Universal target enrichment kits maximize utility across wide evolutionary breadth while minimizing the number of baits required to create a cost‐efficient kit. The Angiosperms353 kit has been successfully used to capture loci throughout the angiosperms, but the default target reference file includes sequence information from only 6–18 taxa per locus. Consequently, reads sequenced from on‐target DNA molecules may fail to map to references, resulting in fewer on‐target reads for assembly, and reducing locus recovery.We expanded the Angiosperms353 target file, incorporating sequences from 566 transcriptomes to produce a ‘mega353’ target file, with each locus represented by 17–373 taxa. This mega353 file is a drop‐in replacement for the original Angiosperms353 file in HybPiper analyses. We provide tools to subsample the file based on user‐selected taxon groups, and to incorporate other transcriptome or protein‐coding gene data sets.Compared to the default Angiosperms353 file, the mega353 file increased the percentage of on‐target reads by an average of 32%, increased locus recovery at 75% length by 49%, and increased the total length of the concatenated loci by 29%.https://github.com/chrisjackson‐pellicle/NewTargets.Increasing the phylogenetic density of the target reference file results in improved recovery of target capture loci. The mega353 file and associated scripts are available at:  Target enrichment  has become the leading high‐throughput sequencing methodology for phylogenomics, offering reliable retrieval of hundreds or thousands of loci at a reasonable price per base pair  de novo assembly of reads and subsequent matching of contigs to target loci, or (2) mapping reads to each locus, followed by de novo assembly of the mapped reads for each locus. Various pipelines are available to perform locus assembly, such as HybPiper . To obtain a phylogenetically diverse set of angiosperm sequences from which to recover the Angiosperms353 loci, transcriptomes were downloaded from the 1KP portal .The target file for the Angiosperms353 kit was downloaded from E‐value cut‐off of 1e‐50, and the top hit (if present) was recovered. Transcriptome hits were added to the corresponding locus alignment, and the 5′ and 3′ termini were trimmed to the longest original target file sequence from either Arabidopsis thaliana (L.) Heynh. (Brassicaceae), Amborella trichopoda Baill. (Amborellaceae), or Oryza sativa L. (Poaceae), as at least one of these three species was included for each locus in the default353 target file. In cases where a transcriptome hit sequence was shorter than the longest original target file sequence for a given locus, the transcriptome hit sequence was extended by grafting with the 5′ and/or 3′ termini of the closest related original sequence. If the resulting grafted sequence was still shorter than the longest original target file sequence, it was grafted again with the longest original sequence. In such cases, the resulting target file sequence was therefore a chimeric construct, and these cases are flagged in the sequence name. This grafting process was necessary as HybPiper translates a single chosen target file sequence for each locus and sample, and the resulting protein sequence is used as a query in Exonerate . In cases where a frameshift could not be corrected, the corresponding transcriptome hit sequence was removed for that locus/sample. Finally, sequences were extracted from each locus alignment, gap positions were removed, and all sequences were concatenated to create a new target file.As recovery of target loci using HybPiper requires correct translation of the chosen target file sequences in the first reading frame, any frameshifts observed in trimmed and/or grafted transcriptome hit sequences were corrected or compensated for (see https://github.com/chrisjackson‐pellicle/NewTargets for full options). In addition to the chosen samples, all sequences from the default353 target file are retained.To tailor the large mega353 target file to investigation‐specific taxon sampling, we include the script filter_megatarget.py. This script can be used to create a filtered target file based on user‐selected taxa or taxon groups, defined by unique 1KP transcriptome codes, families, orders, or clades  to be added to an existing target file. A target file and a directory of transcriptomes are the only inputs required. For Angiosperms353 analyses, this script can be run using a filtered mega353 target file to expand phylogenetic coverage of target file sequences in a custom manner. The default BYO_transcriptome.py pipeline is the same as that described above for creation of the mega353 target file. Optionally, a flag can be specified to discard short transcriptome hits rather than grafting them, and this option can be applied with a user‐specified length threshold. This allows recovery of non‐chimeric homologous sequences from transcriptomes that can be used in downstream phylogenetic analyses. For additional options, see Azorella Lam., Apiaceae; Nepenthes L., Nepenthaceae; Cyperus L., Cyperaceae [Larridon et al., Bulbophyllum Thouars, Orchidaceae), as well as the data set used to test the bait kit in the original Angiosperms353 publication , families (Ericaceae), and genera , Lactuca sativa L. (Cichorioideae), and Carthamus tinctorius L. (Carduoideae). The Asteraceae target file (comprising only the H. annuus and L. sativa target sequences) was expanded using 1KP transcriptomes of taxa closely related to Asteraceae tribe Gnaphalieae (Appendix Abelmoschus esculentus (L.) Moench, Hibiscus cannabinus L., and Hibiscus syriacus L. The Hibisceae target file was expanded using available sequence data from the other Malvaceae subfamily Malvoideae tribes, Malveae and Gossypieae . In the mega353 target file, there are 98,994 target reference sequences, and each locus is represented on average by 280 reference sequences (range 17–373). In terms of improvement in phylogenetic density, the default353 target file has an average of 13.5 orders and 13.5 families per locus, whereas the mega353 target file has an average of 49.8 orders and 170 families per locus see Fig. .To compare locus recovery between the default353 and filtered mega353 target files, results were evaluated using statistics provided by the HybPiper scripts hybpiper_stats.py and get_seq_lengths.py, averaged across all samples for each data set Table . Four sthttps://github.com/chrisjackson‐pellicle/NewTargets/wiki for further information). Nonetheless, the overall length of concatenated sequences was still higher when using the mega353‐derived target files compared to the default files.For each data set, the mega353 target file improved each of these measures Table , Fig. 3.Bulbophyllum data set, analyses using the target file with sequences from 12 additional Bulbophyllum transcriptomes showed improvements over the filtered Orchidaceae target file, with a 2.5% increase in mapped reads, an 11% increase in loci over 75%, and a 7% increase in concatenated loci length . For example, a filtered mega353 target file for Malvales could comprise the target sequences from the order, in addition to selected outgroup sequences , and a specific 1KP sample name . Filtering of the mega353 target file allows the user to develop a data set–appropriate target file and ensures a more efficient trade‐off between increased locus recovery and computational time.The use of the mega353 target file does increase the computation time for HybPiper. For this reason, we recommend strategically selecting the phylogenetic rank used to filter the target file , rather than using the complete mega353 target file. Filtering can be applied using multiple phylogenetic ranks or sample identifiers  compared to the mega353 (blue) target files.Click here for additional data file.APPENDIX S4. The number of target sequences in the default353 target file compared to the mega353 target file, including the average number of targets per locus, and the average number of orders and families for each locus.Click here for additional data file.APPENDIX S5. Heatmap of locus lengths for each sample for each locus for the Angiosperms353 exemplar data set, where the default353 locus lengths are subtracted from the mega353 locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S6. Heatmap of locus lengths for each sample for each locus for the Asparagales data set, where the default353 locus lengths are subtracted from the mega353 (order filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S7. Heatmap of locus lengths for each sample for each locus for the Azorella data set, where the default353 locus lengths are subtracted from the mega353 (family filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S8. Heatmap of locus lengths for each sample for each locus for the Azorella data set, where the default353 locus lengths are subtracted from the mega353 (order filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S9. Heatmap of locus lengths for each sample for each locus for the Bulbophyllum data set, where the default353 locus lengths are subtracted from the mega353 (family filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S10. Heatmap of locus lengths for each sample for each locus for the Bulbophyllum data set, where the default353 locus lengths are subtracted from the mega353 (family + genus filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S11. Heatmap of locus lengths for each sample for each locus for the Cyperaceae data set, where the default353 locus lengths are subtracted from the mega353 (family filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S12. Heatmap of locus lengths for each sample for each locus for the Cyperaceae data set, where the default353 locus lengths are subtracted from the mega353 (order filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S13. Heatmap of locus lengths for each sample for each locus for the Ericaceae data set, where the default353 locus lengths are subtracted from the mega353 (family filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S14. Heatmap of locus lengths for each sample for each locus for the Ericaceae data set, where the default353 locus lengths are subtracted from the mega353 (order filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S15. Heatmap of locus lengths for each sample for each locus for the Nepenthes data set, where the default353 locus lengths are subtracted from the mega353 (order filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S16. Heatmap of locus lengths for each sample for each locus for the Sapindales data set, where the default353 locus lengths are subtracted from the mega353 (order filtered) locus lengths. Increases in length are shown in blue; decreases in length are shown in red.Click here for additional data file.APPENDIX S17. Summary of paralog warnings produced by HybPiper for the default353 and mega353 target files.Click here for additional data file.APPENDIX S18. Comparing custom bait kit target files (Asteraceae/Hibisceae) that were expanded using BYO_transcriptomes.py. Values represent averages of each data set for each target file.Click here for additional data file.


