Bile-volatile organic compounds in the diagnostics of pancreatic cancer and biliary obstruction: A prospective proof-of-concept study.

Objectives: Detection of volatile organic compounds (VOCs) from bodily fluids with field asymmetric waveform ion mobility spectrometry (FAIMS) and related methods has been studied in various settings. Preliminary results suggest that it is possible to detect prostate, colorectal, ovarian and pancreatic cancer from urine samples. In this study, our primary aim was to differentiate pancreatic cancer from pancreatitis and benign tumours of the pancreas by using bile samples obtained during endoscopic retrograde cholangiopancreatography (ERCP). Secondarily, we aimed to differentiate all pancreatic region malignancies from all other kinds of benign causes of biliary obstruction. Methods: A bile sample was successfully aspirated from 94 patients during ERCP in Tampere University Hospital. Hospital and patient records were prospectively followed up for at least two years after ERCP. Bile samples were analysed using a Lonestar chemical analyser (Owlstone, UK) using an ATLAS sampling system and a split-flow box. Diagnoses and corresponding data from the analyses were matched and divided into two subcategories for comparison. Statistical analysis was performed using linear discriminant analysis, support vector machines, and 5-fold cross-validation. Results: Pancreatic cancers (n=8) were differentiated from benign pancreatic lesions (n=9) with a sensitivity of 100%, specificity of 77.8%, and correct rate of 88%. All pancreatic region cancers (n=19) were differentiated from all other kinds of benign causes of biliary obstruction (n=75) with corresponding values of 21.1%, 94.7%, and 80.7%. The sample size was too small to try to differentiate pancreatic cancers from adjacent cancers. Conclusion: Analysing bile VOCs using FAIMS shows promising capability in detecting pancreatic cancer and other cancers in the pancreatic area.

Domestication of drinking: a survey study of changes in types of drinking occasions during periods of increasing and decreasing alcohol consumption in the 2000s in Finland.

BACKGROUND AND AIMS: In Finland, per-capita alcohol consumption increased in the early 2000s and decreased after 2007. Our aim was to determine how these changes originated from changes in drinking practices. DESIGN: Repeated cross-sectional general-population surveys. SETTING: Finland in 2000, 2008 and 2016. PARTICIPANTS: Finnish residents aged 15-69 years (n = 6703, response rate 59-78%). MEASUREMENTS: Event-level data on drinking occasions (n = 21 097). Types of drinking occasions (drinking practices) were identified with latent class analysis using occasion characteristics. The aggregated volume of consumption and intoxication occasions were decomposed into contributions from drinking practice classes and years. FINDINGS: Nine drinking occasion types were identified: three at home without company other than family (51% of occasions in 2016), three socializing occasions in different places and with different company (33%) and three party occasion types (16%). Both the frequency of drinking occasion types and the occasion type-specific amounts of alcohol consumed contributed to aggregate-level changes in alcohol use. Drinking at home without external company (with family only; for men, also alone) contributed most to the increase in alcohol use before 2008. Big parties in homes and bars became less common in the 2000s, contributing most to the decline in drinking after 2008. CONCLUSIONS: The rise in per-capita alcohol consumption in Finland in the early 2000s appears to have been linked mainly to an increase in lighter drinking occasions at home without external company. The fall in per-capita drinking after 2007 was linked mainly to a decrease in big parties in homes and in licensed premises. Changes in drinking frequency and the amounts of alcohol consumed per occasion changed in the same direction as alcohol affordability.

Description of movement sensor dataset for dog behavior classification.

Movement sensor data from seven static and dynamic dog behaviors (sitting, standing, lying down, trotting, walking, playing, and (treat) searching i.e. sniffing) was collected from 45 middle to large sized dogs with six degree-of-freedom movement sensors attached to the collar and the harness. With 17 dogs the collection procedure was repeated. The duration of each of the seven behaviors was approximately three minutes. The order of the tasks was varied between the dogs and the two repetitions (for the 17 dogs). The behaviors were annotated post-hoc based on the video recordings made with two camcorders during the tests with one second resolution. The annotations were accurately synchronized with the raw movement sensors data. The annotated data was originally used for training behavior classification machine learning algorithms for classifying the seven behaviors. The developed signal processing and classification algorithms are provided together with the raw measurement data and reference annotations. The description and results of the original investigation that the dataset relates to are found in: P. Kumpulainen, A. Valldeoriola Cardó, S. Somppi, H. Törnqvist, H. Väätäjä, P. Majaranta, Y. Gizatdinova, C. Hoog Antink, V. Surakka, M. V. Kujala, O. Vainio, A. Vehkaoja, Dog behavior classification with movement sensors placed on the harness and the collar, Applied Animal behavior Science, 241 (2021), 105,393.

