Psychological and sleep-related functioning among women with unsettled infants in Victoria, Australia: a cross-sectional study.

Objective: To identify (a) clinical symptom profiles based on psychological and sleep-related functioning among women admitted to a residential early parenting service (REPS) and (b) factors associated with membership of profile groups. Background: Depression and anxiety are common among women with unsettled infants; less is known about other indicators of psychological distress and about maternal sleep. Methods: Women admitted to a REPS during a 5-month period completed validated measures of depression, anxiety, stress, irritability, alcohol use, fatigue, sleepiness and sleep quality. Latent class analysis was used to identify symptom profiles. Factors significantly associated with class membership were identified. Results: Surveys were completed by 167/380 women. Scores on all measures were statistically significantly poorer than community norms. Two classes were identified, characterised by high versus low psychological distress. Mean scores on measures of fatigue, sleepiness and sleep quality were high in both classes. High psychological distress was associated with having previous mental health problems and an unmet need for emotional support. Conclusion: Fatigue and poor sleep quality are universal among women admitted to REPS. Health services providing assistance with unsettled infant behaviour should include strategies to improve maternal sleep, and encourage social interaction among women to protect against social isolation.

Adherence to the Mediterranean diet and risk of lung cancer in the Netherlands Cohort Study.

The evidence on a cancer-protective effect of the Mediterranean diet (MD) is still limited. Therefore, we investigated the association between MD adherence and lung cancer risk. Data were used from 120 852 participants of the Netherlands Cohort Study (NLCS), aged 55-69 years. Dietary habits were assessed at baseline (1986) using a validated FFQ and alternate and modified Mediterranean diet scores (aMED and mMED, respectively), including and excluding alcohol, were calculated. After 20·3 years of follow-up, 2861 lung cancer cases and 3720 subcohort members (case-cohort design) could be included in multivariable Cox regression analyses. High (6-8) v. low (0-3) aMED excluding alcohol was associated with non-significantly reduced lung cancer risks in men and women with hazard ratios of 0·91 (95 % CI 0·72, 1·15) and 0·73 (95 % CI 0·49, 1·09), respectively. aMED-containing models generally fitted better than mMED-containing models. In never smokers, a borderline significant decreasing trend in lung cancer risk was observed with increasing aMED excluding alcohol. Analyses stratified by the histological lung cancer subtypes did not identify subtypes with a particularly strong inverse relation with MD adherence. Generally, the performance of aMED and World Cancer Research Fund/American Institute for Cancer Research dietary score variants without alcohol was comparable. In conclusion, MD adherence was non-significantly inversely associated with lung cancer risk in the NLCS. Future studies should focus on differences in associations across the sexes and histological subtypes. Furthermore, exclusion of alcohol from MD scores should be investigated more extensively, primarily with respect to a potential role of the MD in cancer prevention.

A snapshot of climate drivers and temporal variation of Ixodes ovatus abundance from a giant panda living in the wild.

Ticks and tick-borne diseases have negative impacts on the health of wild animals including endangered and vulnerable species. The giant panda (Ailuropoda melanoleuca), a vulnerable and iconic flagship species, is threatened by tick infestation as well. Not only can ticks cause anemia and immunosuppression in the giant panda, but also bacterial and viral diseases. However, previous studies regarding tick infestation on giant pandas were limited in scope as case reports from sick or dead animals. In this study, an investigation focusing on the tick infestation of a reintroduced giant panda at the Daxiangling Reintroduction Base in Sichuan, China was conducted. Ticks were routinely collected and identified from the ears of the giant panda from March to September in 2021. A linear model was used to test the correlation between tick abundance and climate factors. All ticks were identified as Ixodes ovatus. Tick abundance was significantly different among months. Results from the linear model showed temperature positively correlated to tick abundance, while air pressure had a negative correlation with tick abundance. To the best of our knowledge, this study is the first reported investigation of tick species and abundance on a healthy giant panda living in the natural environment, and provides important information for the conservation of giant pandas and other species sharing the same habitat.

The growth and shape of the eyeball and crystalline lens in utero documented by fetal MR imaging.

