As of August 27, 2021, the ongoing pandemic of coronavirus disease 2019 (COVID‐19), caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), has spread to over 220 countries, areas, and territories. Thus far, 214,468,601 confirmed cases, including 4,470,969 deaths, have been reported to the World Health Organization. To combat the COVID‐19 pandemic, multiomics‐based strategies, including genomics, transcriptomics, proteomics, and metabolomics, have been used to study the diagnosis methods, pathogenesis, prognosis, and potential drug targets of COVID‐19. In order to help researchers and clinicians to keep up with the knowledge of COVID‐19, we summarized the most recent progresses reported in omics‐based research papers. This review discusses omics‐based approaches for studying COVID‐19, summarizing newly emerged SARS‐CoV‐2 variants as well as potential diagnostic methods, risk factors, and pathological features of COVID‐19. This review can help researchers and clinicians gain insight into COVID‐19 features, providing direction for future drug development and guidance for clinical treatment, so that patients can receive appropriate treatment as soon as possible to reduce the risk of disease progression. In the global COVID‐19 pandemic, multiomics‐based strategies have been applied into the surveillance of newly emerged SARS‐CoV‐2 variants and the study of diagnostic methods, risk factors, and pathological features of COVID‐19, which will contribute to the prevention and control of this pandemic. Without exception, multiomics‐based strategies have been widely used to investigate the pathogenesis, potential drug targets, and diagnostic approaches of COVID‐19.2As the COVID‐19 pandemic spread, more and more mutations were detected in newly isolated SARS‐CoV‐2 strains, indicating adaptive viral evolution.2.1The ongoing evolution of SARS‐CoV‐2 has been the topic of considerable interest as the pandemic spreading globally.As the progression of COVID‐19 pandemic, genomic surveillance has contributed significantly in tracking variants. Series of newly emerging variants are identified for further study, including B.1.1.7 , B.1.351 , P.1 , B.1.167.2 , B.1.427/B.1.429 , P.2 , B.1.525 , P.3 , B.1.526 , B.1.167.1 , C.37 , and some other variants spread in different regions.The SARS‐CoV‐2 B.1.1.7 variant originated in the UK from late Summer to early Autumn 2020. Recently, it has rapidly spread from southeast England to the whole world , indicating a substantial selective advantage over other currently circulating lineages.B.1.351, the main lineage circulating widely in South Africa during the second wave of infections, is characterized by eight lineage‐defining mutations in S protein of SARS‐CoV‐2, including K417N, E484K, and N501Y on the RBD, L18F, D80A, D215G, ∆ 242–244 on the NTD and A701V located in S2 region.The emergence of SARS‐CoV‐2 P.1 variant (B.1.1.28.1) was observed in a surge in severe COVID‐19 case hospitalizations in Brazil in February, 2021. Through whole‐genome sequencing, the P.1 lineage was revealed to be associated with rapid increase of confirmed cases and hospitalization rates.The recently emerging variants almost all carried the L452R mutation, including B.1.427/B.1.429 variant, B.1.526 variant, and B.1.167 variant. B.1.427/B.1.429 variant , first identified variant bearing a L452R mutation, is the prevalent lineage spread in California, USA, which possesses increased infectivity and resistance of neutralization due to the cooccurrence of L452R, S13I, and W152C mutation.Apart from VOCs, series of emerging variants have been monitored for further alerts. A.23.1 is a sub‐lineage of A.23 defined by F157L, V367F, Q613H, and P681R mutations, possessing increased fusion activity and immune evasion ability. In January, 2021, A.23.1 overtook the former circulating variants in Uganda, and spread rapidly to more than 23 countries.2.2The emergence of new variants is driven by the heritable mutations of SARS‐CoV‐2 Figure . As repoAt the early stage of COVID‐19 pandemic, some mutations have existed in the epidemic strains, including H49Y on the S1 N‐terminal domain (NTD) from China, G476S on the RBD from Washington, USA and S943P on FP from Belgium.N439K mutation on the receptor binding motif (RBM) of S protein can enhance the binding affinity of S protein to ACE2 receptor moderately and can lead to resistance against several neutralizing monoclonal antibodies and some polyclonal sera from persons recovered from infection.In chronic infection, D796H substitution in the S2 subunit of S protein appeared to be responsible for the resistance of neutralizing antibodies accompanied by decreased infectivity; however, when combined with ∆H69/∆V70 mutation, this defect can be compensated.Aside from S protein, RNA‐dependent RNA polymerase (RdRp), methyltransferase complex (Nsp10–Nsp16), and helicase (Nsp13) can also be promising drug targets of SARS‐CoV‐2 infection. However, the emergence of mutations poses a challenge on the development of virus‐targeted therapies. By now, silent mutation and composition‐related mutations are identified in the RdRp gene of SARS‐CoV‐2, arisen a risk on possible drug‐resistance to clinical used RdRp‐targeted drugs.Moving forward, long‐term and continuous tracking of emerging variants and the functional consequences of mutations will help researchers and politicians to formulate more appliable strategies for the prevention and control of COVID‐19 pandemic, including vaccination strategies.3Being an RNA virus, the life cycle of SARS‐CoV‐2 is highly dependent on the machinery of the host cell. Therefore, once infected by SARS‐CoV‐2, series of changes occur in the host cells, especially in their transcriptomes. Transcriptomic analysis is useful for investigating the cellular mechanisms underlying risk factors, pathogenesis, and potential drugs targets of SARS‐CoV‐2 infection. Further, the application of transcriptomic analysis in various clinical samples will be helpful to elucidate the mechanisms of COVID‐19‐associated tissue damage and comorbidities . To determine the susceptible factors of SARS‐CoV‐2 infection, series of experiments were conducted and multiple risk factors of severe COVID‐19 were demonstrated.3.2.1The analysis and reanalysis of single‐cell transcriptomic data specialized on ACE2 and TMPRSS2 found coexpression of ACE2 and TMPRSS2 in pulmonary and extrapulmonary tissues, including maternal–fetal interface, salivary glands, and the granulosum of the skin and so on, posing a risk of systematic tissue damage, as well as indicating the possibilities of vertical transmission and contact transmission.ACE2 and TMPRSS2 expression contributed to clinical inflammatory lung injury and respiratory failure. In this procedure, series of inflammation‐related pathways, including Toll‐like receptor 4 (TLR4), C‐C chemokine receptor type 1 (CCR1), CCR5, C‐X‐C chemokine receptor type 6 (CXCR6), mammalian target of rapamycin (mTOR), mitogen‐activated protein kinase (MAPK)/MAPKK/protein kinase B , inhibitor of nuclear factor κB kinase/nuclear factor κB (NF‐κB), and ferroptosis pathways, were involved.In moderately or critically ill patients with COVID‐19, ACE2 and TMPRSS2 expression in epithelial cells of lung was increased in response to Type 2 inflammation‐related interleukin‐13 (IL‐13) and IFN signals. Afterward, increased SARS‐CoV‐2 infection induces hyperactivation of the extrinsic blood coagulation cascade and the suppression of the plasminogen activation system in epithelial cells,Aside from the underlying risks, many acquired risk factors are also observed in SARS‐CoV‐2 infection. The higher expression of ACE2 and TMPRSS2 in individuals who smoked and those with lung cancer, posing relatively higher risk of SAR‐CoV‐2 infection.Besides, COVID‐19 patients could also be distinguished by age and gender. Compared with male and elderly patients, female and children possess higher expression levels of immune modulation‐correlated genes and will experience relatively lower disease severity.3.2.2The severity of COVID‐19 may depend on the immune microenvironment. In asymptomatic or mild COVID‐19 patients, lower proportion of CD169+ expressing monocytes and correlated proinflammatory cytokines, as well as more counts of mature neutrophils, early bystander CD8+ T cell and plasmablast responses and higher levels of growth factors were detected, suggesting that asymptomatic patients mount less proinflammatory and more protective immune responses against SARS‐CoV‐2, and no prolonged immunological activation would exist.3.3SARS‐CoV‐2 infection‐induced systematic tissue damage was marked by inflammation and coagulopathy in blood and tissues.In the postmortem human brain tissue of COVID‐19 patients, monocytes and macrophages infiltrate to choroid plexus across the blood–brain barrier and lead to IRF8‐, ATF5‐, SPI1‐, and TAL1‐mediated activation of microglia inflammatory responses, including cellular activation, mobility, and phagocytosis.COVID‐19 causes cardiac dysfunction in up to 25% of diagnosed patients, independent of disease severity.During to the systematic tissue damage in individuals with COVID‐19, various comorbidities are observed in this population. Transcriptomic analysis conducted in the male reproductive system revealed that during the high expression levels of ACE2 in testis, SARS‐CoV‐2 infection‐correlated spermatogenesis damage was observed.4Nowadays, proteomics has been widely used to study and develop therapies of different diseases. In the COVID‐19 pandemic, the application of proteomics can be roughly divided into two aspects: one is directly applied in virus characterization, including pathogen diagnosis, mutation identification, posttranslational modifications, and so on; the other is for monitoring the impacts of infection on host cells at the protein level, including discovery of potential therapeutic targets, understanding the pathologic processes and the immunogenicity, revealing the antiviral mechanism of drugs, as well as detection of biomarkers for disease course and prognosis Figure .4.1The development of sensitive and specific SARS‐CoV‐2 detection tool is of utmost priority for the control of its transmission, and early diagnosis of infection will help clinicians administer timely intervention to prevent possible disease progression. At present, the most widely used SARS‐CoV‐2 diagnosis method is RT‐PCR, which is also supposed to be a gold standardRecently, mass spectrometry (MS)‐based proteomic methods with rapid and sensitive superiority have been applied for SARS‐CoV‐2 diagnostic testing. Targeted proteomic analysis was conducted to identify candidate viral peptides targets for SARS‐CoV‐2 detection.4.2Identification of disease courses of COVID‐19 is essential to implement preventive measures and personalized intervention, especially in critically patients. Researchers have carried out a number of proteomic studies on different samples to find valuable biomarkers that can accurately predict the COVID‐19 disease trajectories.By analyzing plasma proteomics of COVID‐19 patients, researchers found that some plasma proteins could be used as biomarkers to predict the disease severity. Haljasmägi et al.In face of the long‐term recovery of the prognosis of patients infected by SARS‐CoV‐2, Doykov et al.4.3Investigating the pathogenesis and discovering the potential therapeutic targets of COVID‐19 are critical for the healthcare systems to provide correct interventions. Recently, based on proteomics technology, researchers have performed various attempts and discovered many emerging therapeutic targets. These studies can be roughly divided into three strategies: one is to screen antiviral targets at the cellular level, which is based on the use of human cell lines expressing SARS‐CoV‐2 proteins to explore potential interacting proteins; the other is to directly study the proteomics of various tissue samples from COVID‐19 patients and construct the protein–protein interaction network; the third is to integrate, summarize, and analyze the published proteomic data for revealing more targets with high efficiency and low toxicity.In a pioneering study on COVID‐19, Gordon et al.Viral RNA‐binding proteins in the host play a central role in viral replication cycle. Considering that, researchers systematically analyzed viral RNA–protein interactions in cells and revealed that multiple host and viral RNA‐binding proteins are involved in SARS‐CoV‐2 infection.Multiorgan proteomic landscape was generated based on autopsy samples from seven organs of 19 COVID‐19 patients. The outcomes of this study uncovered multiple biological and pathological processes involved in COVID‐19, which offer a unique perspective for understanding the pathogenesis and provide novel insights into potential targets for the treatment of SARS‐CoV‐2 infection.In addition to perform direct proteomic analysis of SARS‐CoV‐2 infected samples, researchers also reanalyzed published proteomics data. Bock and Ortea5Metabolomics studies focus on the