WRAP53 RNA levels were associated with almost a three‐fold decreased effect of radiotherapy in relation to ipsilateral breast tumor recurrence  compared with high RNA levels [0.33 (0.19–0.55)], with a significant interaction (P = 0.024). In conclusion, low WRAP53 protein is prognostic for local recurrence and breast cancer‐related death. Low WRAP53 RNA is a potential marker for radioresistance.Downregulation of the DNA repair protein WD40‐encoding RNA antisense to p53 (WRAP53) has been associated with radiotherapy resistance and reduced cancer survival. The aim of this study was to evaluate WRAP53 protein and RNA levels as prognostic and predictive markers in the SweBCG91RT trial, in which breast cancer patients were randomized for postoperative radiotherapy. Using tissue microarray and microarray‐based gene expression, 965 and 759 tumors were assessed for WRAP53 protein and RNA levels, respectively. Correlation with local recurrence and breast cancer‐related death was assessed for prognosis, and the interaction between WRAP53 and radiotherapy in relation to local recurrence was assessed for radioresistance prediction. Tumors with low WRAP53 protein levels had a higher subhazard ratio (SHR) for local recurrence [1.76 (95% CI 1.10–2.79)] and breast cancer‐related death [1.55 (1.02–2.38)]. Low  WRAP53 RNA indicated less effect of radiotherapy.We have studied the levels of WRAP53, a DNA repair protein, in 965 breast tumors and correlated this with the prognosis and effect of radiotherapy treatment. Tumors with low levels of WRAP53 had a higher risk for locally recurrent cancer and death from breast cancer. Low levels of  BCDbreast cancer deathCIconfidence intervalERestrogen receptorGSEAgene set enrichment analysisHER2human epidermal growth factor receptor 2IBTRipsilateral breast tumor recurrenceNESnormalized enrichment scorePgRprogesterone receptorRefreferenceRTradiotherapySDstandard deviationSHRsubhazard ratioTMAtissue microarrayWRAP53WD40‐encoding RNA antisense to p531Breast cancer is the most common malignancy in women worldwide  and treaWRAP53 gene also gives rise to another transcript, WRAP53α, which is antisense to p53 mRNA that increases the levels of p53 in response to DNA damage [A potential biomarker of radiotherapy resistance is the protein WRAP53 . WRAP53 is a scaffold protein engaged in the repair of double‐strand DNA breaks , 5, 6, tA damage . IncreasA damage , ovarianA damage , rectal A damage , esophagA damage , as wellA damage . It has A damage .Low levels, in contrast to high levels, of nuclear WRAP53 protein have been associated with impaired survival in both breast  and ovarWRAP53 RNA expression in SweBCG91RT. In this trial, early‐stage breast cancer patients were randomized to postoperative radiotherapy or not, after breast‐conserving surgery. As few patients have received any other adjuvant therapy it allows for analysis of prognostic and predictive value from radiotherapy alone [The aim of the current study was to evaluate the prognostic and predictive roles of WRAP53 protein levels and py alone , 18, 19.py alone , 15, 20 py alone . The hyp22.1n = 1004; IBTR n = 141) was constructed later [in situ hybridization was used. Cancer subtypes were assigned according to the guidelines of the St Gallen International Breast Cancer conference (2013) Expert Panel [The study design of SweBCG91RT has been previously described , as welled later . Represert Panel , but as rt Panel . Brieflyrt Panel . Tumors rt Panel , 22. For2.2th percentile as possible was used [th percentile for C1‐antibody and the 28th percentile for C2‐antibody. Separation at the 25th percentile was also employed for dichotomizing WRAP53 RNA levels when needed.Tissue microarray sections were stained with two primary WRAP53 antibodies , 24 targwas used , hypothe2.3stata . r  was employed for RNA expression processing and analysis. Spearman's rank correlation was used to test the correlation between WRAP53 histoscores (0–12) using the two antibodies. Levels of WRAP53 protein and WRAP53 RNA were correlated with clinicopathological variables using the Pearson's chi‐squared test, Fisher's exact test, independent‐sample t‐test, and Wilcoxon rank‐sum test where appropriate. Competing‐risk regression according to the method of Fine and Gray [WRAP53 RNA expression, as well as radiotherapy, adjuvant therapy, subtype, histologic grade, age, and tumor size. In multivariable analysis, all significant variables, tumor size, and subtype were kept. The multivariable IBTR analysis included WRAP53, radiotherapy, adjuvant therapy, subtype, histologic grade, tumor size, and age. BCD analysis included WRAP53, subtype, histologic grade, and tumor size. Subhazard ratios (SHRs) and 95% confidence intervals (95% CIs) are presented. To test WRAP53 as a marker predictive of radiotherapy, efficacy interaction terms between WRAP53 levels (protein and RNA) and radiotherapy were introduced in the IBTR analyses. The proportional hazard assumption was tested using time interaction with all covariates. It was violated for WRAP53 RNA expression in IBTR and BCD analysis. The SHRs presented for WRAP53 RNA expression must thus be interpreted as mean effects over the entire period. Cumulative incidence functions with competing risks were created with the user‐written command stcompet.ado [P‐values were adjusted using the Benjamini–Hochberg method. Pathway enrichment analyses were performed using GSEA. Data were queried against the Hallmarks database (v 5.2) [t‐test was selected as metric. All other parameters were kept at default settings. The pathway significance cutoff was set to FDR < 0.25. In all analyses, a P‐value < 0.05 was considered significant.Statistical analysis was mainly performed using and Gray  was perfmpet.ado . Differempet.ado  were emp (v 5.2) , permuta33.1P < 0.001; Fig. WRAP53 RNA and 569 having high RNA levels. Scoring concordance and discrepancies are presented in Table WRAP53 RNA expression . Radiotherapy greatly reduced the incidence of IBTR in tumors with high WRAP53 RNA expression . The results are also illustrated in Fig. P = 0.35). Radiotherapy efficiently reduced the incidence of IBTR in both patients with high levels of WRAP53 protein using C1‐antibody . Our results indicate that low levels of WRAP53 RNA are predictive of radiotherapy resistance.Further, the evaluation of WRAP53 as a marker predictive of radiotherapy efficacy was performed. There was a significant interaction between RNA expression of WRAP53 and radiotherapy efficacy P = 0.04. Radiot3.5U test, comparing the difference in WRAP53 protein levels between recurrence and primary tumor depending on radiotherapy treatment, there was a weak tendency towards local recurrences having lower WRAP53 levels after radiotherapy than if untreated, but little evidence was found  based on C1‐antibody, 10 tumors (42%) showed reduced protein levels in the recurrence after radiotherapy compared with the primary tumor, seven (29%) did not change and seven (29%) had higher WRAP53 levels in the recurrence after radiotherapy. In the nontreated group, the corresponding numbers were 19 (29%), 25 (38%), and 22 (33%). In the Mann–Whitney 3.6WRAP53 gene itself did not correlate well (Spearman's ρ > 0.5) with any other gene. A list of the top 20 genes correlated with WRAP53 is presented in Table Differential expression analysis was performed to investigate the cellular processes that could contribute to the impaired prognosis and radiotherapy resistance in tumors with low protein levels of WRAP53. The analysis showed that 8100 genes were differentially expressed between tumors with low and high WRAP53 protein levels (C1). Of these, 5166 genes were enriched in tumors with high WRAP53  and 2934 in tumors with low WRAP53 . GSEA showed that networks enriched in tumors with low WRAP53 related to the p53 pathway, DNA repair pathway, and apoptosis pathway among others  and biological variations such as post‐translational regulation or the rate of degradation of RNA and protein could increase discrepancy. Additionally, both methods could be affected by slightly differing specificity in binding to their corresponding protein and mRNA. Some of the probes in the GeneChip bind to WRAP53α‐ and WRAP53γ‐transcripts, as well as to the transcript of interest, WRAP53β. However, the α‐ and γ‐transcripts contribute to a very small portion of the total RNA amount. For these reasons, it would be interesting to quantify WRAP53 protein using mass‐spectrometry and correlate with RNA levels and immunohistochemical staining, using different antibodies.The diverging results between the three WRAP53 expression evaluation methods  in regards of prognostic and radiotherapy efficacy predictive abilities indicate that this is a complex subject that calls for further research. The discrepancy is reflected in the weak (or nonexisting) correlation between the results from the different measurements. For the two antibodies, it is likely caused by variation in antibody specificity. C1 and C2 bind to separate sections of the protein and thus potentially different isoforms of the protein. These isoforms could be differently affected by cellular processes, which could contribute to the discrepancy in staining patterns and correlation to outcome. Other