Notes

Multifocality just isn't linked to even worse emergency within intermittent pancreatic neuroendocrine tumors.
To evaluate the psychometric properties and validity of the updated version of the Dutch multidimensional Comprehensive Psychosocial Screening Instrument in patients with coronary heart disease and the general population, based upon guideline recommendations from the European Society for Cardiology.

678 participants (M
=48.2, SD=16.8; 46% male) of the Dutch general population and 312 cardiac patients (M
=65.9, SD=9.9; 77% male) who recently received percutaneous coronary intervention completed the Comprehensive Psychosocial Screening Instrument and validated questionnaires for depression (PHQ-9), anxiety (GAD-7), Type D personality (DS14), hostility (CMHS), anger (STAS-T), trauma (SRIP), and chronic work and family stress (ERI, MMQ-6).

Confirmatory factor analysis (CFA) confirmed that the eight screened risk factors were best measured as separate entities, rather than broader indications of distress. Inter-instrument agreement, assessed with the intraclass coefficient (ICC) and the screening accuracy indicators (receiving operator characteristic [ROC] curves, sensitivity, specificity, and the positive and negative predictive values [PPV; NPV]) were good for most screened risk factors. PPV was low in low prevalence risk factors like anxiety, trauma, and depression.

Overall, the current version of the Comprehensive Psychosocial Screening Instrument has an acceptable performance in both populations, with a fair to excellent level of agreement with established full questionnaires. Besides a few suggestions for further refinement, the screener may be implemented in primary care and cardiological practice.
Overall, the current version of the Comprehensive Psychosocial Screening Instrument has an acceptable performance in both populations, with a fair to excellent level of agreement with established full questionnaires. Besides a few suggestions for further refinement, the screener may be implemented in primary care and cardiological practice.Müller glia, a pillar of metabolic, volume regulatory and immune/inflammatory signaling in the mammalian retina, are among the earliest responders to mechanical stressors in the eye. Ocular trauma, edema, detachment and glaucoma evoke early inflammatory activation of Müller cells yet the identity of their mechanotransducers and signaling mechanisms downstream remains unknown. Here, we investigate expression of genes that encode putative stretch-activated calcium channels (SACs) in mouse Müller cells and study their responses to dynamical tensile loading in cells loaded with a calcium indicator dye. Transcript levels in purified glia were Trpc1>Piezo1>Trpv2>Trpv4>>Trpv1>Trpa1. Cyclic radial deformation of matrix-coated substrates produced dose-dependent increases in [Ca2+]i that were suppressed by the TRPV4 channel antagonist HC-067047 and by ablation of the Trpv4 gene. Stretch-evoked calcium responses were also reduced by knockdown and pharmacological inhibition of TRPC1 channels whereas the TRPV2 inhibitor tranilast had no effect. These data demonstrate that Müller cells are intrinsically mechanosensitive, with the response to tensile loading mediated through synergistic activation of TRPV4 and TRPC1 channels. Coupling between mechanical stress and Müller Ca2+ homeostasis has treatment implications, since many neuronal injury paradigms in the retina involve calcium dysregulation associated with inflammatory and immune signaling.Graph classification aims to predict the property of the whole graph, which has attracted growing attention in the graph learning community. This problem has been extensively studied in the literature of both graph convolutional networks and graph kernels. Graph convolutional networks can learn effective node representations via message passing to mine graph topology in an implicit way, whereas graph kernels can explicitly utilize graph structural knowledge for classification. Due to the scarcity of labeled data in real-world applications, semi-supervised algorithms are anticipated for this problem. In this paper, we propose Graph Harmonic Neural Network (GHNN) which combines the advantages of both worlds to sufficiently leverage the unlabeled data, and thus overcomes label scarcity in semi-supervised scenarios. Specifically, our GHNN consists of a graph convolutional network (GCN) module and a graph kernel network (GKN) module that explore graph topology information from complementary perspectives. To fully leverage the unlabeled data, we develop a novel harmonic contrastive loss and a harmonic consistency loss to harmonize the training of two modules by giving priority to high-quality unlabeled data, thereby reconciling prediction consistency between both of them. In this manner, the two modules mutually enhance each other to sufficiently explore the graph topology of both labeled and unlabeled data. Extensive experiments on a variety of benchmarks demonstrate the effectiveness of our approach over competitive baselines.There is a significant challenge in global health and development research that pivots on the difficulties of delivering (cost-)effective treatments or interventions that are scalable andtransferable across settings. That is, how does one deliver "true effects", proven treatments, into new settings? This is often addressed in pragmatic trials or implementation research in which one makes adjustments to the delivery of the treatment to ensure that it works here and there. In this critical analytical review, we argue that the approach mis-characterises the cause-effect relationship and fails to recognise the local, highly contextual nature of what it means to say an intervention "works". We use an ongoing randomised controlled trial (RCT)-an informal settlement redevelopment intervention in Indonesia and Fiji to reduce human exposure to pathogenic faecal contamination-as a vehicle for exploring the ideas and implications of identifying interventions that work in global health and development. We describe the highly contextualised features of the research and the challenges these would pose in attempts to generalise the results. In other words, we detail that which is frequently elided from most RCTs. As our critical lens, we us the work of American philosopher, Nancy Cartwright, who argued that research produces dappled regions of causal insights-lacunae against a backdrop of causal ignorance. Rather than learn about a relationship between a treatment and an outcome, we learn that in the right sort of context, a treatment reliably produces a particular outcome. Moving a treatment from here to there becomes, therefore, something of an engineering exercise to ensure the right factors (or "shields") are in place so the cause-effect is manifest. As a consequence, one cannot assume that comparative effectiveness or cost-effectiveness would be maintained.
Establishing the diagnosis of epilepsy can be challenging if interictal epileptic discharges (IEDs) or seizures are undetectable. Many individuals with epilepsy experience sleep disturbances. A reduced percentage of REM sleep (REM%) has been observed following seizures. We aimed to assess differences of REM% in individuals with epilepsy in comparison with differential diagnoses.

