Protein homeostasis (proteostasis) is a potential mechanism that contributes to cancer cell survival and drug resistance. Constitutively active androgen receptor (AR) variants confer anti-androgen resistance in advanced prostate cancer. However, the role of proteostasis involved in next generation anti-androgen resistance and the mechanisms of AR variant regulation are poorly defined. Here we show that the ubiquitin-proteasome-system (UPS) is suppressed in enzalutamide/abiraterone resistant prostate cancer. AR/AR-V7 proteostasis requires the interaction of E3 ubiquitin ligase STUB1 and HSP70 complex. STUB1 disassociates AR/AR-V7 from HSP70, leading to AR/AR-V7 ubiquitination and degradation. Inhibition of HSP70 significantly inhibits prostate tumor growth and improves enzalutamide/abiraterone treatments through AR/AR-V7 suppression. Clinically, HSP70 expression is upregulated and correlated with AR/AR-V7 levels in high Gleason score prostate tumors. Our results reveal a novel mechanism of anti-androgen resistance via UPS alteration which could be targeted through inhibition of HSP70 to reduce AR-V7 expression and overcome resistance to AR-targeted therapies. The AR-V7 isoform is associated with anti-androgen drug resistance in prostate cancer. Here, the authors show that AR-V7 protein stability is regulated by HSP70/STUB1 complex-mediated proteostasis which confers drug resistance in late stage prostate cancer. Inhibition of HSP70 re-sensitizes resistant cells to enzalutamide therapy. Imbalanced proteostasis disrupts protein clearance and increases abnormal deposition of protein aggregates which facilitates cancer cell survival and progression. Thus, overexpression of oncogenic proteins mediated by proteostasis is a potential mechanism that contributes to drug resistance in cancer cells. Understanding the mechanisms of protein post-translational regulation in order to find strategies to correct proteostasis-imbalance in anti-androgen resistant prostate cancer is warranted.Proteomic equilibrium including protein folding, trafficking, maturation, and degradation controls mammalian cell biological function and maintains physiological environment stabilization. Protein homeostasis (proteostasis) is regulated through a comprehensive network, including molecular chaperone proteins, the ubiquitin–proteasome system, and the autophagy system9. Rearrangements that alter AR gene structure and splicing patterns have been described in prostate cancer cell lines, and xenografts which suggests the origin of AR-V7 might be derived from intragenic AR gene rearrangements or premature translation termination by aberrant mRNA splicing12. However, post-translational regulation of AR-V7 and the mechanisms of AR-V7 proteostasis have not been fully explored.Enzalutamide and abiraterone are the second-generation anti-androgen drugs approved for the treatment of castration-resistant prostate cancer (CRPC). Even though they are effective at first, resistance to both drugs occurs frequently. Considerable evidence from both clinical and experimental studies demonstrate that truncated androgen receptor (AR) variants, particularly AR-V7, plays vital roles in promoting CRPC progression during androgen deprivation therapy and in the induction of resistance to enzalutamide and abiraterone therapy15. The HSP70s family, including stress inducible member HSP70 (HSPA1A/HSPA1B) and constitutively expressed member HSC70 (HSPA8), plays important roles for protein maturation and correct folding in cancer cell signal transduction and regulation18. STUB1 is a co-chaperone protein and functional E3 ubiquitin ligase that links HSP70’s polypeptide-binding activity to the ubiquitin proteasome system. HSP70 interacts with STUB1 and controls protein stabilization. Binding of STUB1 to HSP70 can halt the proper folding of HSP70 substrate proteins and concomitantly facilitate the U-box-dependent ubiquitination of HSP70-bound substrates21. As AR’s co-chaperone protein, HSP70 assists the folding and maturation of AR protein24. However, understanding of the interaction among AR-V7, HSP70, and STUB1 in next generation anti-androgen resistance remains elusive.The chaperone protein family, including heat shock proteins (HSPs), regulates the activity and stability of many oncogenes that control cancer cell survival and progressionIn the present study, we discover that the ubiquitin-mediated proteolysis pathway and proteasome activity are suppressed in enzalutamide and abiraterone-resistant prostate cancer cells which stabilizes AR-V7 protein in these cells through ubiquitin–proteasome alteration. The STUB1/HSP70 complex regulates full length AR (AR-FL) and AR variant proteostasis which confers next generation anti-androgen resistance. HSP70 inhibition significantly disrupts AR and AR-V7 gene programs and re-sensitizes resistant cells to enzalutamide and abiraterone treatment both in vitro and in vivo. Notably, the levels of HSP70 are correlated with AR-V7 in tumors from patients with high Gleason scores. These results suggest that targeting the proteostasis pathway through inhibiting HSP70 might be a valuable strategy to overcome next generation anti-androgen resistance and improve drug therapy in CRPC patients.p = 1.93 × 10−7) . The results were also confirmed in other independent enzalutamide-resistant cells (LNCaP EnzaR and CWR-R1 EnzaR)25 and LuCaP castration-resistant (LuCaP CR)26 patient-derived xenograft (PDX) models overexpressing AR-V7 , CWR-R1 EnzaR (p < 0.001) cells, and LuCaP CR PDX tumor models (p < 0.001). Further proteasome activity fluorometric assay revealed that resistant C4-2B AbiR, C4-2B MDVR, and CWR22Rv1 cells produced significantly lower proteasome activity compared to C4-2B cells  2.4. C4-2B MDVR and CWR22Rv1 cells showed abundant splice junctions between AR exon3 and exon4 Fig. . Among t−7) Fig. . GSEA re-V7 Fig. . The ubills Fig. . Moreovells Fig. . Taken tHeatmap analysis of global gene microarray data from enzalutamide/abiraterone-resistant cells and LuCaP CR tumors showed that the core enrichment genes involved in protein ubiquitination were downregulated. One of the most significantly downregulated genes in the resistant cells and LuCaP CR tumors was E3 ubiquitin ligase STUB1 Fig. . We founTo further investigate the effect of STUB1 on regulation of AR-V7 expression, we transiently transfected STUB1 into C4-2B MDVR and CWR22Rv1 cells and found that overexpression of STUB1 significantly suppressed AR-V7 protein expression but did not affect mRNA expression Fig. . STUB1 sAs a co-chaperone protein of STUB1, HSP70 assists oncogenic proteins folding and maturation. We found that HSP70 but not HSP90 (HSP90AA1) was overexpressed in enzalutamide-resistant prostate cancer cells and LuCaP CR tumors Fig. . HSP70 o27 and Ver155008 (VER)28 are HSP70 inhibitors that function through binding to the HSP70 active pocket and suppressing its ATPase activity 30. As shown in Supplementary Fig.Next, we examined the combinational effects of APO or VER with next generation anti-androgens. As shown in Fig. To determine if inhibition of HSP70 promotes AR-V7 degradation through enhanced ubiquitination, 293 cells overexpressed with AR-V7, HSP70, and HA-Ubiquitin were treated with either 20 μM VER or 20 μM APO overnight, along with 5 μM MG132 during the incubation to prevent degradation of ubiquitinated AR-V7. We found that both APO and VER resulted in enhanced ubiquitination of AR-V7 compared to DMSO-treated control cells Fig.  top. TheTo further explore the gene regulating mechanisms underlying the downregulation of HSP70 in drug-resistant prostate cancer cells, we performed RNA sequencing analyses using C4-2B MDVR and CWR22Rv1 cells treated with APO or VER to identify gene programs that are affected by HSP70 inhibition. There are 10,773 genes and 10,317 genes that were differentially expressed in APO or VER treated C4-2B MDVR cells, respectively, and 7905 genes that were commonly regulated by both APO and VER , both APO and VER significantly inhibited tumor growth . Combination of APO or VER with enzalutamide further inhibited tumor growth of CWR22Rv1 xenografts   Fig. . Survivaly) Fig. . Treatmely) Fig. , left. Vly) Fig. .Fig. 6HSp = 0.54), APO significantly suppressed LuCaP 35CR growth (p = 0.026), while combination of APO and enzalutamide further reduced tumor growth (p = 0.0087). Treatments did not alter mouse body weights , APO treatment significantly suppressed PSA (p = 0.029), and the combination treatment further reduced the PSA levels (p = 0.0053)  Fig. . APO and53) Fig. . Immunoh53) Fig. . Taken tr = 0.792, p = 0.00000143) and AR-FL levels . However, there is no significant correlation between HSP90 and AR-V7/AR-FL in these samples  patients compared to benign prostate and primary prostate cancer in four independent GEO databases Fig. . In addiOur study uncovers a balanced crosstalk between proteostasis and next generation anti-androgen resistance through regulation of the STUB1/HSP70/AR-V7 complex. We discovered that the ubiquitin-mediated proteolysis pathway and proteasome activity are suppressed in enzalutamide and abiraterone-resistant prostate cancer cells, and play a critical role in the degradation of the AR and its variants, particularly AR-V7. Modulation of AR and AR-V7 proteostasis balance could be achieved by inhibition of HSP70, which may provide a valuable strategy to overcome resistance to next generation anti-androgen therapies. Our findings suggest that alteration of the chaperone–ubiquitin–proteasome system may represent a general mechanism for the regulation of AR variants protein stability. With that, we provide rationale targeting proteostasis through inhibition of HSP70 as a potential therapeutic strategy to overcome drug resistance to AR-targeted therapies in CRPC.31. Proteomic equilibrium may be altered during tumorigenesis, and consequently leads to oncogenic activation at the protein level32. Our study determined that the imbalance of proteostasis brought on by anti-androgen treatment in prostate cancer cells might be a critical mechanism conferring drug resistance. Deficiency of proteostasis and lack of proteasome activity in enzalutamide and abiraterone-resistant prostate cancer might trigger overexpression of onco-proteins, such as AR and its variants through an inability of protein clearance. Previous reports suggested that constitutively active AR variants confer the CRPC phenotype and resistance to next generation anti-androgens in both pre-clinical and clinical models35. Among these AR variants, overexpression of AR-V7 and AR-V9 was reported in enzalutamide and abiraterone-resistant prostate cancer patients, which is consistent with our findings in this study36. The literature suggests that AR variants are generated from intragenic AR gene rearrangements that alter AR gene structure11 and aberrant mRNA splicing and premature translation termination evident in prostate cancer cell lines and xenografts10. In the present study, we determined that AR variants are not only generated through mRNA splicing but also through protein stabilization via protein ubiquitin proteasome alteration in drug-resistant prostate cancer. The half-life of AR-V7 is significantly extended in enzalutamide-resistant prostate cancer cells compared with parental cells, suggesting that next generation anti-androgen treatments might alter the prostate cancer ubiquitin-proteolysis system and stabilize AR-V7 protein. Notably, the proteasome activity is significantly suppressed in enzalutamide and abiraterone-resistant prostate cancer cells and the E3 ligase STUB1 and its binding chaperone protein HSP70 might control the AR-V7 proteostasis and confer the resistance.Emerging evidence suggests that proteomic instability, such as protein misfolding and aggregation play pivotal