RNA-binding protein Nocte regulates Drosophila development by promoting translation reinitiation on mRNAs with long upstream open reading frames.

RNA-binding proteins (RBPs) with intrinsically disordered regions (IDRs) are linked to multiple human disorders, but their mechanisms of action remain unclear. Here, we report that one such protein, Nocte, is essential for Drosophila eye development by regulating a critical gene expression cascade at translational level. Knockout of nocte in flies leads to lethality, and its eye-specific depletion impairs eye size and morphology. Nocte preferentially enhances translation of mRNAs with long upstream open reading frames (uORFs). One of the key Nocte targets, glass mRNA, encodes a transcription factor critical for differentiation of photoreceptor neurons and accessory cells, and re-expression of Glass largely rescued the eye defects caused by Nocte depletion. Mechanistically, Nocte counteracts long uORF-mediated translational suppression by promoting translation reinitiation downstream of the uORF. Nocte interacts with translation factors eIF3 and Rack1 through its BAT2 domain, and a Nocte mutant lacking this domain fails to promote translation of glass mRNA. Notably, de novo mutations of human orthologs of Nocte have been detected in schizophrenia patients. Our data suggest that Nocte family of proteins can promote translation reinitiation to overcome long uORFs-mediated translational suppression, and disruption of this function can lead to developmental defects and neurological disorders.

Opposing action of the FLR-2 glycoprotein hormone and DRL-1/FLR-4 MAP kinases balance p38-mediated growth and lipid homeostasis in C. elegans.

Animals integrate developmental and nutritional signals before committing crucial resources to growth and reproduction; however, the pathways that perceive and respond to these inputs remain poorly understood. Here, we demonstrate that DRL-1 and FLR-4, which share similarity with mammalian mitogen-activated protein kinases, maintain lipid homeostasis in the C. elegans intestine. DRL-1 and FLR-4 function in a protein complex at the plasma membrane to promote development, as mutations in drl-1 or flr-4 confer slow growth, small body size, and impaired lipid homeostasis. To identify factors that oppose DRL-1/FLR-4, we performed a forward genetic screen for suppressors of the drl-1 mutant phenotypes and identified mutations in flr-2 and fshr-1, which encode the orthologues of follicle stimulating hormone and its putative G protein-coupled receptor, respectively. In the absence of DRL-1/FLR-4, neuronal FLR-2 acts through intestinal FSHR-1 and protein kinase A signaling to restrict growth. Furthermore, we show that opposing signaling through DRL-1 and FLR-2 coordinates TIR-1 oligomerization, which modulates downstream p38/PMK-1 activity, lipid homeostasis, and development. Finally, we identify a surprising noncanonical role for the developmental transcription factor PHA-4/FOXA in the intestine where it restricts growth in response to impaired DRL-1 signaling. Our work uncovers a complex multi-tissue signaling network that converges on p38 signaling to maintain homeostasis during development.

An integrated full-head OPM-MEG system based on 128 zero-field sensors.

Compact optically-pumped magnetometers (OPMs) are now commercially available with noise floors reaching 10 fT/Hz1/2. However, to be used effectively for magnetoencephalography (MEG), dense arrays of these sensors are required to operate as an integrated turn-key system. In this study, we present the HEDscan, a 128-sensor OPM MEG system by FieldLine Medical, and evaluate its sensor performance with regard to bandwidth, linearity, and crosstalk. We report results from cross-validation studies with conventional cryogenic MEG, the Magnes 3,600 WH Biomagnetometer by 4-D Neuroimaging. Our results show high signal amplitudes captured by the OPM-MEG system during a standard auditory paradigm, where short tones at 1000 Hz were presented to the left ear of six healthy adult volunteers. We validate these findings through an event-related beamformer analysis, which is in line with existing literature results.

Understanding Why Many People Experiencing Homelessness Reported Migrating to a Small Canadian City: Machine Learning Approach With Augmented Data.

BACKGROUND: Over the past years, homelessness has become a substantial issue around the globe. The largest social services organization in Thunder Bay, Ontario, Canada, has observed that a majority of the people experiencing homelessness in the city were from outside of the city or province. Thus, to improve programming and resource allocation for people experiencing homelessness in the city, including shelter use, it was important to investigate the trends associated with homelessness and migration. OBJECTIVE: This study aimed to address 3 research questions related to homelessness and migration in Thunder Bay: What factors predict whether a person who migrated to the city and is experiencing homelessness stays or leaves shelters? If an individual stays, how long are they likely to stay? What factors predict stay duration? METHODS: We collected the required data from 2 sources: a survey conducted with people experiencing homelessness at 3 homeless shelters in Thunder Bay and the database of a homeless information management system. The records of 110 migrants were used for the analysis. Two feature selection techniques were used to address the first and third research questions, and 8 machine learning models were used to address the second research question. In addition, data augmentation was performed to improve the size of the data set and to resolve the class imbalance problem. The area under the receiver operating characteristic curve value and cross-validation accuracy were used to measure the models' performances while avoiding possible model overfitting. RESULTS: Factors predicting an individual's stay duration included home or previous district, highest educational qualification, recent receipt of mental health support, migrating to visit family or friends, and finding employment upon arrival. For research question 2, among the classification models developed for predicting the stay duration of migrants, the random forest and gradient boosting tree models presented better results with area under the receiver operating characteristic curve values of 0.91 and 0.93, respectively. Finally, home district, band membership, status card, previous district, and recent support for drug and/or alcohol use were recognized as the factors predicting stay duration. CONCLUSIONS: Applying machine learning enables researchers to make predictions related to migrants' homelessness and investigate how various factors become determinants of the predictions. We hope that the findings of this study will aid future policy making and resource allocation to better serve people experiencing homelessness. However, further improvements in the data set size and interpretation of the identified factors in decision-making are required.

