Evaluation of oral health status in the population above 50: evidence from the ardakan cohort study on aging (ACSA).

BACKGROUND: The global population is undergoing rapid aging, and older individuals are more susceptible to various health issues, including oral health problems. Despite the increasing attention given to healthy aging, oral health has often been overlooked in discussions related to health problems. This study aims to assess the oral health status of middle-aged and older adults in Iran. METHODS: This cross-sectional study analyzed data from 4970 men and women aged 50 years and above, who participated in the Ardakan Cohort Study on Aging (ACSA) between 2020 and 2022. Trained personnel administered a questionnaire and conducted oral health examinations to determine the oral health status and oral hygiene behaviors of the participants. RESULTS: The mean value (SD) of the total Decayed, Missing, and Filled Teeth (DMFT) index was 21.3 (10.7). Approximately 46% of all participants were completely edentulous (without natural teeth). Moreover, 58.5% of the total sample wore dentures, and the mean age (SD) when they started using dentures was 48.5 (20.7) years. About 71% of participants with natural teeth reported brushing their teeth at least once a day, while about 63% of denture wearers cleaned their dentures daily. In the sample, 28% of individuals had visited a dentist in the last year. The prevalence of difficulty in biting and chewing food among the participants was 48.2% and 44.6%, respectively. Additionally, nearly 68% of all samples reported experiencing at least one difficulty in daily functioning due to oral/dental conditions. The study identified cutoff points of seven (sensitivity = 56.8 and specificity = 77.5) and 10 (sensitivity = 72.1 and specificity = 71.1) missing teeth, indicating the presence of at least one problem in daily functioning due to oral/dental conditions in middle-aged and older adults, respectively. CONCLUSION: The study reveals a high prevalence of edentulism and denture use among participants aged 50 years and above. The majority of samples reported difficulties in daily functioning due to oral and dental conditions, especially in biting and chewing food. These findings highlight the importance of proactive measures to address oral health issues in middle-aged and older adults, thereby enhancing their overall health and well-being.

Systolic myocardial function measured by echocardiographic speckle-tracking and peak oxygen consumption in pediatric childhood cancer survivors-a PACCS study.

Background: Cancer therapy-related cardiotoxicity is a major cause of cardiovascular morbidity in childhood cancer survivors. The aims of this study were to investigate systolic myocardial function and its association to cardiorespiratory fitness in pediatric childhood cancer survivors. Methods: In this sub-study of the international study "Physical Activity and fitness in Childhood Cancer Survivors" (PACCS), echocardiographic measures of left ventricular global longitudinal strain (LV-GLS) and right ventricular longitudinal strain (RV-LS) were measured in 128 childhood cancer survivors aged 9-18 years and in 23 age- and sex-matched controls. Cardiorespiratory fitness was measured as peak oxygen consumption achieved on treadmill and correlated to myocardial function. Results: Mean LV-GLS was reduced in the childhood cancer survivors compared to the controls, -19.7% [95% confidence interval (CI) -20.1% to -19.3%] vs. -21.3% (95% CI: -22.2% to -20.3%) (p = 0.004), however, mainly within normal range. Only 13% of the childhood cancer survivors had reduced LV longitudinal strain z-score. Mean RV-LS was similar in the childhood cancer survivors and the controls, -23.2% (95% CI: -23.7% to -22.6%) vs. -23.3% (95% CI: -24.6% to -22.0%) (p = 0.8). In the childhood cancer survivors, lower myocardial function was associated with lower peak oxygen consumption [correlation coefficient (r) = -0.3 for LV-GLS]. Higher doses of anthracyclines (r = 0.5 for LV-GLS and 0.2 for RV-LS) and increasing time after treatment (r = 0.3 for LV-GLS and 0.2 for RV-LS) were associated with lower myocardial function. Conclusions: Left ventricular function, but not right ventricular function, was reduced in pediatric childhood cancer survivors compared to controls, and a lower left ventricular myocardial function was associated with lower peak oxygen consumption. Furthermore, higher anthracycline doses and increasing time after treatment were associated with lower myocardial function, implying that long-term follow-up is important in this population at risk.

Global incidence, mortality, and burden of esophageal cancer, and its correlation with SDI, metabolic risks, fasting plasma glucose, LDL cholesterol, and body mass index: An ecological study.