roles in cancer cell survival and progression37, ERα38, and AR41. Overexpression of STUB1 in cultured cells promotes ubiquitination of cystic fibrosis transmembrane conductance regulator (CFTR), c-Myc and Raf kinase45. The importance of STUB1 involved in oncogenic proteins regulation was reinforced by our discovery that STUB1 bound with AR/AR-V7 and enhanced their ubiquitination and degradation. The AR-V7 co-chaperone protein, HSP70, formed a complex with AR-V7 and assisted AR-V7 protein maturation. STUB1 blocked HSP70 and AR/AR-V7 complex formation, leading to AR/AR-V7 protein degradation. Targeting HSP70 enhances STUB1 and AR/AR-V7 binding and leads to AR/AR-V7 ubiquitination and degradation  and a C-terminal substrate-binding domain (SBD) that recognizes polypeptide substrates. HSP70s together with HSP40s are the prominent chaperone families involved in chaperone-assisted proteasomal degradation of misfolded proteins52. However, HSP90 binds with the AR ligand-binding domain (LBD) which is missing in constitutively active AR variants. This makes HSP90 inhibition irrelevant in the treatment of AR variant dominated prostate cancer. Additionally, targeting HSP90 significantly increased HSP70 expression, suggesting a compensating role of HSP70 as co-chaperone protein53. Several categories of HSP70 inhibitors have been pursued in drug development, such as targeting the peptide-binding domain (PBD), amino-terminal ATPase domain (ABD), or HSP70 co-chaperones54. In the present study, we provide a proof of concept by using HSP70 inhibitors (APO and VER) targeting ABD to treat AR-V7 overexpressing and drug-resistant prostate cancer. Through the bioinformatics analysis, we found that inhibition of HSP70 using APO and VER suppresses AR/AR-V7 signaling pathways in resistant cells. Additionally, APO and VER activate the UPR pathway and suppress cell cycle. UPR activation induces the caspases which localize to the endoplasmic reticulum (ER) membrane and trigger apoptotic pathways55. Notably, tumors that are resistant to enzalutamide are highly sensitive to APO and VER treatments. APO and VER significantly enhanced enzalutamide treatment both in vitro and in vivo. Our promising preclinical data shed light on future clinical trial development by using HSP70 inhibitors in advanced prostate cancer treatment.Studies over the last decades support the concept of targeting chaperone proteins in cancer therapy. The most well-known therapies targeting chaperone proteins currently in drug development are HSP90 inhibitors. HSP90 assists several oncogenic proteins including AR and facilitates their maturationIn conclusion, our study suggests that the ubiquitin proteasome system is suppressed in enzalutamide and abiraterone-resistant prostate cancer models. The STUB1/HSP70 complex is involved in AR and AR variant stabilization and regulates the sensitivity to next generation AR-targeted therapy. Additionally, we provide a proof of concept study showing that targeting HSP70 could be a valuable strategy to treat AR-V7 overexpressing CRPC and improve enzalutamide treatment. Clinically, HSP70 level is correlated with AR and AR-V7 in high Gleason score prostate tumors, suggesting that HSP70 might serve as a potential marker to indicate prostate cancer progression and therapeutic resistance.57. C4-2B MDVR and C4-2B AbiR were maintained in 20 μM enzalutamide containing medium and 10 μM abiraterone acetate containing medium, respectively. Parental C4-2B cells were passaged alongside the resistant cells as an appropriate control. All cell lines have been routinely tested mycoplasma free by PCR and authenticated by short tandem repeat (STR) method. All cells were maintained at 37 °C in a humidified incubator with 5% carbon dioxide. Enzalutamide, abiraterone acetate, Apoptozole (APO), and Ver155008 (VER) were purchased from Selleck Chemicals.LNCaP, C4-2B, and CWR22Rv1 were maintained in RPMI1640 supplemented with 10% fetal bovine serum (FBS), 100 units per ml penicillin, and 0.1 mg per ml streptomycin. IMR90, 293, and VCaP cells were maintained in DMEM supplemented with 10% FBS, 100 units per ml penicillin, and 0.1 mg per ml streptomycin. PZ-HPV7 cells were maintained in keratinocyte serum-free medium (K-SFM) with the required supplements (Invitrogen). All experiments with cell lines were performed within 6 months of receipt from the American Type Culture Collection (ATCC) or resuscitation after cryopreservation. C4-2B cells were kindly provided and authenticated by Dr. Leland Chung, Cedars-Sinai Medical Center . The resistant cells were isolated and referred to as C4-2B MDVR  and C4-2B AbiR (C4-2B abiraterone resistant)5 cells per well in 12-well plates or 2 × 105 cells per well in six-well plates and transfected with 20 nM of siRNA (Invitrogen) targeting the HSP70 sequence , STUB1 sequence , or control siRNA  using Lipofectamine-iMAX (Invitrogen). The effect of siRNA-mediated gene silencing was examined using qRT-PCR and western blot 2–3 days after transfection. Cells were transiently transfected by expressing plasmids for vectors, AR-FL, AR-V1, AR-V3, AR-V7, AR-V9, AR-V12 (AR-V567es), Flag-STUB1, HA-Ubiquitin, or HSP70  using Lipofectamine 2000 (Invitrogen).For small interfering RNA (siRNA) transfection, cells were seeded at a density of 0.5 × 10® M2 monoclonal antibody ; and Tubulin . Tubulin was used as loading control. Following secondary antibody incubation, immunoreactive proteins were visualized with an enhanced chemiluminescence detection system . All uncropped scans of Western Blot are attached in Supplementary Figs. Whole cell protein extracts were resolved on SDS–PAGE and proteins were transferred to nitrocellulose membranes. After blocking for 1 h at room temperature in 5% milk in PBS/0.1% Tween-20, membranes were incubated overnight at 4 °C with the indicated primary antibodies AR (441), AR (N-20), AR (C-19), HSP70 (F-3 and H-300), STUB1 (H231 and G-2), MDM2 (HDM2-323), HSP90 4F10), HA (F-3), Ubiquitin (P4D1 and FL76), 1:1000 dilution, Santa Cruz Biotechnology, Santa Cruz, CA; STUB1 ; AR-V7 ; FLAG, HA (F-35) and grown to 80% confluence and transiently transfected using Lipofectamine 2000 (Invitrogen). pGL3-PSA6.0 luciferase construct was co-transfected with pRL-TK . Briefly, pGL3-PSA6.0 luciferase construct and pRL-TK along with HSP70 siRNA, AR-V7, or HSP70 were mixed and transfected. The luciferase activity was determined 48 h after transfection using a dual-luciferase reporter assay system (Promega). Cell lysates (35 μL per well) were used for measurement of luciferase activity in a luminometer by first mixing the cell lysates (25 μL) with 20 μL luciferase assay reagent for measuring firefly luciferase activity and subsequently adding 20 μL Stop-Glo reagent for measuring Renilla luciferase activity. Data were normalized to Renilla luciferase activity.C4-2B, CWR22Rv1, or C4-2B MDVR cells were plated into 12-well plates  in 60 mm dishes for 3 weeks; the medium was changed every 7 days. The colonies were rinsed with PBS before staining with 0.5% crystal violet/4% formaldehyde for 30 min and the number of colonies was counted.58. Each reaction was normalized by co-amplification of actin. Triplicates of samples were run on default settings of a Bio-Rad CFX-96 real-time cycler. The primer sequences are shown in Supplementary Table Total RNA was extracted using TriZOL reagent (Invitrogen). cDNA was prepared after digestion with RNase-free RQ1 DNase (Promega) and then subjected to real-time reverse transcription-PCR (RT-PCR) using Sso Fast Eva Green Supermix (Bio-Rad) according to the manufacturer’s instructionsEqual amounts of cell lysates (1500 µg) were immunoprecipitated using 1 µg of Flag antibody, HSP70 antibody, AR-V7 antibody, AR (N20) antibody, or STUB1 antibody with 50 µL of protein A/G agarose with constant rotation overnight. The immunoprecipitants were washed with 10 mM HEPES (pH 7.9), 1 mM EDTA, 150 mM NaCl, and 1% Nonidet P-40 twice with 1 mL each. The precipitated proteins were eluted with 30 µL of SDS–PAGE sample buffer by boiling for 10 min. The eluted proteins were electrophoresed on 8% SDS–PAGE, transferred to nitrocellulose membranes, and probed with indicated antibodies.4 293 cells were plated in four-well Nunc™ Lab-Tek™ II Chamber Slides and transfected with AR-V7, HSP70, and Flag-STUB1 for 3 days and then treated with 10 µM APO or VER for another 24 h. Cells were fixed with 4% paraformaldehyde, permeabilized with 0.5% Triton X-100, and incubated with 1% BSA to block nonspecific binding. Cells were incubated with anti-AR  and anti-Flag antibodies (Sigma) overnight. Intracellular AR-V7 was visualized with FITC-conjugated secondary antibodies, Flag-STUB1 was visualized with Texas red conjugated secondary antibodies and nuclei were visualized with DAPI by all-in-one fluorescence microscope (BZ-X700).1 × 106 C4-2B parental, C4-2B AbiR, C4-2B MDVR, and CWR22Rv1 cells were harvested and homogenized with 0.5% NP-40 in PBS. The proteasome activity was determined by Proteasome Activity Fluorometric Assay Kit . Briefly, AMC standard curve was prepared as described in the instruction. 10 μL samples plus 90 μL assay buffer were added into opaque white 96 microwell plate. 1 μL of the proteasome inhibitor was added into one of the paired wells and 1 μL of the proteasome substrate was added to all the wells. The kinetics of fluorescence was developed at Ex/Em = 350/440 nm in a microplate reader  at 37 °C for 0–120 min. ∆RFU = RFU (without proteasome inhibitor) – iRFU (with proteasome inhibitor). Proteasome activity = AMC amount of samples/(∆RFU at linear time point 2 reading − ∆RFU at linear time point 1 reading) × sample volume × sample dilution factor = nmol per min per ml.2 × 10C4-2B MDVR and CWR22Rv1 cells were treated with vehicle or the HSP70 inhibitors APO (10 μM) and VER (10 μM) for 48 h before RNA extraction. RNA-seq libraries from 1 μg total RNA were prepared using Illumina Tru-Seq RNA Sample, according to the manufacturer’s instructions. mRNA-Seq paired-end library was prepared through Illumina NGS on HiSeq 4000: 2 × 150 cycles per bases . Around 30M reads per sample were generated. Data analysis was performed with a Top Hat–Cufflinks pipeline and sequence read mapping/alignment using HISAT. StringTie Data was mapped to and quantified for 60,658 unique genes/transcripts Gene and transcript expression is quantified as Fragments Per Kilobase of transcript per Million mapped reads (FPKM). Principal component analysis (PCA) was conducted on the FPKM gene-level data for all genes/transcripts passing filter (filtered on expression > 0.1) in the raw data. The relatedness of the differentially expressed genes from APO and VER treatment was depicted with a Venn diagram. The common regulated genes by APO and VER treatment were clustered with Hierarchical Clustering algorithm by StrandNGS software.http://software.broadinstitute.org/gsea/index.jsp)59. Genes were ranked according to the shrunken limma log2 fold changes, and the GSEA tool was used in ‘pre-ranked’ mode with all default parameters. KEGG-Ubiquitin-mediated proteolysis pathway was used in the GSEA analysis.GSEA was performed using the Java desktop software (www.ingenuity.com) and canonical pathways were determined. The p-value associated with a pathway is a measure of the likelihood that the association between a set of focus genes in the experiment and a given process or pathway is the result of random chance; in general, a p-value  < 0.05 indicates a statistically significant value.Pathway analysis of transcripts with changed expression in C4-2B parental and C4-2B MDVR cells was performed using IPA  from Oncomine were analyzed and HSP70 expression in different Gleason score tumors was determined.xyz points with grid spacing of 0.375 Å and vina search space center was designated at