Use of chemotherapy in patients with oesophageal, stomach, colon, rectal, liver, pancreatic, lung, and ovarian cancer: an International Cancer Benchmarking Partnership (ICBP) population-based study.

BACKGROUND: There are few data on international variation in chemotherapy use, despite it being a key treatment type for some patients with cancer. Here, we aimed to examine the presence and size of such variation. METHODS: This population-based study used data from Norway, the four UK nations (England, Northern Ireland, Scotland, and Wales), eight Canadian provinces (Alberta, British Columbia, Manitoba, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, and Saskatchewan), and two Australian states (New South Wales and Victoria). Patients aged 15-99 years diagnosed with cancer in eight different sites (oesophageal, stomach, colon, rectal, liver, pancreatic, lung, or ovarian cancer), with no other primary cancer diagnosis occurring from within the 5 years before to 1 year after the index cancer diagnosis or during the study period were included in the study. We examined variation in chemotherapy use from 31 days before to 365 days after diagnosis and time to its initiation, alongside related variation in patient group differences. Information was obtained from cancer registry records linked to clinical or patient management system data or hospital administration data. Random-effects meta-analyses quantified interjurisdictional variation using 95% prediction intervals (95% PIs). FINDINGS: Between Jan 1, 2012, and Dec 31, 2017, of 893 461 patients with a new diagnosis of one of the studied cancers, 111 569 (12·5%) did not meet the inclusion criteria, and 781 892 were included in the analysis. There was large interjurisdictional variation in chemotherapy use for all studied cancers, with wide 95% PIs: 47·5 to 81·2 (pooled estimate 66·4%) for ovarian cancer, 34·9 to 59·8 (47·2%) for oesophageal cancer, 22·3 to 62·3 (40·8%) for rectal cancer, 25·7 to 55·5 (39·6%) for stomach cancer, 17·2 to 56·3 (34·1%) for pancreatic cancer, 17·9 to 49·0 (31·4%) for lung cancer, 18·6 to 43·8 (29·7%) for colon cancer, and 3·5 to 50·7 (16·1%) for liver cancer. For patients with stage 3 colon cancer, the interjurisdictional variation was greater than that for all patients with colon cancer (95% PI 38·5 to 78·4; 60·1%). Patients aged 85-99 years had 20-times lower odds of chemotherapy use than those aged 65-74 years, with very large interjurisdictional variation in this age difference (odds ratio 0·05; 95% PI 0·01 to 0·19). There was large variation in median time to first chemotherapy (from diagnosis date) by cancer site, with substantial interjurisdictional variation, particularly for rectal cancer (95% PI -15·5 to 193·9 days; pooled estimate 89·2 days). Patients aged 85-99 years had slightly shorter median time to first chemotherapy compared with those aged 65-74 years, consistently between jurisdictions (-3·7 days, 95% PI -7·6 to 0·1). INTERPRETATION: Large variation in use and time to chemotherapy initiation were observed between the participating jurisdictions, alongside large and variable age group differences in chemotherapy use. To guide efforts to improve patient outcomes, the underlying reasons for these patterns need to be established. FUNDING: International Cancer Benchmarking Partnership (funded by the Canadian Partnership Against Cancer, Cancer Council Victoria, Cancer Institute New South Wales, Cancer Research UK, Danish Cancer Society, National Cancer Registry Ireland, The Cancer Society of New Zealand, National Health Service England, Norwegian Cancer Society, Public Health Agency Northern Ireland on behalf of the Northern Ireland Cancer Registry, DG Health and Social Care Scottish Government, Western Australia Department of Health, and Public Health Wales NHS Trust).

Modeling the selective growth advantage of genetically variant human pluripotent stem cells to identify opportunities for manufacturing process control.

BACKGROUND AIMS: The appearance of genetically variant populations in human pluripotent stem cell (hPSC) cultures represents a concern for research and clinical applications. Genetic variations may alter hPSC differentiation potential or cause phenotype variation in differentiated cells. Further, variants may have properties such as proliferative rate, or response to the culture environment, that differ from wild-type cells. As such, understanding the behavior of these variants in culture, and any potential operational impact on manufacturing processes, will be necessary to control quality of putative hPSC-based products that include a proportion of variant threshold in their quality specification. METHODS: Here we show a computational model that mathematically describes the growth dynamics between commonly occurring genetically variant hPSCs and their counterpart wild-type cells in culture. RESULTS: We show that our model is capable of representing the growth behaviors of both wild-type and variant hPSCs in individual and co-culture systems. CONCLUSIONS: This representation allows us to identify three critical process parameters that drive critical quality attributes when genetically variant cells are present within the system: total culture density, proportion of variant cells within the culture system and variant cell overgrowth. Lastly, we used our model to predict how the variability of these parameters affects the prevalence of both populations in culture.

