Technology advances have immensely accelerated large-scale mapping of biological networks, which necessitates the development of accurate and powerful network-based algorithms to make functional inferences. A prevailing approach is to leverage functions of neighboring nodes to predict unknown molecular function. However, existing neighbor-based algorithms have ignored the scale-free property hidden in many biological networks. By assuming that neighbor sharing is constrained by the preferential attachment property, we developed a Preferential Attachment based common Neighbor Distribution (PAND) to calculate the probability of the neighbor-sharing event between any two nodes in scale-free networks, which nearly perfectly matched the observed probability in simulations. By applying PAND to a human protein-protein interaction (PPI) network, we showed that smaller probabilities represented closer functional linkages between proteins. With the PAND-derive linkages, we were able to build new networks where the links are more functionally reliable than those of the human PPI network. We then applied simple annotation schemes to a PAND-derived network to make reliable functional predictions for proteins. We also developed an R package called PANDA (PAND-derived functional Associations) to implement the methods proposed in this study. In conclusion, PAND is a useful distribution to calculate the probability of the neighbor-sharing events in scale-free networks. With PAND, we are able to extract reliable functional linkages from real biological networks and builds new networks that are better bases for further functional inference.

Parasitic plants in the genus Cuscuta (dodders) make their living by extracting resources from other plants. While relatively few dodder species are agricultural pests, those that are can be challenging to control, in part due to their intimate physical and physiological association with host plants. Consequently, dodders remain pervasive and economically damaging pests in a variety of crop systems. The development of improved management strategies would be facilitated by greater understanding of the ecological and environmental factors that influence the establishment and perpetuation of dodder infestations. Light cues play an important role in dodder host location and attachment. To better understand the influence of light conditions on parasite ecology, and potential implications for management, we examined how manipulating the ratio of red to far-red wavelengths (R:FR), via both passive filtering of natural sunlight and active spectral manipulation using LEDs, affects host location and host attachment by two dodder species (C. campestris on tomato hosts and C. gronovii on jewelweed). For both host-parasite combinations, host location and subsequent attachment by dodder parasites was dramatically reduced in high R:FR environments compared to control conditions (with R:FR characteristic of sunlight) and low R:FR conditions. Circumnutation by dodder seedlings was also significantly faster under high R:FR. We observed short-term effects of high R:FR on the height and dry mass of tomato host plants (immediately following 7-day exposure), as well as changes in tomato volatile emissions. However, preliminary investigation of long-term effects on host plants suggests that short-term exposure to high R:FR (i.e. during the critical period when dodder seedlings emerge and attach to hosts) has little or no effect on host plant size or fruit yield at the time of harvest. Synthesis and applications. Our findings suggest that spectral manipulation during the early stages of crop plant growth (e.g. via light-filtering row covers), may have significant potential to augment existing methods for managing or preventing dodder infestations in agricultural crops. We discuss potential obstacles to the realization of its potential, as well as next steps toward the development and optimization of spectral manipulation methods for use in agroecosystems.

Discoveries of RNA roles in cellular physiology and pathology are increasing the need for new tools that modulate the structure and function of these biomolecules, and small molecules are proving useful. In 2017, we curated the RNA-targeted BIoactive ligaNd Database (R-BIND) and discovered distinguishing physicochemical properties of RNA-targeting ligands, leading us to propose the existence of an “RNA-privileged” chemical space. Biennial updates of the database and the establishment of a website platform (rbind.chem.duke.edu) have provided new insights and tools to design small molecules based on the analyzed physicochemical and spatial properties. In this report and R-BIND 2.0 update, we refined the curation approach and ligand classification system as well as conducted analyses of RNA structure elements for the first time to identify new targeting strategies. Specifically, we curated and analyzed RNA target structural motifs to determine the properties of small molecules that may confer selectivity for distinct RNA secondary and tertiary structures. Additionally, we collected sequences of target structures and incorporated an RNA structure search algorithm into the website that outputs small molecules targeting similar motifs without a priori secondary structure knowledge. Cheminformatic analyses revealed that, despite the 50% increase in small molecule library size, the distinguishing properties of R-BIND ligands remained significantly different from that of proteins and are therefore still relevant to RNA-targeted probe discovery. Combined, we expect these novel insights and website features to enable the rational design of RNA-targeted ligands and to serve as a resource and inspiration for a variety of scientists interested in RNA targeting.

