Leptasterias is a genus of brooding sea stars containing several cryptic species complexes. Population genetic methods were used to resolve patterns of fine‐scale population structure in central California Leptasterias species using three loci from nuclear and mitochondrial genomes. Historic samples (collected between 1897 and 1998) were compared to contemporary samples (collected between 2008 and 2014) to delineate changes in species distributions in space and time. Phylogenetic analysis of contemporary samples confirmed the presence of a bay‐localized clade and revealed the presence of an additional bay‐localized and previously undescribed clade of Leptasterias. Analysis of contemporary and historic samples indicates two clades are experiencing a constriction in their southern range limit and suggests a decrease in clade‐specific abundance at sites at which they were once prevalent. Historic sampling revealed a dramatically different distribution of diversity along the California coastline compared to contemporary sampling and illustrates the importance of temporal genetic sampling in phylogeographic studies. These samples were collected prior to significant impacts of Sea Star Wasting Disease (SSWD) and represent an in‐depth analysis of genetic structure over 117 years prior to the SSWD‐associated mass die‐off of Leptasterias.Temporal genetic studies of low‐dispersing organisms are rare. Marine invertebrates lacking a planktonic larval stage are expected to have lower dispersal, low gene flow, and a higher potential for local adaptation than organisms with planktonic dispersal.  Leptasterias is a genus of brooding sea stars with low dispersal and restricted gene flow. Genetic analysis of Leptasterias species along the California coastline revealed high temporal variability and genetic structure over 117 years Photo by Jeyna Perez. GeograpIn comparison with marine organisms with planktonic larvae, marine direct‐developers and brooders tend to have lower vagility, lower levels of gene flow and greater genetic structure among populations, a higher potential for local adaptation, and more frequent speciation and extinction events  clarify the phylogenetic relationship of California Leptasterias lineages, and (b) assess temporal and spatial patterns of population structure. We predict high population structure and high temporal stability in structure over time due to the low‐dispersal potential of Leptasterias.Past studies on the broad‐scale distributions of 22.1Leptasterias individuals were collected from 17 intertidal sites on the Pacific Coast between December 2008 and July 2014 . Whole stars were collected on the Pacific coast ranging from Lonesome Cove, Washington to Diablo Canyon, California  sequences of 2.4Leptasterias based on successful amplification in other echinoderm taxa: i1, i9, i39, i43, and i51. One EPIC locus which offered the highest resolution among sites and clades was chosen and optimized for population genetic analyses. The i51 primer pair amplified a region in the gene group UDP‐N‐acetylglucosaminyl‐transferase  loci . Cycle sequencing reactions were carried out in the reverse direction using the 1/8 reaction BigDyeTerminator v3.1 . Products were sequenced using an ABI 3130 genetic analyzer. Cloning was used to resolve and confirm a subset of alleles for i51 in heterozygous individuals using Vector System II, pGEM‐T (Promega).2.6Leptasterias sequences for phylogenetic analyses  and nucleotide diversity (π1) for each population. DnaSP was used to calculate Tajima's D, Fu and Li's D, and Fu and Li's F. Neutrality statistics were considered significant when p < 0.05 and corrected for multiple comparisons. MEGA v5.2.2 . Arlequin was used to calculate fixation indices FST and ΦST (significant when p < 0.05). ΦST was calculated with the TN93 model of evolution for D‐Loop and COI and HKY was used for i51. Population structure was examined using an Analysis of Molecular Variance (AMOVA) across California populations grouped into three regions to test for previous structure found in Leptasterias populations around San Francisco Bay ; this region included 56 total variable sites: 14 first‐position changes, 4 s‐position changes, and 38 third‐position changes. When ML analyses were performed excluding third‐position changes for COI sequences overall topology was unchanged, though nodal support values increased slightly. Phylogenetic trees built with D‐Loop and COI separately had the same topology regardless of the method used to estimate the tree. Therefore, loci were concatenated for further phylogenetic analyses  L. aequalis D, L. aequalis A, Clade Y, and Clade Z. Genetic distances of clades within the two groupings ranged from 0.9%–2.0% within the first group and 1.3%–2.0% within Grouping B. Genetic distance ranged from 2.4%–2.9% between clades within the two groups. Intra‐clade genetic distances ranged from 0.10%–1.30%, with a mean genetic distance of 0.70%. Leptasterias aequalis K had the highest within‐clade genetic distance (1.30%). Mean inter‐clade genetic distance was higher (1.97%) with a range of 0.9%–2.9%.Genetic distances were calculated for concatenated D‐Loop and COI using the TN93 + G model Table . Two maiL. aequalis A and Clade Z (nESS = 949), TMRCA for Clade Y (nESS = 517) and TMRCA for Clade Z (nESS = 987). The two main groupings of lineages (A and B) were estimated to have diverged between 1.74 and 1.25 Mya.Bayesian reconstruction in BEAST resulted in a tree with overall similar topology to that of Figure L. hexactis through D‐Loop and COI barcoding. Alleles within L. aequalis were not phylogenetically resolved  for contemporary samples revealed significant population structure between most localities  were used to build ML and Bayesian phylogenetic trees . Two dominant haplotypes resolved into Clades Z and Y, respectively, which were historically widespread Figure , in cont44.1Leptasterias genus than analysis using D‐Loop alone  are comparable to differences found in other divergent, brooding asteroid lineages . In comparison, L. aequalis K was the second most abundant clade in contemporary samples. It is possible that L. aequalis K has increased in abundance at sites that are not bay‐proximal, but were once presumably dominated by Clades Z or Y. Low sample sizes of historic collections make this hypothesis difficult to test, though physiological assays could reveal differences in clade tolerances to local conditions.Competition between clades could be another viable hypothesis for the distribution of 4.3Leptasterias clades suggest glacial cycles contributed to reproductive isolation. Phylogenetic analysis and genetic distances indicate the presence of two distinct species complexes. Historic genetic sampling revealed Clades Y and Z as previously widespread and abundant along the California coastline, while contemporary sampling revealed these clades as bay‐localized. Both selection and demographic events can result in low haplotype diversities, negative neutrality statistics, and unimodal mismatch distributions; the maintenance of divergence between Leptasterias clades might be due to both neutral and adaptive processes of divergence.Pleistocene dated divergence times for Leptasterias, largely attributed to low juvenile mortality between generations. Instead, high levels of population structure on a spatial scale  and high genetic variability on a temporal scale (117 years) were observed. Another study also reported high temporal variability for brooding lineages of Pygospio elegans, indicating patterns may vary across taxa and across time periods ; formal analysis (lead); investigation ; methodology ; software (lead); visualization (lead); writing – original draft (lead); writing – review and editing . Cynthia Sarah Cohen: Conceptualization (lead); data curation (supporting); funding acquisition (lead); investigation ; project administration (lead); resources (lead); supervision (lead); writing – review and editing .Supplementary MaterialClick here for additional data file.Supplementary MaterialClick here for additional data file.