How Are All Drinking Occasions, Intoxication Occasions, and All Alcohol Consumed Distributed Across Different Drinking Occasion Types? A Typology of Drinking Occasions in Finland.

OBJECTIVE: To understand the contexts and characteristics of drinking occasions, we typologized drinking occasions and examined how different aspects of drinking vary in them and what part of population-level drinking and intoxication occasions each covers. METHOD: A Finnish general population survey in 2016 (n = 2,285) with event-level data on drinking occasions (n = 6,697) was used. Occasion types were identified by latent class analysis. The characteristics of the drinking occasions were location, purpose, company, timing, duration, the amounts and beverages drunk, and estimated blood alcohol concentration (eBAC). RESULTS: Eight drinking occasion classes were identified. The three most common ones were all light drinking occasions at home, with the company varying. Five of the eight types were about socializing with people beyond the family. The heaviest drinking occasion type, "big party nights," had an average eBAC of .12%, which seemed to be connected to the long duration of these occasions. The most important contributors to total population-level intoxication occasions were "big party nights" and "at home with the family" occasions (accounting for 30% and 20%, respectively). In terms of contributions to the population's total alcohol consumption, the order of these classes was reversed (19% and 26%, respectively). Drinking at home with no visitors covered 40% of all the alcohol drunk in Finland. Different types of occasions varied little in beverage type composition. CONCLUSIONS: For acute harm, "big party nights" are important to consider because of the prevalence of intoxication, whereas for chronic harm, drinking at home without visitors is even more important to consider.

Predicting lecithin concentration from differential mobility spectrometry measurements with linear regression models and neural networks.

Differential mobility spectrometry (DMS) analysis of electrosurgical smoke can be used to distinguish cancerous and healthy tissues. Mass spectrometry studies of surgical smoke have revealed phospholipids as the key compounds enabling this discrimination. Lecithin is a mixture of phospholipids encountered in tissues. We hypothesized that DMS is capable of detecting and quantifying lecithin from water solution in headspace chamber, paving way for analysis of surgical smoke. We measured different lecithin concentrations in a biologically relevant range considering healthy and cancerous tissues with DMS and trained regression models to predict the analyte concentration. The models were internally cross-validated and externally validated. The best cross-validation results were obtained with convolutional neural networks, with root mean square error (RMSE) = 0.38 mg/ml. This is the first demonstration of estimation of analyte concentration from DMS measurements with neural networks. The best external validation results were acquired with sparse linear regression methods, with RMSE varying from 0.40 mg/ml to 0.41 mg/ml. The results demonstrate that DMS is sufficiently sensitive to detect biologically relevant changes in phospholipid concentration, potentially explaining its ability to detect cancerous tissue. In the future, we aim to reproduce the results by using surgical smoke as the medium. In this scenario, the complex background of surgical smoke will be the main challenge to overcome. Predicting concentration with neural networks also lays the foundation for wider analytical usage of DMS.

Discrimination between Pancreatic Cancer, Pancreatitis and Healthy Controls Using Urinary Polyamine Panel.

