The WD40 domain of ATG16L1 is required for its non-canonical role in lipidation of LC3 at single membranes

A hallmark of macroautophagy is the covalent lipidation of LC3 and insertion into the double-membrane phagophore, which is driven by the ATG16L1/ATG5-ATG12 complex. In contrast, non-canonical autophagy is a pathway through which LC3 is lipidated and inserted into single membranes, particularly endolysosomal vacuoles during cell engulfment events such as LC3-associated phagocytosis. Factors controlling the targeting of ATG16L1 to phagophores are dispensable for non-canonical autophagy, for which the mechanism of ATG16L1 recruitment is unknown. Here we show that the WD repeat containing C-terminal domain (WD40 CTD) of ATG16L1 is essential for LC3 recruitment to endolysosomal membranes during non-canonical autophagy, but dispensable for canonical autophagy. Using this strategy to inhibit non-canonical autophagy specifically we show a reduction of MHC class II antigen presentation in dendritic cells from mice lacking the WD40 CTD. Further, we demonstrate activation of non-canonical autophagy dependent on the WD40 CTD during influenza A virus infection. This suggests dependence on WD40 CTD distinguishes between macroautophagy and non-canonical use of autophagy machinery.This research was supported by the Cambridge NIHR BRC Cell Phenotyping Hub. This work was funded by Cancer Research UK (C47718/A16337, O.F.), the Medical Research Council (RG89611, R.B.) and the BBSRC Institute Strategic Programme Gut Health and Food Safety (BB/J004529/1)

The ATG5-binding and coiled coil domains of ATG16L1 maintain autophagy and tissue homeostasis in mice independently of the WD domain required for LC3 associated phagocytosis

Macroautophagy/autophagy delivers damaged proteins and organelles to lysosomes for degradation, and plays important roles in maintaining tissue homeostasis by reducing tissue damage. The translocation of LC3 to the limiting membrane of the phagophore, the precursor to the autophagosome, during autophagy provides a binding site for autophagy cargoes, and facilitates fusion with lysosomes. An autophagy-related pathway called LC3-associated phagocytosis (LAP) targets LC3 to phagosome and endosome membranes during uptake of bacterial and fungal pathogens, and targets LC3 to swollen endosomes containing particulate material or apoptotic cells. We have investigated the roles played by autophagy and LAP in vivo by exploiting the observation that the WD domain of ATG16L1 is required for LAP, but not autophagy. Mice lacking the linker and WD domains, activate autophagy, but are deficient in LAP. The LAP −/- mice survive postnatal starvation, grow at the same rate as littermate controls, and are fertile. The liver, kidney, brain and muscle of these mice maintain levels of autophagy cargoes such as LC3 and SQSTM1/p62 similar to littermate controls, and prevent accumulation of SQSTM1 inclusions and tissue damage associated with loss of autophagy. The results suggest that autophagy maintains tissue homeostasis in mice independently of LC3-associated phagocytosis. Further deletion of glutamate E230 in the coiled-coil domain required for WIPI2 binding produced mice with defective autophagy that survived neonatal starvation. Analysis of brain lysates suggested that interactions between WIPI2 and ATG16L1 were less critical for autophagy in the brain, which may allow a low level of autophagy to overcome neonatal lethality. Abbreviations: CCD: coiled-coil domain; CYBB/NOX2: cytochrome b-245: beta polypeptide; GPT/ALT: glutamic pyruvic transaminase: soluble; LAP: LC3-associated phagocytosis; LC3: microtubule-associated protein 1 light chain 3; MEF: mouse embryonic fibroblast; NOD: nucleotide-binding oligomerization domain; NADPH: nicotinamide adenine dinucleotide phosphate; RUBCN/Rubicon: RUN domain and cysteine-rich domain containing Beclin 1-interacting protein; SLE: systemic lupus erythematosus; SQSTM1/p62: sequestosome 1; TLR: toll-like receptor; TMEM: transmembrane protein; TRIM: tripartite motif-containing protein; UVRAG: UV radiation resistance associated gene; WD: tryptophan-aspartic acid; WIPI: WD 40 repeat domain: phosphoinositide interacting

Prevalence of unplanned pregnancy and factors related to maternal-fetal attachment in Zanjan, 2017

