Applications of ChatGPT and Large Language Models in Medicine and Health Care: Benefits and Pitfalls.

Background: The use of large language models like ChatGPT is becoming increasingly popular in health care settings. These artificial intelligence models are trained on vast amounts of data and can be used for various tasks, such as language translation, summarization, and answering questions. Observations: Large language models have the potential to revolutionize the industry by assisting medical professionals with administrative tasks, improving diagnostic accuracy, and engaging patients. However, pitfalls exist, such as its inability to distinguish between real and fake information and the need to comply with privacy, security, and transparency principles. Conclusions: Careful consideration is needed to ensure the responsible and ethical use of large language models in medicine and health care. The development of [artificial intelligence] is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone. It will change the way people work, learn, travel, get health care, and communicate with each other. Bill Gates1.

AACC Guidance Document on Cervical Cancer Detection: Screening, Surveillance, and Diagnosis.

BACKGROUND: Persistent genital infection with high-risk human papilloma virus (hrHPV) causes the vast majority of cases of cervical cancer. Early screening, ongoing surveillance, and accurate diagnosis are crucial for the elimination of cervical cancer. New screening guidelines for testing in asymptomatic healthy populations and management guidelines for managing abnormal results have been published by professional organizations. CONTENT: This guidance document addresses key questions related to cervical cancer screening and management including currently available cervical cancer screening tests and the testing strategies for cervical cancer screening. This guidance document introduces the most recently updated screening guidelines regarding age to start screening, age to stop screening, and frequencies of routine screening as well as risk-based management guidelines for screening and surveillance. This guidance document also summarizes the methodologies for the diagnosis of cervical cancer. Additionally, we propose a report template for human papilloma virus (HPV) and cervical cancer detection to facilitate interpretation of results and clinical decision-making. SUMMARY: Currently available cervical cancer screening tests include hrHPV testing and cervical cytology screening. The screening strategies can be primary HPV screening, co-testing with HPV testing and cervical cytology, and cervical cytology alone. The new American Society for Colposcopy and Cervical Pathology guidelines recommend variable frequencies of screening and surveillance based on risk. To implement these guidelines, an ideal laboratory report should include the indication for the test (screening, surveillance, or diagnostic workup of symptomatic patients); type of test (primary HPV screening, co-testing, or cytology alone); clinical history of the patient; and prior as well as current testing results.

Establishing a Hospital Artificial Intelligence Committee to Improve Patient Care.

Background: The use of artificial intelligence (AI) in health care is increasing and has shown utility in many medical specialties, especially pathology, radiology, and oncology. Observations: Many barriers exist to successfully implement AI programs in the clinical setting. To address these barriers, a formal governing body, the hospital AI Committee, was created at James A. Haley Veterans' Hospital in Tampa, Florida. The AI committee reviews and assesses AI products based on their success at protecting human autonomy; promoting human well-being and safety and the public interest; ensuring transparency, explainability, and intelligibility; fostering responsibility and accountability; ensuring inclusiveness and equity; and promoting AI that is responsive and sustainable. Conclusions: Through the hospital AI Committee, we may overcome many obstacles to successfully implementing AI applications in the clinical setting.

Molecular Testing of Atypical Thyroid Nodules with Corresponding Surgical Correlation: Five-Year Retrospective Review in Veterans Population.