We studied the patterns of pre-collapse communities, the small-scale and the large-scale signals of collapses, and the environmental events before the collapses using four paleoecological and one modern data series. We applied and evaluated eight indicators in our analysis: the relative abundance of species, hierarchical cluster analysis, principal component analysis, total abundance, species richness, standard deviation (without a rolling window), first-order autoregression, and the relative abundance of the dominant species. We investigated the signals at the probable collapse triggering unusual environmental events and at the collapse zone boundaries, respectively. We also distinguished between pulse and step environmental events to see what signals the indicators give at these two different types of events. Our results show that first-order autoregression is not a good environmental event indicator, but it can forecast or indicate the collapse zones in climate change. The rest of the indicators are more sensitive to the pulse events than to the step events. Step events during climate change might have an essential role in initiating collapses. These events probably push the communities with low resilience beyond a critical threshold, so it is crucial to detect them. Before collapses, the total abundance and the species richness increase, the relative abundance of the species decreases. The hierarchical cluster analysis and the relative abundance of species together designate the collapse zone boundaries. We suggest that small-scale signals should be involved in analyses because they are often earlier than large-scale signals. The current climate change and the ongoing sixth mass extinction  is a phenomenon of dynamical systems near critical transitions. At critical thresholds or tipping points (bifurcation), the complex dynamical systems shift abruptly from one state to another, called critical transition. Critical transitions or abrupt shifts can be observed in complex systems from medicine  with various statistical indicators. Besides using community-level indicators , we also introduced a new indicator at the species level: the relative abundance of the dominant species (the most abundant species in the community). Dominant species quickly respond to environmental events and are likely to be an essential biological contributor to community collapses. The dominant species has not been studied as a collapse indicator yet.As unusual environmental events are also an interest of this study, we also examined whether the indicators are sensitive to pulse events, step events, collapse zone boundaries, and what signals they give.We introduce/reintroduce some phrases for community collapses in this study in our understanding.Community collapse – The collapse of the dominant species, the rise of a new dominant species, and the complete structural changes in the community indicate community collapse. We initiate using the “community collapse” phrase for community shifts and extinctions based on common features.Pre-collapse community – Pre-collapse communities cover a period starting before the environmental event and ending at the collapse boundary.Collapse community – Collapse communities follow pre-collapse communities, and they occupy the collapse zones where the pre-collapse dominant species are no longer the most abundant species.Dominant species – Dominant species is the most abundant species of a community in this study. Its decline is an important biotic sign of a forthcoming collapse. We use pre-collapse dominant and collapse dominant species phrases in the study.Collapse zone vs. collapse point – We used collapse zones instead of the points of the collapse (shift or extinction) because we did not intend to include collapse zone signals in the evaluation of indicators.Collapse zone – We used the HCA clusters, the PCA, and the relative abundance of the dominant species to detect the collapse communities and the collapse zones (a period of collapse).Small-scale signals – We use this phrase for statistically significant, temporary signals (peaks or troughs). Small-scale signals are values outside the 95% confidence interval.Large-scale signals – Large-scale collapse signals are large-scale trend changes  or slope changes (sudden change of steepness). The 95% confidence band usually shows the large-scale trends.Abbreviations of periods, epochs, and events:KPG = Cretaceous-PaleogenePE = Paleocene-EocenePETM = Paleocene-Eocene Thermal MaximumEM1 = Early Miocene 1EM2 = Early Miocene 2PANGAEA—Data Publisher for Earth & Environmental Science open access data library (https://pangaea.de/) and current paleolimnological data obtained from other authors  Hole 198–1210A  Site 516 , HCA , and PCA  to define the communities and the unusual environmental events. We used multidimensional methods, temporal clustering, and principal component analysis (PCA), for dimension reduction in Past v 2.17 , we used an unweighted pair-group average (UPGMA) algorithm, for which we computed the distance matrix using Euclidean distance. We preferred constrained clustering to join the adjacent rows of time series during the agglomerative clustering. The products of our cluster analysis are dendrograms showing the clustered data points which represent the communities  in the time series. We presume that the dendrograms also represent environmental pulse events as outliers. We also assume that environmental step events might give different signs.We used principal component analysis (PCA) to explore the similarities between the clusters (communities). PCA shows how the communities are related to each other, and they provide information about the environmental events . We did the PCA by eigenvalue decomposition of a data covariance matrix. The convex hulls in the PCA scatterplots represent the communities.The relative abundance of species (%) shows the unusual environmental events as a peak of the environmental indicator species and as a sharp drop of the pre-collapse dominant species at the same time. Identifying the dominant species of clusters/sub-clusters helps to define communities.We used the indicators below to explore the pre-collapse pattern and the signals of the environmental events and the collapse zones.Total abundance refers to the number of individuals in a community.Species richness is the number of species in a community.Standard deviation and first-order autoregression are the indicators of critical slowing down  model on the data with a 20-period rolling window using the earlywarnings R package  effectively detect the warning signs of collapses because the dominant species is probably sensitive to collapse triggering environmental events. It is one of the most influential species in a community see “” sectionimpuTS R package so that we can do further analyses. We identified statistically significant warning signals of the indicators with a uniform method. We calculated the 95% pointwise confidence band for the indicators with stats R package. First, we fitted a polynomial curve to the data by loess R function (smoothing span = 1). We used the predict function for predictions from a loess fit with standard errors. Then, we calculated the upper and the lower boundaries of the confidence band with the following formula: pred$fit ± qt*pred$se, where pred = the prediction from loess fit, fit = the predicted values, df = an estimate of the effective degrees of freedom, and se = an estimated standard error for each predicted value. The fitted curve shows the general trends and the large-scale signs. Significant deviations from the confidence band are short-scale signs.We interpolated the data using ggplot2 and patchwork packages for the visualization of the statistical indicators. We georeferenced the world map of Fig. We applied Excel 2016, R 3.6.2, and ArcMap 10.4 for data visualization. We used R software  and 65.6078–65.49708 Ma (cluster 2), respectively, as well as the bolide event between them 65.70326 Ma. The figure of the “Relative abundance of the benthic foraminiferal species across the K/Pg transition” and the HCA  and the collapse community (79.905–79.855 mbsf) Fig. B. The doDictyococcites spp.  Fig. B. EM1 daStaurosirella pinnata  Fig. . The preWe had two types of collapse triggering environmental events in the data series: sudden, temporary pulse events and step events that are sudden shifts in an environmental parameter, namely, temperature. We identified the environmental events that probably contribute to the collapses using the literature, PCA, HCA, and the relative abundance of species.P. rudita, an environmental indicator, has a high peak of 65.70326 Ma  but as a separate sub-cluster  drops sharply, which is a general sign of environmental events affecting communities dramatically. In PCA, 79.925–79.915 mbsf and 79.955 mbsf are close to each other, suggesting a connection between these time steps  and 169.89 mbsf (community 2), respectively, as well as the glaciation period between 157.45 and 137.21 mbsf (community 3)  and small-scale signals (short-term peaks and troughs) separately.We had two types of collapse triggering environmental events in the data series: sudden, temporary pulse events , and step events that are a sudden stepwise increase temperature . We also assume a step event and/or a community threshold in EM1 and EM2 data series.We applied HCA, PCA, and the relative abundance of species to identify the communities, community boundaries, and environmental events. For the detailed description of their signals, see previous parts. Here one can read their short evaluation.HCA has outliers at the pulse events (except at the second EM2 event) and separate clusters/sub-clusters at the step events Figs. B-5B, 8B.PCA is not always effective in identifying environmental events, and it does not seem to be a good collapse