From sleep patterns to heart rhythm: Predicting atrial fibrillation from overnight polysomnograms.

BACKGROUND: Atrial fibrillation (AF) is often asymptomatic and thus under-observed. Given the high risks of stroke and heart failure among patients with AF, early prediction and effective management are crucial. Given the prevalence of obstructive sleep apnea among AF patients, electrocardiogram (ECG) analysis from polysomnography (PSG) offers a unique opportunity for early AF prediction. Our aim is to identify individuals at high risk of AF development from single­lead ECGs during standard PSG. METHODS: We analyzed 18,782 single­lead ECG recordings from 13,609 subjects undergoing PSG at the Massachusetts General Hospital sleep laboratory. AF presence was identified using ICD-9/10 codes. The dataset included 15,913 recordings without AF history and 2054 recordings from patients diagnosed with AF between one month to fifteen years post-PSG. Data were partitioned into training, validation, and test cohorts ensuring that individual patients remained exclusive to each cohort. The test set was held out during the training process. We employed two different methods for feature extraction to build a final model for AF prediction: Extraction of hand-crafted ECG features and a deep learning method. For extraction of ECG-hand-crafted features, recordings were split into 30-s windows, and those with a signal quality index (SQI) below 0.95 were discarded. From each remaining window, 150 features were extracted from the time, frequency, time-frequency domains, and phase-space reconstructions of the ECG. A compilation of 12 statistical features summarized these window-specific features per recording, resulting in 1800 features (12 × 150). A pre-trained deep neural network from the PhysioNet Challenge 2021 was updated using transfer learning to discriminate recordings with and without AF. The model processed PSG ECGs in 16-s windows to generate AF probabilities, from which 13 statistical features were extracted. Combining 1800 features from feature extraction with 13 from the deep learning model, we performed a feature selection and subsequently trained a shallow neural network to predict future AF and evaluated its performance on the test cohort. RESULTS: On the test set, our model exhibited sensitivity, specificity, and precision of 0.67, 0.81, and 0.3, respectively, for AF prediction. Survival analysis revealed a hazard ratio of 8.36 (p-value: 1.93 × 10-52) for AF outcomes using the log-rank test. CONCLUSIONS: Our proposed ECG analysis method, utilizing overnight PSG data, shows promise in AF prediction despite modest precision, suggesting false positives. This approach could enable low-cost screening and proactive treatment for high-risk patients. Refinements, including additional physiological parameters, may reduce false positives, enhancing clinical utility and accuracy.

The association between social jetlag and depression is independent of sleep debt.

OBJECTIVES: To investigate whether the association between SJLsc (sleep-corrected social jetlag) and depressive mood is significant and independent of sleep debt. METHODS: Participants from the general adult population were interviewed using structured questionnaires on sleep duration, weekday/weekend sleep schedules, and depressive mood (Patient Health Questionnaire-9). Social jetlag (SJL) was measured by SJLsc and standard SJL (SJLs). SJLs was the absolute difference between mid-sleep time on free days (MSF) and workdays (MSW). For SJLsc, both MSF and MSW were adjusted for average sleep duration across the week according to the direction of sleep debt. Sleep debt was defined by sleep extension on free days. The association of SJL with depression was investigated, and covariates included age, sex, sociodemographic factors, insomnia symptoms, sleep duration, and sleep debt. RESULTS: A total of 1982 individuals (1089 men; age 43.1 ± 14.4 years) were analyzed. SJL was present in 24.6% measured by SJLsc and 51.0% by SJLs. SJLsc and SJLs were significantly associated with depressive mood (r = 0.06, P = 0.02; r = 0.06, P = 0.01, respectively), independent of sleep debt. Sleep debt was also associated with depression (r = 0.07, P < 0.01). CONCLUSIONS: By adopting sleep-corrected formula for SJL, this study found that misaligned and insufficient sleep, at levels occurring in routine social life, can negatively affect mood. Minimizing social jetlag and sleep deprivation may promote individual psychological well-being.