Background: Despite the progress of family planning programs, a significant proportion of pregnancies are still unplanned which threatens the different dimensions of community health. Unplanned pregnancy affects parent's-child association. Maternal-fetal attachment provides a model for the child's mental-social function at present and in the future. Objectives: This study was conducted to determine the prevalence of unplanned pregnancy and related factors of maternal-fetal attachment in pregnant women referring to Zanjan health centers in 2017. Methods: This descriptive correlational study was part of a clinical trial that was performed on 184 pregnant women who referred to health centers for routine prenatal care from October to February 2017 in Zanjan, Iran. Using multi-stage sampling method, health centers of Zanjan were divided into three categories based on social and economic situation. Then, from each category, three centers were selected, randomly. The inclusion criteria comprised being pregnant, satisfaction to participate in the study, have at least reading and writing skills, lack of the history of obstetric complications, psychological disease and medicine use, lack of known psychological disease, lack of narcotic substances abuse, and living in Zanjan City. Data collection tool included demographic checklists and maternal-fetal attachment questionnaire, which completed in self-report method. The data of this study were analyzed by appropriate statistical tests by SPSS v.16 software. Results: Among the participants 58.2% of women had planned pregnancy, 36.4% had unplanned pregnancy, and 5.4% had unwanted pregnancy. Maternal-fetal attachment scores were significantly higher in the planned pregnancy group 84(75-93) than the unplanned pregnancy group 57(54-60) and unwanted pregnancy group 56(48-64) (P˂0.001). The highest sub-scale in the planned pregnancy group was related to the attributing characteristics and intentions. Also, the most subscale in unplanned and unwanted pregnancies related to giving of self. There was a significant relationship between age, education, socioeconomic level, number of pregnancies, number of children and contraceptive method with type of pregnancy (P˂0.001). Conclusion: Based on the results of the study, it seems that reduction in unplanned pregnancy will enhance the maternal-fetal attachment and will improve the mother role and social-psychological health of the chil

Unobtrusive cot side sleep stage classification in preterm infants using ultra-wideband radar

Background: Sleep is an important driver of development in infants born preterm. However, continuous unobtrusive sleep monitoring of infants in the neonatal intensive care unit (NICU) is challenging.Objective: To assess the feasibility of ultra-wideband (UWB) radar for sleep stage classification in preterm infants admitted to the NICU.Methods: Active and quiet sleep were visually assessed using video recordings in 10 preterm infants (recorded between 29 and 34 weeks of postmenstrual age) admitted to the NICU. UWB radar recorded all infant's motions during the video recordings. From the baseband data measured with the UWB radar, a total of 48 features were calculated. All features were related to body and breathing movements. Six machine learning classifiers were compared regarding their ability to reliably classify active and quiet sleep using these raw signals.Results: The adaptive boosting (AdaBoost) classifier achieved the highest balanced accuracy (81%) over a 10-fold cross-validation, with an area under the curve of receiver operating characteristics (AUC-ROC) of 0.82.Conclusions: The UWB radar data, using the AdaBoost classifier, is a promising method for non-obtrusive sleep stage assessment in very preterm infants admitted to the NICU

Edge Conduction in Vacuum Glazing

Vacuum glazing is a form of low-conductance double glazing using in internal vacuum between the two glass sheets to eliminate heat transport by gas conduction and convection. An array of small support pillars separates the sheets; fused solder glass forms the edge seal. Heat transfer through the glazing occurs by radiation across the vacuum gap, conduction through the support pillars, and conduction through the bonded edge seal. Edge conduction is problematic because it affects stresses in the edge region, leading to possible failure of the glazing; in addition, excessive heat transfer because of thermal bridging in the edge region can lower overall window thermal performance and decrease resistance to condensation. Infrared thermography was used to analyze the thermal performance of prototype vacuum glazings, and, for comparison, atmospheric pressure superwindows. Research focused on mitigating the edge effects of vacuum glazings through the use of insulating trim, recessed edges, and framing materials. Experimentally validated finite-element and finite-difference modeling tools were used for thermal analysis of prototype vacuum glazing units and complete windows. Experimental measurements of edge conduction using infrared imaging were found to be in good agreement with finite-element modeling results for a given set of conditions. Finite-element modeling validates an analytic model developed for edge conduction