Agrobacterium-based infiltration has been widely adopted as a tool for VIGS and in vitro-inoculation of plant virus. Most agrobacterium-based infiltration methods applied to VIGS and virus inoculation have the characteristics of low transformation efficiencies, long plant growth time, large amounts of plant tissue, large test spaces, and complex preparation procedures. Therefore, a rapid, simple, economical, and highly efficient VIGS and virus inoculation method is in need. Previous studies have shown that the selection of suitable plant tissues and inoculation sites is the key to successful infection.Virus-induced gene silencing (VIGS) is one of the most convenient and powerful methods of reverse genetics. In vitro-inoculation of plant virus is an important method for studying the interactions between viruses and plants. Tobacco rattle virus (TRV) mediated VIGS and Tomato yellow leaf curl virus (TYLCV) for virus inoculation were developed in tomato plants based on the agrobacterium tumefaciens-based infiltration by injection of the no-apical-bud stem section (INABS). The no-apical-bud stem section had a “Y- type” asymmetric structure and contained an axillary bud that was about 1–3 cm in length. This protocol provides high transformation (56.7%) and inoculation efficiency (68.3%), which generates VIGS transformants or diseased plants in a very short period (8 dpi). Moreover, it greatly reduces the required experimental space. This method will facilitate functional genomic studies and large-scale disease resistance screening.In this study, Overall, a rapid, simple, and highly efficient method for VIGS and virus inoculation by INABS was developed in tomato. It was reasonable to believe that it can be used as a reference for the other virus inoculation methods and for the application of VIGS to other crops  that develop axillary buds and can survive from cuttings.The online version contains supplementary material available at 10.1186/s12870-021-03331-9. Tobacco rattle virus (TRV), has a broad host range and has been used in VIGS as a vector to study gene function in many species, including Solanum spp.   or for virus inoculation in vitro (TYLCV-[CN:SH2]) was injected into tomato no-apical-bud stem sections. The needle was inserted into the upper end of the top incision, 0.5–1 ml of the bacterial liquid was injected, and the needle was held in place for 1–2 min. The needle was pulled out slowly, and the bacterial liquid naturally formed a liquid film at the incision site  or TYLCV  was injected into different parts of the tomato plants respectively: the no-apical-bud stem section, the dorsal leaf, or the basal stem. The no-apical-bud stem sections without any agrobacterium injection or infiltration were used as WT controls. Each treatment was replicated one-hundred times. Three biological repetitions were developed.Agroinfiltration liquid containing TRV , TRV-The injection of the no-apical-bud stem section is described above.Agrobacterium infiltration. The agroinfiltration liquid was infiltrated into the back of the tomato leaves using 5-ml syringes without needles.Tomato seedlings at the three-true-leaf stage were used for dorsal leaf Agrobacterium infiltration using 5-ml syringes with needles. Three sites on each stem were infiltrated.Tomato seedlings at the three-true-leaf stage were used for basal stem After infiltration, the plants were grown in darkness for 48 h at 25–28 °C with a relative humidity of 80–90%. Thereafter, the stem segments were cultured in a pest-controlled greenhouse at 25–28 °C with 70% relative humidity and a 16 h/8 h light/dark photoperiod. The symptoms of VIGS and infection of TYLCV were recorded and evaluated.Total RNA was extracted from the leaves of the wild type (non-transgenic control), pTRV1 and pTRV2 (empty vector controls), and symptomatic plants using the TRIzol reagent  according to the manufacturer’s instructions. First-strand cDNA was synthesized using mixtures containing 2 mg of total RNA, oligo (dT), and M-MLV Reverse Transcriptase  according to the manufacturer’s instructions. The cDNAs were then used as templates for quantitative RT–PCR (qRT–PCR) with gene-specific primers outside the gene regions targeted for silencing.Total DNA was extracted from leaves that grew from axillary buds inoculated by TYLCV. qRT–PCR was performed with SYBR Premix Ex Taq  using an ABI Prism 7500 instrument  following the manufacturers’ recommendations. The primers used for qRT–PCR are listed in supplementary materials Table S.2O2. Tomato leaves were excised from plants and placed into 20-ml tubes, covered with a DAB-HCl solution , and incubated in a growth chamber for 8 h at 25 °C. When the red-brown DAB solution moved to the top of leaves via the veins, the chlorophyll of whole blades was removed by immersing the samples directly in a fixative solution (anhydrous ethanol: acetic acid = 3:1) for 24 h. Leaves staining was developed with hydrated trichloroacetaldehyde three times and observed under an optical microscope .Inoculated leaves were stained with 3,3-diaminobenzidine (DAB)  to exami− 2 s− 1, 16 h light/8 h dark photoperiod). After 1 month, when the stems were ~ 35 cm in length, two-hundred no-apical-bud stem sections were harvested for each variety , and virus inoculation experiments were performed.Seeds of the TYLCV-susceptible tomato varieties ‘Money Maker’, ‘Zhongshu 4’  and the highly TYLCV-resistant variety ‘Jinpeng 322’ (provided by the Xi’an Jinpeng Seed Co.) were germinated in a growth chamber .


While the economic burden of influenza infection is well described among adults aged 65 and older, less is known about younger adults. A systematic literature review was conducted to describe the economic burden of seasonal influenza in adults aged 18 to 64 years, to identify the main determinants of direct and indirect costs, and to highlight any gaps in the existing published evidence. MEDLINE and Embase were searched from 2007 to February 7, 2020, for studies reporting primary influenza‐related cost data (direct or indirect) or absenteeism data. Of the 2613 publications screened, 51 studies were included in this review. Half of them were conducted in the United States, and 71% of them described patients with influenza‐like illness rather than laboratory‐confirmed disease. Only 12 studies reported cost data specifically for at‐risk populations. Extracted data highlighted that within the 18‐ to 64‐year‐old group, up to 88% of the economic burden of influenza was attributable to indirect costs, and up to 75% of overall direct costs were attributable to hospitalizations. Furthermore, within the 18‐ to 64‐year‐old group, influenza‐related costs increased with age and underlying medical conditions. The reported cost of influenza‐related hospitalizations was found to be up to 2.5 times higher among at‐risk populations compared with not‐at‐risk populations. This review documents the considerable economic impact of influenza among adults aged 18 to 64. In this age group, most of the influenza costs are indirect, which are generally not recognized by decision makers. Future studies should focus on at‐risk subgroups, lab‐confirmed cases, and European countries. The World Health Organization estimates that worldwide each year, influenza epidemics result in up to 5 million severe cases of disease and up to 650,000 respiratory deaths across all ages.Although influenza can affect any person and age group, certain populations are at greater risk of exposure to infection or of developing severe disease. Population groups at higher risk of developing severe outcomes are pregnant women, young children, adults aged 65 years and older, and those with underlying conditions.Influenza imposes a large economic burden to healthcare systems and to society. Notably, for the adult American population, a study published before the COVID‐19 pandemic has demonstrated that influenza accounted for 65% of the total economic burden caused by vaccine‐preventable diseases.While the economic burden of influenza infection among adults aged 65 and older has been well described,2Embase.com) was conducted on February 7, 2020.  statement.Publications were screened against the inclusion and exclusion criteria shown in Table Relevant data were fully extracted by one investigator and validated by a second independent investigator. Data elements extracted covered study characteristics, including method used to identify influenza cases, patient characteristics such as age group and presence of comorbidities, and cost and absenteeism data. If studies focused on cases who reported positive results of a laboratory test for influenza, they were categorized as lab‐confirmed influenza (LCI); if studies relied on the use of International Classification of Diseases (ICD)‐9/10 codes, presence of specified symptoms, READ codes, or patient surveys to identify influenza cases, they were classified as influenza‐like illness (ILI). The extracted cost and absenteeism data included total costs, direct costs, indirect costs, and proportion of patients missing work due to influenza and duration of absenteeism. When reported, the extracted direct costs items were hospitalization costs, emergency department (ED) costs, general practitioner (GP) costs, pharmacy costs, and overall direct costs; the indirect cost items extracted were costs of absenteeism, costs associated with premature death, and overall direct costs. Total costs referred to both direct and indirect costs combined, and overall direct and indirect costs referred to all subtypes of either direct or indirect costs, respectively, combined. Outcomes stratified by age group and risk profile were captured even when age group did not match those defined a priori  and regardless of medical conditions implied.3This SLR identified 51 studies reporting direct and indirect costs or workdays lost related to influenza in patients aged 18 to 64. See Figure Identified studies included 12 reporting on LCI and 36 reporting on ILI. The other three studies examined the link between absenteeism and influenza season. In these latter studies, influenza was considered as an exposure factor such as a calendar period defined by epidemiological indicators.Few studies reported data for at‐risk populations: 11 ILI studies and only one LCI study. Various terms were used in the literature to describe at‐risk populations without a clear or consistent definition. For consistency, this publication uses the term “at‐risk” to refer to studies that used the terms “at‐risk” or “high risk” or identified one of the at‐risk groups of interest as defined in the review methods , overall direct costs (22 studies), and workdays lost (20 studies). Costs of workplace absenteeism were reported in 10 studies, total costs in five studies, and overall indirect costs in two studies. All extracted cost data are available in the Finally, five studies looked at influenza costs specifically among HCWs and primarily focused on influenza‐related absenteeism.3.13.1.1A total of 22 studies reported overall direct costs attributable to influenza, of which eight studies investigated costs in LCI and only two provided data for an at‐risk population among those looking at ILI. Thirteen studies reported individual costs (cost per influenza case), and 10 studies estimated aggregated costs at the population level across the specified age group.Reporting of individual costs was heterogenous and included the following denominators: influenza case, influenza case medically attended, case hospitalized or presented to an ED, or hospitalized case. Moreover, some studies did not report all the direct costs items, and others did not specify how the costs were attributed to their categories.On average, in Europe, overall direct costs ranged from €56 in Italy per self‐reported influenza caseAmong patients aged 18 to 64 years, mean overall direct costs per influenza patient increased with age,Concordantly with individual results, aggregated cost data showed that overall direct cost attributable to influenza increases with age and was significantly higher in the elderly compared to adults less than 65 years old.3.1.2Costs attributable to hospitalizations were a main driver of overall direct costs. US and Australian studies have shown that hospitalization costs accounted for 73 to 75% of overall direct costs of influenza in adult populations aged 15 or 18 to 64 years.Twenty‐five studies reported hospitalization costs: 23 reported individual costs, and six reported aggregated costs. Only three studies reported hospitalization cost data for LCI cases across three different countries.Cost per hospitalization was lower in Europe than in the United States. European cost per hospitalization ranged from €2033 among patients of all ages in Germany to €6827 among 50‐ to 64‐year‐olds in Belgium.Across outcome definitions, individual hospitalization costs in the general population increased with age among patients under 65 years. Indeed, five studies reported higher hospitalization costs for those aged 50 to 64 (or 45 to 59) compared with those aged 18 to 49 (or 18 to 45).Hospitalization costs were higher among complicated cases and at‐risk populations. Indeed, hospitalization costs were 1.4 to 1.5 and 1.1 to 2.0 times higher in complicated influenza cases than in uncomplicated cases among those 18 to 49 years old and 50 to 64 years old, respectively.Aggregated hospitalization costs by age were reported in two studies. These 2 studies reported higher hospitalization costs among those aged 50 to 64 compared with those aged 15 or 18 to 49.3.23.2.1Studies were categorized as overall indirect