This study mainly observes changes in perioperative mineral bone metabolism‐related indicators and inflammatory factors in patients with secondary hyperparathyroidism (SHPT), and analyzed the correlation between mineral bone metabolism‐related indicators and inflammatory factors.Clinical data were collected. The study detects mineral bone metabolism‐related indicators and inflammatory factor of perioperative patients with SHPT before and 4 days after operation. The production of high‐sensitivity c‐reactive protein (hs‐CRP) in human hepatocytes cells (LO2 cells) stimulated by different concentrations of parathyroid hormone‐associated protein was detected by enzyme‐linked immunosorbent assay, reverse‐transcription polymerase chain reaction (RT‐PCR), and western blot.The levels of mineral bone metabolism‐related indicators and hs‐CRP in SHPT group were significantly higher than those of control group. After operation, serum calcium, serum phosphorus, iPTH, FGF‐23 decreased, and the level of osteoblast active biomarkers increased, while the level of osteoclast active biomarkers decreased. The levels of hs‐CRP decreased significantly after operation. With the increase of PTHrP concentration, hs‐CRP level in supernatant of LO2 cells decreased first and then increased. RT‐PCR and western blot shows the same trend.Parathyroidectomy can significantly improve bone resorption and inflammation in SHPT patients. We speculate that there may be an optimal range of PTH concentrations to minimize inflammation in the body. Parathyroidectomy can significantly improve bone resorption and inflammation in secondary hyperparathyroidism (SHPT) patients. We speculate that there may be an optimal range of parathyroid hormone (PTH) concentrations to minimize inflammation in the body. The greatest number of adults living with CKD were in China (up to 159.8 million) and India (up to 140.2 million), collectively having 69.1% of the total number of adults with CKD in the region.Abnormal mineral bone metabolism begins in early stages of CKD and finds its maximum expression in stages 4 and 5.Parathyroid hormone (PTH) is synthesized and secreted by the parathyroid gland. Under normal circumstances, calcium ions in extracellular fluid bind to calcium‐sensitive receptor (CASR) in the plasma membrane of parathyroid cells to reduce the secretion of PTH.Microinflammatory state is a noninfectious, persistent, chronic immune inflammatory response centered on the release of circulating proinflammatory cytokines. Chronic inflammation, oxidative stress, and mitochondrial dysfunction play key roles in the progression and pathophysiology of CKD.Current studies have mainly analyzed the relationship between abnormal mineral bone metabolism indexes and microinflammatory state in patients with different stages of CKD or patients who have entered dialysis treatment stage, but unfortunately the results are inconsistent, and there are no reports regarding perioperative SHPT patients as research objects. Most studies have suggested that PTH is correlated with the inflammatory state and oxidative stress of the body.This study mainly observes the correlation between the perioperative mineral bone metabolism related indicators and inflammatory factors in patients with refractory SHPT, and further verify whether mineral bone metabolism‐related indicators involved in the regulation of inflammatory cytokines by cell in vitro experiments, to provide the theory basis for the diagnosis and treatment of CKD‐mineral and bone disorder (CKD‐MBD), and to improve the patient survival rate and quality of life.22.1A total of 47 patients from Henan Provincial People's Hospital who needed to be hospitalized for parathyroid resection due to refractory secondary hyperparathyroidism from 2018 to 2019 were selected, and 20 healthy people from the same period were selected as the control group. Clinical data of SHPT group were collected, including gender, age, body mass index, hemoglobin, albumin, total cholesterol, triglyceride, hemopoietin (EPO), ferritin, serum calcium, serum phosphorus, and serum iPTH. Fasting blood was collected preoperatively (the first day after admission) and 4 days after surgery, and centrifuged at room temperature  within 30 min. Serum and plasma were collected and divided into 200 μL centrifuge tubes, marked, and placed at −80°C for later use. Vein blood samples, age, height, weight, and other data of the control group were collected.2.2(1)Under regular dialysis, HD patients received heparin‐free dialysis once within 24 h before surgery; peritoneal dialysis (PD) patients were given continuous nonbedridden abdominal dialysis 24 h before surgery.(2)Before skin incision after general anesthesia and immediately after surgery , venous blood of the patients was collected 10 min after surgery and 20 min after surgery, and immediately sent to the isotope room for serum iPTH detection. The criteria for successful surgery were as follows: Serum iPTH level decreased by at least 82.9% 10 min after surgery or 88.9% 20 min after surgery compared with before surgery,2.3Reference range of relevant indicatorsThe reference values of BAP (IDS) were 3.27–19.27 μg/L. The reference values of PINP  were 30.40–65.20 μg/L; the reference value of CTX‐I  was 0.10–0.71 μg/L. The reference value of TRAP‐5b  is 1.18–4.02 U/L. The reference value of iPTH is 12–88 pg/mL; the reference value of FGF‐23 (Immutopics) is 21–82 RU/mL; the reference value of CRP is 0–10 mg/L.2.4−2, 10−1, 1, 10, and 102 ng/mL) was added. The blank control group was set to add the same amount of culture medium. Different groups were placed simultaneously in incubator (containing 5% CO2) at 37°C for 24 h, and then the supernatant and cells were collected. The levels of inflammatory factor hs‐CRP were determined by enzyme‐linked immunosorbent assay (Elabscience) and reverse‐transcription polymerase chain reaction (RT‐PCR) , western blot .It observes the effect of different concentrations of PTHrP (PeproTech) on the expression of inflammatory factors in LO2 cells. Well‐grown LO2 cells were cultured with culture medium  to 60%–70%, then the medium was updated and 20 μL of PTHrP at different concentrations (102.5X ± S), and the data conforming to nonnormal distribution was expressed as quaternary ). The independent sample t test was used for the comparison between the two groups conforming to the normal distribution, while the rank sum test was used for the comparison between the two groups conforming to the nonnormal distribution. Qualitative data were tested by χ2 test. Spearman or Pearson analysis was used for correlation analysis, and p < .05 was considered statistically significant.Statistical software SPSS23.0 was used to conduct statistical analysis on the data. Shapiro–Wilk test was used to identify whether variables are normally distributed. The measurement data conforming to normal distribution was expressed as mean ± standard deviation (33.13.1.1p < .001). Forty‐seven patients in the SHPT group were dialysis aged (7.11 ± 2.84) years, including 43 patients with HD and four patients with PD. The levels of hemoglobin and serum albumin were generally low. The levels of total cholesterol and triglyceride were within the normal reference range. Erythropoietin was high in the normal range; Ferritin levels were above the normal range; the levels of alkaline phosphatase, serum phosphorus, serum calcium, iPTH, FGF‐23, PINP, BAP, CTX‐I, and TRAP‐5b were significantly increased, as detailed in Table There was no significant difference in age and sex composition between SHPT group and control group. Body mass index in SHPT group was significantly lower than that in control group p < .00. Forty‐s3.1.2r = .558, p < .001) and ALP . Serum iPTH was also positively correlated with PINP , BAP , CTX‐I , FGF‐23 , hs‐CRP . FGF‐23 was associated with dialysis age , P , hs‐CRP , See Table Correlation analysis of iPTH, FGF‐23, and clinic data in SHPT patients. Preoperative serum iPTH of SHPT patients was positively correlated with dialysis age , and there was also a positive correlation between PINP and CTX . As shown in Figure Correlation analysis of preoperative bone metabolism markers in SHPT patients: There was a positive correlation between BAP and TRAP‐5b in SHPT patients (3.23.2.1p < .001). Serum BAP level was significantly higher than that before surgery (p = .013), serum PINP had an increasing trend compared with that before surgery, and the difference was not statistically significant (p = .377) as shown in Table After PTX, serum phosphorus, serum calcium, iPTH, FGF‐23, CTX‐I, and TRAP‐5b were lower than those before PTX  (mg/L) before operation to 2.67  (mg/L) after operation, 3.33.3.1The expression levels of inflammatory factor hs‐CRP in the supernatant of the PTHrP stimulation group were firstly decreased and then increased, and the inflection point of the level of hs‐CRP in the supernatant appeared when the PTHrP stimulation concentration was about 1 ng/mL, as shown in Figure 4Lancet published the stream survey data on CKD, which showed that as of 2017, CKD patients in the world were nearly 700 million, accounting for 9.1% of the global population, and China had 132.3 million patients, ranking first in the world.Changes in bone metabolism in patients with SHPT can lead to renal osteodystrophy. Bone biopsy is the gold standard for diagnosis and evaluation of renal osteodystrophy, but it has not been widely used in clinical practice.The study showed that iPTH was positively correlated with PINP, ALP, BAP, and CTX‐I, and that BAP was positively correlated with TRAP‐5b, and PINP was positively correlated with CTX, indicating that iPTH promoted bone formation and also participated in bone resorption, and the activities of osteoclasts and osteoblasts were simultaneously increased in SHPT patients. A domestic study found that there was a positive correlation between iPTH and ALP in SHPT patients, as well as between ALP and TRAP‐5b, and the mechanism of osteoblast‐osteoclast coupling regulation in refractory SHPT patients with high transport bone disease was basically consistent with the results of this study.Microinflammatory state always accompanies CKD and is involved in the process of all‐cause death in patients with