dimensions : 17.3821, 28.7233, and 16.0554. AutoDock/Vina was employed for docking using protein and ligands information along with grid box properties in the configuration file. During the docking procedure, both the protein and ligands are considered as rigid. The results <1.0 Å in positional root-mean-square deviation (RMSD) was clustered together and represented by the result with the most favorable free energy of binding. The pose with lowest energy of binding or binding affinity was extracted and aligned with receptor structure. The obtained docked poses were analyzed with ADT using PyMOL.The X-ray crystallographic structure of HSP70 ATPase domain was retrieved from RCSB Database (PDB code: 1S3X). The Ligands (APO and VER) preparation and grid box creation were completed using Graphical User Interface program AutoDock Tools (ADT). AutoDock saved the prepared file in PDBQT format. AutoGrid was used for the preparation of the grid map using a grid box. The grid size was set to 50 × 50 × 50 The tumor samples were harvested through the University of California, Davis (UC Davis) central biorepository under an approved Institutional Review Board (IRB) protocol in Urology Department #GU001). The informed consent was obtained from all participating patients. Biopsy samples were taken from patients and immediately frozen into liquid nitrogen before the RNA extraction. Twenty-six tumors were classified into high Gleason score (≥8) groups, including 13 HSPC (hormone sensitive prostate cancer) and 13 CRPC (castration-resistant prostate cancer) samples  were randomized into six groups (seven mice per group) and treated as follows: (1) vehicle control , intraperitoneal (i.p.)), (2) enzalutamide ), (3) APO , (4) VER (15 mg/kg i.p.), (5) enzalutamide  plus APO , and (6) enzalutamide  plus VER . Tumors were measured using calipers twice a week and tumor volumes were calculated using length × width × width × 0.52. Tumor tissues, liver, and kidney were harvested and weighed after 3 weeks of treatment. Tumor tissues, liver, and kidney were paraffin embedded and H/E stained.All animals used in this study received humane care in compliance with applicable regulations, policies, and guidelines relating to animals. All experimental procedures using animals were approved by the Institutional Animal Care and Use Committee of UC Davis. CWR22Rv1 cells (3 million) were mixed with matrigel (1:1) and injected subcutaneously into the flanks of 4–5-week-old male C.B17/lcrHsd-Prkdc-SCID mice (ENVIGO). Tumor-bearing mice  and treated as follows: (1) vehicle control , (2) enzalutamide , (3) APO , and (4) enzalutamide  plus APO . Tumors were measured using calipers twice a week and tumor volumes were calculated using length × width × width × 0.52. Tumor tissues were harvested and weighed after 5 weeks of treatment. Serum was collected for PSA determination.To assess the effect of combination of HSP70 inhibitors with enzalutamide on the growth of PDX tumors, the LuCaP35 CR model was obtained from the University of Washington and established in the UC Davis Cancer Center. Briefly, 3–4 weeks C.B17/lcrHsd-Prkdc-SCID mice (ENVIGO) were surgically castrated. Two weeks later, ∼20 to 30-mmMouse blood from the LuCaP 35CR tumor model was collected and the serum was harvested. PSA levels were measured using a PSA ELISA Kit  according to the manufacturer’s instructions.Tumors were fixed by formalin and paraffin-embedded tissue blocks were dewaxed, rehydrated, and blocked for endogenous peroxidase activity. Antigen retrieving was performed in sodium citrate buffer  in a microwave oven at 1000 W for 3 min and then at 100 W for 20 min. Nonspecific antibody binding was blocked by incubating with 10% FBS in PBS for 30 min at room temperature. Slides were then incubated with anti-HSP70 , anti-Ki67 , or anti-AR-V7  at 4 °C overnight. Slides were then washed and incubated with biotin-conjugated secondary antibodies for 30 min, followed by incubation with avidin DH-biotinylated horseradish peroxidase complex for 30 min . The sections were developed with the diaminobenzidine substrate kit (Vector Laboratories) and counterstained with hematoxylin. Nuclear staining of cells was scored and counted in five different vision fields. Images were taken with an Olympus BX51 microscope equipped with DP72 camera.t tests for single comparisons or one-way analysis of variance (ANOVA) followed by the Scheffé procedure for multiple group comparisons. In the tumor growth experiments, size of the tumor at sacrifice serves as the primary response measure. The tumor growth and PSA across groups was analyzed by ANOVA. Concordance between AR-FL, AR-V7, HSP70, and HSP90 level in clinical patient samples was determined by Spearman rank correlation. p < 0.05 was considered statistically significant.Statistical analyses were performed with SPSS16.0. Raw data was summarized by means, standard deviations (SD), and graphical summaries and transformed if necessary to achieve normality. Data from the in vitro experiments are presented as means ± SD from three independent experiments. Differences between individual groups were analyzed by two-tailed Student’s Supplementary InformationPeer Review File


Arabidopsis is established beyond the initial pathogenic infection or is directly induced by treatment with salicylic acid or its functional analogs (SA/INA/BTH). NPR1 protein and WRKY transcription factors are considered the master regulators of SAR. Our previous study showed that NPR1 homologs in wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) regulated the expression of genes encoding pathogenesis-related (PR) proteins during acquired resistance (AR) triggered by Pseudomonas syringae pv. tomato DC3000. In the present examination, AR induced by P. syringae DC3000 was also found to effectively improve wheat resistance to Puccinia triticina (Pt). However, with more complex genomes, genes associated with this SAR-like response in wheat and barley are largely unknown and no specific WRKYs has been reported to be involved in this biological process. In our subsequent analysis, barley transgenic line overexpressing wheat wNPR1 (wNPR1-OE) showed enhanced resistance to Magnaporthe oryzae isolate Guy11, whereas AR to Guy11 was suppressed in a barley transgenic line with knocked-down barley HvNPR1 (HvNPR1-Kd). We performed RNA-seq to reveal the genes that were differentially expressed among these transgenic lines and the wild-type barley plants during the AR. Several PR and BTH-induced (BCI) genes were designated as downstream genes of NPR1. The expression of few WRKYs was significantly associated with NPR1 expression during the AR events. The transient expression of three WRKY genes, including HvWRKY6, HvWRKY40, and HvWRKY70, in wheat leaves by Agrobacterium-mediated infiltration enhanced the resistance to Pt. In conclusion, a profile of genes associated with NPR1-mediated AR in barley was drafted and WRKYs discovered in the current study showed a substantial potential for improving wheat resistance to Pt.Systemic acquired resistance (SAR) in  Arabidopsis, SAR is associated with accumulation of the plant hormone salicylic acid (SA) and transcriptional activation of pathogenesis-related (PR) genes  is a master regulator required for SAR. Upon pathogen infection or treatment with SA or its functional analogs 2,6-dichloroisonicotinic acid (INA) and benzothiadiazole (BTH), NPR1 translocates from the cytoplasm into the nucleus, where it interacts with the TGA2 transcription factor to promote expression of multiple PR genes (ArabidopsisNPR1 (AtNPR1) in other plant species  enhances their resistance against multiple pathogens  have been suggested to play important roles in the NPR1-mediated SAR. A previous genomic approach has identified several WRKYs, including AtWRKY18, AtWRKY58, and AtWRKY70, as regulatory nodes in the transcriptional network of SAR in Arabidopsis (OsWRKY3 and OsWRKY71 in rice were reported as upstream genes of the rice NPR1 homolog (NH1)  is an inducible form of plant defense that confers broad-spectrum immunity to secondary infections beyond the initial infection site. In R) genes . The AraPR genes . Overexpathogens . In Arabbidopsis . On the og (NH1) , 2007. A pathway .Arabidopsis and rice (Arabidopsis and rice (Blumeria graminis and Puccinia triticina (Pt) (PR genes were not induced by such treatments (WCI) and barley chemical-induced (BCI) genes, may be responsible for the enhanced resistance to various pathogens during BIR.Our previous analysis showed that the wheat NPR1 homolog (wNPR1) interacts with four members of the basic-region leucine zipper (bZIP) transcription factor family  . The intand rice . Howeverand rice . In earlina (Pt) . Other seatments . MoreovePseudomonas syringae pv. japonica (Psj) or Xanthomonas translucens pv. cerealis (Xtc) induced systemic immunity (SI) against secondary infection of Xtc in uninfected barley leaves  was induced in the area adjacent to the initial infection of P. syringae pv. tomato DC3000 in a PR genes-induced manner, but such resistance was not systemic  or suppressing barley NPR1 (HvNPR1-Kd) during the P. syringae DC3000-triggered AR  to the secondary pathogen systemic . The levsyringae . In our gered AR . HoweverP. syringae DC3000 also improved wheat resistance to P. triticina (Pt). In addition, the AR responses of the barley transgenic lines wNPR1-OE and HvNPR1-Kd to the Mo isolate Guy11 were evaluated. Further, transcriptome analysis of these transgenic lines during AR response was carried out. The downstream genes of NPR1 were identified based on their expression profiles. The inductions of several transcription factors displayed significant association with the expression of NPR1 during AR. Three differentially expressed WRKY genes, identified in our transcriptome database, showed a considerable potential for improving wheat resistance to Pt.In the present study, we established that AR induced by wNPR1 (wNPR1-OE) and a transgenic line with suppressed barley HvNPR1 (HvNPR1-Kd) under maize Ubiquitin promoter in the background of cultivar “Golden Promise” were derived from previous studies (P. syringae pv. tomato DC3000 infiltration and subsequent M. oryzae (Mo) inoculation. Briefly, P. syringae DC3000 was grown in KB medium with Rif antibiotics and was then diluted to OD600 = 0.5 in sterile water. Third leaves were inoculated with a 1-mL needless syringe by pressure infiltration of bacterial suspensions through the leaf abaxial surface. The borders of the infiltrated region were marked using a marker pen. Control seedlings were infiltrated in the same way with sterile water. After bacterial inoculation, seedlings were maintained at a constant temperature of 23°C to facilitate bacterial growth. Samples for RNA extraction were collected from regions adjacent to the infiltration from the transgenic lines and the wild-type plants 48 h post-inoculation (hpi) after a clear cell death phenotype triggered by P. syringae DC3000 infection was observed  containing 0.05% Tween-20 was dropped to the press-injured spots on the adjacent region and then wrapped with cellophane tape. The plants were kept in a mist chamber at 25°C in the dark for the first 24 hpi and then transferred to a growth chamber at 23°C and 80% humidity under a 16/8-h (light/dark) photoperiod. The inoculated leaves were photographed 5 days later. The size of the lesion caused by Mo on each leaf was measured. The assay for each treatment and phenotype combination consisted of at least six biological replicates. Data were transformed to restore normality and Dunnett’s test was performed using SAS software v9.4 .The same adjacent regions were also used for P. syringae DC3000 infiltration. Water infiltration served as negative control. Fully expanded secondary leaves from seedlings of the