contributing factors could be intratumoral heterogeneity and slightly different sections of the tumor being used in the two cores for each antibody and for the two antibodies. Evaluating both cores from each tumor together, rather than separately and choosing the one with the highest fraction of stained tumor cells, would have decreased the effect of a potential intratumoral heterogeneity. However, the correlation of histoscores for the tumor pairs was strong and intratumoral heterogeneity is not considered to have a large impact on the results. As for the discrepancy between protein and RNA levels, the two diagnostics methods differ fundamentally. In gene expression analysis, serial whole sections from formalin‐fixed paraffin‐embedded material are analyzed, incorporating also the In the gene set enrichment analysis, DNA damage response‐related gene pathways, among others, were enriched in tumors with low WRAP53 protein levels. This is in line with the hypothesis that as the tumor progresses, the DNA damage response is activated. Loss of WRAP53 in this situation allows the escape of damaged cancer cells and the formation of even more malignant clones. A tumor cell would likely not be advantaged by complete loss of DNA damage response since that would generate such a large amount of mutations and DNA breaks that the cell was unable to function. However, some reduction in DNA repair function is favorable as this promotes the gain of new oncogenic or loss of tumor suppressor genes. The majority of the differently expressed genes were enriched in tumors with high WRAP53, but this did not correspond to any pathways. This lack of enriched pathways can be due to a large heterogeneity among tumors with high WRAP53 levels.5WRAP53 RNA were associated with resistance to radiotherapy. More knowledge about WRAP53 and radiotherapy efficacy is needed, as well as further studies investigating the relationship between nuclear protein and RNA expression of WRAP53.We have shown that immunohistochemical assessment of WRAP53 protein using C1‐antibody is prognostic in early‐stage breast cancer, as low nuclear levels were associated with a higher incidence of locally recurrent cancer and death from breast cancer. Low levels of ME and EN involved in all parts. GP and LT involved in the acquisition and interpretation of TMA data. TDM involved in the analysis and interpretation of gene expression data. P‐OB, AST, EH, PK, MF, and FK involved in the design of study and interpretation of data. All authors involved in writing and drafting the manuscript and the approval of the final version.Erik Holmberg and Per Karlsson have research contracts with PFS genomics and Prelude DX and patents pending, not related to the current study.https://www.webofscience.com/api/gateway/wos/peer‐review/10.1002/1878‐0261.13426.The peer review history for this article is available at Fig. S1. Scatter plot with jitter of the nuclear staining results from the two antibodies.Fig. S2. Violin plot of expression of WRAP53 RNA levels in relation to nuclear WRAP53 protein.Fig. S3. Cumulative incidence functions of time to breast cancer death in 15 years depending on WRAP53 levels (C1‐ and C2‐antibody) and WRAP53 RNA expression.Fig. S4. Scatter plot over gene pathways  enriched in tumors depending on WRAP53 protein levels (low and high) according to C1‐ and C2‐antibody.Table S1. Concordance of WRAP53 levels using C1‐antibody, C2‐antibody, and WRAP53 RNA.Table S2. Patient and tumor characteristics in relation to nuclear WRAP53 protein levels (C2‐antibody) and WRAP53 RNA levels.Table S3. Univariable competing‐risk regression depending on nuclear WRAP53 (C1‐ and C2‐antibody) and RNA levels for IBTR within 10 years and BCD within 15 years.Table S4. Absolute events in IBTR‐ and BCD‐competing‐risk analysis stratified by WRAP53 levels presented as total number .Table S5. Multivariable competing‐risk regression depending on three levels of nuclear WRAP53 (C1‐ and C2‐antibody) for IBTR within 10 years and BCD within 15 years.Table S6. Top 20 genes significantly correlating with WRAP53 RNA expression.Click here for additional data file.


In chemistry-related disciplines, a vast repository of molecular structural data has been documented in scientific publications but remains inaccessible to computational analyses owing to its non-machine-readable format. Optical chemical structure recognition (OCSR) addresses this gap by converting images of chemical molecular structures into a format accessible to computers and convenient for storage, paving the way for further analyses and studies on chemical information. A pivotal initial step in OCSR is automating the noise-free extraction of molecular descriptions from literature. Despite efforts utilising rule-based and deep learning approaches for the extraction process, the accuracy achieved to date is unsatisfactory. To address this issue, we introduce a deep learning model named YoDe-Segmentation in this study, engineered for the automated retrieval of molecular structures from scientific documents. This model operates via a three-stage process encompassing detection, mask generation, and calculation. Initially, it identifies and isolates molecular structures during the detection phase. Subsequently, mask maps are created based on these isolated structures in the mask generation stage. In the final calculation stage, refined and separated mask maps are combined with the isolated molecular structure images, resulting in the acquisition of pure molecular structures. Our model underwent rigorous testing using texts from multiple chemistry-centric journals, with the outcomes subjected to manual validation. The results revealed the superior performance of YoDe-Segmentation compared to alternative algorithms, documenting an average extraction efficiency of 97.62%. This outcome not only highlights the robustness and reliability of the model but also suggests its applicability on a broad scale. A significant amount of molecular structure data is embedded within chemistry-centric literature. However, this valuable information remains largely untapped owing to inadequate curatorial practices and the absence of comprehensive open-access repositories . FurtherThe field of OCSR has witnessed substantial evolution over the past decades, with a growing emphasis on harnessing deep learning. These methodologies can effectively identify atoms and bonds in pristine chemical molecular structure illustrations, enabling the reconstruction of chemical molecular structures or their direct transmutation into encoding formats like SMILES or DeepSMILES –11. HoweRecently, studies focusing on deriving complete, noise-free molecular structure descriptions from texts or 2D images have been classified into two primary categories. The first employs rule-based techniques, targeting the extraction of molecular descriptors from 2D visuals, whereas the latter is anchored in deep learning to extract molecular structures. Herein, we present an overview of the molecular structure segmentation algorithms that have gained prominence in contemporary research. The second phase in the optical structure recognition application (OSRA) involves segmenting molecular structures. This segmentation process determines molecular structures based on the dimensions of the rectangular bounding box surrounding the pertinent region, combined with the ratio of black to white pixels within this box . AnotherIn a 2019 study, Staker et al. introduced a deep-learning-oriented OCSR tool , harnessMolecules, Phytochemistry, and Journal of Natural Products) to evaluate the efficacy of their model. Their analysis showed that, on average, ~ 11.2% of the segmented molecular structures contained noise, predominantly originating from non-chemical structures.In 2021, Rajan et al. presented a deep-learning-centric OCSR tool named DECIMER, encompassing a molecular structure segmentation module called DECIMER Segmentation . The fouIn this study, we introduce a refined method for the automated, noise-free extraction of molecular structures, termed YoDe-Segmentation. This process is segmented into three primary phases. Initially, the molecular structure detection phase employs the YOLOv5 network model, specifically modified with a tailored prediction frame, to identify and subsequently crop molecular structures found within academic literature. The subsequent phase, referred to as the mask stage, utilises the DeepLabv3 network model to process these cropped molecular structure images, yielding a corresponding mask map of the molecular structure. The final phase encompasses denoising and differentiating the mask. Here, the molecular structure mask procured via the DeepLabv3 network model undergoes further refinement via an enhanced seed algorithm. This procedure results in the acquisition of a pristine molecular structure descriptor  relative to the pixels in the largest mask within the frame (plargest mask). Mathematically, the equation is:To navigate the residual noise and concurrently address the challenge posed by prediction frames featuring multiple masks, we introduced a metric termed the pixel ratio (PR). This metric encapsulates the proportion of pixels in a given mask .To empirically ascertain the