High prevalence of sleep-disordered breathing in the intensive care unit - a cross-sectional study.

PURPOSE: Sleep-disordered breathing may be induced by, exacerbate, or complicate recovery from critical illness. Disordered breathing during sleep, which itself is often fragmented, can go unrecognized in the intensive care unit (ICU). The objective of this study was to investigate the prevalence, severity, and risk factors of sleep-disordered breathing in ICU patients using a single respiratory belt and oxygen saturation signals. METHODS: Patients in three ICUs at Massachusetts General Hospital wore a thoracic respiratory effort belt as part of a clinical trial for up to 7 days and nights. Using a previously developed machine learning algorithm, we processed respiratory and oximetry signals to measure the 3% apnea-hypopnea index (AHI) and estimate AH-specific hypoxic burden and periodic breathing. We trained models to predict AHI categories for 12-h segments from risk factors, including admission variables and bio-signals data, available at the start of these segments. RESULTS: Of 129 patients, 68% had an AHI ≥ 5; 40% an AHI > 15, and 19% had an AHI > 30 while critically ill. Median [interquartile range] hypoxic burden was 2.8 [0.5, 9.8] at night and 4.2 [1.0, 13.7] %min/h during the day. Of patients with AHI ≥ 5, 26% had periodic breathing. Performance of predicting AHI-categories from risk factors was poor. CONCLUSIONS: Sleep-disordered breathing and sleep apnea events while in the ICU are common and are associated with substantial burden of hypoxia and periodic breathing. Detection is feasible using limited bio-signals, such as respiratory effort and SpO2 signals, while risk factors were insufficient to predict AHI severity.

Evaluation of Viral Inactivation on Dry Surface by High Peak Power Microwave (HPPM) Exposure.

Previous research has shown that virus infectivity can be dramatically reduced by radio frequency exposure in the gigahertz (GHz) frequency range. Given the worldwide SARS-CoV-2 pandemic, which has caused over 1 million deaths and has had a profound global economic impact, there is a need for a noninvasive technology that can reduce the transmission of virus among humans. RF is a potential wide area-of-effect viral decontamination technology that could be used in hospital rooms where patients are expelling virus, in grocery and convenience stores where local populations mix, and in first responder settings where rapid medical response spans many potentially infected locations within hours. In this study, we used bovine coronavirus (BCoV) as a surrogate of SARS-CoV-2 and exposed it to high peak power microwave (HPPM) pulses at four narrowband frequencies: 2.8, 5.6, 8.5, and 9.3 GHz. Exposures consisted of 2 µs pulses delivered at 500 Hz, with pulse counts varied by decades between 1 and 10,000. The peak field intensities (i.e. the instantaneous power density of each pulse) ranged between 0.6 and 6.5 MW/m2 , depending on the microwave frequency. The HPPM exposures were delivered to plastic coverslips containing BCoV dried on the surface. Hemagglutination (HA) and cytopathic effect analyses were performed 6 days after inoculation of host cells to assess viral infectivity. No change in viral infectivity was seen with increasing dose (pulse number) across the tested frequencies. Under all conditions tested, exposure did not reduce infectivity more than 1.0 log10. For the conditions studied, high peak power pulsed RF exposures in the 2-10 GHz range appear ineffective as a virucidal approach for hard surface decontamination. © 2023 Bioelectromagnetics Society.

Association between older subjective age and poor sleep quality: a population-based study.

OBJECTIVE: To examine the association of subjective age (SA) with sleep quality in an adult population. METHODS: In the Korean Sleep and Headache Study, 2,349 participants (49.2% men; 48.1 ± 16.4 years old) were interviewed face-to-face using structured questionnaires between September and December 2018. SA was assessed by asking participants their perceived age in years and then compared with their chronological age (CA). Participants were assigned to three groups: feeling younger, feeling their age, and feeling older. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). Association between SA and sleep quality was analyzed with multiple linear regression controlling for demographics, psychosocial, and sleep characteristics. RESULTS: The group feeling older (n = 404, 17.2%; men, 58.2%; age, 46.5 ± 16.2 years) had worse sleep quality than the groups feeling younger and feeling their age (PSQI score, 4.3 ± 2.7, 3.8 ± 2.4, 3.4 ± 2.1, respectively, p <.001; prevalence of poor sleep quality, 29.0%, 18.4%, 13.5% respectively, p <.001). The association between SA and the PSQI score remained significant after adjusting for confounders (ß = 1.05, 95% confidence interval 0.26, 1.83; p <.001). Stratified analyses by sex and CA showed that the association between SA and the PSQI score was significant only in women and in middle-aged and older group (aged 50-79), suggesting that sex and CA modified the association. CONCLUSION: Age perception was associated with self-reported sleep quality, independent of CA. SA may be a useful marker that complements the conventional assessment of subjective sleep quality.

