.; Tsang, K. V.; Tsverava, N.; Tu, S. Z.; Tufanli, S.; Tunnell, C.; Turner, J.; Tuzi, M.; Tyler, J.; Tyley, E.; Tzanov, M.; Uchida, M. A.; Ureña González, J.; Urheim, J.; Usher, T.; Utaegbulam, H.; Uzunyan, S.; Vagins, M. R.; Vahle, P.; Valdiviesso, G. A.; Vale, V.; Valencia, E.; Valentim, R.; Vallari, Z.; Vallazza, E.; Valle, J. W. F.; Van Berg, R.; Forero, D. V.; Vannozzi, A.; Van Nuland-Troost, M.; Varanini, F.; Vargas Auccalla, T.; Vargas Oliva, D.; Vaughan, N.; Vaziri, K.; Vázquez-Ramos, A.; Vega, J.; Vences, J.; Ventura, S.; Verdugo, A.; Vergani, S.; Verzocchi, M.; Vetter, K.; Vicenzi, M.; Vieira de Souza, H.; Vignoli, C.; Vilela, C.; Villa, E.; Viola, S.; Viren, B.; Vizarreta, R.; Vizcaya Hernandez, A. P.; Vlachos, S.; Vorobyev, G.; Vuong, Q.; Waldron, A. V.; Wallach, M.; Walsh, J.; Walton, T.; Wan, L.; Wang, B.; Wang, H.; Wang, J.; Wang, L.; Wang, M. H. L. S.; Wang, X.; Wang, Y.; Warburton, K.; Warner, D.; Warsame, L.; Wascko, M. O.; Waters, D.; Watson, A.; Wawrowska, K.; Weber, A.; Weber, C. M.; Weber, M.; Wei, H.; Weinstein, A.; Westerdale, S.; Wetstein, M.; Whalen, K.; White, A.; Whitehead, L. H.; Whittington, D.; Wieler, F.; Wilhlemi, J.; Wilking, M. J.; Wilkinson, A.; Wilkinson, C.; Wilson, F.; Wilson, R. J.; Winter, P.; Wolcott, J.; Wolfs, J.; Wongjirad, T.; Wood, A.; Wood, K.; Worcester, E.; Worcester, M.; Wresilo, K.; Wrobel, M.; Wu, S.; Wu, W.; Wu, W.; Wurm, M.; Wyenberg, J.; Wynne, B. M.; Xiao, Y.; Xiotidis, I.; Yaeggy, B.; Yahlali, N.; Yandel, E.; Yang, J.; Yang, T.; Yankelevich, A.; Yates, L.; Yonehara, K.; Young, T.; Yu, B.; Yu, H.; Yu, J.; Yu, Y.; Yuan, W.; Zaki, R.; Zalesak, J.; Zambelli, L.; Zamorano, B.; Zani, A.; Zapata, O.; Zazueta, L.; Zeller, G. P.; Zennamo, J.; Zettlemoyer, J.; Zeug, K.; Zhang, C.; Zhang, S.; Zhao, M.; Zhivun, E.; Zimmerman, E. D.; Zucchelli, S.; Zuklin, J.; Zutshi, V.; Zwaska, R. (2025-06-25)
The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20% increase in the efficiency of sub-1 cm vertex reconstruction across all neutrino flavours.