Purpose: To study the growth model, shape, and developmental relationship of lens and eyeball, we used two-dimensional Magnetic Resonance (MR) imaging to investigate gestationally age-related changes in the selected ocular parameters in vivo. Materials and methods: We retrospectively reviewed the MR images from 126 fetuses ranging from 21 to 39 weeks' gestation. Ocular parameters on MR imaging of transverse plane were measured including lens diameter (LD), anteroposterior lens diameter (APLD), lens surface area (LS), globe diameter (GD), anteroposterior globe diameter (APGD), globe surface area (GS). The growth model of each biometric against gestational age (GA), aspect ratio of lens and globe (LD/APLD and GD/APGD), and growing relationship between the ratio of lens and globe surface area (LS/GS) were studied by statistical analysis. Results: The growth model of most biometry for gestational age is logarithmic, except for the diameter of the ocular globe (GD and APGD) showing a quadratic growth pattern. Our study showed that the lens was consistently larger in the transverse than the anteroposterior diameters during 21-39 weeks(P < 0.001). Besides, the ratio of surface area (LS/GS) was not significantly changing with GA(P = 0.4908), while the increase of LS was significantly accorded with that of GS(P < 0.001). Conclusion: The lens shape throughout fetal life may take part in the process, shape changing from vertical ellipsoid, spherical to transversal ellipsoid, based on the logarithmically increased ratio of lens transverse and anteroposterior diameters. In the meanwhile, the aspect ratio of eyeball in late fetal life may imply a gradually spherical shape during gestation. Nomogram data from this study may provide appropriate information about morphological changes in the fetal lens and the synchronous relationship between lens and eyeball.

Observed versus estimated actual trend of COVID-19 case numbers in Cameroon: A data-driven modelling.

Controlling the COVID-19 outbreak remains a challenge for Cameroon, as it is for many other countries worldwide. The number of confirmed cases reported by health authorities in Cameroon is based on observational data, which is not nationally representative. The actual extent of the outbreak from the time when the first case was reported in the country to now remains unclear. This study aimed to estimate and model the actual trend in the number of COVID -19 new infections in Cameroon from March 05, 2020 to May 31, 2021 based on an observed disaggregated dataset. We used a large disaggregated dataset, and multilevel regression and poststratification model was applied prospectively for COVID-19 cases trend estimation in Cameroon from March 05, 2020 to May 31, 2021. Subsequently, seasonal autoregressive integrated moving average (SARIMA) modeling was used for forecasting purposes. Based on the prospective MRP modeling findings, a total of about 7450935 (30%) of COVID-19 cases was estimated from March 05, 2020 to May 31, 2021 in Cameroon. Generally, the reported number of COVID-19 infection cases in Cameroon during this period underestimated the estimated actual number by about 94 times. The forecasting indicated a succession of two waves of the outbreak in the next two years following May 31, 2021. If no action is taken, there could be many waves of the outbreak in the future. To avoid such situations which could be a threat to global health, public health authorities should effectively monitor compliance with preventive measures in the population and implement strategies to increase vaccination coverage in the population.

MH2c: Characterization of major histocompatibility α-helices - an information criterion approach.

Major histocompatibility proteins share a common overall structure or peptide binding groove. Two binding groove domains, on the same chain for major histocompatibility class I or on two different chains for major histocompatibility class II, contribute to that structure that consists of two α-helices ("wall") and a sheet of eight anti-parallel beta strands ("floor"). Apart from the peptide presented in the groove, the major histocompatibility α-helices play a central role for the interaction with the T cell receptor. This study presents a generalized mathematical approach for the characterization of these helices. We employed polynomials of degree 1 to 7 and splines with 1 to 2 nodes based on polynomials of degree 1 to 7 on the α-helices projected on their principal components. We evaluated all models with a corrected Akaike Information Criterion to determine which model represents the α-helices in the best way without overfitting the data. This method is applicable for both the stationary and the dynamic characterization of α-helices. By deriving differential geometric parameters from these models one obtains a reliable method to characterize and compare α-helices for a broad range of applications. PROGRAM SUMMARY: Program title: MH2c (MH helix curves) Catalogue identifier: AELX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 327 565 No. of bytes in distributed program, including test data, etc.: 17 433 656 Distribution format: tar.gz Programming language: Matlab Computer: Personal computer architectures Operating system: Windows, Linux, Mac (all systems on which Matlab can be installed) RAM: Depends on the trajectory size, min. 1 GB (Matlab) Classification: 2.1, 4.9, 4.14 External routines: Curve Fitting Toolbox and Statistic Toolbox of Matlab Nature of problem: Major histocompatibility (MH) proteins share a similar overall structure. However, identical MH alleles which present different peptides differ by subtle conformational alterations. One hypothesis is that such conformational differences could be another level of T cell regulation. By this software package we present a reliable and systematic way to compare different MH structures to each other. Solution method: We tested several fitting approaches on all available experimental crystal structures of MH to obtain an overall picture of how to describe MH helices. For this purpose we transformed all complexes into the same space and applied splines and polynomials of several degrees to them. To draw a general conclusion which method fits them best we employed the "corrected Akaike Information Criterion". The software is applicable for all kinds of helices of biomolecules. Running time: Depends on the data, for a single stationary structure the runtime should not exceed a few seconds.