Long-term blood pressure patterns in midlife and dementia in later life: Findings from the Framingham Heart Study.

INTRODUCTION: Long-term blood pressure (BP) measures, such as visit-to-visit BP variability (BPV) and cumulative BP, are strong indicators of cardiovascular risks. This study modeled up to 20 years of BP patterns representative of midlife by using BPV and cumulative BP, then examined their associations with development of dementia in later life. METHODS: For 3201 individuals from the Framingham Heart Study, multivariate logistic regression analyses were performed to examine the association between long-term BP patterns during midlife and the development of dementia (ages ≥ 65). RESULTS: After adjusting for covariates, every quartile increase in midlife cumulative BP was associated with a sequential increase in the risk of developing dementia (e.g., highest quartile of cumulative systolic blood pressure had approximately 2.5-fold increased risk of all-cause dementia). BPV was not significantly associated with dementia. DISCUSSION: Findings suggest that cumulative BP over the course of midlife predicts risk of dementia in later life. HIGHLIGHTS Long-term blood pressure (BP) patterns are strong indicators of vascular risks. Cumulative BP and BP variability (BPV) were used to reflect BP patterns across midlife. High cumulative BP in midlife is associated with increased dementia risk. Visit-to-visit BPV was not associated with the onset of dementia.

Risk factors and prognostic implications of diagnosis of cancer within 30 days after an emergency hospital admission (emergency presentation): an International Cancer Benchmarking Partnership (ICBP) population-based study.

BACKGROUND: Greater understanding of international cancer survival differences is needed. We aimed to identify predictors and consequences of cancer diagnosis through emergency presentation in different international jurisdictions in six high-income countries. METHODS: Using a federated analysis model, in this cross-sectional population-based study, we analysed cancer registration and linked hospital admissions data from 14 jurisdictions in six countries (Australia, Canada, Denmark, New Zealand, Norway, and the UK), including patients with primary diagnosis of invasive oesophageal, stomach, colon, rectal, liver, pancreatic, lung, or ovarian cancer during study periods from Jan 1, 2012, to Dec 31, 2017. Data were collected on cancer site, age group, sex, year of diagnosis, and stage at diagnosis. Emergency presentation was defined as diagnosis of cancer within 30 days after an emergency hospital admission. Using logistic regression, we examined variables associated with emergency presentation and associations between emergency presentation and short-term mortality. We meta-analysed estimates across jurisdictions and explored jurisdiction-level associations between cancer survival and the percentage of patients diagnosed as emergencies. FINDINGS: In 857 068 patients across 14 jurisdictions, considering all of the eight cancer sites together, the percentage of diagnoses through emergency presentation ranged from 24·0% (9165 of 38 212 patients) to 42·5% (12 238 of 28 794 patients). There was consistently large variation in the percentage of emergency presentations by cancer site across jurisdictions. Pancreatic cancer diagnoses had the highest percentage of emergency presentations on average overall (46·1% [30 972 of 67 173 patients]), with the jurisdictional range being 34·1% (1083 of 3172 patients) to 60·4% (1317 of 2182 patients). Rectal cancer had the lowest percentage of emergency presentations on average overall (12·1% [10 051 of 83 325 patients]), with a jurisdictional range of 9·1% (403 of 4438 patients) to 19·8% (643 of 3247 patients). Across the jurisdictions, older age (ie, 75-84 years and 85 years or older, compared with younger patients) and advanced stage at diagnosis compared with non-advanced stage were consistently associated with increased emergency presentation risk, with the percentage of emergency presentations being highest in the oldest age group (85 years or older) for 110 (98%) of 112 jurisdiction-cancer site strata, and in the most advanced (distant spread) stage category for 98 (97%) of 101 jurisdiction-cancer site strata with available information. Across the jurisdictions, and despite heterogeneity in association size (I2=93%), emergency presenters consistently had substantially greater risk of 12-month mortality than non-emergency presenters (odds ratio >1·9 for 112 [100%] of 112 jurisdiction-cancer site strata, with the minimum lower bound of the related 95% CIs being 1·26). There were negative associations between jurisdiction-level percentage of emergency presentations and jurisdiction-level 1-year survival for colon, stomach, lung, liver, pancreatic, and ovarian cancer, with a 10% increase in percentage of emergency presentations in a jurisdiction being associated with a decrease in 1-year net survival of between 2·5% (95% CI 0·28-4·7) and 7·0% (1·2-13·0). INTERPRETATION: Internationally, notable proportions of patients with cancer are diagnosed through emergency presentation. Specific types of cancer, older age, and advanced stage at diagnosis are consistently associated with an increased risk of emergency presentation, which strongly predicts worse prognosis and probably contributes to international differences in cancer survival. Monitoring emergency presentations, and identifying and acting on contributing behavioural and health-care factors, is a global priority for cancer control. FUNDING: Canadian Partnership Against Cancer; Cancer Council Victoria; Cancer Institute New South Wales; Cancer Research UK; Danish Cancer Society; National Cancer Registry Ireland; The Cancer Society of New Zealand; National Health Service England; Norwegian Cancer Society; Public Health Agency Northern Ireland, on behalf of the Northern Ireland Cancer Registry; the Scottish Government; Western Australia Department of Health; and Wales Cancer Network.