CUPID, the Cuore upgrade with particle identification
Alfonso, Krystal; Armatol, A.; Augier, C.; Avignone III, F. T.; Azzolini, O.; Barabash, A. S.; Bari, G.; Barresi, A.; Baudin, D.; Bellini, F.; Benato, G.; Benussi, L.; Berest, V.; Beretta, M.; Bergé, L.; Bettelli, M.; Biassoni, M.; Billard, J.; Boffelli, F.; Boldrini, V.; Brandani, E. D.; Brofferio, C.; Bucci, C.; Buchynska, M.; Camilleri, J.; Campani, A.; Cao, J.; Capelli, C.; Capelli, S.; Caracciolo, V.; Cardani, L.; Carniti, P.; Casali, N.; Celi, E.; Chang, C.; Chapellier, M.; Chen, H.; Chiesa, D.; Cintas, D.; Clemenza, M.; Colantoni, I.; Copello, S.; Cremonesi, O.; Creswick, R. J.; D’Addabbo, A.; Dafinei, I.; Danevich, F. A.; De Dominicis, F.; De Jesus, M.; de Marcillac, P.; Dell’Oro, S.; Di Domizio, S.; Di Lorenzo, S.; Dixon, T.; Drobizhev, A.; Dumoulin, L.; El Idrissi, M.; Faverzani, M.; Ferri, E.; Ferri, F.; Ferroni, F.; Figueroa-Feliciano, E.; Formaggio, J.; Franceschi, A.; Fu, S.; Fujikawa, B. K.; Gascon, J.; Ghislandi, S.; Giachero, A.; Girola, M.; Gironi, L.; Giuliani, A.; Gorla, P.; Gotti, C.; Grant, C.; Gras, P.; Guillaumon, P. V.; Gutierrez, T. D.; Han, K.; Hansen, E. V.; Heeger, K. M.; Helis, D. L.; Huang, H. Z.; Hurst, M. T.; Imbert, L.; Juillard, A.; Karapetrov, G.; Keppel, G.; Khalife, H.; Kobychev, V. V.; Kolomensky, Yu. G.; Kowalski, R.; Lattaud, H.; Lefevre, M.; Lisovenko, M.; Liu, R.; Liu, Y.; Loaiza, P.; Ma, L.; Mancarella, F.; Manenti, N.; Mariani, A.; Marini, L.; Marnieros, S.; Martinez, M.; Maruyama, R. H.; Mas, Ph.; Mayer, D.; Mazzitelli, G.; Mazzola, E.; Mei, Y.; Moore, M. N.; Morganti, S.; Napolitano, T.; Nastasi, M.; Nikkel, J.; Nones, C.; Norman, E. B.; Novosad, V.; Nutini, I.; O’Donnell, T.; Olivieri, E.; Olmi, M.; Oregui, B. T.; Pagan, S.; Pageot, M.; Pagnanini, L.; Pasciuto, D.; Pattavina, L.; Penek, Ö.; Peng, H.; Pessina, G.; Pettinacci, V.; Pira, C.; Pirro, S.; Pochon, O.; Poda, D. V.; Polakovic, T.; Polischuk, O. G.; Pottebaum, E. G.; Pozzi, S.; Previtali, E.; Puiu, A.; Puranam, S.; Quitadamo, S.; Rappoldi, A.; Raselli, G. L.; Ressa, A.; Rizzoli, R.; Rosenfeld, C.; Rosier, P.; Rossella, M.; Scarpaci, J. A.; Schmidt, B.; Serino, R.; Shaikina, A.; Shang, K.; Sharma, V.; Shlegel, V. N.; Singh, V.; Sisti, M.; Slocum, P.; Speller, D.; Surukuchi, P. T.; Taffarello, L.; Tomassini, S.; Tomei, C.; Torres, A.; Torres, J. A.; Tozzi, D.; Tretyak, V. I.; Trotta, D.; Velazquez, M.; Vetter, K. J.; Wagaarachchi, S. L.; Wang, G.; Wang, L.; Wang, R.; Welliver, B.; Wilson, J.; Wilson, K.; Winslow, L. A.; Xie, F.; Xue, M.; Yang, J.; Yefremenko, V.; Umatov, V. I.; Zarytskyy, M. M.; Zhu, T.; Zolotarova, A.; Zucchelli, S. (2025-07-03)
CUPID, the CUORE Upgrade with Particle Identification, is a next-generation experiment to search for neutrinoless double beta decay ( 0 ν β β ) and other rare events using enriched Li 2 100 MoO 4 scintillating bolometers. It will be hosted by the CUORE cryostat located at the Laboratori Nazionali del Gran Sasso in Italy. The main physics goal of CUPID is to search for 0 ν β β of 100 Mo with a discovery sensitivity covering the full neutrino mass regime in the inverted ordering scenario, as well as the portion of the normal ordering regime with lightest neutrino mass larger than 10 meV. With a conservative background index of 10 - 4 cts / ( keV · kg · yr ) , 240 kg isotope mass, 5 keV FWHM energy resolution at 3 MeV and 10 live-years of data taking, CUPID will have a 90% C.L. half-life exclusion sensitivity of 1.8 · 10 27 yr, corresponding to an effective Majorana neutrino mass ( m β β ) sensitivity of 9–15 meV, and a 3 σ discovery sensitivity of 1 · 10 27 yr, corresponding to an m β β range of 12–21 meV.
