Activity

Adult-born neurons (ABNs) in the dentate gyrus bestow unique cellular plasticity to the mammalian brain. We recently found that the activity of ABNs during sleep is necessary for memory consolidation. Here, we describe our method for Ca2+ imaging of ABN activity using a miniaturized fluorescent microscope and sleep recordings. As preparatory surgery and post-recording data processing can be major obstacles, we provide detailed descriptions and problem-solving tips. For complete details on the use and execution of this protocol, please refer to Kumar et al. (2020).Analytical methods for quantifying and monitoring the degradation of micronutrients added to food are crucial to food fortification programs. In the case of folic acid in fortified salts, there are difficulties in developing an effective analytical method due to interference of salt in the standard HPLC methods, as salt precipitates in the HPLC column. To circumvent the problem, a spectrophotometric method was developed to quantify folic acid and monitor its degradation in salt. A distinct absorption wavelength was selected for folic acid in sodium carbonate solution. Of the three wavelengths where maximum absorption was observed for folic acid, 285 nm was selected as being selective for folic acid in the presence of pteroic acid, glutamic acid, aminobenzoic acid, and other products of degradation of folic acid. The method was calibrated for 1-25 μg/mL folic acid (R2 = 1). The recovery was 100 ± 1.2% and 100 ± 1.8% for folic acid in salt and solution, respectively. The limit of detection and quantification for this method is 0.011 μg/mL and 0.033 μg/mL, respectively. The method is accurate, precise, and selective for folic acid in the presence of potential products of folic acid degradation, and is suitable for monitoring folic acid degradation in fortified salt.A field experiment was conducted to understand whether non-formalized monocultures of maize could be substituted by the rotations with common bean on smallholder farms. This study was installed in the northern highlands of Tanzania along the slopes of the highest African peak of Mt. Kilimanjaro with the predominance of smallholder farmers. Cropping seasons (S), cropping systems (C), bean varieties (V), and their interactions were evaluated. Data collected were plant height, ground coverage, total biomass, number of pods per bean and seeds per pod, 100-seed weight, and grain yield. Results indicated that bean in long rainy seasons produced significantly larger grain yields as an effect of S (3.3 t ha-1) in 2015, C (3.4 t ha-1) in intercrop, V (2.7 t ha-1) in local bean, S × C (4.4 t ha-1) in 2015 in intercrop, S × V (3.4 t ha-1) in improved bean in 2015, C × V (4.6 t ha-1) in intercropped local bean, and S × C × V (5.0 t ha-1) in intercropped local bean in 2017. In a short rainy season, significantly larger bean grain yield (1.8 t ha-1) was recorded as an effect of C when sown subsquent to maize. The effects of V and/or C × V were not significant on bean grain yield during short rainy season. Maize in long rainy seasons produced significantly larger grain yields as an effect of C (2.9 t ha-1) but not for S and S × C in rotation with the local bean. In short rainy seasons, significantly larger maize grain yield was produced in 2015 (2.6 t ha-1) but the effects of C and S × C were not significant in 2015 and 2016. This study concluded that inclusion of intercrops (of maize and common bean) as part of a rotation with one of these crops significantly improved grain yields and hence provided promising grounds of the options for sustainable food production on smallholder farms.COVID-19, otherwise known as the coronavirus, has precipitated the world into a pandemic that has infected, as of the time of writing, more than 10 million persons worldwide and caused the death of more than 500,000 persons. Early symptoms of the virus include trouble breathing, fever and fatigue and over 60% of people experience a dry cough. Due to the devastating impact of COVID-19 and the tragic loss of lives, it is of the utmost urgency to develop methods for the early detection of the disease that may help limit its spread as well as aid in the development of targeted solutions. Coughs and other vocal sounds contain pulmonary health information that can be used for diagnostic purposes, and recent studies in chaotic dynamics have shown that nonlinear phenomena exist in vocal signals. The present work investigates the use of symbolic recurrence quantification measures with MFCC features for the automatic detection of COVID-19 in cough sounds of healthy and sick individuals. Our performance evaluation reveals that our symbolic dynamics measures capture the complex dynamics in the vocal sounds and are highly effective at discriminating sick and healthy coughs. We apply our method to sustained vowel ‘ah’ recordings, and show that our model is robust for the detection of the disease in sustained vowel utterances as well. L-SelenoMethionine Furthermore, we introduce a robust novel method of informative undersampling using information rate to deal with the imbalance in our dataset, due to the unavailability of an equal number of sick and healthy recordings. The proposed model achieves a mean classification performance of 97% and 99%, and a mean F 1 -score of 91% and 89% after optimization, for coughs and sustained vowels, respectively.Due to the successful emergence of internet of things, sensor-based real-time health monitoring is getting popularized. A usable health-monitoring system is required for prolonged monitoring of the patient with reduced cost. This paper describes a working prototype system for real-time health-monitoring system using DS18B20 temperature sensor, Arduino Nano with