Sleep apnea and respiratory anomaly detection from a wearable band and oxygen saturation.

OBJECTIVE: Sleep-related respiratory abnormalities are typically detected using polysomnography. There is a need in general medicine and critical care for a more convenient method to detect sleep apnea automatically from a simple, easy-to-wear device. The objective was to detect abnormal respiration and estimate the Apnea-Hypopnea Index (AHI) automatically with a wearable respiratory device with and without SpO2 signals using a large (n = 412) dataset serving as ground truth. DESIGN: Simultaneously recorded polysomnography (PSG) and wearable respiratory effort data were used to train and evaluate models in a cross-validation fashion. Time domain and complexity features were extracted, important features were identified, and a random forest model was employed to detect events and predict AHI. Four models were trained: one each using the respiratory features only, a feature from the SpO2 (%)-signal only, and two additional models that use the respiratory features and the SpO2 (%) feature, one allowing a time lag of 30 s between the two signals. RESULTS: Event-based classification resulted in areas under the receiver operating characteristic curves of 0.94, 0.86, and 0.82, and areas under the precision-recall curves of 0.48, 0.32, and 0.51 for the models using respiration and SpO2, respiration-only, and SpO2-only, respectively. Correlation between expert-labelled and predicted AHI was 0.96, 0.78, and 0.93, respectively. CONCLUSIONS: A wearable respiratory effort signal with or without SpO2 signal predicted AHI accurately, and best performance was achieved with using both signals.

Demographic and lifestyle risk factors for gastroesophageal reflux disease and Barrett's esophagus in Australia.

We examined demographic and lifestyle risk factors for incidence of gastroesophageal reflux disease (GERD) and Barrett's esophagus (BE) in an Australian cohort of 20,975 participants aged 40-63 at recruitment (1990-1994). Information on GERD and BE was collected between 2007 and 2010. GERD symptoms were defined as self-reported heartburn or acid regurgitation. BE was defined as endoscopically confirmed columnar-lined esophagus. Risk factors for developing GERD symptoms, BE diagnosis, age at symptom onset, and age at BE diagnosis were quantified using regression. During a mean follow-up of 15.8 years, risk of GERD symptoms was 7.5% (n = 1,318) for daily, 7.5% (n = 1,333) for 2-6 days/week, and 4.3% (n = 751) for 1 day/week. There were 210 (1.0%) endoscopically diagnosed BE cases, of whom 141 had histologically confirmed esophageal intestinal metaplasia. Female sex, younger age, lower socioeconomic position (SEP) and educational attainment, and former smoking were associated with higher GERD risk. Male sex and smoking were associated with earlier GERD symptom onset. Men, older participants, those with higher SEP, and former smokers were at higher BE risk. There was some evidence higher SEP was associated with earlier BE diagnosis. GERD and BE had different demographic risk factors but shared similar lifestyle factors. Earlier GERD symptom onset for men and smokers might have contributed to higher BE risk. The SEP patterns observed for GERD and BE suggest potential inequity in access to care. These findings would be important in the development of clinical risk prediction models for early detection of BE.

