Urinary markers/metabolites of exposure to chemical carcinogens - New possibilities in preventive oncology.

Centuries have passed without tobacco medical evaluation, and similar catastrophes have happened from the Roman Empire to now. We are not aware when, how and how much our body is exposed to chemical carcinogens every day. As a result of such exposure, millions of people fall ill with malignant diseases every year. The objectives of this work are: 1) Determination of the main urinary markers of exposure to the most dangerous chemical carcinogens; 2) Globally raising awareness about necessity of scientific testing chemicals before widespread human use; 3) Introducing the public about ubiquity of: As, Ni, Cr(VI), Cd, Be, and necessity of maximal reducing people's exposure to them. There are well known causal relations between the most dangerous chemical carcinogens and different types of human malignant diseases. Population based studies may determine persons with high concentrations of the urinary markers/metabolites of the most dangerous chemical carcinogens. Then, such selected persons should be removed from such circumstances and/or regularly checked. Better solution is to find out the source(s) of incriminated chemical cancerogens and eliminate or mitigate their emission. These are a kind of (pre)screening (primordial prevention) for persons with high risk of developing malignant diseases causally related to the most dangerous chemical carcinogens.

Bladder cancer screening: The new selection and prediction model.

The objective of this study was to offer new approach for selection of persons with asymptomatic bladder cancer (BC) and highly risky persons for the BC occurrence. Also, it is a part of the BC screening protocol (study is ongoing). Study populations were 100 newly diagnosed (diagnosis maximum 1-year old) males with BC and 100 matched (by sex and age ±5 years) controls (not oncology patients from the same hospital). A hospital based, matched case-control study was done. Statistical analysis comprised of four steps: t-test, univariate logistic regression, multivariate logistic regression, and scoring. The fifth step comprised of two changes, deleting one variable and addition of another variable. Six variables were statistically significant: Caucasian men over 45 years age, tobacco smoking over 40 pack-years, occupational and/or environmental exposure to the proved BC carcinogens over 20 years, macrohematuria, difficulty urinating, BC in relatives up to fourth degree of kinships, and they were used for an easy and fast selection of the individuals with high risk for BC occurrence and BC asymptomatic patients (optimal selection at the population level). The final results showed highly significant probability (p < 0.001), with area under ROC curve of 0.913, negative predictive values of 89.7% (95% CI 10.3-100%), and a specificity of 78%. Positive predictive value was 80.5% (95% CI 19.5-100%) and a sensitivity of 91%. It is possible to recruit asymptomatic BC patients (primary prevention) by using this model, as well as persons with high risk for BC occurrence (primordial prevention). This study is the first part of the BC screening protocol and the second part of the BC screening protocol study is ongoing (urine analysis).

Analysis of COVID-19 outbreak origin in China in 2019 using differentiation method for unusual epidemiological events.

OBJECTIVES: Origin of outbreaks could be natural, accidental, deliberate, and caused by a new or re-emerging bioagent. The aim of this study was the retrospective analysis of whether the COVID-19 outbreak was natural, accidental, deliberate one, or caused by a new or re-emerging bioagent. METHODS: Analysis was performed according to the Radosavljevic-Belojevic method for outbreak scoring and differentiation. Data for the application of this method were obtained by literature review in the Medline database for the period from 2000 to 2020. RESULTS: The analysis of the unusual COVID-19 outbreak shows that the present official assumption of its natural origin is questionable and pointed out to a probability that the pathogen could have also been accidentally introduced in the human population. CONCLUSION: There are no conclusive pieces of evidence about the reservoir of the pathogen or the source of infection. These parameters are essential for the final clarification of the outbreak origin. This study suggests that the COVID-19 outbreak is a consequence of an accidental release of a new COVID-19 virus, probably during the technical accident and/or negligent violation of hygienic norms in the laboratory facility. Further epidemiological, microbiological, and forensic analyses are needed to clarify the COVID-19 outbreak.

Modeling Healthcare Quality via Compact Representations of Electronic Health Records.