Background and Aims: Esophageal cancer (EC) is one of the most common gastrointestinal malignancies. The geographical variation shows the influence of genetic factors, ethnicity, and distribution of various risk factors. Accurate knowledge of EC epidemiology at the global level will help to develop management strategies. Therefore, the present study was conducted to investigate the global and regional disease burden of EC, including the incidence, mortality, and burden of this cancer in 2019. Methods: Incidence, mortality, disability-adjusted life years (DALYs), and age-standardized rates (ASRs) associated with EC in 204 countries in different classifications were extracted from the global burden of disease study. After collecting information on metabolic risks, fasting plasma glucose (FPG), low-density lipoprotein (LDL) cholesterol, and body mass index (body mass index), the relationship between age-standardized incidence rate (ASIR), mortality rate, and DALYs with these variables was determined. Results: In 2019, 534,563 new cases of EC were reported worldwide. The highest ASIR is related to regions with medium sociodemographic index (SDI), and high middle income according to the World Bank, the Asian continent, and the western Pacific region. In 2019, a total of 498,067 deaths from EC were recorded. The highest mortality rate due to ASR is in countries with medium SDI and countries with upper middle income of the World Bank. In 2019, 1,166,017 DALYs were reported due to EC. The ASIR, ASDR, and DALYS ASR of EC showed a significant negative linear correlation with SDI, metabolic risks, high FPG, high LDL cholesterol, and high BMI (p < 0.05). Conclusions: The results of this study showed significant gender and geographic variation in the incidence, mortality, and burden of EC. It is recommended to design and implement preventive approaches based on known risk factors and improve quality and access to efficient and appropriate treatments.

Evaluation of Sleep Quality and Related Factors in Community-Dwelling Adults: Ardakan Cohort Study on Aging (ACSA).

BACKGROUND: Sleep is a necessary physiological process that affects health. The current study aimed to evaluate sleep quality (SQ) and the related factors in Iranian community-dwelling adults. Study Design: A cross-sectional study. Method: Population-based cross-sectional data from the first wave of the Ardakan cohort study on aging (ACSA) were analyzed. The analytical sample consisted of 5197 community-dwelling adults aged≥50. All data were collected by trained staff. Pittsburgh Sleep Quality Index (PSQI) scores were used to measure SQ. Univariable and multivariable logistic regression were used to identify predictors of SQ. RESULTS: The mean age of the participants was 62.22±7.7 years, and 51.8% were female. About threequarters of them (76.36%) were found to have poor SQ (PSQI score≥5). Multivariable logistic regression analysis revealed a relationship between SQ and gender, education, work, and financial level. Furthermore, SQ was found to be associated with self-reported health and physical activity. Regarding comorbidity, SQ had a significant relationship with cardiovascular diseases, musculoskeletal diseases, depression, and anxiety (P<0.05). CONCLUSION: The prevalence of poor SQ was high in these community-dwelling adults in Iran. These findings highlight the importance of intervention programs for sleep hygiene education and screening for middle-aged and older adults.

Acute kidney injury in patients with COVID-19 in the intensive care unit: evaluation of risk factors and mortality in a national cohort.

OBJECTIVES: Acute kidney injury (AKI) is a frequent complication among critical ill patients with COVID-19, but the actual incidence is unknown as AKI-incidence varies from 25% to 89% in intensive care unit (ICU) populations. We aimed to describe the prevalence and risk factors of AKI in patients with COVID-19 admitted to ICU in Norway. DESIGN: Nation-wide observational study with data sampled from the Norwegian Intensive Care and Pandemic Registry (NIPaR) for the period between 10 March until 31 December 2020. SETTING: ICU patients with COVID-19 in Norway. NIPaR collects data on intensive care stays covering more than 90% of Norwegian ICU and 98% of ICU stays. PARTICIPANTS: Adult patients with COVID-19 admitted to Norwegian ICU were included in the study. Patients with chronic kidney disease (CKD) were excluded in order to avoid bias from CKD on the incidence of AKI. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome was AKI at ICU admission as defined by renal Simplified Acute Physiology Score in NIPaR. Secondary outcome measures included survival at 30 and 90 days after admission to hospital. RESULTS: A total number of 361 patients with COVID-19 were included in the analysis. AKI was present in 32.0% of the patients at ICU admission. The risk for AKI at ICU admission was related to acute circulatory failure at admission to hospital. Survival for the study population at 30 and 90 days was 82.5% and 77.6%, respectively. Cancer was a predictor of 30-day mortality. Age, acute circulatory failure at hospital admission and AKI at ICU admission were predictors of both 30-day and 90-day mortality. CONCLUSIONS: A high number of patients with COVID-19 had AKI at ICU admission. The study indicates that AKI at ICU admission was related to acute circulatory failure at hospital admission. Age, acute circulatory failure at hospital admission and AKI at ICU admission were associated with mortality.

