Notes

Predictive Elements for Successful Oral Supply after having a Tryout involving External Cephalic Model: A new Retrospective Cohort Review associated with 946 Ladies.
Muscle tone is an indispensable element in motor development. Its assessment forms an integral part of the infant neurological examination. Knowledge on the prevalence of atypical tone in infancy is lacking.

To assess the prevalence of atypical muscle tone in infancy and of the most common atypical muscle tone patterns, and associations between atypical tone and perinatal risk and neurodevelopmental status.

Cross-sectional study.

1100 infants (585 boys; gestational age 39.4weeks (27.3-42.4)), 6weeks-12months corrected age, representative of the Dutch population.

Muscle tone and neurodevelopmental status were assessed with the Standardized Infant NeuroDevelopmental Assessment (SINDA). Perinatal information was obtained by questionnaire and medical records. Univariable and multivariable statistics were applied.

Ninety-two infants (8%) had atypical muscle tone in 3-4 body parts (impaired pattern), while atypical muscle tone in 1-2 body parts was observed in 50%. Isolated leg hypotonia and isolated arinically relevant pattern is associated with perinatal risk and less favourable neurodevelopmental status.Motor imagery (MI) brain-computer interface (BCI) and neurofeedback (NF) with electroencephalogram (EEG) signals are commonly used for motor function improvement in healthy subjects and to restore neurological functions in stroke patients. Generally, in order to decrease noisy and redundant information in unrelated EEG channels, channel selection methods are used which provide feasible BCI and NF implementations with better performances. Our assumption is that there are causal interactions between the channels of EEG signal in MI tasks that are repeated in different trials of a BCI and NF experiment. Therefore, a novel method for EEG channel selection is proposed which is based on Granger causality (GC) analysis. Additionally, the machine-learning approach is used to cluster independent component analysis (ICA) components of the EEG signal into artifact and normal EEG clusters. After channel selection, using the common spatial pattern (CSP) and regularized CSP (RCSP), features are extracted and with the k-nearest neighbor (k-NN), support vector machine (SVM) and linear discriminant analysis (LDA) classifiers, MI tasks are classified into left and right hand MI. The goal of this study is to achieve a method resulting in lower EEG channels with higher classification performance in MI-based BCI and NF by causal constraint. The proposed method based on GC, with only eight selected channels, results in 93.03% accuracy, 92.93% sensitivity, and 93.12% specificity, with RCSP feature extractor and best classifier for each subject, after being applied on Physionet MI dataset, which is increased by 3.95%, 3.73%, and 4.13%, in comparison with correlation-based channel selection method.Echo State Networks (ESNs) are efficient recurrent neural networks (RNNs) which have been successfully applied to time series modeling tasks. However, ESNs are unable to capture the history information far from the current time step, since the echo state at the present step of ESNs mostly impacted by the previous one. Thus, ESN may have difficulty in capturing the long-term dependencies of temporal data. In this paper, we propose an end-to-end model named Echo Memory-Augmented Network (EMAN) for time series classification. An EMAN consists of an echo memory-augmented encoder and a multi-scale convolutional learner. First, the time series is fed into the reservoir of an ESN to produce the echo states, which are all collected into an echo memory matrix along with the time steps. After that, we design an echo memory-augmented mechanism employing the sparse learnable attention to the echo memory matrix to obtain the Echo Memory-Augmented Representations (EMARs). In this way, the input time series is encoded into the EMARs with enhancing the temporal memory of the ESN. We then use multi-scale convolutions with the max-over-time pooling to extract the most discriminative features from the EMARs. Finally, a fully-connected layer and a softmax layer calculate the probability distribution on categories. Experiments conducted on extensive time series datasets show that EMAN is state-of-the-art compared to existing time series classification methods. The visualization analysis also demonstrates the effectiveness of enhancing the temporal memory of the ESN.The poultry red mite (PRM) Dermanyssus gallinae, the most common ectoparasite affecting laying hens worldwide, is difficult to control. During the period between consecutive laying cycles, when no hens are present in the layer house, the PRM population can be reduced drastically. Heating a layer house to temperatures above 45 °C for several days in order to kill PRM has been applied in Europe. The effect of such a heat treatment on the survival of PRM adults, nymphs and eggs, however, is largely unknown. To determine that effect, an experiment was executed in four layer houses. Nylon bags with ten PRM adults, nymphs or eggs were placed at five different locations, being a) inside the nest boxes, b) between two wooden boards, to simulate refugia, c) near an air inlet, d) on the floor, under approximately 1 cm of manure and e) on the floor without manure. Mite survival was measured in 6 replicates of each of these locations in each of four layer houses. After heating up the layer house, in this case with a wood pellet burning heater, the temperature of the layer house was maintained at ≥ 45 °C for at least 48 h. Thereafter, the bags were collected and the mites were assessed as being dead or alive. The eggs were assessed for hatchability. Despite a maximum temperature of only 44 °C being reached at one location, near an air inlet, all stages of PRM were dead after the heat treatment. It can be concluded that a heat treatment of layer houses between consecutive laying cycles appears to be an effective method to control PRM.COVID-19 greatly disrupted the global supply chain of nasopharyngeal swabs, and thus new products have come to market with little data to support their use. In this prospective study, 2 new 3D printed nasopharyngeal swab designs were evaluated against the standard, flocked nasopharyngeal swab for the diagnosis of COVID-19. Seventy adult patients (37 COVID-positive and 33 COVID-negative) underwent consecutive diagnostic reverse transcription polymerase chain reaction testing, with a flocked swab followed by one or two 3D printed swabs. The "Lattice Swab" (manufacturer Resolution Medical) demonstrated 93.3% sensitivity (95% CI, 77.9%-99.2%) and 96.8% specificity (83.3%-99.9%), yielding κ = 0.90 (0.85-0.96). selleck kinase inhibitor The "Origin KXG" (manufacturer Origin Laboratories) demonstrated 83.9% sensitivity (66.3%-94.6%) and 100% specificity (88.8%-100.0%), yielding κ = 0.84 (0.77-0.91). Both 3D printed nasopharyngeal swab results have high concordance with the control swab results. The decision to use 3D printed nasopharyngeal swabs during the COVID-19 pandemic should be strongly considered by clinical and research laboratories.We retrospectively evaluated whether initial procalcitonin (PCT) levels can predict early antibiotic treatment failure (ATF) in patients with gram-negative bloodstream infections (GN-BSI) caused by urinary tract infections from January 2018 to November 2019. Early ATF was defined as the following (1) hemodynamically unstable or febrile at Day 3; (2) the need for mechanical ventilation or continuous renal replacement therapy at Day 3; (3) patients who died within 3 days (date of blood culture Day 0). The study included 189 patients; 42 showed early ATF. Independent risk factors for early ATF were initial admission to the intensive care unit (odds ratio 7.735, 95% confidence interval 2.567-23.311; P less then 0.001) and PCT levels ≥30 ng/mL (odds ratio 5.413, 95% confidence interval 2.188-13.388; P less then 0.001). Antibiotic factors were not associated with early ATF. Initial PCT levels may be helpful to predict early ATF in these patients.
The association of sugar containing beverages (SCBs) with risk of breast, endometrial, ovarian and colorectal cancers is unclear. Therefore, we investigated these associations in the Canadian Study of Diet, Lifestyle, and Health.

