cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.tdcrwx
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.02501599999999 23.960886, 88.948173 23.955309, 88.87324099999999 23.938717, 88.802083 23.911523, 88.736464 23.874401, 88.67801 23.828275, 88.628162 23.774289, 88.588144 23.713781, 88.558932 23.648247, 88.54123300000001 23.579309, 88.535464 23.508668, 88.541748 23.438063, 88.55991299999999 23.369232, 88.589493 23.303866, 88.62974800000001 23.243569, 88.679678 23.189816, 88.738051 23.143924, 88.803433 23.107013, 88.874222 23.079986, 88.948688 23.063501, 89.02501599999999 23.057962, 89.101344 23.063501, 89.17581 23.079986, 89.246599 23.107013, 89.311981 23.143924, 89.37035400000001 23.189816, 89.420284 23.243569, 89.460539 23.303866, 89.49011900000001 23.369232, 89.508284 23.438063, 89.514568 23.508668, 89.508799 23.579309, 89.4911 23.648247, 89.461888 23.713781, 89.42187 23.774289, 89.372022 23.828275, 89.313568 23.874401, 89.24794900000001 23.911523, 89.17679099999999 23.938717, 89.101859 23.955309, 89.02501599999999 23.960886))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007142-260120142942310/datasets/export for details.
DOI: 10.21950/kyv3rc
title: Federico-Tena World Population Historical Database : Equatorial Guinea (Spanish)

description: Project developed by Giovanni Federico (New York University Abu Dhabi) and Antonio Tena Junguito (Universidad Carlos III de Madrid). Dataset: Equatorial Guinea (Spanish)
description: Microsoft Excel
description: Web site: <strong>https://www.uc3m.es/investigacion/federico-tena-population</strong>



<strong>SEE MAP</strong>
DOI: 10.5281/zenodo.18347609
title: Dataset: Caste-specific proboscis extension responses in honey bees to sucrose and royal jelly stimuli

description: Dataset for publication:

Erdem, B., Sevin, S., Arslan, A. C., Gozen, A. G., Alemdar, H., Turgut, A. E., & Sahin, E. (2026). Caste-specific proboscis extension responses in honey bees to sucrose and royal jelly stimuli. BioRxiv. https://doi.org/BIORXIV/2026/701277

Proboscis extension responses (PER) were found in the files. PER is a binary outcome (0 or 1) recorded repeatedly across trials. Each bee received a total of 60 trials presented in a pseudorandom order (S, W, RJ, M, S, M, W, RJ, M, S, W, RJ, M, W, S, RJ, M, W, RJ, S, W, S, RJ, M, S, M, W, RJ, M, S, W, RJ, M, W, S, RJ, M, W, RJ, S, W, S, RJ, M, S, M, W, RJ, M, S, W, RJ, M, W, S, RJ, M, W, RJ, S), where S = sucrose, W = water, RJ = royal jelly, and M = mixture, each stimulus appears 15 times overall with no consecutive repeats.

Forager_PER_Data.xlsx is the PER of forager bees.

Queen_PER_Data.xlsx is the PER of the queen bees.

1DayOld_PER_Data.xlsx is the PER of the 1-day-old workers.
DOI: 10.5281/zenodo.18347610
title: Dataset: Caste-specific proboscis extension responses in honey bees to sucrose and royal jelly stimuli

description: Dataset for publication:

Erdem, B., Sevin, S., Arslan, A. C., Gozen, A. G., Alemdar, H., Turgut, A. E., & Sahin, E. (2026). Caste-specific proboscis extension responses in honey bees to sucrose and royal jelly stimuli. BioRxiv. https://doi.org/BIORXIV/2026/701277

Proboscis extension responses (PER) were found in the files. PER is a binary outcome (0 or 1) recorded repeatedly across trials. Each bee received a total of 60 trials presented in a pseudorandom order (S, W, RJ, M, S, M, W, RJ, M, S, W, RJ, M, W, S, RJ, M, W, RJ, S, W, S, RJ, M, S, M, W, RJ, M, S, W, RJ, M, W, S, RJ, M, W, RJ, S, W, S, RJ, M, S, M, W, RJ, M, S, W, RJ, M, W, S, RJ, M, W, RJ, S), where S = sucrose, W = water, RJ = royal jelly, and M = mixture, each stimulus appears 15 times overall with no consecutive repeats.