analysis of metabolites perturbations induced by diseases and infection. As direct signatures of disease onset and infection, metabolites can help researchers quickly determine pathogenesis, potential therapeutic targets, as well as cell or tissue damage, and it can also be used as biomarkers to monitor disease progression. At present, metabolomics, including amino acid metabolism, glucose metabolism, lipid metabolism, purine and pyrimidine metabolism, and so on, have been widely applied in the emerging COVID‐19 pandemic. Herein, we summarize the application of metabolomics in identifying pathogenic mechanisms, discovering antiviral targets, and exploring biomarkers from three aspects, namely amino acid metabolism, glucose metabolism, and lipid metabolism Figure .5.1Multiple studies have shown that most amino acid metabolism systems, including branched chain amino acids (BCAAs), aromatic amino acids, gluconeogenic amino acids, and so on, are vulnerable to SARS‐CoV‐2 infection. Here, we mainly review the research progress of several amino acids that are more tightly associated with COVID‐19.Aside from tryptophan/5‐hydroxytryptamine pathway, tryptophan can be metabolized to nicotinamide adenine dinucleotide (NAD) via Kynurenine pathway. Of note, Kynurenine pathway was found to be susceptible to SARS‐CoV‐2 infection and its metabolite, anthranilic acid, could be used as a potentially prognostic biomarker for the evolution of COVID‐19.Moreover, Shen et al.Arginine can regulate the activation of host immune cells and resist pathogens infection. Multiple metabolites involved in arginine metabolism also showed abnormal levels in COVID‐19 patients.5.2Lipid metabolism has a close association with glucose metabolism, and certain metabolites of the two pathways are mutually interconverted. SARS‐CoV‐2‐induced metabolic reprogramming, including lipid metabolism, glycolysis, and tricarboxylic acid (TCA) cycle, provide a comprehensive molecular view of the pathophysiology of COVID‐19. For instance, lipid participates in every process of viral propagation and invasion, and a remarkable alternation of lipid, lipid mediators, and related metabolic pathways was observed in COVID‐19 patients.5.2.1® substrate in paper spray MS (PS‐MS) to determine the metabolomic biomarkers of SAR‐CoV‐2 infection within 60 s of analysis time, and further identified 11 metabolites for integrative analysis using symptomatic PCR. Using metabolomics strategy, multiple metabolites in the exhaled air of COVID‐19 patients were considered to have the potential for SARS‐CoV‐2 detection and as biomarkers of disease deterioration.Compared with proteomics, the pretreatment of lipid samples is simpler and the detection efficiency is higher, which helps to achieve rapid determination of SARS‐CoV‐2 infection and mirror the severity of COVID‐19.5.2.2d‐fructose, citric acid, and 2‐palmitoyl‐glycerol can be applied to distinguish SARS‐CoV‐2‐infected patients from healthy people; and 2‐hydroxy‐3‐methylbutyric acid, 3‐hydroxybutyric acid, cholesterol, succinic acid, l‐ornithine, oleic acid, and palmitelaidic acid can accurately predict the possibility of severe conditions.2 is a class of enzymes that hydrolyze phospholipids to produce fatty acids and lysophospholipids, and specifically, phospholipase A2 Group IIA can be used to distinguish SARS‐CoV‐2 infection or not and the gravity of diseases.Through metabolomics analysis of serum samples of COVID‐19 patients, it was found that multiple metabolites related to glucose metabolism and lipid metabolism can be used as biomarkers for COVID‐19 disease monitoring. Shi et al.5.2.3SARS‐CoV‐2 infection is closely associate with body's physiological functions and metabolic regulation. Cytokine release syndrome (CRS) is the main cause of multiorgan injury and fatal outcome in critical COVID‐19 patients. Xiao et al.Using untargeted and targeted metabolomic method, Jia et al.With respect to arachidonic acid and its lipid mediators , there is a close correlation with COVID‐19 pathophysiology. Importantly, arachidonic acid and other unsaturated fatty acids (such as eicosapentaenoic acid and docosahexaenoic acid [DHA]), as well as their metabolites not only can be regarded as potential antiviral agents, but also play a role in inflammation regulation in severe COVID‐19.The elevation of ketone bodies  was reported in the serum of COVID‐19 patients, indicating a pathological condition in which the liver has an abnormal capacity to oxidize acetyl‐CoA.6Omics technologies are remarkable research approaches for the development of rapid responses to emerging or reemerging infectious diseases. In case of the COVID‐19 pandemic, omics techniques help researchers and clinicians to comprehensively understand and recognize the SARS‐CoV‐2 virus and correlated COVID‐19. Based on the surveillance of the SARS‐CoV‐2 sequences, mutations and variants mediated potential uncontrolled outbreak are closely monitored. And transcriptomics, proteomics, and metabolomics work together to elucidate the underneath pathogenesis of COVID‐19, which will facilitate the identification of biomarkers, risk factors, and drug targets of SARS‐CoV‐2 infection, and realize the early diagnosis and treatment of COVID‐19, so as to fight against the worldwide spread COVID‐19 pandemic.The authors declare no conflict of interest.Not applicable.Jingjing Yang and Yunzheng Yan collected the literatures and drafted manuscript. Wu Zhong revised and edited the manuscript. All authors approved this manuscript for publication.


Ultrasound revealed a right liver tumour, segment VI, measuring at 56 × 53 mm. According to images of ultrasound and MRI, the diagnosis was mesenchymal hepatic sarcoma. The paediatric patient had surgery to remove the entire liver segment containing the tumour. Micropathological examination showed that the tumour was a MHL. The serum AFP level fell rapidly to near normal following the surgery. The MHL benign liver tumour with an atypical presentation caused a very high AFP level. This was a rare clinical case, and it was difficult to diagnose.Mesenchymal hamartoma of the liver (MHL) is a benign tumour that most commonly occurs in children. In most cases of MHL, the α fetoprotein (AFP) level is within the normal limits, only in a few cases, increased AFP has been described which usually causes misdiagnosis of hepatoblastoma. We report a case of a 3-month-old paediatric patient who was incidentally detected with a very high level of AFP, at 6388.4 ng ml This benign tumour usually occurs in children, from birth to 2 years.3The oldest MHL cases were reported in 1959 and 1966. Additional cases have been reported until 2012. In total, less than 200 cases have been reported in the English literature.4MHL is a benign developmental malformation composed of a mixture of loose mesenchymal tissue, bile ducts, connective tissue and hepatocytes with cysts formed either from degenerative areas of mesenchymal or from dilated bile ducts and lymphatics. It is not a true tumour.5The tumour is usually in the form of a large cyst, with macrolobulated margin, multiple septae or a dense tumour containing of small cysts.−1 have been reported in the medical literature.3In most MHL cases, α fetoprotein (AFP) levels are within the normal limits. Only in a few cases with increased AFP, it is easily confused with hepatoblastoma. Very few reports of AFP level above 6000 ng mlWe report a special clinical case of a MHL of a 3-month-old paediatric patient with very high AFP level.A 3-month-old male paediatric patient was with a normal birth to full term. He was breastfed by his mother and weighted at 7.2 kg. His mother was healthy and there was no known liver disease in his family.−1. AFP-L3 and PIVKA (DCP) were within the normal limits, (AFP-L3 <0.5% and DCP was at 15 mAU/mL)  .At that time, an abdominal ultrasound revealed a right hepatic lesion, located in the segment VI, measuring 56 × 54 mm. The mixed echo cystoid tumour was unclearly delineated, multi curvilinear, with a solid content, hyper-echogenicity, echogenic vasculature and liquid with many echogenic septa inside. The solid content had low stiffness around 6.6 kPa in real-time 2D shearwave elastography. .Contrast-enhanced MRI detected a right hepatic lesion in the segment VI, measuring 56 × 53 mm. The lesion had heterogeneous high signal intensity to the liver parenchyma in T2W, heterogeneous low signal intensity in T1W, heterogeneous gadolinium contrast opacification, peripheral enhancement of the arterial phase, progressive centripetally in the venous phase and late phase without filling the whole lesion. Delayed phase was taken through dynamic T1WI vibe pulse with contrast agent, which was recorded after 5–7 min from beginning of artery phase. .−1. AFP L3 and DCP remained within normal limits .5 MHL is rare in adults. Commonly, males are more affected in children while females are more affected in adults.1,6MHL is a rare disease. This benign tumour usually occurs in children, between birth and 2 years of age,3The oldest MHL cases were reported in 1959 and 1966. Additional cases have been reported until 2012. In total, less than 200 cases have been reported in the English literature.5These tumours often have many cysts, ranging in size from a few millimetres to more than 10 cm, and are heterogeneous filled with a thick fluid. However, they may also be solid or of mixed forms. Ultrasound, CT and MRI showed images of a large cystic liver tumour, with a scalloped border, multiple septa or a solid mass of small cysts. The solid tissue composition of the tumour was revealed after the contrast agent injection.7,8Radiographically, MHL is easily misdiagnosed as mesenchymal hepatic sarcoma. However, mesenchymal hepatic sarcoma is very rare, with clinical manifestations of abdominal pain, weakness, loss of appetite and weight loss. Mesenchymal hepatic sarcoma often shows signs of vascular invasion and biliary obstruction.−1 in 256 normal infants. AFP levels decreased by 50% after the first 5 days, then continued to decrease to 16–1995 ng ml−1 (average 178 ng ml−1) by 2 months of age and to 6–1045 ng ml−1 (average 80 ng ml−1) at 3 months of age. From 6 months to 2 years, AFP ranged from 0.8 to 87 ng ml−1 (average 8 ng ml−1).9AFP is a plasma glycoprotein that has a high level in fetal blood, is relatively high in newborns and gradually decreases to normal. M. E. C. Blohm et. al. analysed 524 samples who were aged from infants to 2 years at Düsseldorf University Hospital (Germany). At birth, the mean serum AFP level was 41687 ng ml−1 have been reported in the medical literature.3,10In most MHL cases, the AFP is within the normal range. Only a few cases demonstrated increased AFP, so it was easily confused with hepatoblastoma. Very few reports of an increase in AFP above 6000 ng ml11,12A.Habador et. al reported a case of mesenchymal hepatic hamartoma, which was diagnosed as hepatoblastoma before surgery. The author believes that mesenchymal hamartoma and hepatoblastoma are common liver tumours in children. They have similar geometrical and pathological features. If the serum AFP is measured in a patient, an accurate diagnosis can be made before surgery, since AFP is largely elevated in hepatoblastoma. When in doubt, serum AFP is a good guide for differentiating hepatoblastoma from mesenchymal hamartoma.−1. After 1 month, there was a decrease, but it was still at a high level at 2176.4 ng ml−1. AFP decreased rapidly in 1 month after the surgery removed the whole segment containing the tumour, at 74 ng ml−1. Two months after the surgery, AFP continued to decrease to near the normal limit at 44.4 ng ml−1. It showed that the increase in AFP in this patient was related to the benign MHL tumour. AFP L3 and PIVKA II (DCP) were in normal range before and after the surgery.In this case study, the AFP was very high. Before surgery, AFP level was 6388.4 ng ml13Increased AFP and AFP-L3 are indicators for more accurate diagnose of malignant liver tumours for the newborn.Mesenchymal hepatic hamartoma is a rare benign tumour that sometimes increases AFP level in the blood, causing a misdiagnosis of hepatoblastoma.MHL usually presents as a large cystic, multilobulated, multi-septae or solid tumour with small cysts inside. The solid tissues of the tumour were revealed after enhancement by a contrast agent injection.On imaging diagnose, MHL was misdiagnosed as mesenchymal hepatic sarcoma. To diagnose more accurately, we need to look for signs of vascular and biliary tract invasion in order to differentiate between MHL and mesenchymal hepatic sarcoma.It is very difficult to diagnose liver tumours in children. The diagnosis should rely not only on imaging results but also many other factors.In the event of a mismatch between the imaging results and the tumour markers, a liver biopsy should be performed.Before performing surgery, the patient should be monitored to ensure the malignant diagnosis is correct. If the tumour markers decrease, a diagnosis of benign tumour should prevail.