value of PRT, assessments were performed on 70 masks, each containing multiple molecular structures, along with 70 masks characterised by noise. An analysis of the PR for each of these revealed that genuine molecular structures had PR values ranging from 0.55 to 1. By contrast, the noise masks were situated between 0 and 0.2. Informed by these findings, we designated the PRT as 0.5. Consequently, masks that exhibited a PR surpassing 0.5 were classified as genuine molecular structure masks, as exemplified in Fig. Molecules, Phytochemistry, and Journal of Natural Products, our strategy sought to augment both the diversity and volume of the validation dataset. We included articles from an additional journal—Journal of Medicinal Chemistry—and escalated the article tally to 100 for each journal, culminating in an aggregate of 400 articles. These articles were then distributed across four subsets for a meticulous evaluation, with each subset embracing 100 articles, evenly distributed with 25 from each journal, including a contingent derived from the DECIMER Segmentation’s assembly.To evaluate the efficiency of the YoDe-Segmentation process, we conducted an evaluation deploying a methodology akin to that utilised in DECIMER Segmentation assessments. While DECIMER Segmentation typically encompasses the random selection of 25 articles from journals like Subsequently, we transformed these 400 articles into 4549 PNG images utilising the Python Office package, resulting in groups with distinct image counts: 1229 in Group 1, 1059 in Group 2, 1089 in Group 3, and 1172 in Group 4. Manual scrutiny revealed the presence of 9140 molecular structures dispersed across the groups, with 2724 in Group 1, 2009 in Group 2, 2303 in Group 3, and 2104 in Group 4. The ensuing phase involved quantifying the totality of accurately extricated molecular structures through YoDe-Segmentation and determining the extraction efficacy for each group.Journal of Medicinal Chemistry, 3 in Journal of Natural Products, 2 in Phytochemistry, and 1 in Molecules). Transitioning to the mask acquisition phase, we harnessed the capabilities of the DeepLabv3 model to craft masks corresponding to the molecular structures and fabricate an associated mask map. Despite encountering minimal noise or the simultaneous depiction of multiple molecular structures within a single mask image, the process continued to the denoising and segregating phases. Herein, we implemented an enhanced seed algorithm for the segregation and purification of the mask image, ultimately yielding a depiction devoid of noise. The culmination of this stage manifested in the procurement of a pristine molecular structure representation through meticulous image processing of the cropped molecular structure image.During the inaugural phase, which primarily focused on the detection of molecular structures, YoDe-Segmentation demonstrated a remarkable precision of 99.92%, identifying 9133 molecular structures and falling short by a mere seven structures distributed unevenly across the journals (1 in YoDe-Segmentation supported the extraction of 97.62% molecular structures, with group-specific extraction rates of 97.17% for Group 1, 97.76% for Group 2, 97.65% for Group 3, and 98.05% for Group 4. A comprehensive breakdown of the performance metrics specific to each journal within the individual groups is shown in Fig. Journal of Natural Products, Phytochemistry, and Molecules despite the absence of training on articles from these specific journals. The average accuracy rate achieved by YoDe-Segmentation across these journals was 97.56%. Dissecting this further, the Journal of Natural Products registered an accuracy of 97.71%, Molecules of 96.95%, and Phytochemistry of 98.37%. When compared with the extraction metrics of DECIMER Segmentation, a discernible distinction emerges. The average extraction rate for DECIMER Segmentation across the three journals was 91.3%, with individual rates of 92.7% for the Journal of Natural Products, 92.8% for Molecules, and 86.3% for Phytochemistry (Fig. According to the evaluation results, YoDe-Segmentation performed excellently on articles sourced from the try Fig. .Fig. 12CDelving deeper into the molecular structure detection phase, YoDe-Segmentation showed a minor oversight, failing to detect 0.08% of molecular structures. As we transition to the segmentation and extraction processes, ~ 2.3% of molecular structures exhibited discrepancies, either manifesting as incomplete extractions or being interspersed with noise. A closer examination revealed that a predominant fraction of these discrepancies stemmed from incomplete extraction, with only 0.1% of the images being plagued with noise. An analytical deep dive of the undetected or fragmentarily extracted molecular structures unveiled certain trends: the majority of the overlooked structures were diminutive molecules. Simultaneously, incomplete extractions were primarily evident in the peripheral regions of molecular structures. Two recurring attributes surfaced in these aberrant images—a diminished resolution and the sporadic presence of coloured pixels within segments of the molecular structure, as shown in Fig. Journal of Medicinal Chemistry to train the tool, it also proved effective in handling articles from other journals. Impressively, it identified and extracted ~ 98% of the molecular structures present in our wide range of test documents, demonstrating both reliability and versatility.In this study, we introduced YoDe-Segmentation, a new tool for extracting detailed molecular structures from scientific papers. Although we only used articles from the However, the tool encountered challenges with certain types of images, particularly with the somewhat blurry images and those that lacked detail or contained coloured parts in the structures. These difficulties arose owing to the limited examples of such images in the training data. We are confident that adding our training data to include more of these types of images will enable YoDe-Segmentation to recognise and extract molecular structures from a wider variety of images.In future studies, we will enrich our database with a greater variety of molecular structure images, including those with lower resolutions and coloured components. This enhancement will improve the performance of YoDe-Segmentation, ensuring its ability to extract high-quality molecular structure data reliably. This step is crucial for the next phase of our study, where we plan to develop methods for automatically translating these structures into specialised chemical notation systems like SMILES, SELFIES , and Dee


In anesthetized male rats, we investigated how the blockade of α2- and D2-receptors by atipamezole and raclopride, respectively, modified the firing of noradrenergic neurons in the locus coeruleus (LC) and dopaminergic neurons in the ventral tegmental area (VTA). In freely moving rats, we studied how atipamezole and raclopride modified extracellular noradrenaline, dopamine, and DOPAC levels in the medial prefrontal cortex (mPFC) through microdialysis. When administered alone, atipamezole activated LC noradrenaline but not VTA dopamine cell firing. Combined with raclopride, atipamezole activated dopamine cell firing above the level produced by raclopride. Atipamezole increased extracellular dopamine to the same level, whether administered alone or combined with raclopride. In the presence of the noradrenaline transporter (NET) inhibitor, atipamezole combined with raclopride increased extracellular dopamine beyond the level produced by either compound administered alone. The results suggest that a) the D2-autoreceptor blockade is required for LC noradrenaline to activate VTA cell firing; b) the level of dopamine released from dopaminergic terminals is determined by NET; c) the elevation of extracellular dopamine levels in the mPFC is the resultant of dopamine uptake and release from noradrenergic terminals, independent of dopaminergic cell firing and release; and d) LC noradrenergic neurons are an important target for treatments to improve the prefrontal deficit of dopamine in neuropsychiatric pathologies.Experimental and clinical evidence indicates a deficit of release and function of dopamine in schizophrenia and suggests that α Atipamezole hydrochloride  was administered at 3 mg/kg i.p. or up to 0.5 mg/kg i.v. for microdialysis or electrophysiological experiments, respectively.S(−)-raclopride (+)-tartrate salt  was administered at 0.5 mg/kg i.p. or up to 0.025 mg/kg i.v. for microdialysis or electrophysiological experiments, respectively. Prazosin  was administered at 1 mg/kg i.v. for electrophysiological experiments. Nisoxetine hydrochloride  was administered at 3 mg/kg i.p. for microdialysis experiments.The rats were anesthetized with chloral hydrate , and their femoral vein was cannulated for the i.v. administration of pharmacological agents. The rats were placed in a stereotaxic frame  with their body temperature maintained at 37°C ± 1°C using a heating pad. According to the stereotaxic rat brain atlas by Paxinos and Watson (2007) , the recThe baseline spontaneous firing rate was recorded for 3–5 min; the drugs were administered at 120 s intervals.4, 4.25 g chloral hydrate, 42.8 