Less than one-fifth of Ethiopian children were vaccinated for measles second dose; evidence from the Ethiopian mini demographic and health survey 2019.

Ethiopia introduced the measles second dose vaccine from the routine expanded immunization program in 2018. Shreds of evidence are scarce on the measles second dose vaccination coverage and its associated factors in Ethiopia. We aimed to assess the measles second dose vaccination coverage and associated factors in Ethiopia using the recent Ethiopian Mini Demographic and Health Survey (EMDHS) 2019 data. An in-depth secondary data analysis was conducted based on the Ethiopian mini demographic and health survey 2019 data; which was a cross-sectional survey targeted on key indicators of maternal and child health. A weighted sample of 965 children was included in the analysis. A multi-level mixed effect logistics regression model was fitted. Adjusted Odds Ratio (AOR) with 95 %CI was reported for statistically significant variables. The measles second dose coverage was 12.36 % (95 %CI = 10.89, 15.44). Not vaccinated for the third dose of pentavalent vaccine (Penta 3) (AOR = 0.60, 95 %CI: 0.37, 0.95), age of the child [13 to 23 months (AOR = 2.14, 95 %CI: 1.05, 4.36), 24 to 36 months (AOR = 2.58, 95 %CI: 1.32, 5.05)], household head educational status [no education (AOR = 0.51,95 %CI: 0.26, 0.99), primary (AOR = 0.44, 95 %CI: 0.23, 0.85)], and living in south nation, nationalities and peoples region (SNNPR) (AOR = 2.83,95 %CI: 1.12, 7.11) were significantly associated with measles second dose vaccination coverage. Measles second dose vaccination coverage was low in Ethiopia. Age of the child, being vaccinated for the Penta 3, educational status of the household head, and region of residence were significant determinants of measles second dose vaccination coverage.

Artificial Intelligence-Enabled Electrocardiogram Improves the Diagnosis and Prediction of Mortality in Patients With Pulmonary Hypertension.

Background: Pulmonary hypertension is a disabling and life-threatening cardiovascular disease. Early detection of elevated pulmonary artery pressure (ePAP) is needed for prompt diagnosis and treatment to avoid detrimental consequences of pulmonary hypertension. Objectives: This study sought to develop an artificial intelligence (AI)-enabled electrocardiogram (ECG) model to identify patients with ePAP and related prognostic implications. Methods: From a hospital-based ECG database, the authors extracted the first pairs of ECG and transthoracic echocardiography taken within 2 weeks of each other from 41,097 patients to develop an AI model for detecting ePAP (PAP > 50 mm Hg by transthoracic echocardiography). The model was evaluated on independent data sets, including an external cohort of patients from Japan. Results: Tests of 10-fold cross-validation neural-network deep learning showed that the area under the receiver-operating characteristic curve of the AI model was 0.88 (sensitivity 81.0%; specificity 79.6%) for detecting ePAP. The diagnostic performance was consistent across age, sex, and various comorbidities (diagnostic odds ratio >8 for most factors examined). At 6-year follow-up, the patients predicted by the AI model to have ePAP were independently associated with higher cardiovascular mortality (HR: 3.69). Similar diagnostic performance and prediction for cardiovascular mortality could be replicated in the external cohort. Conclusions: The ECG-based AI model identified patients with ePAP and predicted their future risk for cardiovascular mortality. This model could serve as a useful clinical test to identify patients with pulmonary hypertension so that treatment can be initiated early to improve their survival prognosis.