Objective We report the results of a retrospective five-year study within a veteran population aimed at correlating abnormal thyroid fine-needle aspiration (FNA) diagnosis with associated molecular testing to the histology of the surgical resection. Methods A retrospective analysis of abnormal thyroid FNAs with associated molecular testing and surgical outcome was conducted from January 1, 2015 to December 31, 2020. Aspirates were classified using the Bethesda system for reporting thyroid cytopathology, including atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS), follicular neoplasm/suspicious for follicular neoplasm (FN/SFN), suspicious for malignancy (SM), and malignant. Pertinent data, including patient demographics, imaging, and ancillary testing were reviewed. A thyroid cancer mutation panel assessing the most common mutations and rearrangements associated with neoplasia was utilized. The results of molecular testing were directly compared and correlated with final cytological and histological diagnosis. Results A total of 1850 thyroid aspirates were performed, 200 of which were given an abnormal cytologic diagnosis. Thirty-six samples were submitted for molecular testing and subsequent surgical follow-up. Four were called malignant on cytology. 32 were placed in an indeterminate category (89%). Within indeterminate cases: 53% exhibited positive molecular mutations (n=17), 34% no mutation detected (n=11), and 13% insufficient quantity for testing (n=4). Upon surgical resection in the mutation-positive group: 18% had no malignancy (n=3), and the remaining 82% were positive for malignancy (n=14). Mutations in the histologically malignant group included: 57% BRAF (n=8), 21% NRAS (n=3), 7% HRAS (n=1), 7% KRAS (n=1), and 7% PAX8/PPAR gamma (n=1). In indeterminate cases with no mutation detected, 10 cases were found to be benign, and one case of malignancy was diagnosed. The probability of indeterminate diagnosis in combination with no mutation yielded a 91% chance of benign entity and 9% chance of malignancy. We demonstrated 93% sensitivity and 91% negative predictive value (NPV) for the risk of malignancy in indeterminate cytology specimens with ancillary molecular testing. There was 77% specificity and 82% positive predictive value (PPV) for our data set. Conclusions In indeterminate samples, the detection of a mutation was highly predictive of malignancy and a strong indicating factor for surgery with a high sensitivity and NPV. Molecular testing refined or established the diagnosis in 89% of the cases. Our results indicate that molecular testing of thyroid nodules enhances the accuracy of FNA cytology and the subsequent surgical outcome.

Artificial Intelligence: Review of Current and Future Applications in Medicine.

BACKGROUND: The role of artificial intelligence (AI) in health care is expanding rapidly. Currently, there are at least 29 US Food and Drug Administration-approved AI health care devices that apply to numerous medical specialties and many more are in development. OBSERVATIONS: With increasing expectations for all health care sectors to deliver timely, fiscally-responsible, high-quality health care, AI has potential utility in numerous areas, such as image analysis, improved workflow and efficiency, public health, and epidemiology, to aid in processing large volumes of patient and medical data. In this review, we describe basic terminology, principles, and general AI applications relating to health care. We then discuss current and future applications for a variety of medical specialties. Finally, we discuss the future potential of AI along with the potential risks and limitations of current AI technology. CONCLUSIONS: AI can improve diagnostic accuracy, increase patient safety, assist with patient triage, monitor disease progression, and assist with treatment decisions.

Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis.

BACKGROUND: Coronavirus disease-19 (COVID-19), caused by a novel member of the coronavirus family, is a respiratory disease that rapidly reached pandemic proportions with high morbidity and mortality. In only a few months, it has had a dramatic impact on society and world economies. COVID-19 has presented numerous challenges to all aspects of health care, including reliable methods for diagnosis, treatment, and prevention. Initial efforts to contain the spread of the virus were hampered by the time required to develop reliable diagnostic methods. Artificial intelligence (AI) is a rapidly growing field of computer science with many applications for health care. Machine learning is a subset of AI that uses deep learning with neural network algorithms. It can recognize patterns and achieve complex computational tasks often far quicker and with increased precision than can humans. METHODS: In this article, we explore the potential for the simple and widely available chest X-ray (CXR) to be used with AI to diagnose COVID-19 reliably. Microsoft CustomVision is an automated image classification and object detection system that is a part of Microsoft Azure Cognitive Services. We utilized publicly available CXR images for patients with COVID-19 pneumonia, pneumonia from other etiologies, and normal CXRs as a dataset to train Microsoft CustomVision. RESULTS: Our trained model overall demonstrated 92.9% sensitivity (recall) and positive predictive value (precision), with results for each label showing sensitivity and positive predictive value at 94.8% and 98.9% for COVID-19 pneumonia, 89% and 91.8% for non-COVID-19 pneumonia, 95% and 88.8% for normal lung. We then validated the program using CXRs of patients from our institution with confirmed COVID-19 diagnoses along with non-COVID-19 pneumonia and normal CXRs. Our model performed with 100% sensitivity, 95% specificity, 97% accuracy, 91% positive predictive value, and 100% negative predictive value. CONCLUSIONS: We have used a readily available, commercial platform to demonstrate the potential of AI to assist in the successful diagnosis of COVID-19 pneumonia on CXR images. The findings have implications for screening and triage, initial diagnosis, monitoring disease progression, and identifying patients at increased risk of morbidity and mortality. Based on the data, a website was created to demonstrate how such technologies could be shared and distributed to others to combat entities such as COVID-19 moving forward.