Forager_PER_Data.xlsx is the PER of forager bees.

Queen_PER_Data.xlsx is the PER of the queen bees.

1DayOld_PER_Data.xlsx is the PER of the 1-day-old workers.
DOI: 10.15468/dl.346vdk
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((88.76444499999999 24.055964, 88.687545 24.050387, 88.61255800000001 24.033795, 88.541348 24.0066, 88.47568200000001 23.969479, 88.417185 23.923353, 88.367301 23.869367, 88.32725499999999 23.808858, 88.298024 23.743326, 88.280312 23.674388, 88.27454 23.603747, 88.28083100000001 23.533143, 88.299009 23.464314, 88.32861200000001 23.398949, 88.368897 23.338653, 88.418863 23.284901, 88.477277 23.23901, 88.542705 23.202101, 88.613544 23.175074, 88.688064 23.15859, 88.76444499999999 23.15305, 88.84082600000001 23.15859, 88.915346 23.175074, 88.98618500000001 23.202101, 89.051613 23.23901, 89.110027 23.284901, 89.159993 23.338653, 89.200278 23.398949, 89.22988100000001 23.464314, 89.248059 23.533143, 89.25435 23.603747, 89.24857799999999 23.674388, 89.23086600000001 23.743326, 89.201635 23.808858, 89.16158900000001 23.869367, 89.111705 23.923353, 89.053208 23.969479, 88.987542 24.0066, 88.916332 24.033795, 88.841345 24.050387, 88.76444499999999 24.055964))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007144-260120142942310/datasets/export for details.
DOI: 10.15468/dl.djfxm6
title: Occurrence Download

description: A dataset containing 50 species occurrences available in GBIF matching the query:
{"type":"and","predicates":[{"type":"within","geometry":"POLYGON ((89.16622700000001 23.34445, 89.089743 23.338873, 89.01515999999999 23.322281, 88.944333 23.295087, 88.879019 23.257966, 88.82083299999999 23.21184, 88.77121099999999 23.157853, 88.731373 23.097343, 88.70229 23.031807, 88.684665 22.962865, 88.678915 22.892218, 88.685163 22.821607, 88.703238 22.75277, 88.732677 22.687396, 88.772745 22.627091, 88.822445 22.573331, 88.88055199999999 22.527431, 88.945638 22.490515, 89.016108 22.463483, 89.09024100000001 22.446995, 89.16622700000001 22.441454, 89.24221300000001 22.446995, 89.316346 22.463483, 89.386816 22.490515, 89.451902 22.527431, 89.510009 22.573331, 89.559709 22.627091, 89.599777 22.687396, 89.629216 22.75277, 89.647291 22.821607, 89.65353899999999 22.892218, 89.647789 22.962865, 89.63016399999999 23.031807, 89.60108099999999 23.097343, 89.561243 23.157853, 89.51162100000001 23.21184, 89.453435 23.257966, 89.388121 23.295087, 89.317294 23.322281, 89.242711 23.338873, 89.16622700000001 23.34445))"},{"type":"equals","key":"CLASS_KEY","value":"212","matchCase":false},{"type":"greaterThanOrEquals","key":"YEAR","value":"2015","matchCase":false},{"type":"not","predicate":{"type":"in","key":"BASIS_OF_RECORD","values":["MATERIAL_CITATION","MATERIAL_SAMPLE","PRESERVED_SPECIMEN"],"matchCase":false}},{"type":"lessThanOrEquals","key":"COORDINATE_UNCERTAINTY_IN_METERS","value":"10000","matchCase":false},{"type":"equals","key":"LICENSE","value":"CC BY 4.0","matchCase":false}]}