Urban density differences in colorectal cancer screening participation and screening yield in The Netherlands.

Lower socioeconomic status has been associated with higher colorectal cancer incidence and lower participation in population-based screening with faecal immunochemical testing (FIT) but regional variations in participation may also exist. We analysed differences in participation and yield in colorectal cancer screening by urban density level. Data of all invitees to the Dutch colorectal cancer screening programme in 2014-2015 were included. Primary outcomes were participation (returning FIT), FIT positive predictive value, and screening yield (advanced neoplasia detected in invitees). Differences were explored across five levels of urban density. In total 1,873,639 screening invitees were included. FIT participation was 77.3% in the lowest versus 62.8% in the highest urban areas (RR 1.23; 95%CI 1.23-1.24). FIT positive predictive value was 58.6% in the lowest versus 55.2% in the highest urban areas (RR 1.06; 95% CI 1.04-1.09). Screening yield was also higher in the lowest (2.1%-2.3%) compared to the highest urban areas (1.8%). Compared to socioeconomic status, differences in urban density were associated with larger differences in screening participation. In conclusion, participation is lower and fewer cases of advanced neoplasia are detected in areas with a high urban density in the Dutch colorectal cancer screening programme. Differences in urban density could be used in tailoring regional strategies to target barriers in colorectal cancer screening.

Modeling of Temporal Exposure to the Ambient Environment and Eczema Severity.

Atopic eczema is a common and complex disease. Missing genetic hereditability and increasing prevalence in industrializing nations point toward an environmental driver. We investigated the temporal association of weather and pollution parameters with eczema severity. This cross-sectional clinical study was performed between May 2018 and March 2020 and is part of the Tower Hamlets Eczema Assessment. All participants had a diagnosis of eczema, lived in East London, were of Bangladeshi ethnicity, and were aged <31 years. The primary outcome was the probability of having an Eczema Area and Severity Index score > 10 after previous ambient exposure to commonly studied meteorological variables and pollutants. There were 430 participants in the groups with Eczema Area and Severity Index ≤ 10 and 149 in those with Eczema Area and Severity Index > 10. Using logistic generalized additive models and a model selection process, we found that tropospheric ozone averaged over the preceding 270 days was strongly associated with eczema severity alongside the exposure to fine particles with diameters of 2.5 µm or less (fine particulate matter) averaged over the preceding 120 days. In our models and analyses, fine particulate matter appeared to largely act in a supporting role to ozone. We show that long-term exposure to ground-level ozone at high levels has the strongest association with eczema severity.

Associations of Four sensitization patterns revealed by Latent Class Analysis with Clinical symptoms: A multi-center study of China.

Background: Because of the significant regional differences in the distribution of allergens, the relationship between anaphylaxis and allergic sensitization is complex in China. Using this large-scale epidemiologic survey, we explore the potential patterns of sensitization to common allergens in mainland China and investigate their relationship with various clinical symptoms. Method: The participants were recruited from 13 medical centers in mainland China from October 2019 to June 2021. Skin prick test (SPT) results that cover 18 common allergens were utilized to diagnose atopic sensitization. The demographic characteristics and clinical information were collected through questionnaires during routine medical follow-up. Latent class analysis (LCA) was conducted to determine the optimal sensitization patterns. The logistic regression was used to assess the associations of different sensitization patterns with allergy symptoms. Findings: A total of 1089 patients who had a positive SPT to at least one of 18 allergens were included for formal analysis. An optimal LCA model with 4 classes was obtained in this study, and the corresponding labels were as follows: Class1, house dust mite sensitization; Class2, low pollen sensitization; Class3, middle pollen sensitization; Class4, high pollen sensitization. The prevalence of different classes varied widely in geographical distribution, which was characterized by Class1 being very common in south and east as well as Class2 in north and west of China. Compared with patients in Class1, those in middle and high pollen sensitization clusters had the higher odds ratios (ORs) of allergic rhinitis and allergic conjunctivitis when controlling for other confounders. However, there was no significant difference between low pollen sensitization and house dust mite sensitization groups in the risks for various clinical performances except dermatitis. Additionally, the adjusted ORs (95% confidence interval) of allergic conjunctivitis and dermatitis for participants in pollen sensitization clusters (Class2, 3 and 4) were 1.56 (1.18, 2.06) and 1.43 (1.09, 1.88) respectively compared with those in Class1. Interpretation: In this study, we identified four sensitization clusters with specific risks of various clinical symptoms using common allergens by adopting LCA. Our findings may contribute to improved diagnosis and potential immunotherapy approaches to allergy in mainland China. Funding: This study was supported by the National Natural Science Foundation of China (81802076 and 81871736), the Guangzhou Science and Technology Foundation (202102010327), the Foundation of SKLRD (MS-2019-06 and Z-2022-09), and the Foundation of GYYY (ZH201904) and ZNSA-2020012.

