Maternal depression, childhood resting-state brain connectivity, and adolescent depression during the COVID-19 outbreak (preprint)

Adolescents of mothers with a history of depression are at two-to-five-fold increased risk for developing depression themselves. These adolescents may be especially vulnerable to depression during the COVID-19 pandemic. To better understand the complex vulnerability processes involved in the transmission of maternal depression risk to adolescent offspring in the context of the pandemic-related stress, we examined potential mediating and moderating factors that link maternal depression history and offspring depressive symptoms, including resting-state functional connectivity (rs-FC) and mothers’ depressive symptoms, in 85 adolescents during the pandemic. Adolescents’ pre-pandemic rs-FC between posterior and anterior cingulate cortex (PCC-ACC) moderated the association between maternal depression history and adolescents’ depressive symptoms during the pandemic, such that maternal depression history predicted adolescents’ symptoms only in youths with heightened pre-pandemic PCC-ACC rs-FC. Mothers’ depressive symptoms during pandemic mediated and moderated the link between maternal depression history and adolescents’ depressive symptoms; specifically, mothers with a history of depression had greater depressive symptoms during pandemic outbreak, which were, in turn, associated with offspring depressive symptoms. Additionally, maternal depression history predicted depressive symptoms in adolescents whose mothers had relatively lower depressive symptoms during the pandemic. Findings speak to the complex mediating and moderating processes involved in the transmission of maternal depression risk to adolescent offspring in the context of the COVID-19 pandemic.

Modeling and Role-Modeling Theory on Stunting Children in the Perspective of Philosophy (preprint)

Stunting, during the Covid-19 pandemic, is increasingly becoming a big problem in the world, especially in poor and developing countries. Observational studies have shown that stunting is associated with poor nutrition, especially a plant-based diet, inflammation, caused by infection, enteric dysfunction, an environment with clean water, inadequate sanitation and hygiene (WASH), and endogenous inflammation associated with excess adiposity. This causes nutritional interventions to be often unsuccessful (Kemenkes RI, 2018).The government intervenes to reduce stunting to the target party, which is divided into two categories. The first category is specific nutrition intervention, namely monitoring children under five at the posyandu, giving immunizations, giving vitamin A, giving Supplementary Foods (PMT), and others. The second category is sensitive nutrition interventions, namely the provision of drinking water and proper sanitation, postnatal family planning (KB) services, providing information related to stunting, food social assistance, conditional cash assistance, and others. (KEMEN-PMK, 2018). WHO states, that the impact of stunting can be divided into short-term and long-term impacts. The short-term impacts are; increased incidence of morbidity and mortality; cognitive, motor, and verbal development in children is not optimal; and increased healthcare costs. While the long-term impact; Posture that is not optimal as an adult (shorter than usual); Increased risk of obesity and other diseases; The decline in reproductive health; Less than optimal learning capacity and performance during school years; and Low productivity and work capacity (Kemenkes RI, 2018). The nursing goal is to help people achieve quality, holistic health. Implementation of Modeling and Role Modeling Theory is an option in implementing nursing care for children with stunting. “Modeling” is gaining an understanding of the client’s world from the client’s perspective. That is to build a “model” of the client’s worldview. “Role‑Modeling” is based on the assumption that all humans want to interact with others, they want to carry out selected roles in society. Role-Modeling is using the client’s model of the world to plan interventions that meet his or her perceived needs, grow, develop and heal. Role-Modeling requires that we aim to build trust, promote a positive orientation and a sense of control, affirm strengths and set specific mutual goals.