This data includes the 3-D pin-wise fission rate distribution for the BEAVRS benchmark calculated from Serpent and RAPID. Meanwhile, we also attach the R code to analyze the 2-D pin-wise RMS error, the 3-D pin-wise RMS error and the k-effective difference between results from RAPID and Serpent

Overview Sequence R: Step AOA, No Probes (P) This sequence was designed to quantify the effect of the five-hole probes on the 3-D blade static angle-of-attack response in the presence of rotational influences by repeating Sequence K without five-hole probes. This test sequence used an upwind, rigid turbine with a 0° cone angle. The wind speeds ranged from 6 m/s to 20 m/s, and data were collected at yaw angles of 0° and 30°. The rotor rotated at 72 RPM. Blade pressure measurements were collected. The five-hole probes were removed and the plugs were installed. Plastic tape 0.03-mm-thick was used to smooth the interface between the plugs and the blade. The teeter dampers were replaced with rigid links, and these two channels were flagged as not applicable by setting the measured values in the data file to –99999.99 Nm. The teeter link load cell was pre-tensioned to 40,000 N. During post-processing, the probe channels were set to read –99999.99. The blade pitch angle ramped continuously at 0.18°/s over a wide range of increasing and decreasing pitch angles. A step sequence was also performed. The blade pitch was stepped 5°; the flow was allowed to stabilize; and the pitch angle was held for 5 seconds. Then the pitch angle step was repeated. Again, a wide range of pitch angles was obtained, both increasing and decreasing. The file lengths for this sequence varied from 96 seconds to 6 minutes, depending on the pitch angle range. Some short points were collected at 0° yaw and 3° pitch to ascertain the functionality of the instrumentation and repeatability over time. The file name convention used the initial letter R, followed by two digits specifying wind speed, followed by two digits for yaw angle, followed by RU, RD, or ST, followed by the repetition digit. The angle of attack motion was differentiated by RU (ramp up), RD (ramp down), and ST (step down, then step up). This sequence is related to Sequences K and L. Data Details File naming information can be found in the attached Word document "Sequence R Filename Key", copied from the Phase VI Test Report.

This dataset was collected from K-12 teachers via online surveys (Qualtrics). The statistical analyses were conducted in R-programing.

In the present research, we tested whether a combination of getting perspective and exposure to relevant incremental theories can mitigate the consequences of bias on discipline decisions. We call this combination of approaches a “Bias-Consequence Alleviation” (BCA) intervention. The present research sought to determine how the following components can be integrated to reduce the process by which bias contributes to racial inequality in discipline decisions: (1) getting a misbehaving student’s perspective, “student-perspective”; (2) belief that others’ personalities can change, “student-growth”; and (3) belief that one’s own ability to sustain positive relationships can change, “relationship-growth.” Can a combination of these three components curb troublemaker-labeling and pattern-prediction responses to a Black student’s misbehavior (Exp...

The data collection was carried out in a nationally representative online sample by a Hungarian company (Social Research Ltd.). 16,000 members of the company’s research community were invited to participate voluntarily in the research via email. The sample was stratified according to gender, age, education, and settlement type. Following the stratification, the respondents were randomly selected in order to obtain a final, nationally representative sample. There were five age groups (18-29, 30-39, 40-49, and 50-59 years of age, and 60 years of age or older), and three categories of education level (primary and vocational school, secondary, and higher education). The stratification of the sample was completed by adjusting the true proportions of settlement type (capital, cities/towns, and villages) and regions (Central, Eastern, and Western Hungary).

The total sample size was N = 993, but the number of respondents to the ECR-R-HU questions was N=958, as the questionnaire was not offered to participants who stated that they had never been in a romantic relationship. After the first, main wave of data collection in December 2018, a second wave was carried out in order to assess the stability of the ECR-R-HU scale. After a 4-month interval in March 2019, the questionnaire was administered again to a smaller subsample (N = 98) of the original sample (Wave 2 data). In addition to socio-demographic questions and the ECR-R-HU, participants were given the Hungarian version of the following four questionnaires in order to test the convergent validity of the ECR-R-HU: 1. WHO Well-being Questionnaire (WBI-5), 2. Perceived Stress Scale – 4 (PSS-4), 3. Depression Scale Questionnaire (DS1K), 4. Family Assessment Device (FAD). ECR-R-HU item distributions were checked by Kolmogorov-Smirnov tests. To test the original two-factor model of the ECR-R, a series of Confirmatory Factor Analyses (CFAs) were conducted on AMOS 21.0. Maximum likelihood estimations were used and four model fit indices were examined: the Chi Square Test of Model Fit (χ2/df ratio, which indicates a good model fit below 3), the Steiger-Lind Root Mean Square Error of Approximation (RMSEA which indicates a good model fit below .05), the Tucker-Lewis Index (TLI which signifies a good fit above .95), and the Bentler Comparative Fit Index (CFI which indicates a good fit above .95). RMSEA between .05 and .10, CFI and TLI between .90 and .95 mean a moderate fit. Exploratory Factor Analyses (EFAs) were conducted using Principal Axis Factoring (PAF) method with varimax rotation to examine the orthogonal structure of the latent factors in our study. We also used Hierarchical Cluster Analysis (HCA) to confirm the latent structure of the items based on their similarities. Between-groups linkage method was used, and the items’ distances/similarities were examined with Pearson correlations. The internal consistency of the subscales was measured by calculating Cronbach’s alphas. Descriptive statistics showed that the distribution of the ECR-R-HU subscale scores did not follow a normal distribution, so we used non-parametric statistical tests (Spearman correlations, Mann-Whitney Test, Kruskal-Wallis Test) for further analyses. The research was approved by the Research Ethics Committee of Semmelweis University Budapest, Hungary. The license number: RKEB: 197/2018.