In Japan, over 25% of the population is elderly. As the risk of lung cancer increases with age, the number of elderly patients with lung cancer also increases. Given the challenges of an aging society, it is critical that elderly patients receive safe therapies.We assessed the safety and efficacy of immune checkpoint inhibitors (ICIs) in patients with non‐small cell lung cancer (NSCLC) aged ≥80 years.We retrospectively reviewed NSCLC patients aged ≥80 years old who received ICIs in the National Hospital Organization Kyoto Medical Center. We collected data on patient characteristics, prior treatments, number of cycles, response, and immune‐related adverse events (irAEs) during ICI monotherapy.A total of 45 patients were reviewed. The patients' median age was 85 years. Twenty‐one, 17, and 7 patients received nivolumab, pembrolizumab, and atezolizumab, respectively. The disease control rate  was 60.0%, and the progression‐free survival was 3.4 months. In patients with nivolumab, seven patients (33.3%) achieved SD, and three patients (14.2%) achieved PR. In patients treated with pembrolizumab, seven patients (41.2%) achieved SD, and six patients (35.3%) achieved PR. In patients with atezolizumab, three patients (42.9%) achieved SD, and one patient (14.2%) achieved PR. Sixteen (36%) patients presented with a poor performance status. Three patients treated with pembrolizumab experienced grade 3 pneumonia, while one patient treated with nivolumab experienced grade 5 pneumonia.This study suggested that ICIs are an acceptable treatment option for NSCLC patients aged ≥80 years. Oncologists should pay attention to severe irAEs. Inevitably, the incidence of lung cancer is higher in older populations, and the median age for the diagnosis of lung cancer is around 70 years.In this study, we aimed to evaluate the efficacy and safety of ICIs in patients aged 80 years or older with non‐small cell lung cancer (NSCLC).2This retrospective cohort study was conducted at the National Hospital Organization Kyoto Medical Center (600 beds), in Kyoto, Japan. We reviewed the clinical data of patients with NSCLC aged 80 years or older who received anti‐PD‐1 antibodies and anti‐PD‐L1 antibodies between December 2015 and April 2020. All patients had pathologically confirmed NSCLC. We included patients treated with nivolumab, pembrolizumab, or atezolizumab ICI monotherapy irrespective of any history of previous cytotoxic, epidermal growth factor receptor (EGFR), or tyrosine kinase inhibitor (TKI) therapy. We administered nivolumab, pembrolizumab, and atezolizumab at 3 mg/kg or 240 mg/body biweekly, 200 mg/body every 3 weeks, and 1200 mg/body every 3 weeks, respectively.We collected data on patient characteristics, the number of treatment cycles, progression‐free survival (PFS), treatment regimens, best response, and immune‐related adverse events (irAEs). We evaluated the PD‐L1 expression with tumor proportion score (TPS). We divided TPS into four groups as follows: ≥50%, 1%‐49%, <1%, and unknown. Treatment response was evaluated based on the Response Evaluation Criteria in Solid Tumor version 1.1.33.1We reviewed 45 patients with NSCLC who were ≥80 years of age. Patient characteristics are described in Table 3.2Table 3.3Table 4Japan possesses the world's oldest population, and consequently, a major challenge lies in how to manage the high rates of malignant diseases that invariably develop in elderly people. Indeed, the cumulative lifetime risk of cancer incidence, estimated based on cancer incidence data in 2012, is 63% for men and 47% for women.A previous study reported that patients aged <75 years treated with ICI showed favorable overall survival and PFS compared with similarly aged patients in the non‐ICI groups.In patients receiving nivolumab, 5 (23.8%) patients presented with an irAE of any grade, which is less than the frequency reported in a previous study where 50% of patients sustained an irAE.There were several limitations to our study. First, this study was retrospective in nature and was conducted in a single institution. Moreover, we only included a small sample size, and invariably suffered from bias in the selection of participants. Second, although all patients received ICIs, we did not consider the effects of regimens prior to ICIs. Thirty‐eight (84%) patients had at least 1 cycle of cytotoxic chemotherapy and a molecular target drug prior to ICIs. This may have induced a depressive immune response. Consequently, we cannot rule out that using ICIs as a first‐line regime would produce better results. Third, the timing of treatment was chosen by the attending doctors; therefore, it was not standardized between patients.In conclusion, ICI monotherapy, especially pembrolizumab and atezolizumab, is a reasonable treatment option for patients with lung cancer aged 80 years or older. More attention in the clinic should be placed on evaluating the development of severe irAEs during immunotherapy.The authors have stated explicitly that there are no conflicts of interest in connection with this article.Conceptualization; data curation; formal analysis; investigation; methodology; writing‐original draft; writing‐review & editing, Z.S.; Conceptualization; data curation; formal analysis; funding acquisition; investigation; methodology; project administration; resources; software; supervision; validation; visualization; writing‐original draft; writing‐review & editing, K.F.; Data curation; project administration; supervision, M.O.; Methodology; project administration; supervision, T.I. and Y.Y.; Investigation; project administration; supervision; validation, O.K.; Investigation; project administration; supervision, M.H.; Investigation; methodology; supervision, K.N. and S.S.; Conceptualization; investigation; methodology; supervision, T.M.This study protocol was approved by the Ethical Committee and the Institutional Review Board of the National Hospital Organization Kyoto Medical Center .