wheat susceptible line “Thatcher” were used in the experiments. Urediniospores of highly virulent Pt pathotype THTT were sprayed on the region adjacent to the P. syringae DC3000 infection area 2 days post-infiltration. Inoculated wheat plants were maintained in a moist chamber at 18°C for 16 h in the dark and were next transferred into a growth chamber with 16 h light at 23°C and 8 h darkness at 18°C. The phenotype of leaf rust was recorded at 10 dpi. The percentage of Pt sporulation area in the corresponding region for each leaf was determined using ASSESS (version 2.0) image analysis software for plant disease quantification from the American Phytopathology Society  and actin  as internal references. The qRT-PCR primers, designed for the selected PR genes , BCI genes , and NPR1 gene, are listed in Supplementary Table S1. Further, the amplification efficiency for each pair of primers was calculated using five fourfold cDNA dilutions . To ensure amplification specificity, dissociation curves for the temperature range from 60 to 94°C were generated for each reaction. The threshold values (Ct) generated from the Roche LightCycler 96 were used to quantify the relative gene expression using the Delta-Ct method as described earlier  following the manufacturer’s instructions. The first-strand cDNA was synthesized using a reverse transcription kit . Then, gene expression was quantified as described before , using t earlier . Two indHordeum vulgare genome sequence  were considered enriched. Next, heatmaps were generated by MeV software using FPKM values from the RNA-seq database. Hierarchical clustering analysis was performed by the MeV software, based on which the genes with similar expression patterns were clustered. A summary of GO annotation categories was generated using the GOLevel2 Counter in the TBtools software.Library preparation and RNA-seq were performed as described in the Illumina TruSeq RNA Sample Preparation Version 2 Guide, the Illumina HiSeq 1000 System User Guide (Illumina), and the KAPA Library Quantification Kit-Illumina/ABI Prism User Guide (Kapa Biosystems) by Novogene Co., Ltd. The sequencing run was performed on a HiSeq 1000 instrument. Then, the sequence reads were mapped on the Ensembl Genomes sequence  using Tosequence  with defsequence . Differesequence  and filt package . StatistWRKY genes were PCR-amplified using the primers listed in Supplementary Table S1. Initially, the PCR products were cloned into a pGEM-T easy vector  and then into a wheat transgenic vector pLGY02, which contained the maize (Zea mays) ubiquitin 1 promoter and T-DNA insertion site. The recombinant constructs were transformed into the Agrobacterium strain AGL1, and the wheat leaves were subjected to transient gene expression assays as previously described (Agrobacterium was grown overnight in yeast extract broth (YEB) medium supplemented with Rifampicin and Kanamycin. The bacterial pellets obtained after centrifugation were resuspended in an infiltration buffer containing 10 mM MES, 10 mM MgCl2, and 400 μM acetosyringone to an optical density of OD600 = 2.0. For wheat infiltration, the fully expanded secondary leaf of wheat seedlings was infiltrated using a 1-mL syringe without a needle. The border of the infiltration area was marked with a mark pen. Urediniospores of highly virulent Pt pathotype THTT were spray-inoculated 4 days post-infiltration. The inoculated leaves were photographed at 10 days post-inoculation. The percentage of Pt sporulation area in the infiltration region for each leaf was calculated using ASSESS software v2.0 (American Phytopathology Society) . Subsequently, the cDNA sequences of 10 selected escribed . Fresh ASociety) . The assP. syringae DC3000 in barley was considered as a SAR-like response providing broad-spectrum protection against subsequent pathogen challenge . The percentage of Pt sporulation area for each leaf was calculated using ASSESS software. Significantly more (P < 0.0001) promoted resistance to Pt was observed in the region adjacent to the P. syringae DC3000 infection area than in the mock control .AR triggered by hallenge . To elucMo isolate Guy11 was used to determine the extent of AR triggered by P. syringae DC3000 in a barley transgenic line overexpressing wheat wNPR1 (wNPR1-OE), a transgenic line with knocked-down barley HvNPR1 (HvNPR1-Kd), and wild-type plants . The third leaf of barley plants was infected by infiltration with P. syringae DC3000 or treated with sterile water as a mock control. Mo isolate Guy11 was inoculated in the region adjacent to P. syringae DC3000 infiltration area when a cell death was observed 2 days post-infiltration (dpi). Strong AR against Mo isolate Guy11 was established in the region adjacent to P. syringae DC3000 infection area in the wild-type plants . The size of the lesions caused by the Mo isolate Guy11 in the region adjacent to P. syringae DC3000 infection area was significantly (P < 0.05) lower than that in the mock control . The wNPR1-OE transgenic line had more pronounced resistance to Mo infection than the wild-type plants, even in the mock control . The AR triggered by P. syringae DC3000 in the HvNPR1-Kd transgenic line, was suppressed but not fully eliminated , possibly because NPR1 was not completely removed from the HvNPR1-Kd line. These results indicate that the AR to the Mo isolate Guy11, triggered by P. syringae DC3000, is mediated by NPR1.The NPR1-mediated AR in barley, we performed RNA-seq analysis on samples collected from the region adjacent to either P. syringae DC3000 or water infiltration area in the wNPR1-OE and HvNPR1-Kd barley transgenic lines and the wild-type plants. A number of 4–7 biological replicates for each treatment and genotype combination were sent for 6-Gb RNA sequencing (Supplementary Table S2). At least 46 million reads were sequenced (150-bp pair-end) from each sample and mapped on the Ensembl Genomes H. vulgare genome sequence with a total of 31,794 genes, including 7,583 “Novel” transcripts. A clear correlation between the gene expression levels of the biological replicates was observed . The abundance of accumulated transcripts was estimated using the fragments per kilobase of transcript per million mapped reads (FPKM) value. All raw data were uploaded to NCBI in BioProject PRJNA431836.To explore the gene regulation network during the PR genes were reported as downstream genes of NPR1 during the P. syringae DC3000-triggered AR in our previous study . We noticed that the transcript levels of HvPR1, HvPR2, HvPR3_Chit2a, HvPR5 , HvPR9, and HvPR13, were significantly associated with the expression of NPR1 as either significantly (P < 0.05) higher induced in the wNPR1-OE transgenic line or lower induced in the HvNPR1-Kd transgenic line . In contrast, the expression levels of PR5 (TLP1), PR15, PR16, PR17a, and PR17b showed induction by P. syringae DC3000 but in a NPR1-independent manner. Since a group of BCI genes were previously reported to be responsible for the BTH-induced resistance in barley (BCI genes in our database and found that HvBCI2 (the same gene as HvPR13) and HvBCI7 were regulated by NPR1 during the P. syringae DC3000-triggered AR . qRT-PCR assay was carried out to validate the gene expression data obtained from the RNA-seq database. Two independent transgenic lines for each of the wNPR1-OE and HvNPR1-Kd were used and the barley elongation factor HvEF1a (GenBank accession number Z50789) were employed as a reference gene. We found that the expression level of NPR1 in the wNPR1-OE and HvNPR1-Kd transgenic lines was significantly (P < 0.01) higher and lower, respectively, than that in the wild-type plants . In addition, the expression levels of six selected genes, including HvPR1, HvPR2, HvPR3_Chit2a, HvBCI1, HvBCI3, and HvBCI7, were measured by qRT-PCR. In the wild-type plants, significant (P < 0.01) inductions of HvPR1, HvPR2, HvPR3_Chit2a, and HvBCI1, were observed upon the P. syringae DC3000 treatment . Furthermore, the expression levels of HvPR1, HvPR2, HvPR3_Chit2a, and HvBCI7, were significantly (P < 0.05) upregulated in the wNPR1-OE transgenic lines by the P. syringae DC3000 treatment , which indicated their roles as downstream components of NPR1 during the AR response. On the other hand, the inductions of such downstream genes during the P. syringae DC3000-triggered AR were suppressed in the HvNPR1-Kd transgenic lines . Additionally, we used another reference gene, HvActin (GenBank accession number AK362208), to validate the results of our qRT-PCR assay for HvPR1 and found similar expression patterns .Since many of the us study , in the n barley , we examq-value < 0.05 and | log2foldchange| > 1, with gene annotation). Three types of DEGs were manually classified based on their possible roles in the NPR1-mediated AR . Type I DEGs were highly upregulated genes in the wNPR1-OE transgenic line after P. syringae DC3000 induction. A total of 24 Type I DEGs were designated from significantly upregulated genes based on the comparisons “OE_PST vs. OE_CK” and “OE_PST vs. WT_PST” . Several PR and BCI genes were annotated as Type I DEGs, including probable glucan 1,3-beta-glucosidase A (HvPR2), peroxidase A2-like (HvPR9), and thionin BTH7-like (HvBCI7). GO annotation for the Type I DEGs showed that the majority of these possible downstream genes of NPR1 during AR were annotated with “binding” and “catalytic activity” in the molecular function category, and with “metabolic process” and “response to stimulus” in the biological process category .DEGs in different comparisons, including “WT_PST vs. WT_CK,” “OE_PST vs. OE_CK,” “OE_PST vs. WT_PST,” “Kd_PST vs. Kd_CK,” and “Kd_PST vs. WT_PST,” were identified by DESeq2 . A total of 64 genes were classified into this group, including several genes encoding transcription factors, such as transcription factor JUNGBRUNNEN 1-like, probable WRKY transcription factor 48, and probable WRKY transcription factor 50. Compared with GO annotations for the Type I DEGs, more genes in this group were annotated with “cellular process” but not “response to stimulus” . A third group of Type III DEGs, including only nine genes, were shared DEGs from Type I and Type II groups .Type II DEGs were obtained and categorized into groups from significantly upregulated genes based on the comparisons “Kd_PST vs. Kd_CK” and “Kd_PST vs. WT_PST” . Since the naming system for the WRKY genes in the genera of Triticeae was confusing, a polygenetic tree was generated using sequences of all these 10 WRKY proteins and their homologs from Hordeum vulgare (Hv), Aegilops tauschii (At), Brachypodium distachyon (Bd), Triticum aestivum (Ta), Triticum urartu (Tu), and Sorghum bicolor (Sb) from the GenBank nr database . All WRKYs were temporally designated according to their closest homologs in relative plant species, such as HvWRKY4, HvWRKY6, HvWRKY17, HvWRKY19, HvWRKY20, HvWRKY31, HvWRKY40, HvWRKY64, HvWRKY70, and HvWRKY76.A total of 46 WRKYs for improving wheat resistance to Pt, the open reading frame (ORF) of each WRKY gene was cloned and incorporated into a pLGY02 vector . The recombinant vector was transformed into the Agrobacterium strain AGL1. The transformed Agrobacterium was infiltrated into the secondary leaves of wheat seedlings of the susceptible line “Thatcher,” and the infiltration area was marked with a mark pen. Urediniospores of the highly virulent Pt pathotype THTT were spray-inoculated 4 days post-infiltration. The phenotype of leaf rust was recorded 10 days post-inoculation . The percentage of Pt sporulation area in the infiltration region of each leaf was calculated using ASSESS software. Wheat with transient expression of TaPR1b (GenBank accession number HQ541962) was utilized as a positive control, whereas the untransformed Agrobacterium strain AGL1 was employed as a negative control. Although