costs if they included combined data of multiple components of indirect costs. However, the specific indirect costs included in the evaluation of overall indirect costs varied between studies, making comparisons difficult.Two studies reported overall indirect costs, both from the United States. Both studies reported aggregate costs only. Costs of absenteeism and lost productivity due to death were included in both studies,Indirect costs were consistently higher for patients aged 50 to 64 than for patients aged 18 to 49.3.2.2As 18‐ to 64‐year‐olds comprise most of the working population, the burden of absenteeism due to influenza and its associated costs are of particular interest in this age group. Ten studies reported costs of influenza‐related absenteeism in 18‐ to 64‐year‐olds. Only one study provided data for LCI, one for an at‐risk population, and two for HCWs. Among these studies, nine reported individual costs, and four estimated aggregated costs.Since some studies explored the average cost of absenteeism only among influenza patients using sick leave while others considered all influenza patients without specifying whether they had sick leave, individual absenteeism costs were classified into cost per case with sick leave and cost per case regardless of sick leave. Cost per influenza patient with sick leave ranged from €176 to €577 in Germany.Overall, in the adult population, absenteeism costs per influenza case increased with age in the 18‐ to 64‐year‐old age group but decreased among those aged ≥65.For population aggregated costs, an Italian study showed that absenteeism costs are highest for those aged 40 to 59 years followed closely by those aged 50 to 59 years. As with individual costs, the lowest cost for absenteeism was seen for older individuals (aged ≥60).3.2.3Costs of lost working time are are directly driven by the amount of time lost due to absenteeism (time fully out of work) and presenteeism (time at work but not fully productive).Twenty studies reported data for absenteeism associated with influenza among 18‐ to 64‐year‐olds. Of these, only two studies provided data for a population at‐risk, and four studies focused on HCWs. In addition, only two studies reported data for LCI cases. All studies reported individual data of absenteeism and one additionally reported aggregated data.Identified studies generally reported two types of outcome: either the proportion of patients taking sick leave due to an influenza episode (7 studies) or the duration of absence from work (14 studies). Among studies reporting duration of absence, data were classified as average duration of workplace absence per influenza case with sick leave or average duration of workplace absence per influenza case regardless of taking sick leave .For the proportion of influenza patients taking sick leave, most of the studies reported an average of 30% to 36%. For instance, in Germany, two studies estimated that 33.4% to 35.6% of influenza patients took sick leave.The proportion of patients taking sick leave increased with age within the 18‐ to 64‐year‐old age group and for at‐risk populations compared with a general population in a US study.The reported average duration of workplace absence per influenza patient with sick leave ranged from 6.0 to 8.2 days in European studiesAcross all populations of influenza patients considered, the average duration of absenteeism increased with age within the 18‐ to 64‐year‐old age group.Among the studies that focused on HCWs, three provided average lengths of influenza‐related sick leave. In Italy, where influenza is responsible for 11.9% of all‐cause work absences in HCWs, they had an average of 4.6 days of absence when they had influenza.Only one study incorporated presenteeism as an outcome. While the length of workplace absence was generally lower in the United States compared with European countries, this study suggested that lost productivity is substantial. At 7 to 17 working days post‐disease onset, adults aged ≥18 years reported 67% of their working hours were lost due to absenteeism or presenteeism.3.3Total costs represent the complete economic burden of influenza. Total costs incorporate both direct and indirect costs, such as those due to absence from work or to premature death. However, studies were not always clear about the exact components included in the assessment of total costs.Five studies reported the total costs of influenza. None of these studies reported data for at‐risk populations or HCWs and only one reported data for patients with LCI.Three studies reported total costs on an individual basis (per case); these costs varied considerably between studies. The lowest costs were seen in France at €126.10 per case.Aggregated total costs increased with patient age within the 18 to 64 age group.4The economic burden of seasonal influenza is substantial among adults. Despite methodological heterogeneity observed across studies identified by this SLR, indirect costs have been reported to be the primary driver of total costs of influenza in adults, at both individual and population levels. Indeed, whatever the scope of indirect costs considered, they accounted for up to 82% of the total cost per influenza caseWithin the target age range of this review, older patients  generally had higher influenza‐associated costs compared with younger adults . Additionally, patients with one or more risk factors for influenza complications had higher costs than those patients not at risk. Healthcare resource utilization data were opportunistically extracted alongside costs and showed similar trends with age groups and the presence of risk factors. These data should reflect the fact that severe forms of influenza are more frequent with age and the presence of comorbidities.While this review focused on adults aged 18 to 64 years, many of the included publications also reported data for elderly (≥65 years) patients, which were also opportunistically extracted. Across studies that provided age‐stratified data, the average total cost per case was higher in adults aged <65 than in the elderly. This could be related to the major role played by indirect costs, which are more substantial in those aged 18 to 64 partly due to higher employment rates. Conversely, studies have shown that the overall direct costs per case were higher in the elderly than in younger adults. This may be explained by the more severe impact influenza can have generally on these patients, which would result in increased healthcare use and therefore higher costs. Nevertheless, this trend was not observed when considering only hospitalization costs. Most of the studies reported higher hospitalization costs per case in patients aged 50 to 64 than in the elderly. One reason for this could be a kind of selection bias with the elderly more easily hospitalized due to the greater risk for complications in this age group. Hospitalized young adults may then have more severe disease than the elderly and require more medical intervention. It would be interesting to confirm this trend and hypothesis in future studies. However, when looking at hospitalization costs at population level, they were higher in elderly patients than in younger adults because of the increase of hospitalization incidence with age.The ability to draw robust conclusions regarding the economic burden of influenza in adults is constrained by many limitations, first those inherent to systematic reviews and second those related to the included studies in this review.While studies reporting costs due to influenza in patients aged 18 to 64 were identified systematically, no review can ensure that all available data for an outcome of interest have been identified. Notably, a recent study from 2017 looking at the impact of LCI on absence from work in England was not captured.Regarding limitations related to the studies included, first, half of the included studies were conducted in the United States. As the US healthcare system functions very differently from European systems in relation to costs, results of these studies should not be generalized to other high‐income countries. This results in quite poor evidence on the economic burden of influenza in adults aged ≤65 outside the United States.Second, only 11 studies reporting on patients with LCI were identified in this review. The others, which were categorized as ILI, relied on coding systems or symptoms and may have led to less specific results for influenza infection and may not fully reflect its true economic burden. Nevertheless, as ICD coding practices differ between countries, we classified a study as LCI only if the authors explicitly mentioned that the influenza cases were laboratory confirmed. The others were classified as ILI although in some studies, the authors focused on ICD codes that are theoretically specific to laboratory confirmed influenza. This choice may have excluded three studies from LCI category, as we ignore if ICD codes are appropriately informed.Third, only 12 studies measured the cost of influenza in at‐risk populations, and only one study provided data on at‐risk patients with LCI. No studies on at‐risk patients were available for total costs, overall direct costs, or overall indirect costs. Thus, literature on the economic burden of influenza is poor for the at‐risk population, particularly in Europe. This is an important evidence gap because most European countries mainly recommend influenza vaccination for individuals at risk of developing severe disease. Only five studies looked at HCWs, reporting primarily on absenteeism. This focus can be explained by the central role played by HCWs' sick leaves in health system disruption during the influenza season.It is important to stress that results comparisons were made with caution due to high heterogeneity across studies and differences in definitions of the reported outcomes. For instance, age groups vary across studies: some reported cost data for people aged 16 to 59 years old, while others used the 18‐ to 64‐year‐old age group cutoff. Moreover, when risk groups were analyzed, they differed greatly from one study to another. At‐risk people referred either to people with a specific condition  or to a group of individuals with mixed chronic conditions generally undefined. Nonetheless, these last two limitations did not prevent this review from highlighting some trends in influenza costs.For results reported at the individual level, the estimated value was in some studies an average among all influenza patients; in others, it was an average among patients who consumed this resource, and in others, the denominator was not specified. For instance, it was sometimes not clear if the estimated hospitalization cost was an average among all influenza patients or among hospitalized patients, and if the estimated duration of absenteeism was an average among all influenza patients or among patients with sick leave only.Additionally, even if many studies reported the same composite costs such as overall direct or overall indirect costs, their scope varied from one study to another; some studies defined direct costs as the sum of hospitalizations and GP visits costs, while others added ED visits and pharmacy. Similarly, some studies restricted indirect costs to absenteeism‐related costs, whereas others also estimated costs associated with premature deaths. This required a careful interpretation of the data and in some cases reclassifying the extracted costs. In the same vein, there were difficulties in interpreting some studies which have estimated composite costs such as outpatient or inpatient costs without indicating their definition.This review upholds the complexity of assessing the full economic burden of a disease.5This review identified indirect costs as the main driver of economic burden due to influenza in the 18‐ to 64‐year‐old age group and hospitalizations as the main component of direct costs. Nevertheless, indirect costs are generally not recognized by decision makers, especially in economic evaluations, leading to an underestimation of the economic impact of influenza. Consistently across studies, influenza‐related costs increase with age and the presence of comorbidities within the 18‐ to 64‐year‐old age group.This review highlighted substantial gaps and heterogeneity in the literature, limiting generalizability and interpretation.Due to these gaps, there are multiple opportunities for future research. Areas of focus include economic burden on those at risk of severe outcomes, among patients with lab‐confirmed influenza, and on absenteeism due to influenza. Of note, evidence is missing on the economic burden across all European countries. Future investigations should be designed after reviewing the existing literature to attempt to standardize meaningful outcome and population definitions.Caroline de Courville: Conceptualization; data curation; funding acquisition; investigation; methodology; resources; validation; visualization; writing‐review and editing. Sarah Cadarette: Data curation; investigation; methodology; project administration; resources; validation; visualization; writing‐original draft. Erika Wissinger: Data curation; investigation; methodology; project administration; resources; supervision; validation; visualization; writing‐original draft. Fabián Alvarez: Conceptualization; funding acquisition; methodology; resources; supervision; validation; writing‐review and editing.6https://publons.com/publon/10.1111/irv.12963.The peer review history for this article is available at Data S1. Supporting InformationClick here for additional data file.