Resistance profiles and diversity of ß-lactamases in Escherichia coli strains isolated from city-scale sewage surveillance in Bergen, Norway mimic clinical prevalence.

The aim of this study was to examine antibiotic resistance profiles and diversity of ß-lactamases in Escherichia coli present within the population and the potential spread of resistant E. coli into the receiving environment using city-scale sewage surveillance. In E. coli isolates from ECC plates without antibiotics from ten influent samples (n = 300), highest resistance was observed against ampicillin (16.6%), sulfamethoxazole (9.7%) and trimethoprim (9.0%), while in effluent samples (n = 262) it was against sulfamethoxazole (11.8%), ampicillin (11.5%) and tetracycline (8.8%). All isolates (n = 123) obtained on cefotaxime-containing plates were multidrug-resistant. Several clinically important antibiotic resistance genes (ARGs) were detected in 46 E. coli isolates subjected to whole-genome sequencing, including carbapenemases like NDM-6, VIM-1 and OXA-48-variant, as well as tigecycline resistance gene tet(X4). CTX-M-15 was the most prevalent (42.9%) extended-spectrum ß-lactamase among cefotaxime-resistant isolates, followed by CTX-M-27 (31.4%) and CTX-M-14 (17.1%), resembling clinical prevalence in Norway. Most of the sequenced isolates carried other clinically relevant ARGs, such as dfrA17, sul1, sul2, tet(A), aph(6)-Id, aph(3'')-Ib and aadA5. Sixteen different sequence types (STs) were identified, including ST131 (39.1%), ST38 (10.9%) and ST69 (8.7%). One E. coli isolate belonging to novel ST (ST11874) carried multiple virulence factors including genotoxin, salmochelin, aerobactin and yersiniabactin, suggesting that this isolate has potential to cause health concerns in future. Our study reveals presence of clinically relevant ARGs like blaNDM-6 and tet(X4) in pathogenic strains, which have so far not been reported from the clinics in Norway. Our study may thus, provide a framework for population-based surveillance of antibiotic resistance.

First report of mobile tigecycline resistance gene tet(X4)-harbouring multidrug-resistant Escherichia coli from wastewater in Norway.

OBJECTIVES: The mobile tigecycline resistance gene tet(X4), conferring resistance to all tetracyclines, is largely reported from China, however the global spread of such a novel resistance mechanism is a concern for preserving the efficacy of these last-resort antibiotics. The aim of our study was to determine the genetic basis of resistance in a tigecycline-resistant Escherichia coli strain (2-326) isolated from sewage in Bergen, Norway, using whole-genome sequencing (WGS). METHODS: WGS was carried out using Illumina MiSeq-based sequencing. In vitro conjugation assays were performed to determine the potential of isolate 2-326 to transfer tigecycline resistance to other strains. RESULTS: Escherichia coli isolate 2-326 belongs to pathogenic sequence type 167 (ST167) and carries several clinically important antibiotic resistance genes including tet(X4), blaCTX-M-14, dfrA12, sul2, qnrS1 as well as several aminoglycoside resistance genes. Tigecycline resistance along with resistance to tetracycline, sulfamethoxazole, chloramphenicol and azithromycin was transferred to green fluorescent protein (GFP)-encoding E. coli strain CV601-GFP by conjugation. CONCLUSION: To the best of our knowledge, this is the first report of E. coli carrying mobile tet(X4) gene from Norway. Our study demonstrates the ongoing spread of new mechanisms of resistance against last-resort antibiotics and the need for surveillance of such resistance factors in the population in order to mitigate their spread.

An integrated landscape of protein expression in human cancer.

Using 11 proteomics datasets, mostly available through the PRIDE database, we assembled a reference expression map for 191 cancer cell lines and 246 clinical tumour samples, across 13 lineages. We found unique peptides identified only in tumour samples despite a much higher coverage in cell lines. These were mainly mapped to proteins related to regulation of signalling receptor activity. Correlations between baseline expression in cell lines and tumours were calculated. We found these to be highly similar across all samples with most similarity found within a given sample type. Integration of proteomics and transcriptomics data showed median correlation across cell lines to be 0.58 (range between 0.43 and 0.66). Additionally, in agreement with previous studies, variation in mRNA levels was often a poor predictor of changes in protein abundance. To our knowledge, this work constitutes the first meta-analysis focusing on cancer-related public proteomics datasets. We therefore also highlight shortcomings and limitations of such studies. All data is available through PRIDE dataset identifier PXD013455 and in Expression Atlas.