Rediscovering Shixue: The Point-Notation as Social and Intellectual Signifiers Under the Institutional Censorship of Imperial China in the Eighteenth Century
Zhao, Tianming (2025-06-13)
The late seventeenth century saw a golden era when the scientific technique of perspective, as a gift from the Scientific Revolution, expanded its territory to China via French missionaries. Among them, Giuseppe Castiglione (1688–1766) is the most successful one who not only served as the court painter in China but also collaborated with his Chinese apprentice Nian Xiyao (1671–1738) in publishing the first Chinese treatise specializing in perspective—Shixue (1735). Modeled after Andrea Pozzo’s Perspectiva Pictorum et Architectorum (1693–1700), Shixue has long been overlooked for its novelty, along with its unique semiotics of point-notation. Hence, the scope of this research is aimed at rediscovering Nian’s uncanny style of point-notation in Shixue as a silent response to Chinese institutional censorship. After the interpretation of the concealed orders within these point-notations, it is safe to conclude that Nian composed Shixue into both a poetical anthology and his autobiography to some extent.
Schubert defects in Lagrangian Grassmannians
Gu, Wei; Mihalcea, Leonardo; Sharpe, Eric R.; Xu, Weihong; Zhang, Hao; Zou, Hao (2025-06-13)
In this paper, we propose a construction of GLSM defects corresponding to Schubert cycles in Lagrangian Grassmannians, following recent work of Closset-Khlaif on Schubert cycles in ordinary Grassmannians. In the case of Lagrangian Grassmannians, there are superpotential terms in both the bulk GLSM as well as on the defect itself, enforcing isotropy constraints. We check our construction by comparing the locus on which the GLSM defect is supported to mathematical descriptions, checking dimensions, and perhaps most importantly, comparing defect indices to known and expected polynomial invariants of the Schubert cycles in quantum cohomology and quantum K theory.
Model error propagation in a compatible tree volume, biomass, and carbon prediction system
Westfall, James A.; Radtke, Philip J.; Walker, David M.; Coulston, John W. (2025-06-10)
Background: Individual tree attributes such as volume, biomass and carbon mass are widely known to be highly correlated. As these attributes are typically predicted from statistical models, frameworks that provide compatible relationships among these attributes are usually preferred over approaches that provide independent predictions. However, the propagation of model error can be a concern as this compatibility often relies on predictions for one attribute providing the basis for other attributes. In this study, a compatible tree volume, biomass, and carbon prediction system was evaluated to ascertain how model prediction uncertainty propagates through the system and to examine the contribution to uncertainty in population estimates. Results: Generally, the total and merchantable stem volume predictions are used to derive associated biomass values and subsequently biomass is converted to carbon. As expected, the amount of uncertainty due to the models follows volume < biomass < carbon such that the carbon attribute is the most affected by error propagation. Biomass and associated carbon in tree branches tended to have larger model uncertainty than the stem components due to smaller sample sizes and a greater proportion of unexplained variation. In this model system, direct predictions of whole tree biomass provide the biomass basis and stem and branch components are harmonized to sum to the whole tree value. Corresponding harmonized carbon content values are obtained through application of a common carbon fraction. As such, whole tree biomass and carbon tended to have less model uncertainty than the constituent components primarily due to fewer contributing sources. Conclusions: Although a wide range of outcomes are realized across the various volume, biomass, and carbon components, increases in the standard error of the population estimate due to model uncertainty were always less than 5% and usually smaller than 3%. Thus, forest inventory data users desiring population estimates of tree volume, biomass, and carbon can expect little additional uncertainty due to the prediction model system while benefitting from the implicit compatibility among attributes.
Superselection rules, quantum error correction, and quantum chromodynamics
Bao, Ning; Cao, ChunJun; Chatwin-Davies, Aidan; Cheng, Gong; Zhu, Guanyu (2025-05-28)
We investigate the relationship between superselection rules and quantum error correcting codes. We demonstrate that the existence of a superselection rule implies the Knill-Laflamme condition in quantum error correction. As an example, we examine the code built from quantum chromodynamics, where the proton and neutron states in the model are explored as different superselection sectors that protect logical information. Finally we comment on topological quantum error correcting codes and supersymmetric quantum field theory within this framework.