CKD.At present, Few studies have been conducted on mineral bone metabolism‐related indexes and inflammatory factors in kidney diseases, and the results are inconsistent.Clinically, for patients with SHPT, it is difficult to be controlled by drugs, surgical excision of the parathyroid gland (PTX) is usually adopted, which is a highly effective treatment method, which can improve the clinical symptoms of patients and reduce the risk of cardiovascular and all‐cause mortality in SHPT patients.To further explore the relationship between inflammatory factors and mineral bone metabolism‐related indicators iPTH, we conducted in vitro experiments for further verification. Studies have shown that there are receptors for PTH on the surface of liver cells. CRP is produced by liver cells.There is inflammation in CKD and SHPT patients, and abnormal bone metabolism in SHPT patients. PTH is related to bone formation and bone resorption, and high concentration of PTH is positively correlated with hs‐CRP. Cell experiments suggest that there may be an optimal concentration of PTH to minimize inflammation. Therefore, we speculate that the inflammation and bone metabolism of SHPT patients can be improved by controlling serum PTH level, and controlling inflammation can also delay the progression of CKD and SHPT. For CKD patients with obvious bone pain, nonsteroidal anti‐inflammatory drugs may be used to control the body's inflammation.The study still has some limitations. The sample size still needs to be expanded. And serum hs‐CRP level needs to be detected at low concentration of PTH in patients with SHPT. Due to poor compliance of patients, follow‐up of enrolled patients was difficult to be advanced, and the corresponding specimens were not retained to re‐detect the levels of bone metabolism‐related indicators and inflammatory factors and conduct statistical analysis. Subsequent experiments such as liver cell PTH receptor antagonist are still needed in the in vitro experiment.5In summary, the production of inflammatory factor CRP in SHPT patients is related to mineral bone metabolism indicators. PTH is involved in bone formation and bone resorption, and PTX can significantly improve bone resorption and inflammation state in SHPT patients. In addition, too high or too low PTH level can lead to increased inflammation level, we speculate that there may be an optimal range of PTH concentration to minimize inflammation level in the body. In the future, we still need to further study the specific regulation mechanism of PTH on inflammation, so as to provide theoretical basis for reducing patients' complications and improving survival rate.All authors have read and approved the submission of the manuscript.Lei Yan: Conceptualization (lead); writing—original draft (lead); formal analysis (lead); writing—review and editing , funding acquisition . Qiuyue Xiong: Writing—original draft (supporting), investigation . Qin Xu: Writing—original draft (supporting). Pengru Ren: investigation . Tiantian Li: investigation . Huixia Cao: Methodology (lead); writing—review and editing ; formal analysis (supporting); funding acquisition . Fengmin Shao: Conceptualization (supporting), methodology (supporting), writing—review and editing , project administration (lead).All patients signed the written informed consent. All procedures were approved by Medical Ethics Committee of Henan Provincial People's Hospital (No. 2020.206).


As a nucleolar protein associated with ribosome biogenesis in multiple cancer types, PES1 has been reported to be overexpressed, promoting cancer cell proliferation and invasion. However, in head and neck squamous cell carcinoma (HNSCC), the role of PES1 on the prognosis and immune infiltration remains unknown.Multiple databases and qRT‐PCR evaluated the expression of PES1 in HNSCC. The prognostic potential of PES1 in HNSCC patients was analyzed by Cox regression and Kaplan–Meier curves. Then, we used LASSO regression and stepwise multivariate Cox regression to construct the PES1‐related risk assessment model. In addition, the association between PES1 and tumor immune microenvironment and drug sensitivity was explored by R packages. Finally, we used cell function assays to explore in HNSCC if PES1 influences tumor growth and metastasis.PES1 was significantly up‐regulated in HNSCC and closely correlated with HPV status, tumor stage, clinical grade, and TP53 mutation status. Survival analysis suggested that PES1 is associated with worse survival outcomes, acting as an independent prognostic indicator for HNSCC. Our model also performed well in terms of prognosis prediction. Furthermore, tumor‐infiltrating immune cells and antitumor drug susceptibility were negatively related to PES1 expression. Functionally, as for HNSCC cell lines in vitro, the knockdown of PES1 could inhibit proliferation, migration, and invasion.We have demonstrated that PES1 may be a promoter of tumor growth. PES1 holds excellent promise as a novel biomarker to assess the prognosis of patients with HNSCC and may guide immunotherapy. Flow chart of the present study. The TCGA‐HNSCC cohort was used as the exploration set, and samples from GSE13601, GSE25009, GSE30784, GSE41613, and GSE65858 were used as the validation sets. First, PES1 expression was compared between normal and carcinoma tissues and assessed the relationship of PES1 expression with the clinical feature of HNSCC patients. Subsequently, we evaluated the prognostic role of PES1 in HNSCC patients and established a PES1‐related risk model. Next, we comprehensively analyzed the immune infiltration landscape of HNSCC using multiple algorithms. Finally, we used cell function assays to explore if PES1 influences tumor growth and metastasis in HNSCC. We hope that PES1 can serve as clinical guidance for HNSCC patients.22.1http://timer.cistrome.org/) to PES1 expression in pan‐cancer.http://ualcan.path.uab.edu/analysis.html), we comprehensively analyzed PES1's expression in different clinical subgroups, including TP53 status, HPV status, nodal metastasis status, individual cancer stage, tumor grade, and gender, age, race.We performed TIMER2 (2.2http://gepia2.cancer‐pku.cn/) and Kaplan–Meier plotter  plot the Kaplan–Meier survival curves of PES1.GEPIA2.0 (2.3http://www.linkedomics.org/), the HNSCC cohort from TCGA performed a Co‐expression analysis of PES1.p‐value <0.05 were considered co‐expressed genes by using the Pearson correlation test. Based on the median expression value of PES1, we divided the TCGA HNSCC samples into the high‐expression and low‐expression groups. We used the “limma” R package between two groups to identify differentially expressed genes (DEGs), with the filter |logFC| > 1.0 and p‐value <0.05. PES1‐related genes are the set of co‐expressed genes and differentially expressed genes.Using LinkedOmics  and Gene Set Variation Analysis (GSVA) were used to explore PES1‐associated pathways and phenotypes and to compare biological functions between patients with high and low PES1. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) gene sets were obtained from the licensed portal. The subsets “c5.go.v2022.1.Hs.symbols.gmt” and “c2.cp.kegg.v7.4.symbols.gmt” were downloaded from the Molecular Signatures Database (MSigDB) to evaluate oncogenic or tumor‐associated pathways in HNSCC, and the limma, clusterProfiler, and GSVA packages in R were used for functional analysis.2.5We conducted a univariate Cox regression analysis to obtain survival‐related PES1 genes. And then, we used stepwise multivariate Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression to establish a risk assessment model. Then, we calculated the Akaike information criterion (AIC) values for each attribute on the 5‐year receiver operating characteristic (ROC) curve to assess the cut‐off point high‐ and low‐risk scores. The “survival ROC,” “Survival,” and “Survminer” packages were utilized to evaluate the capability of the model's prediction.2.6We used acknowledged methods to calculate the immune infiltration level of the patients with HNSCC, such as the CIBERSORT‐ABS, EPIC, MCPCOUNTER, QUANTISEQ, TIMER, XCELL, and then evaluated the relationship between the expression of PES1 and immune infiltration cell.To predict the immune response of PES1 to immunotherapy, the TIDE database was used to calculate TIDE scores and immune response rates for high‐PES1 and low‐PES1 subgroups, classified by their median expression. Patients with a higher TIDE score will have a higher chance of immune rejection, indicating a lower likelihood of benefiting from immunotherapy.2.7To evaluate the impact of PES1 in the clinic for HNSCC treatment, the half‐maximal inhibitory concentration (IC50) of chemotherapeutic drugs in patients with HNSCC was figured by the “pRRophetic” R package based on anticancer drug sensitivity information from the GDSC project.2.8Twenty‐seven pairs of quickly frozen HNSCC and surrounding healthy tissue were obtained from patients through the operation. Before the procedure, all experimental patient samples received no other therapies, and a thorough pathologic analysis validated all HNSCC tissues. Each patient signed a written informed permission form, and the Medical Ethics Committee approved the study at Anhui Medical University's Affiliated Stomatological Hospital. Each method was conducted as per appropriate regulations and guidelines.2, all these cell lines were cultured at 37°C.HNSCC cell lines SCC4, SCC9, CAL27, HN4, HN6, and human normal oral epithelial keratinocytes (HOK) were purchased from Ninth People's Hospital Affiliated with Shanghai Jiaotong University School of Medicine. These cell lines were subjected to STR profiling and tested for mycoplasma contamination every 3 months. These cell lines were saved in DMEM  supplemented with 10% fetal bovine serum , 1% penicillin, and streptomycin (NCM). Moreover, in a humidified incubator containing 5% CO2.9We used Thermo Fisher Scientific's TRIzol reagent (USA) to extract total RNA from tissues/cell lines. And then, we used a NanoDrop Spectrophotometer  to determine the concentration and purity of RNA. We used the Prime Script RT Master Mix from Takara (Cat. #RR047A) to reverse transcribe the RNA. Moreover, we used CFX96 Touch Real‐Time PCR Detection System (Bio‐Rad) per the manufacturer's protocol to conduct qRT‐PCR. For internal reference, GAPDH was used, and the reaction was conducted in two steps. The conditions for the reaction were: pre‐denaturation at 95°C for 30 s, denaturation at 95°C for 5 s, and annealing/extension at 60°C for 30 s for 50 cycles. The threshold cycle (Ct) approach was used to estimate expression, and the 2–ΔΔCt method calculated relative expression levels. Information about primers is shown in Table 2.10In RIPA buffer (Epizyme), Cell samples were harvested and then centrifuged at 12,000 × g and 4°C for 15 min. We collected supernatants and used a BCA Kit (Beyotime) to calculate protein concentrations. And 40–60 μg of each sample was taken, and the SDS‐PAGE electrophoresis separated proteins and transferred them into polyvinylidene fluoride membranes. The membranes were incubated with primary antibodies against PES1  and GAPDH  overnight at 4°C after 2 h, closed with 5% milk powder at room temperature. At room temperature, the signal was incubated with a secondary antibody for 1 h after washing 3 times with TBST. Then, according to the manufacturer's recommendations, the signal was detected by enhanced chemiluminescence.2.11We employed a negative control (NC) oligonucleotide and short interfering RNA (siRNA) to target PES1 Table . For cel2.12In each well of a 96‐well plate, a total of 3000 cells were implanted. After transfection, 10 μL of CCK‐8 reagent was added to the culture medium at 0, 24, 48, and 72 h. Then, cells were incubated at 37°C for 1 h, and with a microplate reader, the absorbance was measured at 450 nm.2.132 for 2 weeks. Phosphate buffer solution (PBS), fixed with 4% paraformaldehyde, was used to wash cells for 30 min and stained with 0.1% crystal violet solution for 10 min. Then we counted and analyzed the colonies.At a density of 800 cells per well, transfected SCC9 and CAL27 cells were inoculated in 24‐well plates and then incubated at 37°C in 5% CO2.14Eighty percent fusion was achieved after transfected SCC9 and CAL27 cells were injected onto a 12‐well plate. With the tip of a 10 μL pipette, single‐cell layers were scraped. After three PBS washes to remove cell debris, fresh media containing serum was added. At 0 and 24 h after scratching, three high‐magnification fields were taken to obtain typical images of cell migration. Using ImageJ, the scratch width was estimated.2.15In the migration assay for the Transwell system(BD Biosciences), the upper chamber inoculated the transfected SCC9 and CAL27 cells, and 500 μL of medium containing 10% FBS was filled in the lower chamber. And 24 h later, we used a cotton swab to wipe off the cells remaining on the surface of the filter membrane, and the cells passing through the membrane were fixed with methanol and then stained with crystal violet solution. Three randomly selected fields of view (including the center and periphery of the membrane) counted the number of cells under an inverted microscope. In the invasion assay, Matrigel (BD Biosciences) was used to coat the filters of the Transwell system, and the other steps were similar to the migration assay.2.16p < 0.05 was regarded as statistically significant.The Wilcoxon rank‐sum test analyzed the expression level of PES1 between non‐tumor tissues and HNSCC tumor tissues downloaded from the GEO database. Multivariate and univariate analyses were employed for Cox regression. In addition, the Wilcoxon test analyzed TME scores, immune checkpoint expression, and IC50 between high‐ and low‐expression groups. Moreover, we estimated the correlation coefficient of PES1 expression and immune infiltration cell score by Pearson correlation analysis. All the above statistics used R version 4.1.1 software to perform. Unless otherwise stated, 33.1To assess the differential PES1 expression in normal tissues and tumors, we analyzed the mRNA expression levels of pan‐cancer using the TIMER2 database. The results proved that the PES1 mRNA expression was upregulated in various cancer tissues than in corresponding normal tissues, including HNSCC. However, PES1 expression was decreased in Kidney Chromophobe (KICH) Figure . NotablyAs shown in Figure 3.2p = 0.0025)   Figure . Clinica) Figure . Subsequ) Figure .3.3To further investigate the molecular biological function of PES1 in HNSCC, we divided TCGA HNSCC samples into two groups according to PES1 levels and performed differential expression analysis. Based on the results of differential analysis, GSEA analysis was performed. We selected the highest enrichment pathway based on their normalized enrichment scores (NES). The results showed that PES1 differential genes were most significantly enriched in many immune response‐related processes, such as immunoglobulin complexes, antigen binding, adaptive immune responses, B‐cell receptor signaling pathways, primary immunodeficiency, intestinal immune network promoting IgA production, and hematopoietic stem cells Figure . GSVA is3.4LinkedOmics was utilized to explore the co‐expression profiles of PES1 in HNSCC, and a total of 106 co‐expressed genes were obtained  Figure . Then, f3.5+ and CD8+ T cells, B cells, and macrophage cells  is one of the most common oncogenes in human cancers. The p53 protein exerts antitumor effects by repairing DNA damage, regulating metabolism, normalizing reactive oxygen species levels, regulating non‐coding RNA expression, and promoting autophagy or ferric reduction.Despite the past decade's multidisciplinary treatment strategies having made tremendous achievements, the survival rate of HNSCC patients did not improve significantly, and the 5‐year survival rate remains lower than 50%.In addition, we found some genes co‐expressed with PES1. In the high PES1 expression group, CTCFL (CCCTC‐binding Factor Like), NR0B1 , and GAGE12J (G antigen 12 J) were expressed at higher levels. In the low PES1 expression group, CTCF is a chromatin insulator and multifunctional transcription factor, and mutations in this gene are associated with invasive breast cancer, prostate cancer, HNSCC and nephroblastoma.The GSEA results showed negative enrichment of KEGG pathways and GO terms for immune‐related pathways, including immunoglobulin complexes, antigen binding, adaptive immune responses, B‐cell receptor signaling pathways, and intestinal immune networks promoting IgA production, findings that prompted us to consider the role of PES1 in cancer immunology. Interestingly, pathways associated with tumor growth are also present in the PES1 high‐expression group. These pathways include structural components of ribosomes, mitochondrial protein complexes, oxidative phosphorylation, and glutathione metabolism. New evidence suggests that cancer cells harbor a specialized class of ribosomes (onco‐ribosomes) that facilitate oncogenic translation programs, regulate cellular function, and promote metabolic remodeling.+ T cells, macrophages, B cells, Treg cells, and neutrophils, and may be one of the relevant genes affecting the tumor microenvironment of oral squamous cell carcinoma. In addition, we found that ImmuneScore, StromalScore and ESTIMATEScore were lower in the high PES1 expression group, suggesting that the high PES1 expression group may be in an immunosuppressed state. CD8+ T lymphocyte dysfunction and failure were characterized by the upregulation of immunosuppressive molecules, such as PD‐1 and CTLA‐4, which suppressed the activation of CD8+ T lymphocytes. Persistent suppression in the tumor microenvironment may result in the inability of infiltrating CD8+ T lymphocytes to kill tumor cells, ultimately leading to tumor immune escape.Tumor immune infiltrating cells are an essential component of the tumor microenvironment and have been shown to play an important role in tumor proliferation and metastasis.Immunotherapy has revolutionized the treatment of cancer. Modern cancer immunotherapy has been developed over 50 years, and it was first applied to hematologic malignancies.However, our work also has certain limitations. First, the prognostic value of PES1 must be validated in an actual clinical cohort. The database used in this study lacks post‐translational modifications and, therefore, cannot fully elucidate how these modifications affect the function of PES1. Furthermore, the upregulation of PES1 provides only indirect evidence of changes in TME, not direct evidence. The relationship between PES1 and TME is not well defined. Finally, the response of PES1 to immunotherapy requires further analysis of large‐scale protein sequencing or immunohistochemistry of PES1 to assess their relationship and validation by subsequent preclinical and functional studies. More work is needed to optimize clinical efficiency before it can be considered a practical therapeutic option.5In summary, our study shows that in HNSCC tissues, PES1 is highly expressed, and high expression of PES1 is related to decreased immune cell infiltration and survival in HNSCC. Moreover, we highlight the critical role of PES1 in the course of HNSCC and its potential prognostic and therapeutic value.Yaodong He: Writing – original draft . Junwei Xiang: Writing – original draft . Yunshan Li: Data curation . Wenkai Huang: Visualization . Feihan Gu: Investigation . Yuanyin Wang: Supervision ; writing – review and editing . Ran Chen: Supervision ; writing – review and editing .This study was supported by Research Fund Project of Anhui Institute of Translational Medicine (2022zhyx‐C86) and Anhui Medical University Student Innovation and Entrepreneurship Training Program (S202210366083).The authors declare no competing interests.The collection of the clinical samples was performed under the supervision of Institutional Review Boards of The First Affiliated Hospital of Anhui Medical University . All patients provided written informed consent to provide their tumor tissues for further study, according to the Declaration of Helsinki.Figure S1.Click here for additional data file.Figure S2.Click here for additional data file.Figure S3.Click here for additional data file.Table S1.Click here for additional data file.Table S2.Click here for additional data file.Table S3.Click here for additional data file.Table S4.Click here for additional data file.Table S5.Click here for additional data file.