Six Sigma (6σ) is an efficient laboratory management method. We aimed to analyze the performance of immunology and protein analytes in terms of Six Sigma.Assays were evaluated for these 10 immunology and protein analytes: Immunoglobulin G (IgG), Immunoglobulin A (IgA), Immunoglobulin M (IgM), Complement 3 (C3), Complement 4 (C4), Prealbumin (PA), Rheumatoid factor (RF), Anti streptolysin O (ASO), C‐reactive protein (CRP), and Cystatin C (Cys C). The Sigma values were evaluated based on bias, four different allowable total error (TEa) and coefficient of variation (CV) at QC materials levels 1 and 2 in 2020. Sigma Method Decision Charts were established. Improvement measures of analytes with poor performance were recommended according to the quality goal index (QGI), and appropriate quality control rules were given according to the Sigma values.NCCL, 90% analytes had a world‐class performance with σ>6, Cys C showed marginal performance with σ<4. While using minimum, desirable, and optimal biological variation of TEa, only three , one (CRP), and one (CRP) analytes reached 6σ level, respectively. Based on σNCCL that is calculated from TEaNCCL, Sigma Method Decision Charts were constructed. For Cys C, five multi‐rules  were adopted for QC management. The remaining analytes required only one QC rule . Cys C need to improve precision (QGI = 0.12).While using the TEaThe laboratories should choose appropriate TEa goals and make judicious use of Sigma metrics as a quality improvement tool. NCCL, providing us with a visual view of the analytes’ performance. For Cys C with σ<6, the cause for poor performance was evaluated using QGI.We first evaluated the performance of 10 immunology and protein analytes based on four different sources of TEa. Further the Sigma Method Decision Charts were constructed in terms of TEa How to ensure test performance, provide patients with accurate and reliable results, and provide support for doctors’ diagnosis and treatment are the primary goals of medical laboratories. For this reason, Six Sigma is obviously a rare good tool for quality control (QC). Sigma, which has a statistical appellation—“Standard Deviation,” represents the data dispersion.Quality control is an important part of clinical laboratory management. As a commonly used quality management tool, Six Sigma management program can effectively evaluate the performance indicators of analytes, help the laboratories find problems in time. The “Six” in Six Sigma represents the ideal goal that anything beyond those tolerance specifications is considered a defect.In this study, we evaluated the performance of 10 immunology and protein analytes by calculating their Sigma values based on Bias%, CV%, and four different sources of TEa%. Based on the calculated Sigma value, the QC strategies were personalized and Sigma Method Decision Charts were established. Improvement measures of analytes with σ below 6 were recommended according to the quality goal index (QGI).22.1This study included four steps Figure . The stu2.2Roche c8000  automatic biochemical analysis system was used to quantify the 10 analytes: Immunoglobulin G (IgG), Immunoglobulin A (IgA), Immunoglobulin M (IgM), Complement 3 (C3), Complement 4 (C4), Prealbumin (PA), Rheumatoid factor (RF), Anti streptolysin O (ASO), C‐reactive protein (CRP), and Cystatin C (Cys C). All analytes adopted the principle of immunoturbidimetry. All the reagents and calibrators were Roche original except CRP from Sekisui , PA from Kehua , and Cys C from Mindray .Two‐level internal quality controls (IQC)  were analyzed, all controls were operated in strict accordance with the manufacturer's instructions.Five‐level materials of external quality assessment (EQA) with different concentrations of the analytes were provided by the National Center for Clinical Laboratories . Cys C (NCCL‐C‐14) had only one EQA plan in year 2020 with lots of 202011, 202012, 202013, 202014, and 202015. The remaining nine analytes, which was called “Special proteins plan (NCCL‐C‐06),” had two EQA plans: lots for the first EQA plan were 202011, 202012, 202013, 202014, and 202015; lots for the second EQA plan were 202021, 202022, 202023, 202024, and 202025. Each level material was dissolved in pure water according to the manufacturer's instructions.2.312 + CV22) /2]0.5.Imprecision is estimated using the coefficient of variation (CV%) which is a measure of variability and indicator of random errors. The two IQC levels of cumulative coefficient of variation (CV%) were collected from the Laboratory Department of Guangdong Provincial Hospital of Chinese Medicine from January 1 to December 31, 2020. Each analyte had two concentration levels. The root mean square coefficient of variation (RMS CV%) was calculated.2.4Bias is an indicator of systematic errors. The laboratory was involved in the EQA program by analyzing five different concentration proficiency test (PT) samples provided by NCCL. PT samples were dissolved in pure water according to the NCCL’s instructions, each PT sample was tested for 3 days to obtain three results, and the mean of the three results was calculated and assigned as “Measured mean in our laboratory.” NCCL groups the submitted data according to the instruments or reagent manufacturers that participants use, and takes the ISO13528 robust average value in the group as the target mean. Seven analytes  were grouped according to the instrument, while the other three analytes  were grouped according to reagent manufacturers due to non‐Roche reagents. The target mean assigned by NCCL of each analyte was considered as target value. Excluding unqualified PT data (Data exceeding two standard deviations of the mean), the calculation equation was as followsBias%=│Measured mean in our laboratory‐Target mean assigned by NCCL│/(Target mean assigned by NCCL)×100%.The average bias of each analyte, which was calculated by 1‐year accumulative bias of each analyte sourced from the NCCL plans in 2020, was used in the calculation of Sigma.2.5NCCL.  the biological variation database specifications , designated as TEaBVmin, TEaBVdes and TEaBVopt. BV provided by EFLM.TEa  represents the allowable difference between measured value and trueness. Four different TEa targets were used in this study: (Ⅰ) TEa derived from the quality goals issued by the China National Center for Clinical Laboratories (NCCL) in 2017,https://biologicalvariation.eu/)BV are calculated using the formula:/CV%.2.7https://www.nccl.org.cn/loginCn), entering TEa%, Bias%, and CV% of each analyte which is obtained through the above steps in the interface of the Six Sigma management menu, the Sigma Method Decision Charts are composed with CV%/TEa% along the x‐axis and Bias%/TEa% along the y‐axis.Logging in the NCCLnet . A QGI value less than 0.8 (QGI <0.8) indicates that the precision needs to be improved, whereas a value greater than 1.2 (QGI >1.2) indicates that the accuracy needs to be improved. A QGI value between 0.8 and 1.2 (0.8 ≤ QGI ≤1.2) indicates that both accuracy and precision need to be improved. Analytes with lower Sigma were analyzed according to QGI, that is, the problem was due to precision or accuracy or combination of both, helping the laboratories to take targeted measures.33.1Cumulative Mean, SD, and CV% of two IQC levels were shown in Table 3.2NCCL, 90% (9/10) analytes had a world‐class performance with σ>6, Cys C showed marginal performance with σ<4. However, while we chose the TEa based on biological variation database specifications, the Sigma values were not so satisfactory. Since the TEaBVmin of only two analytes IgM and CRP were looser than TEaNCCL, σBVmin of IgM, and CRP were greater than σNCCL. The other 8 analytes had lower σBVmin than σNCCL. Using minimum biological variation of TEa, seven of the nine analytes (excluded ASO) exhibited a performance of at least 3σ ,and three of these analytes  had a world‐class performance. While using desirable and optimal biological variation of TEa, only one analytes (CRP) reached 6σ level, with poor or unacceptable Sigma values of the remaining nine analytes. TEaBV is too strict for our laboratory, we chose the TEaNCCL specifications for the follow‐up analysis, such as QGI analysis, the QC strategies construction, and composition of Sigma Method Decision Charts.Table 3.3NCCL , one measurement of two QC levels (N = 2) per QC event, and up to 1000 clinical samples in a round of quality control (Batch length: 1000) were adopted for QC management. For Cys C that had “marginal” performance, five multi‐rules (13s/22s/R4s/41s/6X) with N = 6 and up to 45 clinical samples in a round of quality control (Batch length: 45) were adopted for QC management. The calculated QGI (0.12) showed that Cys C had low precision and required a close monitoring and troubleshooting from the aspects of personnel, equipment, material, method, and environment in the daily QC.QC strategies were reset according to σed Table . For ana4NCCL, providing us with a visual view of the analytes’ performance. For analytes with σ<6, the cause for poor performance was evaluated using QGI similar to previous studies.In this study, we evaluated the performance of 10 immunology and protein analytes (which named after their BIO‐RAD controls—“Immunology and Protein Control”) at the Laboratory Department of Guangdong Provincial Hospital of Chinese Medicine for a one year period based on Sigma metrics. The previous studies mainly focused on the evaluation of analytical performance of clinical biochemistry analytes,CLIA in subsequent calculations. The Sigma metrics of 10 immunology and protein analytes were shown in Table According to the equation Sigma = (TEa% ‐ Bias%)/CV%, significantly different σ values are obtained using the same Bias% and CV% but different total allowable error targets similar to the previous studies,NCCL, 9 analytes for IgG, IgA, IgM, C3, C4, CRP, RF, PA, and ASO had a world‐class performance with σ>6, Cys C showed marginal performance with σ<4. On the other hand, while we chose the TEaBV, the Sigma values were quite different, even negative (C3). TEa sources play an important role in the calculation of Sigma value.BV is too strict for our laboratory, after a comprehensive analysis of laboratory status, analytes’ performance, and clinical recognition, therefore, in the subsequent analysis, we chose TEaNCCL as performance specifications.As mentioned above, surprisingly, while using the TEaAfter calculating the Sigma value, how can we have a more intuitive impression of these results? At this time, Sigma Method Decision Charts are on the stage, which converts all the Sigma metrics into a simple intuitive dashboard.3s/22s QC procedure with two QC levels once per day for the 10 immunology and protein analytes empirically to supervise the performance of analytes in the past. By using Sigma metrics, nine analytes for σ>6 can safely use the 13s procedure with one measurement of two QC levels to gain an appropriate level of analytical quality assurance, avoiding economic costs, and overwork. On the contrary, with the decline in performance, more quality control rules, more different levels of quality controls, and higher quality control frequency are required. As Cys C in this study, that had “marginal” performance, five multi‐rules (13s/22s/R4s/41s/6X) were needed and the QC frequency could be increased to one control per 45 clinical samples. As Cys C had 38 average daily measurements in our laboratory,one time QC frequency per day is needed.Sigma metrics are not just a tool to ascertain the performance of analytes but also a beacon for designing a more cost‐effective QC strategy. Through the assessment of Sigma metrics, we can specify the control rules scientifically, including the number of control materials and the necessary frequency of running those controls. The closer the operating dot of an analyte is to the chart's origin, the easier the QC program is. In our laboratory, we chose 13s/22s QC procedure increased to 0.995 using 13s/22s/R4s/41s/6X rules, but also higher probability of false rejection (Pfr), from 0.006 using 13s/22s QC procedure increased to 0.095 using 13s/22s/R4s/41s/6X rules. In future studies, the other aspects should be prioritized to generate more conclusive results.Though the Westgard Sigma multi‐rules provide a scientific and reasonable method for setting QC procedure, it could not fully reflect the precision and accuracy of the method. QGI is a tool to provide easy insights into the reasons for quality errors such as those caused by imprecision, inaccuracy, or both.Nevertheless, there were three aspects of limitations in this research as follows: (Ⅰ).Because the target means in PT/EQA plans were derived from statistical results of peer groups without measurement traceability,This research can provide support for laboratories to select detection systems for these 10 analytes and aid individual laboratories in their choice of proper TEa goals and in working out a detailed troubleshooting action plan as a part of their quality improvement tool. Laboratory staffs can use these tools to help them select high‐quality products, further contributing to the delivery of excellent quality healthcare for patients. The result is more efficient instrument operation, more optimized laboratory workflow, and more reliable test results, ultimately helping clinicians better diagnose and treat their patients.None declared.YL and SO designed the study, drafted the work, analyzed and interpreted the data, and wrote this article; XY, QX, YL, and JP searched the literature, performed the experimental procedure; QL, YC, YC, and HZ supervised this study and reviewed this article; CC reviewed this article. All authors have read and approved the final manuscript.Table S1Click here for additional data file.Supplementary MaterialClick here for additional data file.