The dissolution of the nuclear membrane marks the beginning of the prometaphase. Kinetochores are created when proteins attach to the centromeres. Microtubules then attach at the kinetochores, and the chromosomes begin to move to the metaphase plate.

Data and Code for ALAN Spongy Moth lab experiment In this repository you will find all the raw datasets used for the data analysis performed in our paper about the impacts of artificial light at night (ALAN) on the development of Spongy Moth caterpillars. The files are attached as a csv file. Also attached is all the R-code later used for the statistical analysis and for generating the graphics displayed in the paper. This files are attached as an R.file.

R-loops are non-canonical, three-stranded nucleic acid structures composed of a DNA:RNA hybrid, a displaced single-stranded (ss)DNA, and a trailing ssRNA overhang. R-loops perform critical biological functions under both normal and disease conditions. To elucidate their cellular functions, we need to understand the mechanisms underlying R-loop formation, recognition, signaling, and resolution. Previous high-throughput screens identified multiple proteins that bind R-loops, with many of these proteins containing folded nucleic acid processing and binding domains that prevent (e.g., topoisomerases), resolve (e.g., helicases, nucleases), or recognize (e.g., KH, RRMs) R-loops. However, a significant number of these R-loop interacting Enzyme and Reader proteins also contain long stretches of intrinsically disordered regions (IDRs). The precise molecular and structural mechanisms by which the folded domains and IDRs synergize to recognize and process R-loops or modulate R-loop-mediated signaling have not been fully explored. While studying one such modular R-loop Reader, the Fragile X Protein (FMRP), we unexpectedly discovered that the C-terminal IDR (C-IDR) of FMRP is the predominant R-loop binding site, with the three N-terminal KH domains recognizing the trailing ssRNA overhang. Interestingly, the C-IDR of FMRP has recently been shown to undergo spontaneous Liquid-Liquid Phase Separation (LLPS) assembly by itself or in complex with another non-canonical nucleic acid structure, RNA G-quadruplex. Furthermore, we have recently shown that FMRP can suppress persistent R-loops that form during transcription, a process that is also enhanced by LLPS via the assembly of membraneless transcription factories. These exciting findings prompted us to explore the role of IDRs in R-loop processing and signaling proteins through a comprehensive bioinformatics and computational biology study. Here, we evaluated IDR prevalence, sequence composition and LLPS propensity for the known R-loop interactome. We observed that, like FMRP, the majority of the R-loop interactome, especially Readers, contains long IDRs that are highly enriched in low complexity sequences with biased amino acid composition, suggesting that these IDRs could directly interact with R-loops, rather than being “mere flexible linkers” connecting the “functional folded enzyme or binding domains”. Furthermore, our analysis shows that several proteins in the R-loop interactome are either predicted to or have been experimentally demonstrated to undergo LLPS or are known to be associated with phase separated membraneless organelles. Thus, our overall results present a thought-provoking hypothesis that IDRs in the R-loop interactome can provide a functional link between R-loop recognition via direct binding and downstream signaling through the assembly of LLPS-mediated membrane-less R-loop foci. The absence or dysregulation of the function of IDR-enriched R-loop interactors can potentially lead to severe genomic defects, such as the widespread R-loop-mediated DNA double strand breaks that we recently observed in Fragile X patient-derived cells.

R codes and data for analyses in 2021. Cascading effects of sand stabilization on pathogen communities: connecting global and local processes

Santangelo et al., 2015 Botany_Raw dataThe data file contains a total of 8 sheets. Four of the sheets contain the raw data while the other four contain the metadata describing what each of the columns/variables in the data files mean and how they were measured. Data sheets are numbered and correspond to their relevant metadata sheets within the dataset. Note that individual datasheets should be saved as .csv files for use with attached R-scripts.Santangelo et al., 2015 Botany_Master R scriptR script used in analyzing the attached data files. The script contains 4 sections representing 4 separate analyses, each to be used with one of the four datasheets in the .xls file provided.