Hepatocellular carcinoma (HCC) patients with Child‐Pugh (CP)‐B not eligible for surgery nor other focal therapy options due to impaired liver function, have very limited treatment options. This study aims to retrospectively investigate the toxicity and efficacy of Carbon‐ion radiotherapy (C‐ion RT) on HCC with CP‐B patients.Patients with CP‐B, no extrahepatic metastasis, and treated with C‐ion RT between May 2000 and March 2020 were retrospectively extracted and included in this study.Sixty‐nine lesions of 58 patients were included. The median follow‐up duration was 20.5 (2.7–108) months. During follow‐up, recurrence was observed in 43 patients, including 2 local recurrences and 39 intrahepatic recurrences beyond the irradiation field. A grade 3 acute hepatotoxicity was observed in one patient during the observation period. No acute or late adverse event of grade ≥4 was observed. Overall survival was 80.4% and 46.0% at 1 and 2 years, respectively, and the median survival time was 22.6 months. Local control rate was 96.4% at both 1 and 2 years, and progression‐free survival was 38.6% and 6.9% at 1 and 2 years, respectively, with a median of 9.7 months.The C‐ion RT showed low toxicity and good local effect in patients with HCC and CP‐B. Therefore, C‐ion RT could be an appropriate treatment for patients with HCC with poor liver function. Carbon‐ion RT may improve treatment outcome of patients with poor liver function.1Hepatocellular carcinoma (HCC) is the most common primary cancer in the liver and in Japan, the fifth most common cause of cancer‐related deaths.Stereotactic body radiotherapy (SBRT), a form of high‐precision photon radiotherapy, has recently become more widespread. SBRT is often used when the location of the lesion or the patient's condition makes it difficult to perform surgery or RFA. SBRT has been shown to have high local control rates and low toxicity for HCC in prospective and multicenter studies.Particle radiotherapy, including carbon‐ion radiotherapy (C‐ion RT), is a radiation therapy type that uses charged particles and is clinically applied to various of cancer types.The present study aimed to review C‐ion RT performed on patients with HCC with CP‐B background liver and evaluate its therapeutic efficacy and toxicity.22.1Cases were extracted from an inhouse all‐in treatment database matching the following criteria: (1) HCC diagnosed pathologically by biopsy or imaging by computed tomography (CT)/magnetic resonance imaging (MRI); (2) presence of CP‐B liver; (3) absence of distant organ or lymph node metastasis evaluated by CT; (4) tumor not in contact with the digestive tract; (5) ≤3 irradiation fields; (6) difficulty in or refusal for receiving standard treatment; and (7) Eastern Cooperative Oncology Group performance status 0–2. The exclusion criteria were as follows: (1) previous radiation therapy for the target tumor; (2) portal hypertension with well‐developed extrahepatic portal collateral vessels; (3) difficult‐to‐treat gastric or esophageal varices, and (4) other active cancers Figure . In thisAll patients were evaluated for eligibility to receive C‐ion RT by the Ethics Committee and a Tumor Board comprising experts consisting of gastroenterologists, gastroenterological surgeons, and radiation oncologists. The participants provided informed consent for participation or had the opportunity to opt‐out of the study.2.2Before performing CT for planning treatment, fiducial markers were inserted near the tumor in the liver under ultrasound examination. For patients with ascites in the path of the beam, diuretics would be prescribed to ensure that the ascites was gone or that the increase or decrease was stable before proceeding to treatment planning. The CT was performed at each respiratory phase as 4D‐CT. Thermoplastic sheets , customized cradles , and gating system (NIRS) were used during the treatment plan CT and treatment room to improve alignment and accuracy during treatment.The C‐ion RT method was reported previously.The radiation dose of C‐ion RT was expressed as the photon equivalent dose (Gy)  and defined as the physical dose multiplied by the C‐ion RBE.After completion of C‐ion RT, patients were required to undergo follow‐up every 3 months, and CT and MRI were performed every 3–6 months to evaluate the lesions and check for recurrence. Local recurrence was defined as regrowth of the irradiated lesion after C‐ion RT by CT and MRI. Regional recurrence was defined as recurrence within the liver outside the irradiated area. Blood samples were collected during each visit. Adverse events were assessed in accordance with the Common Terminology Criteria for Adverse Events, version 4.0, and previous reports.2.3p < 0.05 was considered to be statistically significant.The Kaplan–Meier method was used to analyze overall survival (OS), local control (LC), and progression‐free survival (PFS), and the log‐rank test was used for comparison between elements. Age, sex, and CP score were included in the analysis. The relationship between acute and late CP scores and PTV, mean irradiated liver dose (MLD), and whole liver volume was examined using t‐tests. SPSS software version 25.0 (IBM Inc.) was used for all analyses. A 2.4This research was conducted in accordance with the Declaration of Helsinki (1964) and the subsequent Code of Ethics, and the study design was approved by the Institutional Review Board (permit number: 20‐046).33.1Between May 2000 and March 2020, 496 cases of HCC were treated with C‐ion RT, and 69 lesion of 58 patients met the criteria of this study. There were 36 men and 22 women with a median age of 71  years. Hepatitis B, hepatitis C, alcoholic hepatitis, and NASH were detected in 7, 33, 7, and 4 patients, respectively, as background liver conditions. The CP score were 7, 8, and 9 in 42 (72.4%), 13 (22.4%), and 3 (5.2%) patients, respectively. No patient received systemic therapy prior to C‐ion RT. No patient was treated at two sites at the same time, and there were 9 patients who received C‐ion RT for intrahepatic recurrence at different times. Three patients had four intrahepatic lesions, but the placement was such that treatment was possible with one irradiation field. The median PTV was 74.6 mL , and MLD was 8.7 Gy . Other patient backgrounds are shown in Table 3.2The median follow‐up period was 20.5  months. There were 45 deaths during the study period. Twenty‐eight, 10, 7, and 13 deaths were due to cancer, liver failure, other causes, and unknown causes, respectively. Patients who died from the progression of their current cirrhosis without developing radiation‐induced liver disease (RILD) and unrelated to direct liver damage from C‐ion RT are defined here as death from liver failure. The median follow‐up period focused only on survivors, which was 22.4  months.During follow‐up, recurrence was observed in 43 patients, including 2 local recurrences and 39 intrahepatic recurrences out of the irradiation field. Among the recurrent cases, 2 patients were treated by RFA, 9 patients were treated by C‐ion RT, 2 patients were treated by palliative photon RT, and the rest were in best supportive care. Reasons for not performing C‐ion RT again for recurrent lesions included ADL, financial issues, and distance and time constraints for hospital visits.OS was 80.4%  and 46.0% (95% CI: 32.5%–59.5%) at 1 and 2 years, respectively, and the median survival time (MST) was 22.6 months. LC was 96.4% (95% CI: 91.5%–100%) at both 1 and 2 years, and PFS was 38.6% (95% CI: 25.9%–51.3%) and 6.9% (95% CI: 0%–14.7%) at 1 and 2 years, respectively, with a median 9.7 months. Kaplan–Meier survival curves for each are shown in Figure p < 0.001, p = 0.008, and p = 0.028, respectively). In PFS, there were significant differences in ascites, the liver background and total dose . The results are presented in Table Influences of prognostic factors of patient backgrounds, such as age, sex, and CP score on OS and PFS were analyzed; significant differences in OS were observed in ascites, CP score and alpha fetoprotein (AFP) . On the other hand, there was no significant correlation between whole liver volume and adverse events.Regarding hepatotoxicity, a grade 3 acute adverse event was observed in one patient during the observation period but did not meet RILD criteria.p = 0.157). However, a worsening of the CP score in the late phase was significantly associated with OS (p < 0.001)  in Japan for liver cancer.A review of C‐ion RT outcomes for HCC shows that CP‐B has a significantly poorer prognosis than CP‐A.The results of SBRT for HCC with CP‐B have been reported by several groups. Culleton et al. performed SBRT on 29 patients with CP scores of 7–10, including 20 patients with a CP score of 7.Additionally, the results of the present study suggest that worsening of the CP score leads to worsening of survival rate, and thus, reducing the volume of the liver irradiated outside the target region is also important in terms of improving survival after C‐ion RT. Because of its pathogenesis, HCC is a disease with a high potential for repeated intrahepatic recurrence, and multiple treatments are often required. Although several treatments have been tried in this study for recurrence after C‐ion RT, few treatment options were considered safe due to low background liver function, and few cases were treated aggressively and radically. A threshold for confidently and safely performing C‐ion RT on such cases is a very important topic. Therefore, a future task is to predict outcomes based on the volume of the unirradiated liver and pre‐treatment liver function.As for systemic therapy, several studies have evaluated the use of sorafenib; of which, some have reported CP‐B outcomes and toxicity. The GIDEON study, which included 368 patients with CP‐B, reported an MST of 5 months.The survival rate in patients with liver failure has been improved due to several factors, including improvements in the treatment of hepatitis virus infections and the emergence of new hepatoprotective drugs. The Japanese NDB data suggest that survival rates have improved, possibly due to supportive care and improved treatments.There are limitations to the present study: retrospective, long inclusion period, and various background liver states. However, to the best of our knowledge, there are no reports on treating a large number of patients with HCC with CP‐B using C‐ion RT; and as we report that the treatment appears to be safe, C‐ion RT could be an option for patients with impaired liver function. However, the results for CP 9 cases are not satisfactory, and due to the high risk of liver failure, we believe that the indication should be cautious and only those cases in which the dose to the liver is minimal should be applied. In addition, it is currently difficult to directly compare the outcomes of C‐ion RT with other local treatments for HCC patients with CP‐B. In the future, prospective studies focusing on CP‐B with a large number of patients collected in collaboration with multiple centers and comparisons using propensity score matching are needed. Besides, for dose–volume–histogram analysis, it is necessary to define parameters for C‐ion RT, because unlike conventional radiotherapy, C‐ion RT can be performed with fewer gates and with a little affecting the surrounding liver. This point will need to be studied in detail in the future with the addition of the CP‐A patient group.In conclusion, this study describes the treatment outcome and toxicity of C‐ion RT in patients with HCC with CP‐B. C‐ion RT appeared to be minimally toxic and demonstrated favorable efficacy, providing a potential treatment option for those with impaired liver function suffering HCC.Yuichi Hiroshima: Conceptualization (lead); data curation (lead); formal analysis (lead); investigation (lead); methodology (lead); visualization (lead); writing – original draft (lead). Masaru Wakatsuki: Conceptualization (supporting); supervision ; writing – review and editing . Takashi Kaneko: Formal analysis (supporting); resources . Hirokazu Makishima: Investigation (supporting); resources (supporting); writing – review and editing (supporting). Naomi Nagatake Okada: Resources (supporting). Shigeo Yasuda: Resources (supporting). Hitoshi Ishikawa: Supervision . Hiroshi Tsuji: Project administration (lead).None.The authors have no conflicts of interest to declare.Figure S1Click here for additional data file.


