The species we have studied the spatiotemporal genetic change in the northern dragonhead, a plant species that has experienced a drastic population decline and habitat loss in Europe. We have added a temporal perspective to the monitoring of northern dragonhead in Norway by genotyping herbarium specimens up to 200 years old. We have also assessed whether northern dragonhead has achieved its potential distribution in Norway. To obtain the genotype data from 130 herbarium specimens collected from 1820 to 2008, mainly from Norway (83) but also beyond (47), we applied a microfluidic array consisting of 96 SNP markers. To assess temporal genetic change, we compared our new genotype data with existing data from modern samples. We used sample metadata and observational records to model the species' environmental niche and potential distribution in Norway. Our results show that the SNP array successfully genotyped all included herbarium specimens. Hence, with the appropriate design procedures, the SNP array technology appears highly promising for genotyping old herbarium specimens. The captured genetic diversity correlates negatively with distance from Norway. The historical‐modern comparisons reveal similar genetic structure and diversity across space and limited genetic change through time in Norway, providing no signs of any regional bottleneck . The regional areas in Norway have remained genetically divergent, however, both from each other and more so from populations outside of Norway, rendering continued protection of the species in Norway relevant. The ENM results suggest that northern dragonhead has not fully achieved its potential distribution in Norway and corroborate that the species is anchored in warmer and drier habitats. Dracocephalum ruyschiana). It also showcases a fruitful integration of methods and data sources that jointly enables a holistic species assessment covering space and time.Our study provides new insight to guide conservation priorities for the charismatic flowering plant called northern dragonhead ( In order to predict how climatic and other changes will affect biodiversity, holistic knowledge is needed, from the level of genes to ecosystems. Drivers of biodiversity act both across space and through time. Holistic biodiversity studies should therefore include both spatial and temporal data of various kinds. Contemporary genetic, distributional, and ecological data provide a spatial snapshot across the latest generations only. In the absence of real‐time historical genetic data, various methods have been developed for approximating the past and predicting the future impacts of change  based on contemporary data alone. Liberating genetic, distributional, and ecological data from archived biological specimens, however, would enable to create a solid base to study temporal biodiversity dynamics in real time.Post‐mortem degradation of DNA is an inherent trait and unending process of biological materials challenging the usability of archived biological specimens in DNA studies  collected throughout the world, some of which are several 100 years old. Such scientific collections provide verifiable records of the existence of an organism at a given time and place. With the exception of a few studies, such biological specimen archives have remained a largely untapped resource to study trajectories and trends of genetic diversity  with eco‐informatics  promises to be a fruitful integration of scientific domains, enabling more holistic species knowledge to guide monitoring efforts, in which knowledge about a species' behavior in relation to external forces over time is key. While genomic data can provide an evolutionary framework and delimit units at which selection is operating, georeferenced herbarium records provide basic occurrence data that can be used to understand, predict, and map species distributions and examine past phenological trends and even species interactions  by testing a microfluidic‐based SNP genotyping array on old herbarium specimens. This approach has recently been applied by others to historical materials of, for example, tropical tree species and salmon  contain about 390 million specimens collected throughout the world for more than 350 years Thiers, . In the Northern dragonhead is considered a remnant of the glacial steppe flora in Europe with its westernmost occurrences in France and Scandinavia , insect‐pollinated, perennial herb  The plant's biology as insect‐pollinated and mainly outcrossing  and across space . More specifically, we wanted to assess whether the overall and regional genetic diversity of northern dragonhead in Norway has changed. Performing environmental niche modelling (ENM) on occurrence records of northern dragonhead in Norway, we wanted to reveal which abiotic factors may be limiting its distribution and whether there are areas in which northern dragonhead do not occur today that may represent suitable habitats.22.1For the present study, we sampled 130 herbarium specimens of northern dragonhead collected between 1820 and 2008 Table . The maj2.22 of leaf material was removed from each herbarium specimen using clean forceps and placed directly into a microfuge tube. The leaf material was pulverized with two Qiagen 3 mm tungsten carbide beads in a Qiagen TissueLyser LT at 50 Hz for 2 min. We extracted DNA using the DNeasy® Plant Mini Kit (Qiagen) with modifications from the manufacturer's instructions as described by Martin et al. (https://www.fluidigm.com/software). Positive and negative controls were included.All manipulations of the herbarium specimens postsampling were performed within the NTNU University Museum's dedicated, positively pressurized, paleo‐genomics laboratory. About 0.5 cmn et al. . We incun et al. . The samWe excluded SNPs with more than 10% missing data across all herbarium samples. For each genotyped sample, we subsequently calculated the call rate (CR) and the proportion of successfully genotyped loci. The relationships between specimen collection year, CR, and DNA concentration were estimated using the Pearson's correlation test implemented in R . Due to incomplete overlap between historical and modern sampling sites (some even representing extinct populations), which complicated direct temporal comparisons of populations, we grouped samples into the geographical regions that correspond to the distinct genetic groups discovered by Kyrkjeeide et al. (https://doi.org/10.5061/dryad.c59zw3r8g).The contemporary samples from Kyrkjeeide et al.  are heree et al. . RegionsK from 1 to 40, with 20 replicates for each value of K. For the GLOB dataset, we performed three different runs including (1) all samples, (2) only extra‐Norwegian samples, and (3) only 2–4 individuals from each country for a reduced and balanced sampling. For all three runs with GLOB, we tested K from 1 to 10, with 20 replicates for each value of K. Calculation of the optimal number of clusters and visualization of the results were obtained using find.cluster  and ΔK  for NOR using the R function stamppFst  and expected heterozygosity (HE), and the inbreeding coefficient (FIS) using the basic.stats function in R. We used the R summary function (adegenet package) to obtain the number of alleles, isPoly for the number of polymorphic loci, and private_alleles . To visually explore the potential change in genetic diversity over time, we plotted the estimated HE of historical and modern regions against the oldest and youngest collection year, respectively. The subsample averaged HE (and SD) was used for regions with uneven historical and modern sample size. We additionally plotted the individual proportion of heterozygous loci (PHt) against the sample collection year within each region.For NOR, after transforming our data to a adegenet function isPoly. To evaluate whether the GLOB genetic diversity was affected by distance from the SNP array's source population (Norway), we estimated the Pearson's correlation between PHt and the sample localities' distance from Oslo , an approximate centre of the SNP array's source populations.For GLOB, genetic diversity was estimated as the proportion of heterozygous loci per individual (PHt). We calculated the number of polymorphic loci for the individual countries utilizing the 2.410.15468/dl.748g3v, accessed via GBIF.org on 2021‐03‐13). We added coordinates for GBIF‐IDs lacking this information according to locality information and its precision , mean annual precipitation (MAP), and precipitation seasonality . These are the same variables that, according to Speed and Austrheim , represe33.1R = 0.35 , the optimal number of genetic clusters varied depending on the applied optimization method. The mean log posterior ln P(K) was found to continuously increase with increasing K and reached the highest value for K = 24  was low at K = 1. Highest MedMed K, MedMean K, and MaxMean K were observed for K = 7, whilst MaxMed K was highest for K = 8. Using find.cluster, the lowest BIC value was found between K = 5 and K = 8 , when sorting samples according to predefined regions, six of the clusters largely corresponded to the regional areas: Hedmark, Oslofjorden (east and west), Randsfjorden, Tyrifjorden, and Valdres‐Gudbrandsdalen . Pairwise comparisons of regions (in both time and space) yielded generally low FST values, but all 95% confidence intervals were above zero (Table FST = 0.033) and Tyrifjorden (FST = 0.028), which both also displayed a decline in spatial divergence over time. This decline in FST was only significant for Randsfjorden . The genetic differentiation between Gudbrandsdalen and Hedmark, on the other hand, increased significantly over time, and represented the highest value among all modern pairwise comparisons (FST = 0.042).The DAPC results corroborated the separation of Oslofjorden and Tyrifjorden, respectively, from the remaining regions, when a priori grouping our samples according to the regional areas Figure . The firro Table . The laren Table . Values HE) averaged over all regions was slightly higher in the historical  compared to that in the modern group , both with positive FIS values (Table FIS = 0.107 (SD ± 0.056) in the historical to FIS = 0.062 (SD ± 0.019) in the modern group. Looking at a finer scale, HE ranged from 0.303 to 0.353 for the historical regions and 0.299–0.336 for the modern (Table HE and PHt) across time varied between regions  in FIS values (Table FIS), averaged across all replicates, was 0.085 (SD ± 0.032) for Hedmark, 0.052 (SD ± 0.012) for Oslofjorden, 0.073 (SD ± 0.092) for Randsfjorden, and 0.110 (SD ± 0.067) for Tyrifjorden.The genetic diversity ( SD ± 0.06 in the es Table . The inb3.3ln P(K), increased until K = 3 and made a drop before increasing to its maximum at K = 7. We found the highest value of ΔK under K = 2, although ln P(K) was low at K = 1. We found the highest MedMed K, MedMean K, MaxMean K, and MaxMed K for K = 4. Using find.cluster, we observed the lowest BIC value between K = 2 and K = 6  increased until K = 4 and K = 3, respectively. For increasing values of K, the ln P(K) continued to decrease. For both these analyses, the highest value of ΔK was found under K = 2, whereas MedMed K, MedMean K, MaxMean K, and MaxMed were highest at K = 3.Results from the STRUCTURE analysis on the full GLOB dataset varied with regard to the number of optimal genetic clusters depending on the applied optimization method Figure . The mea6 Figure . At K = s Figure . At K =  Figures . Furthere Figure . Belaruse Figure  and balae Figure , we obseR = −0.49, p = 5.69 × 10−9; Figure When a priori grouping the herbarium specimens by geography , the first and second DA explained 59.3% and 40.7% of their total genetic variation, respectively Figure . The DAP3.4Across all the replicated environmental niche models, the mean AUC was 0.95 (SD ± 0.03). The relative variable importance was highest for mean summer temperature , followed by mean annual precipitation , and lowest for precipitation seasonality  for the herbarium specimens.Despite the lower DNA concentration of the extracts from the historical specimens, all samples were successfully SNP genotyped. As for the DNA stock concentration, the call rate (CR) seemed to be surprisingly little affected by time since collection when comparing modern with historical samples Figure ; our hisC. odorata, typically contain high levels of anti‐predation polyphenolic compounds in their leaves , our results demonstrate the effect of SNP ascertainment bias , which shows a systematic deviation from theoretical expectations  or changes in levels of heterozygosity through time . We did record a small decrease in the overall inbreeding coefficient over time, from FIS = 0.107 in the historical to FIS = 0.062 in the modern group. A decrease in FIS (but still FIS >0) could be an indication of overall less effects of genetic drift or a higher degree of outcrossing compared with historical times. It should, however, be mentioned that the standard deviation for the obtained overall FIS was relatively large for the historical group (SD ± 0.056). Moreover, our current data may not be suitable for robustly inferring a reduction in population size, due to ascertainment bias of the SNP array. The SNP array we have used is based on modern material alone and would not have recovered genetic diversity only present in historical samples.By comparing our obtained SNP data from herbarium specimens with modern SNP data of Kyrkjeeide et al. , we founSalmo salar L.) over approximately 100 years with only 82 SNPs (vs. 92 in the present study). Species with shorter generation turnover tend to have higher rates of temporal genetic change, presumably because more frequent genome replication leads to more replication errors per unit time . The analysis software STRUCTURE, which we have used herein, assumes that markers are not linked and that populations are panmictic  was shown to be present in modern samples of northern dragonhead in Norway , indicative of genetic drift or inbreeding. Surprisingly, the genetic diversity (HE) within Gudbrandsdalen, Oslofjorden, and Tyrifjorden had increased over time  also decreased in both regions, consistent with the loss of rare alleles following genetic drift. As genetic drift proceeds, the genetic divergence is expected to increase, which potentially can explain why the only significant temporal increase in FST values was recorded between Hedmark and its adjacent region, Gudbrandsdalen (Table n = 3). Our genetic statistics based on subsampling of the modern regions to the same sample size as the historical ones indicated that Randsfjorden was most affected by sample size—displayed by the largest standard deviations , the inbreeding coefficient decreased over time Table . There we Figure . Given ten Table . Randsfjns Table .HE = 0.316 vs. HE = 0.30, HO = 0.296 vs. HO = 0.27, and FIS = 0.062 vs. FIS = 0.10, respectively). This may not always be the case, however, especially in cases of strong subpopulation structuring. Hence, the approach used herein may not be applicable for other species or certain areas of their distribution.Future studies, focusing on temporal genetic changes, should map available historical specimens in natural history collection prior to collecting modern data. In this way, one could allow targeted and regular modern sampling in historically well‐covered sites, ensuring sufficient sample sizes and preferably enabling direct population comparisons. Our overall measures of modern diversity, which were based on regions, were comparable to those obtained by Kyrkjeeide et al. , which w4.2.3Carex jemtlandica . It is therefore possible that dry and calcareous habitats in Finnmark in northeastern Norway may represent a suitable area for the species, to which it has so far not reached. This would imply that similar habitats in northern Finland, northern Sweden, and northwestern Russia could represent suitable areas for northern dragonhead survival, areas where the species does not occur today.We applied environmental niche modeling (ENM) to identify areas potentially suitable for northern dragonhead in Norway. Our ENM results suggest that the distribution of northern dragonhead is anchored in warmer and drier regions within Norway, more specifically areas with mean summer temperatures higher than 10°C and <~800 mm of mean annual precipitation Figure . These felvetica , norther5With this study, we demonstrate that, with the appropriate design procedures, the microfluidic SNP array technology is promising for genotyping old herbarium specimens; an invaluable source of information from the past. As expected, the SNP array picked up less genetic variability in the extra‐Norwegian specimens, likely due to both genetic divergence and the fact that the array was developed based on modern Norwegian samples alone. Our temporal genomic analyses of northern dragonhead in Norway show no signs of any severe reduction in population size in any of the studied regions. This may seem like good news, which indeed it might be if it is so that the populations have remained large enough to withstand the effect of genetic drift and inbreeding. The same results may, however, be due to a time lag in the response caused by the relatively long generation time of northern dragonhead. It is tempting to speculate whether our results could also be reflecting the ongoing climate change; increasing temperatures and less precipitation could potentially lead to an increase in connectivity and gene flow between neighboring populations and an expansion of the limits of currently suitable habitats. Regardless, the regional areas studied are genetically divergent across space, both from each other and clearly so from populations outside of Norway, rendering continued protection of the species and its regional genetic variation in Norway relevant. Our ENM results suggest that northern dragonhead has not yet reached its potential distribution in Norway. With the future inclusion of additional parameters , ENM should prove useful for guiding management authorities in translocation for conservation initiatives.Malene Nygaard: Data curation ; formal analysis (lead); investigation ; methodology ; visualization (lead); writing – original draft (lead); writing – review and editing . Alexander Kopatz: Formal analysis (supporting); investigation ; methodology ; supervision (supporting); visualization (supporting); writing – review and editing (supporting). James D. M. Speed: Formal analysis (supporting); investigation ; methodology ; visualization (supporting); writing – review and editing (supporting). Michael D. Martin: Conceptualization ; funding acquisition ; investigation (supporting); visualization (supporting); writing – review and editing (supporting). Tommy Prestø: Conceptualization ; data curation (supporting); funding acquisition ; writing – review and editing (supporting). Oddmund Kleven: Data curation ; investigation ; methodology ; supervision ; visualization (supporting); writing – review and editing (supporting). Mika Bendiksby: Conceptualization ; data curation ; funding acquisition ; investigation ; methodology ; project administration (lead); supervision ; visualization (supporting); writing – original draft (supporting); writing – review and editing .The authors have no conflict of interest and no relevant financial or nonfinancial interests to disclose.Figure S1–S14Click here for additional data file.Table S1–S5Click here for additional data file.