Comparing Artificial Intelligence Platforms for Histopathologic Cancer Diagnosis.

Two machine learning platforms were successfully used to provide diagnostic guidance in the differentiation between common cancer conditions in veteran populations.

Circulating long noncoding RNA GAS5 levels are correlated to prevalence of type 2 diabetes mellitus.

BACKGROUND: Diabetes mellitus (DM), a metabolic disease, is characterized by impaired fasting glucose levels. Type 2 DM is adult onset diabetes. Long non-coding RNAs (lncRNAs) regulate gene expression and multiple studies have linked lncRNAs to human diseases. METHODS: Serum samples obtained from 96 participating veterans at JAH VA were deposited in the Research Biospecimen Repository. We used a two-stage strategy to identify an lncRNA whose levels correlated with T2DM. Initially we screened five serum samples from diabetic and non-diabetic individuals using lncRNA arrays. Next, GAS5 lncRNA levels were analyzed in 96 serum samples using quantitative PCR. Receiver operating characteristic (ROC) analysis was performed to determine the optimal cutoff GAS5 for diagnosis of DM. RESULTS: Our results demonstrate that decreased GAS5 levels in serum were associated with diabetes in a cohort of US military veterans. The ROC analysis revealed an optimal cutoff GAS5 value of less than or equal to 10. qPCR results indicated that individuals with absolute GAS5 < 10 ng/µl have almost twelve times higher odds of having diabetes (Exact Odds Ratio [OR] = 11.79 (95% CI: 3.97, 37.26), p < 0.001). Analysis indicated area under curve (AUC) of ROC of 0.81 with 85.1% sensitivity and 67.3% specificity in distinguishing non-diabetic from diabetic subjects. The positive predictive value is 71.4%. CONCLUSION: lncRNA GAS5 levels are correlated to prevalence of T2DM. GENERAL SIGNIFICANCE: Assessment of GAS5 in serum along with other parameters offers greater accuracy in identifying individuals at-risk for diabetes.

Warfarin pharmacogenomics: recommendations with available patented clinical technologies.

Warfarin pharmacogenomic testing has become a prime example of the utility of personalized molecular testing in the modern clinical laboratory. Warfarin is a commonly used drug for the prevention and treatment of thromboembolic complications in a variety of clinical situations. However, a number of factors lead to a high interindividual variability in dose requirements. Among the primary factors in this variability are genetic polymorphisms in general patient populations, which can account for 35-50% of varying dose requirements among patients. In this review, we discuss the implications of polymorphisms in the cytochrome P-450 enzyme 2C9 (CYP2C9) and Vitamin K Epoxide Reductase Enzyme Complex subunit 1 (VKORC1) as they relate to therapeutic warfarin dosing. We discuss the clinical utility of pharmacogenomics testing as related to warfarin dosing, and propose a clinical model for the implementation of the pharmacogenomic test results. Finally, we provide a brief overview of the currently available commercial testing platforms with discussion of the complexities of utilizing patented methodologies in bringing genetic testing such as this to the clinical laboratory.

PKCλ haploinsufficiency prevents diabetes by a mechanism involving alterations in hepatic enzymes.