Cardiopulmonary Coupling.

Cardiopulmonary coupling (CPC) is a technique that generates sleep spectrogram by calculating the cross-spectral power and coherence of heart rate variability and respiratory tidal volume fluctuations. There are several forms of CPC in the sleep spectrogram, which may provide information about normal sleep physiology and pathological sleep states. Since CPC can be calculated from any signal recording containing heart rate and respiration information, such as photoplethysmography (PPG) or blood pressure, it can be widely used in various applications, including wearables and non-contact devices. When derived from PPG, an automatic apnea-hypopnea index can be calculated from CPC-oximetry as PPG can be obtained from oximetry alone. CPC-based sleep profiling reveals the effects of stable and unstable sleep on sleep apnea, insomnia, cardiovascular regulation, and metabolic disorders. Here, we introduce, with examples, the current knowledge and understanding of the CPC technique, especially the physiological basis, analytical methods, and its clinical applications.

Assessment of Automated Flow Cytometry Data Analysis Tools within Cell and Gene Therapy Manufacturing.

Flow cytometry is widely used within the manufacturing of cell and gene therapies to measure and characterise cells. Conventional manual data analysis relies heavily on operator judgement, presenting a major source of variation that can adversely impact the quality and predictive potential of therapies given to patients. Computational tools have the capacity to minimise operator variation and bias in flow cytometry data analysis; however, in many cases, confidence in these technologies has yet to be fully established mirrored by aspects of regulatory concern. Here, we employed synthetic flow cytometry datasets containing controlled population characteristics of separation, and normal/skew distributions to investigate the accuracy and reproducibility of six cell population identification tools, each of which implement different unsupervised clustering algorithms: Flock2, flowMeans, FlowSOM, PhenoGraph, SPADE3 and SWIFT (density-based, k-means, self-organising map, k-nearest neighbour, deterministic k-means, and model-based clustering, respectively). We found that outputs from software analysing the same reference synthetic dataset vary considerably and accuracy deteriorates as the cluster separation index falls below zero. Consequently, as clusters begin to merge, the flowMeans and Flock2 software platforms struggle to identify target clusters more than other platforms. Moreover, the presence of skewed cell populations resulted in poor performance from SWIFT, though FlowSOM, PhenoGraph and SPADE3 were relatively unaffected in comparison. These findings illustrate how novel flow cytometry synthetic datasets can be utilised to validate a range of automated cell identification methods, leading to enhanced confidence in the data quality of automated cell characterisations and enumerations.

Current trends in flow cytometry automated data analysis software.

Automated flow cytometry (FC) data analysis tools for cell population identification and characterization are increasingly being used in academic, biotechnology, pharmaceutical, and clinical laboratories. The development of these computational methods is designed to overcome reproducibility and process bottleneck issues in manual gating, however, the take-up of these tools remains (anecdotally) low. Here, we performed a comprehensive literature survey of state-of-the-art computational tools typically published by research, clinical, and biomanufacturing laboratories for automated FC data analysis and identified popular tools based on literature citation counts. Dimensionality reduction methods ranked highly, such as generic t-distributed stochastic neighbor embedding (t-SNE) and its initial Matlab-based implementation for cytometry data viSNE. Software with graphical user interfaces also ranked highly, including PhenoGraph, SPADE1, FlowSOM, and Citrus, with unsupervised learning methods outnumbering supervised learning methods, and algorithm type popularity spread across K-Means, hierarchical, density-based, model-based, and other classes of clustering algorithms. Additionally, to illustrate the actual use typically within clinical spaces alongside frequent citations, a survey issued by UK NEQAS Leucocyte Immunophenotyping to identify software usage trends among clinical laboratories was completed. The survey revealed 53% of laboratories have not yet taken up automated cell population identification methods, though among those that have, Infinicyt software is the most frequently identified. Survey respondents considered data output quality to be the most important factor when using automated FC data analysis software, followed by software speed and level of technical support. This review found differences in software usage between biomedical institutions, with tools for discovery, data exploration, and visualization more popular in academia, whereas automated tools for specialized targeted analysis that apply supervised learning methods were more used in clinical settings.

Sleep structure and electroencephalographic spectral power of middle-aged or older adults: Normative values by age and sex in the Korean population.