 The dataset includes 50 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007145-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5066/p9kzcm54
title: National Land Cover Database (NLCD) 2019 Products (ver. 3.0, February 2024)

description: The U.S. Geological Survey (USGS), in partnership with several federal agencies, has developed and released five National Land Cover Database (NLCD) products over the past two decades: NLCD 1992, 2001, 2006, 2011, and 2016. The 2016 release saw landcover created for additional years of 2003, 2008, and 2013. These products provide spatially explicit and reliable information on the Nation’s land cover and land cover change. To continue the legacy of NLCD and further establish a long-term monitoring capability for the Nation’s land resources, the USGS has designed a new generation of NLCD products named NLCD 2019. The NLCD 2019 design aims to provide innovative, consistent, and robust methodologies for production of a multi-temporal land cover and land cover change database from 2001 to 2019 at 2–3-year intervals. Comprehensive research was conducted and resulted in developed strategies for NLCD 2019: continued integration between impervious surface and all landcover products with impervious surface being directly mapped as developed classes in the landcover, a streamlined compositing process for assembling and preprocessing based on Landsat imagery and geospatial ancillary datasets; a multi-source integrated training data development and decision-tree based land cover classifications; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a hierarchical theme-based post-classification and integration protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and an automated scripted operational system for the NLCD 2019 production. The performance of the developed strategies and methods were tested in twenty composite referenced areas throughout the conterminous U.S. An overall accuracy assessment from the 2016 publication give a 91% overall landcover accuracy, with the developed classes also showing a 91% accuracy in overall developed. Results from this study confirm the robustness of this comprehensive and highly automated procedure for NLCD 2019 operational mapping. Questions about the NLCD 2019 land cover product can be directed to the NLCD 2019 land cover mapping team at USGS EROS, Sioux Falls, SD (605) 594-6151 or mrlc@usgs.gov. See included spatial metadata for more details.
DOI: 10.5281/zenodo.18349513
title: R script for the construction and analysis of fatal occupational falls among brazilian workers, 2015–2023

description: This R script was developed to prepare and analyze data from the Mortality Information System (SIM), available through DATASUS, Ministry of Health, Brazil. It supports the construction of the analytical dataset and the descriptive and inferential analyses for an article aimed at characterizing deaths among workers aged 18 to 69 years due to falls during economic activity in Brazil, between 2015 and 2023. The analyses consider sociodemographic characteristics, medical assistance, occupational groups, and geographic distribution, as well as the estimation of odds ratios for mortality.
DOI: 10.5281/zenodo.18349666
title: RawData gene-gene interaction

description: RawData table (excel file) shows: sample code, sex, diagnosis, age at onset and age at last follow-up (≤55, 56-65, 66-74, ≥75), genetic group (sheet 1); variants identified with chromosomal position, MAF, genotypes probability, number of homozygous and heterozygotes, genetic group (sheet 2).

This research was funded by the European Union - Next Generation EU – NRRP M6C2 - Investment 2.1 Enhancement and strengthening of biomedical research in the NHS - PNRR-MR1-2022-12375654 - Cup Code: C83C22001300001

Users must clarify how they intend to use data here uploaded and whether the research protocol has been approved by an Ethics committee.
DOI: 10.5281/zenodo.18349665
title: RawData gene-gene interaction

description: RawData table (excel file) shows: sample code, sex, diagnosis, age at onset and age at last follow-up (≤55, 56-65, 66-74, ≥75), genetic group (sheet 1); variants identified with chromosomal position, MAF, genotypes probability, number of homozygous and heterozygotes, genetic group (sheet 2).