Tissue-specific knockout (KO) of atypical protein kinase C (aPKC), PKC-λ, yields contrasting phenotypes, depending on the tissue. Thus, whereas muscle KO of PKC-λ impairs glucose transport and causes glucose intolerance, insulin resistance, and liver-dependent lipid abnormalities, liver KO and adipocyte KO of PKC-λ increase insulin sensitivity through salutary alterations in hepatic enzymes. Also note that, although total-body (TB) homozygous KO of PKC-λ is embryonic lethal, TB heterozygous (Het) KO (TBHetλKO) is well-tolerated. However, beneath their seemingly normal growth, appetite, and overall appearance, we found in TBHetλKO mice that insulin receptor phosphorylation and signaling through insulin receptor substrates to phosphatidylinositol 3-kinase, Akt and residual aPKC were markedly diminished in liver, muscle, and adipose tissues, and glucose transport was impaired in muscle and adipose tissues. Furthermore, despite these global impairments in insulin signaling, other than mild hyperinsulinemia, glucose tolerance, serum lipids, and glucose disposal and hepatic glucose output in hyperinsulinemic clamp studies were normal. Moreover, TBHetλKO mice were protected from developing glucose intolerance during high-fat feeding. This metabolic protection (in the face of impaired insulin signaling) in HetλKO mice seemed to reflect a deficiency of PKC-λ in liver with resultant 1) increases in FoxO1 phosphorylation and decreases in expression of hepatic gluconeogenic enzymes and 2) diminished expression of hepatic lipogenic enzymes and proinflammatory cytokines. In keeping with this postulate, adenoviral-mediated supplementation of hepatic PKC-λ induced a diabetic state in HetλKO mice. Our findings underscore the importance of hepatic PKC-λ in provoking abnormalities in glucose and lipid metabolism.

Hepatitis C genotype analysis: results in a large veteran population with review of the implications for clinical practice.

CONTEXT: Hepatitis C virus (HCV) infects up to 1.8% of the US general population, although the rate is significantly higher in military veterans at 5.4-20%. Early detection and accurate diagnosis are critical as chronic HCV infection can lead to liver cirrhosis and hepatocellular carcinoma. Genotype analysis has both therapeutic and prognostic importance in patients with HCV infections. OBJECTIVE: We compare two versions of a commonly utilized platform for genotype analysis in HCV infections and review the implications of the results for clinical practice. DESIGN: A retrospective review of 9401 genotype results from 2001-2010 were analyzed. All results were obtained from the James A. Haley VA Medical Center, a large referral veterans' healthcare facility. RESULTS: Genotype 1 was identified in 80.1% of samples, genotype 2 in 11.1%, genotype 3 in 7.4%, and genotype 4 in 1.2%. Genotypes 5 and 6 were rarely present in our patient population. Improvements in diagnostic methodologies over the study period resulted in shifts in genotype subtyping. Specifically, upgrading from the Versant HCV genotype assay (LIPA) (Siemens, Tarrytown, NY) to the newer version 2.0 assay resulted in an increase in identification of genotype 1a by 18.5%. CONCLUSIONS: Improved technologies lead to accurate genotype identification and subtyping, both of which have increasingly important prognostic and therapeutic implications. The clinical importance of these results in patients with HCV infections is reviewed.

Correction of metabolic abnormalities in a rodent model of obesity, metabolic syndrome, and type 2 diabetes mellitus by inhibitors of hepatic protein kinase C-ι.