indicator. However, it helps to detect environmental trends. We applied PCA to visualize communities and to reveal their relationships to each other Figs. C-5C, 8C.The dominant species and the environmental indicators are particularly vulnerable to environmental changes. Hence, the relative abundance of species is a helpful indicator in identifying the environmental events. The decline of the dominant species and, at the same time, the increase of a subdominant species/environmental indicator/opportunist species usually refer to some significant environmental changes Figs. -7, 8A. TWe detected a general pattern of the total abundance before collapses in all of the data series. The abundance first increases sharply. Then it starts a segment with a significantly smaller slope lasting approximately until the collapse zone boundary Fig. . The shaS. brevispinosa) is an opportunist , the significant increase of other species counterbalances the decrease of the dominant species. In this segment, the relative abundance of the dominant species is much lower than it was in the previous period. In the PE data series, the decline of the dominant species is delayed.The small-scale signs of the total abundance (both peaks and troughs) Fig.  reflect The total abundance has a uniform pre-collapse pattern with distinct and explicable segments giving general information about the condition of the community before the collapse. The dominant species probably has a vital role in shaping the pattern of the total abundance of the community before the collapse. It gives small-scale and large-scale signs at environmental events. It typically provides sharp, small-scale signs (troughs or peaks) at the pulse events and large-scale signs (steep increase) after the pulse events, while the step events/community thresholds initiate large-scale signs, relatively longer segments with a significantly smaller slope. However, it may not be a good indicator for the collapse zone boundary. At the collapse zone boundary, it gives different and sometimes late signals (upward or downward trend), though it starts a decreasing trend uniformly in the warming data series . The total abundance of the KPG is quite different, strongly fluctuating, and probably does not have a critical-slowing-down segment.The KPG data series includes few data. Because of the interpolation, the total abundance seems to give a signal before the event. However, the signal triggered by the probable impact event is the absolute minimum. The total abundance of the KPG data series is strongly fluctuating, making the analysis more difficult. Despite this fact, we did not smooth the data to preserve the small-scale signs or avoid their displacement. Smoothing can affect even the direction of large-scale signs.Pulse events can initiate a sharper increasing trend after a sudden trend change or an increase of the slope, see PE presumed pulse event, EM2 second pulse event (presumed), EM1, and KPG pulse events Fig. . A smallAfter the step event, the species richness of the PE pre-collapse community continues its general increasing trend, the species richness of the EM 2 data series stagnates at a high level, and that of the Modern data series increases slightly. After the presumed EM1 step event or community threshold, the species richness starts increasing before the collapse.The sudden increase of the species richness is frequent after pulse events. However, step events or community thresholds do not always provoke significant changes, and these changes do not always point in one direction. Small-scale signs do not always indicate the events . Another observation is that the maximum at the end of the increasing trend sometimes locates before the collapse zone boundary, sometimes right at the boundary. In EM1 and KPG data series, species richness starts decreasing before the collapse zone boundary. Species richness may not be a good indicator for the approaching collapse zone because of the diversity of the signals. However, applying it all together with the abundance, they can give helpful information about the general condition of the pre-collapse community.The standard deviation does not have a uniform pattern before the collapses. It has a decreasing trend before PE and Modern collapses (warming events), while it increases in the case of EM2 (warming), EM1 (cooling), and KPG (impact event) communities before the collapse zone boundary. Near the events, the change points and the slope change of the standard deviation provide small-scale signs (peaks and troughs).It usually has small-scale signs at the environmental events (peaks and troughs). Since this statistical indicator does not have any consistent signs, we do not consider it reliable.We applied blank cells where we had no data, and we did not apply a rolling window. Authors usually use standard deviation with a rolling window in articles on critical slowing down , but then it speeds up approaching the collapse zone boundary. The KPG bolide event causes the fall of the dominant species right immediately. At the collapse zone boundary, it does not change a trend.The dominant species are sensitive to major environmental events. The relative abundance of the dominant species has a decreasing trend before all the analyzed collapses result from some significant environmental event. Long-term trend changes or the changes of the slope and then the final decline follow these events. At the trend changes and the changes of the slope, we can see peaks as small-scale signs. Troughs as a small-scale sign are typical at the pulse events. It does not give a signal at the collapse zone boundary.S. brevispinosa, is probably an opportunist species capable of adapting to changing environments  They often give large-scale signs, but not in every case. The species richness gives a large-scale sign (increase) and sometimes a small-scale sign at the pulse events. The abundance and the species richness often start a sharp increase  at pulse events. The standard deviation gives a small-scale sign (peaks) at the pulse events, but its large-scale signs are inconsistent (decrease or increase). The HCA has an outlier at the pulse events except at the second presumed EM2 pulse event. PCA not always has an outlier at the pulse events.The abundance, the relative abundance of species, and the relative abundance of dominant species give small-scale signs at step events/community thresholds before the collapses. The relative abundance of the dominant species gives both small-scale signs (peaks) and large-scale signs (decreasing trend) at the step events/community thresholds. The relative abundance of the species is also sensitive to step events. However, to interpret the results, one needs to have background information about the dominant species and the environmental indicators. The abundance has a trend change or the change of the slope at step events where the slope of the trend line decreases dramatically. (The modern data series is too short to see exactly where the segment with a gentle slope starts.) The HCA mainly shows step events as separate sub-clusters.Fewer indicators give consistent, reliable signs at the indicators of the collapse zone. Applying the HCA, the PCA, and the relative abundance of species together effectively identify collapse zone boundaries. AR1 is a good collapse zone indicator in climate change data series . In EM1 and Modern data series, it gives an earlier signal (an increasing trend) than HCA, PCA, and the relative abundance of species together. However, during the KPG bolide event, it fluctuates before the collapse and drops sharply at the collapse zone boundary. Standard deviation without a moving window is not a good collapse indicator. Probably, using a moving window can enhance its performance.Some indicators sensitive to environmental events  are not reliable Unusual environmental events are important causes of community collapses  might precede the collapses triggered by climate change where the community gets beyond a critical threshold (biotic cause of the collapse). It might cause the long-term decline of the dominant species and the rise of other species. These processes develop the distinctive pattern of some indicators . If our hypothesis is confirmed, we should focus on detecting pre-collapse step events in the data series because they give earlier signals than the collapse zones.Based on the analyzed data series, we assume that a During our analysis, we distinguished between small-scale signals (peaks and troughs) and large-scale signals . Small-scale signs (maximum-minimum points) can precede large-scale signs. Hence, they can indicate the forthcoming trend changes. When several indicators simultaneously give a significant small-scale sign, they refer to important events . The frequently used critical slowing down indicators do not focus on small-scale signs. We propose that it might be helpful to include small-scale signals in collapse-related studies as they often precede large-scale signals.We believe it is essential to forecast the collapse zones and recognize the antecedent collapse-triggering, unusual environmental events. We suggest that the authors apply several statistical indicators to reveal pre-collapse community patterns and signals since some indicators are sensitive to pulse events, others to step events, and some indicators detect the best collapse zones. Another reason for using several indicators is that it is easier to track less obvious yet significant environmental events striking communities with decreased resilience.A future task is to test more statistical indicators to see whether they are sensitive to pulse events, step events, or collapse zones. For example, constancy, dominance, Shannon-H, diversity indices, or indicators combined with AR1 might reveal some new aspects of pre-collapse communities.