Binding functional biomolecules to non-biological materials, such as single-walled carbon nanotubes (SWNTs), is a challenging task with relevance for different applications. However, no one has yet undertaken a comparison of the binding of SWNTs to different recombinant filamentous viruses (phages) bioengineered to contain different binding peptides fused to the virus coat proteins. This is important due to the range of possible binding efficiencies and scenarios that may arise when the protein’s amino acid sequence is modified, since the peptides may alter the virus’s biological properties or they may behave differently when they are in the context of being displayed on the virus coat protein; in addition, non-engineered viruses may non-specifically adsorb to SWNTs. To test these possibilities, we used four recombinant phage templates and the wild type. In the first circumstance, we observed different binding capabilities and biological functional alterations; e.g., some peptides, in the context of viral templates, did not bind to SWNTs, although it was proven that the bare peptide did. The second circumstance was excluded, as the wild-type virus was found to hardly bind to the SWNTs. These results may be relevant to the possible use of the virus as a “SWNT shuttle” in nano-scale self-assembly, particularly since the pIII proteins are free to act as binding-directing agents. Therefore, knowledge of the differences between and efficiencies of SWNT binding templates may help in choosing better binding phages or peptides for possible future applications and industrial mass production. Escherichia coli bacteria (E. coli). Utilization of the M13 template as a programmable method to integrate SWNTs into photovoltaic and electronic devices [Single-walled carbon nanotubes are exciting nanomaterials because of their unique physical and chemical properties. They are widely deployed for different applications in materials science, nanotechnology, sensor technology, and electronics and are also used for several biological and biomedical applications ,6,7,8,9. devices ,34, imag devices ,36,37, a devices ,40,41,42 devices , and . The viruses were bioengineered to display nanotube-binding peptides fused to the major coat protein of the virus (pVIII). Our purpose was to bind the SWNTs along the viral filament; hence, we used pVIII rather than pIII/pIX/pVI/pVII. The investigation included precise controls by comparing the binding efficiencies of different modified viruses to the non-engineered wild-type virus and to a virus-free sample. Briefly, this was done by (i) comparing four selected strong SWNT-binding peptides  ,25,46 fuTo bioengineer the virus’s major coat (pVIII) protein to display nanotube-binding peptides, four different SWNT-binding peptides, previously isolated by other groups from combinatorial phage display pIII-peptide libraries ,24,25,46The wild-type and the four engineered viruses—V4, V19, V23, and V28, displaying P4, P19, P23, and P28, respectively —were suc10 mL−1, 1.2 × 1012 mL−1, 1.5 × 1012 mL−1, and 5 × 1011 mL−1 for V4, V19, V23, and V28, respectively. However, the foreign insert that was intended to be displayed via engineered phage proteins can have a negative effect on protein expression, phage assembly, and infectivity. Titers were recorded as the averages of three different virus purifications: 6 × 10Engineered virus clones with corresponding SWNT-binding peptides were verified and tested. To detect the incorporated engineered pVIII in the virus’s cylindrical structure, ELISA, with a specific anti-recombinant pVIII protein antibody, was used and an anti-M13 virus general antibody ELISA was included as a control. A general antibody is a critical control to verify a virus’s existence in samples. The phages were captured on the surface of the ELISA plate, which was coated with general mouse anti-M13 phage antibodies. The primary detection antibodies were either general rabbit anti-M13 phage antibodies or rabbit anti-recombinant pVIII antibodies. The horseradish peroxidase-conjugated anti-IgG secondary anti-bodies were anti-rabbit antibodies for prevention of cross-reactivity toward mouse coating/capturing general anti-M13 phage antibodies. Based on the relative total protein concentration , two virm/z = 603.7 amu), corresponding to the mass-to-charge ratio of an amino acid fragment due to the native pVIII proteins (m/z = 491.8/737.3 amu) corresponded to the mass-to-charge ratio of the engineered p23–pVIII proteins, indicating that the SWNT-binding peptides were displayed on the pVIII proteins of the bacteriophage mosaic. Similar experiments were undertaken for V19, V4, and V28 (data not shown).At a similar optical signal level, the anti-M13 general antibody (referred to as anti-Fd) was supposed to recognize and bind to both engineered and native non-modified viruses. These ELISA results illustrated that general anti-M13 antibodies efficiently bind to both native and engineered phages A. Similaproteins A. The twBefore preparing SWNT–virus samples, the virus’s thermal and sonication stabilities were assayed. The stability threshold was determined by testing the virus’s biological titer drop . The finBased on all these observations, we prepared SWNT–virus samples  in Tris-buffered saline (TBS buffer). Sono-chemistry protocols were used to disperse the SWNT bundles without using surfactants . The fulSuccessfully bound virus samples were visualized using cryo-transmission electron microscopy (cryo-TEM) to characterize bound SWNTs along the major coat proteins of the virus filament . The TEMFour virus clones displaying P4, P19, P23, and P28 SWNT-binding peptides were produced. The peptides were selected based on their SWNT-binding affinity and their reported reliability. The four designed Fd viruses with SWNT-binding peptides underwent successful assembly and proved to be functional and viable. Virus cultural purification results showed similar relative concentrations for each engineered virus sample  compared to the native non-engineered Fd. The biological titers (concentration was based on virus infection) of V4 and V28 were roughly 5–20-fold lower than the native virus. The differences between the concentrations obtained by Coomassie brilliant blue quantification and the virus biological titer suggest a negative effect on the biological infection of V4 and V28, which can be attributed to a structural modification of the coat proteins. On the other hand, the assembly and secretion of the four engineered viruses seemed to be unaltered. Modified phage genome fragment sequencing proved that each clone genotypically contained the appropriate DNA encoding SWNT-binding peptide sequences. Phenotypic expression, corresponding to the SWNT-binding peptides displayed on the virus filament, was verified through a specific anti-recombinant pVIII (rec pVIII) antibody ELISA and mass spectrometry. The ELISA binding data indicated that the SWNT-binding peptides were displayed, that they contained the correct amino acid sequences, and that they were accessible to the solution molecules. Visual inspection of the sonicated dispersions of the modified virus/SWNTs and the non-modified virus/SWNTs highlighted differences in the dispersion abilities since the color intensity indicated the quantity of dispersed SWNTs. The binding efficiency of the viruses to the SWNTs strongly depended on the peptide used. The quantity of dispersed SWNTs seemed to be higher in the V4 and V28 virus samples than in the native non-modified virus. Cryo-TEM visualization showed bound SWNTs along the major coat proteins of the virus filament. This may be relevant to the possible use of the virus as a “shuttle,” particularly since the pIII, pIV, pXI, and pVII proteins are free to act as binding-directing agents. The different binding capabilities of the different peptides are correlated with each peptide’s physical and chemical properties, derived directly from the peptide’s specific amino acid sequence, as previously mentioned. The engineered M13 virus may pave the way for using aligned and highly organized SWNT–virus samples as anisotropic molecular building blocks for nanoscale devices and circuits. Further studies can expand this system by adding compatible functionalization and selectivity to the rational design section. A significant advantage of using biological M13 system peptides to bind nanotubes is that the process can be controlled by specifying the amino acid sequence at the DNA level. We exploited this advantage in this study to engineer a self-binding function into the peptides, but other capabilities can also be envisioned. Other than pVIII engineering, the virus genome bio-system enables further genome modifications that could be applied in the future to produce other specific modifications in defined regions of the virus filaments; for example, biotinylating on specific amino acids assembled in the virus’s cylindrical structure or displaying semiconductor or metal-binding peptides as linkers in specific positions and orientations, producing an ordered hybrid biostructure. Finally, this work might be a step towards arranging SWNTs into architectures that are useful for electrical circuits and molecular-sensing applications. As such, specific modifications of the pIII region with given functionalities, such