BACKROUND: Polyamines play an important role in cellular proliferation, and the change in polyamine metabolism is reported in various cancers. We searched for urinary polyamine signature for distinguishing between pancreatic cancer, premalignant lesions of the pancreas (PLP), acute and chronic pancreatitis, and controls. METHODS: Patients and controls were prospectively recruited in three Finnish hospitals between October 2013 and June 2016. The patients provided a urine sample at the time of the diagnosis. The panel of 14 polyamines was obtained in a single run with mass spectrometry. The polyamine concentrations were analysed with quadratic discriminant analysis and cross-validated with leave-one-out cross-validation. RESULTS: Sixty-eight patients with pancreatic cancer, 36 with acute pancreatitis, 18 with chronic pancreatitis and 7 with PLP were recruited, as were 53 controls. The combination of 4 polyamines - acetylputrescine, diacetylspermidine, N8-acetylspermidine and diacetylputrescine - distinguished pancreatic cancer and PLP from controls (sensitivity = 94%, specificity = 68% and AUC = 0.88). The combination of diacetylspermidine, N8-acetylspermidine and diacetylspermine distinguished acute pancreatitis from controls (sensitivity = 94%, specificity = 92%, AUC = 0.98). The combination of acetylputrescine, diacetylspermidine and diacetylputrescine distinguished chronic pancreatitis from controls (sensitivity = 98%, specificity = 71%, AUC = 0.93). CONCLUSIONS: Optimally selected urinary polyamine panels discriminate between pancreatic cancer and controls, as well as between acute and chronic pancreatitis and controls.

Differential mobility spectrometry imaging for pathological applications.

Pathologic examination of clinical tissue samples is time consuming and often does not involve the comprehensive analysis of the whole specimen. Automated tissue analysis systems have potential to make the workflow of a pathologist more efficient and to support in clinical decision-making. So far, these systems have been based on application of mass spectrometry imaging (MSI). MSI provides high fidelity and the results in tissue identification are promising. However, the high cost and need for maintenance limit the adoption of MSI in the clinical setting. Thus, there is a need for new innovations in the field of pathological tissue imaging. In this study, we show that differential ion mobility spectrometry (DMS) is a viable option in tissue imaging. We demonstrate that a DMS-driven solution performs with up to 92% accuracy in differentiating between two grossly distinct animal tissues. In addition, our model is able to classify the correct tissue with 81% accuracy in an eight-class setting. The DMS-based system is a significant innovation in a field dominated by mass-spectrometry-based solutions. By developing the presented platform further, DMS technology could be a cost-effective and helpful tool for automated pathological analysis.

Urine headspace analysis with field asymmetric ion mobility spectrometry for detection of chronic kidney disease.

Electronic noses (eNoses) are an emerging class of experimental diagnostic tools. They are based on the detection of volatile organic compounds. Urine is used as sample medium in several publications but neither the effect of chronic kidney disease (CKD) on the analysis nor the potential to detect CKD has been explored. Materials & methods: We utilized an eNose based on field asymmetric ion mobility spectrometry (FAIMS) technology to classify urine samples from CKD patients and controls. Results: We were able to differentiate extremes of kidney function with an accuracy of 81.4%. Conclusion: In this preliminary study, applying eNose technology we were able to distinguish the patients with impaired kidney function from those with normal kidney function.

FAIMS analysis of urine gaseous headspace is capable of differentiating ovarian cancer.

AIM: We hypothesized that field asymmetric waveform ion mobility spectrometry (FAIMS) as a novel artificial olfactory technology could differentiate urine of women with malignant ovarian tumors from controls and women with benign tumors, based on previous findings on the ability of canine olfactory system to "smell" cancer. PATIENTS AND METHODS: Preoperative urine samples from 51 women with ovarian tumors, both benign and malignant, and from 18 women with genital prolapse, as controls, were collected. The samples were analyzed by FAIMS device. Data analysis was processed by quadratic data analysis (QDA) and linear discriminant analysis (LDA), and cross-validated using 10-fold cross-validation. RESULTS: Thirty-three women had malignant ovarian tumors, of which 18 were high-grade cancers. FAIMS distinguished controls from malignancies with the accuracy of 81.3% (sensitivity 91.2% and specificity 63.1%), and benign tumors from malignancies with the accuracy of 77.3% (sensitivity 91.5% and specificity 51.4%). Moreover, low grade tumors were also separated from high grade cancers and benign ovarian tumors with accuracies of 88.7% (sensitivity 87.8% and specificity 89.6%) and 83.9% (sensitivity 73.1% and specificity 92.9%), respectively. CONCLUSIONS: This proof of concept-study indicates that the FAIMS from urine has potential to discriminate malignant ovarian tumors from no tumor-bearing controls and benign tumors.

