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An artificial intelligence (AI) algorithm for prostate cancer detection and grading was developed for clinical diagnostics on biopsies. The study cohort included 4221 scanned slides from 872 biopsy sessions at the HUS Helsinki University Hospital during 2016–2017 and a subcohort of 126 patients treated by robot-assisted radical prostatectomy (RALP) during 2016–2019. In the validation cohort (n = 391), the model detected cancer with a sensitivity of 98% and specificity of 98% (weighted kappa 0.96 compared with the pathologist's diagnosis). Algorithm-based detection of the grade area recapitulated the pathologist's grade group. The area of AI-detected cancer was associated with extra-prostatic extension (G5 OR: 48.52; 95% CI 1.11–8.33), seminal vesicle invasion (cribriform G4 OR: 2.46; 95% CI 0.15–1.7; G5 OR: 5.58; 95% CI 0.45–3.42), and lymph node involvement (cribriform G4 OR: 2.66; 95% CI 0.2–1.8; G5 OR: 4.09; 95% CI 0.22–3). Algorithm-detected grade group 3–5 prostate cancer depicted increased risk for biochemical recurrence compared with grade groups 1–2 (HR: 5.91; 95% CI 1.96–17.83). This study showed that a deep learning model not only can find and grade prostate cancer on biopsies comparably with pathologists but also can predict adverse staging and probability for recurrence after surgical treatment. [ABSTRACT FROM AUTHOR]

d-metal oxides play a crucial role in numerous technological applications and show a great variety of magnetic properties. We have systematically investigated the structural properties, magnetic ground states, and fundamental electronic properties of 100 binary d-metal oxides using hybrid density functional methods and localized basis sets composed of Gaussian-type functions. The calculated properties are compared with experimental information in all cases where experimental data are available. The used PBE0 hybrid density functional method describes the structural properties of the studied d-metal oxides well, except in the case of molecular oxides with weak intermolecular forces between the molecular units. Empirical D3 dispersion correction does not improve the structural description of the molecular oxides. We provide a database of optimized geometries and magnetic ground states to facilitate future studies on the more complex properties of the binary d-metal oxides. [ABSTRACT FROM AUTHOR]

Shift workers are at increased risk of health problems. Effective preventive measures are needed to reduce the unfavourable effects of shift work. In this study we explored whether use of digital participatory working time scheduling software improves employee well-being and perceived workability by analysing an observational cohort study as a pseudo-experiment. Participants of the Finnish Public Sector cohort study with payroll records available between 2015 and 2019 were included (N = 2427). After estimating the propensity score of using the participatory working time scheduling software on the baseline characteristics using multilevel mixed-effects logistic regression and assigning inverse probability of treatment weights for each participant, we used generalised linear model to estimate the effect of using the participatory working time scheduling software on employees' control over scheduling of shifts, perceived workability, self-rated health, work-life conflict, psychological distress and short sleep (≤ 6 h). During a 2-year follow-up, using the participatory working time scheduling software reduced the risk of employees' low control over scheduling of shifts (risk ratio [RR] 0.34; 95% CI 0.25–0.46), short sleep (RR 0.70; 95% CI 0.52–0.95) and poor workability (RR 0.74; 95% CI 0.55–0.99). The use of the software was not associated with changes in psychological distress, self-rated health and work-life conflict. In this observational study, we analysed as a pseudo-experiment, the use of participatory working time scheduling software was associated with increased employees' perceived control over scheduling of shifts and improved sleep and self-rated workability. [ABSTRACT FROM AUTHOR]

Polymer foams are widely used in several fields such as thermal insulation, acoustics, automotive, and packaging. The most widely used polymer foams are made of polyurethane, polystyrene, and polyethylene but environmental awareness is boosting interest towards alternative bio-based materials. In this study, the suitability of bio-based thermoplastic cellulose palmitate for extrusion foaming was studied. Isobutane, carbon dioxide (CO2), and nitrogen (N2) were tested as blowing agents in different concentrations. Each of them enabled cellulose palmitate foam formation. Isobutane foams exhibited the lowest density with the largest average cell size and nitrogen foams indicated most uniform cell morphology. The effect of die temperature on foamability was further studied with isobutane (3 wt%) as a blowing agent. Die temperature had a relatively low impact on foam density and the differences were mainly encountered with regard to surface quality and cell size distribution. This study demonstrates that cellulose palmitate can be foamed but to produce foams with greater quality, the material homogeneity needs to be improved and researched further. [ABSTRACT FROM AUTHOR]