mL propylene glycol, and 11.5 mL 90% ethanol in 100 mL; 5 mL/kg, i.p.) and stereotaxically implanted with vertical microdialysis probes  in the mPFC , according to Paxinos and Watson  was pumped using a CMA/100 microinjection pump  through the dialysis probes at a constant rate of 1.1 μL/min in freely moving animals. Dialysate samples were collected every 20 min and immediately injected using HPLC. Drugs were administered after stable extracellular levels were obtained, i.e., three consecutive samples with a variance not exceeding 15%. Noradrenaline, dopamine, and DOPAC were simultaneously analyzed using HPLC with electrochemical detection using HPLC systems equipped with 3.0 × 150 mm C18 (3.5 µ) Symmetry columns , maintained at 40°C using Series 1100 thermostats  and ESA Coulochem II detectors . The mobile phase was 80 mM Na2HPO4, 0.27 mM EDTA, 0.6 mM sodium octyl sulfate, 7% methanol, and 4% acetonitrile, adjusted to pH 2.4 with H3PO4, delivered at 0.3 mL/min; the Coulochem analytical cell first electrode was set at +200 mV and the second was set at −200 mV. Quantification was performed by recording the second electrode signal. Under these conditions, the noradrenaline and dopamine detection limit  was 0.3 pg per injection on the column. On the completion of testing, the rats were euthanized by an Equithesin overdose; their brains were removed and sectioned using a cryostat (Leica CM3050 S) into 40-µm-thick coronal slices to verify the locations of dialysis probes.The rats were deeply anaesthetized with Equithesin . Data were analyzed by one-way or two-way repeated measures (RM) ANOVA. The n = 7) produced a dose-dependent increase in the firing rate of LC noradrenergic neurons (p = 0.035).The intravenous administration of atipamezole  nor the bursting activity  = 1.43; p = 0.27; fig. 2B) of dopamine neurons in VTA (n = 6–7).On the other hand, atipamezole at the same cumulative dose modified neither the firing rate  = 1.242; n = 10) produced an additional increase in the firing rate  = 23.64; p <0.0001; p = 0.043; p = 0.042; bursting activity: F = 4.09; p = 0.035; n = 4) reversed the activation produced by the combined administration of atipamezole and raclopride  failed to modify the atipamezole-induced activity of LC noradrenergic cell firing .n = 7), raclopride , and their combination (n = 4) was analyzed by microdialysis in mPFC in freely moving rats , while raclopride failed to modify the extracellular dopamine level  = 1.533; p = 0.293). The combined administration of atipamezole and raclopride increased extracellular noradrenaline to the same level  = 8.277; p = 0.028) as that elicited by atipamezole alone. Two-way RM ANOVA evidenced a significant treatment effect  = 6.93; p = 0.010). The effect of raclopride was significantly different from that of atipamezole at time points from T80 to T160 min and from that of atipamezole plus raclopride at time points from T80 to T140 min; no difference was found between the effects of atipamezole alone and atipamezole combined with raclopride (Šídák’s multiple comparison post hoc test).Atipamezole increased the extracellular noradrenaline levels to a maximum of 240% of the basal values  = 10.99; p = 0.001) as well as combined with raclopride  = 12.49; p = 0.011), while raclopride alone was ineffective  = 0.9247; p = 0.425).The effect of atipamezole, raclopride, and their combination on extracellular dopamine reproduced those on extracellular noradrenaline. Thus, atipamezole increased extracellular dopamine to the same level (250% of the baseline) when administered alone  = 10.60; p = 0.027). The effect of raclopride was significantly different from that of atipamezole at time points T80, T100, T120, and T160 min and from that of atipamezole plus raclopride at time point T100 min; no difference was found between the effects of atipamezole alone or in association with raclopride (Šídák’s multiple comparison post hoc test).Two-way repeated measures ANOVA evidenced a significant treatment effect  = 4.95; p = 0.010; raclopride: F = 12.54, p = 0.026; and atipamezole + raclopride: F = 10.62 , p = 0.030). Two-way repeated measures ANOVA indicated a significant effect of the treatment  = 4.37; p = 0.037), but no difference was found by Šídák’s post hoc test.Extracellular DOPAC levels were increased to 160, 240, and 280% of the basal values by atipamezole, raclopride, and their association, respectively  = 8.723, To verify whether the uptake into the noradrenergic terminal limited the elevation of extracellular dopamine elicited by the combination of atipamezole and raclopride, the effect of atipamezole alone and combined with raclopride was analyzed after the blockade of the noradrenergic transporter (NET) with nisoxetine .n = 6) increased the extracellular dopamine level to 330% of the baseline  = 14.99; p = 0.002). Raclopride coadministered with nisoxetine (n = 6) increased the extracellular dopamine level to 410%  = 17.04; p = 0.0002) and with atipamezole (n = 5) to 530% of the baseline  = 11.61; p = 0.014).n = 11) increased the extracellular dopamine level to more than ten times the baseline. Two-way repeated measures ANOVA evidenced a significant effect of the treatment  = 6.50; p = 0.002), due to the difference between nisoxetine + atipamezole + raclopride co-administration with respect to the other treatments, as no difference was found between nisoxetine alone and nisoxetine–raclopride or nisoxetine–atipamezole combination (Šídák’s multiple comparison post hoc test).Crucially, in the presence of NET blockade, the combination of atipamezole and raclopride . Changes in extracellular DOPAC were correlated with the electrical activity of dopamine neurons, which is in line with the notion that DOPAC represents the intracellular oxidation of dopamine presynaptically recaptured by DAT other than the oxidation of newly synthetized dopamine (A major outcome of this study was that the activation of dopamine cell firing by the combined αdopamine .On the other hand, in contrast to what could be expected from the electrical activity of dopamine neurons, atipamezole produced the same increase in extracellular dopamine levels, whether administered alone or in combination with raclopride. Burst activation of dopamine neurons by electrical stimulation of VTA has been shown to produce a long lasting availability of released dopamine in cortical  and subcIndeed, the rise in extracellular dopamine after NET blockade should represent the amount of dopamine taken up by noradrenergic terminals from the extracellular space and, indirectly, of the amount of dopamine released from dopaminergic terminals and co-released with noradrenaline from noradrenergic terminals.1-receptor overstimulation (The elevation of the dopamine level demonstrates that the uptake into noradrenergic terminals plays a major role in terminating dopamine action, limiting excessive dopamine concentrations in the extracellular fluid and preventing the negative consequences of Dmulation . Mostly,mulation .2 but not α2 receptors, similar to raclopride, stimulated dopamine cell firing but did not increase the extracellular dopamine level (2 and α2 receptors, increased both dopamine cell firing and extracellular dopamine, similar to raclopride/atipamezole in this study. Anesthetics can affect the firing properties of dopamine neurons, meant as quantitative rather than qualitative changes. Yet, dosage adjustments for pharmacological studies are generally producing comparable effects under different anesthesia conditions (Due to the systemic administration of the drugs, an action at the nerve terminal level by atipamezole and raclopride is not excluded; this possibility is not alternative but complementary to an action at the cell level . A limitne level . Conversnditions .2- and D2-receptor activates VTA cell firing and increases dopamine release in mPFC. However, dopamine release from dopamine terminals cannot be monitored by microdialysis because dopamine that escapes the synapse is taken up from extracellular fluid into noradrenergic nerve terminals. By contrast, the elevation of extracellular dopamine produced by atipamezole alone or in combination with raclopride, originates from noradrenergic terminals, independent of the firing of dopamine neurons and the amount of dopamine taken up by noradrenergic terminals.In conclusion, our results demonstrate that the combined blockade αMounting evidence indicates that mesolimbic dopamine neurons release dopamine in the nucleus accumbens and other striatal regions in a phasic and tonic mode to control cognitive and motivational functions, respectively . Accordi