as an affinity to a specific semiconductor or metal nanoparticle, solid face, or targeting agent , could allow the virus to serve as a shuttle for connecting SWNTs to these systems.SfiI restriction enzymes were purchased from New England Biolabs (NEB). Oligonucleotides and PCR primers were from Sigma-Aldrich. DH5α Escherichia coli bacteria were obtained from Prof. Jonathan Gershoni  [2, MnCl2, MgCl2, NaCl, HCl, and KCl were purchased from Merck. Acetic acid, PEG 800, glycerol, and Tris were obtained from Sigma-Aldrich. Bacterial media were purchased from Difco. ‘type 88’ virus design: All protocols were as previously described [E. coli overnight culture before the phage DNA was isolated with a JETstar Plasmid Maxiprep kit according to the manufacturer’s instructions. The isolated vector DNA was verified by fragment sequencing, the DNA 1% gel electrophoresis pattern, and restriction site mapping (data not shown). The Fth1 phage vector pVIII cloning site was digested with the SfiI restriction enzyme according to the manufacturer’s instructions. SWNT-binding peptides were encoded at the DNA level according to E. coli codon usage [E. coli-competent cells by heat shock and plated on tetracycline agar plates. Colonies that contained the four phage inserts were propagated to produce the engineered viruses. The four modified viruses  were purified and titered. For the sake of clarification, we named the peptides after their sequences . Determination of viral particle concentration: The virus particle titer was measured by infecting DH5α E. coli bacteria with serial dilutions of the phages, plating and incubating the tetracycline agar plates overnight at 37 °C. On the following day, the titer was calculated by counting the tetracycline-resistant bacterial colonies and multiplying the number by the dilution factor. The relative quantity of physical virus particles was evaluated with the Coomassie brilliant blue protein reagent following the manufacturer’s instructions, an enzyme-linked immunosorbent assay (ELISA), and sample spectrophotometric absorption measurements from 220 nm to 340 nm using a UV-visible spectrophotometer and 1-cm optical-path quartz cuvettes. Virus thermal and sonication stability: Ultrasonication was carried out in a sonicator bath for a predetermined time, with 40 K Hz frequency and 150 watt rated power. The thermal stress test was carried out in a heated bath that contained a digital thermometer with thermostat control. The viral titer was determined with different time intervals in both a sonicator bath and thermal bath. Molecular verification of a viral particle: Engineered DNA fragments of viruses were sequenced for code verification. Biological infectivity and functionality were checked. An anti-recombinant pVIII ELISA for recombinant pVIII detection was used as previously described [Materials. The Fth1 phage vector was kindly provided by Prof. Jonathan Gershoni  . The vir Israel) . DNA pol Israel) . We used Israel) . CaCl2, escribed  unless oon usage ; four DNescribed , and mas


Globally, Hepatitis E virus (HEV) causes over 20 million cases worldwide. HEV is an emerging and endemic pathogen within economically developed countries, chiefly resulting from infections with genotype 3 (G3) HEV. G3 HEV is known to be a zoonotic pathogen, with a broad host range. The primary source of HEV within more economically developed countries is considered to be pigs, and consumption of pork products is a significant risk factor and known transmission route for the virus to humans. However, other foods have also been implicated in the transmission of HEV to humans. This review consolidates the information available regarding transmission of HEV and looks to identify gaps where further research is required to better understand how HEV is transmitted to humans through food.The online version contains supplementary material available at 10.1007/s12560-021-09461-5. Hepeviridae, is considered the most common cause of acute viral hepatitis. There were an estimated 20 million infections worldwide annually in 2005 from genotype 1 (G1) and 2 (G2) HEV combined , of the family HEV was once thought only to be endemic to certain economically developing countries within Asia and Africa, but research over the past decade has highlighted the emergence of HEV within higher income countries. The virus spreads through a faecal-oral route, making it easily transmissible through faecally contaminated water. Indeed, this is thought to be the main transmission route within China, where G1 and genotype 4 (G4) HEV are dominant   samples together, a conservative measure would be to cook pork products for longer than 20 min at temperatures higher than 72 °C.In addition to the potential for HEV to survive some cooking processes, raw pork products are used in some consumables. Raw blood products are commonly used in ready-cooked foods such as processed ham (fibrinogen) and other blood proteins are used as food additives such as emulsifiers. Spray-dried plasma powder (SDPP) is also used in domestic and farm animal foods but this has some heat processing prior to use. SDPP is commonly fed to weaned piglets; however, a previous study reported no transmission of HEV in pigs fed spray-dried plasma products that were positive for HEV RNA  from China, where both antibody seroprevalence and HEV RNA of G4 have been identified in multiple studies. Hu and Ma  were identified in confirmed HEV-positive patients out of 919 from 2015 to 2016 , vegetarians still displayed a relatively high seroprevalence (13.8%) , and there is also potential for other livestock species to be unidentified hosts for the virus. Generally, foodstuffs containing raw meat or shellfish products are more likely to cause a foodborne infection than cooked foods or crops due to no thermal inactivation of the virus through cooking. Cooking in such a way that a minimum internal temperature of 72 °C is reached for at least 20 min is likely to completely inactivate any HEV present; however, this is likely to produce unwanted deterioration of organoleptic qualities in some risky food types, e.g. shellfish.In addition to animal meat, milk from cows, sheep, goats, donkeys and camels has also been found to contain HEV in some countries, but studies investigating the presence of HEV in milk are much more limited. Because of this, the true risk of HEV transmission from animal milk is yet unknown and requires further research. However, if proven to be a prominent transmission route for the virus, a worrying consideration is that high-temperature short-time (HTST) pasteurisation of milk products, which is commonly used in the UK and USA, may be insufficient to reduce infectious HEV within milk, as generally the heat treatment used for HTST pasteurisation is only 72 °C for 15 s. Other pasteurisation methods, such as ultrahigh-temperature pasteurisation, which utilise treatments of around 135 °C for 2–4 s should be more capable of removing viable virus from milk products due to the higher temperature.Though crops can also become contaminated with HEV, it seems that the risk of contracting HEV from them is much less likely, as confirmed outbreaks from crops have not been identified, and the HEV RNA prevalence and copies of viral RNA present are lower for these foods. However, it may be safe to conduct further research into the contamination of irrigation water, and the presence of HEV in crops from other countries to better assess the risk of contracting HEV from crop contamination.It has also been shown that marine mammals can be infected with HEV, which is concerning both from an ecosystem and a seafood point of view. If marine mammals are becoming infected naturally, it could be possible that fish and other seafood also become contaminated or infected. Considering that shellfish in many countries have been found to be contaminated with HEV, this is perhaps something that warrants further investigation.Due to mixed conclusions between and within countries about HEV presence within different hosts or matrices, it appears that there needs to be not only standardised and improved methods for the purpose of HEV detection, but also that further research through larger studies around the world is required to identify the full host range of HEV and the risk of each potential host to transmit the virus to humans (through food or other means). In particular, the suggestion that a HEV-related virus may be causing seroprevalence estimates to be higher than they genuinely are requires investigation.Further studies identifying both the seroprevalence and the presence of HEV through ELISA and RT-PCR techniques, respectively (or similar techniques identifying RNA presence), would be best equipped to identify both the prevalence of the virus within animal populations and the amount of active infections within the populations at that point in time. However, sequencing technologies such as nanopore RNA sequencing within human and animal populations would also be useful to identify similarities between HEV sequences, enabling the identification of infection sources. Some studies investigating the evolution of the virus have already been performed, but are often biased by the large amount of HEV sequences derived from humans Below is the link to the electronic supplementary material.