We aimed to evaluate the impact of recommending supplementation to pregnant women with serum ferritin (SF) < 20 µg/L in early pregnancy on use of supplements, and to explore which factors were associated with changes in iron status by different iron indicators to 14 weeks postpartum.A multi-ethnic population-based cohort study of 573 pregnant women examined at mean gestational week (GW) 15 (enrolment), at mean GW 28 and at the postpartum visit (mean 14 weeks after delivery). Women with SF < 20 µg/L at enrolment were recommended 30-50 mg iron supplementation and supplement use was assessed at all visits. Change of SF, soluble transferrin receptor and total body iron from enrolment to postpartum were calculated by subtracting the concentrations at the postpartum visit from that at enrolment. Linear and logistic regression analyses were performed to assess associations between use of supplements in GW 28 and changes in iron status and postpartum iron deficiency/anaemia. Change of iron status was categorized into ‘steady low’, ‘improvement’, ‘deterioration’, and ‘steady high’ based on SF status at enrolment and postpartum. Multinomial logistic regression analyses were performed to identify factors associated with change of iron status.p < 0.05) and with haemoglobin concentration (p < 0.001) from enrolment to postpartum, and with lower odds of postpartum iron deficiency by SF and TBI (p < 0.05). Factors positively associated with ‘steady low’ were: use of supplements, postpartum haemorrhage, an unhealthy dietary pattern and South Asian ethnicity ; with ‘deterioration’: postpartum haemorrhage, an unhealthy dietary pattern, primiparity and no use of supplements , and with ‘improvement’: use of supplements, multiparity and South Asian ethnicity .At enrolment, 44% had SF < 20 µg/L. Among these women (78% non-Western European origin), use of supplements increased from 25% (enrolment) to 65% (GW 28). Use of supplements in GW 28 was associated with improved iron levels by all three indicators (Both supplement use and iron status improved from enrolment to the postpartum visit among women recommended supplementation. Dietary pattern, use of supplements, ethnicity, parity and postpartum haemorrhage were identified as factors associated with change in iron status.The online version contains supplementary material available at 10.1186/s12884-023-05668-5. Iron is crucial for numerous physiological and cellular processes, and iron deficiency (ID) has diverse health consequences . Persist.Iron supplementation programs are implemented in low-income countries to meet the WHO Global Nutrition Target from 2012 to reduce the prevalence of anaemia with 25% by 2025 . There iThe STORK-G study included hard-to-reach-women, as all information, material and questionnaires were translated into eight languages, and about 20% of women with non-Western European origin were assisted by professional interpreters. We have previously described the prevalence of gestational and postpartum ID by different indicators and anaemia in our cohort , 20. We Data from the population-based multi-ethnic STORK-G cohort were collected at public Child Health Clinics for primary antenatal care in three administrative districts in Oslo, Norway between 2008 and 2010. The study methods have been described in detail elsewhere . In shorIn total, 823 healthy women were enrolled at mean GW 15 ± standard deviation (SD) 3.4 in this cohort study; referred to as ‘at enrolment’ with planned follow-up visits in GW 28 (GW 28 ± 1.3) and approximately three months after delivery (13.9 ± 2.4 weeks after delivery), referred to as ‘postpartum visit’. Questionnaire data covering a wide range of health issues were collected through interviews by authorized study personnel, assisted by professional interpreters when needed at all three study visits . In addiBlood samples were drawn at all visits (2008-2011)  and sent10 (sTfR × 1000 ÷ SF) − 2.8229] ÷ 0.1207). To convert our Roche sTfR concentration to Flowers sTfR concentrations, we used the conversion equation Flowers sTfR = 1.5 × Roche sTfR + 0.35 mg/L [In 2016, sTfR was analysed by ELISA , at the Department of Medical Biochemistry at Oslo University Hospital, Oslo, Norway, using biobanked serum samples. We calculated TBI according to Cook  from theFor ethical reasons, and according to the protocol, women with depleted iron stores (SF < 20 µg/L) at enrolment were provided written information describing their SF concentration, recommended to start iron supplementation 30-50 mg/day, and to consult their General Practitioner (GP) for follow-up. At enrolment, in GW 28, and postpartum, all participants were asked about their intake of iron supplements during the past two weeks and to specify the name of the compounds used, and the number of tablets per day and per week. Of those reporting type of iron supplements, 57% used ferrous gluconate, 39% ferrous sulphate, and 4% ferrous fumarate. However, we were only able to calculate the exact iron intake in GW 28 in about 40% of cases. Iron supplementation was therefore dichotomized as ‘no intake’ and ‘intake of iron supplementation’, covering daily or intermittent iron supplement use.Our outcome measures were postpartum ID  and anaemia (defined as Hb < 12.0 g/dL), and changes in SF, sTfR, TBI and Hb concentrations, calculated by subtracting the concentrations at the postpartum visit from that at enrolment for each indicator. Further, according to the SF concentration at enrolment the sample was first dichotomized, as either ‘recommended supplements’ (SF < 20 μg/L) or ‘not recommended supplements’ (SF ≥ 20 μg/L). Second, we further categorized women with SF > 20 μg/L into four groups . Third, the sample was categorized based on the postpartum iron status (SF < 15 μg/L or ≥ 15 μg/L), resulting in four distinct groups called ‘steady low’, ‘improvement’, ‘deterioration’, and ‘steady high’, reflecting their change in iron status by SF from enrolment to postpartum.2) was calculated from self-reported weight before pregnancy and height measured at enrolment [Maternal age was calculated from date of birth and date at enrolment in the present study. Parity was dichotomized into primiparous (first pregnancy lasting > 22 weeks) and parous (one or more previous births) women. Pre-pregnancy BMI  no medical conditions associated with anaemia or ID, (II) self-reported chronic illness or medication associated with ID or normochromic, and (III) self-reported chronic illness or medication associated with ID or hypochromic anaemia . Data frWe have detailed data on birth complications extracted from hospital birth records. Delivery mode was categorized as normal vaginal delivery, instrumental vaginal delivery , elective caesarean section and emergency caesarean section. Blood loss after delivery was dichotomized into < 500 mL and ≥ 500 mL, where the latter was defined as postpartum haemorrhage. We constructed a composite index for birth complications reflecting the presence of at least one of the following complications; episiotomy, third- or fourth-degree perineal tear, obstructed labour and manual removal of placenta, due to small numbers in each of the categories.Of the 823 women enrolled in mean GW 15, 644 (78%) women gave birth to a live and singleton baby and attended the postpartum visit. For this study, we included participants with values for SF from both visits, resulting in a total sample of 573 women  are presented. GW, age, parity, SEP, diet, ethnicity, use of iron supplementation in GW 28 and postpartum, postpartum haemorrhage and birth complications were included in the fully adjusted model.Furthermore, we stratified the cohort in two subsamples based on whether the women were recommended use of iron supplements at enrolment or not. In each stratum, we performed two sets of regression analyses. Linear regression analyses were performed to assess the association between self-reported use of iron supplementation in GW 28 and changes in SF, sTfR, TBI, and Hb concentrations from enrolment to the postpartum visit. Logistic regression analyses were performed when postpartum ID  and anaemia were the outcome. Adjustments were made for GW, age, parity, SEP, diet, ethnicity, and use of iron supplements in pregnancy. In addition, SF concentration at enrolment was included to reduce dilution