Increased availability of Electronic Health Record (EHR) data provides unique opportunities for improving the quality of health services. In this study, we couple EHRs with the advanced machine learning tools to predict three important parameters of healthcare quality. More specifically, we describe how to learn low-dimensional vector representations of patient conditions and clinical procedures in an unsupervised manner, and generate feature vectors of hospitalized patients useful for predicting their length of stay, total incurred charges, and mortality rates. In order to learn vector representations, we propose to employ state-of-the-art language models specifically designed for modeling co-occurrence of diseases and applied clinical procedures. The proposed model is trained on a large-scale EHR database comprising more than 35 million hospitalizations in California over a period of nine years. We compared the proposed approach to several alternatives and evaluated their effectiveness by measuring accuracy of regression and classification models used for three predictive tasks considered in this study. Our model outperformed the baseline models on all tasks, indicating a strong potential of the proposed approach for advancing quality of the healthcare system.

Large-Scale Discovery of Disease-Disease and Disease-Gene Associations.

Data-driven phenotype analyses on Electronic Health Record (EHR) data have recently drawn benefits across many areas of clinical practice, uncovering new links in the medical sciences that can potentially affect the well-being of millions of patients. In this paper, EHR data is used to discover novel relationships between diseases by studying their comorbidities (co-occurrences in patients). A novel embedding model is designed to extract knowledge from disease comorbidities by learning from a large-scale EHR database comprising more than 35 million inpatient cases spanning nearly a decade, revealing significant improvements on disease phenotyping over current computational approaches. In addition, the use of the proposed methodology is extended to discover novel disease-gene associations by including valuable domain knowledge from genome-wide association studies. To evaluate our approach, its effectiveness is compared against a held-out set where, again, it revealed very compelling results. For selected diseases, we further identify candidate gene lists for which disease-gene associations were not studied previously. Thus, our approach provides biomedical researchers with new tools to filter genes of interest, thus, reducing costly lab studies.

Analysis of Escherichia Coli O104:H4 Outbreak in Germany in 2011 Using Differentiation Method for Unusual Epidemiological Events.

AIM: The aim of the study was to further clarify the origin of Escherichia coli O104:H4 outbreak in Germany in 2011 (German Ec) as the likelihood of a deliberate act has not been excluded in previous analyses. METHODS: We use an original and the most detailed scoring method so far, with 33 parameters pertaining to the source of infection/reservoir or possible perpetrator, pathogen or biological agent, transmission mechanism/factors or means/media of delivery, and population at risk or target. RESULTS: Total scores for a deliberate or accidental epidemic indicate that the outbreak was more probably caused unintentionally, presumably due to technical accidents or hygienic shortcomings in the food chain. CONCLUSIONS: The validity of the present assessment is limited by the lack of data on the reservoir of the pathogen, the source of infection, and the mode of food contamination. Conclusive evidences on these parameters are essential for the final clarification of the outbreak origin.

Escherichia coli O104:H4 outbreak in Germany--clarification of the origin of the epidemic.

BACKGROUND: In 2011, Germany was hit by one of its largest outbreaks of acute gastroenteritis and haemolytic uraemic syndrome caused by a new emerging enterohaemorrhagic Escherichia coli O104:H4 strain. The German Haemolytic Uraemic Syndrome/Enterohaemorrhagic E. coli (GHUSEC) outbreak had unusual microbiological, infectiological and epidemiological features and its origin is still only partially solved. The aim of this article is to contribute to the clarification of the origin of the epidemic. METHODS: To retrospectively assess whether the GHUSEC outbreak was natural, accidental or a deliberate one, we analysed it according to three published scoring and differentiation models. Data for application of these models were obtained by literature review in the database Medline for the period 2011-13. RESULTS: The analysis of the unusual GHUSEC outbreak shows that the present official assumption of its natural origin is questionable and pointed out to a probability that the pathogen could have also been introduced accidentally or intentionally in the food chain. CONCLUSION: The possibility of an accidental or deliberate epidemic should not be discarded. Further epidemiological, microbiological and forensic analyses are needed to clarify the GHUSEC outbreak.

Shortcomings in bladder cancer etiology research and a model for its prevention.