Kaplan–Meier survival analysis showed a significant increase in LRR-free survival at 5.58 years when CME was performed (Group A: 81%), in contrast to non-CME surgery (Group B: 67.2%). Conclusions: The prediction score placed 76.6% of patients with LRR in the high-risk category, with a strong predictive value. Patients with long vascular stumps and positive nodes could benefit from second surgery to complete the mesocolic excision.Background: Monitoring surgical quality has been shown to reduce locoregional recurrence (LRR). We previously showed that the arterial stump length (ASL) after complete mesocolic excision (CME) is a reproducible quality instrument and correlates with the lymph-node (LN) yield. We hypothesized that generating an LRR prediction score by integrating the ASL would predict the risk of LRR after suboptimal surgery. Methods: 502 patients with curative resections for stage I–III colon cancer were divided in two groups (CME vs. non-CME) and compared in terms of surgical data, ASL-derived parameters, pathological parameters, LRR and LRR-free survival. A prediction score was generated to stratify patients at high risk for LRR. Results: The ASL showed significantly higher values (50.77 mm ± 28.5 mm) with LRR vs. (45.59 mm ± 28.1 mm) without LRR ( The principles of complete mesocolic excision (CME) for colon cancer (CC), as reinvigorated by Hohenberger , generat2 or D3 lymphadenectomy have shown the benefits of a good surgical quality care program in reducing locoregional recurrence (LRR) [CC surgery, however, is still a field of non-standardized colectomies, with proven variations amongst clinicians, hospitals, and countries. Complete mesocolic excision is not yet adopted as a gold standard recommendation to the same extent as total mesorectal excision is for rectal cancer. Some professional and national societies such as the American Japanese, Norwegian and French colon cancer societies recommend CME but with variations regarding the lymphadenectomy level ,5,6,7,8.ce (LRR) ,13,14,15Paralleling Heald’s concept of the mesorectal fascia, CME has emerged as an anatomical plane for an ontogenetic compartment surgical plane, using sharp dissection in the mesocolic avascular interface ,17. Few The literature on patients with LRR after curative resection for CC is scarce, and surgical details, incidence, treatment, or follow-up have not been thoroughly reported to the same extent as systemic oncologic outcomes ,23. The 3 vascular ligation [The optimum level of ligation in CME remains debatable, as several studies advocate that no further benefit can be derived after a central Dligation ,26; otheligation ,29,30,312/high/central/D3), could be a better quality marker and may be included in a score of LRR prediction, alongside the established risk factors [Currently, the only method to evaluate surgical quality is through pathologically derived parameters, such as the number of harvested LNs, the number of positive LNs, and the LN index, all of which are quantitative indicators of surgical quality and represent validated prognostic markers of locoregional and systemic recurrences ,32,33,34 factors ,28.2 ligation standard is frequently not reached, suggesting the presence of residual mesenteric tissue and LNs [Several studies flagged the vascular ligation level as a risk factor for LRR ,10,28,36 and LNs ,38,39. T and LNs  showed tTo this end, a score analysis was employed based on retrospective cohorts of patients with and without LRR after surgical treatment, using classic and modern multivariate analysis risk predictors in association with the quantitative CT measurements of ASL and derived ASL angiometry parameters to mathematically predict the importance of the ligation height on the overall LRR risk. Hypothetically, a patient with multiple negative prognostic factors would benefit from a second surgical intervention to complete the mesocolic excision before LRR occurs.Our purpose was to generate a score for selecting patients at high risk of LRR after CC surgical treatment. Identification of such a subgroup may be used to support an indication for salvage surgical procedures for cases with suboptimal primary surgery with long arterial stumps, aiming to prevent LRR and unfavorable oncological prognosis. The score validation would be verified by applying it to the cohorts of patients with and without LRR after surgical treatment.This study was a retrospective analysis conducted on a prospectively maintained database of patients treated at a tertiary hospital—Regional Oncology Institute (IRO) Iasi, Romania.The study cohort was divided into two groups of patients based on the surgical technique:2 lymphadenectomy);high ligation of the ileocolic artery (ICA) adjacent to the lateral wall of the superior mesenteric vein (commonly referred to as SMV) in right colectomies , at approximately 10 mm from the aorta in left colectomies;3 lymphadenectomy).low ligation of the IMA in segmental colectomies for sigmoid cancer, just below the emergence of the left colic artery (LCA), but with further dissection around the IMA trunk up to its origin from the aorta . Colectomies from this group had been performed in compliance with the CME technique, with adjustments to the high vascular ligation level: Group B comprised patients operated on in other surgical units , who had an oncologic registration in our institutional database in the same period of time. These patients were under oncologic treatment and surveillance in our institution. Operations in this group were non-CME, radical colectomies with curative intent. The study was approved by the Institutional Ethics Committee of the IRO, and patients had given consent for inclusion in the research database.The study inclusion criteria were patients with CC stages I–III, according to the 8th edition of Union for International Cancer Control (commonly known as UICC), without preoperative chemotherapy, who underwent surgery with curative intent, with accessible good quality postoperative contrast-enhanced CT.The exclusion criteria were stage IV CC (UICC 8th edition), palliative colectomies, transverse CC, perforated CC, age under 18 years, low quality CT examination or with large reconstruction interval (>5 mm), unavailable or incomplete pathological results, R1 resections, and pT4b stage.In accordance with ESMO guidelines, all stage III patients and high-risk T3N0 patients positive for microsatellite instability were given adjuvant chemotherapy .The statistical indexes of the entire electronic database of the IRO were correlated with the disease codes for “colon cancer” as allocated by our national diagnosis related groups. Thus, an output of 3600 unique consecutive patients was generated and used as an instrument for systematic identification of all the patients eligible for the study. Hardcopy oncologic registries of the IRO Department of Oncology were used to retrieve essential medical information for patients in Group B. The CT images were accessed from the IRO Patient Archiving and Communication System  of the hospital’s intra-network.2 position of predicted ligation level (D2PLL); theoretical best D3 position of predicted ligation level (D3PLL); D2 improvement potential (D2IP); D3 improvement potential (D3IP)) [All 3600 unique entries were individually analyzed for inclusion and exclusion criteria. Of these, 502 passed all the eligibility criteria  and were (D3IP)) , patholo (D3IP)) ,40,41 (p (D3IP)) , lymphatAlthough LRR still lacks a clear definition , for the® 8165 mg/mL  with an automated infusion pump at a rate of 2.50 mL/s. Arterial and venous phases were obtained with an acquisition delay of 15 s or 50 s using the automated bolus tracker. Data sets were reconstructed with a 1–3 mm section thickness, and the reconstruction interval varied between 1 mm and 3 mm [The technical aspects of the imaging protocol for the patients scanned at the IRO were consistent with previous work published from our workgroup . The radand 3 mm . The remA dedicated software package for radiological examinations was used  with 3D multiplanar reconstructions and maximum intensity projection tools for vascular identification. Arterial length measurements were standardized using the dedicated software instrument, conducted by the primary investigator (CL). Relevant CT sections and reconstructions were classified and saved in accordance with each designated clinic as proof of arterial stump measurement. The CT scans had been originally used for routine oncologic follow-up and were not ordered for the purpose of this study.2PLL, D3PLL, D2IP, D3IP) as follows: 2 ligation, D2PLL  was measured from the IMA origin to below the LCA emergence, explicitly as the norm D2 lymphadenectomy level with conservation of the LCA. The D2IP was defined as the subtraction between actual stump lengths and the D2PLL , median and the values of quartiles Q25 and Q75. Tests were applied to verify the type of distribution (Kolmogorov–Smirnov test) and for the homogeneity of the variances of the analyzed numerical value series (Levene’s test). Depending on the characteristics of the numerical values series, parametric (Student’s t test) or non-parametric  comparison tests were applied. The Pearson chi-square test was applied to test the association of categorical variables. For testing the relation between two numerical variables, the Pearson correlation test was applied, and for qualitative variables of the ordinal type, the Spearman correlation test was applied. LRR predictability based on the analyzed values was evaluated based on the receiver operating characteristic (commonly known as ROC) curve and the area under the ROC curve (AUC) value. A risk score was generated for predicting LRR based on the logistic regression models that included certain explanatory variables. Based on this score, the probability of a patient presenting with LRR could be estimated. To validate the risk score, the internal validation bootstrap method (based on 2000 bootstrap samples) was applied. The reference threshold for the significance level A total of 502 patients out of 3600 were statistically analyzed. Baseline demographic and pathologic characteristics of patients are listed in 2PLL values from each group. The compact and narrow distribution of ASLs from Group A is to be noted in contrast with the wide dispersion of ASL from Group B .The median follow-up interval was 23 months, and LRR arose after 12 months. ASL stratified by colectomy type was significantly smaller in Group A. The mean ASL (± SD) showed significantly higher values, 50.8 mm ± 28.5 mm in the LRR group vs. 45.5 mm ± 28.1 mm in the group without LRR (p < 0.001). There was a strong, statistically significant correlation between the LN number < 12  and the presence of LRR, as 24 out of the 77 cases (31.2%) had LRRs. These patients (subgroup with LNs < 12 with LRR) illustrated a significantly longer ASL, with mean 62.2 mm, and 22 out of 24 cases having left-sided CCs  out of 502 colectomies resulted in an LN count below 12. This accounted for 53 cases (34.4%) from Group B and 24 cases (6.9%) from Group A. A comparison between the two groups revealed that Group B consisted of a statistically higher frequency of cases with less than 12 LNs  for LN values < 12 and an ASL cut-off value of 52.8 mm (p < 0.001) for LN values > 12. This reference threshold is a good risk predictor, as shown by the area under curve: AUC for LN < 12 = 0.67; AUC for LN > 12 = 0.68 (p < 0.001). The predictive value of the proposed ASL reference does not show a significant difference between the specificity and sensitivity of the evaluation method for LRR prediction (p = 0.9650), depending on the adjustment variable  and in the absence of LRR . Similarly, no significant differences were identified between the ASL cut-off predictive value calculated using the LRR adjustment variable (p = 0.991)  with the calculated ASL cut-off value being generated by applying the adjustment after LRR. Thus, the cut-off value of ASL was calculated to assess the risk of LNs < 12 in the presence of LRR (ASL= 0.991) .The predictive value of the parameters for predicting LRR after surgical treatment of CC was evaluated based on the univariate and multivariate logistic regression model . The firTo create a risk score, the rule based on the ratio between the numbers of events per variable (prediction factor) was considered. This requires a minimum of 10–15 events for each predictor entered in the model.To reduce the number of predictors before creating the risk score, the stepwise selection model  was applied in the second stage, in which non-significant predictors had been gradually removed from a model that initially contained all candidate predictors. Subsequently, for establishing the risk score, the internal bootstrap validation was applied. This way, the variables that did not have a significant contribution to the risk score were excluded from the model.All steps corresponding to the model validation were followed (four steps). Before using the risk model, the predictive capacity of the model was evaluated—more precisely, the validation of the model. This involved an assessment of calibration (agreement between observed results and predictions) and discrimination (the model’s ability to discriminate between low- and high-risk patients). Subsequently, the model was internally validated using bootstrapping. Based on the constant model (without predictors), 84.7% of cases could be correctly anticipated from the LRR point of view. At this stage, the contribution of each independent variable to the improvement of the model was evaluated.Only the last step (step 4) was presented in establishing the predictor variables that would be subsequently included in the risk score. Variables not statistically significant were excluded from the model .p < 0.001) of cases, with the difference between the complete model and the model without predictors being small (−2LL = 18.15). Nagelkerke R Square estimated the share of cases for which the evolution could be explained based on the chosen model as 86.2%.In order to be considered with good predictive power, the significance of the proposed model was evaluated. The results indicated that the model was able to correctly evaluate a significant number , confirming that the generated model was appropriate.Based on the results of the Hosmer–Lemeshow test, the model was fit and did not show a significant difference between the real case evolution and the one estimated by it. The model calibration results for the analyzed data (Hosmer–Lemeshow test) indicated that the estimated frequency of LRR was not significantly different from the estimated model .The internal validation highlighted that the model was correct and coefficients’ values remained constant after bootstrapping had been applied. Based on the model defined in this way, the probability of LRR for all patients with CC was estimated .Patient’s risk of LRR is calculated as follows:The variables corresponding to the previous formula are:Intercept = 0.215—the corresponding value in GRP = 0.596  proved the highly predictive value of the created risk score  and the patient LRR itself. This was clearly demonstrated by the fact that, in patients without LRR, the generated risk category based on the prediction score placed 87.76% of patients at low risk. On the other hand, the prediction score placed 76.6% of patients with LRR in the high risk class. The strong, significant correlation . p = 0.02) in Group A (81%) compared to Group B (67.2%) at 67 months after surgery , some may argue that this may impact stump length. However, there are studies that have clearly shown post-colectomy arterial stumps over 2 years after surgery [Considering that the time from surgery to postoperative CT was statistically different between the two groups  and the ASL were the statistically significant variables that constructed the score. CME provides surgical specimens superior in quality, with lower LRR rates and longer LRR-free survival in contrast to conventional unstandardized colectomies. The ASL has been shown to significantly differ between CME and conventional colectomies. The cut-off value of the arterial stump could be informative for the multidisciplinary team, when evaluating the need for re-surgical completion of the mesocolic excision, if integrated in the validated LRR score. If a patient with a long residual vascular stump presents other known risk factors, a second surgery could provide prophylaxis of the recurrence in due time, before it occurs.