Diuretic braking during furosemide continuous rate infusion (FCRI) curtails urine production.Renin‐angiotensin‐aldosterone system (RAAS) activation mediates braking, and RAAS inhibition will increase urine production.Ten healthy purpose‐bred male dogs.Dogs received placebo, benazepril, or benazepril and spironolactone PO for 3 days before a 5‐hour FCRI (0.66 mg/kg/h) in a 3‐way, randomized, blinded, cross‐over design. Body weight (BW), serum creatinine concentration (sCr), serum electrolyte concentrations, PCV, and total protein concentration were measured before PO medications, at hours 0 and 5 of FCRI, and at hour 24. During the FCRI, water intake, urine output, urine creatinine concentration, and urine electrolyte concentrations were measured hourly. Selected RAAS components were measured before and after FCRI. Variables were compared among time points and treatments.Diuretic braking and urine production were not different among treatments. Loss of BW, hemoconcentration, and decreased serum chloride concentration occurred during FCRI with incomplete recovery at hour 24 for all treatments. Although unchanged during FCRI, sCr increased and serum sodium concentration decreased at hour 24 for all treatments. Plasma aldosterone and angiotensin‐II concentrations increased significantly at hour 5 for all treatments, despite suppressed angiotensin‐converting enzyme activity during benazepril background treatment.The neurohormonal profile during FCRI supports RAAS mediation of diuretic braking in this model. Background treatment with benazepril with or without spironolactone did not mitigate braking, but was well tolerated. Delayed changes in sCr and serum sodium concentration and incomplete recovery of hydration indicators caused by furosemide hold implications for clinical patients. ACEangiotensin‐converting enzymeAGanion gapBPblood pressureBUNblood urea nitrogenBWbody weightCHFcongestive heart failure−ClchlorideFCRIfurosemide continuous rate infusionHCO3−bicarbonate+Kpotassium+NasodiumPO4−phosphorusRAASrenin‐angiotensin aldosterone systemsCrserum creatininesNa : sKserum sodium to potassium ratioTStotal solidsUAldo : Curine aldosterone to creatinine ratiouNa : uKurine sodium to potassium ratio1Furosemide continuous rate infusion (FCRI) has been shown to cause more urine production than bolus administration of the same dose in normal dogs and normal horsesBecause RAAS stimulation may be mechanistically important to the phenomenon of diuretic braking, and because RAAS inhibitors may protect against adverse effects of diuretics, such as electrolyte depletion and other harmful aspects of diuretic‐induced RAAS activation,22.1The Institutional Animal Care and Use Committee at the North Carolina State University Veterinary Hospital approved this study (protocol #17‐075‐O). The study consisted of a 3‐way crossover design utilizing 10 healthy, male, purpose‐bred dogs, for a total of 30 dog studies. Treatment order was randomized and investigators were blinded to treatment. Each dog underwent all 3 treatments before FCRI, with a 17‐day washout period between crossovers.+) content of 112 mg/100 kcal  twice daily (7 am and 4 pm) before and during the study, except that food was withheld on the morning of baseline blood collection and on the morning of the study. The study timeline is shown in Figure Treatments consisted of PO medications once daily at 7 am for 3 days before and including the morning of FCRI (3.3 mg/kg administered as an IV infusion over 5 hours) diluted to 2.2% with dextrose 5% in water after a 0.66 mg/kg IV loading bolus of furosemide. Medications were placed in an opaque gel capsule and consisted of cellulose as placebo (treatment A), benazepril 0.25 mg/kg minimum dose (treatment B), and benazepril 0.25 mg/kg and spironolactone 2 mg/kg minimum doses (treatment C). Benazepril and spironolactone dosages were selected based on results of studies indicating favorable modulation of the RAAS utilizing these dosages in dogs.2.2Dogs were fasted the morning of each study but PO medications were administered. After body weight (BW) was obtained, 2 peripheral IV catheters (18 gauge) were placed for blood sampling, administration of sedative medication for urinary catheter placement (butorphanol 0.3 mg/kg IV), and administration of furosemide during the study period. A urinary catheter  was passed into the urinary bladder, attached to a closed collection system and sutured to the skin. The urinary bladder was emptied before the baseline period. Dogs were allowed to recover from sedation until they could stand (hour −2 to hour −1) and were continuously monitored throughout the study. Water was available at all times. The FCRI ran for 5 hours and urinary and peripheral catheters were removed at the end of each study infusion (at hour 5).2.3+, serum potassium [K+], serum chloride [Cl−], serum phosphorus [PO4−], serum bicarbonate [HCO3−], anion gap [AG], PCV, total solids [TS], plasma angiotensin II concentration, BW, and blood pressure [BP]) were obtained in the morning (9 am on day −4). Blood for plasma angiotensin II concentration was obtained again at 3 pm to evaluate diurnal variation,Results for baseline variables , HCO3−, AG, PCV, TS, BW, BP, hourly urine volume (per kg BW), plasma angiotensin II concentration, urine aldosterone concentration, urine creatinine concentration, urine Na+ concentration, and urine K+ concentration. Urine volume, plasma aldosterone concentration, urine aldosterone concentration, and urine creatinine concentration were measured hourly during the 5‐hour FCRI. Final data collection was performed 24 hours after the start of the FCRI and included blood collection for BUN, sCr, serum electrolyte concentrations , HCO3−, AG, PCV, TS, BW, and BP. Residual serum samples were used to measure ACE activity by radioenzymatic assay and both chymase activity and ACE activity by equilibrium analysis at hour 0, hour 5, and hour 24. Residual samples for hour −96 were not available for these analyses.Data collection on the day of each study began after recovery from sedation and during the 1‐hour baseline period before the 5‐hour FCRI (hour −1 to 0). Baseline study data (at hour 0 before the start of the FCRI) and at the end of the FCRI (hour 5) included BUN, sCr, serum electrolyte concentrations  at the clinical pathology laboratory of the North Carolina State University Veterinary Hospital.2.4.2Aldosterone concentrations (pmol/L) in plasma and urine were measured using a commercially available radioimmunoassay kit , at a veterinary diagnostic laboratory  following manufacturer's instructions as previously described.2.4.3g, +4°C). Plasma was withdrawn and placed into cold plastic cryo‐tubes and snap frozen using liquid nitrogen within 10 minutes, for immediate storage at −80°C until analysis. A commercially available enzyme‐linked immunoassay was used to assay plasma samples for angiotensin II concentrations in pg/mL .A commercially available protease inhibitor was utilized to prevent generation of or degradation of angiotensin II ex vivo in plasma  as previously described.2.4.4Activity of ACE (U/L) was directly measured in serum using a radioenzymatic assay  as previously described .2.4.5+ × sCr]/[serum Na+ × uCr]).Body weight change was calculated by comparing BW to that of the previous time point. Absolute BW was not used for group and time comparisons because of the size differences among dogs. Urine aldosterone amount (μg) was indexed to uCr amount (grams) to generate UAldo : C, an indicator of RAAS, under the assumption that renal aldosterone elimination remains constant.2.5P values for multiple comparisons and adjusted P values are reported where indicated. Power calculation, based on a previous study,P < .05.Generalized linear mixed effect modeling was performed  to evaluate for differences among treatments for repeated hourly and time point measurements. One‐way analysis of variance was used to assess for differences in urine volume among treatments with variables of time, treatment group and time : group interaction after confirming normally distributed residuals and homogeneity of variances. Least square means were estimated for measured variables and data are presented as mean and SD when normally distributed. Tukey's method was utilized to adjust 3Study dogs were clinically healthy, intact males, consisting of 8 hound dogs and 2 beagles. Median BW was 23.4 kg  and median age was 44 months .3.1P < .001) in the same pattern as previously noted, with a decrease in urine volume starting at hour 2,P = .55 for hourly urine volume, P = .59 for total urine volume; Figure +, used to indicate diuretic resistance when <0.2%, increased from hour 0 to hour 5 for all treatment groups, with no difference among treatment groups  increased over time for all treatments (3.2P < .001) but were not different among treatments . Systolic, diastolic, and mean BP were significantly higher at hour −96 (baseline before PO treatments) compared to other hours for all treatments (P < .001), but did not change significantly after hour 0 (during the FCRI or at hour 24).Absolute BW and change in BW at each time point were significantly different over time for all treatments . A significant decrease in serum Na+ concentration occurred at hour 24 for all treatments . A significant decrease in serum Cl− concentration occurred at hour 5 for all treatment groups and did not return to baseline at hour 24 . A significant increase in serum PO4− concentration was noted at hour 5 for all treatments . Similarly, a significant increase in serum HCO3− concentration occurred at hour 5 for all treatments  and in AG at hour 5 for all treatments . No change in serum K+ concentration over time (P = .4) or among treatments (P = .58) was found.Figure P < .001 over time), evident only at hour 24 for all treatments . The percentage change in sCr from hour 0 to 5 and from hour 0 to 24 was not different among treatments . The mean (SD) percentage increase in sCr from 0 hour to 24 hour was 23.9% (12.4) for all 3 treatments.Both BUN and sCr increased significantly  over time, mean results remained within the reference ranges for all variables except serum Cl− concentration, TS, and AG. Biochemical results for all treatments reflected movement toward hypochloremic metabolic alkalosis, with a resulting AG increase at hour 5, and persisting at hour 24.Despite statistically significant changes in all blood variables (except serum K3.3P = 1.0 between morning and afternoon at hour −96) or day‐to‐day variation (P = 1.0) but were significantly increased at the end of the FCRI (hour 5) compared to before the FCRI  for all treatments . Whereas UAldo : C increased in dogs receiving treatment C, the difference among treatments did not reach statistical significance (P = .08) and no overall time effect was observed (P = .72). The uNa : uK changed over time (P < .001) in concert with diuresis, but no treatment effect was noted (P = .74). The uNa : uK was >1.0 at all time points during diuresis, indicative of diuretic responsiveness.P < .008, with hour 5 significantly higher than hours −96 and 24), but no treatment effect was identified (P = .92).Hourly plasma aldosterone concentrations increased over time for all treatments (P < .001). After FCRI, treatment C (benazepril and spironolactone) ACE activity remained significantly lower than treatment A (placebo) ACE activity (P = .02 at hour 5 and P = .04 at hour 24). The ACE activity at hour 5 for treatment B (benazepril) was not significantly different when compared to treatment A , and no significant increase compared to its own baseline was observed at hour 0 (P = .6). No difference in ACE activity was identified among time points for treatment A .Direct assessment of ACE activity by radioenzymatic assay at hours 0, 5, and 24 for dogs with residual serum available is shown in Table 4Our results support RAAS activation as a mechanism of diuretic braking in this FCRI model using healthy dogs, despite finding that background PO administration of RAAS suppressive medications did not mitigate diuretic braking. The increase in plasma angiotensin II concentrations at the end of the furosemide infusion and the increase in hourly plasma aldosterone concentrations throughout the infusion support the involvement of these neurohormones in curtailing diuresis even with continued IV diuretic administration and previously demonstrated furosemide presence in the urine.Although true baseline ACE activity (before PO treatments) was not available to allow calculation of the percentage of ACE suppression in each treatment group, the treatments for which benazepril was administered before FCRI (treatments B and C) showed only 10% of the ACE activity after 3 days of medication compared to treatment A (no benazepril). The low ACE activity with benazepril administration in our study is consistent with other studies that found significant ACE suppression with an ACE inhibitor.http://www.iris-kidney.com/guidelines/grading.html). Higher doses, longer infusions, or even high‐dose PO furosemide may predispose to similar or more marked changes in sCr, particularly in older patients. Although the increases in sCr in the dogs of our study likely were based in hemodynamics (decreased glomerular filtration as a result of diuretic‐induced volume depletion),http://www.iris-kidney.com/guidelines/grading.html). Repeated subclinical episodes of acute kidney injury could contribute to cardiovascular‐renal disorders in dogs, which can contribute to poor outcome or death.Ours is the first study in dogs evaluating biochemical variables 24 hours after cessation of IV furosemide administration. Some