Quality assurance and quality control of the 26 m 2 SiPM production for the DarkSide-20k dark matter experiment
Acerbi, F.; Adhikari, P.; Agnes, P.; Ahmad, I.; Albergo, S.; Albuquerque, I. F.; Alexander, T.; Alton, A. K.; Amaudruz, P.; Angiolilli, M.; Aprile, E.; Atzori Corona, M.; Auty, D. J.; Ave, M.; Avetisov, I. C.; Azzolini, O.; Back, H. O.; Balmforth, Z.; Barrado Olmedo, A.; Barrillon, P.; Batignani, G.; Bhowmick, P.; Bloem, M.; Blua, S.; Bocci, V.; Bonivento, W.; Bottino, B.; Boulay, M. G.; Buchowicz, A.; Bussino, S.; Busto, J.; Cadeddu, M.; Cadoni, M.; Calabrese, R.; Camillo, V.; Caminata, A.; Canci, N.; Capra, A.; Caravati, M.; Cardenas-Montes, M.; Cargioli, N.; Carlini, M.; Castello, P.; Cavalcante, P.; Cebrian, S.; Cela Ruiz, J.; Chashin, S.; Chepurnov, A.; Cifarelli, L.; Cintas, D.; Cleveland, B.; Coadou, Y.; Cocco, V.; Colaiuda, D.; Conde Vilda, E.; Consiglio, L.; Costa, B. S.; Czubak, M.; D’Auria, S.; Da Rocha Rolo, M. D.; Darbo, G.; Davini, S.; de As mundis, R.; De Cecco, S.; Dellacasa, G.; Derbin, A. V.; Capua, F. D.; Noto, L. D.; Stefano, P. D.; Dias, L. K.; Dionisi, C.; Dolganov, G.; Dordei, F.; Dronik, V.; Elersich, A.; Ellingwood, E.; Erjavec, T.; Fearon, N.; Fernandez Diaz, M.; Ficorella, A.; Fiorillo, G.; Franchini, P.; Franco, D.; Frandini Gatti, H.; Frolov, E.; Gabriele, F.; Gahan, D.; Galbiati, C.; Galiski, G.; Gallina, G.; Gallus, G.; Garbini, M.; Garcia Abia, P.; Gawdzik, A.; Gendotti, A.; Giovanetti, G. K.; Goicoechea Casanueva, V.; Gola, A.; Grandi, L.; Grauso, G.; Grilli di Cortona, G.; Grobov, A.; Gromov, M.; Gulino, M.; Guo, C.; Hackett, B. R.; Hallin, A.; Hamer, A.; Haranczyk, M.; Hessel, T.; Horikawa, S.; Hu, J.; Hubaut, F.; Hucker, J.; Hugues, T.; Hungerford, E. V.; Ianni, A.; Ippoliti, G.; Ippolito, V.; Jamil, A.; Jillings, C.; Keloth, R.; Kemmerich, N.; Kemp, A.; Kester, Carlos E.; Kimura, M.; Kondo, K.; Korga, G.; Kotsiopoulou, L.; Koulosousas, S.; Kubankin, A.; Kunze, P.; Kuss, M.; Kuźniak, M.; Kuzwa, M.; La Commara, M.; Lai, M.; Le Guirriec, E.; Leason, E.; Leoni, A.; Lidey, L.; Lissia, M.; Luzzi, L.; Lychagina, O.; Macfadyen, O.; Machulin, I. N.; Manecki, S.; Manthos, I.; Marasciulli, A.; Margutti, G.; Mari, S. M.; Mariani, C.; Maricic, J.; Martinez, M.; Martoff, C. J.; Matteucci, G.; Mavrokoridis, K.; Mazza, E.; McDonald, A. B.; Merzi, S.; Messina, A.; Milincic, R.; Minutoli, S.; Mitra, A.; Monroe, J.; Moretti, E.; Morrocchi, M.; Mroz, T.; Muratova, V. N.; Murphy, M.; Murra, M.; Muscas, C.; Musico, P.; Nania, R.; Nessi, M.; Nieradka, G.; Nikolopoulos, K.; Nikoloudaki, E.; Nowak, J.; Olchanski, K.; Oleinik, A.; Oleynikov, V.; Organtini, P.; Ortiz de