Titanium alloy has become a promising candidate material for oil country tubular goods (OCTGs) in harsh service environments owing to its high specific strength, low density, low elastic modulus, excellent toughness, excellent anti-fatigue and corrosion resistance. However, because the high-quality natural gas resources in China are mainly concentrated deep underground, titanium alloy tubing and casing will bear great external pressure loads underground, so the collapse strength of titanium alloy tubing and casing is very important for the safety of the string in the well. In this paper, a new collapse strength calculation model, the strength collapse criterion model (SCM), was proposed for titanium alloy tubing and casing. 35 different specifications of titanium alloy tubing and casing were selected for the full-scale collapse tests to verify the reliability of the established SCM model. Furthermore, the effect of different key parameters  on collapse strength of titanium alloy pipes were investigated systematically and compared with the same specifications of steel pipes. The strength collapse criterion model and analysis results can provide a technical reference for the design and use of titanium alloy OCTGs in the petroleum and natural gas industries. As the main pipe string channel and protective shield for deep oil and gas development, the tubing and casing not only bear the extremely combined load of the high-temperature and high-pressure in the well, but also bear the corrosion effects of hydrogen sulfide, carbon dioxide, a high concentration of chloride ion and even elemental sulfur in service conditions4. Once a failure accident occurs, it will not only cause the failure of the deep energy exploration and bring considerable economic loss, but also pose a threat to safety and environmental damage. Therefore, OCTGs are extremely important to the oil and gas industry. Titanium alloy materials have become a hot research direction for oil country tubular goods (OCTGs) and offshore components in harsh service environments owing to their high specific strength, low density, low elastic modulus, excellent toughness, and excellent fatigue and corrosion resistance6.With the development of unconventional oil and gas resources in deep and ultra-deep well of China7. The United States, Japan and other countries had developed commercial products of titanium alloy tubular goods, such as tubing, casing, coiled tubing, drill pipe, drilling riser and catenary riser11. Schutz and Jackie verified the feasibility of using titanium alloy materials in high-temperature, high-pressure and high-corrosion environments through experimental methods since the 1990s, RMI Titanium Company developed titanium alloy tubing, casing, marine risers and other products with strength exceeding 1000 MPa, and these products have been successfully applied in multiple oil and gas fields in the United States, the Oryx Neptune project in the Gulf of Mexico and the thermal acid gas wells in the Mobile Bay oil field13. Titanium alloy materials such as Ti-6246, Ti–6Al–4V, Gr.29 and Beta-C developed by Chevron have been applied in ultrahigh-pressure high-temperature wells in the Gulf of Mexico14. In China, the CNPC Tubular Goods Research Institute (TGRI) conducted a comprehensive study of the feasibility of titanium alloy tubular goods for oil and gas development, it is proved that titanium alloy pipes had good application prospects under high-temperature and high-pressure exploration conditions. TGRI also defined the material selection map of titanium alloy OCTG used for oil and gas exploration and established related standards in China17. Tianjin Pipe Group Corporation, Panzhihua Iron and Steel Group and other companies have trial-produced titanium alloy tubing products20.At the end of the last century, the feasibility and application of titanium alloys in oil and gas development had studied worldwide, and the performance of titanium alloys OCTGs in oil and gas exploration conditions was evaluated in detail. It had been concluded that titanium alloy materials have significant advantages and application prospects in oil and gas exploration environments21, this service condition require the higher requirements of titanium alloy tubing and casing, especially the collapse strength. However, the evaluation system and standards of OCTGs in the petroleum industry were established based on carbon steel, and titanium alloys are significantly different from steel in terms of elastic modulus and Poisson's ratio. There is no calculation model or standard for predicting the collapse strength of titanium alloy tubing and casing. The gap between the actual collapse strength of titanium alloy pipes and the calculation results of the collapse strength in API and ISO standard systems is still unknown. Bob Hargrave et al. conducted a physical collapse test on Ti–3Al–8V–6Cr–4Zr–4Mo (Beta-C) titanium alloy tubes14, and the results showed that the collapse strength of Beta-C titanium alloy pipes could only reach 90% of the theoretical calculation value according to the API 5C3 standard22. However, the collapse strength formula in the API 5C3 standard has many limitations, including that the calculation accuracy of this formula is not sufficient for small D/t ratio pipes, this formula cannot be applied to non-API OCTGs, and it cannot reflect the resistance induced by different manufacturing processes and heat treatments to the pipe materials. The Klever–Tamano formula recommended by the ISO RP 10400 standard23 has a calculation error of ± 35% for special OCTGs25, so it is difficult to use for the actual design and application of titanium alloy OCTGs. Because there is a lack of research on the collapse strength calculation and tests of titanium alloy OCTGs, the change rule of key parameters  on collapse strength of the tubing and casing is still unclear, and the difference between titanium alloy and steel pipe under the same specifications need to be further analyzed. In this paper, a new collapse strength prediction model, the strength collapse criterion model (SCM), was established for titanium alloy tubing and casing. The collapse strengths of titanium alloy tubing and casing were calculated by this mode and compared with the same specifications of steel pipes. The change in collapse strength with different key parameters was also investigated, and the calculated results were verified by the full-size physical collapse tests. This collapse strength calculation model will provide a technical reference and guidance for the design and application of titanium alloy tubing and casing.Due to the particularity of oil and gas resources in China, the service conditions underground have the characteristics of high temperature, high pressure and high corrosion, such as the Bozi-9 well of Tarim Oilfield in the western of China has reached a drilling depth of nearly 8000 m and bottom pressure of nearly 140 MPaThe analysis and comparison of the full-scale collapse experiments of tubing and casing over the years shows that the collapse failure of the pipe occurs suddenly when the external pressure reaches the limit value. Because the shape of the pipe cannot reach an ideal circle, the stress of the noncircular pipes is not uniformly distributed in the circumferential direction, resulting in an additional bending moment effect. When the external pressure increases, the pipe yields at the place of maximum compressive hoop stress. When the yielding exceeds the limit value, the tubing and casing fail due to an insufficient bearing capacity, resulting in instability collapse, so the strength collapse criterion under external pressure is established as follows:R, and the external pressure is p, as shown in Fig. t, the material is ideally elastoplastic, and the stress–strain relationship can be expressed asFor the casing with initial ovality, assume the initial ovality of the center circle is mentclass2pt{minimTaking the microelements from the long semi-axis of the cross-section of the casing , the angle before and after deformation is entclass1pt{minimas from the inner surface at the long axis of the casing cross-section yields, and due to the symmetry of the casing with an elliptical cross-section, the radial shear stress is zero. For the convenience of calculation, it is assumed that the radial stress of the wall at the long semiaxis is linearly distributed without considering the plastic unloading effect. According to elastoplastic theory, the circumferential stress Assuming that when the pipe collapses, the material with a length of In the elastic zoneIn the plastic zoneSubstituting entclass1pt{minimaM is the bending moment.According to the balance between the force on the long semi-axis of the casing cross-section and the applied circumferential pressure, there is a similar relationship with the bending moment load effect:Taking a unit length of casing, according to the balance between the axial pressure and bending moment in the wall along the long semi-axis of the casing,For the ellipse Combining Eqs.  to 14),,14), the23, as the external pressure gradually increases, the yield length S on the wall thickness section of the long semi-axis also increases until the external pressure reaches the maximum value. Therefore, the extreme value method can be used to obtain the instability and collapse pressure of the pipe. Therefore, the derivative of S gives the following equation:According to the collapse criterion of the external pressure on the pipeS from Eq.  is 0.974, indicating that the absolute error value of the prediction of the collapse strength is less than 3%, and it has relative high prediction accuracy, which can provide a good prediction for the calculation of the collapse strength for titanium alloy tubing and casing  model can effectively predict collapse strength values for titanium alloy tubing and casing, so it is necessary to conduct an in-depth analysis to the influence of key parameters on the collapse strength of titanium alloy pipes compared with steel pipes based on the SCM model.To investigate the influence of ovality on the collapse strength of tubing and casing, it is assumed that the calculated pipes are not affected by the axial load, the external diameter and wall thickness are nominal values from API Spec 5CT, there is no residual stress, the wall thickness is uniform, the yield strength is the nominal yield strength at the 758 MPa level, the elastic modulus and Poisson's ratio of the carbon steel material are 207 GPa and 0.33, respectively, and the elastic modulus and Poisson's ratio of the titanium alloy are 110 GPa and 0.3, respectively. 