Epitranscriptomic modifications in RNA can dramatically alter the way our genetic code is deciphered. Cells utilize these modifications not only to maintain physiological processes, but also to respond to extracellular cues and various stressors. Most often, adenosine residues in RNA are targeted, and result in modifications including methylation and deamination. Such modified residues as N-6-methyl-adenosine (m6A) and inosine, respectively, have been associated with cardiovascular diseases, and contribute to disease pathologies. The Ischemic Heart Disease Epitranscriptomics and Biomarkers (IHD-EPITRAN) study aims to provide a more comprehensive understanding to their nature and role in cardiovascular pathology. The study hypothesis is that pathological features of IHD are mirrored in the blood epitranscriptome. The IHD-EPITRAN study focuses on m6A and A-to-I modifications of RNA. Patients are recruited from four cohorts: (I) patients with IHD and myocardial infarction undergoing urgent revascularization; (II) patients with stable IHD undergoing coronary artery bypass grafting; (III) controls without coronary obstructions undergoing valve replacement due to aortic stenosis and (IV) controls with healthy coronaries verified by computed tomography. The abundance and distribution of m6A and A-to-I modifications in blood RNA are charted by quantitative and qualitative methods. Selected other modified nucleosides as well as IHD candidate protein and metabolic biomarkers are measured for reference. The results of the IHD-EPITRAN study can be expected to enable identification of epitranscriptomic IHD biomarker candidates and potential drug targets. [ABSTRACT FROM AUTHOR]

The increasing environmental awareness is driving towards novel sustainable high-performance materials applicable for future manufacturing technologies like additive manufacturing (AM). Cellulose is abundantly available renewable and sustainable raw material. This work focused on studying the properties of thermoplastic cellulose-based composites and their properties using injection molding and 3D printing of granules. The aim was to maximize the cellulose content in composites. Different compounds were prepared using cellulose acetate propionate (CAP) and commercial cellulose acetate propionate with plasticizer (CP) as polymer matrices, microcellulose (mc) and novel cellulose-ester additives; cellulose octanoate (C8) and cellulose palmitate (C16). The performance of compounds was compared to a commercial poly(lactic acid)-based cellulose fiber containing composite. As a result, CP-based compounds had tensile and Charpy impact strength properties comparable to commercial reference, but lower modulus. CP-compounds showed glass transition temperature (Tg) over 58% and heat distortion temperature (HDT) 12% higher compared to reference. CAP with C16 had HDT 82.1 °C. All the compounds were 3D printable using granular printing, but CAP compounds had challenges with printed layer adhesion. This study shows the potential to tailor thermoplastic cellulose-based composite materials, although more research is needed before obtaining all-cellulose 3D printable composite material with high-performance. [ABSTRACT FROM AUTHOR]

Low back pain (LBP) patients undergoing lumbar spine decompression surgery (LSDS) often suffer from multi-comorbidity and experience high work disability. This study aimed to identify diagnosis-specific work disability patterns in all LBP-patients before and after LSDS during 2008-2010, that were aged 19-60 years and living in Sweden ( n = 10,800) and compare these patterns to LBP-patients without LSDS ( n = 109,179), and to matched individuals without LBP ( n = 472,191). Work disability days (long-term sickness absence (LTSA), disability pension (DP)) during the three years before to three years after the cohort's entry date were identified by generalised estimating equations. LBP-patients undergoing LSDS had higher overall work disability during the three years following surgery (LTSA: 23.6%, DP: 6.3%) than LBP-patients without LSDS (LTSA: 19.5%, DP: 5.9%), and those without LBP (LTSA: 7.9%, DP: 1.7%). Among patients undergoing LSDS, the prevalence of work disability due to dorsopathies increased from 20 days three years before surgery to 70 days in the year after and attenuated to 30 days in the third year following surgery. Work disability for other diagnoses remained stable at a low level in this group (<10 days annually). LBP-patients undergoing LSDS have an unfavourable long-term work disability prognosis, primarily due to dorsopathies. Decompression surgery seemed to restrict further inclines in work disability in the long run.