susceptible phenotypes were observed in all treatments, Pt sporulation in the leaves of the wheat with transient expression of TaPR1b and three WRKYs, including HvWRKY6, HvWRKY40, and HvWRKY70, were significantly (P < 0.001) reduced or delayed . The transient expression of the other seven WRKY genes, including HvWRKY4, HvWRKY17, HvWRKY19, HvWRKY20, HvWRKY31, HvWRKY64, and HvWRKY76, in wheat leaves exerted no positive effect on wheat resistance to Pt (Supplementary Table S5).To test the potential of the differentially expressed NPR1 has been reported as the master regulator of SAR in model plants of Arabidopsis and rice. Recent studies on NPR1 homologs in wheat and barley have provided the initial clue to understand the mechanism of SAR in these two plant species , suggested a potential use of NPR1-mediated AR in improving the resistance of Triticeae crops. The diminished AR to M. oryzae observed in the HvNPR1-Kd transgenic line indicated a key role of NPR1 during the AR triggered by P. syringae DC3000 infection . Finally, the resistance of the wNPR1-OE transgenic line to Mo was enhanced , providing valuable evidence that NPR1 can be utilized in improving barley resistance to Mo, possibly also to the recently emerged wheat blast disease . Further studies on HvPR13/BCI2 and HvBCI7 may provide initial evidence for understanding the relationship between AR and BIR. Interestingly, the expression levels of several PR genes, including HvPR3_Chit2b, HvPR5_TLP1, HvPR15, HvPR16, HvPR17a, and HvPR17b, were induced in a NPR1-independent manner, which indicated that other unknown regulators were functioning during the AR triggered by P. syringae DC3000.So far, a total number of 18 athogens . Severalgered AR . Anotherreatment . In the PR and BCI genes were categorized into Type I and Type III DEGs (Table 1 and Supplementary Table S4). The possible downstream genes of NPR1 during the P. syringae DC3000-triggered AR were mainly identified as Type I DEGs. Interestingly, we also discovered a large group of Type II DEGs (Supplementary Table S3) which were highly induced only in the HvNPR1-Kd transgenic line after P. syringae DC3000 infection. We speculated that some of them were negative regulators or upstream genes of NPR1 during the AR. Furthermore, the regulator network of NPR1 in barley during the P. syringae DC3000-triggered AR was initially established in our investigation .In this investigation, we classified three DEG groups based on their expression patterns. Several WRKY transcription factors in the NPR1-mediated AR. In model plants of Arabidopsis and rice, several WRKYs, including AtWRKY18, AtWRKY58, AtWRKY70, OsWRKY03, OsWRKY71, and OsWRKY45, have been suggested to play important roles in the SAR , a total of 10 HvWRKY genes with relatively higher induction in either the wNPR1-OE or HvNPR1-Kd transgenic line were selected for further functional validation.In addition, we checked the involvement of barley  the SAR . A totaln barley . It was HvWRKYs, including HvWRKY6, HvWRKY40, and HvWRKY70, exerted positive effects on wheat resistance to Pt . HvWRKY6_MLOC_78461 was a barley homolog of AtWRKY6_XP_020181741 , which had been reported to be associated with both senescence- and defense-related processes . In an earlier study, AtWRKY40 was found to be a repressor of antimycin A-induced mitochondrial retrograde expression and high-light-induced signaling , which exerted dual roles as negative regulators of SA biosynthesis and positive regulators of SA-mediated gene expression and resistance in Arabidopsis . In the present study, we have identified genes associated with the NPR1-mediated AR. Several PR and BCI genes were confirmed to be the downstream genes of NPR1. The expression levels of several WRKY transcription factors were significantly associated with NPR1 expression, which might be key components in the NPR1-mediated AR. Furthermore, it is noteworthy that three differentially expressed WRKYs identified in the current study showed potential for resistance improvement of wheat plants.In conclusion, XW conceived the original screening and research plans. XW and DL supervised the experiments. JG and WB performed most of the experiments. HL, JW, and XY provided technical assistance to JG. XW designed the experiments and analyzed the data. XW conceived the project and wrote the article with contributions of all the authors. DL supervised and complemented the writing.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.


This stage-specific upregulation of autophagy in SCs may be related to AR suppression, mitochondrial damage, lipid accumulation, and phagocytosis of apoptotic cells. The phenomenon may be an essential part of ensuring the viability of SCs and supporting germ cells in toxic environments.In a recent study, we reported that acute ethanol exposure enhanced autophagy in Sertoli cells (SCs) of adult rats. However, further research is needed to clarify the specific spermatogenic stage exhibiting the highest autophagic response, the mechanisms behind such specificity, and the related relevance to sperm. This brief report provides results indicating that stages VII–VIII (androgen-dependent or spermiation stages) of the spermatogenic cycle exhibited more marked autophagic response in acute-ethanol treated rats (ETRs) than other stages based on suppression of androgen receptor (AR), analysis of microtubule-associated protein 1 light chain 3 (LC3)  immunostaining in SCs, double labeling of LC3 and lysosomal proteins and electron microscopy. Ultrastructural observations and TUNEL method revealed a notable presence of phagocytosed apoptotic germ cells and retained sperm in SCs of ETRs at these specific stages—a finding rarely observed in control testes. In addition, PTEN-induced putative kinase 1 ( PINK1)  and giant lipid droplets were found to have accumulated in SCs of ETRs at same stages. Our data show novel findings indicating that stages VII–VIII of the spermatogenic cycle exhibit high levels of autophagy, specifically under stress conditions, as expressed by the term  Autophagy is a survival pathway for the clearance and recycling of damaged cellular components within autophagic vacuoles (AVs) upon exposure to various stressors such as hypoxia, oxidative stress, mitochondrial damage, and lipid droplet (LD) accumulation. This recycling of autophagic cargo provides sources of energy or building blocks for the synthesis of macromolecules ,2. MorphVarious roles played by autophagy have been recently reported in relation to Sertoli cells (SCs). First, the process is required for efficient clearance of apoptotic germ cells by SCs in mice based on LC3-associated phagocytosis (LAP) . Second,Excessive alcohol intake has been reported to enhance germ cell apoptosis, resulting in infertility problems via mechanisms related to oxidative stress, upregulation of inducible nitric oxide synthase (iNOS) and mitochondrial dysfunction ,5,6. TheWestern blot analysis of testicular lysates 24 h after a single intraperitoneal injection of ethanol (5 g/kg) in adult rats showed a statistically significant reduction of AR in ethanol-treated rats (ETRs) compared to the control group A,B. ImmuThe IHC information in As autophagy in SCs was reportedly triggered by enhanced germ cell apoptosis via LAP , the autautophagic stages. Second, this enhanced autophagic response in SCs relating to ethanol may be associated with AR suppression, mitochondrial damage, LD accumulation and enhanced phagocytosis of germ cells and retained sperm. Third, PINK1 accumulation in these SCs and the activation of mitophagy could be related to the Parkin signaling pathway. To the authors’ knowledge, this is the first report to show such findings in specific stages of spermatogenic cycle.This report details several novel findings. First, SCs of ETRs in stages VII–VIII exhibit high levels of autophagy, as expressed by the term The specific ultrastructural features of SCs in stages VII–VIII in normal adult rat testes have been reported in detail previously , with obAnother important specific characteristic of this stage range concerns AR. Stages VII–VII, or the spermiation stages, are known to be AR-dependent, because they exhibit the highest levels of AR expression in SCs under normal conditions and are more sensitive to androgen suppression by Leydig cell toxicants (such as EDS) and genetic or hormonal manipulation ,18,19,27As AR signaling from SC nuclei is essential for spermiation and germ cell maturation and survival ,27, the The current study showed the accumulation of numerous large LDs in SCs of ETRs, which may be related to enhanced phagocytosis of germ cells and RBs .® 488 (DI-3788) from Vector, CA, USA. A TUNEL kit  was used for apoptosis detection. Vectastain ABC Standard Kit (PK-4000) and ImmPACT DAB(SK-4105) from Vector were used for IHC. Donkey anti-rabbit IgG-HRP, Santa Cruz (sc-2077) was used for Western blot as secondary antibody.The following primary antibodies were used: rabbit anti-LC3B antibody (PM036) from MBL, Nagoya, Japan; rabbit anti-PINK1 (NB600-973) from Novus Biologicals; goat anti-pan-cathepsin (sc-6499), Rabbit anti-AR (sc-816) antibodies, goat anti-Actin (sc-1616) from Santa Cruz . For immunofluorescence, the following secondary antibodies were used: Alexa Fluor 594-conjugated secondary antibodies  and VectaFluor™ R.T.U. DyLightThe animals were given a single intraperitoneal dose of ethanol (5 g/kg) (this dose of ethanol represents a human binge drinking model) ,4, and aThe methods for immunohistochemical staining of AR, LC3 and PINK1 were performed according to the manufacturer’s recommendations and our recent study . From pat-test. p values of <0.05 were considered statistically significant.For quantification for LC3 immunostaining in SCs at stages I–VI, VII–VIII, IX–XI, and XII–XIV, 10–15 seminiferous tubules per stage group were used from ETRs and the control group. Using Adobe Photoshop, the tubules were captured and saved for computer analysis using Image J . The LC3 intensity in SCs were identified using the threshold feature of Image menu of the ImageJ program as reported by us  and othe® 488 were used as secondary reagents (30 min). The sections were observed under the Olympus BX41 immunofluorescence microscope after nuclear counterstaining with DAPI (blue color) (Vector).For double-labeling of LC3 and pan-cathepsin, we used a sequential method as previously reported ,3,4. FolTerminal deoxynucleotidyl transferase dUTP-mediated nick-end labelling (TUNEL) was performed according to the manufacturer’s protocols, as previously reported ,3,4. TUNUltrathin sections (70 nm) from blocks embedded in epoxy were cut, double-stained with uranyl acetate and lead citrate, and examined using an H-7650 transmission electron microscope. The ultrastructural features of apoptosis, autophagy and mitophagy were defined as reported by us and others ,36,37.In brief, after homogenization and centrifugation of whole testicular tissues, the supernatant was electrophoresed on 12% sodium dodecyl sulfate polyacrylamide gel and transferred onto a polyvinylidene difluoride membrane. Proteins were detected with the specific primary antibodies for AR and PINK1, and then with specific peroxidase-labelled secondary antibodies as previously reported . The relStage-specific enhancement of autophagic and mitophagic responses in SCs in response to ethanol toxicity is marked in stages VII–VIII, which may be related to AR suppression, accumulation of damaged mitochondria and LDs and phagocytosis of germ cells. This may be essential for supplying remaining germ cells with antiapoptotic factors such as lactate and for stimulation of spermiation, thereby maintaining fertility during these critical stages, specifically with exposure to various toxic insults such as alcohol abuse.