of regression to the mean. In a final model we also adjusted for use of supplements postpartum, postpartum haemorrhage, and birth complications although these were not true confounders, but potentially strongly associated with the outcome. The estimates changed marginally by including the last covariates. Results are presented as β-coefficients and ORs with accompanied 95% confidence intervals (CI). SPSS version 28 and Stata version 16 were used for statistical analysis.2, 45% were primiparous and 62% had ethnic origin from countries outside Western Europe (Table At enrolment (mean GW 15.1 (SD ± 3.4), maternal age was 29.7 ± 4.8 years, pre-pregnant BMI was 24.6 ± 4.8 kg/m).From enrolment in early pregnancy to GW 28, the reported use of iron supplementation increased from 25 to 65% in women recommended supplements, and from 13 to 26% in the group not exposed to our recommendations. Further, the proportion of women reporting use of iron supplements at GW 28 was higher (68%) in the group with ‘improvement’ in iron status from enrolment in early pregnancy to postpartum (mean postpartum week 13.9 (SD ± 2.5), compared to the group with ‘steady low’ iron status (55%). It was also higher in women with ‘steady high’ (29%) compared to the group with ‘deterioration’ (15%) in iron status (Table 1p < 0.001), while a reduction was seen in all other groups . As a consequence, the prevalence of postpartum ID by SF (defined as SF < 15 µg/L) was approximately 40% in all groups, except in women with SF concentration ≥ 70 µg/L at enrolment (24%) , but even more strongly with ‘improvement’  in iron status by SF, while negatively associated with having ‘deterioration’ in iron status by SF   (Table ). Use of supplements were associated with lower odds of postpartum ID by SF and TBI (p < 0.05—0.001) both in women exposed to recommendations and not. However, supplement use in iron depleted women (SF < 20 µg/L at enrolment) was not significantly associated with lower odds of postpartum ID by sTfR, and supplement use was in neither groups significantly associated with lower odds of postpartum anaemia  Table . Use of ia Table . Both SFp < 0.01) and postpartum haemorrhage  were associated with higher odds of having ‘steady low’ and ‘deterioration’ of iron status by SF (Table p = 0.03) and higher odds of ‘deterioration’  in iron status by SF. Further, South Asian ethnic origin was associated with having high odds of ‘improvement’ in iron status by SF, but higher odds of having ‘steady low’’ in iron status by SF   at enrolment in mean GW 15, of whom the majority (78%) were of non-Western European origin. In the group recommended supplementation, the use of iron supplements increased from 25% at enrolment to 65% at the postpartum visit. Further, in women recommended supplements, median SF concentration increased from 11 to 16 µg/L, while the median SF concentration was substantially reduced in women not exposed to our recommendations. Use of iron supplements in GW 28 was associated with lower odds of ‘deterioration’ and higher odds of ‘improvement’ in iron status by SF, and with lower odds of postpartum ID by SF and TBI, both in women recommended iron supplement and those not exposed to our recommendations. Use of supplements in GW 28 did however not reduce the odds of postpartum anaemia or postpartum ID by sTfR in women with depleted iron stores (SF concentration < 20 µg/L) at enrolment. Primiparity, unhealthy dietary pattern and postpartum haemorrhage were independently associated with ‘steady low’ and ‘deterioration’ in iron status by SF. South Asian ethnic origin was associated with higher odds of both ‘steady low’ and ‘improvement’ of iron status by SF.This study confirms the widespread prevalence of depleted iron stores in pregnancy and the early postpartum period . Even thIn our multi-ethnic cohort, we observed that 65% of the women recommended supplementation seemed to follow our recommendations and reported use in GW 28, and the median SF and the mean TBI concentration in this group increased from enrolment to 14 weeks postpartum. The compliance in randomized, controlled trials (RCT’s) has been reported to be around 85-90% –31, howeIn line with others, we found that use of supplements reduced the risk of postpartum ID and that women reporting use of iron supplements were more likely to improve their iron status by SF and mean Hb concentration in the postpartum period , 5. We aIn high-income countries, haemorrhage is recognized as the most important factor associated with postpartum ID and anaemia . Our stuThe major strength of our multi-ethnic population-based study is that we followed a large number of healthy women from enrolment in early pregnancy to 14 weeks postpartum with measurements of iron status by three different indicators, analysed at the same laboratories. We collected a broad high-quality data set, which enabled us to explore relations between iron status and a wide range of explanatory factors, and to adjust for a range of possible confounders. The questionnaires were translated to eight languages and data collection methods were adapted to facilitate enrolment of ethnic minorities and even illiterate women, who often are excluded in research . ProfessHowever, there are also weaknesses to report. We evaluated the impact of giving a simple recommendation of iron supplementation by self-reported use of supplements in GW 28 through a pre-post-test design, not a RCT. We do not know to which extent the women adhered to our recommendations. However, substantially more women reported use of iron supplements in GW 28 among women undergoing this ‘simple intervention’, compared to those not exposed to recommendation, suggesting an effect. In Norway ferrous gluconate, sulphate and fumarate can be bought in grocery stores or pharmacies without prescription. For the majority of women we lack information of the iron dose taken, the frequency and duration of intake, the type of iron supplements as well as of other variables affecting the iron uptake. We assessed the effect of recommending iron supplementation on the women's postpartum status only, and have not evaluated the effect of iron supplementation on the neonates. Further, the number of participants in some ethnic groups was low, and the presence of heterogeneity within relatively broad ethnic groups is possible. As in most studies, we had some loss to follow-up at the postpartum visit, partly due to logistic reasons, but we prioritized ethnic minority women for blood sampling. Further, the collected food-frequency data were used to identify dietary patterns, and we were therefore not able to calculate iron intake. Postpartum haemorrhage was not exactly measured, but based on clinical judgement. On average, the plasma volume increases from about 2.4 L to about 2.8 L from the time before pregnancy to week 19 , and we First, our results lend support to recommend iron supplementation to women during pregnancy to prevent gestational and postpartum ID and anaemia, and indicate that there is a need for an enhanced focus on iron supplementation during pregnancy to be incorporated in high risk groups in antenatal care. Further, our findings also suggest that postpartum ID or IDA needs to be addressed, and postpartum counselling that includes measurement of Hb and SF concentrations are required in high-risk women. In addition, as prophylactic iron supplementation during pregnancy is still a subject of international disagreement, further research to examine the effect on ID and IDA in pregnant women should be undertaken.We evaluated the impact of recommending supplements to pregnant women with depleted iron stores, including women in hard-to-reach-groups, and observed an increase of use of supplements and improved iron status from at enrolment to the postpartum visit. Women not exposed to our recommendations, showed a deteriorated iron status postpartum. Further, factors associated with change in iron status were dietary iron intake, use of iron supplements, ethnicity, parity and postpartum haemorrhage.Additional file 1. Flow chart of study participants in the STORK-G multi-ethnic cohort from Oslo 2008-2010.Additional file 2. Table S1. Average SF, sTfR, TBI and Hb concentration in early pregnancy and postpartum, and prevalence of postpartum iron deficiency/anaemia.