A fluorescence microscope is one of the most important tools for biomedical research and laboratory diagnosis. However, its high cost and bulky size hinder the application of laboratory microscopes in space-limited and low-resource applications. Here, in this work, we proposed a portable and cost-effective fluorescence microscope. Assembled from a set of 3D print components and a webcam, it consists of a three-degree-of-freedom sliding platform and a microscopic imaging system. The microscope is capable of bright-field and fluorescence imaging with micron-level resolution. The resolution and field of view of the microscope were evaluated. Compared with a laboratory-grade inverted fluorescence microscope, the portable microscope shows satisfactory performance, both in the bright-field and fluorescence mode. From the configurations of local resources, the microscope costs around USD 100 to assemble. To demonstrate the capability of the portable fluorescence microscope, we proposed a quantitative polymerase chain reaction experiment for meat product authenticating applications. The portable and low-cost microscope platform demonstrates the benefits in space-constrained environments and shows high potential in telemedicine, point-of-care testing, and more. With the rapid development of nucleic acid detection technology, polymerase chain reaction (PCR), invented by Mullis in 1983 , emulsioGiardia lamblia cysts by incorporating machine learning [For portability and cost-efficiency purposes, smartphone-based microscopes provide a potential straightforward solution for a broad range of applications. Several mobile phone-based portable microscopic imaging systems have been developed for point-of-care diagnostics . For exalearning . Anotherlearning  by desiglearning  and our learning  both demGenerally speaking, the way to achieve a low-cost and portable fluorescent microscope system is to replace expensive components with inexpensive alternatives to achieve similar functionality. Current developments in consumer-oriented manufacturing technologies, such as 3D printing, are facilitating individual researchers to customize laboratory equipment or build entire devices from scratch . In paraTo evaluate the capability of the portable fluorescence microscope, we proposed a quantitative polymerase chain reaction experiment for meat product authenticating, using a microfluidic chip. In recent years, researchers have also made efforts in on-chip PCR technology. Continuous microfluidics-based on-chip PCR systems were developed for the detection of Epstein–Barr virus  and multOur goal was to design a portable miniature fluorescence microscope. It had to provide sufficient precision to focus on microscopic objects while being mechanically stable. To control costs, 3D printed parts were used for assembly to make it affordable and deployable in low-resource situations. Importantly, it also had to provide fine resolution and image quality for most applications to enable bright-field and fluorescence channel measurements.The overall structure of the portable microscope is shown in X-Y axis sliding stage was assembled with high-precision miniature slides and springs. The movement of the Z-axis depended on the manual rotor that fits into the base.The base structure of the microscope was fabricated by 3D printing using white photosensitive resin with a layer thickness of 200 μm. The model was designed in the 3D drawing software SolidWorks 2016 . All holes and threads for bolt and screw assembly can be printed out directly without additional machining. An A commercially available webcam  was mounted on the bottom. The bracket extending from the bottom was used to install the LED light source. For the webcam to perform the functions of a microscope, the lens was inverted to achieve magnification rather than the magnification mechanism employed by the camera. Images were obtained from a laptop with the webcam connected through a universal serial bus (USB) port, using a webcam program.XY direction is designed to adjust the focusing area, while the Z direction is designed for focusing and magnifications. The demonstration video of the operations for the XYZ movement is provided in the To obtain clear microscopic images from targets with different sizes, a sliding stage was assembled based on a combination of 3D-printed components and four micro-slides . Among the three freedom-of-degrees, the X-direction and another set for movement in the Y-direction. In order to limit the volume and to have a large adjustment range, each slide was machined into being 50 mm long to allow a movement range of approximately 2 cm × 2 cm in area after assembly. Two hand-screwed bolts (M5 × 25) were used for adjustment and four springs for bringing the stage into position. Note that the bracket should be designed to be dispersed and assembled, otherwise it will not be assembled due to interference. For Z-direction adjustment, utilizing the bolt and nut mechanism, a 3D-printed nut fits into the threads on the base, and the stage can be focused with the rotation of the manual rotor  of the portable microscope, a commercial hemocytometer  was used for calibration. Polystyrene microspheres of different diameters  were used to evaluate the spatial resolution of the portable microscope. Bright-field images were captured, and pixel intensities were measured with ImageJ software . The field of view was calculated by imaging the grids on the hemocytometer.To facilitate observation, sealable microfluidic chips were fabricated to replace the centrifuge tubes used in commercial PCR instruments. First, polydimethylsiloxane  was poured onto a clean slide. Note that the slides need to be silanized to strengthen the hydrophobicity for PDMS peeling. After curing at 80 °C for 2 h, the PDMS was peeled off the slides. Next, according to the experimental requirements, one or several holes of 3 mm diameter were punched. Then, the PDMS chip was bonded on top of the glass substrate by standard plasma bonding. Finally, after adding the reaction solution, an adhesive sealing film was placed on the chip to seal it. Furthermore, a miniature thermocouple  connected with a microcontroller was placed on the side of the glass slider to satisfy the temperature requirements of nucleic acid amplifications shown on The meat used in this study was duck purchased from a local supermarket. DNA was extracted from the tissues and purified using MightyPrep™  according to the manufacturer’s protocols. First, 25 mg of chopped test samples were placed in a 1.5 mL tube. Next, 100 μL of sterilized water was added, capped tightly, and processed at 95 °C for 5 min. Finally, centrifugation  was performed, and the supernatant was taken as the test sample. A reagent blank was used as a negative control for each DNA extraction. The concentration and purity of the extracted DNA were quantified using an ultraviolet (UV) spectrophotometer . All DNA samples were stored at −20 °C before use.A duck-derived commercial thermostatic assay kit  was used in this work. Following the instruction guides, the primers were mixed with the solution containing the recombinase, polymerase, and the buffers, following which 2.5 μL of sample DNA was added; the preparation  was then kept at 39 °C for 20 min. The acquisition of fluorescent images was carried out every 30 s.2  and a dichroic mirror. The UHP is capable of emitting high-intensity ultraviolet and blue-violet light, which is sufficient to excite various fluorescent targets. The dichroic mirror could filter the excitation light to ensure that the emitted light can be received for imaging. These components ensure the imaging quality of the commercial microscope. However, with a bulky size, the cost of a commercial microscope is generally no less than several hundred dollars, making them unsuitable for low-cost and portable applications.LEDs have a very narrow band spectrum (20–40 nm), so it is possible to replace UHP as the light source to omit the dichroic mirror. Instead, emission filters could be used to improve the specificity of the optical spectrum. Therefore, we used RGB LED beads as the excitation light source and low-cost filters were fixed on the lens after easy assembly. As shown in To analyze the fluorescent images in 5 copies/μL, 104 copies/μL, 103 copies/μL, 102 copies/μL, 101 copies/μL, and blank control, where amplification curves were observed for concentrations 102 copies/μL and above, indicating that the detection limits of our device and method were 102 copies/μL.We tested the sensitivity of the device and method by detecting serial dilutions of duck-derived DNA. As shown in We extracted DNA samples from duck products purchased from local supermarkets. To ensure the reliability of the experimental results, the experiment was set up with two identically configured experimental groups (test 1 and test 2), a positive control group (positive sample DNA in kit) and a blank control group (ddH2O instead of DNA samples). The blue LED was used as the excitation light for the experiments because the probes in the kit were labeled with carboxy fluorescein . As shown in To make the device more convenient for resource limited situations, we developed an Android application for grayscale analysis of fluorescence intensities. As shown in Published works demonstrate a smartphone-based portable microscope by combining a microscope with a smartphone using the camera on the smartphone ,13,14,15Regarding the on-chip PCR heating system, we chose the contact heating method as we used the MIRA method, which is a thermostatic and rapid amplification method. By calibration, the temperature can be kept constant, and the heating system is simplified. In addition, the background noise in fluorescence mode reduces the sensitivity of fluorescence microscopy to some extent, and this problem can be solved by optimizing the optical path and using an artificial intelligence image processing algorithm. We will make efforts to improve the sensitivity in our future work.Here, we have demonstrated that it is possible to build a portable  microscope with bright-field and fluorescence modes under a USD 100 budget. With a specific design of optical path, the low-cost and portable microscope has a magnification and field-of-view similar to a commercial microscope. With a spatial resolution of 5 μm, the proposed portable microscope shows satisfied performance for fluorescence imaging in many bio-applications such as cell imaging or nuclei acid detections. Here, we analyzed the meat authenticating tests using real time fluorescence nucleic acid detection method. With a channel splitting operation for RGB images obtained from our portable microscopic device, the cost-effective nucleic acid detection system could recognize any changes in fluoresce intensities during the nuclei acid amplification process. In the future, our portable microscopes will be ideal for downstream applications in combination with microfluidic devices, especially in conditions of limited space and resources. Additionally, we can also foresee applications in diagnostics or telemedicine.


