The dauer diapause stage in C. elegans is a non-feeding alternative to the L3 larval stage that is highly resistant to harsh environmental conditions. The decision to enter dauer is a two-step process. First, L1 larvae encounter adverse conditions such as lack of food or overcrowding and decide to enter the L2d rather than the L2 stage. Second, L2d worms that continue to experience disadvantageous conditions decide to enter dauer instead of L3. Here, we have used RNA-seq to characterize the transcriptional response to a cocktail of dauer-inducing ascaroside pheromones at the late L1 stage as worms enter the L2d phase. We find that, in response to ascarosides, C. elegans L1 larvae preparing to enter the L2d stage begin upregulating genes involved in stress response and downregulating genes associated with growth and metabolism.The function of the budding yeast YML018C protein remains to be determined. High-throughput studies have reported that the YML018C protein localizes to the vacuolar membrane and physically interacts with the autophagy-related protein Atg27p. While this evidence suggests a potential role for this uncharacterized protein in the process of autophagy, the function of this putative interaction remains uncharacterized. In this micropublication, we report our finding that the localization of the YML018C protein to the vacuolar membrane does not require Atg27p.The utility of single copy transgenic insertions in C. elegans is often limited by low expression. We examined the effects of modifying the trans-splicing signal, the Kozak ribosome binding site, the N-terminal amino acid of the reporter and the 3′ UTR sequences on the expression level of a mec-4 promoter GFP transgene. The trans-splicing signal and the 3′ UTR had most dramatic effects on expression while modifying the Kozak signal or the N-terminal amino acid had less influence on expression.Cilia are microtubule-based organelles that carry out a wide range of critical functions throughout the development of higher animals. Regardless of their type, all cilia rely on a motor-driven, bidirectional transport system known as intraflagellar transport (IFT). Of the many components of the IFT machinery, IFT20 is one of the smallest subunits. Nevertheless, IFT20 has been shown to play critical roles in the assembly of several types of mammalian cilia. Here we show that the IFT20 homolog in Caenorhabditis elegans, IFT-20, is also important for correct cilium assembly in sensory neurons. Strikingly, however, we find that IFT-20-deficient animals are able to assemble short, vestigial cilia. In spite of this, we show that practically all IFT-20-deficient animals fail to respond to environmental cues that are normally detected by cilia to modulate their behavior. Altogether, our results indicate that IFT-20 is critical for both the correct assembly and function of cilia in C. elegans.

Intraoperative neurophysiological monitoring (IONM) is the use of electrophysiological methods during certain high-risk surgeries to assess the functional integrity of nerves in real time and alert the surgeon to prevent damage. selleck chemicals llc However, the efficiency of IONM in current practice is limited by latency of verbal communications, inter-rater variability, and the subjective manner in which electrophysiological signals are described.

In an attempt to address these shortcomings, we investigate automated classification of free-running electromyogram (EMG) waveforms during IONM. We propose a hybrid model with a convolutional neural network (CNN) component and a long short-term memory (LSTM) component to better capture complicated EMG patterns under conditions of both electrical noise and movement artifacts. Moreover, a preprocessing pipeline based on data normalization is used to handle classification of data from multiple subjects. To investigate model robustness, we also analyze models under different methods for processing of artifacts.

Compared with several benchmark modeling methods, CNN-LSTM performs best in classification, achieving accuracy of 89.54% and sensitivity of 94.23% in cross-patient evaluation.

The CNN-LSTM model shows promise for automated classification of continuous EMG in IONM.

This technique has potential to improve surgical safety by reducing cognitive load and inter-rater variability.

This technique has potential to improve surgical safety by reducing cognitive load and inter-rater variability.

This study sought to compare three sensor-based wear-time estimation methods to conventional diaries for ActiGraph wGT3X-BT accelerometers worn on the non-dominant wrist in early pregnancy.

Pregnant women (n= 108) wore ActiGraph wGT3X-BT accelerometers for 7 days and recorded their device on and off times in a diary (criterion). Average daily wear-time estimates from the Troiano and Choi algorithms and the wGT3X-BT accelerometer wear sensor were compared against the diary. The Hibbing 2-regression model was used to estimate time spent in activity (during periods of device wear) for each method. Wear-time and time spent in activity were compared with multiple repeated measures ANOVAs. Bland Altman plots assessed agreement between methods.

Compared to the diary [825.5 minutes (795.1, 856.0)], the Choi [843.0 (95% CI 812.6, 873.5)] and Troiano [839.1 (808.7, 869.6)] algorithms slightly overestimated wear-time, whereas the sensor [774.4 (743.9, 804.9)] underestimated it, although only the sensor differed significantly from the diary (

< .0001). Upon adjustment for average daily wear-time, there were no statistically significant differences between the wear-time methods in regards to minutes per day of moderate to vigorous physical activity (MVPA), vigorous PA, and moderate PA. Bland Altman plots indicated the Troiano and Choi algorithms were similar to the diary and within ≤ 0.5% of each other for wear-time and MVPA.

The Choi or Troiano algorithms offer a valid and efficient alternative to diaries for the estimation daily wear-time in larger-scale studies of MVPA during pregnancy, and reduce burden for study participants and research staff.

The Choi or Troiano algorithms offer a valid and efficient alternative to diaries for the estimation daily wear-time in larger-scale studies of MVPA during pregnancy, and reduce burden for study participants and research staff.