28 typical specifications of tubing and casings with an outer diameter of 73.02–339.72 mm were selected from API Spec 5CT standard for calculation, and the ovality of the calculated pipes was set at 0.1%, 1%, and 5%, respectively. The calculated collapse strengths of the titanium alloy and carbon steel pipes are shown in Fig. Figure The difference in the collapse strength (the collapse strength “gap”) and reduction percentage between carbon steel pipes and titanium alloy pipes with different ovalities are shown in Fig. In order to evaluate the effect of eccentricity on the collapse strength of titanium alloy and steel pipes, the eccentricity of the calculated pipes was assumed to be 1%, 5%, and 10%. All the calculation parameters were the same as the settings in the ovality analysis above except that the ovality of the pipe was set to 1%. The calculated collapse strength results of 28 typical specifications of titanium alloy and carbon steel pipes are shown in Fig. Figure The collapse strength gap and reduction percentage between the steel pipes and titanium alloy pipes with different eccentricities are shown in Fig. The effect of residual stress on the collapse strength of titanium alloy pipes and steel pipes was evaluated by assuming the residual stress values of 0 MPa, 100 MPa and 200 MPa. The calculation parameters were the same as the settings in the eccentricity analysis above except that the eccentricity of the tubing and casing was set to 5%. The collapse strength comparison of the steel pipes and titanium alloy pipes with different residual stresses were calculated and is shown in Fig. Figure Titanium alloy pipes and steel pipes with 758 MPa and 931 MPa yield strengths were selected to calculate their collapse strengths. The ovality and eccentricity of the calculated pipes were set to 1% and 5%, and the residual stress of both pipes was set to 100 MPa. The other calculation parameters were the same as the settings in the analysis above. The calculation results shows that the collapse strengths of both two pipes can be significantly improved, and the effect of yield strength on the collapse strengths is more obvious in the low D/t ratio area. As the D/t ratio increases, the effect of yield strength on the collapse resistance of pipes gradually disappears, especially for titanium alloy pipes. No obvious changes were observed when the D/t ratio was greater than 20, as shown in Fig. The influence of collapse strength and other key parameters on the collapse resistance of two types of pipes were also investigated and shown in Fig. 28, the comparison of the calculation results calculated by three methods is shown in Fig. The experimental verification tests showed that the strength collapse criterion model (SCM) which proposed in this paper can provide a good prediction for the calculation of the collapse strength for titanium alloy tubing and casing, Compared with the Klever–Tamano formula recommended by the ISO RP 10400 standard and FEA method used a lotFrom the above in-deep analysis of key parameters, it also can be conducted that the ovality had the most significant negative effect on the collapse strength of titanium alloy tubing and casing, due to the ovality of pipe can greatly affect the radius of curvature of the center circle at the long semi-axis in Eq. , thus thA new collapse strength prediction model, the strength collapse criterion model (SCM), was established for titanium alloy tubing and casing. This model assumes that the circumferential stress of a non-ideal circular pipe is not uniformly distributed along the circumference under an external pressure, and an additional bending moment effect exists. When the external pressure increases, the pipe yields at the maximum compressive hoop stress and collapses due to an insufficient bearing capacity, resulting in strength or instability collapse.35 different specifications of 758 MPa strength titanium alloy tubing and casing were selected for full-scale collapse tests to verify the reliability of this SCM model. All the results of the full-scale collapse test were slightly above or close to the calculated results, indicative of a good prediction accuracy for titanium alloy tubing and casing.The in-depth analysis of the influence of key parameters on collapse strength based on the SCM model showed that the ovality had a significant negative effect on collapse strength of pipe, and the influence of material differences on collapse strength can be diminished with the increase of the ovality, the influences of the eccentricity, residual stress and strength on collapse strength were much smaller than that of ovality.In particular, the influences of residual stress and strength can be ignored when the D/t ratio is greater than 20. The collapse strengths of both the titanium alloy and the steel pipes decreased with the increase of the D/t ratio, and the collapse strengths of the titanium alloy pipes were smaller than that of the steel pipes under the same specification due to the low elastic modulus of titanium alloy.In this study, a new collapse strength calculation model for tubing and casing based on the strength collapse criterion model (SCM) was proposed. Full-scale collapse tests were carried out to verify the reliability of the calculation model, and the collapse strengths of titanium alloy pipes and steel pipes with different key parameters were calculated and compared. The following conclusions can be drawn from this work:


Theileria annulata is a tick-borne protozoan parasite responsible for bovine theileriosis, a disease that impacts cattle population in many developing countries. Development and deployment of effective control strategies, based on vaccine or therapy, should consider the extent of diversity of the parasite and its population structure in different endemic areas. In this study, we examined T. annulata in Pakistan and carried out a comparative analysis with similar data garneted in other areas, to provide further information on the level of parasite diversity and parasite genetic structure in different endemic areas. Methods: The present study examined a set of 10 microsatellites/minisatellites and analyzed the genetic structure of T. annulata in cattle breeds from Pakistan (Indian sub-continent) and compared these with those in Oman (Middle East), Tunisia (Africa), and Turkey (Europe). Result: A high level of genetic diversity was observed among T. annulata detected in cattle from Pakistan, comparable to that in Oman, Tunisia, and Turkey. The genotypes of T. annulata in these four countries form genetically distinct groups that are geographically sub-structured. The T. annulata population in Oman overlapped with that in the Indian Subcontinent (Pakistan) and that in Africa (Tunisia). Conclusions: The T. annulata parasite in Pakistan is highly diverse, and genetically differentiated. This pattern accords well and complements that seen among T. annulata representing the global endemic site. The parasite population in the Arabian Peninsula overlapped with that in the Indian-Subcontinent (India) and that in Africa (Tunisia), which shared some genotypes with that in the Near East and Europe (Turkey). This suggests some level of parasite gene flow, indicative of limited movement between neighboring countries.Background:  Theileria genus infect a wide range of domestic and wild animals and are transmitted by Ixodid ticks of several genera including Amblyomma, Haemaphysalis, Hyalomma, and Rhipicephalus , targeting the 18S ribosomal gene (rDNA) as described elsewhere [1 − ∑p2] where n is the number of isolates and p is the frequency of each different allele at a locus [Genetic diversity parameters, including an estimation of the number of alleles per locus and expected heterozygosity lex v6.5  in order a locus .T. annulata populations, whether they comprised of a single panmictic population with a high degree of genetic exchange or not, the multi-locus linkage disequilibrium (LD) of the alleles at pairs of loci was measured using the standard index of association (ISA). Both ISA and the variance of data were calculated using the program LIAN version 3.5 [To determine the genetic structure of sion 3.5 .STF index using the Fstat computer package Version 2.9.3.2. Two estimators of STF (G′ST and θ) [STF) and geographical distances (km) between populations, using the Mantel test of the correlation between the two distance matrices (GenAlex v6.5) [Population differentiation was assessed by estimating Wright’s T and θ) ,39 were ex v6.5) .Finally, the software Structure V. 2.3.4 was used to deduce the underlying structure of parasite population and to determine the number of its sub-populations. This method detects clusters without prior information on the origin of samples. Ten iterations for K = 2 to K = 6 (K being the number of clusters) were run, each with a burn-in period of 10,000 steps and then 20,000 Markov Chain Monte Carlo (MCMC) iterations . In addi


Cascade genetic testing is the identification of individuals at risk for a hereditary condition by genetic testing in relatives of people known to possess particular genetic variants. Cascade testing has health system implications, however cascade costs and health effects are not considered in health technology assessments (HTAs) that focus on costs and health consequences in individual patients. Cascade health service use must be better understood to be incorporated in HTA of emerging genetic tests for children. The purpose of this review was to characterise published research related to patterns and costs of cascade health service use by relatives of children with any condition diagnosed through genetic testing. To this end, a scoping literature review was conducted. Citation databases were searched for English-language papers reporting uptake, costs, downstream health service use, or cost-effectiveness of cascade investigations of relatives of children who receive a genetic diagnosis. Included publications were critically appraised, and findings were synthesised. Twenty publications were included. Sixteen had a paediatric proband population; four had a combined paediatric and adult proband population. Uptake of cascade testing varied across diseases, from 37% for cystic fibrosis, 39% to 65% for hypertrophic cardiomyopathy, and 90% for rare monogenic conditions. Two studies evaluated costs. It was concluded that cascade testing in the child-to-parent direction has been reported in a variety of diseases, and that understanding the scope of cascade testing will aid in the design and conduct of HTA of emerging genetic technologies to better inform funding and policy decisions. Cascade genetic testing is the systematic identification of individuals at risk for a hereditary condition by performing genetic testing in the family members of persons known to possess particular genetic variants  . Three-gCascade health services are recommended for a variety of diseases. Early identification of at-risk individuals is important clinically, as it enables initiation or cessation of periodic screening/surveillance and may trigger lifestyle changes. Cascade testing can be performed as parent-to-child, with a parent identified as the index case and children undergoing carrier testing as indicated. When the proband is a child, cascade health service use occurs as child-to-sibling or child-to-parent. Even when parents do not present with signs or symptoms of disease, they undergo testing for segregation analysis  or to guIn addition to prompting care for family members, cascade testing has implications for the health system because genetic testing can be costly and any consequential care is associated with additional health service use, such as physician referrals. Moreover, cascade service consumption may also result in improved quality or length of life in individuals beyond the proband since genetic testing provides an opportunity to improve surveillance and clinical management in patients’ families. Despite this, cascade effects are not traditionally considered in health technology assessment (HTA) or economic evaluations that form part of the evidence-base for funding and policy decision making. While guidelines for economic evaluation and HTA have begun to recognise the spillover effects of patients’ illness on the costs and health of caregivers , they doThis scoping review was guided by the following research questions: What is the rate and pattern of uptake of cascade testing or screening of family members of children who receive a genetic diagnosis? What are the costs and downstream health services associated with this type of cascade testing and screening? While the purpose of a systematic review is to arrive at a “critically appraised and synthesised answer to a particular question” , scopingOvid Medline and Embase were searched for studies published from January 1, 2000 to January 8, 2020 using keywords, MeSH terms, and Emtree subject headings  flow diagram was constructed .For each study, bibliographic information, purpose, design, methodology, and findings were extracted by one researcher. The literature was categorised according to disease type and findings were summarised descriptively.Included papers were critically appraised using the Scottish Intercollegiate Guidelines Network (SIGN) critical appraisal checklist appropriate to the study design . DetailsThe search yielded 19 publications of which 11 proceeded to full-text review and 17 articles were retrieved through hand-searching. In total, 20 studies were included  (HCM) , 18, 24,Miller et al.  investigAlfares et al.  performeWald et al.  screenedIn