Using Deep Learning to Extrapolate Protein Expression Measurements.

Mass spectrometry (MS)-based quantitative proteomics experiments typically assay a subset of up to 60% of the ≈20 000 human protein coding genes. Computational methods for imputing the missing values using RNA expression data usually allow only for imputations of proteins measured in at least some of the samples. In silico methods for comprehensively estimating abundances across all proteins are still missing. Here, a novel method is proposed using deep learning to extrapolate the observed protein expression values in label-free MS experiments to all proteins, leveraging gene functional annotations and RNA measurements as key predictive attributes. This method is tested on four datasets, including human cell lines and human and mouse tissues. This method predicts the protein expression values with average R2 scores between 0.46 and 0.54, which is significantly better than predictions based on correlations using the RNA expression data alone. Moreover, it is demonstrated that the derived models can be "transferred" across experiments and species. For instance, the model derived from human tissues gave a R2=0.51 when applied to mouse tissue data. It is concluded that protein abundances generated in label-free MS experiments can be computationally predicted using functional annotated attributes and can be used to highlight aberrant protein abundance values.

Proteogenomics of Non-smoking Lung Cancer in East Asia Delineates Molecular Signatures of Pathogenesis and Progression.

Lung cancer in East Asia is characterized by a high percentage of never-smokers, early onset and predominant EGFR mutations. To illuminate the molecular phenotype of this demographically distinct disease, we performed a deep comprehensive proteogenomic study on a prospectively collected cohort in Taiwan, representing early stage, predominantly female, non-smoking lung adenocarcinoma. Integrated genomic, proteomic, and phosphoproteomic analysis delineated the demographically distinct molecular attributes and hallmarks of tumor progression. Mutational signature analysis revealed age- and gender-related mutagenesis mechanisms, characterized by high prevalence of APOBEC mutational signature in younger females and over-representation of environmental carcinogen-like mutational signatures in older females. A proteomics-informed classification distinguished the clinical characteristics of early stage patients with EGFR mutations. Furthermore, integrated protein network analysis revealed the cellular remodeling underpinning clinical trajectories and nominated candidate biomarkers for patient stratification and therapeutic intervention. This multi-omic molecular architecture may help develop strategies for management of early stage never-smoker lung adenocarcinoma.

The role of organizational factors in nurse burnout: Experiences from Iranian nurses working in psychiatric wards.

INTRODUCTION: The optimal performance of a healthcare organization is one of the effective factors in increasing the efficiency and productivity of nurses and thus reducing their burnout. The aim of this study was to investigate the role of organizational management on nurse burnout based on experiences from Iranian nurses working in psychiatric wards. MATERIALS AND METHODS: This qualitative study was conducted on 15 nurses working in psychiatric wards selected through purposive sampling. Data collection was done through in-depth semi-structured interviews in psychiatric wards in Ahvaz (southwest of Iran) and Tehran. Data analysis was done through conventional content analysis. RESULTS: The findings included one main category and three subcategories. The main category was "Providing care at an inadequate organization," and the three sub-classes namely "Shortages of human resources," "Shortage of physical resources," and "Impact of management approaches to care provision" were extracted. CONCLUSION: The results of this study showed that inadequate supply of equipment and human resources along with ineffective managerial approaches in the organization could lead to mental and emotional exhaustion, negative attitudes toward the profession, decreased and poor service quality, employee turnover, and early retirement of nurses in psychiatric wards. Therefore, by adopting appropriate policies in their programs, paying special attention to the physical and mental health of nurses, and addressing their problems, managers of healthcare organizations can motivate and sustain the human resources within the organization.

The effectiveness of clinical teaching of mental health courses in nursing using clinical supervision and Kirkpatrick's model.