Spatial variations and social determinants of life expectancy in China, 2005-2020: A population-based spatial panel modelling study.

Background: Social determinants of health (SDOH) produce a broad range of life expectancy (LE) disparities. In China, limited literatures were found to report association between SDOH and LE at ecological level during a consecutive period of time from the spatial perspectives. This study aimed to determine the existence, quantify the magnitude, and interpret the association between SDOH and LE in China. Methods: Provincial-level LE were estimated from mortality records during 2005-2020 from National Mortality Surveillance System in China. A spatial panel Durbin model was used to investigate LE associated SDOH proxies. Spatial spillover effects were introduced to interpret direct and indirect effects caused by SDOH during long-term and short-term period on LE disparities. Findings: Nationwide, LE increased from 73.1 (95% confidence interval (CI): 71.3, 74.4) years to 77.7 (95%CI: 76.5, 78.7) years from 2005 to 2020. Unequally spatial distribution of LE with High-High clustering in coastal areas and Low-Low clustering in western regions were observed. Locally, it was estimated that SDOH proxies statistically significant related to an increase of LE, including GDP (coefficient: 0.02, 95%CI: 0.00, 0.03), Gini index (coefficient: 2.35, 95%CI: 1.82, 2.88), number of beds in health care institutions (coefficient: 0.02, 95%CI: 0.00, 0.05) and natural growth rate of resident population (coefficient: 0.02, 95%CI: 0.01, 0.02). Direct and indirect effects decomposition during long-term and short-term of LE associated SDOH proxies demonstrated that GDP, urbanization rate, unemployment rate, education attainment, Gini index, number of beds in health care institutions, sex ratio, gross dependence ratio and natural growth rate of resident population not only affected local LE, but also exerted spatial spillover effects towards geographical neighbors. Interpretation: Spatial variations of LE existed at provincial-level in China. SDOH regarding socioeconomic development and equity, healthcare resources, as well as population characteristics not only affected LE disparities at local scale but also among nearby provinces. Externalities of policy of those SDOH proxies should be took into consideration to promote health equity nationally. Comprehensive approaches on the basis of population strategy should be consolidated to optimize supportive socioeconomic environment and narrow the regional gap to reduce health disparities and increase LE. Funding: National Key Research & Development Program of China (Grant No.2018YFC1315301); Ministry of Education of China Humanities and Social Science General Program (Grant No.18YJC790138).

The efficacy profiles of concurrent chemoradiotherapy with intensity-modulated radiotherapy followed by durvalumab in patients with unresectable stage III non-small cell lung cancer: A multicenter retrospective cohort study.