furosemide‐induced biochemical changes were not evident until the day after the infusion, and some biochemical changes that occurred during the infusion had not returned to baseline at 24 hours. Concurrent PO administration of RAAS inhibitors did not significantly affect these changes, which were found for all treatments . This observation indicates that the major driver for these findings likely was the loop diuretic, and not RAAS‐inhibiting medications. Because no differences were noted among treatments, the biochemical results of our study support the safety of RAAS‐suppressive medications administered before FCRI in healthy dogs, but the implications for CHF management in dogs have not been elucidated. Although changes were relatively mild in this model, the discovery of serum biochemical abnormalities indicating volume depletion and electrolyte derangements appearing the day after the FCRI raise concern about the potential for similar changes in clinical patients. Dogs hospitalized for treatment of acute CHF may have pre‐existing renal dysfunction or may receive higher doses or longer infusions of furosemide to manage their condition and therefore may be at higher risk for azotemia and electrolyte abnormalities. The average sCr increase in these dogs at hour 24 approached the International Renal Interest Society definition of acute kidney injury (The model used in our study of normal dogs has limited applicability to dogs with naturally occurring CHF, but nevertheless provides mechanistic information to drive future clinical studies. The neurohormonal RAAS and sympathetic nervous system profiles of dogs with CHF are activated at baseline, which was not the case for these healthy dogs. Accordingly, the different fluid balance and neurohormonal state between healthy dogs and dogs with CHF could influence the response to RAAS suppression and diuresis with FCRI. Equilibrium analysis of the entire RAAS cascade would have been helpful in understanding the source of increased angiotensin II at hour 5, but we were unfamiliar with this methodology during study planning. Moreover, equilibrium analysis utilizing liquid chromatography and mass spectroscopy may have provided more accurate aldosterone concentrations in light of specificity concerns for radioimmunoassay testing. Additional time points after FCRI discontinuation would have provided more information regarding RAAS involvement in the unexpected findings of prolonged biochemical changes and hydration recovery. Despite these limitations, the results of our study provide insight into the response of the RAAS, renal function, and electrolyte balance during and after intense RAAS stimulation caused by FCRI, with and without RAAS‐suppressive treatment with relatively low‐dose ACE inhibition and mineralocorticoid antagonism.5Oral administration of RAAS inhibitors did not prevent the diuretic braking that occurred with FCRI in this healthy dog model, but the observed curtailment in urine production appeared to be at least partially mediated by some components of the RAAS. The biochemical changes that occurred in response to FCRI are attributable only to the furosemide and therefore administration of RAAS inhibitors before FCRI appears safe in healthy dogs. Results of other chronic studies support the use of RAAS inhibitors, especially mineralocorticoid receptor antagonists, to protect against the maladaptive effects of aldosterone when the RAAS is activated; our results support the safety of this approach in the setting of acute CHF treatment. The delayed biochemical effects secondary to IV furosemide observed in our study warrant evaluation in dogs with naturally occurring CHF to determine if similar effects occur with IV diuresis in a clinical setting.Dr Adin is a consultant for Ceva Santé Animale and Boehringer Ingelheim. She has received speaking honoraria and travel reimbursements from Ceva Santé Animale. Dr Atkins has received funding from and has consulted for Ceva Santé Animale, Boehringer Ingelheim, and Vetoquinol. Dr Wallace and Ms Klein do not have conflicts of interest to report.Authors declare no off‐label use of antimicrobials.Approved by North Carolina State University IACUC, protocol #17‐075‐O.Authors declare human ethics approval was not needed for this study.


Obesity has several effects on the mechanics of the rib cage that may impair the exercise performance of obese individuals and therefore impact the assessment of surgical risk. This study aimed to establish a reference value for the 6-minute walk distance (6 MWD) in obese Brazilian men in the preoperative period of bariatric surgery that considers the effect of lung function.  This was a cross-sectional study in which 104 obese men underwent the six-minute walk test (6 MWT) before bariatric surgery. They also underwent the spirometry test and respiratory muscle strength measurement before the 6 MWT. r = −0.388, p=0.0005), weight , height , body mass index (BMI) , forced vital capacity (FVC) , peak expiratory flow , and maximal inspiratory pressure . In the stepwise forward regression analysis, BMI, FVC, and age were the only variables that independently predicted the 6 MWD and explained 40% of its variability. The reference equation proposed for obese Brazilian men is 6 MWD (m) = 570.5 − (3.984 × BMIkg/m2) + (1.093 × FVC%predicted) − (0.836 × ageyrs).  The 6 MWD was correlated with age ( In this sample of obese Brazilian men, lung function contributed to poor performance in the 6 MWT. In these individuals, BMI, FVC, and age were the variables that composed the reference equation for the 6 MWD. Thus, in several clinical settings, such as in the evaluation before bariatric surgery, pulmonary function data are important to determine the reference value for the 6 MWD. Obesity hinders walking and is therefore an important component of functional limitation, which can be caused by a sedentary lifestyle and the numerous adverse effects of excess weight , 2. ObesThe performance of an obese individual in the 6 MWT should be evaluated considering the various repercussions that obesity causes in the body , resultiAlthough spirometry test results have been used in preoperative assessments of obese people, their relationship with the functional capacity of obese individuals is uncertain , 10. Con2 [A cross-sectional study was conducted between March 2020 and February 2021 with 104 obese men (of 123 eligible) in the preoperative period before bariatric surgery at the University Center Fundação Assis Gurgacz, Cascavel, PR, Brazil. All individuals older than 18 years with a body mass index (BMI) ≥ 30 kg/m2  who atteThe study protocol was approved by the research ethics committee of our institution under CAAE no. 11613219.0.0000.5219, and all participants read and signed the informed consent form.The spirometry test was performed using a MicroLoop device  according to the recommendations of the American Thoracic Society/European Respiratory Society . Respira2), and Borg's perceived exertion scale were measured before and after the 6 MWT. The examiner also used words of encouragement every minute. At the end of the sixth minute, the stop point and the 6 MWD were recorded. Thirty minutes after the first 6 MWT, the participants performed a second 6 MWT to avoid possible learning and adaptation effects, as observed in conditions affecting the respiratory system [The 6 MWT was performed according to previously described recommendations using a 30 m runway demarcated with cones at both ends . Blood py system . Only thp < 0.05.Parametric methods were applied because the variables showed a Gaussian distribution according to the Shapiro-Wilk test, and a graphical analysis of histograms was performed. For the test-retest reliability analysis, a two-way random-effects intraclass correlation coefficient (ICC) was calculated using a confidence interval of 95% (95% CI). The correlations of the 6 MWD with anthropometric, demographic, and pulmonary function data were analysed by Pearson's coefficient. Stepwise forward linear regression analysis was applied to identify independent variables that explained the 6 MWD and generate the reference equation for 6 MWD. The results are expressed as the mean ± standard deviation (SD) or frequency (percentage), and statistical significance was accepted at Calibration was verified using a limits of agreement (LoA) plot with the Bland–Altman method and a calibration plot . Data analysis was performed using SAS 6.11 software .α = 0.05 (two-tailed) and a complete-case analysis showed that the observed significant effects were detected with a power in the range of 73% to 99%.Post hoc power analysis using GPower 3.1.1 software based on an a priori type I error n = 10); reporting prior cardiopulmonary disease (n = 5); history of lower limb surgery (n = 2); and difficulties in performing acceptable manoeuvres in the spirometry test (n = 2). No patients refused to perform the 6 MWT.Among the 123 obese subjects who were eligible for the study, 19 were excluded for the following reasons: individuals with a smoking load ≥10 pack-years  had a history of smoking (smoking load < 10 pack-years). The mean BMI was 48.1 ± 8.4 kg/m1)/FVC < 70%. According to measurements of respiratory muscle strength, the maximal inspiratory pressure (MIP) and maximal expiratory pressure were <80% of the predicted values in 23 (22.1%) and 16 (15.4%) participants, respectively. Anthropometric, demographic, pulmonary function, and 6 MWT data are shown in According to the spirometry test, 38 (36.5%) and 30 (28.8%) participants had a forced vital capacity (FVC) and peak expiratory flow (PEF) < 80% of the predicted values, respectively, and no patient showed a forced expiratory volume in one second .When comparing the means of the two 6 MWT trials performed by the participants, no significant difference was noted, although the distance covered in the second 6 MWT was longer , FVC , PEF , and MIP . Significant negative correlations were observed between the 6 MWD and the following variables: age , weight , and BMI   .m) = 570.5 − (3.984 × BMIkg/m2) + (1.093 × FVC%predicted) − (0.836 × ageyrs); R2 = 0.40 (standard error of the regression coefficient = 47.3 m).Finally, we evaluated whether the anthropometric, demographic, and pulmonary function variables could predict performance during the 6 MWT using nine predictor variables. In the stepwise forward regression analysis, BMI, FVC, and age were the only variables that independently predicted 6 MWD, and these variables explained 40% of its variability . The refRegarding the calibration of the regression model, most differences were within the LoA, with a random distribution over the mean values in the range of the highest concentration (350–500 m). However, a slight bias was observed for high and low values of the distance covered . AdditioThe main finding of the present study was that, in a population of obese men with a high BMI in the preoperative period before surgery, obesity, BMI, FVC, and age were independent factors predicting the 6 MWD. In addition, the 6 MWT was highly reproducible in these individuals, although a second test showed greater distance walked, possibly due to a learning effect. In this study, the reference equation for the 6 MWD in obese Brazilian men obtained shortly before bariatric surgery was reported for the first time. These results are important in risk assessment and fitness assessment before bariatric operations.6 MWT outcomes are associated with daily physical activity and can also be considered a direct measure of impaired quality of life . The 6 MThe 6 MWT evaluates the global and integrated responses of all systems involved in exercise, including the respiratory system. Obesity causes numerous repercussions for the respiratory system, including reduced lung compliance and increased surface tension of the alveoli due to a lower functional residual capacity and airway closure, with the formation of atelectatic areas , 26. ExcInterestingly, the pattern of body fat distribution as determined by anthropometric measurements or complementary tests such as dual-energy X-ray absorptiometry seems to be relevant to the changes in lung function observed in obese people. The android pattern with fat accumulation in the abdominal region seems to have a more negative impact on lung function, as it causes greater impairment of ventilatory mechanics and increases resistance to diaphragmatic contraction. This phenomenon explains the greater FVC impairment in obese men than in women of the same BMI since in women, the predominant pattern of fat accumulation is gynoid, where fat accumulation occurs in the gluteofemoral region , 30.Reliability, repeatability, and reproducibility are three of the fundamental properties of a test and are influenced by many factors . The rep1 were the only significant independent predictors of 6 MWD, which explained 33.9% of the variance in their model. In their study, most individuals (63%) were overweight or obese, although the entire group had median FEV1 and FVC values within the normal ranges. Unlike our model, their 6 MWD explanatory model did not include BMI, possibly because few subjects had a BMI >30 kg/m2. In obese Brazilian women, it was recently shown that BMI, FVC, age, and maximal inspiratory pressure explained 41% of the variability in 6 MWD [In our reference equation, BMI, FVC, and age explained 40% of the 6 MWD variability. Few studies have evaluated the impact of lung function on the 6 MWD in obese and nonobese individuals. Camarri et al.  evaluatein 6 MWD . Since w2 [1< 70% of the predicted value, although lung function is a major contributor to performance during the 6 MWT in obese people [The reference equations for the 6 MWD in healthy adults (men and women) by Enright and Sherrill  are amone people , 36.Our study has limitations. First, the present study evaluated only obese men, precluding extrapolation of our results to obese men of other age groups, such as adolescents and elderly men. Second, we used only spirometry tests and measurements of respiratory muscle strength. More complex pulmonary function analysis tools, such as whole-body plethysmography, the forced oscillation technique, and carbon monoxide diffusion capacity, may better predict the impact of lung function on the 6 MWD. Our reference value of the 6 MWD in obese men may serve as a useful reference for future clinical and research studies. Future studies should also evaluate the impact of other organ systems that are known to be compromised in obesity, such as the cardiovascular and musculoskeletal systems.In this sample of obese Brazilian men, lung function contributed to poor performance in the 6 MWT. In these individuals, BMI, FVC, and age were the variables that composed the reference equation for the 6 MWD. Thus, in the preoperative evaluation before weight loss surgery, pulmonary function data are important to determine the reference value for the 6 MWD in obese Brazilian men.