BACKGROUND: Clinical experience associated with the fear and anxiety of nursing students in the psychiatric unit. Mental health nursing instructors find it challenging to teach nursing students to deal with patients with mental disorders in an environment where they need to provide patient teaching and clinical decision-making based on evidence and new technology. OBJECTIVE: To measure the effectiveness of clinical teaching of mental health courses in nursing using clinical supervision and Kirkpatrick's model evaluation in the psychiatry unit of Imam Reza Hospital, Bojnurd, Iran. METHODS: This cross-sectional study was carried out from 2011 to 2016 on 76 nursing students from a university as part of a clinical mental health course in two semesters. The students were selected by a non-probable convenient sampling method. After completing their clinical education, each student responded to checklist questions based on the four-level Kirkpatrick's model evaluation and open questions relating to clinical supervision. Finally, all data was analyzed using the SPSS version 16. RESULTS: The students have evaluated clinical supervision as a useful approach, and appreciated the instructor's supportive behavior during teaching and imparting clinical skills. This has made them feel relaxed at the end of the clinical teaching course. In addition, in the evaluation through Kirkpatrick's model, more than 70% of the students have been satisfied with the method of conducting the teaching and average score of nursing students' attitude toward mental health students: Their mean self-confidence score was 18.33±1.69, and the mean score of their performance in the study was evaluated to be 93.74±5.3 from 100 points. CONCLUSION: The results of clinical mental health teaching through clinical supervision and Kirkpatrick's model evaluation show that the satisfaction, self-esteem, attitude, and skill of nursing students are excellent, thereby portraying the effectiveness of clinical teaching. But this program still needs to be reformed. To establish long-term goals and obtain knowledge and clinical skills of nursing, it is recommended to develop a curriculum and evaluate it appropriately.

Genomic Determinants of Protein Abundance Variation in Colorectal Cancer Cells.

Assessing the impact of genomic alterations on protein networks is fundamental in identifying the mechanisms that shape cancer heterogeneity. We have used isobaric labeling to characterize the proteomic landscapes of 50 colorectal cancer cell lines and to decipher the functional consequences of somatic genomic variants. The robust quantification of over 9,000 proteins and 11,000 phosphopeptides on average enabled the de novo construction of a functional protein correlation network, which ultimately exposed the collateral effects of mutations on protein complexes. CRISPR-cas9 deletion of key chromatin modifiers confirmed that the consequences of genomic alterations can propagate through protein interactions in a transcript-independent manner. Lastly, we leveraged the quantified proteome to perform unsupervised classification of the cell lines and to build predictive models of drug response in colorectal cancer. Overall, we provide a deep integrative view of the functional network and the molecular structure underlying the heterogeneity of colorectal cancer cells.

A Critical Overview on the Pharmacological and Clinical Aspects of Popular Satureja Species.

Throughout the world, various parts of most Satureja species are traditionally used to treat patients with various diseases and complications. As for the presence of different classes of metabolites in Satureja and their numerous ethnomedical and ethnopharmacological applications, many species have been pharmacologically evaluated. The current work aimed to compile information from pharmacological studies on this savory for further investigations. The keyword Satureja was searched through Scopus and PubMed up to January 1, 2016. We found nearly 55 papers that dealt with the pharmacology of Satureja. We found that 13 species had been evaluated pharmacologically and that Satureja khuzestanica, Satureja bachtiarica, Satureja montana and Satureja hortensis appeared to be the most active, both clinically and phytopharmacologically. Regarding the content of rich essential oil, most evaluations were concerned with the antimicrobial properties. However, the antioxidant, antidiabetic and anticholesterolemic properties of the studied species were found to be good. In addition to the pharmacological activities that have been indentified for some species, opportunities still exist to assess the effectiveness of other well-known species. If different Satureja species are to have extensive ethnopharmacological applications, comprehensive assessments of the acute and chronic toxicities, as well as the teratogenicity, of those plants are needed.

A nonhomogeneous hidden markov model for gene mapping based on next-generation sequencing data.

The analysis of polygenetic characteristics for mapping quantitative trait loci (QTL) remains an important challenge. QTL analysis requires two or more strains of organisms that differ substantially in the (poly-)genetic trait of interest, resulting in a heterozygous offspring. The offspring with the trait of interest is selected and subsequently screened for molecular markers such as single-nucleotide polymorphisms (SNPs) with next-generation sequencing. Gene mapping relies on the co-segregation between genes and/or markers. Genes and/or markers that are linked to a QTL influencing the trait will segregate more frequently with this locus. For each identified marker, observed mismatch frequencies between the reads of the offspring and the parental reference strains can be modeled by a multinomial distribution with the probabilities depending on the state of an underlying, unobserved Markov process. The states indicate whether the SNP is located in a (vicinity of a) QTL or not. Consequently, genomic loci associated with the QTL can be discovered by analyzing hidden states along the genome. The aforementioned hidden Markov model assumes that the identified SNPs are equally distributed along the chromosome and does not take the distance between neighboring SNPs into account. The distance between the neighboring SNPs could influence the chance of co-segregation between genes and markers. To address this issue, we propose a nonhomogeneous hidden Markov model with a transition matrix that depends on a set of distance-varying observed covariates. The application of the model is illustrated on the data from a study of ethanol tolerance in yeast.