DecentTree: Scalable Neighbour-Joining for the Genomic Era (preprint)

Summary Neighbour-Joining is one of the most widely used distance-based phylogenetic inference methods. However, current implementations do not scale well for datasets with more than 10,000 sequences. Given the increasing pace of generating new sequence data, particularly in outbreaks of emerging diseases, and the already enormous existing databases of sequence data for which NJ is a useful approach, new implementations of existing methods are warranted. Here we present DecentTree, which provides highly optimised and parallel implementations of Neighbour-Joining and several of its variants. DecentTree is designed as a stand-alone application and a header-only library easily integrated with other phylogenetic software (e.g. it is integral in the popular IQ-TREE software). We show that DecentTree shows similar or improved performance over existing software (BIONJ, Quicktree, FastME, and RapidNJ), especially for handling very large alignments. For example, DecentTree is up to 6-fold faster than the fastest existing Neighbour-Joining software (e.g. RapidNJ) when generating a tree of 64,000 SARS-CoV-2 genomes. Availability and implementation DecentTree is open source and freely available at https://github.com/iqtree/decenttree . Contact Minh Bui: m.bui@anu.edu.au ; Robert Lanfear: rob.lanfear@anu.edu.au Supplementary information Supplementary data are available at Bioinformatics online.

ONTdeCIPHER: An amplicon-based nanopore sequencing pipeline for tracking pathogen variants (preprint)

Motivation Amplicon-based nanopore sequencing is increasingly used for molecular surveillance during epidemics (e.g. ZIKA, EBOLA) or pandemics (e.g. SARS-CoV-2). However, there is still a lack of versatile and easy-to-use tools that allow users with minimal bioinformatics skills to perform the main steps of downstream analysis, from quality testing to SNPs effect to phylogenetic analysis. Results Here, we present ONTdeCIPHER, an amplicon-based Oxford Nanopore Technology (ONT) sequencing pipeline to analyze the genetic diversity of SARS-CoV-2 and other pathogenes. Our pipeline integrates 13 bioinformatics tools. With a single command line and a simple configuration file, users can pre-process their data and obtain the sequencing statistics, reconstruct the consensus genome, identify variants and their effects for each viral isolate, infer lineage and, finally perform multi-sequence alignments and phylogenetic analyses. Availability and implementation: ONTdeCIPHER is available at https://github.com/emiracherif/ONTdeCIPHER Contact emira.cherif@ird.fr Supplementary information Supplementary data are available at …

Augmented Reality and Gamification: A Framework for Developing Supplementary Learning Tool (preprint)

The main purpose of the study is to develop a supplementary learning tool framework by the use of a dynamic mobile application using Unity AR and Vuforia for Senior High School (SHS) students and teachers to help the learning process in SHS Earth Science. The researchers will be using the Software Development Life Cycle (SDLC) Model of methodology to ensure the quality of the software as well as the correctness of the development process. The expected result of the study is that Augmented Reality and Gamification will now be used as a supplementary learning tool in SHS Earth Science. Augmented Reality and Gamification can now be used as a supplementary learning tool in SHS Earth Science using the designed framework. Future studies will focus on the development of the framework and the mobile application. Since the system has a lot of potential in the education sector and due to the effects of COVID-19, the software will serve as a pioneer to show that a supplementary tool will help students learn logically and entertainingly especially since schools nowadays are transitioning with either distance learning or blended learning.

The ethical-political dimension of social and community praxis: The case of Ecuador´s early response to covid-19 (preprint)

In Ecuador, the painful impact of the covid-19 pandemic elicited early responses by the government, and by local communities. This critical, positioned and exploratory case study analyses such responses, underscoring the fundamental ethical-political dimension of any academic and professional praxis aimed at the construction of healthier societies worldwide. While critical traditions are familiar with this stance, the inequalities and ideological mechanisms made visible by covid-19 responses may enable the wider community of researchers and practitioners to join ongoing collective ethical-political efforts. Findings from Ecuador underline the potentially harmful role of neoliberalism, and issues of democratic legitimacy; significant problems before and during the pandemic shock; and official discourses which blame communities for their own suffering and death. Neutrality and depoliticized notions of scientific evidence are notoriously insufficient in these scenarios. We need to engage more deeply with diverse forms of global and local community resistance, in times of covid-19, and beyond. Please refer to the Supplementary Material section to find this article’s Community and Social Impact Statement

Testing a Developmental Model of Parental Warmth, Amygdala–Subgenual Anterior Cingulate Cortex Connectivity, and Depressive Symptoms in Adolescents During the COVID-19 Pandemic (preprint)