We performed a retrospective, monocentric, two-armed case-control study with 128 age-matched individuals who underwent ≥72 hours of continuous video-EEG monitoring at our epilepsy monitoring unit (EMU) for diagnostic evaluation. We assessed REM% on the first and last night of EMU admission. Logistic regressions models were used to evaluate the predictive value of REM%.

We included 64 individuals diagnosed with epilepsy and 64 with a differential diagnosis. REM% in the epilepsy group was significantly lower [12.2% (±4.7) vs. 17.2% (±5.2), p<0.001]. We found no significant influence of sex, age, anti-seizure, or other medicatioREM% as a biomarker should be evaluated in prospective, multicentric trials.
Postictal generalized EEG suppression (PGES) has been suggested as a pathophysiological hallmark for sudden unexpected death in epilepsy (SUDEP). We aimed to characterize the clinical determinants for PGES occurrence after generalized convulsive seizures (GCS).

We systematically searched Pubmed, Embase and Medline databases up to 30 August 2021. Eligibility screening, data extraction, and quality assessment of the retrieved articles were conducted by two independent reviewers. Studies reporting potential risk factors of PGES occurrence in GCS were included for subsequent meta-analysis and PGES was defined as a generalized EEG attenuation of any duration >1s below 10μV, immediately or within 30s after an ictal EEG pattern has terminated. A fixed-effects model was applied when the heterogeneity is low (I
values < 50%). Otherwise, a random-effects model was used (I
values ≥ 50%). We assessed the odds ratio (OR) as outcome measure for dichotomous variables and the STD Mean Difference (SMD) for conti1.59; 95%CI, 0.80 to 3.17; p=0.184).

The current study informed that PGES is common after GCS. Early identification should be considered among individuals with GCS at high risk of PGES through clinical screening. Further studies with larger sample size are required for individualized evaluation of the risk of PGES in GCS and more effort is needed to further evaluate the risk of SUDEP.
The current study informed that PGES is common after GCS. Early identification should be considered among individuals with GCS at high risk of PGES through clinical screening. Further studies with larger sample size are required for individualized evaluation of the risk of PGES in GCS and more effort is needed to further evaluate the risk of SUDEP.The relationship between the maternal endocrine environment and late embryonic mortality (> 28 d of gestation) in cattle is poorly defined. A definitive rise and alterations in secretion patterns of prostaglandin F2α (PGF2α) concentration without luteal regression is a trademark of this period. The objective was to evaluate whether consecutively induced PGF2α pulses would alter steroid hormone production and luteal blood perfusion potentially influencing pregnancy success. Pregnant beef cows (n = 12) were selected to receive either an oxytocin injection (OT, n = 8) or saline injection (CON, n = 4) on d 30 and 31 of gestation to stimulate sequential prostaglandin releases 24 h apart. Blood samples were collected every 30 min for 1 h before and continuing for 4 h post oxytocin administration. Luteal blood perfusion was measured via Doppler ultrasound at the beginning and end of the OT challenge. Danirixin manufacturer Concentrations of prostaglandin F2α metabolite (PGFM) were quantified to show effectiveness of the treatment while concentrations of progesterone, estradiol and pregnancy-associated glycoproteins (PAG) were measured to examine the effect of PGF2α release. Control animals exhibited no changes in any quantified hormone and an expected numerical increase in circulating PAG concentrations. Peak concentrations of PGFM in OT cows were observed 2 h post OT administration and concentrations returned to basal levels by the end of the sampling period. Peak concentrations of PGFM were decreased on d 31 compared to d 30. Following OT administration, progesterone and estradiol concentrations did not change in response to PGF2α release but were decreased on d 31 compared to d 30. There were no changes in luteal blood perfusion in response to PGF release on d 30 or d 31. Repeated PGF2α release may alter steroid hormone production; however, it does not negatively affect pregnancy status during the transition between early and late embryonic development.
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