This research was funded by the European Union - Next Generation EU – NRRP M6C2 - Investment 2.1 Enhancement and strengthening of biomedical research in the NHS - PNRR-MR1-2022-12375654 - Cup Code: C83C22001300001

Users must clarify how they intend to use data here uploaded and whether the research protocol has been approved by an Ethics committee.
DOI: 10.15468/dl.x8eeam
title: Occurrence Download

description: A dataset containing 2268 records in GBIF matching the query:
SELECT
 '173' AS fish_cell,
 GBIF_MGRSCode(1000, decimalLatitude, decimalLongitude, 0) AS cell, -- NO randomization
 COUNT(DISTINCT speciesKey) AS species_richness
 FROM occurrence
 WHERE hasCoordinate = TRUE
 AND speciesKey IS NOT NULL
 AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
 AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
 AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
 AND decimalLatitude &gt;= 0.0
 AND decimalLatitude &lt;= 4.045127286108716
 AND decimalLongitude &gt;= 9.977774122253765
 AND decimalLongitude &lt;= 14.989708454849
 AND "year" &gt;= 2015
 AND "year" &lt;= 2026
 AND (coordinateUncertaintyInMeters &lt;= 100 OR coordinateUncertaintyInMeters IS NULL)
 GROUP BY fish_cell, cell

 The dataset's 2268 records were derived from 100 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007128-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.31135489
title: Incidence, risk factors and prognostic impact of cerebrovascular events after transcatheter aortic valve implantation

description: Ischaemic cerebrovascular events (CVEs) are a major complication of transcatheter aortic valve implantation (TAVI) in patients with severe aortic stenosis. We aimed to determine the incidence and risk factors for CVE at 30 days and 1 year after TAVI in a large, real-world patient cohort and evaluate the association of these events with all-cause mortality at 1 year. All consecutive patients undergoing TAVI at a single centre between April 2008 and February 2024 were included in the analysis. CVE were defined as a composite of stroke and transient ischaemic attack. One thousand and three patients (mean age 81.8 ± 7.0 years, 52.6% male, median EuroSCORE II 6% [<i>Q</i>1 = 3.51%; <i>Q</i>3 = 10.9%]) underwent TAVI with a self-expandable valve (SEV) (<i>n</i> = 275; 27.4%) or balloon-expandable valve (BEV) (<i>n</i> = 728; 72.6%). The cumulative incidence of CVE was 3.6% (95% confidence interval (95% CI) = [2.6%; 4.9%], <i>n</i> = 36) at 30 days (77.8% within 48 h) and 6.2% (95% CI = [4.8%; 7.8%], <i>n</i> = 62) at 1 year. Risk factors associated with a lower risk of CVE at 30 days included BEV vs. SEV (OR 0.32 [0.16–0.63], <i>p</i> = 0.0009) and larger baseline aortic valve area (AVA) (OR<sub>Unit = 0.1 cm2</sub> 0.74 [0.61–0.91], <i>p</i> = 0.0035), while the risk was higher in the case of new-onset atrial fibrillation (AF) (OR 3.19 [1.18–8.59], <i>p</i> = 0.0218), diabetes (OR 2.00 [1.01–3.97], <i>p</i> = 0.0484), and conversion to sternotomy (OR 16.57 [4.62–59.48], <i>p</i> &lt; 0.0001). Analysis at 1-year follow-up identified the same associations. Finally, the occurrence of CVE significantly increased 1-year all-cause mortality (OR 2.44 [1.32–4.50], <i>p</i> = 0.0045). CVE after TAVI were associated with double the odds of 1-year all-cause mortality. Risk factors associated with CVE include the use of a SEV, new-onset AF, diabetes, conversion to sternotomy, and a smaller AVA.
DOI: 10.6084/m9.figshare.31135489.v1
title: Incidence, risk factors and prognostic impact of cerebrovascular events after transcatheter aortic valve implantation