The effects of an interventional program based on self-care model on health-related quality of life outcomes in hemodialysis patients.

BACKGROUND: Hemodialysis patients have lower quality of life and one of the ways to improve their quality of life is providing self-care education to them using some models including self-care model. This study aimed to determine and evaluate the effects of using self-care model on health and quality of life outcomes in hemodialysis patients. MATERIALS AND METHODS: This was a quasi-experimental study conducted in 2012 on the patients who were referred to a military hospital in Tehran, Iran to be treated with hemodialysis. All 32 patients referred to this hospital in 2012 were selected and studied. Required data were collected using the Short Form-36 (SF-36) standard questionnaire and a researcher-made questionnaire. The educational intervention was implemented using self-care model. Collected data were analyzed using SPSS for Windows version 18.0 and some statistical tests including paired samples t-test, Wilcoxon and McNemar tests. RESULTS: The results showed that the mean and standard deviation (SD) of patients' parameters including weight and blood pressure improved significantly after the educational intervention compared to before the intervention (P < 0.001). Also, all dimensions of the quality of life of hemodialysis patients, including physical function, role physical, bodily pain, general health, vitality, social function, mental health, and role emotional improved compared to those before the intervention (P < 0.001). CONCLUSION: Implementing the self-care model increased the quality of life of hemodialysis patients. Therefore, the use of this model in hemodialysis patients is recommended.

The use of the isotopic distribution as a complementary quality metric to assess tandem mass spectra results.

Shotgun proteomics is a powerful technology to study the protein population of a biological system. This approach employs tandem mass spectrometry for amino acid sequencing. Fragmented ion masses can be used in correlative database-searching, like SEQUEST or Mascot, to identify peptides. The database-search method depends upon a score function that evaluates matches between the predicted ions and the ions observed in the tandem mass spectrum. Principally, peptide identification based on tandem MS and database-search algorithms does not take into account information about isotope distributions of the precursor ions. To determine the effectiveness of these search algorithms in terms of their ability to distinguish between correct and incorrect peptide assignments, we propose an additional metric that quantifies the similarity between the theoretical isotopic distribution for the precursor ions selected for tandem MS and the experimental mass spectra by using Pearson's χ(2) statistic. The observed association between Pearson's χ(2) statistic and the score function indicates that good scores can be obtained for molecules which exhibit atypical isotope profiles, while low scores can be obtained for fragment spectra which have a clear peptide-like isotope pattern. These results demonstrate that Pearson's χ(2) statistic can be used in conjunction with the score of database-search algorithms to increase the sensitivity and specificity of peptide identification. BIOLOGICAL SIGNIFICANCE: In this manuscript, we present a workflow that provides a new perspective on the quality of peptide-to-spectrum matches (PSM) employed in database-searching strategies for peptide identification. Additional views on a dataset can facilitate a more hypothesis-driven interpretation of the mass spectrometry signals. The similarity metric on the PSM scores contemplates the isotopic profile and results in a measure that conveys a degree of biomolecular similarity observed from the precursor of the selected tandem MS spectra. A close agreement between the PSM score and the similarity metric will result in a higher confidence for the identification of the selected precursor ion.

Comparison of the Mahalanobis distance and Pearson's χ² statistic as measures of similarity of isotope patterns.

To extract a genuine peptide signal from a mass spectrum, an observed series of peaks at a particular mass can be compared with the isotope distribution expected for a peptide of that mass. To decide whether the observed series of peaks is similar to the isotope distribution, a similarity measure is needed. In this short communication, we investigate whether the Mahalanobis distance could be an alternative measure for the commonly employed Pearson's χ(2) statistic. We evaluate the performance of the two measures by using a controlled MALDI-TOF experiment. The results indicate that Pearson's χ(2) statistic has better discriminatory performance than the Mahalanobis distance and is a more robust measure.