micro-controller ATmega328 where Zigbee module is used for wireless communication. link2 In this prototype sensor data gets acquired and analyzed to give proper feedback to the patient with or without mobility support at indoor. The sensor vitals are collected and sent to the computing device using shielded cable and ZigBee, i.e., through wired and wireless communication, respectively. Analysis of patient vitals based on medical definitions gives patient’s real-time health condition so that if condition is not normal, then timely preventive measures can be taken to avoid further complication. Per user data can be saved in the system database for further reference.Currently, the use of voice-assistants has been on the rise, but a user-centric usability evaluation of these devices is a must for ensuring their success. System Usability Scale (SUS) is one such popular usability instrument in a Graphical User Interface (GUI) scenario. However, there are certain fundamental differences between GUI and voice-based systems, which makes it uncertain regarding the suitability of SUS in a voice scenario. The present work has a twofold objective to check the suitability of SUS for usability evaluation of voice-assistants and developing a subjective scale in line with SUS that considers the unique aspects of voice-based communication. We call this scale as the Voice Usability Scale (VUS). For fulfilling the objectives, a subjective test is conducted with 62 participants. An Exploratory Factor Analysis suggests that SUS has a number of drawbacks for measuring the voice usability. Moreover, in case of VUS, the most optimal factor structure identifies three main components usability, affective, and recognizability and visibility. The current findings should provide an initial starting point to form a useful theoretical and practical basis for subjective usability assessment of voice-based systems.The outbreak of pandemic COVID-19 across the world has completely disrupted the political, social, economic, religious, and financial structures of the world. According to the data of April 22nd, 2020, more than 4.6 million people have been screened, in which the infection has made more than 2.7 million people positive, in which 182,740 people have died due to infection. More than 80 countries have closed their borders from transitioning countries, ordered businesses to close, instructed their populations to self-quarantine, and closed schools to an estimated 1.5 billion children. The world’s top ten economies such as the United States, China, Japan, Germany, United Kingdom, France, India, Italy, Brazil, and Canada stand on the verge of complete collapse. In addition, stock markets around the world have been pounded, and tax revenue sources have fallen off a cliff. The epidemic due to infection is having a noticeable impact on global economic development. It is estimated that by now the virus could exceed glo variation and the stock market to see how well and how far in advance the prediction holds true, if at all. The hope is that the model will be able to correctly make predictions a couple of quarters in advance, and describe why the changes are occurring. This research can support how policymakers, business strategy makers, and investors can understand the situation and use the model for prediction.We consider the approximation of an abstract evolution problem with inhomogeneous side constraint using A-stable Runge-Kutta methods. We derive a priori estimates in norms other than the underlying Banach space. Most notably, we derive estimates in the graph norm of the generator. These results are used to study convolution quadrature based discretizations of a wave scattering and a heat conduction problem.Immunotherapy that targets lymphoid cell checkpoints holds great promise for curing cancer. However, a majority of cancer patients do not respond to this form of therapy. In addition to lymphoid cells, myeloid cells play essential roles in controlling immunity to cancer. Whether myeloid checkpoints exist that can be targeted to treat cancer is not well established. Here we show that c-Rel, a member of the nuclear factor (NF)-B family, specified the generation of myeloid-derived suppressor cells (MDSCs) by selectively turning on pro-tumoral genes while switching off anti-tumoral genes through a c-Rel enhanceosome. c-Rel deficiency in myeloid cells markedly inhibited cancer growth in mice, and pharmaceutical inhibition of c-Rel had the same effect. Combination therapy that blocked both c-Rel and the lymphoid checkpoint protein PD1 was more effective in treating cancer than blocking either alone. Thus, c-Rel is a myeloid checkpoint that can be targeted for treating cancer.Long-range oncogenic enhancers play an important role in cancer. Yet, whether similar regulation of tumor suppressor genes is relevant remains unclear. Loss of expression of PTEN is associated with the pathogenesis of various cancers, including T-cell leukemia (T-ALL). Here, we identify a highly conserved distal enhancer (PE) that interacts with the PTEN promoter in multiple hematopoietic populations, including T-cells, and acts as a hub of relevant transcription factors in T-ALL. Consistently, loss of PE leads to reduced PTEN levels in T-ALL cells. Moreover, PE-null mice show reduced Pten levels in thymocytes and accelerated development of NOTCH1-induced T-ALL. Furthermore, secondary loss of PE in established leukemias leads to accelerated progression and a gene expression signature driven by Pten loss. Finally, we uncovered recurrent deletions encompassing PE in T-ALL, which are associated with decreased PTEN levels. link3 Altogether, our results identify PE as the first long-range tumor suppressor enhancer directly implicated in cancer.