State-of-the-art software for window energy-efficiency rating and labeling

Measuring the thermal performance of windows in typical residential buildings is an expensive proposition. Not only is laboratory testing expensive, but each window manufacturer typically offers hundreds of individual products, each of which has different thermal performance properties. With over a thousand window manufacturers nationally, a testing-based rating system would be prohibitively expensive to the industry and to consumers. Beginning in the early 1990s, simulation software began to be used as part of a national program for rating window U-values. The rating program has since been expanded to include Solar Hear Gain Coefficients and is now being extended to annual energy performance. This paper describes four software packages available to the public from Lawrence Berkeley National Laboratory (LBNL). These software packages are used to evaluate window thermal performance: RESFEN (for evaluating annual energy costs), WINDOW (for calculating a product`s thermal performance properties), THERM (a preprocessor for WINDOW that determines two-dimensional heat-transfer effects), and Optics (a preprocessor for WINDOW`s glass database). Software not only offers a less expensive means than testing to evaluate window performance, it can also be used during the design process to help manufacturers produce windows that will meet target specifications. In addition, software can show small improvements in window performance that might not be detected in actual testing because of large uncertainties in test procedures

Analysis of a Modular Autonomous Driving Architecture: The Top Submission to CARLA Leaderboard 2.0 Challenge

In this paper we present the architecture of the Kyber-E2E submission to the map track of CARLA Leaderboard 2.0 Autonomous Driving (AD) challenge 2023, which achieved first place. We employed a modular architecture for our solution consists of five main components: sensing, localization, perception, tracking/prediction, and planning/control. Our solution leverages state-of-the-art language-assisted perception models to help our planner perform more reliably in highly challenging traffic scenarios. We use open-source driving datasets in conjunction with Inverse Reinforcement Learning (IRL) to enhance the performance of our motion planner. We provide insight into our design choices and trade-offs made to achieve this solution. We also explore the impact of each component in the overall performance of our solution, with the intent of providing a guideline where allocation of resources can have the greatest impact

Week 48 resistance analyses of the once-daily, single-tablet regimen darunavir/cobicistat/emtricitabine/tenofovir alafenamide (D/C/F/TAF) in adults living with HIV-1 from the Phase III Randomized AMBER and EMERALD Trials

Darunavir/cobicistat/emtricitabine/tenofovir alafenamide (D/C/F/TAF) 800/150/200/10 mg is being investigated in two Phase III trials, AMBER (NCT02431247; treatment-naive adults) and EMERALD (NCT02269917; treatment-experienced, virologically suppressed adults). Week 48 AMBER and EMERALD resistance analyses are presented. Postbaseline samples for genotyping/phenotyping were analyzed from protocol-defined virologic failures (PDVFs) with viral load (VL) >= 400 copies/mL at failure/later time points. Post hoc analyses were deep sequencing in AMBER, and HIV-1 proviral DNA from baseline samples (VL = 3 thymidine analog-associated mutations (24% not fully susceptible to tenofovir) detected at screening. All achieved VL <50 copies/mL at week 48 or prior discontinuation. D/C/F/TAF has a high genetic barrier to resistance; no darunavir, primary PI, or tenofovir RAMs were observed through 48 weeks in AMBER and EMERALD. Only one postbaseline M184I/V RAM was observed in HIV-1 of an AMBER participant. In EMERALD, baseline archived RAMs to darunavir, emtricitabine, and tenofovir in participants with prior VF did not preclude virologic response

Unobtrusive cot side sleep stage classification in preterm infants using ultra-wideband radar

Background: Sleep is an important driver of development in infants born preterm. However, continuous unobtrusive sleep monitoring of infants in the neonatal intensive care unit (NICU) is challenging. Objective: To assess the feasibility of ultra-wideband (UWB) radar for sleep stage classification in preterm infants admitted to the NICU. Methods: Active and quiet sleep were visually assessed using video recordings in 10 preterm infants (recorded between 29 and 34 weeks of postmenstrual age) admitted to the NICU. UWB radar recorded all infant's motions during the video recordings. From the baseband data measured with the UWB radar, a total of 48 features were calculated. All features were related to body and breathing movements. Six machine learning classifiers were compared regarding their ability to reliably classify active and quiet sleep using these raw signals. Results: The adaptive boosting (AdaBoost) classifier achieved the highest balanced accuracy (81%) over a 10-fold cross-validation, with an area under the curve of receiver operating characteristics (AUC-ROC) of 0.82. Conclusions: The UWB radar data, using the AdaBoost classifier, is a promising method for non-obtrusive sleep stage assessment in very preterm infants admitted to the NICU