In silico computational modeling, drug affinity responsive target stability (DARTS), and fluorescence polarization (FP) assays altogether determined that 323–1 and 323–2 directly target the STAT3 SH2 domain and inhibited both phosphorylated and non-phosphorylated STAT3 dimerization. Computational docking predicted that compound 323s bind to three subpockets of the STAT3 SH2 domain. The 323s inhibition of STAT3 dimerization was more potent than the commercial STAT3 SH2 domain inhibitor S3I-201 in the co-immunoprecipitation assay, correlating with computational docking data. The fluorescence polarization assay further confirmed that the compound 323s target the STAT3 SH2 domain by competitively abrogating the interaction between STAT3 and the SH2-binding peptide GpYLPQTV. Compared with S3I-201, the 323 compounds exhibited stronger inhibition of STAT3 and reduced the level of IL-6-stimulated phosphorylation of STAT3 (Tyr705) in LNCaP cells over the phosphorylation of STAT1 (Tyr701) induced by IFN-ɣ in PC3 cells or the phosphorylation of STAT1 (Ser727) in DU145 cells. Both compounds downregulated STAT3 target genes MCL1 and cyclin D1. Thus, the two compounds are promising lead compounds for the treatment of cancers with hyper-activated STAT3.Our drug discovery model has identified two novel STAT3 SH2 domain inhibitors 323–1 and 323–2 (delavatine A stereoisomers) in a series of experiments.  Junaid etal. found activation of STAT3 in 67% of bone and 77% of lymph node metastases of prostate cancer patients  and integrates with other signaling pathways to activate the androgen receptor (AR) pathway. STAT3 may promote stem-like cells and the epithelial-to-mesenchymal transition (EMT) and interactions between tumor cells and the microenvironment . Liu C. patients . Don-Donpatients . All thepatients  and may STAT3 was originally described in 1993 as a transcription factor in IL-6-stimulated human hepatoma (HepG2) cells . The fulCytokines  or growth factors  bind to their corresponding cell surface receptors . These bThe function of STAT3 relies significantly on its SH2 domain, which promotes STAT3 homo- or hetero-dimerization, protein–protein interactions, and nuclear translocation of the STAT3 dimers needed for transcription. Thus, the STAT3 SH2 domain mediates the phosphorylation and dimerization of STAT3 due to its association between STAT3 monomers and phospho-tyrosine motifs within relevant receptors . Due to [de]isoquinoline skeleton, was first reported from the medicinal plant Incarvillea delavayi, with subsequently completed total synthesis of -delavatine A and its chiral isomer -delavatine A (named as compound 323–1 or 323–2) -delavatine A (named as compound 323–1 or 323–1), a natural product with novel cyclopentar 323–2) . Herein,Cryptotanshinone and IL-6 were purchased from . S3I-201 was bought from Thermo Fisher Scientific .Human prostate cancer cell lines LNCaP and 22Rv1 were purchased from the American Type Culture Collection  and cultured in RPMI 1640 medium with 10% FCS. HEK 293T and DU145 cells (ATCC) were cultured in a DMEM with 10% FCS. EPT3M1-STAT3  were culLNCaP, 22Rv1, and DU145 cells were seeded in 96-well plates for 24 h, followed by treatment with different doses of drugs for 4 days. The alamarBlue assay was performed by adding 10 µL/well alamarBlue cell viability reagent  for 4 h, and the absorbance at 570 nm was thereafter recorded using 600 nm as a reference wavelength by using the BioTek Synergy H1 plate reader . The absorbance data of each group were normalized to the data of the DMSO-treated group to get the relative cell viability. Data were analyzed by Prism software-log (inhibitor) vs. response-variable slope (four parameters) with the formula Y = bottom + (top-bottom)/(1 + 10^((LogIC50-X) *HillSlope)), X: log of dose or concentration, Y: response, decreasing as X increases, top and bottom: plateaus in same units as Y.HEK 293T cells were transiently transfected with the Cignal STAT3 reporter  using lipofectamine 3000 transfection reagent  for 24 h, following treatment with 20 ng/ml IL-6 and the indicated concentrations of 323–1, 323–2, S3I-201, or cryptotanshinone. Luciferase activity was measured by using the Dual-Luciferase assay kit  using a luminescence microplate reader . Values were normalized to Renilla luciferase activity of the DMSO vehicle.Franklin Lakes, New Jersey, US).DU145 cells were seeded in 6-well plates for 24 h, followed by treatment with various drugs for 72 h. Apoptosis assay was conducted by using the CellEvent™ Caspase-3/7 Green Flow Cytometry Assay Kit . After removing the media from the cells, 1 µL of CellEvent™ Caspase-3/7 Green Detection Reagent was added to 1 ml of each cell sample to make a final concentration of 500 nM and incubated at RT for 1 h. At the final 5 min of staining, 1 μL of the 1 mM SYTOX™ AADvanced™ dead cell stain solution was added to the samples to a final concentration of 1 μM. The samples were analyzed by using the BD LSRFortessa™ cell analyzer (g for 10 min at 4°C). Lysates were diluted to the same final volume and proteolyzed in TNC buffer . Then, 200 µM 323–1 or 200 µM 323–2 or the same volume of DMSO was added and incubated for 1 h at room temperature (RT). A measure of 1.25 mg/ml of pronase solution was diluted serially using 1x TNC buffer to generate 1:300, 1:1,000, and 1:3,000 pronase stock aliquots. Pronase was added into both the DMSO and drug groups and incubated for 30 min at RT. Digestion was stopped by adding 4X loading buffer and heating to 90°C for 10 min immediately prior to the Western blot assay, according to publications  containing protease  and phosphatase inhibitors  and centrifuged . Images were captured using the Leica DMRBE microscope or Cytation5 Cell Imaging Multi-Mode Reader.EPT3M1-STAT3 cells (grown on coverslips) were treated with DMSO, 20 µM 323–1 or 323–2, 100 µM S3I-201, or 5 µM cryptotanshinone for 24 h. Cells were fixed with 4% paraformaldehyde, washed with PBS, and permeabilized with cold methanol. Primary and secondary antibodies were described, cat. no. and dilutions , and moDU145 cells were seeded and treated with 5–20 µM 323–1 or 323–2 or 100 µM S3I-201 for 24 h. Nuclear extraction was performed according to the STAT Family Transcription Factor Assay Kit  .The levels of expressions of phosphorylated STAT3 , pSTAT1 , and pSTAT1 (S727) proteins were determined by Western blotting, following the procedures described . The fol6 HEK 293T cells were transfected with 10 µg/10 cm dish FLAG-STAT3 and 10 µg/10 cm dish HA-STAT3 plasmids for 24 h, followed by treatment with 20 µM 323–1 or 323–2 and 100 µM S3I-201 for 4 or 24 h Thereafter, 293T cells were collected in the medium and centrifuged at 800 g × 5 min and then washed with cold PBS twice before adding 500 μL Pierce™ IP lysis buffer , containing protease and phosphatase inhibitor cocktail without DTT  into the cells. Cell lysates were passed several times through a 271⁄2-gauge needle to disrupt the nuclei. Then, 1–2 mg extracts were added with a pre-cleaned 50 µL slurry of Pierce™ DYKDDDDK magnetic agarose , and then, supernatants were collected with magnet and immunoprecipitated (IP) at RT on a rotator for 30 min. Beads were boiled at 95°C for 5 min followed by the addition of 100 μL of 1x non-reducing sample buffer  into beads. The supernatants were collected with a magnet and then added 5 μL of 1M DTT  into samples before proceeding with immunoblotting.For this procedure, 7.5 × 10The computational docking of 323s to three-dimensional crystal structures of STAT3, including the phosphorylated (PDB entry 1BG1) and the non-phosphorylated (PDB entry 3CWG) structure, was utilized by the molecular docking tool Maestro 9.0 Glide, as illustrated previously . The lowdrc. Ki was determined from the resulting IC50 using the Cheng–Prusoff equation and the Kd for fluorochrome-labeled peptide binding to STAT3, Ki = IC50/(([L])/Kd) +1. The assays were performed at the high-throughput chemical biology screening platform  Centre for Molecular Medicine Norway (NCMM), University of Oslo.The FP assay was conducted as described in 6 cells were subcutaneously injected into the right flank. Tumor volume was calculated using the following formula: V = (L × W2)/2, where L is the length and W is the width of the tumor nodules measured with vernier calipers. Once the volume of the tumors reached 75–100 mm3, the mice were randomly divided into three groups (n = 6). The mice were treated daily for 3 weeks with IP injections of either vehicle (olive oil) or 323–2 (20 mg/kg or 40 mg/kg in the vehicle). Body weights and tumor volumes were measured before each drug injection. After the 22nd day, the mice were euthanized, and the tumors were isolated, weighed, and photographed.Four-week-old male BALB/c-nu nude mice (15–20 g) were obtained from the Shanghai BiKai Laboratory Animal Co., Ltd. . The animals were maintained under specific pathogen-free conditions with food and water supplied ad libitum in the Laboratory Animal Center of the Second Military Medical University, Shanghai. All animal experiments were carried out in accordance with the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health and were approved by the Committee on the Ethics of Animal Experiments of the Second Military Medical University, China. LNCaP cells were harvested and resuspended in PBS. A total of 5 × 10p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001.Significance in groups was determined by using one-way ANOVA multiple comparison. *1H NMR, 13C NMR, and chiral HPLC chromatography (see c = 0.05 in CHCl3) and -6.7 (c = 0.05 in CHCl3), respectively -delavatine A (compound 323–1) and -delavatine A (compound 323–2)  were fouaphy see  with opty in the . As showHerein, we sought to determine whether 323–1 and 323–2 were able to suppress STAT3 phosphorylation and activation. First, to confirm the inhibitory effect of 323s on STAT3 activity, luciferase assays were carried out using a STAT3-luciferase reporter vector in 293T cells, following treatment with 323–1, 323–2 or the commercial STAT3 inhibitors S3I-201 and cryptotanshinone in the presence of IL-6 for 24 h . 323–1 aAberrant STAT3 regulates the expression of downstream target genes involved in anti-apoptosis , cell cycle (cyclin D1 and c-Myc), angiogenesis (VEGF and HIF1α), invasion and metastasis , and the inhibition of host immune surveillance . To furtSeveral available STAT3 inhibitors target the DBD or SH2 domains of STAT3 or inhibit activating phosphorylation of Tyr705. Due to the highly conserved region of the SH2 domain, such as in Src, compared with other proteins and the insufficient capability of the available STAT3 SH2 domain inhibitors , the intTo directly address if compounds 323–1 and 323–2 target STAT3, the DARTS assay was used, based on the observation that proteins bound by drugs may be more stable against protease degradation. In Nuclear translocation of the STAT3 dimers mediates STAT3 transcriptional activity. In order to test whether compound 323s are STAT3 dimerization inhibitors, 293T cells were transiently transfected with HA-tagged STAT3 and FLAG-tagged STAT3 expression plasmids, then stimulated with 323s or S3I-201 for 24 h, and next immunoprecipitated with the anti-FLAG antibody to pull down the STAT3-associated proteins, which were finally subjected to Western blot with anti-HA, anti-FLAG, or anti-β-actin antibodies. As exemplified in in silico computational screening assay by docking compounds into the STAT3 SH2 domain, such as S3I-201 (The STAT3 SH2 domain (residues 583–688) contains three sub-pockets: PY, PY+1, and PY + X. The STAT3 SH2 domain facilitates the phosphorylation and dimerization of STAT3 due to its association between STAT3 monomers and phospho-tyrosine motifs within relevant receptors . To date S3I-201 .in silico computational modeling and the fluorescence polarization (FP) assay. Computational docking and molecular dynamics simulation identified potential binding sites for 323–1 and 323–2 in the STAT3 SH2D . The nitrogen of the isoquinoline group in 323–1 forms a hydrogen bond with Glu594, the carbonyl oxygen on the formaldehyde group faces the pY binding pocket and forms a hydrogen bond with Arg609, and Arg609 can form a direct polarity with phosphotyrosine 705. Arg609 can inhibit the binding of SH2 to phosphotyrosine 705. The