Background: Neurobiological measures may serve as predictive markers of risk for and resilience to depressive symptoms during the COVID-19 pandemic. We tested a developmental model linking variation in amygdala–subgenual anterior cingulate cortex (sgACC) resting-state connectivity both to earlier experiences in the family environment and to subsequent vulnerability to depressive symptoms during the pandemic. Methods: We used data from a longitudinal study that included three waves (N=214 adolescents; ages 9-15 years at Time 1 (T1), 11-17 years at Time 2 (T2), and 12-19 years during the pandemic at Time 3 [T3]). We assessed parental warmth (T1), depressive symptoms (T1 to T3), and functional connectivity between the sgACC and basolateral (BLA) and centromedial amygdala (CMA) (T1 and T2). We modeled associations among early parental warmth, amygdala–sgACC connectivity, and depressive symptoms before and during the pandemic. Results: Less parental warmth was associated prospectively with stronger BLA–sgACC connectivity approximately two years later (=-.23, p=.021) over and above the effect of BLA–sgACC connectivity at T1. Stronger BLA–sgACC connectivity, in turn, was associated with heightened depressive symptoms, both before (r=.21, p=.031) and during the pandemic (=.22, p=.031; independent of the effect of pre-pandemic symptoms). Conclusion: Adolescents who experience less parental warmth may develop a pattern of BLA–sgACC connectivity that increases their risk for mental health problems during the pandemic. BLA–sgACC connectivity in early to middle adolescence may be a predictive marker of risk for depressive symptoms in general and specifically during periods of heightened stress.

COVIDHunter: An Accurate, Flexible, and Environment-Aware Open-Source COVID-19 Outbreak Simulation Model (preprint)

Motivation Early detection and isolation of COVID-19 patients are essential for successful implementation of mitigation strategies and eventually curbing the disease spread. With a limited number of daily COVID-19 tests performed in every country, simulating the COVID-19 spread along with the potential effect of each mitigation strategy currently remains one of the most effective ways in managing the healthcare system and guiding policy-makers. We introduce COVIDHunter , a flexible and accurate COVID-19 outbreak simulation model that evaluates the current mitigation measures that are applied to a region and provides suggestions on what strength the upcoming mitigation measure should be. The key idea of COVIDHunter is to quantify the spread of COVID-19 in a geographical region by simulating the average number of new infections caused by an infected person considering the effect of external factors, such as environmental conditions (e.g., climate, temperature, humidity) and mitigation measures. Results Using Switzerland as a case study, COVIDHunter estimates that the policy-makers need to keep the current mitigation measures for at least 30 days to prevent demand from quickly exceeding existing hospital capacity. Relaxing the mitigation measures by 50% for 30 days increases both the daily capacity need for hospital beds and daily number of deaths exponentially by an average of 23.8 ×, who may occupy ICU beds and ventilators for a period of time. Unlike existing models, the COVIDHunter model accurately monitors and predicts the daily number of cases, hospitalizations, and deaths due to COVID-19. Our model is flexible to configure and simple to modify for modeling different scenarios under different environmental conditions and mitigation measures. Availability https://github.com/CMU-SAFARI/COVIDHunter Contact alserm@ethz.ch , omutlu@ethz.ch Supplementary information Supplementary data is available at Bioinformatics online.

Leveraging Lean Research Principles to Engage Caregivers to Improve Child Undernutrition: a Case Example in Kolkata, India. (preprint)