description: Ischaemic cerebrovascular events (CVEs) are a major complication of transcatheter aortic valve implantation (TAVI) in patients with severe aortic stenosis. We aimed to determine the incidence and risk factors for CVE at 30 days and 1 year after TAVI in a large, real-world patient cohort and evaluate the association of these events with all-cause mortality at 1 year. All consecutive patients undergoing TAVI at a single centre between April 2008 and February 2024 were included in the analysis. CVE were defined as a composite of stroke and transient ischaemic attack. One thousand and three patients (mean age 81.8 ± 7.0 years, 52.6% male, median EuroSCORE II 6% [<i>Q</i>1 = 3.51%; <i>Q</i>3 = 10.9%]) underwent TAVI with a self-expandable valve (SEV) (<i>n</i> = 275; 27.4%) or balloon-expandable valve (BEV) (<i>n</i> = 728; 72.6%). The cumulative incidence of CVE was 3.6% (95% confidence interval (95% CI) = [2.6%; 4.9%], <i>n</i> = 36) at 30 days (77.8% within 48 h) and 6.2% (95% CI = [4.8%; 7.8%], <i>n</i> = 62) at 1 year. Risk factors associated with a lower risk of CVE at 30 days included BEV vs. SEV (OR 0.32 [0.16–0.63], <i>p</i> = 0.0009) and larger baseline aortic valve area (AVA) (OR<sub>Unit = 0.1 cm2</sub> 0.74 [0.61–0.91], <i>p</i> = 0.0035), while the risk was higher in the case of new-onset atrial fibrillation (AF) (OR 3.19 [1.18–8.59], <i>p</i> = 0.0218), diabetes (OR 2.00 [1.01–3.97], <i>p</i> = 0.0484), and conversion to sternotomy (OR 16.57 [4.62–59.48], <i>p</i> &lt; 0.0001). Analysis at 1-year follow-up identified the same associations. Finally, the occurrence of CVE significantly increased 1-year all-cause mortality (OR 2.44 [1.32–4.50], <i>p</i> = 0.0045). CVE after TAVI were associated with double the odds of 1-year all-cause mortality. Risk factors associated with CVE include the use of a SEV, new-onset AF, diabetes, conversion to sternotomy, and a smaller AVA.
DOI: 10.6084/m9.figshare.30747116
title: Picornavirus VP2 protein suppresses innate immunity through selective autophagic degradation of IKBKE/IKKε

description: Senecavirus A (SVA) belongs to the picornaviruses and has emerged as a promising candidate for oncolytic virotherapy in humans. Understanding the immune suppression mechanisms employed by SVA can help optimize its therapeutic efficacy as an oncolytic virus while simultaneously minimizing its immune suppressive effects on normal tissues. In this study, we identified a novel function of the SVA structural protein VP2 as a key viral immune suppressive factor during SVA infection. VP2 targets and degrades IKBKE/IKKε, a key component of the innate immune pathway, thereby suppressing host innate immune responses. It preferentially interacts with the selective autophagic receptor CALCOCO2/NDP52 (calcium binding and coiled-coil domain 2), which then recognizes the K33-linked ubiquitinated IKBKE and delivers it to phagophores for degradation. The E3 ligase RNF114 is responsible for catalyzing the K33-linked ubiquitination of IKBKE at Lys490, and VP2 significantly promoted this modification, which further accelerated IKBKE degradation. Importantly, we found that picornavirus VP2 proteins share this conserved mechanism in degradation of IKBKE and suppression of host innate immunity. These data elucidate the negative regulatory mechanism involving the VP2-RNF114-IKBKE/IKKε-CALCOCO2 axis, and reveal an immune evasion strategy employed by picornaviruses. These findings will provide valuable insights for the development of picornaviral vaccines and antiviral/antitumor therapeutics. <b>Abbreviations</b>: 3-MA: 3-methyladenine; ATG5: autophagy related 5; ATG7: autophagy related 7; CALCOCO2/NDP52: calcium binding and coiled-coil domain 2; CQ: chloroquine; co-IP: co-immunoprecipitation; DAPI: 4’,6-diamidino-2’-phenylindole; EV71: enterovirus 71; FMDV: foot-and-mouth disease virus; hpi: hours post-infection; IFN: interferon; IKBKE/IKKε: inhibitor of nuclear factor kappa B kinase subunit epsilon); ISGs: IFN-stimulated genes; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MG132: cbz-leu-leu-leucinal; MOI: multiplicity of infection; NBR1: NBR1 autophagy cargo receptor; OPTN: optineurin; RNF114: ring finger protein 114; RT-PCR: real-time polymerase chain reaction; siRNA: small interfering RNA; SQSTM1/p62: sequestosome 1; SVA: Senecavirus A; TCID<sub>50</sub>: 50% tissue culture infectious doses. TOLLIP: toll interacting protein; TRIM17: tripartite motif containing 17; TRIM25: tripartite motif containing 25; TRIM28: tripartite motif containing 28; TRIP12/THRI12: thyroid hormone receptor interactor 12; Ub: ubiquitin; Vec: vector; WCL: whole-cell lysate; WT: wild-type.
DOI: 10.6084/m9.figshare.30747116.v1
title: Picornavirus VP2 protein suppresses innate immunity through selective autophagic degradation of IKBKE/IKKε