Altered Polyamine Profiles in Colorectal Cancer.

BACKGROUND: The declining mortality rate of patients with colorectal cancer (CRC) can be explained, at least partially, with early diagnosis. Simple diagnostic methods are needed to achieve a maximal patient participation rate in screening. MATERIALS AND METHODS: Liquid chromatography electrospray tandem mass spectrometry (LC-MS/MS) was used to determine urinary polyamine (PA) profiles. In a prospective setting, 116 patients were included in the study: 57 with CRC, 13 with inflammatory bowel disease (IBD), 12 with adenoma, and 34 controls. RESULTS: N1,N12-diacetylspermine (DiAcSPM) level was significantly higher in patients with CRC than controls (sensitivity=78.0%, specificity=70.6%; p=0.00049). The level of diacetylated cadaverine (p=0.0068) was lower and that of diacetylated putrescine (p=0.0078) was higher in patients with CRC than in those with IBD. Cadaverine (p=0.00010) and spermine (p=0.042) levels were lower and that of DiAcSPM (p=0.018) higher in patients with CRC than in those with adenoma. CONCLUSION: The simultaneous determination of urinary PAs by means of LC-MS/MS can be used to discriminate CRC from controls and patients with benign colorectal diseases.

Electronic Nose in the Detection of Wound Infection Bacteria from Bacterial Cultures: A Proof-of-Principle Study.

BACKGROUND: Soft tissue infections, including postoperative wound infections, result in a significant burden for modern society. Rapid diagnosis of wound infections is based on bacterial stains, cultures, and polymerase chain reaction assays, and the results are available earliest after several hours, but more often not until days after. Therefore, antibiotic treatment is often administered empirically without a specific diagnosis. METHODS: We employed our electronic nose (eNose) system for this proof-of-concept study, aiming to differentiate the most relevant bacteria causing wound infections utilizing a set of clinical bacterial cultures on identical blood culture dishes, and established bacterial lines from the gaseous headspace. RESULTS: Our eNose system was capable of differentiating both methicillin-sensitive Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA), Streptococcus pyogenes, Escherichia coli, Pseudomonas aeruginosa, and Clostridium perfringens with an accuracy of 78% within minutes without prior sample preparation. Most importantly, the system was capable of differentiating MRSA from MSSA with a sensitivity of 83%, a specificity of 100%, and an overall accuracy of 91%. CONCLUSIONS: Our results support the concept of rapid detection of the most relevant bacteria causing wound infections and ultimately differentiating MRSA from MSSA utilizing gaseous headspace sampling with an eNose.

Comparison of non-invasive blood pressure monitoring using modified arterial applanation tonometry with intra-arterial measurement.

Intermittent non-invasive blood pressure measurement with tourniquets is slow, can cause nerve and skin damage, and interferes with other measurements. Invasive measurement cannot be safely used in all conditions. Modified arterial tonometry may be an alternative for fast and continuous measurement. Our aim was to compare arterial tonometry sensor (BPro®) with invasive blood pressure measurement to clarify whether it could be utilized in the postoperative setting. 28 patients who underwent elective surgery requiring arterial cannulation were analyzed. Patients were monitored post-operatively for 2 h with standard invasive monitoring and with a study device comprising an arterial tonometry sensor (BPro®) added with a three-dimensional accelerometer to investigate the potential impact of movement. Recordings were collected electronically. The results revealed inaccurate readings in method comparison between the devices based on recommendations by Association for the Advancement of Medical Instrumentation (AAMI). On a Bland-Altman plot, the bias and precision between these two methods was 19.8 ± 16.7 (Limits of agreement - 20.1 to 59.6) mmHg, Spearman correlation coefficient r = 0.61. For diastolic pressure, the difference was 4.8 ± 7.7 (LoA - 14.1 to 23.6) mmHg (r = 0.72), and for mean arterial pressure it was 11.18 ± 11.1 (LoA - 12.1 to 34.2) mmHg (r = 0.642). Our study revealed inaccurate agreement (AAMI) between the two methods when measuring systolic and mean blood pressures during post-operative care. The readings for diastolic pressures were inside the limits recommended by AAMI. Movement increased the failure rate significantly (p < 0.001). Thus, arterial tonometry is not an appropriate replacement for invasive blood pressure measurement in these patients.