Excessive activity of hepatic atypical protein kinase (aPKC) is proposed to play a critical role in mediating lipid and carbohydrate abnormalities in obesity, the metabolic syndrome, and type 2 diabetes mellitus. In previous studies of rodent models of obesity and type 2 diabetes mellitus, adenoviral-mediated expression of kinase-inactive aPKC rapidly reversed or markedly improved most if not all metabolic abnormalities. Here, we examined effects of 2 newly developed small-molecule PKC-ι/λ inhibitors. We used the mouse model of heterozygous muscle-specific knockout of PKC-λ, in which partial deficiency of muscle PKC-λ impairs glucose transport in muscle and thereby causes glucose intolerance and hyperinsulinemia, which, via hepatic aPKC activation, leads to abdominal obesity, hepatosteatosis, hypertriglyceridemia, and hypercholesterolemia. One inhibitor, 1H-imidazole-4-carboxamide, 5-amino-1-[2,3-dihydroxy-4-[(phosphonooxy)methyl]cyclopentyl-[1R-(1a,2b,3b,4a)], binds to the substrate-binding site of PKC-λ/ι, but not other PKCs. The other inhibitor, aurothiomalate, binds to cysteine residues in the PB1-binding domains of aPKC-λ/ι/ζ and inhibits scaffolding. Treatment with either inhibitor for 7 days inhibited aPKC, but not Akt, in liver and concomitantly improved insulin signaling to Akt and aPKC in muscle and adipocytes. Moreover, both inhibitors diminished excessive expression of hepatic, aPKC-dependent lipogenic, proinflammatory, and gluconeogenic factors; and this was accompanied by reversal or marked improvements in hyperglycemia, hyperinsulinemia, abdominal obesity, hepatosteatosis, hypertriglyceridemia, and hypercholesterolemia. Our findings highlight the pathogenetic importance of insulin signaling to hepatic PKC-ι in obesity, the metabolic syndrome, and type 2 diabetes mellitus and suggest that 1H-imidazole-4-carboxamide, 5-amino-1-[2,3-dihydroxy-4-[(phosphonooxy)methyl]cyclopentyl-[1R-(1a,2b,3b,4a)] and aurothiomalate or similar agents that selectively inhibit hepatic aPKC may be useful treatments.

The critical role of atypical protein kinase C in activating hepatic SREBP-1c and NFkappaB in obesity.

Obesity is frequently associated with systemic insulin resistance, glucose intolerance, and hyperlipidemia. Impaired insulin action in muscle and paradoxical diet/insulin-dependent overproduction of hepatic lipids are important components of obesity, but their pathogenesis and inter-relationships between muscle and liver are uncertain. We studied two murine obesity models, moderate high-fat-feeding and heterozygous muscle-specific PKC-lambda knockout, in both of which insulin activation of atypical protein kinase C (aPKC) is impaired in muscle, but conserved in liver. In both models, activation of hepatic sterol receptor element binding protein-1c (SREBP-1c) and NFkappaB (nuclear factor-kappa B), major regulators of hepatic lipid synthesis and systemic insulin resistance, was chronically increased in the fed state. In support of a critical mediatory role of aPKC, in both models, inhibition of hepatic aPKC by adenovirally mediated expression of kinase-inactive aPKC markedly diminished diet/insulin-dependent activation of hepatic SREBP-1c and NFkappaB, and concomitantly improved hepatosteatosis, hypertriglyceridemia, hyperinsulinemia, and hyperglycemia. Moreover, in high-fat-fed mice, impaired insulin signaling to IRS-1-dependent phosphatidylinositol 3-kinase, PKB/Akt and aPKC in muscle and hyperinsulinemia were largely reversed. In obesity, conserved hepatic aPKC-dependent activation of SREBP-1c and NFkappaB contributes importantly to the development of hepatic lipogenesis, hyperlipidemia, and systemic insulin resistance. Accordingly, hepatic aPKC is a potential target for treating obesity-associated abnormalities.

Screening for hemoglobinopathies during routine hemoglobin A1c testing using the Tosoh G7 Glycohemoglobin Analyzer.