small-molecule skeleton cyclopenta [de] isoquinoline faces the pY-X binding pocket and interacts hydrophobically with adjacent amino acid residues . Similarly, compound 323–2 forms a bond with PY, PY+1, and PY-X pockets  in the STAT3 SH2 domain (To confirm that 323s bind to STAT3, we used AT3 SH2D . In the 2 domain .de] isoquinoline of 323s associated with the pY-X binding pocket bound by tetrahydro cyclopentane and formed hydrophobic interactions lined by residues Phe588, IIe589, Ser590, and Val637. These data suggest that 323s are STAT3 SH2 domain inhibitors by disrupting STAT3 dimerization and further supporting the results of the DARTS assay.It is reported that non-phosphorylated STAT3 may also form dimers, enter the nucleus from the cytoplasm to bind to DNA, and activate transcription . In dockin silico predictions were further examined by competition binding FP assays, which detected the displacement by drugs of the binding of labeled phosphopeptide, 5-FLU-GpYLPQTV-NH2, to the human recombinant STAT3 protein. The phosphotyrosine peptide GpYLPQTV corresponds to the residues 903–909 within the gp130 subunit of the IL-6 receptor, which has been validated to bind the STAT3-SH2 domain according to the method (The e method . Stratege method .As STAT3 may be recruited to gp130 within phosphotyrosine residues , we utilTaken together, these data confirm that 323–1 and 323–2 are direct STAT3 SH2 inhibitors by disrupting the binding of the STAT3 phosphotyrosine-peptide, corresponding with the computational docking and DARTS assay.via in vitro clonogenic assays, which correspond to tumorigenicity in nude mice (The effect of compounds 323–1 and 323–2 concerning the inhibition of clonogenicity was investigated ude mice . On the in vitro anti-tumor activity by inhibition of cell proliferation, clonogenicity, and apoptosis induction.One of the effects of antitumor drugs is to induce apoptosis in cancer cells. We next evaluated the anti-apoptotic effect of 323s in DU145 cells. Caspases 3 and 7 are regarded as vital modulators of mitochondrial events of apoptosis. As shown in in vivo tumor model. Compound 323s were administrated i.p. daily to validate the effect on tumor growth. The in vivo data supported that 323s significantly inhibited tumor growth by measuring the tumor weight and tumor volume, respectively (As shown in ectively , especiaThe STAT3 SH2 domain is essential for STAT3 dimerization and activity. Strategies to target STAT3 SH2 have been pursued recently by various groups. Several STAT3 inhibitors have been discovered, and some are in clinical trials. STA-21 reportedly exhibited treatment effects against psoriasis and rheumatoid arthritis but remains unclear concerning cancer treatment . LLL12 hWe have shown in this work that two compounds 323–1 and 323–2 were identified as STAT3 SH2 domain inhibitors with better potency than the S3I-201 in terms of drug-target affinity as well as than cryptatanshinone regarding the capability of deactivating STAT3 signaling. Tyr705 phosphorylation, which is vital for STAT3 dimerization and is prevalent in prostate cancer , was demHowever, the short-time 4 h treatment with drugs did not show disruption of STAT3 dimerization in the co-IP assay . One posThe FP assay allows quantitative analysis of molecular interactions based on a single fluorescent label strategy. Fewer proteins and compounds are needed for the experimental steps, and samples might be repetitively measured without being destroyed. These benefits of the FP assay are one important approach in HTS . HoweverAccording to the FP assay, the ligands 323–1 and 323–2 were found to interrupt the binding between GpYLPQTV and STAT3. Notably, both 323–1 and 323–2 exhibited increased polarization at concentrations above 200 µM. These compounds did not appear to be fluorescent at the measured wavelengths, so at high concentrations, some interaction occurs between the drug and fluorophore to decrease the fluorophore’s mobility. This was confirmed by measuring the polarization of peptides in the presence of high concentrations of the drugs and without STAT3. In particular, at concentrations above 200 µM of 323 drugs, GpYLPQTV became significantly polarized in the absence of STAT3. Another reason is due to the autofluorescence of drugs. The 323 drugs have minor emissions at the wavelengths tested for the GpYLPQTV probe. The emission also appears to be polarized, and the polarization increases with an increasing concentration of 323 drugs in the presence of STAT3. This is further evidence for the binding of the drugs to STAT3.via the ubiquitin-proteasome mechanism (323s appear to bind to the STAT3 SH2 domain with favorable affinity and selectivity compared with other STAT3 inhibitors, especially S3I-201. Modification of the 323s structure may be executed to get more analogs and improve potency and selectivity. The small molecule-based PROTAC technology is reported to degrade target proteins selectively with high potency echanism . To achiTaken together, our study identified two STAT3 SH2 domain inhibitors, which also provide diversified biological activities and structural diversity for anti-tumor drug discovery and might be promising in the treatment of cancers with hyper-activated STAT3.


FST between CC and North East Arctic Cod  with increasing latitude, (2) that in the north, samples of CC from outer‐fjord areas were genetically more similar to NEAC than were samples of CC from their corresponding inner‐fjord areas, (3) greater population genetic differentiation among CC sampled from outer‐fjord areas along the coast, than among CC sampled from their corresponding inner‐fjord areas, (4) genetic differentiation among samples of CC from both within and among fjords. Collectively, these results permit us to draw two main conclusions. First, that differences in the relative presence of the genetically highly distinct, migratory ecotype NEAC, declining from north to south and from outer to inner fjord, plays the major role in driving population genetic structure of the Norwegian CC. Second, that there is limited connectivity between CC from different fjords. These results suggest that the current management units implemented for this species in Norway should be divided into smaller entities. Furthermore, the situation where introgression from one ecotype drives population genetic structure of another, as is the case here, may exist in other species and geographical regions, thus creating additional challenges for sustainable fisheries management.Identifying how physical and biotic factors shape genetic connectivity among populations in time and space is essential to our understanding of the evolutionary trajectory as well as the management of marine species. Atlantic cod is a widespread and commercially important marine species displaying several ecotypes with different life history strategies. Using three sets of SNPs: neutral, informative, and genome‐inversion linked, we studied population genetic structure of ~2500 coastal Atlantic cod (CC) from 40 locations along Norway's 2500 km coastline, including nine fjords. We observed: (1) a genetic cline, suggesting a mechanism of isolation by distance, characterized by a declining  In addition, it provides us with essential knowledge which is required to base informed decisions for sustainable management, and where relevant, exploitation      with the Qiagen DNA Blood and Tissue kit, following the manufacturer's instructions. Each 96 well plate contained 2 non template controls. DNA from approximately 10% of the individuals was quantified on a NanoDrop 8000, by Thermo Fisher, and DNA diluted according to block wise average. The 2768 individuals were thereafter genotyped in 386‐well format on a Sequenom MassArray platform (Agena Bioscience), as described in  with 2 principal components plotted . In addition, the Bayesian clustering analysis which were performed in STRUCTURE v.2.3.4  were tested for by the means of both the four statistic methods  and the ad hoc summary statistic ΔK in the Evanno method  against geographic distance.Isolation by distance was tested via Mantel test using Wickham,  plotting33.1Following genotyping quality checks and removal of NEAC, the main data set consisted of 2139 fish genotyped for 148 markers  and paired outer‐fjord (O) sample Figure . Using bes Table . To illuFST between the inner sample and NEAC was 0.033, but only 0.012 between the outer sample and NEAC  along the coast of Norway, including both inner‐outer and north–south gradients, is strongly influenced by introgression from the vastly more abundant and genetically distinct migratory North East Arctic Cod (NEAC) ecotype in the north, and, possibly North Sea Cod (NSC) in the south. We therefore draw two primary conclusions: 1—Introgression of NEAC plays the major role in driving population genetic structure of CC along the long Norwegian coastline, and 2—genetic differentiation among samples of CC from both within and among fjords suggests small‐scale spatial genetic structure. The situation revealed here, that introgression from one genetically distinct ecotype controls population genetic structure of another, may well exist in other species and oceans where ecotypes overlap in time and space. In turn, such complicated scenarios create additional challenges for sustainable management of important fisheries resources.4.1The genomic architecture underpinning differences between highly migratory and more stationary ecotypes of Atlantic cod are primarily restricted to four chromosomal inversions , there is greater potential for physically isolated populations in inner‐fjord areas , and the inner‐fjord habitats are likely to be more divergent . However, when combined with the fact that the outer‐fjord samples were genetically more similar to NEAC than their corresponding inner‐fjord sample, it is clear that as for the north–south gradient already discussed, this pattern of gene‐flow appears to be the major driver of the observed genetic differences among CC populations. South of 62°N, where NEAC does not seem to influence the structure, there are indications that NSC, as described in Jorde et al., Coexisting ecotypes of cod are commonly found in several parts of the species range. For example, in Iceland, two distinct cod ecotypes overlap in time and space, yet differ in their migrating behavior, where one performs deep water feeding migrations , where the Ecotypes and morphotypes are found in a multitude of species. One example of this is the European anchovy (4.2The observed genetic difference between pairs of samples of CC from inner‐ and outer‐fjord areas, and between adjacent inner fjords, especially in the north of Norway, strongly suggests limited genetic connectivity among CC from separate fjords. Although as detailed above, these differences primarily arise through the patterns of interbreeding between NEAC and CC. If there was substantial gene‐flow between CC from inner‐ and outer‐fjord areas, and among fjords, then the geographic pattern of NEAC interbreeding would most likely be eroded or cancelled, as already concluded for the north–south pattern observed in this region (Dahle, Quintela, et al., Small‐scale spatial genetic structure has also been observed among samples of cod from environments other than fjords. For example, a recent study in the Baltic Sea reported sub‐structuring in samples from the West Baltic stock, indicating an isolation by distance pattern, most likely driven by salinity (Wenne et al., 4.3Throughout its natural distribution, many Atlantic cod stocks have declined, with well‐profiled examples of fishery collapses in some regions (Myers et al., None declared.Appendix S1.Click here for additional data file.


