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FRAUD AUDITING AND FORENSIC ACCOUNTING With the responsibility of detecting and preventing fraud falling heavily on the accounting profession, every accountant needs to recognize fraud and learn the tools and strategies necessary to catch it in time. Providing valuable information to those responsible for dealing with prevention and discovery of financial deception, Fraud Auditing and Forensic Accounting, Fourth Edition helps accountants develop an investigative eye toward both internal and external fraud and provides tips for coping with fraud when it is found to have occurred. Completely updated and revised, the new edition presents: Brand-new chapters devoted to fraud response as well as to the physiological aspects of the fraudster A closer look at how forensic accountants get their job done More about Computer-Assisted Audit Tools (CAATs) and digital forensics Technological aspects of fraud auditing and forensic accounting Extended discussion on fraud schemes Case studies demonstrating industry-tested methods for dealing with fraud, all drawn from a wide variety of actual incidents Inside this book, you will find step-by-step keys to fraud investigation and the most current methods for dealing with financial fraud within your organization. Written by recognized experts in the field of white-collar crime, this Fourth Edition provides you, whether you are a beginning forensic accountant or an experienced investigator, with industry-tested methods for detecting, investigating, and preventing financial schemes.

Over the past 30 years, both information systems and accounting have undergone radical changes. Standards and regulations have also become frustratingly complex. But there's a powerful remedy for today's auditing headaches: continuous auditing and reporting (CAR). The authors explain what CAR is and how to determine if it will help your company. They also profile several affordable CAR products. Low‐ cost “instant auditing” is now possible! © 2005 Wiley Periodicals, Inc.

BackgroundClassical randomisation of clinical trial patients creates a source of genetic variance that may be contributing to the high failure rate seen in neurodegenerative disease trials. Our objective was to quantify genetic difference between randomised trial arms and determine how imbalance can affect trial outcomes.Methods5851 patients with Parkinson’s disease of European ancestry data and two simulated virtual cohorts based on public data were used. Data were resampled at different sizes for 1000 iterations and randomly assigned to the two arms of a simulated trial. False-negative and false-positive rates were estimated using simulated clinical trials, and per cent difference in genetic risk score (GRS) and allele frequency was calculated to quantify variance between arms.Results5851 patients with Parkinson’s disease (mean (SD) age, 61.02 (12.61) years; 2095 women (35.81%)) as well as simulated patients from virtually created cohorts were used in the study. Approximately 90% of the iterations had at least one statistically significant difference in individual risk SNPs between each trial arm. Approximately 5%–6% of iterations had a statistically significant difference between trial arms in mean GRS. For significant iterations, the average per cent difference for mean GRS between trial arms was 130.87%, 95% CI 120.89 to 140.85 (n=200). Glucocerebrocidase (GBA) gene-only simulations see an average 18.86%, 95% CI 18.01 to 19.71 difference in GRS scores between trial arms (n=50). When adding a drug effect of −0.5 points in MDS-UPDRS per year at n=50, 33.9% of trials resulted in false negatives.ConclusionsOur data support the hypothesis that within genetically unmatched clinical trials, genetic heterogeneity could confound true therapeutic effects as expected. Clinical trials should undergo pretrial genetic adjustment or, at the minimum, post-trial adjustment and analysis for failed trials.