Purpose: Intensity-modulated radiotherapy (IMRT) is currently used more commonly than 3-dimensional conformal radiation for definitive thoracic radiation. We examined the efficacy profiles of concurrent chemoradiotherapy (CCRT) with IMRT after durvalumab became clinically available. Methods: We reviewed the clinical records of patients with stage III non-small cell lung cancer (NSCLC) treated with CCRT and IMRT at seven centers in Japan and investigated relapse and survival from May 2018 to December 2019. The primary endpoint of this report was progression-free survival (PFS). Results: Among 107 patients enrolled in the study, 87 were sequentially administered durvalumab. From CCRT commencement, patients were followed up for a median period of 29.7 months. The median PFS at the end of the CCRT was 20.7 months. Among the 87 patients, 58 experienced disease relapses, of whom 36 (62.1 %) had distant metastases. Multivariate Cox regression analysis revealed that a favorable response to CCRT, a radiation dose ≥ 62 Gy, and stage IIIA NSCLC were associated with prolonged PFS (all P = 0.04). Multivariate logistic regression by landmark analysis revealed that mortality risk factors were durvalumab treatment duration ≤ 11.7 months, a lower maximum grade of immune-related adverse events, FEV1 < 2805 mL, and radiation dose < 62 Gy (P = 0.01, 0.01, 0.03, and 0.04, respectively). Conclusions: In patients with NSCLC receiving CCRT using IMRT, long PFS was associated with a better response to CCRT, stage IIIA NSCLC, and an increased radiation dose. The duration of durvalumab consolidation also played an essential role in the survival of patients receiving CCRT with IMRT. (250 words).

A CT-based deep learning radiomics nomogram for predicting the response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer: A multicenter cohort study.

Background: Accurate prediction of treatment response to neoadjuvant chemotherapy (NACT) in individual patients with locally advanced gastric cancer (LAGC) is essential for personalized medicine. We aimed to develop and validate a deep learning radiomics nomogram (DLRN) based on pretreatment contrast-enhanced computed tomography (CT) images and clinical features to predict the response to NACT in patients with LAGC. Methods: 719 patients with LAGC were retrospectively recruited from four Chinese hospitals between Dec 1st, 2014 and Nov 30th, 2020. The training cohort and internal validation cohort (IVC), comprising 243 and 103 patients, respectively, were randomly selected from center I; the external validation cohort1 (EVC1) comprised 207 patients from center II; and EVC2 comprised 166 patients from another two hospitals. Two imaging signatures, reflecting the phenotypes of the deep learning and handcrafted radiomics features, were constructed from the pretreatment portal venous-phase CT images. A four-step procedure, including reproducibility evaluation, the univariable analysis, the LASSO method, and the multivariable logistic regression analysis, was applied for feature selection and signature building. The integrated DLRN was then developed for the added value of the imaging signatures to independent clinicopathological factors for predicting the response to NACT. The prediction performance was assessed with respect to discrimination, calibration, and clinical usefulness. Kaplan-Meier survival curves based on the DLRN were used to estimate the disease-free survival (DFS) in the follow-up cohort (n = 300). Findings: The DLRN showed satisfactory discrimination of good response to NACT and yielded the areas under the receiver operating curve (AUCs) of 0.829 (95% CI, 0.739-0.920), 0.804 (95% CI, 0.732-0.877), and 0.827 (95% CI, 0.755-0.900) in the internal and two external validation cohorts, respectively, with good calibration in all cohorts (p > 0.05). Furthermore, the DLRN performed significantly better than the clinical model (p < 0.001). Decision curve analysis confirmed that the DLRN was clinically useful. Besides, DLRN was significantly associated with the DFS of patients with LAGC (p < 0.05). Interpretation: A deep learning-based radiomics nomogram exhibited a promising performance for predicting therapeutic response and clinical outcomes in patients with LAGC, which could provide valuable information for individualized treatment.

Driving effect of multiplex factors on human brucellosis in high incidence region, implication for brucellosis based on one health concept.

Brucellosis is a typical zoonosis driven by various risk factors, including environmental ones. The present study aimed to explore the driving effect of environmental factors on human brucellosis in a high incidence rate area, which provides understanding and implications in mitigating disease transmission risk in a multi-system between the human-animal-environment interface for preventing and controlling brucellosis based on the One Health concept. Based on the monthly time series data of human brucellosis and environmental variables, a Seasonal Autoregressive Integrated Moving Average Model with explanatory variables (SARIMAX) was applied to assess the association between environmental indicators and human brucellosis incidence (IHB). The results indicated distinct seasonal fluctuation during the study duration, tending to climb from April to August. Atmospheric pressure, precipitation, relative humidity, mean temperature, sunshine duration, and normalized difference vegetation index significantly drive IHB. Moreover, the well-fitting and predicting capability were performed and assessed in the optimal model was the SARIMAX (0,1,1) (0,1,1)12 model with the normalized difference vegetation index (ß = 0.349, P = 0.036) and mean temperature (ß = 0.133, P = 0.046) lagged in 6 months, and the precipitation lagged in 1 month (ß = -0.090, P = 0.004). Our study suggests the association between environmental risk factors and human brucellosis infection, which can be contributed to mitigating the transmission risk in the environmental drivers in a multi-system interface through comprehensive prevention and intervention strategies based on the One Health concept.