The fine structure of sleep electrocortical activity reflects health and disease. The current study provides normative data for sleep structure and electroencephalography (EEG) spectral power measures derived from overnight polysomnography (PSG) and examines the effect of age and sex among Korean middle-aged and older adults with or without obstructive sleep apnea (OSA). We analysed home PSG data from 1,153 adult participants of an ongoing population-based cohort study, the Korean Genome and Epidemiology Study. Sleep stages were visually scored and spectral power was measured on a single-channel EEG (C4-A1). We computed spectral power for five frequency ranges. The EEG power was reported in relative (%) and log-transformed absolute values (µV2 ). With ageing, the proportion of N1 sleep increased, whereas N3 decreased, which is more noticeable in men than in women. The amount of N3 was relatively low in this cohort. With ageing, relative delta power decreased and alpha and sigma power increased for the whole sleep period, which was more pronounced during REM sleep in non-OSA. For men compared with women, relative theta power was lower during REM and sigma and beta were higher during N1 sleep. The differences of relative powers by age and sex in OSA were comparable to those in non-OSA. In a community-based Korean population, we present normative data of sleep structure and spectral power for middle-aged or older adults of a non-Caucasian ethnicity. The values varied with age and sex and were not influenced by sleep apnea.

The effect of acute exposure to morphine on breathing variability and cardiopulmonary coupling in men with obstructive sleep apnea: A randomized controlled trial.

Opioid-related deaths from respiratory depression are increasing but there is only limited information on the effect of morphine on breathing during sleep. This study aimed to detect and quantify opioid-induced cardiorespiratory pattern changes during sleep in obstructive sleep apnea (OSA) patients using novel automated methods and correlate these with conventional polysomnography (PSG) measures. Under a randomized double-blind placebo-controlled crossover design, 60 male OSA patients attended two one-night visits to the sleep laboratory, at least a week apart. Either a 40-mg controlled-release oral morphine dose or placebo was administered. Breathing during sleep was measured by standard in-laboratory PSG. We analysed the inter-breath interval (IBI) from the PSG flow channel to quantify breathing irregularity. Cardiopulmonary coupling (CPC) was analysed using the PSG electrocardiogram (ECG) channel. Following the consumption of morphine, the 60 OSA patients had fewer breaths (p = .0006), a longer inter-breath interval (p < .0001) and more irregular breathing with increased IBI coefficient of variation (CV) (p = .0015) compared to the placebo night. A higher CPC sleep quality index was found with morphine use. The change of key IBI and CPC parameters was significantly correlated with the change of key PSG sleep-disordered breathing parameters. In conclusion, 40 mg controlled-release morphine resulted in a longer breathing cycle and increased breathing irregularity but generally more stable sleep in OSA patients. The significant links between the IBI and CPC techniques and a range of PSG sleep-disordered breathing parameters may suggest a practical value as surrogate overnight cardiorespiratory measurements, because both respiratory flow and ECG can be detected by small portable devices.

Neck Circumference and Cerebral Gray Matter Volume.

BACKGROUND: While obesity is linked with brain atrophy and dementia incidence, associations with regional adiposity are uncertain. Our goal was to determine whether cerebral gray matter volume is related to neck circumference (NC), a measure of regional adiposity having unique relationships with metabolic disorders and cardiovascular disease. METHODS: Magnetic resonance imaging and NC were cross-sectionally assessed from 2011 to 2014 in a population-based sample of 2916 men and women in the Korean Genome and Epidemiology Study. RESULTS: For men, NC was inversely associated with total and regional gray matter in the frontal, temporal, and occipital lobes after adjusting for age and intracranial brain volume. Associations were especially strong in the presence of diabetes. With further adjustment for indices of body composition and other characteristics, total and frontal gray matter in diabetic men were lowered by 6.1 mL (95% confidence interval: 2.5-9.7, P=0.004) and 2.9 mL (95% confidence interval: 1.0-4.9, P=0.017), respectively, per SD increase in NC (2.3 cm). For men without diabetes, and in all women, associations were less apparent. CONCLUSIONS: In men with diabetes, NC was inversely associated with cerebral gray matter volume. The link between neck anthropometry and brain aging in diabetic men warrants further consideration.

The pathway to diagnosis and treatment for surgically managed lung cancer patients.