Pinus elliottii Engelm var. elliottii) is the primary tree species for resin tapping due to its high resin yield, low resin crystallization rate, and high turpentine content. Current researches focuse on the targeted improvement of several significant components to meet industrial needs rather than just resin yield. The objective of this study was to examine the genetic variation and correlation of genetic and phenotype for four main resin components  of 219 half-sib progenies from 59 families. The results showed that the levopimaric acid had the largest content , while the β pinene content had the largest variation coefficient (CV = 0.42). The α pinene content has the highest heritability (2h = 0.67), while levopimaric acid has the lowest heritability (2h = 0.51). There was a significant negative correlation between α pinene and the other three components and a significant positive correlation between β pinene and the two diterpenes. The family ranking and genetic gain suggested that it is possible to improve the contents of main resin components of slash pine through genetic breeding selection.Pine resin, as a natural material, has been widely used in food, pharmaceutical, and chemical industries. Slash pine ( It is aediators ; and pimPinus palustris Miller was first reported in America , originally from the southeastern United States and widely planted in southern China in the 1930s, is the primary tree species for resin tapping because of its high resin yield, low resin crystallization rate, and high turpentine content  to examine and describe the four resin components of slash pine; (2) to evaluate the narrow-sense inheritance of the four resin components; (4) to determine the genetic and phenotype correlations within the four resin components; (3) to rank the families and select the elite families and individuals by the breeding value of the four resin components; and (5) to obtain the genetic gain of the four resin components at different selection intensities.All 59 half-sib families with 6 replications and 6 individual trees of slash pine were planted in a randomized complete block of a 2 m × 3 m spacing in the Yuhang region in Hangzhou, China , established in March 1994. The specific experimental design has been detailed in Ding .Pine resin samples were collected in July 2021 from individuals whose diameter at breast height was close to the mean value of a family. A special plastic pipe with an aperture of 20 mm and volume of 15 ml was fixed at the drilling hole in the trunk to collect resin from the sunny side . In tota-1 to 80°C, and reached a maximum of 280°C at a rate of 2°C per min for 5 min. The helium gas flow was set at 1 ml min-1. The temperature of the injector was 260°C, and the volume was 1 µL with a 1/50 split ratio. Mass spectra were recorded under electron impact ionization at an electron energy of 70 eV in the range from m/z 30 to 600 along with solvent delay for 3 min.Gas chromatography experiments were carried out with a GC 6890 gas chromatograph coupled with a Hewlett Packard GC 5975B mass spectrometer . The GC-MS operation was performed according to the procedure described by . To obtaResin compositions were identified by matching experimental fragmentation patterns in mass spectra with the NIST08 database through the data processing system of Agilent Chem Station and then comparing with the relevant literature. Monoterpene and sesquiterpene content were determined by isobutylbenzene content, and diterpene content was determined by heptadecanoic acid content. We calculated the resin component content by comparing their peak areas.iy for a tree is shown in Equation (1):Mixed linear model (LMM) with restricted maximum likelihood (REML) analysis was used for the estimation of genetic parameters. The model for a single-trait observation ix is a vector linking the fixed effects m to the observation iy, and ib, if, and ie are the random block, family, and residual effects, respectively. Stacking those vectors for all trees produces model Equation (2):where where y is a vector of total phenotypic observations, m is the vector of fixed effects , and b, f, and e are vectors of bivariate random effects for block, family, and residual effects, respectively. X, Z1, and Z2 are the incidence matrices linking observations to the appropriate effects. We defined the vector of expected values (E) and dispersion matrices (Var) as:andi, respectively; and bibjσ , fifjσ, and eiejσ are the covariances of block, family, and residual between traits i and j.where ⊗ and ⊕ are the direct product and direct sum operations, respectively; 2h):The variance components from the model were used to calculate the narrow sense heritability (rgij ) between trait i and trait j were calculated as:The genetic correlations (rpij ):and phenotypic correlation ( σfij is the estimated family covariance between trait i and trait j and i and trait j.where RG) was computed by subtracting the mean BVs of the selected top ratio trait from its total mean.The breeding value (BV) of each tree is the family random effect value of the LMMs, and the realized genetic gain  of the four resin components were 0.67, 0.57, 0.63, and 0.51, respectively  and phenotypic correlation (pr) analyses of the four resin components of slash pine are shown in gr = -0.67) and phenotypic correlation (pr = -0.89) were found between the two monoterpenes (α pinene and β pinene). The β pinene and abietic acid had the weakest genetic correlation (gr = 0.62) and phenotypic correlation (pr = 0.67). Interestingly, the genetic correlation (gr = 0.67) and phenotypic correlation (pr = 0.84) between the two diterpenes (abietic acid and levoprimaric acid) were stronger than those between monoterpenes and diterpenes.The genetic rg and phenWe ranked the family performance of slash pine by a breeding value (BV) of α pinene, β pinene, abietic acid and levoprimaric acid in The relationship between α pinene, β pinene, abietic acid and levoprimaric acid traits is displayed in The ΔG% (improved percentage of the genetic gain) was calculated with the top 10% to 40% samples from 59 families for each resin component Figure 6The largest average ΔG% was observed in β pinene, where the top 10% to 40% families yielded 42.7%, 39.9%, 37.1, and 35.1%, respectively, followed by α pinene, abietic acid, and levoprimaric acid, with estimated genetic gains ranging from 37.0% to 31.0%, 40.3% to 28.4%, and 11.8% to 9.3%, respectively.In this study, we first assessed the variation and heritability of four relatively important resin components in the slash pine population. The results showed that the content of α pinene is approximately 1.4 times higher than that of β pinene, which was similar to the study conducted by Zhang  and Lai Heritability is an important population parameter that can help understand the genetic architecture of complex traits . In thisUnderstanding the genetic and phenotypic correlation among traits contributes to researchers developing breeding strategies more effectively . The corSassafras tzumu  study of four important slash pine resin components provided the possibility for their joint selection. This method has been successfully applied to the combined selection of slash pine growth and wood traits , as wellas tzumu . In thisGenetic gain can characterize the effect of direct or indirect breeding selection. Stronger genetic selection ratios tend to lead to higher genetic gain , and theResin is an important nontimber secondary forest product. In this study, a total of 219 individuals from 59 slash pine families were used for resin tapping. Then, we used GC-MS to characterize and quantify different resin components. Different from the usual selection of resin yield and mixture of turpentine or rosin in previous studies, we selected four components considered to be more important, including two kinds of turpentine (α pinene and β pinene) and two kinds of resin acids (levopimaric acid and abietic acid). Industrial production often requires some important chemical components rather than the entire resin. To this end, we first analyzed the genetic variation in the contents of the four resin components. The results suggested an abundant variation and a strong genetic control in resin components of slash pine breeding population. The β pinene has the largest variation coefficient, and the α pinene has the highest heritability. Then, correlation analysis revealed a law consistent with the other results found in previous studies on slash pine resin. Moreover, we ranked the families by breeding value and selected 5 families, including 2, 3, 4, 6 and 7, whose BVs were above the mean of all four resin components. Finally, we found that the largest average ΔG% was observed in β pinene, while the lowest was observed in levopimaric acid at all selection intensities. These results help us to gain a deeper understanding of the genetic basis of resin traits of slash pine and facilitate its genetic improvement.The original contributions presented in the study are included in the article/Conceptualization: QL and XD. Data curation: QL and JJ. Formal analysis: XD. Funding acquisition: QL. Investigation: QL, XD, and YZ. Methodology: QL and XD. Project administration: QL. Resources: QL and JJ. Software: XD. Supervision: JJ, QL, YL, and SD. Validation: QL. Visualization: XD. Writing – original draft: XD. Writing – review & editing: QL, YL, SD, and XD. All authors contributed to the article and approved the submitted version.