Rapid detection of Cd content in soil is beneficial to the prevention of soil heavy metal pollution. In this study, we aimed at exploring the rapid quantitative detection ability of laser- induced breakdown spectroscopy (LIBS) under the conditions of air and Ar for Cd in soil, and finding a fast and accurate method for quantitative detection of heavy metal elements in soil. Spectral intensity of Cd and system performance under air and Ar conditions were analyzed and compared. The univariate model and multivariate models of partial least-squares regression (PLSR) and least-squares support vector machine (LS-SVM) of Cd under the air and Ar conditions were built, and the LS-SVM model under the Ar condition obtained the best performance. In addition, the principle of influence of Ar on LIBS detection was investigated by analyzing the three-dimensional profile of the ablation crater. The overall results indicated that LIBS combined with LS-SVM under the Ar condition could be a useful tool for the accurate quantitative detection of Cd in soil and could provide reference for environmental monitoring. Soil is the most important part of the ecosystem, and plays an important role in agricultural production and human activities ,2. The rCurrently, atomic absorption spectrometry (AAS) , inducti2 (CIGS) absorber layer under the conditions of open air and Ar jet flow (25 L min−1), and the elements of Cu, In, Ga, and Se were analysed. The results showed that Ar had a great influence on the signal of Se I 196.090 nm, of which the spectral intensity was increased by about three times and the value of RSD decreased by 0.01 (from 0.045 to 0.035). Sarkar used [−1 to explore the signal enhancement effect of LIBS on uranium (U) in the vitrified simulated high level barium borosilicate waste glass matrix. The results showed that the spectral intensity of U in Ar was about five times higher than that in air. In summary, above studies showed that LIBS detection in Ar could enhance spectral signal, and had great potential for the rapid and accurate detection of elements. To the best of our knowledge, the LIBS technique has been applied to the determination of Cd in water [Laser-induced breakdown spectroscopy (LIBS) is an atomic analysis technique developed in recent years . Specifikar used  Ar at a in water , agriculin water ,33, fertin water , and soiin water , but theIn this paper, we used the simulated Cd-containing soils as samples to explore the quantitatively detection ability of LIBS for Cd in soil under the conditions of air and Ar, and the enhancement effect of Ar on LIBS signal was further analysed. The specific objectives of this research were to: (1) compare the spectral intensity and system performance under different gas conditions; (2) to build univariate and multivariate quantitative analysis models of Cd in soil under different gas conditions; and (3) to further compare the performance of models to explore the principle of LIBS signal enhancement of Ar.2 powder of 99% purity purchased from Aladdin Reagent Shanghai Pure Biochemistry Technology Co. Ltd. , was used to prepare different concentrations of CdCl2 solution  and distilled water was used as the solvent. Specifically, 10 g CRM soil powders were firstly added to the CdCl2 solution of different concentrations, and they were mixed evenly by a grinder . Then, the mixture was dried in the oven at 60 °C for 6 h. After the above steps, Cd-containing soil samples with 10 content gradients were prepared. The content of Cd in the soil samples were 0.22 mg·g−1, 0.45 mg·g−1, 0.67 mg·g−1, 0.90 mg·g−1, 1.12 mg·g−1, 1.35 mg·g−1, 1.57 mg·g−1, 1.80 mg·g−1, 2.02 mg·g−1, and 2.25 mg·g−1, respectively. Finally, 0.5 g dried powders from soil samples of each content were weighed, and pressed into tablets with 12 mm in diameter and 2 mm in thickness, using 10-MPa force for 60 s . Five pellets were prepared for each content. Thus, 50 soil tablets were used for LIBS experiments under the conditions of air and Ar, respectively.In this experiment, Cd-containing soil samples were prepared by adding the heavy metal element into the certified reference material (CRM) of soil (GBW07455), which was provided by National Institute of Metrology, P.R. China. Referring to the national soil heavy metal pollution grade standard of China, CdCl−1, respectively. Parameters under the condition of air were optimized at 120 mJ, 1.827 µs, 10 µs. The experiment was conducted in open air, so flow rate was not considered. After setting parameters, sample tablets were placed on the X-Y-Z stage, and the laser beam was adjusted to focus 2 mm below the sample surface to acquire LIBS spectra. In order to eliminate shot-to-shot fluctuation and obtain reliable datasets, the spectra of 16 spots with 5 times accumulation were collected, and the average of 80 spectra was recorded as the LIBS spectrum for each pellet. The experiment under the open air was done first, and then high purity Ar was passed into the sample chamber through the gas transmission tube to conduct the experiment under the condition of Ar. Instead of vacuuming, we directly passed a steady flow of Ar into the sample chamber for half an hour before the experiment to ensure an Ar atmosphere in the sample chamber. Besides, a steady flow of Ar was continuously passed into the sample chamber during the experiment under the condition of Ar.A self-built LIBS system used in this experiment is shown in Due to the matrix effect of the sample and the fluctuation of experimental parameters, noise and abnormal spectra might exist in the raw spectra of samples, which might influence the accuracy of data analysis. Thus, spectral pre-processing methods including wavelet transform (WT) and outlier rejection were used to eliminate the influence. WT is a widely used denoising method, which can effectively reduce the noise generated in the experiment . The speI means the intensity of the spectral line, and C means the concentration of elements to be analysed. The d means the function related to the element content, and the value of b can be 1 when the concentration of the analytical element is low and there is no self-absorption. Therefore, the calibration curve of the element can be fitted according to the intensity of the LIBS spectrum and the concentration of the corresponding element. Then the unknown concentration of the sample can be further calculated by the spectral intensity and the calibration curve. In addition, several indicators are adopted to evaluate the performance of the univariate model. The coefficient of determination for calibration (R2C) and prediction (R2P) reflect the prediction accuracy of the model, and the closer the value is to 1, the stronger the prediction ability of the model is. The root mean squared error for calibration (RMSEC) and prediction (RMSEP) reflect the prediction deviation of the model, and the smaller the value is, the better the model prediction performance will be. Besides, the limit of detection (LOD) is also a key indicator of evaluation. According to the definition given by international union of pure and applied chemistry (IUPAC), LOD means the lowest concentration obtained from the minimum analytical signal that can be reasonably detected by a particular analysis step. It reflects the sensitivity of the model, and a lower LOD represents a better detection method. The value could be calculated with the following equation:background means the standard deviation of the background intensities, and b means the slope of calibration curve.Univariate analysis is the most basic elemental quantitative analysis method in LIBS. Under certain conditions, the LIBS spectral intensity is proportional to the content of elements in the sample, as seen in the following equation: m is the regression vector of the PLSR model, m. According to Equations (2) and (3), an approximation LOD of the PLSR model could be calculated with the following equation [Partial least-squares regression (PLSR) is a multivariate linear analysis method, and is commonly used for the quantitative analysis of spectra ,43. Partequation ,52,53: is an optimized statistical learning method based on the standard SVM ,55. Due ng error . Detaileng error ,61. In oDesign Expert  was employed to design experiments and optimize experimental parameters. Andor SOLIS for Imaging  was used to collect LIBS spectra. Unscrambler × 10.1  and MATLAB R2009a  was utilized to process data and establish the chemometrics model. In addition, Origin Pro 8.0 SR0  was used to draw graphics.−1) as an example for analysis. The spectra were collected over the range from 211.92–232.90 nm, and 2014 variables were contained. According to the National Institute of Standards and Technology (NIST) database, three main characteristic lines of Cd element were identified, including Cd II 214.44 nm, Cd II 226.5 nm, and Cd II 228.8 nm. Due to the consistency of spectral trends among samples with different Cd contents, we only took the sample of medium content (1.12 mg·g−1) was taken as an example for analysis. The average value of five samples with a medium content for these three parameters were calculated, and the results are presented in Signal-to-background ratio (SBR), signal-to-noise ratio (SNR), and the relative standard deviation (RSD) are important parameters in spectral analysis, which directly reflect the detection ability and stability of the system . SBR is It was seen that three Cd characteristic lines had a consistent trend. The values of SBR and SNR under the condition of Ar was higher than those in air condition, and a reverse trend was presented by the value of RSD. The results indicated that the detection ability of LIBS and the stability of detection signal under the condition of Ar were superior to those in air condition. Comparing the three spectral lines of Cd, we found that the signal of Cd II 214.44 nm was weak, while the signals of the other two lines were relatively strong, with a high value of SBR in Cd II 226.5 nm and a high value of SNR in Cd II 228.8 nm. However, the value of RSD for Cd II 226.5 nm was large. After a comprehensive comparison, Cd II 228.8 nm was regarded as the most suitable for subsequent analysis.Before modeling, sample division was firstly conducted. Three samples of each content were assigned for calibration, and the rest was used for prediction. Thus, all soil samples were divided into a calibration set  and a predication set  with a ratio close to 2:1. Then, univariate models of peak intensity and Cd content for three Cd spectral lines were established by means of calibration curve. It was found that there was no obvious linear relationship between the spectral intensities of Cd II 214.44 nm and Cd II 226.5 nm and the corresponding Cd concentration in soil samples. The results were similar to the previous study of Li et al. ,64, whic2 in both calibration and prediction sets above 0.9. Besides, the values of RMSEC and RMSEP in the model under the condition of Ar were lower than those in air condition. In addition, according to Equation (2) mentioned above and the slope of calibration curve in Due to complex matrix effects of the soil and the rich spectral emission lines of elements, some important information might be lost in univariate analysis, affecting the accuracy of quantitative analysis. In contrast, the multivariate analysis method can effectively reduce the influence of matrix effects, and make full use of the spectral information to improve the accuracy and repeatability of quantitative analysis. Thus, multivariate analysis models including PLSR and LS-SVM, based on the whole collected band (211.92–232.90 nm), were built to quantitatively analyze Cd content in soil samples under the condition of air and Ar. In addition, variables with great contribution in the whole collected data set are conducive to the PLSR and SVM models. Since scores, x and y loadings, and regression coefficient reflect the contribution of the variable, variables with large value of these parameters played an important role in PLSR and SVM analysis. Furthermore, the sample partitioning method was the same as that used in univariate models.2 being greater