AIMS AND BACKGROUND: Bladder cancer (BC) is the most expensive cancer to treat. Its incidence and mortality have not decreased in the last three decades. Numerous uncertainties are still surrounding the etiology of BC. There is a need for a low-cost screening test for BC that would be applicable for early detection in asymptomatic persons, a test that would preferably be noninvasive and have satisfactory sensitivity and specificity. METHODS AND STUDY DESIGN: The first part of this paper addresses critical issues in the research into BC etiology, which we classified as entrances, toxicity and metabolism, amounts, and duration of exposure to carcinogens in the bladder. In the second part, based on the proven risk factors for BC, we present a simple scoring system as part of a new BC screening method. RESULTS: The heterogeneous results of studies on BC etiology are largely due to a lack of research into the compounds (and their mutual interactions) present in the urinary bladder, carcinogens absorbed through the skin and/or inhaled, and the daily dynamics of exposure to exogenous risk factors. We have calculated a score for BC screening which is an integral component of a new, four-level system of BC prevention. CONCLUSIONS: Interactions of carcinogens and their daily dynamics deserve more attention in further clarifying BC etiology. New attempts in BC screening should be focused on urine content analyses (carcinogens, antioxidants, vitamins, minerals) and not only on hematuria and currently used biomarkers. We propose a score for BC pre-evaluation and recruitment for screening and a new model of BC prevention.

A data-driven acute inflammation therapy.

Acute inflammation is a severe medical condition defined as an inflammatory response of the body to an infection. Its rapid progression requires quick and accurate decisions from clinicians. Inadequate and delayed decisions makes acute inflammation the 10th leading cause of death overall in United States with the estimated cost of treatment about $17 billion annually. However, despite the need, there are limited number of methods that could assist clinicians to determine optimal therapies for acute inflammation. We developed a data-driven method for suggesting optimal therapy by using machine learning model that is learned on historical patients' behaviors. To reduce both the risk of failure and the expense for clinical trials, our method is evaluated on a virtual patients generated by a mathematical model that emulates inflammatory response. In conducted experiments, acute inflammation was handled with two complimentary pro- and anti-inflammatory medications which adequate timing and doses are crucial for the successful outcome. Our experiments show that the dosage regimen assigned with our data-driven method significantly improves the percentage of healthy patients when compared to results by other methods used in clinical practice and found in literature. Our method saved 88% of patients that would otherwise die within a week, while the best method found in literature saved only 73% of patients. At the same time, our method used lower doses of medications than alternatives. In addition, our method achieved better results than alternatives when only incomplete or noisy measurements were available over time as well as it was less affected by therapy delay. The presented results provide strong evidence that models from the artificial intelligence community have a potential for development of personalized treatment strategies for acute inflammation.

Obesity and fat distribution as predictors of aortoiliac peripheral arterial disease in middle-aged men.

BACKGROUND: Peripheral arterial disease (PAD) in the aortoiliac segment is found in nearly a half of patients with PAD. The aim of this study was to estimate the influence of obesity and fat distribution on the occurrence of aortoiliac PAD in middle-aged men. METHODS: This case-control study included 204 middle-aged men (mean 58±7 years; range 45-70 years): 102 patients with aortoiliac PAD and 102 healthy controls without PAD. Aortoiliac PAD was diagnosed by ankle-brachial index (ABI) and angiography. Body mass index (BMI) was categorized as: normal weight, overweight, and obese. Percents of body fat were grouped according to quartile distribution. The relationship between anthropometrics and aortoiliac PAD was estimated by multivariate logistic regression. RESULTS: Patients with aortoiliac PAD had higher body mass index, waist circumference, waist-hip ratio and percent of body fat. A strong correlation between all anthropometric parameters and ABI index and mean angiographic score was shown among patients with PAD. Multivariate regression, adjusted for blood pressure and cholesterol level, identified being overweight, body fat over 26.5% and WHR over 1.02 as predictors for aortoiliac PAD. Body fat over 26.5% and WHR over 1.02 remained significant after further adjustment for blood pressure, cholesterol and body mass index. CONCLUSION: This study has identified the quantity of fat tissue (body fat over 26.5%) and its visceral distribution (waist-hip ratio over 1.02) as predictors of aortoiliac PAD in middle-aged men. Body mass index, a crude indicator of obesity, should be combined with these parameters when assessing the risk for aortoiliac PAD.