BACKGROUND: Most lung cancer is diagnosed at an advanced stage, resulting in poor survival. This study examined diagnostic pathways for patients with operable lung cancer to identify factors contributing to early diagnosis. METHODS: Surgically treated lung cancer patients (aged ≥40, within 6 months of diagnosis), approached via the population-based Cancer Registry, with their primary care physicians (PCPs) and specialists completed cross-sectional surveys assessing symptoms, diagnostic route (symptomatic or 'investigation' of other problem), tests, key event dates and treatment. Time intervals to diagnosis and treatment were determined, and quantile regression examined differences between the two diagnostic routes. Cox proportional hazard regression analyses examined associations between survival and diagnostic route adjusting for stage, sex and age. RESULTS: One hundred and ninety-two patients (36% response rate), 107 PCPs and 55 specialists participated. Fifty-eight per cent of patients had a symptomatic diagnostic route reporting an average of 1.6 symptoms, most commonly cough, fatigue or haemoptysis. Symptomatic patients had longer median primary care interval than 'investigation' patients (12 versus 9 days, P < 0.05) and were more likely to report their PCP first-ordered imaging tests. Secondary care interval was shorter for symptomatic (median = 43 days) than investigation (median = 62 days, P < 0.05) patients. However, 56% of all patients waited longer than national recommendations (6 weeks). While survival estimates were better for investigation than symptomatic patients, these differences were not significant. CONCLUSION: Many operable lung cancer patients are diagnosed incidentally, highlighting the difficulty of symptom-based approaches to diagnosing early stage disease. Longer than recommended secondary care interval suggests the need for improvements in care pathways.

Complementary roles of gasotransmitters CO and H2S in sleep apnea.

Sleep apnea, which is the periodic cessation of breathing during sleep, is a major health problem affecting over 10 million people in the United States and is associated with several sequelae, including hypertension and stroke. Clinical studies suggest that abnormal carotid body (CB) activity may be a driver of sleep apnea. Because gaseous molecules are important determinants of CB activity, aberrations in their signaling could lead to sleep apnea. Here, we report that mice deficient in heme oxygenase-2 (HO-2), which generates the gaseous molecule carbon monoxide (CO), exhibit sleep apnea characterized by high apnea and hypopnea indices during rapid eye movement (REM) sleep. Similar high apnea and hypopnea indices were also noted in prehypertensive spontaneously hypertensive (SH) rats, which are known to exhibit CB hyperactivity. We identified the gaseous molecule hydrogen sulfide (H2S) as the major effector molecule driving apneas. Genetic ablation of the H2S-synthesizing enzyme cystathionine-γ-lyase (CSE) normalized breathing in HO-2-/- mice. Pharmacologic inhibition of CSE with l-propargyl glycine prevented apneas in both HO-2-/- mice and SH rats. These observations demonstrate that dysregulated CO and H2S signaling in the CB leads to apneas and suggest that CSE inhibition may be a useful therapeutic intervention for preventing CB-driven sleep apnea.

Prevalence and Characteristics of Restless Legs Syndrome in Korean Adults: A Study in Two Independent Samples of the General Population.

BACKGROUND: Restless legs syndrome (RLS) is a common sleep disorder, although it has a low prevalence in Asian populations. However, the reported RLS prevalence in -Korean adults is mostly 4.5-12.1%, which is higher than that reported in other Asian populations. This study aimed to diagnose RLS and exclude mimicking conditions in 2 independent samples of Korean adults, and to compare its prevalence to that from previous studies performed in Asian countries. METHODS: Study populations included a (1) nationwide stratified random sample (n = 2,824; age 19-79 years) and (2) community-based cohort (n = 2,685; age 47-79 years). We applied the Cambridge-Hopkins diagnostic questionnaire to diagnose RLS and differentiate it from RLS mimics. Sleep-related symptoms, mood, and medical conditions were compared between the RLS and non-RLS groups. Prior studies of the RLS prevalence in Asia were systematically reviewed and compared to our findings. RESULTS: The adjusted RLS prevalence was 0.4 and 1.3% in populations 1 and 2, respectively. In both populations, subjects with RLS had more depression. The prevalence of RLS mimics was 5.1 and 2.6%, in populations 1 and 2, respectively. The RLS prevalence in Asia was higher when RLS was defined by the presence of essential clinical features and lower when a differential diagnosis was additionally implemented. CONCLUSIONS: The RLS prevalence in Korean adults considering RLS mimics is comparable to that in adults from other Asian countries (< 2%). The reported RLS prevalence varies depending on the diagnostic method employed.