Background: For social purpose organizations (SPOs), decisions on which programs to scale are driven by information that often falls short of the gold-standard randomized control trial (RCT). This article offers a case study of how lean research, lean experimentation and lean impact principles can be leveraged by SPOs to inform strategic decision-making.Methods: Through two Phases of iterative experimentation, Children International assessed the feasibility and effectiveness of at-home anthropometric evaluation [mid-upper arm circumference Z-score (MUACz) tape] and nutritional support [supplementary foods (SupF)] to influence caregiver engagement and improve children’s nutritional status compared to centralized interventions. Body Mass Index Z-scores (BMIz) at baseline and completion of each Phase were collected along with semi-structured survey and focus group discussion data. Results: Phase I enrolled 37 caregiver/child dyads (17 MUACz, 20 control). The group receiving MUACz tapes reported ease of use for the intervention and a trend towards improved nutrition outcomes. The findings informed the design of Phase II, which enrolled 88 caregiver/child dyads across four groups (20 control, 21 MUACz, 27 SupF, 20 MUACz + SupF). Phase II uncovered low satisfaction with supplementary food and modest overall impact of the interventions despite favorable perceptions of changes in children’s overall health and higher levels of caregiver engagement addressing child nutritional needs. Conclusions: Lean approaches allow SPOs to innovate within the constraints of their organizations, and provide practical platforms to co-create and test evidence-based solutions with the populations they serve. Lean process and a lean mindset allowed the team to rapidly respond with at-home nutrition implementation strategies when faced with the emerging COVID-19 pandemic. Lean approaches can provide a framework to guide teams towards new solutions even during the most unpredictable and unprecedented times.

D-graph clusters flaviviruses and β-coronaviruses according to their hosts, disease type and human cell receptors (preprint)

Motivation There is a need for rapid and easy to use, alignment free methods to cluster large groups of protein sequence data. Commonly used phylogenetic trees based on alignments can be used to visualize only a limited number of protein sequences. DGraph, introduced here, is a dynamic programming application developed to generate 2D-maps based on similarity scores for sequences. The program automatically calculates and graphically displays property distance (PD) scores based on physico-chemical property (PCP) similarities from an unaligned list of FASTA files. Such “PD-graphs” show the interrelatedness of the sequences, whereby clusters can reveal deeper connectivities. Results PD-Graphs generated for flavivirus (FV), enterovirus (EV), and coronavirus (CoV) sequences from complete polyproteins or individual proteins are consistent with biological data on vector types, hosts, cellular receptors and disease phenotypes. PD-graphs separate the tick- from the mosquito-borne FV, clusters viruses that infect bats, camels, seabirds and humans separately and the clusters correlate with disease phenotype. The PD method segregates the β-CoV spike proteins of SARS, SARS-CoV-2, and MERS sequences from other human pathogenic CoV, with clustering consistent with cellular receptor usage. The graphs also suggest evolutionary relationships that may be difficult to determine with conventional bootstrapping methods that require postulating an ancestral sequence. Availability and implementation DGraph is written in Java, compatible with the Java 5 runtime or newer. Source code and executable is available from the GitHub website ( https://github.com/bjmnbraun/DGraph/releases ). Documentation for installation and use of the software is available from the Readme.md file at ( https://github.com/bjmnbraun/DGraph ). Contact bjmnbraun@gmail.com or webraun@utmb.edu Supplementary information Supplementary information Table S1 and Fig. S1 are online available.

coronaSPAdes: from biosynthetic gene clusters to RNA viral assemblies (preprint)

Motivation The COVID-19 pandemic has ignited a broad scientific interest in viral research in general and coronavirus research in particular. The identification and characterization of viral species in natural reservoirs typically involves de novo assembly. However, existing genome, metagenome and transcriptome assemblers often are not able to assemble many viruses (including coronaviruses) into a single contig. Coverage variation between datasets and within dataset, presence of close strains, splice variants and contamination set a high bar for assemblers to process viral datasets with diverse properties. Results We developed coronaSPAdes, a novel assembler for RNA viral species recovery in general and coronaviruses in particular. coronaSPAdes leverages the knowledge about viral genome structures to improve assembly extending ideas initially implemented in biosyntheticSPAdes. We have shown that coronaSPAdes outperforms existing SPAdes modes and other popular short-read metagenome and viral assemblers in the recovery of full-length RNA viral genomes. Availability coronaSPAdes version used in this article is a part of SPAdes 3.15 release and is freely available at http://cab.spbu.ru/software/spades . Contact a.korobeynikov@spbu.ru Supplementary information Supplementary data are available at Bioinformatics