A new model of bioterrorism risk assessment.

There has been an abundance of different bioterrorist attack scenarios and consequently an unclear biodefense strategy so far. We present a framework for bioterrorism risk assessment that we believe would be useful for policymakers and understandable without needing to be an expert in this field. We retrieved the Medline database via PubMed (from January 1987 to January 2009) and cross-referenced and reviewed the terms biological weapons, biological attacks, bioterror, bio(defense), bio(strategy) and epidemiologic models, and risk assessment. Additionally, we conducted an internet search with the same terms and strategy. We divided bioterrorist attacks into 3 categories: strategical (large-scale), operational (middle-scale), and tactical (small-scale). A bioterrorist attack is presented as a 4-component chain model, including perpetrators, agents, means of delivery, and targets. For any of these 4 components, we propose quantitative and qualitative risk assessment parameters. Here we present a simple scoring system within our model applied to the 2001 U.S. anthrax attacks.

Epidemics of panic during a bioterrorist attack--a mathematical model.

A bioterrorist attacks usually cause epidemics of panic in a targeted population. We have presented epidemiologic aspect of this phenomenon as a three-component model--host, information on an attack and social network. We have proposed a mathematical model of panic and counter-measures as the function of time in a population exposed to a bioterrorist attack. The model comprises ordinary differential equations and graphically presented combinations of the equations parameters. Clinically, we have presented a model through a sequence of psychic conditions and disorders initiated by an act of bioterrorism. This model might be helpful for an attacked community to timely and properly apply counter-measures and to minimize human mental suffering during a bioterrorist attack.

Arsenic and bladder cancer: observations and suggestions.

Arsenic from drinking water is a well-known risk factor for bladder cancer. The purpose of this paper is to systematize some important yet often overlooked facts considering the relationship between arsenic exposure and the occurrence of bladder cancer. Since the exposure to inorganic arsenic from food, inhaled air, and skin absorption as well as arsenic methylation ability are not fully investigated, our assumption is that the exposure of arsenic only from drinking water is underestimated and its role as a risk factor is highly overestimated. This paper proposes some qualitative and quantitative parameters of arsenic as a risk factor for bladder cancer. The recommended qualitative parameters of arsenic intake are first, pathways of exposure, and second, toxicity and metabolism. The suggested quantitative parameters of arsenic intake include amounts of arsenic absorbed in the body, duration of arsenic exposure, and duration of arsenic presence in the urinary bladder. This approach can be implemented in a systematic classification and explanation of various risk factors and their mutual interactions for other types of cancer or diseases in general.

[An outbreak of trichinellosis in a military unit].

BACKGROUND/AIM: In December 2001, an outbreak of trichinellosis spreaded in a military unit. The aim of this paper was to show possibilities and consequences of trichinellosis infestations in military units during peace time, as well as to improve knowledge and awareness of medical corps personnel, commanders and soldiers about this disease. METHODS: A descriptive and analytical epidemiological models were used to find out a source of outbreak and to identify the ways of its transmission. RESULTS: This outbreak was caused by the contaminated raw smoked sausage which had not undergone health inspection and brought from civilians to a military unit. Thirty-eight persons were exposed, twenty-one affected and hospitalized. The most frequent symptoms reported were fever (76.2%), myalgia (76.2%), palpebral edema (42.8%), face edema (19.0%) and diarrhea (14.3%). Test for indirect immunofluorescence was positive in 14.3% and ELISA test was positive in 28.6% of the patients. Eosinophilia was present in 85.7% of the affected. IgE values were increased in 28.6% and CPK values were increased in 61.9% of the diseased. All of the 17 exposed undiseased had negative laboratory analyses for trichinellosis. CONCLUSION: We propose intensifying health education and continuing the implementation of duly supervised and evaluated self-check programs. A well-tuned, fast-reacting epidemiological monitoring system has to be obligatory.

Risk factors for bladder cancer.