Case study: Targeted RNA-sequencing of aged formalin-fixed paraffin-embedded samples for understanding chemical mode of action.

Formalin-fixed paraffin-embedded (FFPE) samples are the only remaining biological archive for many toxicological and clinical studies, yet their use in genomics has been limited due to nucleic acid damage from formalin fixation. Older FFPE samples with highly degraded RNA pose a particularly difficult technical challenge. Probe-based targeted sequencing technologies show promise in addressing this issue but have not been directly compared to standard whole-genome RNA-Sequencing (RNA-Seq) methods. In this study, we evaluated dose-dependent transcriptional changes from paired frozen (FROZ) and FFPE liver samples stored for over 20 years using targeted resequencing (TempO-Seq) and whole-genome RNA-Seq methods. Samples were originally collected from male mice exposed to a reference chemical (dichloroacetic acid, DCA) at 0, 198, 313, and 427 mg/kg-day (n = 6/dose) by drinking water for 6 days. TempO-Seq showed high overlap in differentially expressed genes (DEGs) between matched FFPE and FROZ samples and high concordance in fold-change values across the two highest dose levels of DCA vs. control (R2 ≥ 0.94). Similarly, high concordance in fold-change values was observed between TempO-Seq FFPE and RNA-Seq FROZ results (R2 ≥ 0.92). In contrast, RNA-Seq FFPE samples showed few overlapping DEGs compared to FROZ RNA-Seq (≤5 for all dose groups). Modeling of DCA-dependent changes in gene sets identified benchmark doses from TempO-Seq FROZ and FFPE samples within 1.4-fold of RNA-Seq FROZ samples (93.9 mg/kg-d), whereas RNA-Seq FFPE samples were 3.3-fold higher (310.3 mg/kg-d). This work demonstrates that targeted sequencing may provide a more robust method for quantifying gene expression profiles from aged archival FFPE samples.

Violations of proportional hazard assumption in Cox regression model of transcriptomic data in TCGA pan-cancer cohorts.

BACKGROUND: Cox proportional hazard regression (CPH) model relies on the proportional hazard (PH) assumption: the hazard of variables is independent of time. CPH has been widely used to identify prognostic markers of the transcriptome. However, the comprehensive investigation on PH assumption in transcriptomic data has lacked. RESULTS: The whole transcriptomic data of the 9,056 patients from 32 cohorts of The Cancer Genome Atlas and the 3 lung cancer cohorts from Gene Expression Omnibus were collected to construct CPH model for each gene separately for fitting the overall survival. An average of 8.5% gene CPH models violated the PH assumption in TCGA pan-cancer cohorts. In the gene interaction networks, both hub and non-hub genes in CPH models were likely to have non-proportional hazards. Violations of PH assumption for the same gene models were not consistent in 5 non-small cell lung cancer datasets (all kappa coefficients < 0.2), indicating that the non-proportionality of gene CPH models depended on the datasets. Furthermore, the introduction of log(t) or sqrt(t) time-functions into CPH improved the performance of gene models on overall survival fitting in most tumors. The time-dependent CPH changed the significance of log hazard ratio of the 31.9% gene variables. CONCLUSIONS: Our analysis resulted that non-proportional hazards should not be ignored in transcriptomic data. Introducing time interaction term ameliorated performance and interpretability of non-proportional hazards of transcriptome data in CPH.

Subjective well-being predicts health behavior in a population-based 9-years follow-up of working-aged Finns.