Urinary Polyamines as Biomarkers for Ovarian Cancer.

OBJECTIVES: Elevated concentrations of polyamines have been found in urine of patients with malignant tumors, including ovarian cancer. Previous research has suffered from poorly standardized detection methods. Our liquid chromatography-tandem mass spectrometry (LC-MS/MS) method is capable of simultaneous standardized analysis of most known polyamines. Liquid chromatography-tandem mass spectrometry has not previously been used in the differential diagnostics of ovarian tumors in postmenopausal women. MATERIALS AND METHODS: In this prospective study, postmenopausal women (n = 71) presenting with an adnexal mass and, as controls, women with genital prolapse or urinary incontinence scheduled for surgery (n = 22) were recruited in the study. For analysis of the polyamines, a morning urine sample was obtained before surgery. Preoperative serum CA125 concentrations were determined in the study group. RESULTS: Twenty-three women with benign and 37 with malignant ovarian tumors were eligible. Of all analyzed polyamines, only urinary N,N-diacetylspermine showed statistically significant differences between all groups except controls versus benign tumors. N,N-diacetylspermine was elevated in malignant versus benign tumors (P < 0.001), in high-grade versus low malignant potential tumors (P < 0.001), in stage III to IV versus stage I to II cancers (P < 0.001), and even in early-stage cancer (stage I-II) versus benign tumors (P = 0.017). N,N-diacetylspermine had better sensitivity (86.5%) but lower specificity (65.2%) for distinguishing benign and malignant ovarian tumors than CA125 with a cut-off value of 35 kU/L (sensitivity, 75.7%; specificity, 69.6%). CONCLUSIONS: Urinary N,N-diacetylspermine seems to be able to distinguish benign and malignant ovarian tumors as well as early and advanced stage, and low malignant potential and high-grade ovarian cancers from each other, respectively.

Determination of saturation, heart rate, and respiratory rate at forearm using a Nellcor™ forehead SpO2-saturation sensor.

Alterations in arterial blood oxygen saturation, heart rate (HR), and respiratory rate (RR) are strongly associated with intra-hospital cardiac arrests and resuscitations. A wireless, easy-to-use, and comfortable method for monitoring these important clinical signs would be highly useful. We investigated whether the Nellcor™ OxiMask MAX-FAST forehead sensor could provide data for vital sign measurements when located at the distal forearm instead of its intended location at the forehead to provide improved comfortability and easy placement. In a prospective setting, we recruited 30 patients undergoing surgery requiring postoperative care. At the postoperative care unit, patients were monitored for two hours using a standard patient monitor and with a study device equipped with a Nellcor™ Forehead SpO2 sensor. The readings were electronically recorded and compared in post hoc analysis using Bland-Altman plots, Spearman's correlation, and root-mean-square error (RMSE). Bland-Altman plot showed that saturation (SpO2) differed by a mean of -0.2 % points (SD, 4.6), with a patient-weighted Spearman's correlation (r) of 0.142, and an RMSE of 4.2 points. For HR measurements, the mean difference was 0.6 bpm (SD, 2.5), r = 0.997, and RMSE = 1.8. For RR, the mean difference was -0.5 1/min (4.1), r = 0.586, and RMSE = 4.0. The SpO2 readings showed a low mean difference, but also a low correlation and high RMSE, indicating that the Nellcor™ saturation sensor cannot reliably assess oxygen saturation at the forearm when compared to finger PPG measurements.

Rapid and accurate detection of urinary pathogens by mobile IMS-based electronic nose: a proof-of-principle study.