AIMS AND BACKGROUND: To summarize risk factors for bladder cancer, emphasizing the role of recently established associations and to present some ongoing debates on the issue. METHODS: A systematic literature search was performed using MEDLINE database on bladder cancer risk factors between January 1985 and June 2006 and by detailed examination of the references of original articles, reviews and monographs retrieved. RESULTS: Cigarette smoking is recognized as the main cause of bladder cancer and accounts for about 50% of cases in developed countries. A strong link exists between the amount and duration of cigarette smoking. A high risk of bladder carcinoma has been observed in workers exposed to some aromatic amines. Based on these and other occupational risks, it has been estimated that 5-10% of bladder carcinomas in industrialized countries were due to exposures of occupational origin. Infectious agents have a major influence on bladder cancer risks in the areas of the world where Schistosoma haematobium infestation is endemic. Other potential risk factors for bladder cancer are other urinary tract infections and drinking tap water with chlorination by-products or arsenic. Exposure to certain drugs, like cyclophosphamide used in chemotherapy and heavy consumption of phenacetin-containing analgesics, has been shown to cause bladder cancer in humans. Total fluid intake and high consumption of fruits and vegetables are probably associated with a small decrease in risk. CONCLUSIONS: Avoidance of tobacco smoking and incriminated occupational exposures, habitual intake of fresh fruits and vegetables, and prevention and control of urinary tract infections should be recommended for bladder cancer prevention. Further studies are required to assess the role of genetic polymorphisms and their modifying effect of lifestyle risk factors for bladder cancer occurrence and to evaluate the benefit of bladder cancer screening, particularly in those at high risk.

Non-occupational risk factors for bladder cancer: a case-control study.

AIMS: The aim of this study was to determine non-occupational risk factors for bladder cancer in Serbia. METHODS AND DESIGN: A hospital-based, case-control study included 130 newly diagnosed bladder cancer patients and the same number of individually matched controls with respect to sex, age (+/- 2 years) and type of residence (rural or urban), from the Clinical Center of Serbia in Belgrade and from the Clinical Center in Kragujevac in central Serbia. The study took place from June 1997 to March 1999. RESULTS: According to multivariate logistic regression analysis, there was an association between: frequency of daily urination (OR = 0.18; 95% CI = 0.08-0.39); consumption of liver (OR = 13.81; 95% CI = 2.49-76.69), canned meat (OR = 8.38; 95% CI = 1.74-40.36), fruit juices (OR = 0.08; 95% CI = 0.01-0.56); the highest tertile of pork (OR = 4.55; 95% CI = 1.30-15.93), cabbage (OR = 0.25; 95% CI = 0.06-1.01) and vinegar (OR = 4.41; 95% CI = 1.18-16.50) intake and risk for bladder cancer. CONCLUSIONS: Consumption of liver, canned meat, pork (h vs l tertile) and vinegar (m vs l tertile) was indicated as a risk factor for bladder cancer, whereas frequent daily urination, consumption of fruit juices and cabbage (h vs l tertile) were indicated as protective factors.

[Alcohol consumption, arterial blood pressure and general mortality rate--twenty-years follow-up study]. / Unos alkohola, arterijski pritisak i opsti mortalitet--dvadesetogodisnja prospektivna studija.

BACKGROUND: Alcohol consumption has both adverse and beneficial effects on health and survival. The aim of this prospective study was to examine the association between alcohol consumption and arterial hypertension as well as general mortality rate. METHODS: The study included 286 participants, middle-aged men and women examined in 1974, and again in 1994 during twenty years of follow-up (mean age at the beginning of the study 43.61 +/- 7.09 years). Alcohol consumption was assessed by the specific questionnaire. Consumption levels were grouped into three categories: rare drinkers (consuming less than 6 drinks a week), moderate drinkers, who consume 1-2 alcohol drinks a day and heavy drinkers (consumers of 3 or more drinks a day). RESULTS: In both phases of the follow-up the lowest values of systolic and diastolic pressure were recorded in the group with moderate alcohol consumption, and the highest values in the group with excessive consumption. The observed differences were statistically significant. The general mortality rates were the highest among participants reporting excessive alcohol consumption (relative risk 3.2; 95% confidence interval 1.84-5.62), and among the abstainers (relative risk 1.8; 95% confidence interval 0.99-3.36), compared to the moderate consumption group. CONCLUSION: Analysis of the obtained results suggested the protective effect of moderate alcohol consumption on cardiovascular system.