The 2015 highly pathogenic avian influenza virus (HPAIV) H5N2 clade 2.3.4.4 outbreak in upper midwestern U.S. poultry operations was not detected in wild birds to any great degree during the outbreak, despite wild waterfowl being implicated in the introduction, reassortment, and movement of the virus into North America from Asia. This outbreak led to the demise of over 50 million domestic birds and occurred mainly during the northward spring migration of adult avian populations.There have been no experimental examinations of the pathogenesis, transmission, and population impacts of this virus in adult wild waterfowl with varying exposure histories—the most relevant age class.Anas platyrhynchos) with HPAIV H5N2 clade 2.3.4.4 and measured viral infection, viral excretion, and transmission to other mallards.We captured, housed, and challenged adult wild mallards .Based on these results, adult mallards are viable hosts of HPAIV H5N2 regardless of prior exposure history and are capable of transporting the virus over short and long distances. These findings have implications for surveillance efforts. The capture and sampling of wild waterfowl in the spring, when most surveillance programs are not operating, are important to consider in the design of future HPAIV surveillance programs. The economic cost of the outbreak and control measures was estimated to be nearly 5 billion dollars.Poecile atricapillus) and a Cooper's hawk (Accipiter cooperii) in Minnesota and a Wisconsin snowy owl (Nyctea scandiaca). These detections all came from passive collection of moribund or dead birds and raise the issue of how efficient and effective surveillance in wild birds was during this agricultural emergency.The roles of wild waterfowl in the transport and transmission of this virus during the outbreak are unknown. No HPAIV was detected in wild waterfowl in the poultry outbreak area, and the only wild birds found with the virus in that region were a black‐capped chickadee (Anas platyrhynchos), as well as 8‐month‐old mallards, with the HPAIV H5N2 clade 2.3.4.4A virus from the outbreak. These were the ages of birds that coincided with the ages of wild waterfowl present during the outbreak—adult birds with histories of previous LPAIV exposure and younger birds hatched the previous summer. We measured infection, virus excretion, and transmission and documented any morbidity and health effects of the HPAIV infection in these birds. We specifically examined whether age and previous exposure to LPAIVs impacted the timing and intensity of viral shedding, as well as the transmissibility to naïve birds. Knowledge of HPAIV ecology in wild waterfowl is critical for developing effective surveillance systems, biosecurity measures, and meaningful risk analyses.To better define how wild waterfowl were involved in the outbreak, we challenged adult wild mallards , both male and female, were captured using rocket nets at Horicon National Wildlife Refuge, Wisconsin  in August 2018 during seasonal banding operations. The birds were transported to the USGS National Wildlife Health Center (NWHC), Madison, Wisconsin and group housed in a BSL‐3 biocontainment animal room. Thirteen hatchling mallards were purchased from a commercial source in September 2018  and brooded and housed in a separate BSL‐3 room from the adult birds to prevent naturally acquired infections being transmitted from the adults to the immunologically naïve young birds. All birds had their primary flight feathers clipped, were provided food and water ad libitum, and allowed free movement within the room with access to tubs of fresh water for bathing and swimming. All husbandry and experimental procedures were performed according to methods approved by the NWHC Institutional Animal Care and Use Committee. Birds were housed in BSL‐3 for ~8 months until the commencement of the study in April 2019. Prior to start of the study, the birds were moved into high efficiency particulate air (HEPA)‐filtered isolator cages (two birds/cage) with a mixture of seropositive adults, seronegative adults, and young birds  according to the manufacturer's instructions. This assay detects antibodies to influenza A virus (IAV) nucleoprotein (NP).Hemagglutination inhibition (HI) assays were performed on a panel of reference viruses representing IAV HA subtypes frequently identified in wild waterfowl.2.3The HPAIV used to inoculate the birds, A/Turkey/MN/11668‐1/2015 (H5N2) clade 2.3.4.4A, was provided by St. Jude Children's Research Hospital. This is the index virus from the poultry outbreak in the Midwest United States and was passaged twice in embryonated chicken eggs.2.45 50% egg infectious doses (EID50) of virus in 1 ml of BHI using a 1‐ml syringe tipped with a metal canula. The birds in cage #1, one adult and one young bird, were mock inoculated using a corresponding volume of BHI. The experimental design is outlined in Table The virus inoculum was prepared by diluting the stock virus isolate in brain heart infusion (BHI). The inoculum virus titer was confirmed in embryonated chicken eggs according to the method of Reed and Muench.2.5Ct values of duck swabs were compared with those from a standard curve of known viral concentrations to calculate the amounts of virus excreted by infected ducks and were reported as EID50 RNA equivalents/ml.50 RNA equivalents/ml.Viral RNA was extracted from cloacal and oropharyngeal swabs using the MagMAXTM‐96 AI/ND Viral RNA Isolation Kit  following the manufacturer's procedures. Real‐time reverse transcription‐polymerase chain reaction (RT‐PCR) was performed using the published procedure of Spackman et al.2.650 equivalents) were fit to a nonlinear function that has been demonstrated to capture the shape of viral infection dynamics in AIV challenges,Vp was the maximum EID50 excretion at the infection peak for mallards that were seropositive for IAV exposure on the inoculation day with coefficients βv,1 − 2 estimated for effect sizes of seronegative adults  and subadults (β2); tp was the estimate of the time (days postinfection) of the maximum EID50, and βtp,1−2 were the estimated effect sizes of adult and subadult maximum EID50; g was the exponential growth rate of viral shedding, d was the exponential rate of viral shedding decline,  were the estimates of decline effect sizes of adults and subadults, and t was the time (DPI) of the observed EID50 response. We modeled the EID50 response as a lognormally distributed response variable with hierarchical components to incorporate individual variation using Bayesian implementation and Gibbs sampling to estimate the mean values for Vp, tp, and d, as well as coefficients for effects of seronegative adults  and 8‐month‐old birds . We did not estimate the exponential growth rate parameter, g, because it was nonidentifiable given the sampling frequency. Rather, we included this as an informative closed‐form prior that was bounded by biologically relevant values.We assessed the transmissibility of HPAIV H5N2 clade 2.3.4.4A by comparing the proportion of noninoculated cage mates with detectable viral RNA from oral swabs before 14 DPI between ages and serostatus. We used a nonlinear hierarchical model to estimate the viral shedding dynamics of the inoculated birds. This analytical method allowed us to estimate key mechanistic parameters that control transmission through viral shedding intensity and timing. The response data  that detects antibodies to the viral NP. This assay is extensively used to measure the serological status of wild ducks.To characterize the virus exposure histories of the seropositive birds, we performed HI analyses on the adult mallard sera using an array of virus subtypes common in wild waterfowl, as well as the H5N8 and H5N2 HPAI clade 2.3.4.4A viruses from 2014/2015. None of the sera inhibited hemagglutination from any of the viruses utilized except the sera from duck Y290 reacted weakly (1:10 dilution) to the H4 isolate, and duck Y271 also reacted at 1:10 to the LPAIV H5N2 isolate. None of the sera contained preexisting antibodies to the HPAIV tested.3.250 and 95% credible interval [CI]; Vp = 8.60 ), effect size in adult mallards with no prior exposure , and effect size in 8 month‐old‐mallards . Time to maximum viral shedding in adult mallards with serologic exposure, tp = 1.9 days , effect size in adult mallards with no serological exposure , and effect size in 8‐month‐old mallards . All noninoculated birds cohoused with an inoculated bird became infected by DPI 2 or 4, with viral detection via oral excretion in 19/19 and detection via cloacal shedding in 15/19 , effd = 0.5 ,βd,1 =  − 0.13 ,βd,2 =  − 0.03 ). Interestingly, eight birds, some inoculated and some transmission subjects, remained infected, based on virus shedding, for the entire 14 days of the study , that was euthanized on DPI 12 for overly aggressive behavior towards its cagemate. None of the infected birds, either by inoculation or transmission, or the control birds showed any overt clinical signs of disease over the course of this study. Most of the ducks, including the control birds, showed moderate loss of weight  and serological evidence from several American robins (Turdus migratorius) captured and sampled at a poultry facility during an active outbreak.Branta canadensis) occurred outside of the outbreak region.Given the massive, widespread outbreak in poultry, why did not the large population of wild ducks in the region become infected with the HPAIV to the point that surveillance systems could detect it? In contrast to widespread detection of HPAIV in hunter killed waterfowl in the Pacific flyway, none of the limited active surveillance conducted during the poultry outbreak found evidence of HPAIV H5N2 clade 2.3.4.4A in any wild duck.Wild waterfowl were clearly instrumental in the introduction, reassortment, and dissemination of HPAIV H5 viruses into NA in 2014 and 2015. Even though the HPAIV H5N2 clade 2.3.4.4A virus was isolated from poultry, our findings show it readily infects all ages of mallards and underscores the potential that the virus could still circulate in wild duck populations undetected by the limited surveillance efforts. Since the outbreak there has been only one detection of HPAIV H5N2 clade 2.3.4.4A in wild waterfowl, from a single mallard sampled in Alaska in the summer of 2016.Daniel A. Grear: Data curation; formal analysis; methodology. Scott Krauss: Conceptualization; investigation; methodology. Patrick Seiler: Data curation; formal analysis; investigation; methodology. Robert J. Dusek: Investigation; methodology. Sean W. Nashold: Data curation; formal analysis; investigation; methodology. Robert G. Webster: Conceptualization; investigation; methodology.None of the authors have any financial interests or conflicts of interest. Use of product, trade, or firm names is for descriptive purposes only and does not imply endorsement by the U. S. government.Table S1. Avian influenza virus isolates used in hemagglutination inhibition assays.Click here for additional data file.Table S2. Body weights (grams) of highly pathogenic avian influenza virus H5N2 clade 2.3.4.4A challenged mallardsClick here for additional data file.