Enterocytozoon hepatopenaei (EHP) is a microsporidian parasite that infects Litopenaeus vannamei, causing severe hepatopancreatic microsporidiosis (HPM) and resulting in significant economic losses. This study utilizes a combined analysis of transcriptomics and metabolomics to unveil the dynamic molecular interactions between EHP and its host, the Pacific white shrimp, during the early and late stages of infection. The results indicate distinct immunological, detoxification, and antioxidant responses in the early and late infection phases. During early EHP infection in shrimp, immune activation coincides with suppression of genes like Ftz-F1 and SEPs, potentially aiding parasitic evasion. In contrast, late infection shows a refined immune response with phagocytosis-enhancing down-regulation of Ftz-F1 and a resurgence in SEP expression. This phase is characterized by an up-regulated detoxification and antioxidant response, likely a defense against the accumulated effects of EHP, facilitating a stable host–pathogen relationship. In the later stages of infection, most immune responses return to baseline levels, while some immune genes remain active. The glutathione antioxidant system is suppressed early on but becomes activated in the later stages. This phenomenon could facilitate the early invasion of EHP while assisting the host in mitigating oxidative damage caused by late-stage infection. Notably, there are distinctive events in polyamine metabolism. Sustained up-regulation of spermidine synthase and concurrent reduction in spermine levels suggest a potential role of polyamines in EHP development. Throughout the infection process, significant differences in genes such as ATP synthase and hexokinase highlight the continuous influence on energy metabolism pathways. Additionally, growth-related pathways involving amino acids such as tryptophan, histidine, and taurine are disrupted early on, potentially contributing to the growth inhibition observed during the initial stages of infection. In summary, these findings elucidate the dynamic interplay between the host, Litopenaeus vannamei, and the parasite, EHP, during infection. Specific phase differences in immune responses, energy metabolism, and antioxidant processes underscore the intricate relationship between the host and the parasite. The disruption of polyamine metabolism offers a novel perspective in understanding the proliferation mechanisms of EHP. These discoveries significantly advance our comprehension of the pathogenic mechanisms of EHP and its interactions with the host. Litopenaeus vannamei) has a pivotal role in the global shrimp aquaculture industry, contributing to over 70% of the total global shrimp production [Enterocytozoon hepatopenaei (EHP) and its associated hepatopancreatic microsporidiosis (HPM) has led to significant economic losses in the Asian shrimp farming sector [P. monodon, L. vannamei, and P. stylirostris [The Pacific white shrimp  enables the study of gene function under specific conditions through genomic structure analysis and functional annotation . Metabolnfection ,20. In this study, through sampling of infected shrimp at two distinct life stages, we gained valuable insight into the EHP-shrimp interaction during different phases of the infection process. Comparative to single time-point analyses, analyzing juveniles versus adults offers a higher-resolution perspective into EHP pathogenesis during shrimp development. Our primary goal was to comprehensively investigate the interaction between Pacific white shrimp and EHP through a combined transcriptomics and metabolomics approach. By examining EHP infections in juvenile versus adult shrimp hepatopancreas, we explore the relationship between shrimp life stage and gene expression as well as metabolic pathways in diseased shrimp. Our research provides a rich dataset of the interaction between Pacific white shrimp and EHP, potentially yielding a better understanding of the changing impacts on shrimp during development and EHP progression, and offering deeper insights for future studies.6 copies of EHP DNA per nanogram of host DNA. In contrast, juvenile shrimp infected with EHP (Jsp group) showed a lower EHP load, averaging 4.3 × 104 copies/ng of host DNA. The uninfected adult (Asn group) and juvenile (Jsn group) shrimp showed no detectable levels of EHP, confirming their uninfected status  exhibited a notably high EHP load, with an average of 2.6 × 10d status . These rLitopenaeus vannamei hepatopancreas samples, with and without EHP infection. Sequencing on the Illumina platform yielded 110.15 Gb of high-quality clean data, with alignment ratios ranging from 78.37% to 91.91% to the NCBI reference genome. The clean data exhibited Q30 scores above 93.08%, GC content higher than 42%, and an error rate below 0.03%, ensuring its suitability for transcriptome analysis  database provided annotations for 96.75% of the genes, while the Cluster of Orthologous Groups (COG) database contributed to 69.36% of the gene annotations. Remarkably, a substantial portion of the unigenes, amounting to 96.86% , were successfully annotated across all utilized databases, underscoring the comprehensiveness of our transcriptomic data . Figure Principal coordinate analysis (PCoA) on the transcriptome data delineated distinct clustering of shrimp based on health status and developmental stage in the context of EHP infection . Notablyp-value below 0.05. The results are visually represented in Differential expression analysis was conducted using DESeq2. Unigenes were considered differentially expressed genes (DEGs) if they exhibited an absolute log2 fold change greater than 1 and an adjusted In the comparison between the uninfected adult group (Asn) and the EHP-infected adult group (Asp), a total of 1769 DEGs were identified. Specifically, 963 genes were up-regulated and 806 genes were down-regulated in the Asp group relative to the Asn group a. SimilaTo discern the developmental differences between adults and juveniles, and to isolate the specific transcriptional changes attributable to EHP infection, we compared the uninfected groups (Asn vs. Jsn) and the infected groups (Asp vs. Jsp). In the Asn vs. Jsn comparison, 2687 DEGs were identified, indicating the inherent transcriptomic differences due to developmental stage c. This cThe Venn diagram in Analysis of DEGs via KEGG functional annotation provides insight into the biological processes most impacted by EHP. In the late stage of infection a, adult In contrast, early-stage infected juvenile shrimp b displayWhen comparing healthy adult shrimp with juvenile shrimp c,d, uniqTo elucidate the biological functions of the DEGs, we carried out a comprehensive KEGG pathway enrichment analysis. The process involved the utilization of the Python Scipy (v1.11.1) software package, which facilitates the comparison of DEGs against the database of KEGG pathways to identify significant enrichments. We employed Fisher’s exact test to calculate the enrichment significance of each pathway.p-value of less than 0.05 was considered indicative of significant enrichment. In our detailed examination of the transcriptomic data, To ensure the reliability of our findings, we adopted the Benjamini–Hochberg (BH) method to correct the multiple testing problem, thereby controlling the false discovery rate. We set a stringent threshold, where a Corrected Our analysis revealed distinct metabolic responses between the infected adult and juvenile shrimp. In the Asn vs. Asp comparison, a significant enrichment of metabolic pathways was observed, with a notable focus on carbohydrate metabolism (Starch and sucrose metabolism), antioxidant processes , lipid metabolism (Sphingolipid metabolism), and amino acid metabolism . Additionally, several pathways implicated in detoxification were also enriched. In contrast, the Jsn vs. Jsp comparison highlighted an enrichment of pathways associated with immune response and detoxification, including those involved in the metabolism of reactive oxygen species and xenobiotics by cytochrome P450. Pathways related to growth, such as steroid hormone biosynthesis, were also more prominent in juvenile shrimp, suggesting an early-stage toxic response to EHP infection that influences immunity, detoxification, and hormone regulation. Adult shrimp, on the other hand, showed signs of metabolic adaptation to EHP infection in later stages, with a focus on energy metabolism. Nonetheless, the persistence of enriched detoxification pathways indicates ongoing toxic challenges due to EHP. The specific distribution of DEGs across these pathways is detailed in Gene expression levels of 24 genes were assessed via qPCR. The obtained data revealed that the expression trends observed in qPCR and RNA-Seq analyses exhibited a concordant pattern, as depicted in This study employed untargeted metabolomics analysis to investigate metabolites in the hepatopancreas of Pacific white shrimp at different time points after EHP infection, aiming to identify metabolites potentially related to infection duration. Principal Component Analysis (PCA) results demonstrated satisfactory sample classification in both positive and negative ion modes a. Partiap-value below 0.05, a Variable Importance in Projection (VIP) score exceeding 1, and an absolute fold change (|FC|) greater than 1. The volcano plot analyses, presented in In our investigation of Selectivity Differential Metabolites (SDMs), Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) served as the basis for screening. We identified SDMs based on the criteria of a In the Asn vs. Asp comparison, we identified 143 metabolites that were up-regulated and 180 that were down-regulated in the infected adult shrimp (Asp) relative to the control adult group (Asn). For the juvenile shrimp, the Jsn vs. Jsp comparison revealed 108 metabolites up-regulated and 266 