The study population comprised an age-stratified subcohort of 3185 women and 848, 161, 91 and 243 breast, endometrial, ovarian and colorectal cancer cases, respectively. We used Cox proportional hazards regression models modified for the case-cohort design to assess the associations of SCBs with risk of the aforementioned cancers.

Compared to SCB intake in the lowest tertile, SCB intake in the highest tertile was positively associated with endometrial cancer risk (HR
= 1.58, 95 % CI = 1.08-2.33 and 1.78, 95 % CI = 1.12-2.81 for overall and Type 1 endometrial cancer, respectively) and ovarian cancer (HR
= 1.76, 95 % CI 1.09-2.83). Fruit juice intake was also positively associated with risk of Type 1endometrial (HR
= 1.63, 95 % CI = 1.03-2.60). After excluding women with diabetes or cardiovascular diseases, we also observed sugar-sweetened beverages (SSBs) intake in the highest tertile was associated with higher risk of Type 1 endometrial cancer (HR
= 1.65; 95 % CI 1.03-2.64). None of the beverages was associated with risk of breast or colorectal cancer.

We conclude that, in this cohort, relatively high SCB intake was associated with higher risk of endometrial and ovarian cancers, but not of breast or colorectal cancers. Our findings also suggest that relatively high SSB and fruit juice intake are associated with higher risk of Type 1 endometrial cancer.
We conclude that, in this cohort, relatively high SCB intake was associated with higher risk of endometrial and ovarian cancers, but not of breast or colorectal cancers. Our findings also suggest that relatively high SSB and fruit juice intake are associated with higher risk of Type 1 endometrial cancer.
Despite overall striking advances in survival of childhood liver tumors, outcomes remain poor for specific patient segments. We aimed to assess overall survival (OS) of this rare disease and evaluate the generalizability of prognostic variables included in international collaborative systems using, for the first time, harmonized clinical data from two geographically different cohorts (Greece and Moscow).

Data for children (0-14 years) with liver tumors were retrieved from two Southern-Eastern European areas (Greece; 2001-2019 and Moscow; 2012-2019). Kaplan-Meier curves were constructed, and OS values were derived from Cox proportional models controlling for study variables.

A total of 171 newly diagnosed cases (54.4% males) were included. The OS
exceeded 80% in patients <5 years, reaching 85% among 133 patients with hepatoblastoma (HBL). By contrast, children with other than HBL histology, especially hepatocellular carcinoma (HCC) had significantly worse prognosis (hazard ratio [HR]
7.09, 95% confidence intervals [CI] 2.56-19.65; HR
5.18; 95%CI 2.15-12.49). The OS
was poorer (40%-60%) in patients with extensive local, metastatic or relapsed disease. By contrast, a significantly lower risk of death was shown in case of microscopically margin-negative resection (HR 0.06, 95%CI 0.02-0.17) and liver transplantation (HR 0.12, 95% CI 0.02-0.63) compared to the non- operated group.

Outcomes of patients with liver tumors registered in two SEE areas were comparable to those reported by major collaborative trials. Ongoing clinical cancer registration could facilitate comparison of outcomes between different study groups in order to shape state of the art of treatment.
Outcomes of patients with liver tumors registered in two SEE areas were comparable to those reported by major collaborative trials. Ongoing clinical cancer registration could facilitate comparison of outcomes between different study groups in order to shape state of the art of treatment.
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