PHKG2 ) definitively diagnosed using the GSD gene panel. She presented with hypoglycemia, hepatomegaly, and short stature and died of cirrhosis and recurrent multiple hepatocellular adenoma at the age of 69 years and 11 months.Glycogen storage disease type IX (GSD IX), the most common form of GSD, is caused by a defect in phosphorylase kinase (PhK). We describe the case of a female patient with GSD IXc harboring a homozygous mutation in  PhK (EC 2.7.1.38) is a serine/threonine-specific complex protein kinase consisting of four subunits: alpha (α), beta (β), gamma (γ), and delta (δ)2. PhK activates glycogen phosphorylase (EC 2.4.1.1), which releases glucose-1-phosphate from glycogen3. Patients with GSD IX have elevated transaminases and hepatomegaly, growth retardation, hypertriglyceridemia, and hypercholesterolemia. However, compared to that in patients with other types of liver GSDs, clinical manifestation in GSD IX patients can be mild, and patients may become asymptomatic as they age5. Mutations in PHKA1, PHKA2, or PHKB and PHKG2 cause GSD IX. PHKG2 encodes the hepatic isoform of the γ unit of PhK. Mutation in PHKG2 causes GSD IXc (MIM: 613027), a rare form that manifests as hepatomegaly, hypotonia, and growth retardation in childhood. Although these symptoms improve with age, some patients develop hepatic fibrosis, cirrhosis, and liver dysfunction6.Glycogen storage disease type IX (GSD IX) is one of the most common forms of GSD caused by a defect in phosphorylase kinase (PhK). This disease accounts for 25% of all GSD cases, with an estimated frequency of 1 in 100,000 individualsA female patient was definitively diagnosed with GSD IXc at the age of 68 years using the GSD gene panel. She was diagnosed with hepatic GSD in childhood but self-discontinued clinical examination and treatment; later, she developed liver cirrhosis and hepatocellular carcinoma (HCC). Herein we present her clinical course and discuss the mechanism and treatment of HCC in GSD IXc based on her clinical course.A 67-year-old female patient with suspected GSD was introduced to our institution to receive a definitive diagnosis while receiving conservative care therapy for liver cirrhosis and multiple HCC. She was the first child of healthy consanguineous parents. Her height was 141.9 cm , and her weight was 54.7 kg. She presented with anasarca and ascites due to cirrhosis and HCC. She had no drinking habit and no history of hepatitis B or C infection. She also had no history of blood transfusion before receiving hepatectomy at the age of 56 years. Her intelligence was not impaired, and she could write advanced sentences. Hepatomegaly was first detected in this patient at 7 years; however, the diagnosis was not completed. At 12 years, she was diagnosed with GSD (type: unknown) at our institution, but she self-discontinued regular follow-up. At 30 years of age, she visited the Department of Internal Medicine because of frequent upper abdominal pain and fasting hypoglycemia symptoms, such as irritation and wooziness. In addition, she developed multiple adenomas and cirrhosis of the liver and received regular follow-up and medicine, including a gastrointestinal drug every month  mutation in Written informed consent was obtained from the patient’s parents. This study was approved by the Institutional Ethics Committee of the Faculty of Life Science, Kumamoto University.PHKG2. We have summarized the case report of GSD IXc in Table We present a female patient with GSD IXc who developed liver cirrhosis and multiple HCC. She underwent aggressive surgical and medical treatment until the age of 68 years. However, she did not modify her diet, including consuming uncooked cornstarch for GSD, owing to her specific characteristics, including being stubborn, obsessive, and unwilling to accept others’ opinions. She was not aware of the need to follow a diet suitable for preventing hypoglycemia. To our knowledge, this is the first report of a patient with GSD IXc developing multiple HCC and receiving aggressive surgical and medical treatment. She carried a novel mutation in 7. Hepatomegaly, fasting hypoglycemia, fasting ketosis, hypertriglyceridemia, hypercholesterolemia, growth delay, developmental delay, and elevated transaminase were present in 100% (30/30), 94.7% (18/19), 100% (6/6), 94.4% (17/18), 45.4% (5/11), 70.8% (17/24), 50% (10/20), and 100% (22/22) of patients with GSD IXc, respectively. Eighty percent (24/30) of patients underwent a liver biopsy. According to pathology reports, 95.8% of patients (23/24) presented with either fibrosis  or cirrhosis. Three patients developed a hepatic adenoma. Only one patient developed HCC at the age of 27 years; this patient is awaiting liver transplantation.The clinical outcome in 30 patients with GSD IXc was collected in an earlier study9. Poor metabolic control is a risk factor for the development of long-term complications such as hepatocellular adenoma in hepatic GSD13. Moreover, hepatocellular adenoma may be regressed in a well-controlled metabolic state with strict dietary therapy. Nevertheless, the effectiveness of strict diet therapy is controversial because there are few adult patients with GSD IXc who receive long-term strict diet therapy.There is no consensus on effective treatment for GSD IXc. Nasogastric tube feeding, uncooked cornstarch (0.3–2.0 g/kg body weight (BW)/day), and a high-protein diet (3.0–4.0 g/kg BW/day) are common treatments for GSD IXcWe believe that this patient should have received a liver transplant when she was diagnosed with HCC. We had reservations in treating her HCC, which developed at the age of 58 years, particularly with regard to choosing between aggressive invasive treatment, including hepatectomy and TACE, and conservative treatment because HCC is known to recur. Overall, it is important to control the radical metabolic state in metabolic disease.14. Liver fibrosis and hepatocellular carcinoma occur in patients with GSD VI16 caused by a defect in glycogen phosphorylase. GSD IXc with pathogenic variants in PHKG2 is associated with more severe clinical and biochemical abnormalities, including increased risk for liver fibrosis and cirrhosis18, because γ is the catalytic subunit, whereas α and β are regulatory subunits of PhK. Glycogen is a key energy store for cancer cells19, and glycogen turnover allows cancer cells to adapt and survive under adverse oxygen and nutrient conditions within the tumor microenvironment. Glycogen breakdown supports the pentose phosphate pathway, which generates the nucleotides required for proliferation and DNA repair, and NADPH, which is an important reducing agent for reactive oxygen species scavenging and for the synthesis of nucleotides, amino acids, and lipids19. Therefore, both cirrhosis and glycogen accumulation are important factors in recurrent and multiple HCC. Activated PhK β-subunit expression regulates the occurrence of HCC by inhibiting AKT/protein kinase B and signal transducer and activator of transcription 3 signaling pathway activation, independent of the glycogenolytic pathway20. In hepatic GSD, the formation and proliferation of HCC may be related to a mechanism independent of the glycogenolytic pathway, which should be investigated in the future.Cirrhosis is the most important risk factor for the development of HCC, regardless of etiologyThe specific characteristics of our patient might be a clinical manifestation of GSD IXc. We should have realized this possibility earlier and administered appropriate counseling.In conclusion, we present the case of a patient with GSD IXc who developed liver cirrhosis and multiple HCC. This case shows the long-term clinical course in GSD IXc. Liver cirrhosis and HCC were important complications in this long-term surviving patient with GSD IXc. However, there is no established effective therapy for GSD IXc, and it is not clear to what extent HCC should be aggressively treated with invasive treatment. Knowledge of clinical outcomes in more patients with GSD IXc is essential to design a treatment course for GSD IXc.Supplemental data 1Supplemental data 2