an FH study in Beijing , the firIn a case series describing outcomes of cascade genetic testing and clinical screening for FH in Vietnam , five inFinally, Knight et al.  examinedC282Y and H63D (HH-conferring) variants. Nineteen infants from 18 families were C282Y homozygotes and 657 infants were C282Y heterozygotes. Eleven (61%) of the families of homozygous children underwent cascade genetic testing and ten (1.6%) families of heterozygous children requested cascade investigations. Ten relatives were C282Y homozygotes. Cadet et al. concluded that neonatal screening is more effective than untargeted screening of adults for detection of HH.Four studies addressed haematologic conditions such as hereditary hemochromatosis (HH) , severe Gorakshakar and Colah  contacteNine studies examined other monogenic conditions, such as Fragile X syndrome –23, cystIn Australia, uptake of cascade genetic testing after diagnosis of a newborn with CF was 16.3% for all relatives including parents and 11.8% in non-parent relatives . Larger In a Japanese study of prenatal diagnosis for XP-A in ten families , two foeFMR1 (Fragile X syndrome-associated) variants in the US. As of 2013, 3,042 newborns were screened, and 44 family members of genotype-positive newborns underwent testing. In all, 14 newborns and 27 relatives from ten families were variant-positive. Sorensen et al. also presented a case series of three newborns identified as having premutations in FMR1 where carrier testing was performed in relatives including parents, aunts and uncles, grandparents, and great-grandparents [Sorensen et al.  reporteddparents .Stark et al.  investigCase reports of individual families in which a child received a genetic diagnosis of Fragile X syndrome , 22 or tStudies were categorised as high quality, acceptable or low quality (Supplementary Tables This scoping review characterised the research to-date related to the pattern and costs of cascade health service use by the families of children with any condition diagnosed using genetic testing. The 20 included studies were conducted in a variety of diseases, including CMP , 18, 24,sDisease mode of inheritance, penetrance, and expressivity are important factors to consider with respect to cascade genetic testing or clinical screening. Studies included in this review focused on diseases typically inherited in an autosomal dominant manner such as LQTS , HCM 16, 24, DCMStudies mainly reported uptake or yield of cascade genetic testing in probands’ relatives. Uptake of cascade testing in relatives of paediatric HCM patients ranged from 39%  to 65% . In contIn one study , 67% of Only two included publications addressed costs , 19. Of Though economic evaluation guidelines have begun to recognise various forms of spillover effects, cascade effects of genetic testing are not currently incorporated in HTA –5. HowevA strength of this review was that inclusion was not limited by disease. Additionally, a variety of study types were included, enabling a better understanding of the state of research on cascade testing prompted by a genetic diagnosis in a child. Qualitative works were excluded as they likely would not have provided specific data on uptake, yield, or costs of cascade service use. This is a limitation: understanding families’ perspectives would provide important context related to the uptake of these services. Moreover, in some studies with a combined paediatric and adult proband population, the number of index cases from each age group whose relatives underwent cascade investigations was not provided , 25. As An additional challenge was developing a comprehensive search strategy and some eligible papers may have been missed. Of included studies, only three were identified through an electronic search of Medline or Embase, and the remaining 17 were found manually. When designing the search, emphasis was placed on capturing the idea of a paediatric proband. However, it is possible that the focus on a child as the index patient may have compromised the identification of papers with a combined paediatric and adult proband population. In addition, there is no MeSH term or Emtree subject heading for cascade genetic testing, so there is no index for articles specifically about this topic. There is wide variation in the keywords authors use to describe cascade testing, for instance, some call it cascade testing or cascade screening , 28, 31;In conclusion, cascade testing in the child-to-parent direction has been reported in a variety of diseases. This study examined 20 primary studies describing the uptake, yield and consequences of cascade testing triggered by genetic testing in a child. While most studies discussed the uptake and yield of testing, few addressed the costs and health system implications of cascade testing, so these areas remain poorly understood. Cascade effects are not currently considered in HTA and understanding the scope of cascade health service use will aid in the design and conduct of economic evaluations of emerging genetic testing technologies to more accurately assess their costs and benefits.Table S1. Scoping literature review search strategy for Medline.Table S2. Scoping literature review search strategy for Embase.Supplementary File A. Critical appraisal methods and results.Table S3. Critical appraisal of economic evaluations.Table S4. Critical appraisal of cohort studies.Video summary


Glioblastoma is the most common primary brain cancer in adults. One reason for the development and malignancy of this tumor is the misregulation of certain cellular proteins. The oncoprotein STAT3 that is frequently overactive in glioblastoma cells is associated with more aggressive disease and decreased patient survival. Autophagy is a form of cellular self digestion that normally maintains cell integrity and provides nutrients and basic building blocks required for growth. While glioblastoma is known to be particularly resistant to conventional therapies, recent research has suggested that these tumors are more sensitive to excessive overactivation of autophagy, leading to autophagy-dependent tumor cell death. Here, we show a hitherto unknown role of STAT3 in sensitizing glioblastoma cells to excessive autophagy induced with the repurposed drug pimozide. These findings provide the basis for future research aimed at determining whether STAT3 can serve as a predictor for autophagy-proficient tumors and further support the notion of overactivating autophagy for cancer therapy.Glioblastoma (GBM) is a devastating disease and the most common primary brain malignancy of adults with a median survival barely exceeding one year. Recent findings suggest that the antipsychotic drug pimozide triggers an autophagy-dependent, lysosomal type of cell death in GBM cells with possible implications for GBM therapy. One oncoprotein that is often overactivated in these tumors and associated with a particularly dismal prognosis is Signal Transducer and Activator of Transcription 3 (STAT3). Here, we used isogenic human and murine GBM knockout cell lines, advanced fluorescence microscopy, transcriptomic analysis and FACS-based assessment of cell viability to show that STAT3 has an underappreciated, context-dependent role in drug-induced cell death. Specifically, we demonstrate that depletion of STAT3 significantly enhances cell survival after treatment with Pimozide, suggesting that STAT3 confers a particular vulnerability to GBM. Furthermore, we show that active STAT3 has no major influence on the early steps of the autophagy pathway, but exacerbates drug-induced lysosomal membrane permeabilization (LMP) and release of cathepsins into the cytosol. Collectively, our findings support the concept of exploiting the pro-death functions of autophagy and LMP for GBM therapy and to further determine whether STAT3 can be employed as a treatment predictor for highly apoptosis-resistant, but autophagy-proficient cancers. Glioblastoma  is a primary brain tumor that mainly occurs in adults. GBM-patients have a very dismal prognosis with a median survival of ~15 months despite aggressive radiochemotherapy after maximally possible surgery . DiffereAn underappreciated function of STAT3 is its involvement in autophagy and lysosomal function. Recent studies could already show that STAT3 can transcriptionally regulate several genes relevant for autophagy ,25,26,27The lysosomes have been fittingly described as the “suicide bags” of the cells, because of their low pH and content of acidic hydrolases which are able to degrade macromolecules . Damage Here, we used multiple isogenic Crispr/Cas9-derived knockout and stable shRNA-mediated knockdown cell lines to show that depletion of STAT3 has strong rescuing effects on lysosomal stability and this type of cell death, suggesting that STAT3-proficient tumors are particularly vulnerable to this novel therapeutic approach.To analyze the possible role of STAT3 in ADLCD we first tested a panel consisting of 12 human and murine GBM cell lines for their STAT3 expression level and activation state . We obseHereafter, we generated STAT3-knockouts via Crispr/Cas9. Successful STAT3-knockouts of MZ-54 were validated via western Blot A. We couAfter successfully confirming the biological applicability of these STAT3-KO cells we analyzed whether loss of STAT3 may influence the sensitivity of the cells to pro-death autophagy and LMP by using recently described ADLCD-inducing drugs consisting of (1) a combination treatment of imipramine and ticlopidine (IM + TIC) , which sIn addition, we re-expressed STAT3 using stable lentiviral overexpression in MZ-54 STAT3-KO cells  and coulSince changes in ADCD-induction could be caused by a perturbation of the autophagic flux, we next assessed if STAT3-depletion may directly affect it. For this purpose we analyzed the conversion of MAP1LC3B-I (LC3-I) to MAP1LC3B-II (LC3-II) after treatment with Pimo A, STF FB,D and ITo further analyze the functionality of the autophagy pathway, we analyzed the autophagic flux using the LC3-mRFP-GFP tandem construct . TherefIn order to systematically investigate the potential underlying effects of STAT3-depletion on drug sensitivity, we took two of the STAT3-KO lines and compared their transcriptomic profiles with control cells under basal, i.e., untreated conditions. We found that in both KO lines, 141 transcripts were significantly decreased and 140 increased compared to WT A,B. ExceGiven that the drugs used in this study have been previously shown to affect lipid metabolic processes and lysosomal function ,57 and tTo investigate how lipid trafficking and lysosomal accumulation may be affected by STAT3-depletion we decided to analyze lysosomal cholesterol accumulation as a surrogate for lipid accumulation. For this purpose, we analyzed the cells 18 h after treatment with IM + TIC, Pimo, STF, solvent (DMSO) or the positive control U18666A , a catioThese changes in lysosomal function are in agreement with previous reports showing an involvement of STAT3 in LMP and LDCD ,34,35. TOne key characteristic of LMP is the subsequent leakage of lysosomal content, such as cathepsins into the cytosol. Accordingly, we performed digitonin-mediated fractionation of the cytosolic and lysosomal compartments after treatment with IM + TIC, STF or Pimo and detected cathepsin B (CTSB) and D (CTSD) via Western Blot. In WT cells both proteins were found to be prominently enriched in the cytosolic fraction after treatment, whereas the amount of released cathepsins was considerably reduced in at least two out of three knockout lines .In order to obtain more quantifiable data, we measured CTSB activity in the cytosolic fraction using a fluorescence-based enzyme kinetic assay . For thiThe oncogenic transcription factor STAT3 acts as a signaling hub molecule involved in regulation of most, if not all hallmarks of cancer, including proliferation, tumor invasion, altered cellular metabolism, angiogenesis, immune evasion and cell survival. Overactivation of STAT3 is frequently observed in malignant gliomas and correlated to the mesenchymal subtype of GBM, a particularly aggressive and treatment-resistant molecular