Solrzano, A.; Pallavicini, M.; Pandola, L.; Pantic, E.; Paoloni, E.; Papi, D.; Pastuszak, G.; Paternoster, G.; Pegoraro, P. A.; Pelczar, K.; Perez, R.; Pesudo, V.; Piacentini, S.; Pino, N.; Plante, G.; Pocar, A.; Poehlmann, M.; Pordes, S.; Pralavorio, P.; Preosti, E.; Price, D.; Puglia, S.; Queiroga Bazetto, M.; Ragusa, F.; Ramachers, Y.; Ramirez, A.; Ravinthiran, S.; Razeti, M.; Renshaw, A. L.; Rescigno, M.; Resconi, S.; Retiere, F.; Rignanese, L. P.; Rivetti, A.; Roberts, A.; Roberts, C.; Rogers, G.; Romero, L.; Rossi, M.; Rubbia, A.; Rudik, D.; Sabia, M.; Salomone, P.; Samoylov, O.; Sanfilippo, S.; Santone, D.; Santorelli, R.; Santos, E. M.; Savarese, C.; Scapparone, E.; Schuckman, F. G.; Scioli, G.; Semenov, D. A.; Sheshukov, A.; Simeone, M.; Skensved, P.; Skorokhvatov, M. D.; Smirnov, O.; Smirnova, T.; Smith, B.; Sotnikov, A.; Spadoni, F.; Spangenberg, M.; Stefanizzi, R.; Steri, A.; Stornelli, V.; Stracka, S.; Sulis, S.; Sung, A.; Sunny, C.; Suvorov, Y.; Szelc, A. M.; Taborda, O.; Tartaglia, R.; Taylor, A.; Taylor, J.; Testera, G.; Thieme, K.; Thompson, A.; Torres-Lara, S.; Tricomi, A.; Unzhakov, E. V.; Van Uffelen, M.; Viant, T.; Viel, S.; Vishneva, A.; Vogelaar, R. B.; Vossebeld, J.; Vyas, B.; Wada, M.; Walczak, M.; Wang, Y.; Wang, H.; Westerdale, S.; Williams, L.; Wojaczyski, R.; Wojcik, M. M.; Wojcik, M.; Wright, T.; Xie, Y.; Yang, C.; Yin, J.; Zabihi, A.; Zakhary, P.; Zani, A.; Zhang, Y.; Zhu, T.; Zichichi, A.; Zuzel, G.; Zykova, M. P. (2025-05-14)
DarkSide-20k is a novel liquid argon dark matter detector currently under construction at the Laboratori Nazionali del Gran Sasso (LNGS) of the Istituto Nazionale di Fisica Nucleare (INFN) that will push the sensitivity for Weakly Interacting Massive Particle (WIMP) detection into the neutrino fog. The core of the apparatus is a dual-phase Time Projection Chamber (TPC), filled with 50 tonnes of low radioactivity underground argon (UAr) acting as the WIMP target. NUV-HD-cryo Silicon Photomultipliers (SiPM)s designed by Fondazione Bruno Kessler (FBK) (Trento, Italy) were selected as the photon sensors covering two 10.5 m 2 Optical Planes, one at each end of the TPC, and a total of 5 m 2 photosensitive surface for the liquid argon veto detectors. This paper describes the Quality Assurance and Quality Control (QA/QC) plan and procedures accompanying the production of FBK NUV-HD-cryo SiPM wafers manufactured by LFoundry s.r.l. (Avezzano, AQ, Italy). SiPM characteristics are measured at 77 K at the wafer level with a custom-designed probe station. As of March 2025, 1314 of the 1400 production wafers (94% of the total) for DarkSide-20k were tested. The wafer yield is 93.2 ± 2.5 %, which exceeds the 80% specification defined in the original DarkSide-20k production plan.