White blood cell count to mean platelet volume ratio (WMR) is increasingly recognized as a promising biomarker. However, its predictive capability for acute ischemic stroke (AIS) patients is relatively less researched. The primary aim of this study is to explore its prognostic value in AIS patients after reperfusion regarding 3-month poor functional outcome.A total of 549 AIS patients who had undergone vascular reperfusion procedure with complete 3-month follow-up were retrospectively recruited in this study. White blood cell count, mean platelet volume at 24 h of admission were recorded. Stroke severity had been estimated using the National Institutes of Health Stroke Scale (NIHSS) and poor outcome was defined as modified Rankin Scale (mRS) 3–6 at 3 months.p < 0.001). After adjusting potential confounders, WMR was still an independent risk factor for poor prognosis at 3 months  in multivariate logistic regression model. Subgroup analyses further suggested a significant association between WMR and poor outcome in high baseline NIHSS  group. Receiver operating characteristic (ROC) curves analysis was utilized to assess the predictive ability of WMR, indicating a cut-off value of 0.86. A nomogram that includes age, sex, NIHSS on admission, high WMR for predicting 1-year all-cause survival was also developed (C-index = 0.628).AIS patients with poor functional outcome at 3 months displayed higher WMR. A positive correlation between WMR and NIHSS score was found (r = 0.334, WMR is significantly correlated with stroke severity on admission and is proved to be an important prognostic indicator for AIS outcomes, especially in high NIHSS on admission group. Additionally, the developed nomogram that includes high WMR for predicting 1-year survival provides us with an effective visualization tool. Acute ischemic stroke (AIS) is a major type of stroke that can cause high mortality and morbidity . As a cuSystemic inflammation response, in which white blood cell (WBC) plays a vital role, has been proved to be involved in the pathogenesis in ischemic stroke . PreviouMean platelet volume (MPV), which reflects platelet size, can provide information of platelet function and activation . HyperacAs a combination of the two above-mentioned biomarkers, white blood cell count to mean platelet volume ratio (WMR) indicates to be more stable and comprehensive regarding the pathology of AIS . It has In this retrospective study, a total of 549 AIS patients receiving intravenous thrombolysis therapy were consecutively recruited from the First Affiliated Hospital of Wenzhou Medical University from January 2019 to December 2020. The exclusion criteria were set as follows (1): with cancer; (2) with autoimmune diseases; (3) with severe hepatic failure or renal failure; (4) use of steroid or non-steroid anti-inflammatory treatment , 16; (5)We followed up these patients for 3 months and 1 year after AIS onset. After excluding 108 patients with missing data, there remained 441 patients. Finally, a total of 329 patients were eligible for analysis with complete 3-month follow-up. The study was approved by the Ethics Committee of the First Affiliated Hospital of Wenzhou Medical University and was performed in accordance with the Declaration of Helsinki. All patients signed a written informed consent form.Demographic data  and medical history  of patients were obtained from medical records. Serum biomarkers included WBC count, MPV collected at 24 h of admission. WMR was calculated with WBC counts divided by MPV. Stroke severity was measured by NIHSS on admission and 24 h after admission. At 3 months and 1 year after the onset of AIS, the prognoses of patients were assessed using modified Rankin Scale (mRS) through telephone follow-up by two experienced clinicians.The etiology of AIS was classified based on the Trial of Org 10,172 in Acute Stroke Treatment (TOAST) criteria: large artery atherosclerosis (LAA), small artery occlusion (SAO), cardio-embolism (CE), and others , early nWe used SPSS Statistics 26.0.0.0, MedCalc Statistical Software version 18.2.1, GraphPad Prism version 9.0.0 and R version 4.1.3 for plots and statistical analyses. Data were first analyzed for normality of distribution using the Kolmogorov-Smirnov test of normality. Continuous variables with normal distribution were expressed as mean with standard deviation (mean ± SD) while continuous variables with non-normal distribution were expressed as medians and interquartile range . Patients were attributed into high/low WMR groups according to the cut-off value and inter-group differences were compared using Mann-Whitney U test. Participants were then divided into four groups according to WMR quartile . Differences of baseline characteristics across WMR quartile were compared using Kruskal-Wallis test. Categorical variables were presented as frequency and percentages  and differences among groups were compared through chi-squared test or Fisher’s exact test.Case distribution across quartile-based categories of WMR and mRS score at 3 months was presented using density plots. To test the correlation between WMR and NIHSS, we calculated Spearman’s correlation coefficient. To account for differences in low WMR distributions across stroke subtype, and differences in mRS distribution in high and low WMR groups classified using WMR cutoff value, chi-squared test was performed.p-value < 0.1 in model 1. To further explore the potential predictive ability disparity in different subgroups, stratified analysis was undertaken. With WMR median as a node undergoing binary logistic regression, restricted cubic splines with 3 knots  were also plotted to demonstrate the correlation between WMR and AIS outcomes.Univariate and multivariate logistic analyses were utilized to demonstrate the association between WMR and primary outcome. The crude model, model 1, was carried out by univariate analysis. In model 2, we adjusted for covariates with a p-value of less than 0.05 was considered statistically significant.Receiver operating characteristic (ROC) analysis was employed to determine the optimal cutoff value and the ability of WMR to distinguish poor functional outcomes. Multivariable time-to-event analysis was performed using Cox proportional hazards regression models to develop a nomogram using weighted estimators corresponding to each covariate that was found statistically significant in predicting 1-year mortality using multivariate regression model. A p < 0.001), higher proportion of hypertension , higher proportion of atrial fibrillation (AF) , higher WBC count , higher WMR , higher NIHSS on admission , and at 24 h . Those with a good functional outcome were more likely to be male  and the small artery occlusion (SAO) subtype . Furthermore, smoking history , alcohol drinking history  were more prevalent in patients with a good outcome in comparison with those with a poor outcome.A total of 329 AIS patients after intravenous thrombolysis were retrospectively included for analysis in this study, with a median age of 67 years and men accounting for 64.1% (211). The median NIHSS score on admission for all study patients was 6, and median WMR was 0.73. A total of 91 (27.7%) patients had poor functional outcomes at 3 months, 31 patients (9.4%) died during the 1-year follow-up. The clinical characteristics of AIS patients were displayed in As illustrated in p < 0.001). Correlation analysis demonstrated a significant linear trend between WMR and baseline NIHSS . The size of circles represented the relative weighting of mRS score at 3 months. It can be seen in p < 0.001), and proportion of mRS 3-6 in high WMR group was more prominent compared with that in low WMR group (p = 0.007), and proportion of low WMR was reported to be the largest in SAO subtype (85.7%).We plotted a density plot to display patient distribution cross WMR quartile. The intensity of color represented the frequency of cases. It can be observed in p < 0.001) were found significantly associated with primary outcome (mRS 3-6) at 3 months. To determine whether high WMR possessed the ability to independently indicate the prognosis for poor outcome at 3 months, multivariate logistic regression was then performed. In model 2, after adjusting for potential confounders with a p-value < 0.1 in model 1, high WMR remained to have an independent association with poor 3-month function outcome   Table 3.p < 0.001) . Additionally, The area under curve (AUC) was 0.662  and NIHSS on admission ≥ 6  groups , an attenuated association between WMR and poor functional outcomes in patients with lower NIHSS score on admission was identified Table 4.p < 0.001), sex , hypertension , AF , NIHSS on admission  and high WMR  were found to be independent risk factors for 1-year mortality. After including these factors with p < 0.05 into the multivariate logistic regression model, age , NIHSS on admission , and high WMR  still remained significant. By including those, a nomogram was constructed  WMR was significantly higher in patients with poor functional outcomes; (2) There was a linear relationship between WMR and NIHSS on admission, mRS 3-6, and mRS 2-6; (3) After adjusting for potential confounders, high WMR was still significantly correlated with primary outcome; (4) WMR was independently associated with poor functional outcome in older age and high NIHSS score on admission group, and the association was attenuated in patients with lower NIHSS score on admission. (5) WMR could be utilized to predict 1-year survival with a nomogram.Vascular reperfusion as a therapy to restore the blood supply and limit the brain damage plays an important role in the management of AIS. Currently, available types of therapy to realize the purpose of vascular reperfusion in AIS patients mainly include intravenous thrombolysis and endovascular treatment . HoweverThe impact of inflammatory processes in the progression of AIS has been widely recognized . PreviouPlatelets play a role in the formation of atherosclerosis and atherothrombosis, which is a critical process during the pathophysiology of stroke . They noWMR as a composite marker comprised of WBC count and MPV, indicates a promising value for the prognosis of cardiovascular outcomes . The intOur findings of the elevation in WMR might be explained by an increase in the WBC count and an decrease in the MPV in the inflammation process, which can provide indications for the disease development for AIS patients . SensitiHowever, it should be noted that several limitations still exist in our study. First, considering the retrospective and observational nature of this study, it was unable to determine the causality between WMR and poor functional outcomes. Second, the sample size was relatively small. Among the 549 patients who were initially enrolled under the inclusion criteria, 31 (5.6%) patients were excluded for missing baseline data and 77 (14.0) were excluded for the loss of 3 months follow-up. Partly due to the sample size, the ROC curve for the prediction of a 3-month poor outcome using WMR did not reach a high prediction capability , which needs to be further researched with a larger data base. Additionally, this study was monocentric so selection bias might still exist and an external validation of the nomogram could not be conducted.Our study demonstrated that there is a linear correlation between WMR and NIHSS on admission. High WMR is positively related to a poor functional outcome, and possesses a prognostic potential for AIS outcomes. The predictive capability is especially prominent in older and neurologically more severe groups. Furthermore, as an easily obtainable and cost-effective parameter, WMR can also be utilized to predict 1-year mortality.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the First Affiliated Hospital of Wenzhou Medical University. The patients/participants provided their written informed consent to participate in this study.XL and XZ conceptualized this work. XL and XZ supervised the study. YW, YG, MZ, TZ, JH, HX, JH, YC, XH, JX, JZ, SL, TK acquisition of data, YW, YG, MZ performed the statistical analysis and interpreted data. YW, YG, MZ prepared the manuscript. XL, XZ, YW, YG, MZ, TZ, JH, HX, JH, YC, XH, JX, JZ, SL, TK revised the manuscript. All authors approved the protocol.We sincerely thank the participating hospitals, patients, their families and colleagues who have provided valuable suggestions for this study.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.