subgroup of these tumors ,65,66. TRecently, we demonstrated that the ACD-inducing compounds Pimo and the combination of IM + TIC, all three being clinically approved drugs that act as “functional inhibitors of the lysosomal enzyme acid sphinogomyelinase” (FIASMAs), severely impair the trafficking/metabolism of cholesterol and other lipids and induce robust lipid-ROS formation to destabilize lysosomal membranes, thereby triggering lysosomal dysfunction and a type of cell death that is dependent both on autophagy and LMP in GBM cells . The curMechanistically, this death-sensitizing role of STAT3 appears to be independent from alterations in the early steps of the autophagy pathway, because STAT3-deficient and proficient cell lines displayed a very similar extent of LC-3-conversion and an unchanged autophagic flux in our experiments. These findings indicate that STAT3 may rather interfere at the later steps of the autophagosomal/lysosomal pathway, in particular at the lysosomal level. Consistent with this hypothesis, an LMP-promoting role of STAT3 has been documented in several previous studies, for example during mammary gland involution ,34 as weIn addition to enhanced lysosomal activation, the demand for cholesterol may be a second vulnerability of (STAT3-driven) tumors, in particular GBMs that are incapable of de novo cholesterol synthesis and rely on exogenous cholesterol ,78,79. HIn conclusion, our data support the concept of using FIASMAs to simultaneously overactivate autophagy and induce LMP in order to target two potential Achilles heels of GBM, i.e., lysosomal function and lipid trafficking as a novel strategy for the treatment of GBM. In light of the sensitizing function of STAT3 in this context, STAT3-driven tumors may be especially suited for such a therapeutic approach.2. For passaging and seeding, the cells were detached using Trypsin/EDTA-solution (Gibco). The GSC lines PB1, FPW1, MN1, RKI1, RN1, MMK1 were gifted from Bryan Day and Brett Stringer [Human GBM cell lines A172 (ATCC #1620), MZ-18 , MZ-54 , MZ-256 Stringer  and the Stringer , NCH644,Stringer  were gifTo generate Crispr/Cas9-knockouts various potential small guide RNAs (sgRNA) were determined using the Web-App Benchling.com and were cloned into pSpCas9(BB)-2A-Puro (px459) vector (addgene #48139) as described ,83. AfteThe following sequences were used to generate STAT3-KOs: sgSTAT3_A_sense: 3′-aaacCAGTGGCTGCAGTCTGTAGAC-5′, sgSTAT3_A_antisense: 3′-CACCGTCTACAGACTGCAGCCACTG-5′; sgSTAT3_B_sense: 3′-aaacTTGGCTTCTCAAGATACCTGC-5′, sgSTAT3_B_antisense: 3′-CACCGCAGGTATCTTGAGAAGCCAA-5′; sgSTAT3_C_sense: 3′-aaacGTGGGAAGAATCACGCCTTC-5′, sgSTAT3_C_antisense: 3′-CACCGAAGGCGTGATTCTTCCCAC-5′. MZ-54 STAT3-KO#1, #2 and #3 were generated after transfection of sgSTAT3_A and B; A and C; B and C, respectively.Genotyping PCR of STAT3 was conducted using the following Primer: STAT3_fwd: 3′-GTAACGACCTCCCCTTCGC-5′, STAT3_rev: 3′-TGTTTTGTCTCAGGTCTCACCT-5′.The following sequences were used to generate Stat3-KOs: sgStat3_A_sense: 3′-aaacGGCACCTTGGATTGAGAGTC-5′, sgStat3_A_antisense: 3′-CACCGACTCTCAATCCAAGGTGCC-5′; sgStat3_B_sense: 3′-aaacGCTGTACAGCGACAGCTTCC-5′, sgStat3_B_antisense: 3′-CACCGGAAGCTGTCGCTGTACAGC-5′; sgStat3_C_sense: 3′-aaacCATGGAGCTGCGGCAGTTCC-5′, sgStat3_C_antisense: 3′-CACCGGAACTGCCGCAGCTCCATG-5′; sgStat3_D_sense: 3′-aaacGCTGCAGCAGCTGGACACAC-5′, sgStat3_D_antisense: 3′-CACCGTGTGTCCAGCTGCTGCAGC-5′.Tu9648 Stat3-KO#1, #2 and #3 were generated after transfection of sgStat3_A and B; B and D; C and D, respectively. Genotyping PCR of Stat3 was conducted using the following Primer: Stat3_Fwd01: 3′-GAAGCCACGTGTGTGGTAGA-5′, Stat3_Rev02: 3′-TCCTTTTCAGAGTCACCAGGG-5′. All oligonucleotides were ordered from Eurofins Scientific .® SHCLNV-NM_003150, Sigma-Aldrich, Taufkirchen, Germany) or control cells expressing non-mammalian targeting control shRNA  150,000 HEK293T cells were seeded into 6-well plates. After overnight incubation, cells were transfected with 2 μg plasmid DNA (pLKO.1-puro), 1.5 μg gag/pol plasmid  and 0.5 µg VSV-G envelope plasmid  in 57 µL Opti-MEM and 6 µL FuGENE HD  transfection reagent. After medium change after 6 h the viral supernatant was collected after an additional 16 h and 40 h, pooled, filtered through a 0.45 µm filter. The viral supernatant was dilutet 1:1 with fresh medium and supplied 3 µg/mL hexadimethrine bromide . Puromycin was applied at 5 µg/mL and maintained to select for positively transduced cells. psPAX2 was a gift from Didier Trono . pMD2.G was a gift from Didier Trono To generate stable shRNA-mediated STAT3-KD cells . pMRX-IP-GFP-LC3-RFP-LC3ΔG was a gift from Noboru Mizushima . pmCherry-Gal3 was a gift from Hemmo Meyer .To generate cells stably expressing of mRFP-GFP-MAP1LC3B using the plasmid ptf-LC3 , pMRX-Ihttp://n2t.net/addgene:82235; RRID:Addgene_82235, accessed on: 10 December 2021). pLenti CMV Puro DEST (w118-1) was a gift from Eric Campeau & Paul Kaufman . All cell lines were monthly tested for mycoplasma infection using the PCR Mycoplasma Test Kit II (AppliChem) and only negatively tested cells were used for experiments.To re-express STAT3 into MZ-54 STAT3-KO, we used the plasmid pDONR223_STAT3_WT  to clonThe following compounds were dissolved in dimethyl-sulfoxide : imipramine hydrochloride , ticlopidine hydrochloride , Pimozide , STF-62247 , ABT-737 , Etoposide , Fillipin III , U18666A , Digitonin (Sigma-Aldrich) E64D , Pepstatin A .The following antibodies were used in this study: CTSB , 1:1000 (WB), CTSD , 1:1000 (WB), GAPDH  1:20,000 (WB), MAP1LC3B , 1:1000 (WB), LAMP1 , 1:250 (WB), 1:25 (Immunofluorescence (IF)), STAT3 , #9139), 1:1000 (Western Blot (WB)), STAT3 (phospho Tyr705) (CST #9131), 1:1000 (WB) Stat3 , 1:200 (WB), Tubulin (clone DM1A) (Sigma-Aldrich), 1:10,000 (WB).The following Taqman-Probes were used in this study: APOL2 (Hs01935263_s1), APOL3 (Hs00600896_m1), APOL6 (Hs00229051_m1), BIN1 (Hs00184913_m1), BNIP3 (Hs00969291_m1), BNIP3L (Hs00188949_m1), CTSA (Hs00264902_m1), CTSL (Hs00964650_m1), HIF1A (Hs00153153_m1), MMP1 (Hs00899658_m1), MMP2 (Hs01548728_m1), MMP9 (Hs00957555_m1), NPRL3 (Hs00429221_m1), PLAC8 (Hs00930964_g1), SLC2A1 (Hs00892681_m1), SLC2A3 (Hs00359840_m1), SLC66A1 (Hs01120803_m1), SNAI1 (Hs00195591_m1), TBP (Hs00427620_m1).Preparation of protein lysates, SDS-PAGE and Western Blotting was performed as described . BrieflyDigitonin-based fractionation was performed as described previously ,86. Briev/v) absorbance was measured using a Tecan Spark plate reader .MTT -2,5-diphenyltetrazolium bromide) assay was basically performed as described previously . BrieflyFor Scratch assays 200,000 to 350,000 cells were seeded into 6-well plates. The next day 10 µg/µL Mitomycin C (Sigma-Aldrich) was added for 2 h to inhibit cell division. Hereafter a “scratch” was applied using a pipet tip and after refreshing of the medium (without Mitomycin C) the starting point (0 h) was captured using a Nikon eclipse TE2000-S inverted fluorescence microscope operated by NIS Elements AR version 3.2 at 4× magnification. After the indicated incubation times the same regions were examined again and migrating cells were manually counted with the Cell Counter tool from FIJI .® 96 Well 3D Spheroid BME Cell Invasion assay  according to the manufacturer’s instructions. Therefore, 3000–5000 cells were seeded in U-bottomed 96 well plate in 4 °C cold 1× Spheroid Formation Extracellular Matrix (ECM). Samples were centrifuged at 200× g for 3 min at RT to center the cells. Afterwards, samples were incubated for 72 h under culture conditions to allow spheroid formation. Next, the whole plate was chilled for 15 min on ice. Continuously working on ice, 50 µL Invasion Matrix were added to each sample followed by centrifugation at 300× g for 4 min at 4 °C. To promote formation of the Invasion Matrix gel, samples were incubated for 1 h at 37 °C and 5% CO2. Subsequently, 100 µL FBS-containing medium was added. The spheroids were directly analyzed from 0 h to 48 h with Eclipse TS100 inverted fluorescence microscope using 4× magnification and NIS Elements AR software (version 3.22). Quantitation of the area invaded by the tumor cells occurred with Fiji [2). To exclude area changes due to proliferation or spheroid core shrinkage as it may be the case in highly invasive cells [Tumor cell invasion was determined using the Cultrexith Fiji . Therefove cells , the corAll flow cytometry-based application were measured on a BD FACS Aria II or a BD Accuri C6 , per sample 10,000 cells were analyzed.2) containing Annexin V-APC (BD Biosciences) or Annexin V-Fluos (BD Biosciences) and PI and measured within 2 h.Annexin V/Propidium Iodide (PI) assay was performed as described previously . BrieflyEGFP-LC3-mRFP-LC3ΔG  fluorescTM Deep Red  was used according to the manufacturer’s instruction. Briefly, 30 min prior to cell harvesting 25 nM LTDR was added and incubated at 37 °C in the dark. After trypsination, the cells were pelleted and washed twice with PBS and finally resuspended in 50 µL PBS for measurement in the FL-4 channel of a BD Accuri C6.Lysotracker®-coupled secondary IgG antibodies (Thermo Fisher).Standard immunofluorescent stainings were performed as described previously  using 8-2O and mounted DAPI containing immunoselect antifading mounting medium .To monitor the autophagic flux using stable transfectants of ptf-LC3  the cellCellular cholesterol was stained using the cell-based cholesterol assay kit  including filipin III based on the manufacturer’s instructions. Afterwards the slides were prepared for standard immunofluorescent stainng against LAMP1 as described above.To monitor leaky lysosomes stable transfectants of pmCherry-Gal3, excitation/emission max 586/610 nm were treated as indicated and further processed for standard immunofluorescence staining as described above.All images were acquired using a Nikon eclipse TE2000-S inverted fluorescence microscope operated by NIS Elements AR version 3.2 .In total, 50–100 ng of total RNA was fragmented by addition of 5× fragmentation buffer  and heating at 94 °C for 2 min in a thermocycler followed by ethanol precipitation with ammonium acetate and GlycoBlue (Life Technologies) as carrier. Fragmented RNA was further processed using the Ovation Human FFPE RNA-Seq Library Systems (Tecan) according to the instructions of the manufacturer. This library preparation includes reverse transcription using random priming, second strand synthesis, blunt end repair, adapter ligation with nucleotide analog-marked adaptors, strand selection and insert dependent adapter cleavage (inDA-C) to remove rRNA, globin, and other house-keeping transcripts. Target sequences for inDA-C were derived from human sequences. The barcoded libraries were purified and quantified using the Library Quantification Kit—Illumina/Universal . A pool of up to 10 libraries was used for sequencing at a concentration of 10nM. Sequencing of 2 × 150 bp was performed with an Illumina NextSeq 550 sequencer at the sequencing core facility of the IZKF Leipzig  according to the instructions of the manufacturer. Demultiplexing of raw reads, adapter trimming and quality filtering was done according to Stokowy et al. . Mappinghttp://www.pantherdb.org/; v14.1, accessed on: 7 May 2019) [To analyze biologically relevant signaling pathways we employed the PANTHER-tool (ay 2019) ,93 to peRNA-isolation and cDNA-synthesis was performed as described previously . BrieflyHere, we present a novel pro-death function of the oncoprotein STAT3, which is frequently overactivated in multiple human cancers including glioblastoma and is associated with the most aggressive mesenchymal subtype. Using isogenic Crispr/Cas9-Knockouts and stable shRNA-mediated STAT3-KD cells we show that loss of STAT3 leads to reduced sensitivity to known ACD-inducers. We show further that this is accompanied by reduced lysosomal lipid accumulation in STAT3-deficient cells and therefore less leakage of lysosomal contents in the cytosol, which causes LDCD in STAT3-proficient cells. In conclusion, these findings offer new research directions to develop targeted therapies of STAT3-activated, autophagy-proficient tumors such as glioblastoma.