New insights into the cold tolerance of upland switchgrass by integrating a haplotype-resolved genome and multi-omics analysis
Wu, Bingchao; Luo, Dan; Yue, Yuesen; Yan, Haidong; He, Min; Ma, Xixi; Zhao, Bingyu; Xu, Bin; Zhu, Jie; Wang, Jing; Jia, Jiyuan; Sun, Min; Xie, Zheni; Wang, Xiaoshan; Huang, Linkai (2025-05-14)
Background: Switchgrass (Panicum virgatum L.) is a bioenergy and forage crop. Upland switchgrass exhibits superior cold tolerance compared to the lowland ecotype, but the underlying molecular mechanisms remain unclear. Results: Here, we present a high-quality haplotype-resolved genome of the upland ecotype “Jingji31.” We then conduct multi-omics analysis to explore the mechanism underlying its cold tolerance. By comparative transcriptome analysis of the upland and lowland ecotypes, we identify many genes with ecotype-specific differential expression, particularly members of the cold-responsive (COR) gene family, under cold stress. Notably, AFB1, ATL80, HOS10, and STRS2 gene families show opposite expression changes between the two ecotypes. Based on the haplotype-resolved genome of “Jingji31,” we detect more cold-induced allele-specific expression genes in the upland ecotype than in the lowland ecotype, and these genes are significantly enriched in the COR gene family. By genome-wide association study, we detect an association signal related to the overwintering rate, which overlaps with a selective sweep region containing a cytochrome P450 gene highly expressed under cold stress. Heterologous overexpression of this gene in rice alleviates leaf chlorosis and wilting under cold stress. We also verify that expression of this gene is suppressed by a structural variation in the promoter region. Conclusions: Based on the high-quality haplotype-resolved genome and multi-omics analysis of upland switchgrass, we characterize candidate genes responsible for cold tolerance. This study advances our understanding of plant cold tolerance, which provides crop breeding for improved cold tolerance.
AEOL-induced NRF2 activation and DWORF overexpression mitigate myocardial I/R injury
Asensio-Lopez, Maria del Carmen; Ruiz-Ballester, Miriam; Pascual-Oliver, Silvia; Bastida-Nicolas, Francisco J.; Sassi, Yassine; Fuster, Jose J.; Pascual-Figal, Domingo; Soler, Fernando; Lax, Antonio (2025-05-15)
Background: The causal relationship between the activation of nuclear factor erythroid 2-related factor 2 (NRF2) and the preservation of SERCA2a function in mitigating myocardial ischemia–reperfusion (mI/R) injury, along with the associated regulatory mechanisms, remains incompletely understood. This study aims to unravel how NRF2 directly or indirectly influences SERCA2a function and its regulators, phospholamban (PLN) and Dwarf Open Reading Frame (DWORF), by testing the pharmacological repositioning of AEOL-10150 (AEOL) in the context of mI/R injury. Methods C57BL6/J, Nrf2 knockout (Nrf2−/−), and wild-type (Nrf2+/+) mice, as well as human induced pluripotent stem cell-derived cardiomyocytes (hiPSCMs) were subjected to I/R injury. Gain/loss of function techniques, RT-qPCR, western blotting, LC/MS/MS, and fluorescence spectroscopy were utilized. Cardiac dimensions and function were assessed by echocardiography. Results: In the early stages of mI/R injury, AEOL administration reduced mitochondrial ROS production, decreased myocardial infarct size, and improved cardiac function. These effects were due to NRF2 activation, leading to the overexpression of the micro-peptide DWORF, consequently enhancing SERCA2a activity. The cardioprotective effect induced by AEOL was diminished in Nrf2−/− mice and in Nrf2/Dworf knockdown models in hiPSCMs subjected to simulated I/R injury. Our data show that AEOL-induced NRF2-mediated upregulation of DWORF disrupts the phospholamban-SERCA2a interaction, leading to enhanced SERCA2a activation and improved cardiac function. Conclusions: Taken together, our study reveals that AEOL-induced NRF2-mediated overexpression of DWORF enhances myocardial function through the activation of the SERCA2a offering promising therapeutic avenues for mI/R injury.
Notes on gauging noninvertible symmetries. Part II. Higher multiplicity cases
Perez-Lona, Alonso; Robbins, D.; Sharpe, Eric R.; Vandermeulen, T.; Yu, Xingyang (2025-05-07)
In this paper we discuss gauging noninvertible zero-form symmetries in two dimensions, extending our previous work. Specifically, in this work we discuss more general gauged noninvertible symmetries in which the noninvertible symmetry is not multiplicity free, and discuss the case of Rep(A4) in detail. We realize Rep(A4) gaugings for the c = 1 CFT at the exceptional point in the moduli space and find new self-duality under gauging a certain non-group algebra object, leading to a larger noninvertible symmetry Rep(SL(2, ℤ3)). We also discuss more general examples of decomposition in two-dimensional gauge theories with trivially-acting gauged noninvertible symmetries.

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