down-regulated in the infected juveniles (Jsp) compared with the uninfected juveniles (Jsn). When comparing the adult and juvenile uninfected shrimp (Asn vs. Jsn), there were 278 metabolites up-regulated in the adults (Asn) alongside 82 down-regulated metabolites. The contrast between the infected adult and juvenile shrimp (Asp vs. Jsp) showed 68 metabolites up-regulated in the adult infected group (Asp) and 49 down-regulated.Taking into account all four comparison pairs—Asn vs. Asp, Jsn vs. Jsp, Asn vs. Jsn, Asp vs. Jsp—a total of 323, 374, 360, and 117 SDMs were identified, respectively. Notably, we discovered seven metabolites consistently modulated across all comparison groups, indicative of a core metabolic response to EHP infection and developmental stage differences  with increasing abundance from the uninfected group to the long-term infected group. Key pathways mapped by these metabolites include tryptophan, caffeine, pyrimidine, purine, and glycerophospholipid metabolism pathways, along with lysine degradation a. The suOur integrative analysis, depicted in During the early stages of shrimp infection with EHP, 8 SDMs and 25 DEGs were involved in purine metabolism . In the During the early stages of shrimp infection with EHP, 1 SDM, and 43 DEGs were enriched in the glutathione metabolism pathway . Among tIn the late stages of shrimp infection with EHP, we observed a significant impact on glycerophospholipid metabolism, with 9 SDMs and 9 DEGs enriched in this pathway . Among tIn lipid metabolism, we also observed a significant impact on sphingolipid metabolism during the later stages of infection, with 2 SDMs and 20 DEGs enriched in this pathway . Among tIn this study, we discovered a striking contrast between the late and early stages of infection in the glutathione metabolism pathway, with 1 SDM and 20 DEGs enriched . We obseMicrosporidian infections often impact the host’s behavior and interact with various regulatory mechanisms within the host’s body . In thisUnder the stress of EHP infection, there are significant differences in the immune responses of shrimp during the early and late stages. Shrimp identified more immune-related DEGs during the early infection compared to the late infection, suggesting that EHP may activate a broad spectrum of immune defenses in the early stages. In the late infection stage, the expression of these DEGs returned to normal, possibly indicating a strategy employed by EHP to establish a long-term symbiotic relationship with the shrimp while reducing the host stress response. However, during the early infection, we observed that certain immune-related genes might be regulated by EHP to facilitate invasion. Previous research indicates that microsporidia can suppress host immunity during invasion .We observed a significant impact on the transcriptional expression of two genes, Ftz-F1 and SEPs, during the early infection stage. Ftz-F1 overexpression can inhibit phagocytosis of blood cells. This suggests that in the early stages of EHP infection, the parasite might manipulate the host’s Ftz-F1 to evade phagocytosis and promote its infection ,25. SimiVibrio harveyi infection [In contrast, the reduced number of DEGs during the late infection stage suggests that the effects of EHP are gradually diminishing. This includes most immune-related DEGs that exhibited significant differences in the early stages, such as the expression of SEPs which returned to normal in the late infection stage. Interestingly, some immune activities become more pronounced. For example, the expression of Ftz-F1 is significantly down-regulated in the late infection stage, leading to a significant increase in the cell’s phagocytic ability against pathogens . Additionfection . We obseTrachipleistophora hominis for the critical purine building blocks of its DNA and RNA [In the context of metabolic pathways, our data indicate a strong reliance of EHP on the host’s energy metabolism. During the early infection stage, ATP synthase exhibits significant up-regulation. ATP synthase is essential for electron transport and ATP synthesis . Moreove and RNA . Our stu and RNA . COX is  and RNA . MitochoNosema bombycis infection, another microsporidian [In contrast, during the late infection stage, EHP seems to become more reliant on the host’s energy metabolism. Several fundamental ATP-generating pathways, including glycolysis and oxidative phosphorylation, are significantly affected. Glycolysis is a key carbohydrate metabolism pathway. Although genes related to glycolysis are missing in the Enterocytozoon family of microsporidia, each lineage retains genes from different parts of the glycolytic pathway . This suporidian ,43. ThesEriocheir sinensis [Tubulinosema ratisbonensis proliferation [Lipids, as a principal component of hepatopancreas, play a vital role in energy storage, among other functions. During the late infection stage, the high load of EHP leads to the disruption of hepatopancreas function, resulting in the disturbance of lipid metabolism pathways. In this study, we observed a significant enrichment in glycerophospholipid and sphingolipid metabolism pathways. This aligns with Ding et al.’s research, which showed that microsporidian infection disrupts glycerophospholipid and sphingolipid metabolism in sinensis . Our temsinensis . The sigsinensis . Additioferation . These fSphingolipids, as another important class of lipids, are integral components of membrane lipids and play vital roles in signal transduction. In this study, we observed a continuous decrease in sphingolipids as the infection cycle progressed. Existing research suggests that microsporidia might form invasion vesicles through interactions with the host cell membrane during invasion ,48. ThisNosema ceranae highlighted the importance of the glutathione system in microsporidian invasion. Knocking down the expression of γ-glutamyl-cysteine synthetase and thioredoxin reductase genes resulted in a significant reduction in spore load within honeybees [Our study also revealed a significant down-regulation of genes involved in glutathione metabolism during the early EHP infection period. The glutathione system plays a crucial role in antioxidant defense and maintaining redox balance, which are essential during the infection process. A study focusing on oneybees . InteresEnterocytozoon cuniculi exhibit polyamine synthesis and transformation activities before germination, shown by the conversion of spermine to spermidine. Furthermore, the use of polyamine analogs as inhibitors effectively interferes with spore uptake and conversion of polyamines before germination [Enterocytozoon cuniculi, demonstrate significant potential for polyamine transformation [It is worth noting that polyamine metabolism, as a part of the glutathione metabolic pathway, is significantly affected both in the early and later infection phases. Polyamines include putrescine, spermidine, and spermine. Notably, spermidine levels show significant down-regulation in both early and late infection phases, while the expression of spermine synthase is significantly up-regulated in both periods. Interestingly, the reduction in spermidine levels is more pronounced in the later phase, while the transcriptional level of spermine synthase is even higher in the later phase. Polyamine metabolism is considered important for parasite survival . Relatedmination . This sumination . Some miormation . These fParanosema locustae, significantly reduces taurine levels in infected Locusta migratoria, leading to growth inhibition in the infected locusts [Finally, in the infection cycle of EHP, we observed that shrimp seem to experience more pronounced growth inhibition during the early infection phase. In the early stages of EHP infection, we observed significant disruption in amino acid metabolism, particularly for growing essential amino acids such as tryptophan and histidine. Our KEGG topology analysis of SDMs suggests that this disruption could impair shrimp growth and development, as these amino acids are crucial for protein synthesis and various metabolic processes  Furtherm locusts  This sug locusts  However,In our study, we also found that certain metabolic pathways, such as tryptophan, phenylalanine metabolism pathways, and lysine degradation pathways, were significantly enriched in both early and late infection stages, albeit in different host groups (Asn vs. Jsn and Asp vs. Jsp). Among them, lysine degradation seems to be more affected, as it was significantly enriched in Clusters 3, 6, and 7 in the temporal analysis. Lysine-rich proteins, such as extreme-heat pipe protein 2 (EHPPTP2), were identified in EHP’s infective polar tube  This sugIn summary, our study provides new insights into the metabolic adaptations of shrimp during EHP infection. However, our understanding of the complex interactions between EHP and its host is still in its early stages. Further research is needed to validate these findings and uncover the molecular mechanisms behind these metabolic changes. This study not only enhances our understanding of the pathogenesis of EHP but also identifies potential targets for therapeutic intervention.In August 2022, we identified EHP infection in samples collected from ponds located in