UNLABELLED: Urinary tract infection (UTI) is a common disease with significant morbidity and economic burden, accounting for a significant part of the workload in clinical microbiology laboratories. Current clinical chemisty point-of-care diagnostics rely on imperfect dipstick analysis which only provides indirect and insensitive evidence of urinary bacterial pathogens. An electronic nose (eNose) is a handheld device mimicking mammalian olfaction that potentially offers affordable and rapid analysis of samples without preparation at athmospheric pressure. In this study we demonstrate the applicability of ion mobility spectrometry (IMS) -based eNose to discriminate the most common UTI pathogens from gaseous headspace of culture plates rapidly and without sample preparation. We gathered a total of 101 culture samples containing four most common UTI bacteries: E. coli, S. saprophyticus, E. faecalis, Klebsiella spp and sterile culture plates. The samples were analyzed using ChemPro 100i device, consisting of IMS cell and six semiconductor sensors. Data analysis was conducted by linear discriminant analysis (LDA) and logistic regression (LR). The results were validated by leave-one-out and 5-fold cross validation analysis. In discrimination of sterile and bacterial samples sensitivity of 95% and specificity of 97% were achieved. The bacterial species were identified with sensitivity of 95% and specificity of 96% using eNose as compared to urine bacterial cultures. IN CONCLUSION: These findings strongly demonstrate the ability of our eNose to discriminate bacterial cultures and provides a proof of principle to use this method in urinanalysis of UTI.

Detection of prostate cancer by an electronic nose: a proof of principle study.

PURPOSE: We evaluate the ability of an electronic nose to discriminate prostate cancer from benign prostatic hyperplasia using urine headspace, potentially offering a clinically applicable noninvasive and rapid diagnostic method. MATERIALS AND METHODS: The ChemPro® 100-eNose was used to discriminate prostate cancer from benign prostatic hyperplasia using urine sample headspace. Its performance was tested with 50 patients with confirmed prostate cancer and 24 samples from 15 patients with benign prostatic hyperplasia (15 patients provided urine preoperatively and 9 patients provided samples 3 months postoperatively) scheduled to undergo robotic assisted laparoscopic radical prostatectomy or transurethral resection of prostate, respectively. The patients provided urine sample preoperatively and those with benign prostatic hyperplasia also provided samples 3 months postoperatively to be used as a pooled control sample population. A discrimination classifier was identified for eNose and subsequently, sensitivity and specificity values were determined. Leave-one-out cross-validation was performed. RESULTS: Using leave-one-out cross-validation the eNose reached a sensitivity of 78%, a specificity of 67% and AUC 0.77. CONCLUSIONS: The electronic nose is capable of rapidly and noninvasively discriminating prostate cancer and benign prostatic hyperplasia using urine headspace in patients undergoing surgery.

Correlation approach for the detection of the heartbeat intervals using force sensors placed under the bed posts.

This study proposes a method for detecting the heartbeat intervals of a person lying on a bed from ballistocardiographic signals recorded unobtrusively with four dynamic force sensors located under the bed posts. The method does not recognize individual heartbeats, but the intervals where the correlation between two consecutive signal segments maximizes. This study evaluated the performance of the method with nine subjects in 1-h long recordings and achieved 91% beat-to-beat interval (BBI) recognition coverage; 98.6% of the detected BBIs differed less than 50 ms from the values calculated from a reference electrocardiogram signal. This study also evaluated the reliability of two parameters of heart rate variability that have been used in sleep quality assessment in several studies and are usually calculated for 30 s epochs. The results suggest that the method is able to provide sufficient reliability for using the data in evaluation of sleep quality.

Detection of smell print differences between nonmalignant and malignant prostate cells with an electronic nose.

AIM: To determine whether an electronic nose can differentiate cultured nonmalignant and malignant prostatic cells from each other and whether the smell print is secreted to the surrounding medium. MATERIALS & METHODS: Prostatic nonmalignant (EP-156T and controls) and malignant (LNCaP) cell lines, as well as conditioned and unconditioned media, were collected. The smell prints of the samples were analyzed by a ChemPro(®) 100 electronic nose device. The data were normalized and dimension reduction was conducted. The samples were classified and misclassification rates were calculated. RESULTS: The electronic nose differentiated the nonmalignant and malignant cell lines from each other, achieving misclassification rates of 2.9-3.6%. Cells did not differ from the conditioned medium but differed from the unconditioned medium (misclassification rates: 0.0-25.6%). CONCLUSION: Malignant and nonmalignant prostatic cell lines have distinct smell prints. Prostatic cancer cells seem to modify the smell print of their medium.