Fusarium head blight (FHB) is one of the economically important diseases of wheat as it causes severe yield loss and reduces grain quality. In winter wheat, due to its vernalization requirement, it takes an exceptionally long time for plants to reach the heading stage, thereby prolonging the time it takes for characterizing germplasm for FHB resistance. Therefore, in this work, we developed a protocol to evaluate winter wheat germplasm for FHB resistance under accelerated growth conditions. The protocol reduces the time required for plants to begin heading while avoiding any visible symptoms of stress on plants. The protocol was tested on 432 genotypes obtained from a breeding program and a genebank. The mean area under disease progress curve for FHB was 225.13 in the breeding set and 195.53 in the genebank set, indicating that the germplasm from the genebank set had higher resistance to FHB. In total, 10 quantitative trait loci (QTL) for FHB severity were identified by association mapping. Of these, nine QTL were identified in the combined set comprising both genebank and breeding sets, while two QTL each were identified in the breeding set and genebank set, respectively, when analyzed separately. Some QTLs overlapped between the three datasets. The results reveal that the protocol for FHB evaluation integrating accelerated growth conditions is an efficient approach for FHB resistance breeding in winter wheat and can be even applied to spring wheat after minor modifications. Triticum aestivum L., 2n=6x=42, AABBDD) is an essential small-grain cereal crop grown for food and feed. In northern Europe, including Germany, wheat is the single most cultivated cereal crop where winter wheat is occupying the first place in production  obtained from the Nordic Genetic Resource Center (Nordgen). The second source of the plant material consisted of 338 genotypes (breeding set) provided by the Swedish agricultural cooperative .−2 s−1 for 8h at °C 22, night 16h of darkness with at 20°C while keeping relative humidity (RH) of 50%. After successful germination, plants were thinned and only one plant was allowed to grow in each pot.This work was conducted in the biotron, a facility with controlled-climate chambers at the Swedish University of Agricultural Sciences (SLU) in Alnarp, Sweden. Several seeds of each genotype were planted in 8×8×8cm plastic pots filled with peat soil from Emmaljunga Torvmull AB, Sweden. The pots were arranged using the augmented block design described under the experimental design section. The pots were watered as required, and the seeds were left to germinate for 5days. During the seed germination period, day-length parameters were adjusted at a light intensity (LI) of 250μmolm−2 s−1. At this intensity, vernalization light source, wavelength composition, and individual wavelength intensities are described under accelerated growth conditions. RH was 80% for 8–9weeks (approximately 60days).Seedlings were vernalized by growing under short-day conditions of 8/16h day/night regime with the temperature of 3°C and LI of 250μmolm−2 s−1 on the second day and was left unchanged throughout the acclimatization period. RH was gradually lowered to reach 50% at the end of the acclimatization . High nitrogen fertilizer was added at 10 dpa followed by high potassium soluble fertilizer Yara Tera Kristalon NPK 12-5-30 with S, and micro was added twice at 15 and 20 dpa.At the end of the acclimatization period, the plants were allowed to grow for 32days under the same conditions as on the last acclimatization day . The lig earlier . Due to Fusarium species F. graminearum and F. culmorum provided by the plant breeding company Lantmännen Lantbruk were used in the preparation of the inoculum. These included six isolates of F. graminearum and three isolates of F. culmorum. Using a large number of isolates was intended to identify germplasm with broad resistance to various Fusarium species. The isolates were cultured on the weak Spezieller Nahrstoffarmer agar media (®20 0.002% (v/v) was added to the final suspension containing the spore concentration of 5×105 spore/ml.Isolates belonging to ar media . The culUpon completing ear emergence and the emergence of anthers, approximately 33 dpa plants were moved to grow under a long-day regime with 16/8h day/night in the greenhouse chamber. RH was adjusted to 60%, and the temperature was maintained at 24°C. The new growth conditions were intended to allow the plants to continue growing for 24days without accelerated growth until physiological maturity. Daily watering and weekly fertilization were carried out at this stage. Plants at 75% heading were spray-inoculated once, and inoculated plants were incubated at a high RH of 90% for 48h while keeping other growth parameters unchanged. At the end of this incubation period, RH was lowered to 60%, and plants were allowed to grow until the end of the 24day period.The visual assessment of FHB disease severity on the spikes was carried out at 6, 8, 10, and 12-days post-inoculation (dpi). Generally, visual symptoms, such as bleached, yellowish or discolored, and stunted spikes, indicate the development of FHB on the ears. Disease spread was evaluated as percentage infection ranging between 5% (most resistant phenotypes) and 100% (most susceptible phenotype). The percentage rating scoring was based on the relative number of infected spikelets to the total number of spikelets per spike on the main tiller  with an The genotypic variation in heading and flowering represents a challenge that may affect the uniformity of FHB development on a large and diverse number of artificially inoculated plants. Additionally, certain genotypes may require longer periods of vernalization to promote heading and subsequently flowering leading to the inoculated plants at earlier stage for those genotypes compared to the rest of the genotypes in the germplasm. In order to limit the bias in the downstream analysis of FHB resistance, germplasm genotypes that showed 0% infection phenotype (absence of infection symptoms) in the material were discarded together with genotypes that have not reached heading at the time of inoculation. Only genotypes that scored varying FHB symptoms that ranged between 5 and 100% were included in the analysis.Watering was discontinued 21days after FHB infection conditions while keeping all other growing conditions unchanged. RH was lowered to 40% 24days after reproductive growth in the greenhouse and the plants were left to mature. Spikes were harvested approximately 30days after FHB infection conditions.During the reproductive growth period, flag leaf area (FLA) was measured for each genotype using LI-3000C Portable Leaf Area Meter. Spike length (SL) and spike width (SW) were estimated using a digital Vernier caliper scale. In order to avoid bias in SW (thickness of the spike), width measurement was always performed at the third lower spikelet.Heading time (HT) was taken depending on the emergence of 75% of the spikes out of the sheath of the flag leaf at three time points recorded every third day consecutively. Spikes were categorized according to the three HTs as early (HT1), medium (HT2), and late (HT3). Anther extrusion was recorded at two time points with 2days difference and was recorded as early (AE1) and late (AE2).Four replicates each of genebank and breeding sets were arranged in an augmented block design developed using the package Agricolae in R . The desUnadjusted means of cultivars within the augmented design of each replicate were filtered and removed for the cultivars that gave a percentage of 0%. Phenotypic data were analyzed in two steps. First, the checks in each augmented block were used to adjust the means for each trait per experiment/replicate using the Agricolae R package  based onwhere, y_il is the adjusted means of the ith wheat genotype in the lth block, u is the general mean value, G_il is the effect of the ith wheat genotype in the lth block, B_l is the lth block effect, and ε_il is the residual. For FHB severity, the area under disease progress curve (AUDPC) was estimated from the adjusted means of the four disease ratings for each experiment. In the second step, the adjusted means were used to calculate the best linear unbiased estimates (BLUEs) following the randomized complete block design option in META-R 6.04  based onwhere, y_ijm is the BLUE of the ith wheat genotype from the jth source/population in mth replicate, u is the general mean value, S_j is the effect of the jth source of material, G_ijm is effect of the ith wheat genotype in the mth replicate, R_m is the mth replicate effect, and ε_ijm is the residual effect. The source of wheat genotypes, S_j, was treated as the grouping factor.The genebank set was genotyped previously using a 20K SNP marker array as described by Seven models were used for the GWAS: general linear model , mixed l−2 s−1 while RH was decreased from 80 to 50%. After that, accelerated growth conditions allowed plants to rapidly reach the reproductive phase within 30–33days while limiting any visible symptoms of plant stress. At this stage, scoring for heading time, anthesis time, and FLA was performed. Thereafter, FHB infection conditions were introduced to promote FHB infection. Plants were thereafter allowed to mature before harvesting  consisted of three major growth periods, namely, (a) the pre-accelerated growth period when the plants were allowed to germinate and vernalize under optimal growth conditions; (b) the accelerated growth period when the plant growth was fast-tracked; and (c) the FHB infection period when the plants were grown in conditions optimal for FHB infection and maturity . The prervesting . The entThe AGFHB protocol was used for the evaluation of a total of 519 genotypes consisting of 181 genotypes in the genebank set and 338 genotypes in the breeding set. At the time of the FHB inoculation, 88 and 90% of the plants completed 75% heading of their spikes intended for FHB resistance evaluation in the breeding and genebank sets, respectively. With regard to flowering, 67 and 88% of the plants reached anthesis in the breeding and genebank sets, respectively. As previously stated, genotypes that did not reach the stage of 75% heading at inoculation time were discarded from the following FHB severity scoring together with genotypes that exhibited no visual disease development on the ears.2 (s=3.87), while for the genebank set, it was 17.15mm2 , while in the breeding set was 87.82mm , while in the breeding set was 11.10mm . The average AUDPC was 225.13 (s=129.98) for breeding set and 195.53 (s=130.44) for genebank set . We found highly significant genotypic variances (p<0.0001) and moderate to high broad-sense heritabilities, depending on the trait and the source of genotypes  was observed between the two groups for mean FHB estimates obtained under controlled conditions.To further evaluate the FHB severity estimates from this work, comparison was done with FHB scores from a previous field trial from 2019 conducted by the breeding company Lantmännen Lantbruk. The FHB scores from the field trial were collected in the scale of 1–8. From the breeding set, 275 genotypes were found to be common in the two datasets. A spearman correlation of 0.24 was observed in the FHB scores between the two datasets. When the genotypes were grouped as resistant (FHB scores 1–3) and susceptible (FHB scores 6–8) a statistically significant difference (p≤0.0001) in the combined dataset (N=432). Four QTLs were co-detected by at least two GWAS models  and genebank set (N=160) for the resistance against FHB severity was located on the sub-genome B  than for lines from within each source population alone (p=0.001 [−log(P)=3] for the GWAS within each source population  based on field trials , FHB (0.53–0.57), FLA (0.41–0.53), spike length (0.70–0.77), and spike width (0.44–0.64). In previous studies, the average broad-sense heritabilities for FHB resistance traits were 0.54–0.73  reported by r=−0.16, p=0.001). FHB resistance QTLs may be population specific and QTLs with minor effects control FHB resistance and are difficult to detect in smaller populations. In this study, the presence of common FHB resistance QTL regions in both breeding and genebank sets increased the power to detect more QTLs in the combined set and even at a higher significance threshold  might be associated with a major QTL (SLUfhbchr3B.4) that regulates FHB severity in the material analyzed  as well as FLA and SL .The genetic architecture of heading, anthesis, SW, SL, and FLA is complex, being influenced by several QTLs  and 4. Sp=0.0001, we found more QTLs for GWAS incorporating lines from both genebank and breeding sets than GWAS within each source population separately. However, within genebank set or breeding set, several QTLs could be detected at a lower significant threshold , only a few were present at p<0.0001, depending on the trait (α=0.05; In GWAS, large population sizes are required to detect QTLs with small effects and to reduce the Beavis effect . Consequhe trait  and 4. Fhe trait . The res α=0.05; . Higher Speeding up of the generation cycle was achieved by integrating SB protocol in diverse winter wheat genotypes used in the improvement for Nordic winter wheat cultivars. Within this work frame, screening for disease resistance among the genotypes for FHB was evaluated in the assigned Nordic germplasm. A significant genetic variation could be found for FHB resistance and agronomic traits in Nordic wheat germplasm. The molecular mechanism of FHB resistance is very complex, governed by multiple loci. Resistant alleles were present in both LM and NG materials and can be harnessed to improve FHB resistance in winter wheat by genomics-assisted speed breeding.Due to the prolonged nature of winter wheat growth requiring vernalization at every generation, conventional breeding programs have the potential to release new cultivars in 15years. Taking into account the period required for vernalization, the current protocol for disease resistance in wheat provides the potential for reducing the growth by 55 to 110days per generation. Therefore, a significant time saving up to 2–3years can be expected in trait introgression breeding programs using several generations of backcrossing and 1year in conventional SSD programs.The original contributions presented in the study are included in the article/AC and TH conceived the study. AC, MZ, and FO planned the greenhouse experiments. TH developed the breeding population set. MZ, FL, MA, and FO performed the greenhouse experiments. MZ and DG analyzed the data and wrote the first draft. All authors contributed to the data interpretation and approved the final version of this manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.