Approximately 5.1% of the US population has diabetes mellitus, and hemoglobin (Hb) A1c levels are routinely measured to monitor long-term glycemic control in these patients. Many laboratories use ion exchange chromatography for such measurements, and the presence of hemoglobin variants and hemoglobinopathies often results in abnormal peaks on the chromatogram. The goal of this study was to evaluate the potential that detection of these abnormal peaks provides as a screening tool for Hb variants and hemoglobinopathies. We examined 366 specimens with abnormal peaks observed during routine Hb A1c measurements using the G7 Glycohemoglobin Analyzer (Tosoh Bioscience, Inc.). Hb variants and hemoglobinopathies were characterized by alkaline and acid electrophoresis, solubility testing for Hb S, and clinical parameters. In 252 cases, sickle cell trait was identified with a mean retention time (RT) of 1.44 (SD +/-0.02) min. In 82 cases, Hb C trait was identified with a mean RT of 1.66 +/-0.03 min. RTs for other Hb abnormalities, including sickle cell disease, homozygous Hb C disease, C Harlem trait, alpha-chain Hb variants, Hb D trait, Hb G trait, Hb J trait, Hb Raleigh, and Hb Lepore were also determined. Our results demonstrate that routine Hb A1c testing provides a potential screening tool for the detection of common hemoglobin variants and hemoglobinopathies. The previously unreported RTs for the G7 Glycohemoglobin Analyzer are provided, which can facilitate further testing in previously undiagnosed patients and confirm the cause of abnormal peaks in patients with known hemoglobin abnormalities.

Kupffer cell-derived Fas ligand plays a role in liver injury and hepatocyte death.

Liver injury is an important prognostic indicator during acute pancreatitis. The aim of this study was to determine the role of Fas ligand (FasL) in hepatocyte injury. Liver parenchymal enzymes were measured in cocultures of hepatocytes and Kupffer cells treated with elastase. FasL and FasL mRNA were measured in elastase-treated Kupffer cells. Hepatocytes were treated with FasL and their viability was assessed by monotetrazolium (MTT), apoptosis by flow cytometry, as well as caspase-3 and p38-mitogen-activated protein kinase (MAPK) by immunoblotting. Elastase increased aspartate aminotransferase and lactate dehydrogenase in cocultures of hepatocyte and Kupffer cells (P<0.040). Elastase increased FasL production from Kupffer cells (P=0.02) and upregulated FasL mRNA (FasL/beta-2 microglobulin (BMG): 0.23+/-0.03 vs. 0.11+/-0.003; P=0.04). FasL increased alanine aminotransferase and lactate dehydrogenase (P<0.03) and reduced hepatocyte viability by 45% (P=0.01). FasL increased the number of dually labeled cells with AnnexinV/7AAD (P=0.03) while upregulating cleavage of caspase-3 and the phosphorylation of p38-MAPK. FasL antibody attenuated the FasL-related increase in dually labeled cells (P=0.02), the cleavage of caspase-3, and phosphorylation of p38-MAPK. Pancreatic elastase upregulates FasL within Kupffer cells. FasL induces hepatocyte injury and death and upregulates p38-MAPK and caspase-3 within hepatocytes. The ability to manipulate interactions between Kupffer cells and hepatocytes may have important therapeutic implications.

Liver injury during acute pancreatitis: the role of pancreatitis-associated ascitic fluid (PAAF), p38-MAPK, and caspase-3 in inducing hepatocyte apoptosis.

We have demonstrated that pancreatitis-associated ascitic fluid contributes to hepatocyte injury during acute pancreatitis; a phenomenon independent of ascites' enzymatic content and Kupffer cell-derived cytokines. Our aim is to characterize the mechanisms of pancreatitis-associated ascitic fluid induced hepatocyte death. NIH mice were injected intraperitoneally with pathogen-free pancreatitis-associated ascitic fluid. Twenty-four hours later, serum AST, ALT, LDH, and hepatocyte apoptosis (TUNEL) were measured. Human hepatocytes (CCL-13) were treated with pancreatitis-associated ascitic fluid +/-SB203580 or caspase-3 inhibitor-II. Mitochondrial membrane integrity was determined by DiOC6 staining. Apoptosis was measured by TUNEL staining and flow cytometry after dual labeling with Annexin-V/7-AAD. Data are mean +/- SEM of triplicates. Pancreatitis-associated ascitic fluid increased serum AST, ALT, LDH, and apoptotic cells in the mouse liver (all P < 0.03 vs. sham). In CCL-13 cells, pancreatitis-associated ascitic fluid induced a time and dose-dependent increase in apoptosis, in addition to p38-MAPK phosphorylation (P = 0.02 vs. control), caspase-3 cleavage (P < 0.03 vs. control) and decreased DiOC6 mitochondrial staining (P < 0.01 vs. control). Both caspase-3 inhibitor-II and SB203580 decreased apoptosis, but the former had no effect on DiOC6 staining. Pancreatitis-associated ascitic fluid induces liver injury and hepatocyte apoptosis by activating p38-MAPK and caspase-3 dependent pro-apoptotic pathways.