A viral infection can modify the risk to subsequent viral infections via cross‐protective immunity, increased immunopathology, or disease‐driven behavioral change. There is limited understanding of virus–virus interactions due to lack of long‐term population‐level data.Our study leverages passive surveillance data of 10 human acute respiratory viruses from Beijing, Chongqing, Guangzhou, and Shanghai collected during 2009 to 2019: influenza A and B viruses; respiratory syncytial virus A and B; human parainfluenza virus (HPIV), adenovirus, metapneumovirus (HMPV), coronavirus, bocavirus (HBoV), and rhinovirus (HRV). We used a multivariate Bayesian hierarchical model to evaluate correlations in monthly prevalence of test‐positive samples between virus pairs, adjusting for potential confounders.Of 101,643 lab‐tested patients, 33,650 tested positive for any acute respiratory virus, and 4,113 were co‐infected with multiple viruses. After adjusting for intrinsic seasonality, long‐term trends and multiple comparisons, Bayesian multivariate modeling found positive correlations for HPIV/HRV in all cities and for HBoV/HRV and HBoV/HMPV in three cities. Models restricted to children further revealed statistically significant associations for another ten pairs in three of the four cities. In contrast, no consistent correlation across cities was found among adults. Most virus–virus interactions exhibited substantial spatial heterogeneity.There was strong evidence for interactions among common respiratory viruses in highly populated urban settings. Consistent positive interactions across multiple cities were observed in viruses known to typically infect children. Future intervention programs such as development of combination vaccines may consider spatially consistent virus–virus interactions for more effective control. For example, public health interventions such as vaccination campaigns targeting a particular virus may impact the abundance of other viruses competing for or occupying the same niche.Statistical methods are needed to better tease out potential biological interactions between viruses in the presence of confounding socioenvironmental factors associated with virus survival and transmission, such as climatic conditions, age‐dependent contact patterns, and changes in testing frequencies. For example, shared seasonality patterns between influenza and RSV often confound interpretation of temporal correlation between the two viruses. One study in Scotland accounted for these factors via hierarchical autoregressive modeling to examine interactions between multiple groups of respiratory viruses over several years.Herein, we adapt a Bayesian virus–virus interaction framework designed for surveillance data with relatively dense sampling22.1Our data on acute respiratory infections (ARIs) were collected by the Surveillance for Etiology of Respiratory Infections program, an ongoing nationwide passive surveillance program initiated from 2009, which covers 314 sentinel hospitals in all 31 provinces in China. The ARIs were defined as (1) at least one of the following conditions: fever, abnormal white blood cell differentials, leukocytosis or leukopenia; and (2) at least one of the following symptoms/signs: cough, chills, expectoration, nasal congestion, sore throat, chest pain, tachypnea, and abnormal pulmonary breath sounds. In compliance with the standard operating protocol of surveillance developed by China CDC, a random sample of inpatients and outpatients presenting ARIs were enrolled, and nasopharyngeal specimens were collected from enrolled patients prior to any treatment to be tested for the presence of influenza virus , RSV‐A and RSV‐B, HPIV types 1–4, HAdV, HMPV, HCoV, HBoV, and HRV. All viruses were tested by reverse transcription‐polymerase chain reaction (RT‐PCR) except HAdV and HBoV, which were tested by PCR. Details about the laboratory procedures are given elsewhere.We focus on four metro cities that consistently tested patients for these viruses throughout the 11‐year period: Beijing, Chongqing, Guangzhou, and Shanghai. Nearly all enrolled patients presenting with acute respiratory symptoms were tested for all respiratory viruses during 2009–2019. There was a lower testing rate, however, for HRV during 2009–2011, so we restricted analyses related to HRV to 2012–2019. We also excluded influenza C from analysis and grouped HPIV 1–4 viruses into a single HPIV group due to the relatively low frequency of each individual virus. Analyses were done for the total population studied and separately for children <18 years and adults ≥18 years. There was a lower testing rate for adults in Chongqing in 2011 and 2015–2019; therefore, that subgroup was excluded from age‐stratified analyses.2.2p < 0.05 and p < 0.10, with weights corresponding to the number of tests administered. The p values were corrected for multiple comparisons using the Benjamin–Hochberg procedure,q values were reported. Statistical significance was defined as q ≤ 0.10, that is, controlling the FDR at 10%. We also calculated weighted Pearson's coefficients in monthly infection prevalence by sex for each virus in each city. At the individual level, we also calculated the odds of co‐infection for each virus with each of the other viruses (45 virus pairs) in each city and used Fisher's exact test for statistical significance, and similarly, FDR‐adjusted q values were reported.For correlation analyses, we aggregated data into monthly infection counts for each virus to evaluate the population‐level covariation patterns between viruses in each city . We calculated a measure of prevalence of positive tests for each virus as the number of infected patients over the total number of patients tested for each virus for each month. We calculated weighted Pearson's coefficients and 95% confidence intervals (CIs) to evaluate unadjusted correlations in monthly infection prevalence between each of the 45 virus pairs with statistical significance set at 2.3Simple correlations among respiratory viruses may be confounded by changes in testing frequencies, temporal autocorrelation, and other factors. To address these challenges, we used a multivariate Bayesian hierarchical model, adapting an approach initially designed by Mair et al.Before applying the hierarchical model, we smoothed observed monthly infection counts for each virus using logistic regression, adjusting for common risk factors for infection. We fitted generalized linear models for each virus and city, incorporating harmonic functions to account for seasonality and polynomials of year to capture long‐term trends, while also adjusting for sex and age groups.ρ to characterize virus–virus interactions. A range of  for ρ effectively covers a range of  for the correlation coefficient. A fundamental distinction in our model compared with previous workIn the second stage, we modeled interactions between pairs of viruses separately. We introduced a multiplicative random odds ratio (OR) to describe how the realized prevalence of positive samples for each virus deviates from the expected prevalence. This random OR is related to the random effect φ, which follows a multivariate AR (1) structure to capture correlations between viruses. Specifically, we used the correlation coefficient We used 10 chains, each with a burn‐in of 20,000 iterations, followed by 600 thinned draws from 60,000 additional iterations per chain, ensuring convergence Figure . Models 33.1Our dataset included 216,030 patients from January 2009 to December 2019, of whom 115,622 (53.5%) were from Beijing, Chongqing, Guangzhou, and Shanghai, four large metro cities each with a population size of 15–31 million. Of 101,643 patients from the four cities who were tested for any of the viruses of interest, 44.7% were from Beijing, 59.2% were male, and 50.8% were children Table . Of pati3.2There were 33,650/101,643 (33.1%) patients who tested positive for any of the 10 viruses studied Figure , of whomq ≤ 0.10 in Beijing , 30 in Shanghai , 26 in Guangzhou , and 22 in Chongqing  , HPIV and HCoV in Shanghai , HRV and HBoV in Guangzhou , and IBV and RSV‐B in Chongqing .At the individual level, we evaluated for each pair of viruses the OR of co‐infection by city but lumping data from all 11 years, while controlling for FDR ≤ 0.10. Of 45 pairwise tests in each city, 36 were significant at ) Figure . In Beij3.3p ≤ 0.05 and p ≤ 0.1 that are unadjusted for multiple comparisons are shown in Figures p ≤ 0.05. Stratifying by age group, viral correlations for children were largely consistent with the overall population , 12 in Chongqing , 10  in Beijing, and seven in Guangzhou . HPIV was positively correlated with HRV in all four cities with correlations ranging from 0.49 to 0.56   and Chongqing , RSV‐B and HRV in Guangzhou , and HMPV and HRV in Shanghai . Some viruses were interactive with as many as five other viruses in a particular city, for example, IAV in Chongqing and HRV in Shanghai. Using p value ≤0.05 to determine statistical significance but without adjustment for multiple comparisons  Figure . Monthly) Figure  confirmes Figure  yielded l Figure  addition3.6q ≤ 0.10 among adults in Beijing, Guangzhou, and Shanghai, respectively. Chongqing was not examined due to sparsity in the number of tested adults.The Bayesian model fitted solely on children revealed many more significant virus–virus correlations than the total population, 24–29 in each of the four cities Figure . All vir4We assessed potential positive and negative interactions between acute respiratory viral infections among four major cities in China over an 11‐year period, adjusting for demographics, temporal autocorrelations, seasonality, long‐term trends, and multiple comparisons. The data are unique because of not only the coverage of a long time‐span and large metro‐populations but also the simultaneous testing of a comprehensive panel of respiratory viruses from each patient. The most convincing interactions, as shown by both the overall analyses and children‐specific analyses, are the positive correlations between HPIV and HRV and between HBoV and HRV. Although the pair of HBoV and HRV did not reach statistical significance in Shanghai, the direction of association is consistent in all four cities. Equally noticeable is the pair of RSV‐A and HCoV among children, which showed consistent positive associations in all four cities and statistical significance in three. More positive correlations were found than negative correlations, and more associations were found in children than in the general population. There was also a substantial level of spatial heterogeneity in the virus–virus interactions, for example, strong negative correlation of IAV with HRV and HMPV, as well as that between RSV‐A and RSV‐B, were only seen in Chongqing.HPIV was positively correlated with HRV in all cities in Bayesian analyses. HPIVs are one of the most common causes of lower respiratory tract infections among children <5 years, accounting for up to 17% of hospitalizations from pneumonia.HCoV was positively correlated with HPIV in three cities for children in adjusted analyses. We are unaware of other population‐level analyses supporting these findings, but several studies reported increased frequency of co‐infection between HPIV and HCoV‐229E in Shanghai,In adjusted analyses, we observed positive correlations among pairs of viruses including RSV‐B, HBoV, HAdV, and HMPV—viruses that frequently cause lower respiratory tract infections in young children. This is consistent with a 10‐year study in central Europe, which found that HRV/HBoV, HRV/HAdV, RSV/HBoV, RSV/HAdV, RSV/HRV, and RSV/HCoV‐OC43 were the most prevalent co‐infections.Among children, IAV was negatively correlated with HAdV in three cities, and HRV, HBoV, HMPV, and RSV‐B in Chongqing, which is in accord with several studies that reported shifts in the timing and severity of other respiratory infections following IAV epidemics.Most of the statistically significant correlations among respiratory viruses were positive associations, which could result from several factors, including shared transmission routes, interactions with the host immune system, or environmental conditions that favor multiple virus types.There were inconsistencies in virus–virus interactions between adult and child populations, even within the