Yoga may reduce body weight in individuals with overweight or obesity, but whether this occurs through decreased energy intake (EI) or increased energy expenditure (EE)/physical activity (PA) is unclear.A systematic search of PubMed, Web of Science, Embase, and PsychINFO was conducted from inception until April 26, 2021. Eligible studies included randomized controlled trials or single‐arm pre‐post studies with any type and duration of yoga intervention in adults with overweight or obesity. Studies with measures related to EI , EE, or PA were eligible. The review initially identified 1,373 articles.Of the 10 included studies, one used indirect calorimeter measures of resting EE, while nine used self‐reported measures of EI and PA. Of the seven studies measuring parameters related to EI, only one found greater decreases in EI relative to the control group, although three other investigations reported trends toward improved dietary intake. Of the eight studies measuring PA, two reported greater increases in resting EE or PA in the yoga group relative to the control group. Two reported significant within‐group increases in PA from pre‐post intervention, and four studies reported a trend for increased PA with no p‐values reported.Limited evidence suggests yoga may reduce EI and increase PA in adults with overweight or obesity. Additional studies that investigate the effects of yoga interventions on energy balance parameters using objective techniques are warranted. Understanding how yoga affects specific aspects of energy balance in people with overweight or obesity can inform novel and potentially more effective strategies for sustained weight loss. However, to date there has not been a systematic evaluation of the literature examining the extent to which yoga interventions lead to reduced EI, increased EE, or a combination of both in people with excess body weight. As such, the objective of this systematic review was to evaluate the existing literature examining the effect of yoga interventions on EI and PA among adults with overweight or obesity.22.1This review was planned, conducted, and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) recommendations.2.2Records uncovered during the literature search were assessed to determine if they met the following inclusion criteria2.2.1Adults (age ≥ 18) with overweight or obesity, defined by body composition or any anthropometric measurement.2.2.2asanas, pranayama, or meditation/mindfulness.Yoga interventions of any duration or frequency and consisting of any combination of 2.2.3Sedentary, dietary, or exercise control conditions. Single‐arm interventions were also included.2.2.4All outcome measures related to EI, PA, or EE were eligible for inclusion. Specific eligible outcomes include dietary intake, hunger, satiety, appetite, dietary inhibition, dietary restraint, eating behavior, PA measured by any method, activity EE, resting metabolic rate, non‐exercise PA, or sedentary behavior. Notably, this article intentionally refers to the term “dietary intake” when describing specific dietary components or general food consumption and “EI” when referring to measured EI specifically  and with regard to energy balance more broadly throughout this manuscript.Eligible publications included RCTs, quasi‐experimental studies, and single arm pre‐post studies. Cross‐sectional observational studies, conference papers, abstracts, dissertations, reviews, and non‐English publications were excluded. Three authors  independently sorted titles and abstracts. Potentially eligible records underwent full‐text review by A.C. and S.A.P. Two authors (A.C. and S.A.P.) also assessed the bibliographies of full‐text articles to identify other potentially eligible studies. Disagreements were resolved by review and consensus by A.C. and S.A.P.2.3Two authors (A.C. and S.A.P) independently extracted relevant data. Authors were not blinded to information regarding authorship, institutions of origin, or journal of publication. Information extracted included: First author last name, publication year, methods , participants , intervention, comparator/control groups, outcomes related to EI or EE, other outcomes, results , conclusions by the authors, and references to other potentially relevant publications. This review reported PA with or without the yoga sessions, according to what parameter was included within each eligible article. Where possible, the team extracted the means and corresponding standard deviation, standard error, or 95% confidence intervals (CI) for each pre‐post‐ outcome variable.2.4The National Institutes of Health’s study quality assessment tools were used to determine risk of bias.33.1The literature search uncovered 1373 potentially eligible articles. After removing 482 duplicates and screening titles, abstracts, and full texts, 10 articles met inclusion criteria, Figure Table asanas, with three studies focusing exclusively on yoga postures.asana practices included in the interventions varied from being low intensity—described as restorative, therapeutic, or a means of stretchingasana practice.pranayama controlled breathing techniques,Yoga interventions varied widely in the styles and specific body‐, breath‐, and mind‐based practices included, as well on the level of detail provided to interpret the style of yoga or practices included in the intervention. All studies included body‐based yoga postures, or 3.2not change their diet during the intervention.Seven studies measured some dimension of dietary intake before and after a yoga intervention.n = 260) received a personalized diet plan by a registered dietitian. In this study 130 individuals were randomized to also receive a yoga intervention 5 days/week in‐person and at‐home. Both groups had decreased total EI and % of EI from fat, increased % EI from protein and carbohydrates, and increased fiber (g/day). The yoga group had greater reductions in total EI. In a recent RCT by Jakicic et al.n = 26) among women with overweight or obesity by Ruby et al.n = 29) received a 12‐weeks yoga intervention  and a lacto‐vegetarian diet plan consisting of 1900 to 2000 kcal/day. EI appeared to decrease with concomitant decreases in protein and increases in carbohydrate and fat intake (in g/day) in the yoga group.p‐values were presented. In a single‐arm, 5‐days residential yoga study by Braun et al.n = 39). A general “nutrition score” improved directly following the brief intervention and after 12 weeks; however, the 12‐weeks change was not significant after Bonferroni correction.Of the five studies in which participants were given dietary advice, four reported changes in dietary intake and one found no change. In a large 12‐weeks RCT reported by Yadav et al.n = 137). There were no significant differences self‐reported EI, macronutrients, sugar, or cholesterol attained by 3‐days food records between groups. Notably, self‐reported EI assessed by the Block Food Frequency Questionnaire (FFQ) appeared to increase in both yoga and wait‐list control groups in the pilot study by Cohen et al.p‐values were presented and the differences in EI change between groups was not significant.The RCTs by Siu et al.3.3not to change habitual non‐yoga PA levels in two studies.Seven studies measured PA and one study measured resting metabolic rate before and after a yoga intervention. In six of these studies,p‐values were reported as this was a pilot study. In the study by Jakicic et al.p‐values were reported. There was also no change in minutes spent in moderate‐to‐vigorous PA in either group as measured by accelerometer. In the single‐arm study by Braun et al.p < 0.001). However, this increase included yoga completed in a residential setting and was not maintained at the 3‐months follow‐up.In the six studies in which participants were not given instructions to keep habitual levels of PA the same, all six reported initial increases in PA or resting metabolic rate following the intervention, although not all were statistically significant. In the large RCT by Yadav et al.not to raise PA, Siu et al.p‐values were not reported for within‐group changes. In the pilot study by Cohen et al.p‐values were reported for within‐group changes.Two RCTs explicitly instructed participants not to change habitual levels of PA. Despite instructions 3.4n = 3, 30%) or moderate risk of bias ; 1 (10%) had a high risk of bias  EI generally produces greater weight loss than exercise‐only interventionsThere was also wide variability across studies included in this review in the different styles and specific yoga practices that comprised the yoga interventions that make comparing data across studies difficult. To date, there is no consensus on what styles of yoga should be included in interventions, which impedes rigorous scientific study of yoga and its potential health benefits. In the context of obesity or related chronic disease treatment, the intensity of the yoga practices, and the purpose of their inclusion  should be much more clearly considered, measured, and detailed in future research. Importantly, studies conducted in India and China placed a much greater emphasis on describing the specific yoga practices included in each intervention, and used practices more consistent with authentic yoga methods described in classic Sanskrit texts.There are several unique aspects of yoga that suggest yoga positively influences factors upstream could enhance EI‐related sustained behavior changes and support maintenance of weight loss. Improvements in subjective ratings of appetite occur following 10 minutes of slowed breathing (6 bpm vs. 9 bpm).p‐values for these changes,p‐values not included).not associated with compensation. This may be related to yoga eliciting a relatively lower EE compared to other, higher intensity exercise modalities.PA is also important for weight loss and especially weight loss maintenance, as individuals who successfully maintain weight loss regularly engage in high levels of PA.This systematic review highlights a paucity of research that has characterized the effects of yoga interventions on PA in adults with overweight or obesity. However, other related research in populations that are not exclusively overweight or obese suggests that yoga practice is expected to improve PA levels though mechanisms that are not related to the assumed increased EE from yoga sessions. Bernstein et al.This review is the first to describe changes in EI and PA in response to yoga in people with obesity and uncovered several limitations that should be considered when interpreting the literature. The widespread reliance on self‐reported measures of dietary intake and PA is the most important limitation of the current evidence. These measures have poor accuracy in identifying actual EI and PA,In conclusion, there is currently only limited evidence that yoga improves EI and PA parameters in adults with overweight or obesity. However, this is at least partially due to the small number of studies that have measured these outcomes in this population in response to a yoga intervention , the wide variability in study designs, and lack of rigorous, objective measurements of these variables. The rationale for examining the effects of yoga on EI and PA during weight loss is compelling and suggests that yoga holds promise as a strategy to support weight loss and weight loss maintenance in people with obesity. Whether yoga may elicit changes in energy balance as a stand‐alone intervention or as part of a comprehensive lifestyle modification interventions is unknown. Rigorously designed research with objective measures of energy balance is warranted to measure the effects of yoga on EI and PA to understand how yoga leads to weight loss in this population in order to reduce the burden of obesity.The authors declare no conflicts of interest.Ann E. Caldwell, Sarah A. Purcell, and Victoria A. Catenacci conceptualized the review. Ann E. Caldwell and Sarah A. Purcell developed and implemented the search strategy. BAG and HS conducted the title and abstract screening. Ann E. Caldwell and Sarah A. Purcell reviewed the selected abstracts and full texts, extracted and analyzed the data, reviewed the risk of bias, and wrote the original draft of the manuscript. All authors provided critical feedback on the manuscript.Supporting Information S1Click here for additional data file.