Total white blood cell (WBC) and neutrophil counts are lower among individuals of African descent due to the common African-derived \"null\" variant of the Duffy Antigen Receptor for Chemokines (DARC) gene. Additional common genetic polymorphisms were recently associated with total WBC and WBC sub-type levels in European and Japanese populations. No additional loci that account for WBC variability have been identified in African Americans. In order to address this, we performed a large genome-wide association study (GWAS) of total WBC and cell subtype counts in 16,388 African-American participants from 7 population-based cohorts available in the Continental Origins and Genetic Epidemiology Network. In addition to the DARC locus on chromosome 1q23, we identified two other regions (chromosomes 4q13 and 16q22) associated with WBC in African Americans (P<2.5×10(-8)). The lead SNP (rs9131) on chromosome 4q13 is located in the CXCL2 gene, which encodes a chemotactic cytokine for polymorphonuclear leukocytes. Independent evidence of the novel CXCL2 association with WBC was present in 3,551 Hispanic Americans, 14,767 Japanese, and 19,509 European Americans. The index SNP (rs12149261) on chromosome 16q22 associated with WBC count is located in a large inter-chromosomal segmental duplication encompassing part of the hydrocephalus inducing homolog (HYDIN) gene. We demonstrate that the chromosome 16q22 association finding is most likely due to a genotyping artifact as a consequence of sequence similarity between duplicated regions on chromosomes 16q22 and 1q21. Among the WBC loci recently identified in European or Japanese populations, replication was observed in our African-American meta-analysis for rs445 of CDK6 on chromosome 7q21 and rs4065321 of PSMD3-CSF3 region on chromosome 17q21. In summary, the CXCL2, CDK6, and PSMD3-CSF3 regions are associated with WBC count in African American and other populations. We also demonstrate that large inter-chromosomal duplications can result in false positive associations in GWAS.

Although over 90 independent risk variants have been identified for Parkinson’s disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson’s disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci ( MTF2 , PIK3CA , ADD1 , SYBU , IRS2 , USP8 , PIGL , FASN , MYLK2 , USP25 , EP300 and PPP6R2 ) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations. Multi-ancestry genome-wide association analyses identify new risk loci for Parkinson’s disease, and fine-mapping and co-localization analyses implicate candidate genes whose expression is associated with disease susceptibility.

Accurate diagnosis and early detection of complex diseases, such as Parkinson's disease, has the potential to be of great benefit for researchers and clinical practice. We aimed to create a non-invasive, accurate classification model for the diagnosis of Parkinson's disease, which could serve as a basis for future disease prediction studies in longitudinal cohorts. We developed a model for disease classification using data from the Parkinson's Progression Marker Initiative (PPMI) study for 367 patients with Parkinson's disease and phenotypically typical imaging data and 165 controls without neurological disease. Olfactory function, genetic risk, family history of Parkinson's disease, age, and gender were algorithmically selected by stepwise logistic regression as significant contributors to our classifying model. We then tested the model with data from 825 patients with Parkinson's disease and 261 controls from five independent cohorts with varying recruitment strategies and designs: the Parkinson's Disease Biomarkers Program (PDBP), the Parkinson's Associated Risk Study (PARS), 23andMe, the Longitudinal and Biomarker Study in PD (LABS-PD), and the Morris K Udall Parkinson's Disease Research Center of Excellence cohort (Penn-Udall). Additionally, we used our model to investigate patients who had imaging scans without evidence of dopaminergic deficit (SWEDD). In the population from PPMI, our initial model correctly distinguished patients with Parkinson's disease from controls at an area under the curve (AUC) of 0·923 (95% CI 0·900–0·946) with high sensitivity (0·834, 95% CI 0·711–0·883) and specificity (0·903, 95% CI 0·824–0·946) at its optimum AUC threshold (0·655). All Hosmer-Lemeshow simulations suggested that when parsed into random subgroups, the subgroup data matched that of the overall cohort. External validation showed good classification of Parkinson's disease, with AUCs of 0·894 (95% CI 0·867–0·921) in the PDBP cohort, 0·998 (0·992–1·000) in PARS, 0·955 (no 95% CI available) in 23andMe, 0·929 (0·896–0·962) in LABS-PD, and 0·939 (0·891–0·986) in the Penn-Udall cohort. Four of 17 SWEDD participants who our model classified as having Parkinson's disease converted to Parkinson's disease within 1 year, whereas only one of 38 SWEDD participants who were not classified as having Parkinson's disease underwent conversion (test of proportions, p=0·003). Our model provides a potential new approach to distinguish participants with Parkinson's disease from controls. If the model can also identify individuals with prodromal or preclinical Parkinson's disease in prospective cohorts, it could facilitate identification of biomarkers and interventions. National Institute on Aging, National Institute of Neurological Disorders and Stroke, and the Michael J Fox Foundation.