than 0.94. Furthermore, it was worth noting that the model performance under the condition of Ar was slightly better than that in air condition, with R2 in both calibration and prediction sets over 0.97. Judging from the R2 of the model, the enhancement effect of Ar on the quantitative analysis of LIBS was not significant. This might arise from the fact that the quantitative prediction of the model was already very good under the condition of air, so the model performance was more difficult to increase despite the use of Ar for signal enhancement. Besides, according to Equation (4) and the regression vector of the PLSR model that displayed directly in the software of Unscrambler × 10.1, the LOD of PLSR for Cd under the conditions of air and Ar were 14.79 ± 0.47 ppm and 7.17 ± 0.17 ppm, respectively. In terms of detection sensitivity, the enhancement effect of Ar on the quantitative analysis of LIBS was very obvious. The elemental detection sensitivity was reduced by approximately half in the condition of Ar. In general, the results demonstrated the feasibility of quantitative detection of Cd by LIBS coupled with the PLSR model in the condition of Ar.Calibration and prediction results of the PLSR model are given in 2 in the prediction set under both air and Ar conditions were greater than 0.96. In particular, the model performance under Ar condition was perfect, with R2 in calibration and prediction sets reaching 0.999 and 0.988, respectively. However, although the model under Ar condition performed well, it was only slightly better than that under air condition, which was similar to the results of PLSR models. As for the LOD of LS-SVM model, its calculation method remained to be further studied. On the whole, the results indicated that LIBS combined with the LS-SVM model had a reliable prediction power for quantitative analysis of Cd in soil. Moreover, signals collected in Ar condition were more suitable for the on-line detection of Cd content in soil with an improved accuracy.2 of LS-SVM models under both air and Ar conditions were higher than that of the PLSR models and univariate models, and the trend was the opposite for the value of RMSEC and RMSEP. The LS-SVM model based on the spectra collected in the condition of Ar obtained the best result, with a high prediction accuracy close to one. As for the sensitivity of the model, compared with univariate models, Cd detection limits of PLSR models had been improved. In addition, the improving effect of Ar on the prediction accuracy of the univariate model was better than that of the other two models, indicating that Ar was more effective when the model had a relativity poor prediction performance. Therefore, it could be concluded that both chemometrics methods and signal enhancement techniques had influence on the quantitative detection performance of LIBS. Reasonable combination of chemometrics methods and signal enhancement techniques could greatly improve the LIBS quantitative detection capability. In this case, LIBS combined with the LS-SVM model and the signal enhancement technique of Ar realized fast and accurate detection of Cd content in soil. This work offered a potential method for the detection of heavy metals, and it could further provide guidance for environmental monitoring.In order to evaluate the reliability of the detection performance of LIBS under both air and Ar conditions, we compared the results of three models, and they are summarized in −1 under air and Ar conditions was taken as an example for comparative analysis, respectively, and the results are shown in Since LIBS elemental quantitative detection is based on the plasma generated from the laser ablation of samples, shapes of ablation craters were scanned by a three-dimensional contour scanner  to further analyze the effect of Ar on LIBS analysis. Multiple shots for each point of each sample were performed. It was found that the morphology of the ablation craters were approximately the same under the same experimental conditions, and the trend of parameters increasing with concentration were also consistent under Ar and air conditions. In order to explore the influence of Ar and be consistent with the above analysis, one three-dimensional profiles picture of the ablation crater in the soil sample with the content of 1.12 mg·g2 in both calibration and prediction sets more than 0.98. In addition, the influence principle of Ar on LIBS detection of Cd was analysed based on the three-dimensional profile of the ablation pit. It turned out that Ar could make laser focus more concentrated and ablate more quality of samples, which improved the LIBS signal intensity and quantitative detection ability. The overall results demonstrated that LIBS combined with the chemometrics method of LS-SVM in Ar condition could be a great tool for quantitative analysis of Cd in soil. With the perfect predictive performance, it was able to provide guidance for environmental monitoring. Additionally, portable instruments based on the method could be developed for further application.This research revealed that LIBS combined with chemomentrics methods in Ar condition had a perfect ability to determine Cd content in soil. Several aspects including spectral intensity, System performance, quantitative analysis models of Cd under air and Ar conditions were compared. It was proved that LIBS in Ar condition acquired a higher spectral intensity and obtained a better system performance. Besides, the results of quantitative analysis of Cd in Ar condition were better than those in air condition. Moreover, LS-SVM models were superior to the other two models. Thus, the LS-SVM model in the condition of Ar showed perfect ability in the quantitative detection of Cd in soil, with R


Traditionally, surgical pathology reports are narrative. These report types are prone to error and missing data; therefore, structured standardized reporting was introduced. However, the effect of synoptic reporting on the completeness of esophageal and gastric carcinoma pathology reports is not yet established.A population-based retrospective nationwide cohort study in the Netherlands was conducted over a period of 2012–2016, utilizing the Netherlands Cancer Registry for patient data and the nationwide network and registry of histology for pathology data.p < 0.01). Out of 21 standard items, 15 were significantly more frequently reported in synoptic reports.In total, 1148 narrative and 1311 synoptic pathology reports were included. Completeness was achieved in 56.4% of the narrative reports versus 97.0% of the synoptic reports  contains supplementary material, which is available to authorized users. Traditionally, surgical pathology reports are narrative, meaning they are written without a fixed form or structured outline . NarratiIn 1991, the idea of a synoptic pathology format was introduced, meaning that completing a standardized structured form based on relevant and up-to-date guidelines will create a pathology report . Since iThe main objective of this study is to assess the effect of SSR on the completeness of esophageal and gastric carcinoma pathology reports. We hypothesize that SSR will improve the completeness of reporting .Pathologisch-Anatomisch Geautomatiseerd Landelijk Archief; PALGA) [A population-based retrospective nationwide cohort study was conducted including surgically treated patients with primary gastric or esophageal cancer, diagnosed between January 2012 and January 2016. Patient data, as registered by the Netherlands Cancer Registry (NCR), were linked to corresponding pathology report data from the nationwide network and registry of histo- and cytopathology in the Netherlands  . Since nn = 45) were not included in further analyses.Surgical pathology reports concerning EC and GC types 15.0 to 15.9 and 16.0 to 16.9 respectively, according to the 10th edition of International Classification of Disease (ICD), were included in the study. The period 2014–2016 was selected, since both SSR and NR were used during that period, with SSR for EC and GC being gradually introduced in March 2014 in the Netherlands. Narrative pathology reports from the cohorts 2012 and 2013 were added as a separate reference group. The small number of SSR in this period of introduction , comparable to the guidelines of the College of American Pathologists’ (CAP) [The primary outcome was completeness, which was defined as the inclusion of all items in the pathology report as recommended by Dutch guidelines (s’ (CAP) , 8. Stans’ (CAP) , 12. StaDifferentiation grade is applied for grading squamous cell carcinomas and intestinal adenocarcinomas according to the WHO classification system . The iteCompleteness was also compared when pathology reports were further grouped into academic and non-academic centers regarding SSR.p values less than 0.05 were considered to be statistically significant.Statistical analysis was performed with the SPSS software package, version 24.0 . For dichotomous or ordinal variables, the Pearson’s chi-squared test or Fisher’s exact test was used if appropriate. All tests were two-sided, and p = 0.80).In total, 4838 pathology reports were included: 2379 (49.2%) reference, 1311 (27.1%) synoptic and 1148 (23.7%) narrative reports . Besides “number of lymph nodes” and “T stage,” which were comparable, all standard items were significantly more frequently reported in SSR. The difference in completeness between SSR and NR did not affect the distribution of reported histological tumor types in the EC group (p = 0.46): adenocarcinoma 890 (80.8%), squamous cell carcinoma 154 (14.0%), and other types 57 (5.2%). Regarding optional items, SSR resulted in a much higher percentage of reported “lymphovascular invasion” and “perineural invasion”.In total, 2858 EC pathology reports were included, 685 narrative and 806 synoptic and 1367 in the reference cohort. Completion was achieved in 450 (65.7%) narrative versus 789 (97.9%) synoptic reports (p < 0.01). “Differentiation grade” was significantly more reported in SSR compared with NR , whereas “invasion depth,” “number of lymph nodes,” and “histological tumor type” showed no significant difference between NR and SSR. Reporting of GC histological tumor type, consisting mainly of adenocarcinoma (864 (96.0%)), did not differ between SSR and NR; however, “subtype of AC” was less frequently reported with NR compared with SSR . The optional items, “lymphovascular invasion” and “perineural invasion” were much more frequently reported with SSR.In total, 1980 GC pathology reports were included, of which 463 narrative, 505 synoptic and 1012 in the reference cohort. In total, 197 (42.5%) NR were complete versus 483 (95.6%) SSR (Missing data in SSR was caused on one hand by software-related issues in the early stages of implementation (teething problems). For EC, 20%, and GC, 19% of the omitted items were due to software-related factors. Also, in the SSR software, differentiation grade is considered optional when neoadjuvant therapy was given (since grading is not possible in (sub-)total regression). On the other hand, the option of manually turning off several features, including standard items, remained through all development stages. It remains up to the pathologist whether he uses the complete protocol and/or the standard pathology conclusion or not.This study shows that SSR increases the completeness of surgical esophageal and gastric cancer resection pathology reports, in particular for items as tumor size, grade, location, tumor regression after neoadjuvant therapy. SSR also increases lymphovascular invasion and perineural invasion reporting. Essential items for staging including depth of invasion, number of (metastasized) lymph nodes and tumor type were present in almost all narrative reports, and only minimal improvements could be achieved by SSR. For GC reporting especially, SSR leads to an increase in the reporting of histological subtype of adenocarcinomas. This is clinically relevant, since poorly cohesive adenocarcinomas (WHO) show a different biological behavior resulting in different clinical patient outcomes .all pathologists with their histopathology reports. Although improved report completeness does not seem to have a direct impact on adjuvant treatment in GC and EC, as is the case in colorectal cancer—since the presence of lymph node metastases and pT4 tumor stage necessitate adjuvant therapy—this might very well change in the future. We do not claim that the introduction of SSR is the only or main factor for improved pathology reporting. Other factors, that may have influenced awareness among Dutch pathologists for EC/GC pathology reporting, are increased centralization of gastro-esophageal oncological surgery, comparative feedback by the Dutch Upper GI Cancer Audit (DUCA) (https://dica.nl/duca/) and monitoring during the multicenter gastric cancer CRITICS trial [The differences between NR and SSR, regarding pathology report completeness, are in line with the systematic review by Sluijter et al. . In accoCS trial .To our knowledge, this is the first report on a nationwide level with roughly 5000 pathology reports describing the influence of SSR on the completeness of EC/GC surgical pathology reports. The data originate from a nationwide database, which increases the power of the overall study, despite its retrospective nature.Furthermore, PALGA’s SSR software is considered to be level 6 on the 1–6 reporting level and quality scale developed by Shrigley et al., which scores pathology reporting on format, content and several other quality indicators . Level 1Despite comparing reporting type on academic and non-academic level, inter- and intra-pathologist reporting differences were not accounted for, which possibly could have affected the completeness of reports .In conclusion, our study has shown that SSR definitely improves the quality of surgical pathology reports of EC/GC and, therefore, should be part of standard patient care.ESM 1(PDF 354 kb)