Baseline correction using a deep-learning model combining ResNet and UNet.

Most spectral data, such as those obtained via infrared, Raman, and mass spectroscopy, have baseline drifts due to fluorescence or other reasons, which have an adverse impact on subsequent analyses. Therefore, several researchers have proposed the use of various baseline-correction methods to address the aforementioned issue. However, most baseline-correction methods require manual adjustment of the parameters to achieve desirable performance. In this study, we propose a baseline-correction method based on a deep-learning model that combines ResNet and UNet. The method uses a deep-learning model trained with simulated spectral data to perform baseline corrections and eliminates the need for manual parameter adjustments. Based on the results of the qualitative and quantitative analyses of the simulated spectral data and actual Raman spectra, the proposed method is easier to apply and has better performance compared to the existing methods. As the proposed method can be applied to Raman spectra and other spectra, it is expected to be widely used.

Adaptive Hit-Quality Index for Raman Spectrum Identification.

The recognition capability of the identification system using Raman spectroscopy is increasing with the demands in the field. Among the various approaches that determine the identity of a target, signal correlation using a moving window is one of the most effective and intuitive methods. In this paper, we report a new correlation method that is robust to spectral intensity variations. Using the peak distribution of a given spectrum, this method adaptively determines meaningful spectral regions for the identification target. Three commercial Raman spectrometer and a 14 033 library were included in the study, which was used for a library-based chemical discrimination test and mixed material analysis experiments. According to the identification experimental results, the proposed method correctly identified all of the spectra and maintained a mean correlation score above 0.95 while maintaining the correlation score of nontarget materials as low as possible.

Minimizing the risk of perioperative cardiovascular complications in homozygous familial hypercholesterolemia: a case report.

Homozygous familial hypercholesterolemia (HoFH) is a rare inherited disorder that presents as abnormally elevated levels of low-density lipoprotein cholesterol and premature heart disease, requiring frequent intervention through lipid apheresis for management. The risk of perioperative cardiac events is higher in patients with HoFH because of its pathophysiological manifestations in the vascular system. Careful cardiac precautions and anesthetic assessments are necessary to ensure patient safety. In the following case report, we discuss the clinical course and anesthetic considerations for a 14-year-old girl with HoFH undergoing sedation for dental extractions and mandibular molar uprighting in an outpatient oral surgery clinic. Considerations included the use of heparin in the patient's weekly plasma lipid apheresis treatment. In order to reduce the risks of peri- and postoperative bleeding and perioperative cardiac events, the operation was scheduled for 4 days after apheresis. This allowed for adequate heparin clearance, while also reducing the likelihood of possible cardiac events. A literature review revealed no results for the outpatient management of patients with HoFH undergoing sedation for noncardiac procedures. Our reported case serves as a clinical example for physicians to be utilized in the future.

MIRROS: a randomized, placebo-controlled, Phase III trial of cytarabine ± idasanutlin in relapsed or refractory acute myeloid leukemia.

Patients with refractory or relapsed acute myeloid leukemia (R/R AML) have a poor prognosis, with a high unmet medical need. Idasanutlin is a small-molecule inhibitor of MDM2, a negative regulator of tumor suppressor p53. By preventing the p53-MDM2 interaction, idasanutlin allows for p53 activation, particularly in patients with TP53 wild-type (WT) status. MIRROS (NCT02545283) is a randomized Phase III trial evaluating idasanutlin + cytarabine versus placebo + cytarabine in R/R AML. The primary end point is overall survival in the TP53-WT population. Secondary end points include complete remission rate (cycle 1), overall remission rate (cycle 1) and event-free survival in the TP53-WT population. MIRROS has an innovative design that integrates a stringent interim analysis for futility; continuation criteria were met in mid-2017 and accrual is ongoing. Trial registration number: NCT02545283.

Gesicle-Mediated Delivery of CRISPR/Cas9 Ribonucleoprotein Complex for Inactivating the HIV Provirus.