Dafeng District, Yancheng City, Jiangsu Province, using EHP PCR. Diseased shrimp samples were collected from the ponds, measuring approximately 3.9 ± 0.2 cm in size. Simultaneously, healthy shrimp under identical conditions were also collected, measuring approximately 4.6 ± 0.2 cm. Thirty days later, we collected samples from the same batch of diseased and healthy shrimp in the previously mentioned ponds. The size of the diseased shrimp was approximately 8.1 ± 0.2 cm, while the healthy shrimp measured approximately 11.3 ± 0.2 cm. After collection, the shrimp were individually reared for subsequent pathogen detection and RNA extraction. The rearing system maintained a constant temperature of 24 ± 1 °C and a salinity of 12 ± 2 PPT.Before RNA extraction, four groups of samples were tested for pathogen PCR and EHP content to confirm that there was no other pathogen infection and to determine the degree of EHP infection. The four groups were EHP-negative juvenile shrimp (Jsn), EHP-positive juvenile shrimp (Jsp), EHP-negative adult shrimp (Asn), and EHP-positive adult shrimp (Asp). This was performed to confirm the absence of other pathogen infections and to assess the extent of EHP infection. To minimize individual variations, three shrimp liver and pancreatic mixtures were combined to form one sample for each group. For transcriptome and metabolomics analysis, three replicate samples were taken from each group. All samples were immediately frozen in liquid nitrogen and stored until RNA and metabolite extraction.For the detection of pathogens in our samples, we followed the established PCR protocols as described by Shen et al. . This inTo quantify the EHP load in infected shrimp, we employed TaqMan probe real-time PCR, a more sensitive and specific method that allows for the precise measurement of pathogen copies . We used® Reagent  as per the manufacturer’s instructions. To assess the concentration, purity, and integrity of the extracted RNA, Nanodrop2000, agarose gel electrophoresis, and Agilent2100 were employed [Total RNA was extracted from the samples using TRIzolemployed . High-quAfter extracting RNA, we proceeded to construct the mRNA library for sequencing. mRNA was isolated from the total RNA using magnetic beads coated with oligo(dT) to selectively bind the polyA tail of mRNA molecules. The isolated mRNA was then fragmented using a fragmentation buffer under optimized conditions. This was followed by the synthesis of first-strand cDNA using reverse transcriptase with the fragmented mRNA as a template, and subsequently, second-strand cDNA was synthesized to form a stable double-stranded structure using random primers, as described in . The cDNLitopenaeus vannamei reference genome (GCF_003789085.1) using HiSat2, ensuring that our transcriptome data mapping was specific to the shrimp host and free from EHP contamination. Following alignment, we employed StringTie (v2.1.2) for de novo assembly and gene annotation of the shrimp transcriptome. The quality of the assembled transcripts was rigorously evaluated using established benchmarks [In our bioinformatics pipeline, we initially aligned the RNA sequencing reads to the EHP reference genome (GCA_002081675.1) using HiSat2 (v2.1.0) to identify and separate EHP-specific sequences. Reads that did not align with the EHP genome were extracted using Samtools (v1.9) and converted into fastq files for subsequent analysis. These unaligned reads were then aligned to the nchmarks . For funnchmarks ,63,64,65p-value of less than 0.05 for statistical significance, and an absolute log2 fold change (|log2FC|) of 1 or greater to ensure biological relevance. Only genes meeting both thresholds were considered DEGs.Differential expression analysis was conducted using the DESeq2 (v1.24.0) package in R, which enabled the identification of genes with significant expression changes between the experimental groups . We estaFor the quantification of gene expression levels, we utilized RSEM (v1.3.3) to calculate the counts, which were then normalized to transcripts per million (TPM). This normalization accounts for gene length and sequencing depth differences, allowing for accurate cross-sample transcript abundance comparisons.To validate the reliability of our transcriptomic findings, we performed quantitative real-time PCR (qRT-PCR) on a subset of six genes from each comparison group . The 18s RNA gene was employed as an internal reference for normalization in our qRT-PCR analyses. To ensure the stability and suitability of 18s RNA as a reference, we conducted a stability analysis across all experimental conditions, including the four groups from this study and additional conditions from a related study. The cycle threshold (Ct) values of 18s RNA were assessed and are presented in a box plot format , demonstPrimer sequences for both target and reference genes were crafted using Primer Premier 5 software, with the sequences detailed in g for 15 min. The resulting supernatant was collected for LC-MS analysis. To assess the repeatability of the entire analysis process, a quality control (QC) sample was included every four samples.Samples were collected in 2 mL centrifuge tubes and subsequently ground. Metabolites were extracted by adding 400 μL of 80% methanol extraction solution. The sample solution was then ground for 6 min at −10 °C and 50 Hz using a cold tissue grinder. Next, low-temperature ultrasound extraction was performed for 30 min at 5 °C and 40 kHz. Following extraction, the samples were left to stand at −20 °C for 30 min, followed by centrifugation at 4 °C and 13,000× LC-MS analysis was conducted using the UHPLC-Q Exactive system manufactured by Thermo Fisher Scientific.The raw metabolomic data were processed using Progenesis QI (v2.3) software from Waters Corporation, Milford, USA. After importing the raw data, the MS and MSMS spectral information were matched with the metabolic databases HMDB and Metlin. Principal component analysis (PCA) and orthogonal partial Least Squares Discriminant Analysis (OPLS-DA) were performed on the preprocessed matrix file using Ropls (v1.6.2). The stability of the model was assessed using seven rounds of cross-validation.p-value less than 0.05 were considered SDMs. The KEGG database was used for metabolic pathway annotation of the SDMs. Pathway enrichment analysis was performed using Scipy.stats (v1.0.0), and Fisher’s exact test was employed to identify the most relevant biological pathways associated with the experimental treatments.Differential metabolites were selected based on the OPLS-DA model. Metabolites with a VIP score greater than 1 and a p-value of less than 0.05. Pathways meeting this criterion were considered significantly enriched and indicative of a concerted biological response to EHP infection. This integrative analysis allows for a more robust interpretation of the interplay between the transcriptome and metabolome during the infection process, providing insights into the coordinated changes in gene expression and metabolite abundance within key biological pathways.To investigate the correlation between the DEGs and SDMs associated with shrimp infection by EHP, we adopted an integrated KEGG pathway enrichment approach. This method involves the enrichment analysis of selected sets of DEGs and SDMs, utilizing the hypergeometric distribution algorithm to identify pathways significantly enriched with genes and metabolites from our datasets. We applied the Benjamini–Hochberg (BH) method to correct for multiple hypothesis testing, with a threshold for significance set at a t-test with a significance level of 0.05.Statistical analysis was performed using SPSS 18.0 software. Data are expressed as mean ± standard deviation (SD). Significant differences (copies of EHP in the hepatopancreas) between samples were analyzed by Our study delineates the complex interplay between shrimp and EHP at different infection stages, characterized by marked transcriptional and metabolic shifts. Initially, the immune system ramps up, as shown by the 2444 DEGs and 374 selectivity SDMs, yet some immune genes are paradoxically down-regulated—potentially a tactic by EHP to establish infection. As the disease advances, we see signs of the host immune system adapting, indicative of a longer-term adjustment to the pathogen’s presence. The consistent alteration of energy metabolism pathways, intensifying over time, highlights EHP’s reliance on the host’s energy supply. The late-stage infection also profoundly affects lipid metabolism, likely due to EHP’s proliferation and associated hepatopancreatic damage. Notably, the activation of antioxidant and detoxification pathways later in the infection points to the host’s defense against EHP-induced oxidative stress, with the glutathione system playing a key role in this protective response. The modulation of polyamine metabolism, intertwined with the glutathione pathway, emerges as another critical factor in the host–pathogen dynamic, potentially aiding EHP’s growth. In summary, our findings illuminate the nuanced host–pathogen dynamics in EHP infection, providing a window into the pathogen’s exploitation strategies and the host’s adaptive mechanisms, and thereby contributing to our understanding of EHP pathogenicity.