description: Senecavirus A (SVA) belongs to the picornaviruses and has emerged as a promising candidate for oncolytic virotherapy in humans. Understanding the immune suppression mechanisms employed by SVA can help optimize its therapeutic efficacy as an oncolytic virus while simultaneously minimizing its immune suppressive effects on normal tissues. In this study, we identified a novel function of the SVA structural protein VP2 as a key viral immune suppressive factor during SVA infection. VP2 targets and degrades IKBKE/IKKε, a key component of the innate immune pathway, thereby suppressing host innate immune responses. It preferentially interacts with the selective autophagic receptor CALCOCO2/NDP52 (calcium binding and coiled-coil domain 2), which then recognizes the K33-linked ubiquitinated IKBKE and delivers it to phagophores for degradation. The E3 ligase RNF114 is responsible for catalyzing the K33-linked ubiquitination of IKBKE at Lys490, and VP2 significantly promoted this modification, which further accelerated IKBKE degradation. Importantly, we found that picornavirus VP2 proteins share this conserved mechanism in degradation of IKBKE and suppression of host innate immunity. These data elucidate the negative regulatory mechanism involving the VP2-RNF114-IKBKE/IKKε-CALCOCO2 axis, and reveal an immune evasion strategy employed by picornaviruses. These findings will provide valuable insights for the development of picornaviral vaccines and antiviral/antitumor therapeutics. <b>Abbreviations</b>: 3-MA: 3-methyladenine; ATG5: autophagy related 5; ATG7: autophagy related 7; CALCOCO2/NDP52: calcium binding and coiled-coil domain 2; CQ: chloroquine; co-IP: co-immunoprecipitation; DAPI: 4’,6-diamidino-2’-phenylindole; EV71: enterovirus 71; FMDV: foot-and-mouth disease virus; hpi: hours post-infection; IFN: interferon; IKBKE/IKKε: inhibitor of nuclear factor kappa B kinase subunit epsilon); ISGs: IFN-stimulated genes; MAP1LC3/LC3: microtubule associated protein 1 light chain 3; MG132: cbz-leu-leu-leucinal; MOI: multiplicity of infection; NBR1: NBR1 autophagy cargo receptor; OPTN: optineurin; RNF114: ring finger protein 114; RT-PCR: real-time polymerase chain reaction; siRNA: small interfering RNA; SQSTM1/p62: sequestosome 1; SVA: Senecavirus A; TCID<sub>50</sub>: 50% tissue culture infectious doses. TOLLIP: toll interacting protein; TRIM17: tripartite motif containing 17; TRIM25: tripartite motif containing 25; TRIM28: tripartite motif containing 28; TRIP12/THRI12: thyroid hormone receptor interactor 12; Ub: ubiquitin; Vec: vector; WCL: whole-cell lysate; WT: wild-type.