Investigators have utilized the CRISPR/Cas9 gene-editing system to specifically target well-conserved regions of HIV, leading to decreased infectivity and pathogenesis in vitro and ex vivo. We utilized a specialized extracellular vesicle termed a "gesicle" to efficiently, yet transiently, deliver Cas9 in a ribonucleoprotein form targeting the HIV long terminal repeat (LTR). Gesicles are produced through expression of vesicular stomatitis virus glycoprotein and package protein as their cargo, thus bypassing the need for transgene delivery, and allowing finer control of Cas9 expression. Using both NanoSight particle and western blot analysis, we verified production of Cas9-containing gesicles by HEK293FT cells. Application of gesicles to CHME-5 microglia resulted in rapid but transient transfer of Cas9 by western blot, which is present at 1 hr, but is undetectable by 24 hr post-treatment. Gesicle delivery of Cas9 protein preloaded with guide RNA targeting the HIV LTR to HIV-NanoLuc CHME-5 cells generated mutations within the LTR region and copy number loss. Finally, we demonstrated that this treatment resulted in reduced proviral activity under basal conditions and after stimulation with pro-inflammatory factors lipopolysaccharide (LPS) or tumor necrosis factor alpha (TNF-α). These data suggest that gesicles are a viable alternative approach to deliver CRISPR/Cas9 technology.

In silico prediction of potential chemical reactions mediated by human enzymes.

BACKGROUND: Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms. RESULT: We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition. CONCLUSION: Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

Freehand diffuse optical spectroscopy imaging for intraoperative identification of major venous and arterial vessels underlying peritoneal fat: an in vivo demonstration in a pig model.

Inadvertent injury to important anatomic structures is a significant risk in minimally invasive surgery (MIS) that potentially requires conversion to an open procedure, which results in increased morbidity and mortality. Surgeons operating minimal-invasively currently do not have an easy-to-use, real-time device to aid in intraoperative identification of important anatomic structures that underlie tissue planes. We demonstrate freehand diffuse optical spectroscopy (DOS) imaging for intraoperatively identifying major underlying veins and arteries. An applicator probe that can be affixed to and detached from an 8-mm laparoscopic instrument has been developed. The 10-mm DOS source-detector separation renders sampling of tissue heterogeneities a few millimeters deep. DOS spectra acquired consecutively during freehand movement of the applicator probe on the tissue surface are displayed as a temporal and spectral image to assist in spatially resolved identification of the underlying structures. Open surgery identifications of the vena cava and aorta underlying peritoneal fat of ∼4 mm in thickness using the applicator probe under room light were demonstrated repeatedly in multiple pigs in vivo.

Raman spectrum identification based on the correlation score using the weighted segmental hit quality index.

In this paper, we consider a novel method for identification of Raman spectra recorded on different instruments with different wavelengths. Since the conventional hit quality index (HQI) is vulnerable to intensity variation, it needs intensity calibration or standardization for each spectrometer, which causes additional time consuming work. To simplify this process and enhance the identification performance, we propose a new scoring method which is defined as the weighted sum of the HQIs from segmented spectra by windowing. To show the effectiveness of the proposed method, the experiments were carried out with 10 kinds of chemicals with their spectra recorded on 3 different instruments with different laser wavelengths. According to the identification results with 14 033 chemicals, the proposed method identified all test chemicals without error, which indicates that the proposed method could be used as a promising alternative to the existing methods.

Baseline correction using asymmetrically reweighted penalized least squares smoothing.

Baseline correction methods based on penalized least squares are successfully applied to various spectral analyses. The methods change the weights iteratively by estimating a baseline. If a signal is below a previously fitted baseline, large weight is given. On the other hand, no weight or small weight is given when a signal is above a fitted baseline as it could be assumed to be a part of the peak. As noise is distributed above the baseline as well as below the baseline, however, it is desirable to give the same or similar weights in either case. For the purpose, we propose a new weighting scheme based on the generalized logistic function. The proposed method estimates the noise level iteratively and adjusts the weights correspondingly. According to the experimental results with simulated spectra and measured Raman spectra, the proposed method outperforms the existing methods for baseline correction and peak height estimation.

Bilateral canalicular adenomas of the upper lip.

An unusual case of canalicular adenomas appearing bilaterally and simultaneously as separate nodules of the right and left upper lip is described. Upon histological examination, both nodules revealed tumor islands within their respective capsules, as well as outside their capsules and extending into normal salivary gland tissues. The article describes this unusual case and reviews the significance of the extracapsular tumor islands. The immunohistochemical profiles of canalicular adenoma and other salivary gland neoplasms with similar histology are compared and discussed.

The gene encoding xylulose-5-phosphate/fructose-6-phosphate phosphoketolase (xfp) is conserved among Bifidobacterium species within a more variable region of the genome and both are useful for strain identification.

The nucleotide sequence of the xfp-gene region in six known and two unknown species of Bifidobacterium was determined and compared with the published sequences of B. animalis subsp. lactis DSM10140 and B. longum biovar longum NCC2705. The xfp coding sequences were 73% identical and coded for 825 amino acids in all 10 sequences. Partial sequences of an adjacent gene, guaA, were 61% identical in six sequences for which data were available. The region between xfp and guaA was variable in both length and sequence. Oligonucleotide sequences from the conserved and variable xfp regions were used as PCR primers, in combinations of appropriate specificity, for the detection and identification of Bifidobacterium isolates.