Several studies have been found on the cytogenetic effects of dibutyl phthalate (DBP) on different organisms but no documented evidence has been found on the cytotoxic and genotoxic effects of dibutyl phthalate (DBP) on bovine cultured lymphocytes. MTT assay was performed on different series of DBP concentrations . A concentration-dependent decrease in cell viability was observed by the DBP. The LD50, LD50/2, and 2∗LD50 were found to be 50 μM, 30 μM, and 80 μM on bovine lymphocytes, respectively. Then, these concentrations of DBP were utilized to perform comet, micronucleus assays, and oxidative stress. A concentration-dependent increase in DNA damage, oxidative stress, and micronuclei formation was observed in lymphocytes by the DBP as compared to the control group. Highest genotoxic effects were observed at a concentration of 2∗LD50. Similarly, total oxidative stress was found higher, and antioxidative stress was lower in concentration-dependent manner by the DBP. The current study revealed a significant cytotoxic, genotoxic, and oxidative stress of DBP on cultured bovine lymphocytes.Recently, there have been numerous reports showing that phthalates have negative human health impacts and may cause several diseases such as asthma, breast cancer, obesity, type II diabetes, and male infertility. Animals are also exposed to phthalate In vivo and epidemiological studies associated structural impairment of the lung with phthalate exposure [Phthalates are the diesters of orthophthalic acid  and commonly known as diester compounds. These lipid-containing organic compounds are produced annually in huge volumes. One million ten of phthalate is produced and used in European countries as itis used in the formation of a wide variety of materials . In vivoexposure . DBP is exposure . DBP is exposure .Phthalates are also used in the manufacturing of plastic containers, water bottles, medicine jars, infant formula milk, and nutritional supplements. Phthalate exposures from indoor sources are vapours produced from materials used for the construction of buildings, domestic fragrances, and home stuff. Different kinds of medical devices for therapeutic maintenance such as tubes for circulatory fluids, blood bags, and dialysis tubing materials are also made up of plastic which makes them softer with different kinds of PVC and organic compounds. Skin absorption can occur through direct contact with cosmetics and clothing products containing phthalate . In silaAll chemicals were of Sigma-Aldrich, Munich, Germany. Main chemicals were dibutyl phthalate (CAS No. 84074-2), low melting point agarose (A4018), normal melting point agarose (A9539), Triton X-100, basic fuchsin, ethidium bromide (EtBr), sodium hydroxide, hydrochloric acid, RMPI-1640 media, HEPES, methyltetrazolium (MTT), EDTA, etc. All chemicals were of analytical grade.2, 2% O2, and 95% N2 at 37°C in incubator.A total of 6 healthy cattle were selected, and their blood samples were taken in sterilized EDTA syringes and shifted to clean falcon tubes. Lymphocytes were isolated using histopaque-1077 technique . Isolated lymphocytes were observed under the microscope for analyzing viable cells. Cells were cultured by using the RMPI-1640 culture medium having 10% FBS, 1% penicillin-streptomycin, amphotericin-B, and 1% HEPES. Cells were cultured using this growth medium in culture flasks and incubated with the appropriate conditions of 5% CO5 cells were cultured in each well for 24 h. After 24 h, viable cells were exposed to the different concentrations of DBP from 10 μM, 20 μM, 30 μM, 50 μM, 70 μM, and 100 μM in triplicate for 24 h. 0.1% dimethyl sulfoxide (DMSO) was taken as solvent control, whereas distilled water was taken as a negative control. After 24 h, MTT reagent (10 μL) was added in all wells including controls and again incubated for 3 h. After 3 h of incubation, the medium was removed, and 100 μL DMSO was added, gently shaken, and kept at room temperature for 30 min. Absorbance was measured at 630 nm, and average values were calculated for all concentrations and controls [The MTT assay was performed for the cytotoxic assessment after 24 h incubation in 96 well plates. Total of 1 × 10controls .TOS and TAS levels were determine by Rel Assay Diagnostic kit RL0024 and RL0017 . Procedure was adopted as per manufacturer protocol. Sample oxidants oxidized the ferrous ion-o-dianisidine complex into ferric ion. Colored complex was formed by ferric ion in the presence of acidic medium. Spectrophotometer was used to determine the total amount of oxidant molecules present in the sample. TOS was analyzed spectrophotometrically at 530 nm while TAS was analyzed spectrophotometrically at 660 nm. TOS and TAS were calculated as reported by Ali and his colleagues .8) in 25 cm2 flasks and incubated for 24. Briefly, the treated cells (10 μL) were mixed with low melting agarose (1.5%) and loaded in 1% normal melting agarose precoated slides. Slides were kept on ice for 5 min followed by lysis in lysis buffer  at 4°C. Lysis was performed for an hour, and then, slides were kept in electrophoresis buffer solution  for 20 min. Electrophoresis was further carried out at 4°C for 20 min at 25 mV and 300 Amp. Slides were stained with EtBr (20 μg/mL) to observe under fluorescence microscope at 40x. Level of DNA damage was observed for each concentration and control group and expressed as an arbitrary unit (AU). A total of 50 nuclei were randomly counted from each slide per each concentration and scored from 0 to 4 depending on the level of DNA damage . Three slides were made from each experiment [Comet assay was performed as described earlier by Liman et al. . Brieflyperiment , 17.8) were treated with these concentrations in 25 cm2 flasks and incubated for 24 h. Treated cells were centrifuged with 1% KCL. Then, pellets were centrifuged with fixative 1 (50 mL fixative II and 50 mL 0.09%NaCl) and fixative 11 , respectively. Samples were coated on prechilled wet slides, air-dried, and stained with 10% Giemsa stain. Then, slides were washed with distilled water and observed under a compound microscope for the identification of micronuclei and binuclei. The total of 500 cells was counted from each slide. All experiments were repeated in triplicate.Micronucleus test was carried out as described by the Cigerci and his colleagues . Micronup < 0.05 was kept to represent significance difference.One-way ANOVA was applied to analyze the results of an alkaline comet and MN test using SPSS version 15.0 for the Windows software. Duncan test was applied in the SPSS package to compare different concentration of groups. Statistical significant value μM after 24 h of exposure to DBP concentration. The LD50, LD50/2, and 2∗LD50 were found as 50 μM, 30 μM, and 80 μM on bovine lymphocytes, respectively.The effect of DBP concentrations on cell viability using MTT assay is shown in p < 0.05). Similarly, a significant effect of induction of micronuclei and binuclei has been observed at all the three concentrations of DBP (Total DNA damage score induced by the DBP is represented in s of DBP  comparedTOS was increased in concentration-dependent manner whereas a decrease in TAS values was observed with increase in concentrations of DBP. TOS values were significantly higher in different treatment groups of DBP as compared to TAS values .Low molecular weight phthalates like DBP can interact with animals directly through inhalation or indirectly through the contact with plastic utensils . SeveralSimilarly, genotoxic effects were also observed by the DBP on bovine lymphocytes. Previously, different types of phthalates have already shown genotoxicity –26 in diμM and 35 μM [Higher DNA damage and formation of micronuclei in the current study were suggestive of adverse genotoxic effects due to DBP on bovine lymphocytes. Current results are in agreement with the findings of Kleinsasser and his colleagues who demonnd 35 μM . DBP alsnd 35 μM .Genotoxic effects exerted by phthalates and their metabolites were observed at chromosome and DNA level . These gGenotoxic effects of phthalates have also been observed at the higher concentrations by other studies –38. GenoDifferent studies have been observed by the DBP induced toxic effects on different model organisms. However, no documented evidence has been found on the genotoxic effects of DBP on bovine peripheral lymphocytes. Findings of the current study provide an insight into potential cytotoxic, genotoxic, and oxidative stress effects of DBP on bovine lymphocytes. It can be predicted that accidental exposure of animals to DBP is hazardous at their cellular and genetic level. In future, this study would provide a potential information regarding the cautious use of DBP in products of animal use.