Alaska Native children experience high rates of lower respiratory tract infections (LRTIs) and lung conditions, which are associated with substandard indoor air quality (IAQ). We conducted an intervention of home remediation and education to assess the impact on IAQ, respiratory symptoms and LRTI visits. We enrolled households of children 1-12 years of age with lung conditions. Home remediation included improving ventilation and replacing leaky woodstoves. We provided education about IAQ and respiratory health. We monitored indoor airborne particles (PM2.5), CO 2 , relative humidity and volatile organic compounds (VOCs), and interviewed caregivers about children's symptoms before, and for 1 year after intervention. We evaluated the association between children's respiratory visits, symptoms and IAQ indicators using multiple logistic regression. A total of 60 of 63 homes completed the study. VOCs decreased (coefficient = −0.20; p < 0.001); however, PM2.5 (coeff. = −0.010; p = 0.89) did not decrease. Burning wood for heat, VOCs and PM2.5 were associated with respiratory symptoms. After remediation, parents reported decreases in runny nose, cough between colds, wet cough, wheezing with colds, wheezing between colds and school absences. Children had an age-adjusted decrease in LRTI visits (coefficient = −0.33; p = 0.028). Home remediation and education reduced respiratory symptoms, LRTI visits and school absenteeism in children with lung conditions.

Indoor air pollutants contribute to respiratory infections and asthma exacerbations in children. Rural Alaska Native children experience some of the highest U.S. rates of respiratory hospitalizations, which are associated with lack of in-home running water, household crowding, and woodstove use. In our previous study, in-home education and modifications reduced respiratory symptoms, and medical visits. In this study, we evaluated the feasibility of providing in-hospital environmental health consults for parents/guardians of children < 5 years old hospitalized at the Alaska Native Medical Center with respiratory infections or asthma. Environmental health specialists conducted 92 in-hospital consults and mailed Healthy Homes Toolkits to households. Local housing authorities completed low-cost home modifications in 47 eligible households. Participants reported changes in household behaviors that were specifically addressed in the consult or included in the Toolkit (e.g. allergen-impermeable pillow covers). Reported respiratory symptoms were decreased at the 6-month follow-up. Over a 2 year period the median overall medical costs for respiratory illness in study children were $70,500. Children with in-home piped water had half the daily overall medical costs than children without in-home piped water ($74 compared to $144). In this study, we demonstrate that it is feasible to provide environmental consults, mail Toolkits, and arrange home modifications to the homes of children hospitalized with respiratory illness. These findings, along with the high costs of medical care for these children, suggest in-hospital environmental health consults are a cost-effective intervention.

Candidatus Patescibacteria is a diverse bacterial phylum that is notable for members with ultrasmall cell size, reduced genomes, limited metabolic capabilities, and dependence on other prokaryotic hosts. Despite the prevalence of the name Ca. Patescibacteria in the scientific literature, it is not officially recognized under the International Code of Nomenclature of Prokaryotes and lacks a nomenclatural type. Here, we rectify this situation by describing two closely related circular metagenome-assembled genomes and by proposing one of them (ABY1TS) to serve as the nomenclatural type for the species Patescibacterium danicumTS gen. nov., sp. nov. according to the rules of the SeqCode. Rank-normalized phylogenomic inference confirmed the stable placement of P. danicumTS in the Ca. Patescibacteria class ABY1. Based on these results, we propose Patescibacterium gen. nov. to serve as the type genus for associated higher taxa, including the phylum Patescibacteriota phyl. nov. We complement our proposal with a genomic characterization, metabolic reconstruction, and biogeographical analysis of Patescibacterium. Our results confirm small genome sizes (<1 Mbp), low GC content (>36%), and the occurrence of long gene coding insertions in the 23S rRNA sequences, along with reduced metabolic potential, inferred symbiotic lifestyle, and a global distribution. In summary, our proposal will provide nomenclatural stability to the fourth-largest phylum in the bacterial domain.