STAT3) gain-of-function (GOF) mutations cause early-onset immune dysregulation syndrome, characterized by multi-organ autoimmunity and lymphoproliferation. Of them, interstitial lung disease (ILD) usually develops after the involvement of other organs, and the onset time is childhood and beyond rather than infancy. Here, we reported a patient who presented with fatal infancy-onset ILD, finally succumbing to death. Next-generation sequencing identified a novel heterozygous mutation in STAT3 . Functional experiments revealed it was a gain-of-function mutation. Upon interleukin 6 stimulation, this mutation caused a much higher activation of STAT3 than the wild-type control. In addition, the mutation also activated STAT3 under the steady state. The T helper 17 cell level in the patient was significantly higher than that in normal controls, which may contribute to the autoimmune pathology caused by the STAT3P330R mutation. Apart from Janus kinase (JAK) inhibitors, we also provided experimental evidence of a STAT3 selective inhibitor (Stattic) effectively suppressing the activation of mutant STAT3 in vitro. Collectively, our study expanded the clinical spectrum of STAT3 GOF syndrome. STAT3 GOF mutation appears as a new etiology of ILD and should be considered in patients with early-onset ILDs. In addition to JAK inhibitors, the specific STAT3 inhibitor would be an appealing option for the targeted treatment.Signal transducer and activator of transcription 3 ( STAT3 is involved in multiple physiological and developmental processes, including immune cell activation and differentiation (STAT3 cause either loss-of-function or gain-of-function (GOF) and present with different immune-related clinical phenotypes  belongs to the STATs family of transcription factors . In the ntiation . Distincferation , 5. The feration . The onsferation .STAT3 GOF mutation  cells and the presence or absence of regulatory T (Treg) cell abnormality have been reported  using genomic DNA isolated from the whole blood of the patient and his parents. The panel was designed to cover the genes known to cause immune diseases.http://www.rcsb.org/). All heteroatoms were removed, and chain A was kept as a STAT3 wild type (WT) monomer. The STAT3 P330R structure was mutated using the PyMol mutagenesis tool. Hydrophobic surfaces were colored based on a normalized hydrophobicity scale using the Color_h script (https://pymolwiki.org/index.php/Color_h). The electrostatic potential was calculated using the PyMol vacuum electrostatics program.All structure models were visualized using the molecular graphics program PyMol. The STAT3 structure (PDB ID: 6TLC) was obtained from the Research Collaboratory for Structural Bioinformatics Protein Data Bank  simulations were carried out using Gromacs 5.0.7 on the STAT3The patient was hospitalized in the inpatient ward and treated with steroid, hydroxychloroquine and antimicrobial agents. Peripheral blood was collected and peripheral blood mononuclear cells (PBMCs) were isolated by density centrifugation. The cells were resuspended in RPMI 1640 supplemented with penicillin, streptomycin, and L-glutamine along with 10% fetal calf serum. PBMCs were then stimulated for 15 min with 20 ng/ml IL-6 (Peprotech) or not. Following stimulation, cells were immediately fixed with PhosFlow Fix Buffer I (BD Biosciences) for 10 min at 37°C, then permeabilized using BD Phosflow Perm Buffer III (BD Biosciences) following the manufacturer’s instruction. Cells were then stained with anti-STAT3 (pY705) or isotype-matched control antibodies (BD Biosciences) for 1 hour. Samples were collected with FACSCanto II (BD Biosciences) and analyzed with FlowJo Software (TreeStar).STAT3 coding sequence was cloned from cDNA isolated from the whole blood using reverse transcription PCR. The primer pair was forward: 5’-cttggtaccgagctcggatccgccaccATGGCCCAATGGAATCAGCTA-3’; reverse: 5’-gaagggccctctagactcgagCATGGGGGAGGTAGCGCA-3’. The PCR product was then ligated into the pcDNA3.1-3×Flag-C vector between the BamHI and XhoI restriction sites using ClonExpress II One Step Cloning Kit (Vazyme). The mutation was introduced using Mut Express II Fast Mutagenesis Kit V2 (Vazyme) following the manufacturer’s instructions. The mutagenesis primer pair was forward 5’-CCTGCATGCgCATGCATCCTGACCGGCCCCTCGTC-3’; reverse 5’-AGGATGCATGcGCATGCAGGGCTGCCGCTCCACCAC-3’.The human STAT3 plasmid or empty vector. The transfected cells were stimulated with IL-6 (20 ng/mL) for 15, 30, or 60 min. Total STAT3 protein , phospho-STAT3 (Y705)  and GAPDH (Proteintech) were measured by western blot. For dephosphorylation experiments, the transfected HEK293 cells were stimulated with IL-6 (20 ng/mL) for 30min and then harvested at different times  after IL-6 withdrawal.Human embryonic kidney 293 (HEK293) cells (ATCC) were transfected with the WT or mutant STAT3 expression plasmid and a STAT3-responsive firefly luciferase reporter plasmid (Beyotime) and a renilla luciferase reporter plasmid (Beyotime) using Lipofectamine 3000 reagent (Invitrogen) according to the manufacturer’s protocol. Twenty-four hours after the transfection, the cells were not or treated with 20 ng/mL IL-6 for 16 hours. The luciferase activity was measured using the Dual-Glo Luciferase Assay System (Promega).HEK293 cells were transiently co-transfected with indicated PBMCs were stimulated with 50 ng/ml phorbol myristate acetate (PMA) plus 500 ng/ml ionomycin for five hours in the presence of 1 µl/ml GolgiStop (BD Biosciences). The cells were then stained with anti-CD3 (BioLegend) and anti-CD8 (BD Biosciences) monoclonal antibodies for 30 min. Cells were fixed with Fixation and Permeabilization Solution (BD Biosciences) for 30 min at 4°C and permeabilized with Perm/Wash Buffer (BD Biosciences) for 20 min at room temperature. Cells were then stained for 30 min with anti-IL-17A antibody (BioLegend). Samples were collected with FACSCanto II and analyzed with FlowJo Software.For Treg cells, PBMCs were first stained with anti-CD3 antibody (BioLegend), then fixed and permeabilized. Cells were then stained with anti-FOXP3 antibody (BD Biosciences) for 1 hour before washing and acquisition. The T lymphocyte subpopulations were detected with the antibodies against CD3 (BioLegend), CD4 (BioLegend), CD8 (BioLegend), CD45RA (BD Biosciences) and CD27 (BD Biosciences). Cells acquisition was performed using a FACSCanto II flow cytometer, and the data were analyzed using FlowJo software.STAT3 plasmid or empty vector. Forty-eight hours after the transfection, the cells were incubated for 4 hours in the presence of ruxolitinib (Abmole Bioscience), tofacitinib (Abmole Bioscience), stattic (Abmole Bioscience), or dimethyl sulfoxide (Sigma-Aldrich) before being activated with IL-6 (20 ng/mL) or not.HEK293 cells were transfected with the WT or mutant STAT3 GOF germline mutations-related ILDs. All the search terms were Medical Subject Heading terms, including STAT3 terms  and gain of function terms . Additional studies were manually screened from citations of relevant articles. All selected articles were reviewed by abstract or full-text. Review articles, duplicate articles, and meeting abstracts were excluded.The literature search was conducted in the PubMed, Web of Science, and Cochrane Library databases for relevant articles published until January 11, 2022, to identify studies reporting t-test using GraphPad Prism software, and p < 0.05 was considered statistically significant.Results were analyzed with the Student Acinetobacter baumanni, Klebsiella pneumonia, Pseudomonas aeringinosa and Stentophomonas maltophilia, and even twice respiratory failures requiring intubation and mechanical ventilation. Multiple courses of antibiotics have been required since then. He responded to the antibiotics with decreased inflammatory markers over 2-3 weeks, but fever recurred while on broad-spectrum antibiotics. At 6 months old, chest computed tomography suggested interstitial lung disease with diffuse ground-glass opacity  was identified in the patient  ILD patients had mutations in the DBD  in a patient with ILD, leading to increased phosphorylation and transcriptional activity of STAT3 and activated Th17 pathway. Unlike general STAT3 GOF-related ILDs reported before, the case described here was infancy-onset with a fatal presentation. Apart from JAK inhibitors, the STAT3 selective inhibitor also effectively decreased the STAT3 phosphorylation caused by the P330R mutation.In this study, we identified a novel STAT3 GOF syndrome shows diverse clinical phenotypes in terms of the involved organs, predominant clinical manifestation and disease severity, which make the timely and correct diagnosis very challenging. Genetically, about half of the patients with ILD have mutations in the STAT3 DNA-binding domain. However, no exact genotype-phenotype correlation has been defined so far. Clinically, STAT3 GOF mutations cause multiple clinical manifestations appearing sequentially , no additional raw data is available at this time. Data of this project can be accessed after an approval application to the China National Genebank . Please refer to https://db.cngb.org/, or email: CNGBdb@cngb.org for detailed application guidance. The accession code CNP0002801 should be included in the application.According to national legislation/guidelines, specifically the Administrative Regulations of the People’s Republic of China on Human Genetic Resources , and minor(s)’ legal guardian/next of kin, for the publication of any potentially identifiable images or data included in this article.MD and YL (2nd author) performed the experiments and analyzed the data. MD wrote the manuscript. YL (3rd author) and XM screened the relevant literature. HK performed the molecular dynamics simulations guided by XL. WL collected and analyzed the clinical data guided by Y-LL. HM designed and guided the study and revised the manuscript critically. All authors contributed to the article and approved the submitted version.This study was supported in part by the National Key Research and Development Program of China , the Research Fund for Outstanding Youth Scholar of Chongqing Talents (CQYC201905003), and the High-level Medical Reserved Personnel Training Project of Chongqing (2019181) and the Beijing Outstanding Young Scientist Program (BJJWZYJH01201910001001).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.