The range of hourly subglacial CH4 flux rate through the discharge point was estimated to be 3.1 to 134 g CH4 hr−1. These measurements are the first observations of direct emissions of CH4 from the subglacial environment under the Greenlandic Ice Sheet to the atmosphere and indicate a novel emission pathway of CH4 that is currently a non-quantified component of the Arctic CH4 budget.During a 2016 field expedition to the West Greenland Ice Sheet, a striking observation of significantly elevated CH Disintegration of these cryospheric caps could lead to large increases in CH4 emissions in the Arctic with a significant feedback to the global climate system3. Direct evidence of the occurrence, magnitude and temporal extent of cryospheric CH4 emissions are currently derived from Arctic wetlands4, lakes6 and sub-marine CH4 sources7. Subglacial sediments and glacial meltwater have been shown to hold the potential for CH4 production and emission11, due to anaerobic decomposition of organic carbon12 by methanogenic archaea. This subglacial CH4 may subsequently be oxidized by methanotrophs facilitated by atmospheric oxygen (O2) or O2 release from basal ice melting11. Reservoirs of CH4 hydrates have been found beneath ice sheets15 of which the future stability may change due to accelerated melting and marginal thinning of the ice sheet leading to potential emissions of CH4 to the atmosphere. These studies suggest that subglacial environments could be active components of the Earth’s CH4 cycle. However, observations of direct emissions of subglacial CH4 have so far not been documented and the importance of subglacial CH4 for cryospheric CH4 release in the Arctic thus remains unknown.Permafrost and glaciers have been hypothesized to function as important caps of methane  and varied between 5.4 and 31.7 ppm  from 380 to 450 ppm. CO2 concentrations above the ambient level occurred with the highest CH4 concentrations on August 25th and 26th  and CO2 (range 0.21–1.49 ppm) concentrations were observed  than the natural fluctuations of the atmospheric background level CH4 and CO2 measured on site with a portable CH4 and CO2 analyzer . The fluctuations indicate that the subglacial CH4 and CO2 is mixed by air with lower concentrations, which likely is atmospheric air entering the subglacial system via surface moulins or other pathways which connects the subglacial system to the atmosphere. A net emission of CH4 from the subglacial meltwater to atmosphere was also measured directly  from the sediment at the edge of the glacier  and wind tunnel experiments  microbial and/or thermogenic gas from the subglacial domain1 which could be formed and stored under the Ice Sheet in the presence of a gas-hydrate stability zone15. Following entrainment in the subglacial water this old CH4 could be released following degassing of saturated subglacial meltwater in a similar process as described in Dieser et al.8. Alternatively, the emitted CH4 could be a product of more recently in situ produced biological CH4 from subglacial sediments18 or intermediately aged CH4 formed in carbon containing sediments capped during neoglacial readvances3. Finally, the possibility exist that the emitted CH4 could be a combined product of mentioned sources, which could be transported to the emission point via either running meltwater at the bedrock-glacier bed interface or as part of a deeper groundwater aquifer below the Isunnguata Sermia Glacier19. A plausible mechanism for the observed CO2 sink is the dissolution of CO2 in undersaturated meltwater resulting in a net uptake of atmospheric CO220.The highly elevated CH4 and CO2 could be (1) caused by venting of the subglacial drainage system if atmospheric air entered the subglacial system due to alternating surface meltwater volumes. This could push out any gas that had accumulated in non-deformed englacial cavities through to the subglacial drainage system resulting in a short-lived but intense period of emissions. In this context, the glacial deformation of the meltwater drainage system will likely determine releases of gases to the atmosphere. Alternatively, (2) continuous emissions extending over the entire melt season could be due to a constant degassing of subglacial meltwater at the margin. This implies also that the subglacial emission would be tightly linked to the meltwater volume and the coupling between climate and supraglacial melting. Finally, obtaining data on the composition of C-isotopes in the emitted CH4 and CO2 will shed light on the origin of the emitted C-gases.Future research efforts could be guided by two hypotheses focusing on the interrelations between meltwater volumes and glaciological dynamics. Thus, the release of subglacial CH4 and CO2, the mechanism of release and the limited extend of the measurement period, our measurements present the first evidence of a new pathway for direct interaction between the subglacial carbon cycle below the Greenland Ice Sheet and the atmosphere through the direct emission of CH4 and CO2. However, caution should be taken before drawing unjustified conclusions about the importance of subglacial CH4 emission in the Arctic CH4 budget and potential climate impact. Improving our understanding of the overall importance of subglacial CH4 emissions for the Arctic CH4 budget is therefore to expand the documentation of the spatial and temporal occurrences of subglacial emissions along the Greenland Ice Sheet. Also, further investigation into the release mechanism from the source area(s) can help resolve whether expected future increases in meltwater runoff due to increased surface melting and thinning of the ice sheet in a warming climate will affect the magnitude of subglacial CH4 emissions.Despite these uncertainties in the origin of subglacial CH22 as well as drilling projects to assess groundwater chemistry below the Isunnguata Sermia Glacier23.The study site is located at a lateral subglacial meltwater discharge point on the southern flank at the terminus of the Isunnguata Sermia Glacier at the western margin of the Greenland Ice sheet (67°09′16.40′′N 50°04′08.48′′W) Fig. . The sit4 and CO2 concentrations in the subglacial air streams from the air-filled ice cavities took place in the period August 23rd to 26th 2016. The 3-dimensional shape of the subglacial cavity was highly irregular, but the cross-section area  the ice sheet advanced again reaching a maximum position around 1850 AD with the maximum extent of the edge of the Isunnguata Sermia approximately 50–200 meters beyond its current position23. The Isunnguata Sermia Glacier and the surrounding glaciers are underlain by granodioritic gneiss with no or only little sediment or organic material21. The glacier is warm based with an annual ice flow of 150–200 meters and surface meltwater reaches the base of the glacier21. The meltwater at the discharge point has been characterized as acidic (pH between 5.82–6.53)22 and poorly mineralized and may represent an outlier in terms of the pH of the subglacial meltwater24. However, the reported range in pH values of the subglacial meltwater with a seasonal average of 6.8 ± 0.5 at a nearby subglacial meltwater discharge point8 are within the range of typical pH values for silica-bedded glaciers and ice sheets (5.1 to 7.8)24. Borehole geochemistry at the site suggests that glacial meltwater extends deep in bedrock fractures below the Isunnguata Sermia Glacier and that groundwater below the permafrost is flowing away from the glacier margin23.Continuous permafrost extending to 350 meters below the surface has been reported at the study areaIn situ concentrations of CH4 and CO2 of the subglacial air were measured using a portable greenhouse gas analyzer based on state-of-the-art cavity ring-down spectroscopy with a measurement precision of 3 ppb and 0.4 ppm for CH4 and CO2, respectively and a sampling frequency of 1 hz . The analyzer was connected to a flux chamber via a PVC tube (4 meter) which was deployed under the following ways: (1) the open chamber was lowered into the opening of one subglacial ice cavity  thered Fig. , (3) thered Fig.  and (4) red Fig. . Air temin situ observation of a smoke fan placed directly in the air filled cavity in the ice with a verification experiment in the laboratory using a small-scale wind tunnel with smoke injection. The general assumption was that movement of smoke when entrained in moving air in the ice cavity would be identical to movement of smoke entrained in moving air in a wind tunnel. The wind tunnel was constructed using a circular array of parallel straws to create laminar flow placed in the inlet end of a cardboard tube (inner diameter 10 cm). At the outlet end of the tube, a 12 V fan generated a laminar air flow that could be varied by controlling the power of the fan with an adjustable power supply. The flow velocity inside the tube was measured with a hot wire anemometer . Generated wind speeds in the tunnel ranged from 0.2 to 1.2 m s−1. Details on the wind tunnel setup and test is presented in Supplementary Material.The velocity of the air flow in the subglacial cavity was estimated by combining in situ smoke movement in the air filled cavity in the ice was compared with observations of the smoke fans in the laboratory under wind speeds of 0.2, 0.5 and 1.2 m s−1 . This approach provided a best estimate of the in situ velocity of air flow in the subglacial cavity, and indicated that air speeds in the subglacial cavity reached at least 1.2 m s−1 and probably exceeded this value. We thus estimated that the likely range of air flow velocities in the subglacial cavity had a flow range between 0.2–2 m s−1 which was used for the estimation of the subglacial CH4 and CO2 flux rates.Video footage of 2 (g m−2 h−1) were calculated combining a constant air flow rate through a 1 m2 cross-section area of the subglacial cavity and the measured CH4 and CO2 concentrations over a one hour measurement period  of CO2 or CH4, ῡ is the wind speed (m s−1), A is the cross sectional area (m2), Mv is the molar volume (m3 mol−1), Ta is the air temperature (°C) measured in the cavity, M is the molar mass of CO2 or CH4 (g mol−1), the multiplier 3600 converts the flux to hourly values and the constant 10−6 converts the flux from µg to g CO2/CH4.Cumulative hourly flux rates of subglacial and CO g m−2 h− were calSupplementary informationSupplementary video