Does Klinefelter syndrome (KS) lead to a distinct gene expression pattern at single-cell level in the testes that could provide insight into the reported microvascular dysfunction in the testes?A distinct gene expression pattern within microvascular-associated cells of males with KS suggests excessive endothelial cell (EC) activation, disorganized vessel formation, and the presence of immature vessels with compromised integrity.Recent studies show that males with KS exhibit microvascular dysfunction in their testes, which affects blood flow and is associated with lower circulating levels of testosterone.A comparative cross-sectional study of males with KS (n = 6), non-obstructive azoospermia (NOA) (n = 5), cryptozoospermia (n = 3), and controls (n = 15) was carried out.We analyzed publicly available single-cell RNA sequencing data of testicular cells from males with KS, males with NOA, males with cryptozoospermia, and controls. The integration of these datasets allowed us to analyze gene expression profiles and communication patterns among the cell types within the testis and to identify capillary ECs to investigate changes at the microvascular level.Padj < 0.05). Specifically, the unique microvascular gene expression in males with KS indicated enhanced capillary EC activation and increased inflammatory cross-talk, leading to impaired vessel maturation and increased EC barrier permeability.Rooted in changes at the single-cell level, our study demonstrates a shift in gene expression forming the foundation for altered cellular communication, microvascular remodeling, and pro-inflammatory responses within the testes of males with KS. We identified genes that were dysregulated in capillary ECs from males with KS . C.H.G. was supported by Novo Nordisk Foundation , ‘Fonden til lægevidenskabens fremme’, the Familien Hede Nielsen foundation and the Independent Research Fund Denmark (0134-00406A). E.B.J. was supported by Aarhus University and E.B.J. and C.H.G by the Independent Research Fund Denmark (2096-00165A). J.M.K. was supported by Lundbeckfonden (R307-2018-3667), Carlsberg Fonden (CF19-0687), Novo Nordisk Fonden (0073440) and Steno Diabetes Center Aarhus (SDCA). The authors declare no conflicts of interest.N/A. Hypergonadotropic hypogonadism, small testes, and non-obstructive azoospermia (NOA), with the resultant endpoint being infertility, are some of the hallmarks of Klinefelter syndrome . The testicular phenotype in males with KS is well described, including degeneration of germ cells, Leydig cell (LC) hyperplasia, hyalinization of the seminiferous tubules, thickening of the tubule walls, fibrosis, and in some cases spermatogenic foci , the understanding of the molecular mechanisms associated with the testicular phenotype of NOA has improved . In addiy mice had an increased density of blood vessels (blood vessel area/testis volume) compared to 40,XY mice (2) , pericytes, and smooth muscle cells (SMCs), plays a crucial role in supporting both spermatogenesis and testosterone production. It supplies oxygen and nutrients to the seminiferous tubules and LCs, removes waste products, and exports testosterone into the circulation  and three iNOA samples (iNOA2–4) were generated from the BD Rhapsody platform, referred to as ‘BD samples’, while the remaining samples were generated from the 10x Genomics platform, referred to as ‘10× samples’. For the BD samples, gene expression count files were downloaded. For 10x samples, fastq-files were downloaded and demultiplexed via CellRanger . Seurat objects were created using the Seurat package in R (Seurat 4.1.1) . Furtherand PRM2 , which wand PRM2 . To addrand PRM2 , to remoand PRM2 . We obseand PRM2 , and a cand PRM2 . DoubletPRM1, PRM2, and TNP1 > 2 were removed to avoid spermatozoa contamination in the subsequent analyses. Vascular EC types were subcategorized as arterial, venous, capillary, or lymphatic based on a murine EC single-cell atlas by Testicular cell types were determined based on marker genes obtained from the literature. From here, EC and SMC clusters were isolated. Cells expressing the spermatogenic markers P-value of 0.05 (Padj < 0.05) and a log2 fold change of 0.5, unless stated otherwise. To avoid residual spermatozoa contamination and dead cells affecting the analyses, mitochondrial genes/PRM1/PRM2/TNP1 were excluded from the differential expression output. To examine gene expression in specific Gene Ontology (GO) categories, tables of genes within terms of interest  were obtained from QuickGO (ebi.ac.uk/QuickGO), selecting taxon ‘Homo sapiens’ (9606). The FindMarkers function was applied and restricted to the capillary EC cells and the genes within each selected GO term. Adjusted P-values and log2 fold changes were extracted to generate plots displaying the expression differences between KS, NOA, and CTRL using ggplot2  .Differences in cell type frequency between groups were analyzed using a Kruskal–Wallis test. Pairwise comparisons were then performed using a Wilcoxon rank sum test. Results were considered statistically significant when To investigate the testicular microvasculature of males with KS at the cellular level, we included samples from six publicly available scRNAseq studies of testicular tissue from adult males (P = 0.0085) and KS (P = 0.00035), which in turn had higher relative somatic counts of LCs compared to controls   .To identify the cell types of the testis mostly responsible for oxygen, nutrient, and hormone exchange, i.e. the cell types that constitute the microvasculature, we filtered the collected dataset to include only ECs and SMCs and performed re-clustering. Based on the testis EC markers described by First, we conducted an overall analysis of genes associated with cell-to-cell communication among all the vasculature cell types. Notably, we found that expression of genes associated with cell-to-cell communication was stronger in controls, for all cell types, compared to males with KS and NOA, suggesting an overall impaired or dysfunctional vasculature in males with KS and NOA .Padj < 0.05)  and EC barrier tightness   . As expend AHNAK . Previou, AHNAK)   downregulated genes compared to CTRLs were also downregulated compared to males with NOA, and hence uniquely downregulated in males with KS. These included CCN2, CLEC14, EGFL7, ENG, FLNA, ID1, RAPGEF3, RASIP1, ROBO4, SOX18, and YWHAZ, indicating reduced signaling in capillary ECs in both males with KS and NOA. This observation was supported by the amount of outgoing and incoming signaling in capillary ECs of males with KS  . Only ge with KS .CLDN5 and CDH5 (VE-Cadherin), which play crucial roles in EC barrier tightness , ENG, NOTCH4, JAG1, and ID1, in addition to the anti-angiogenic gene FLT-1 (VEGFR1)  and ICAM1 and -2 were increased and are known to be associated with innate immune responses and leukocyte adhesion to the microvasculature , previous studies of KS testes have identified an increased number of immune cells and increased inflammation as the possible foundation for the observed testicular fibrosis (culature . The intBased on our results, it is pivotal to address the sequence of events. Does the dysfunctional microvasculature lead to oxidative stress, hypoxia, inflammation, and impaired testosterone release, or is the dysfunctional microvasculature a consequence of inflammation in the testes, already being in a pathophysiological state? Regardless of the sequence of events, these processes seem to be intricately linked. Chronic microvascular dysfunction might potentiate inflammation and, conversely, chronic inflammation may disrupt the normal progression of angiogenesis and vessel maturation. As such, the cross-talk between the endothelium and the surrounding tissues plays a crucial role in the regulation and co-ordination of the inflammatory response and, importantly, both these scenarios could negatively interfere with hormonal control in the testes.The general picture emerging concerning the genomics of KS is that across tissues, multiple changes in the DNA methylome, transcriptome, and metabolome are present (While the utilization of scRNAseq from publicly available databases enables a larger cohort size leading to a more precise examination of gene expression profiles in specific testicular cell types, we acknowledge that the scope of our study design warrants caution in drawing definitive conclusions. While our findings indeed point towards a complex interplay encompassing altered cellular communication, vascular remodeling, and pro-inflammatory responses in KS testes , it is iTaken together, our results indicate a complex interplay of altered cellular communication, vascular remodeling, and pro-inflammatory responses within the testes of males with KS . Specifidead224_Supplementary_Figure_S1Click here for additional data file.dead224_Supplementary_Figure_S2Click here for additional data file.dead224_Supplementary_Figure_S3Click here for additional data file.dead224_Supplementary_Figure_S4Click here for additional data file.dead224_Supplementary_Figure_S5Click here for additional data file.dead224_Supplementary_Figure_S6Click here for additional data file.