Comparison of safety, delivery, and efficacy of two oncolytic herpes viruses (G207 and NV1020) for peritoneal cancer.

G207 and NV1020 are two replication-competent, multimutant oncolytic herpes simplex viruses evaluated in the current studies for their anticancer effects in the treatment of gastric cancer. Deletion of both gamma(1)34.5 genes and inactivation of ICP6 (ribonucleotide reductase) allows G207 to selectively replicate within tumor cells. NV1020 is another attenuated recombinant herpes virus with deletions of the HSV joint region, with deletion of only one copy of the gamma(1)34.5 gene, and with the ICP6 gene intact. In vitro, both G207 and NV1020 effectively infected, replicated, and killed human gastric cancer cells, with NV1020 being more effective at lower concentrations of virus. In a murine xenograft model of peritoneally disseminated gastric cancer, both NV1020 and G207 reduced tumor burden when given intraperitoneally (i.p.) at higher doses. When viral doses were lowered or when advanced tumor was treated, i.p. NV1020 was superior to i.p. G207. In vitro viral replication and cytotoxicity predicted the in vivo antitumor response. Intravenous delivery of either G207 or NV1020 failed to reduce tumor burden, demonstrating the importance of regional therapy as treatment for compartmentalized malignancy. Both agents were safe for use in animals, and immunohistochemistry performed on mouse tissue revealed selective viral targeting of tumor. Oncolytic therapy using genetically engineered HSVs represents a promising strategy for peritoneal malignancies.

Pancreatic elastase induces liver injury by activating cytokine production within Kupffer cells via nuclear factor-Kappa B.

Liver injury is a manifestation of the systemic inflammatory response during acute pancreatitis. We have demonstrated that elastase induces macrophage tumor necrosis factor (TNF) production in distant organs, thus mimicking pancreatitis-associated organ injury. The aim of this study was to determine the mechanism by which elastase induces hepatic cytokine production. Rat livers (n = 40) were perfused with elastase +/- gadolinium (Gd) to inhibit Kupffer cells. Liver parenchymal enzymes and TNF were measured in the effluent. In vitro, rat hepatocytes or Kupffer cells were treated with elastase (1 U/ml) +/- Gd (0.5 mg/ml) or pyrrolidine dithiocarbamate (PDTC; 0.5 mg/ml). TNF protein, TNF messenger RNA, and NF-kappa B activation were determined. In vivo, Gd blunted the elastase-induced TNF production and decreased AST, ALT, LDH, and nonviable cells (propidium iodide) (P < or= 0.03 vs. elastase). In vitro, elastase induced TNF production from Kupffer cells (P < 0.001 vs. control) but not from hepatocytes. Gd or PDTC significantly attenuated the elastase-induced TNF production (P < 0.001). Elastase-induced overexpression of TNF messengerRNA and activation of NF-kappa B was attenuated by Gd. Pancreatic elastase induces a pattern of liver injury similar to that seen during acute pancreatitis by activating cytokine production and gene expression within Kupffer cells via NF-kappa B. Gd exhibits a protective effect against elastase-induced liver injury by inhibiting activation of NF-kappa B.