The cross-sectional association between measures of subjective well-being (SWB) and various health behaviors is well-established. In this 9-year (2003-2012) follow-up study, we explored how a composite indicator of SWB (range 4-20) with four items (interest, happiness, and ease in life, as well as perceived loneliness) predicts a composite health behavior measure (range 0-4) including dietary habits, physical activity, alcohol consumption, and smoking status. Study subjects (n = 10,855) originated from a population-based random sample of working-age Finns in the Health and Social Support study (HeSSup). According to linear regression analysis, better SWB predicted better health behavior sum score with a ß = 0.019 (p < 0.001) with a maximum effect of 0.3 points after adjusting for age (p = 0.038), gender (p < 0.001), education (p = 0.55), baseline self-reported diseases (p = 0.020), baseline health behavior (ß = 0.49, p < 0.001), and the interaction between SWB and education (p < 0.001). The results suggest that SWB has long-term positive effect on health behavior. Thus, interventions aiming at health behavioral changes could benefit from taking into account SWB and its improvement in the intervention.

Discovering different profiles in the dynamics of depression based on real-time monitoring of mood: a first exploration.

BACKGROUND: Although depression is typically characterized by a persistent depressed mood, mood dynamics do seem to vary across a depressed population. Heterogeneity of mood variability (magnitude of changes) and emotional inertia (speed at which mood shifts) is seen in clinical practice. However, studies investigating the heterogeneity of these mood dynamics are still scarce. The aim of the present study is to explore different distinctive profiles in real-time monitored mood dynamics among depressed persons. METHODS: After completing baseline measures, mildly-to-moderately depressed persons (n = 37) were prompted to rate their current mood (1-10 scale) on their smartphones, 3 times a day for 7 consecutive days. Latent profile analyses were applied to identify profiles based on average mood, variability of mood and emotional inertia as reported by the participants. RESULTS: Two profiles were identified in this sample. The overwhelming majority of the sample belonged to profile 1 (n = 31). Persons in profile 1 were characterized by a mood just above the cutoff for positive mood (M = 6.27), with smaller mood shifts (lower variability [SD = 1.05]) than those in profile 2 (n = 6), who displayed an overall negative mood (M = 4.72) and larger mood shifts (higher variability [SD = 1.95]) but at similar speed (emotional inertia) (AC = 0.19, AC = 0.26, respectively). CONCLUSIONS: The present study provides preliminary indications for patterns of average mood and mood variability, but not emotional inertia, among mildly-to-moderately depressed persons.

Identification of Classes of Functioning Trajectories and Their Predictors in Individuals With Spinal Cord Injury Attending Initial Rehabilitation in Switzerland.

OBJECTIVES: To identify classes of functioning trajectories in individuals with spinal cord injury (SCI) undergoing initial rehabilitation after injury and to examine potential predictors of class membership to inform clinical planning of the rehabilitation process. DESIGN: Longitudinal analysis of the individual's rehabilitation stay using data from the Inception Cohort of the Swiss Spinal Cord Injury Cohort Study (SwiSCI). SETTING: Initial rehabilitation in specialized centers in Switzerland. PARTICIPANTS: Individuals with newly acquired SCI (N=748; mean age, 54.66±18.38y) who completed initial rehabilitation between May 2013 and September 2019. The cohort was primarily composed of men (67.51%), persons with paraplegia (56.15%), incomplete injuries (67.51%), and traumatic etiologies (55.48%). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Functioning was operationalized with the interval-based sum score of the Spinal Cord Independence Measure version III (SCIM III). For each individual, the SCIM III sum score was assessed at up to 4 time points during rehabilitation stay. The corresponding time of assessment was recorded by the difference in days between the SCIM III assessment and admission to the rehabilitation program. RESULTS: Latent process mixed model analysis revealed 4 classes of functioning trajectories within the present sample. Class-specific predicted mean functioning trajectories describe stable high functioning (n=307; 41.04%), early functioning improvement (n=39; 5.21%), moderate functioning improvement (n=287; 38.37%), and slow functioning improvement (n=115; 15.37%), respectively. Out of 12 tested factors, multinomial logistic regression showed that age, injury level, injury severity, and ventilator assistance were robust predictors that could distinguish between identified classes of functioning trajectories in the present sample. CONCLUSIONS: The current study establishes a foundation for future research on the course of functioning of individuals with SCI in initial rehabilitation by identifying classes of functioning trajectories. This supports the development of specifically tailored rehabilitation programs and prediction models, which can be integrated into clinical rehabilitation planning.