same city. Children and adults have distinct immune responses due to differences in immune system maturity and prior exposure to respiratory viruses.Our study had several limitations. First, we did not assess higher order interactions between three or more viruses. Second, bacterial infections, which were not examined in this study, may also play a mediating role in one's susceptibility to viral co‐infection. Third, 4.9% of patients included in this study were only tested for two viruses of interest (IAV and IBV) during the 2009 H1N1 influenza pandemic, suggesting some co‐infections in those patients might have been missed. Fourth, our study used hospital surveillance data, which includes symptomatic individuals seeking care. Influenza, RSV, and other viral infections may not present clinically, so it is unclear to what extent asymptomatic infections impacted the observed interactions.5Virus–virus interactions may have a significant impact on viral disease severity, transmissibility, immune response, and vaccine effectiveness. Different virus pairings may trigger different pathogenic mechanisms, which could inhibit or amplify clinical and public health consequences. Spatially consistent virus–virus interactions warrant future research to understand their biological pathways and social determinants and may be considered for more effective intervention programs, for example, developing combination vaccines for children. Our method extends the statistical approach designed for dense sampling to sparse sampling to provide insights of virus–virus interactions among four major cities in China over an 11‐year period. The method could be further improved by incorporating individual‐level co‐infection status. The SARS‐CoV‐2 pandemic may pose new challenges on modeling virus–virus interactions. Recent research demonstrates a significant reduction in a broad spectrum of acute respiratory viruses consequent to SARS‐CoV‐2 likely due to the synergy of nonpharmaceutical interventions , reduced testing of seasonal respiratory viruses, and viral interferences.Zachary J. Madewell: Formal analysis; investigation; methodology; software; validation; visualization; writing—original draft; writing—review and editing. Li‐ping Wang: Conceptualization; data curation; funding acquisition; investigation; methodology; project administration; resources; writing—review and editing. Natalie E. Dean: Funding acquisition; investigation; methodology; writing—original draft; writing—review and editing. Hai‐Yang Zhang: Data curation; investigation; methodology; resources; writing—review and editing. Yi‐Fei Wang: Data curation; investigation; methodology; resources; writing—review and editing. Xiao‐Ai Zhang: Data curation; investigation; methodology; resources; writing—review and editing. Wei Liu: Data curation; investigation; methodology; resources; writing—review and editing. Wei‐Zhong Yang: Data curation; funding acquisition; investigation; methodology; resources; writing—review and editing. Ira M. Longini: Funding acquisition; investigation; methodology; writing—review and editing. George F. Gao: Data curation; funding acquisition; investigation; methodology; resources; writing—review and editing. Zhong‐Jie Li: Data curation; funding acquisition; investigation; methodology; resources; writing—review and editing. Li‐Qun Fang: Conceptualization; data curation; funding acquisition; investigation; methodology; project administration; resources; supervision; validation; visualization; writing—review and editing. Yang Yang: Conceptualization; formal analysis; funding acquisition; investigation; methodology; project administration; resources; software; supervision; validation; visualization; writing—original draft; writing—review and editing.The authors declare no conflict of interests.Data collection was considered to be public health surveillance by the National Health Commission of the People's Republic of China and verbal informed consent was obtained from patients or their legal guardians. The surveillance protocol was reviewed and approved by the ethics review committees of the China CDC (2015‐025).https://www.webofscience.com/api/gateway/wos/peer-review/10.1111/irv.13212.The peer review history for this article is available at Figure S1. Example MCMC trace plots of model parameter estimates for the Bayesian hierarchical model for influenza B virus (IBV) and human parainfluenza virus (HPIV) in Beijing.Figure S2. Monthly numbers of laboratory‐tested samples with and without viral infections from January 2009 to December 2019 in four metro cities, China.Figure S3. Monthly percentage of patients diagnosed with a single viral infection, a viral co‐infection, or determined to be virus‐negative from January 2009 to December 2019 in four metro cities, China.Figure S4. Monthly viral prevalence by sex from January 2009 to December 2019 in four metro cities, China. Weighted Pearson's coefficients in monthly infection prevalence between the two sexes for each virus in each city and 95% confidence intervals are shown, with weights corresponding to the number of tests administered by city. Prevalence was the number of infected patients over the total number of patients tested for each virus for each month.Figure S5. The proportion of all tests for each virus that were positive and total number of infections in four metro cities, China. Larger circles represent a greater proportion of positive tests and darker colors represent greater numbers of infections.Figure S6. Number of tests (light) and proportion of tests that were positive (dark) for each acute respiratory virus by age group in four metro cities, China.Figure S7. Relative prevalence of viruses from January 2009 to December 2019 in four metro cities, China.Figure S8. Ratio of odds of infection with one virus between presence vs. absence of the other virus for each virus pair, based on tabulating individual detection data from January 2009 to December 2019 in four metro cities, China. Blue represents odds ratios (OR) > 1, red represents ORs < 1, and larger circles represent smaller q‐values. The q‐values control for false discovery rate and are based on p‐values from the Fisher's exact test.Figure S9. Weighted Pearson's correlation coefficients for the total population studied and 95% confidence intervals of monthly prevalence for each pair of respiratory viruses in four metro cities of China, where weights are the numbers of tests administered. This figure is identical to Figure 3, but with 95% confidence intervals instead of q‐values. Blue and red indicate statistically significant (p < 0.05) positive and negative coefficients, respectively. Green and purple borders indicate virus pairs significant in three and four cities, respectively. The p‐values are not adjusted for multiple comparisons.Figure S10. Weighted Pearson's correlation coefficients for the total population studied and 90% confidence intervals of monthly prevalence for each pair of respiratory viruses in four metro cities of China, where weights are the numbers of tests administered. This figure is identical to Figure 3, but with 90% confidence intervals instead of q‐values. Blue and red indicate statistically significant (p < 0.1) positive and negative coefficients, respectively. Green and purple borders indicate virus pairs significant in three and four cities, respectively. The p‐values are not adjusted for multiple comparisons.Figure S11. Weighted Pearson's correlation coefficients for children <18 years and q‐values of monthly prevalence for each pair of respiratory viruses in four metro cities of China, where weights are the numbers of tests administered. The q‐values represent statistical evidence adjusted for multiple comparisons by controlling the false discovery rate. Significant correlations (q ≤ 0.10) are shown in colour. Blue and red indicate positive and negative coefficients, respectively. Green and purple borders indicate virus pairs statistically significant with consistent directions in three and four cities, respectively.Figure S12. Weighted Pearson's correlation coefficients for adults ≥18 years and q‐values of monthly prevalence for each pair of respiratory viruses in four metro cities of China, where weights are the numbers of tests administered. The q‐values represent statistical evidence adjusted for multiple comparisons by controlling the false discovery rate. Significant correlations (q ≤ 0.10) are shown in colour. Blue and red indicate positive and negative coefficients, respectively. Yellow borders indicate virus pairs statistically significant with consistent directions in two of the three cities, respectively. There was a lower testing rate for adults in Chongqing, therefore that subgroup was not analyzed.Figure S13. The observed and expected prevalence of each virus before applying the multivariate Bayesian hierarchical model, January 2009 to December 2019 in four metro cities, China. The expected prevalence was calculated by fitting generalized linear models for each virus and city with harmonic functions to account for seasonality and polynomials to account for long‐term trends, while adjusting for sex and age group . Prevalence was the number of infected patients over the total number of patients tested for each virus for each month.Figure S14. Monthly prevalence of human parainfluenza virus and human rhinovirus from January 2009 to December 2019 in four metro cities, China. Prevalence was the number of infected patients over the total number of patients tested for each virus for each month.Figure S15. Bayesian hierarchical model correlation coefficients for the total population studied and 95% credible intervals, adjusting for age, sex, seasonality, changes in testing frequency, and autocorrelation. This figure is identical to Figure 4, but with 95% credible intervals instead of q‐values. Blue and red indicate statistically significant (p < 0.05) positive and negative coefficients, respectively. Purple borders indicate virus pairs significant in four cities. The p‐values are not adjusted for multiple comparisons.Figure S16. Bayesian hierarchical model correlation coefficients for the total population studied and 90% credible intervals, adjusting for age, sex, seasonality, changes in testing frequency, and autocorrelation. This figure is identical to Figure 4, but with 90% credible intervals instead of q‐values. Blue and red indicate statistically significant (p < 0.10) positive and negative coefficients, respectively. Green and purple borders indicate virus pairs significant in three and four cities, respectively. The p‐values are not adjusted for multiple comparisons.Figure S17. Bayesian hierarchical model correlation coefficients for children <18 years and q‐values, adjusting for age, sex, seasonality, changes in testing frequency, and autocorrelation. The q‐values represent corrected p‐values for multiple comparisons by controlling the false discovery rate. Significant correlations (q ≤ 0.10) are shown in color. Blue and red indicate positive and negative coefficients, respectively. Green and purple borders indicate virus pairs significant in three and four cities, respectively.Figure S18. Bayesian hierarchical model correlation coefficients for adults ≥18 years and q‐values, adjusting for age, sex, seasonality, changes in testing frequency, and autocorrelation. The q‐values represent statistical evidence adjusted for multiple comparisons by controlling the false discovery rate. Significant correlations (q ≤ 0.10) are shown in colour. Blue and red indicate positive and negative coefficients, respectively. There was a lower testing rate for adults in Chongqing, therefore that subgroup was excluded from this analysis.Table S1. Numbers of viruses tested for each patient (N = 101 643). Viruses tested included: influenza A and B; respiratory syncytial virus A and B; and human parainfluenza virus, adenovirus, metapneumovirus, coronavirus, bocavirus, and rhinovirus.Table S2. Quasi‐Akaike information criteria for harmonic regression models for the total population studied by virus and city. The lowest Quasi‐Akaike information criteria for each model is shown in bold.Table S3. Mean, standard deviation, and quantiles of the marginal posterior distribution for ρ, and convergence diagnostics for Bayesian hierarchical model.Click here for additional data file.