We used R for all data analyses. We have attached R Markdown files, with code, adjoining the datasets used for analyses related to our objectives. R Core Team. 2017. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Work passion is considered desirable as it's harmonious (HWP) facet is related to adaptive work outcomes while it's obsessive (OWP) facet is primarily related to less desirable work outcomes yet may also yield some benefits. The dualistic model of passion (Vallerand et al., 2003, 2019) suggests a major role of basic need satisfaction at work for work passion development, while basic need satisfaction off-work may play a role for OWP (Lalande et al., 2015). Yet how exactly HWP and OWP can be fostered or transformed into each other remains largely unknown. Therefore, this training study investigated if HWP can be fostered via an individual online-training targeting autonomy, competence, relatedness at work. Furhtermore, autonomy, competence, relatedness at leisure were measured alongside. The three wave experimental design study including 3 measurement occasions across 8 weeks in April to June in 2021 was completed by a sample of German working students (N=67). The training was designed as a real online experiment, containing separate branches for each of the three basic needs (with 5 exercises each) as well as a control group. Longitudinal multilevel-modelling revealed no effects of training on either autonomy, competency or relatedness at work, nor on HWP or OWP. Relationships among observed variables however, were mostly in line with theory. While the training was unsuccessful in fostering HWP/ OWP, this study gained relevant insights on how to approach the fostering HWP/ OWP in the workplace, points out where limits to this endeavour might be, and proposes a different perspective to be taken on the topic. Limitations are discussed and specific recommendations for future HWP/ OPW training studies are given. The R data files in this repository are heavily modified and ready for analysis with the attached R syntax. The .CSV data file contains the unprepared, anonymized data. Unfortunately, some free text input for the exercises contained personal innformation. Therefore, none of the according variables is included in any data files contained in this repository.

Bacteria Counts CTD Bottle Measurements HRS2204

Motivation: Home range is a common measure of animal space use as it provides ecological information that is useful for conservation applications. In macroecological studies, values are typically aggregated to species means to examine general patterns of animal space use. However, this ignores the environmental context in which the home range was estimated and does not account for intraspecific variation in home range size. In addition, the focus of macroecological studies on home ranges has been historically biased toward terrestrial mammals. The use of aggregated numbers and terrestrial focus limits our ability to examine home range patterns across different environments, variation in time and between different levels of organisation. Here we introduce HomeRange, a global database with 75,611 home-range values across 960 different mammal species, including terrestrial, as well as aquatic and aerial species. Main types of variable contained: The dataset contains mammal home-range estim..., Mammalian home range papers were compiled via an extensive literature search. All home range values were extracted from the literature including individual, group and population-level home range values. Associated values were also compiled including species names, methodological information on data collection, home-range estimation method, period of data collection, study coordinates and name of location, as well as species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit. Here we include the database, associated metadata and reference list of all sources from which home range data was extracted from. We also provide an R package, which can be installed from https://github.com/SHoeks/HomeRange. The HomeRange R package provides functions for downloading the latest version of the HomeRange database and loading it as a standard dataframe into R, plotting several statistics of the database and finally attaching species traits (e.g. spe..., , # Title of Dataset: HomeRange: A global database of mammalian home ranges

Mammalian home range papers were compiled via an extensive literature search. All home range values were extracted from the literature including individual, group and population-level home range values. Associated values were also compiled including species names, methodological information on data collection, home-range estimation method, period of data collection, study coordinates and name of location, as well as species traits derived from the studies, such as body mass, life stage, reproductive status and locomotor habit.

We also provide an R package, which can be installed from https://github.com/SHoeks/HomeRange. The HomeRange R package provides functions for downloading the latest version of the HomeRange database and loading it as a standard dataframe into R, plotting several statistics of the database and finally attaching species traits (e.g. species average body mass, trophic level). from the CO...

AE1918 was a cruise of opportunity on which two oceanographic sampling activities were conducted: a CTD cast and a MOCNESS net tow. These are the net data from the MOCNESS tow. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv acquisition_description=Standard MOCNESS procedure. It was observed filtered volumes to be too high (and speeds too high), so flowmeter was "recalibrated"\u00a0using deployments and files reanalyzed. It is likely that, since the flowmeter was too new, after several recent deployments has finally "broken-in" and now goes faster. Flow calibration was done by running the LVpki software for several profiles looking at average CF values.

Refer to the cruise report for more information. See also: the xmlcon and hdr files under Supplemental Files. awards_0_award_nid=764113 awards_0_award_number=OCE-1829318 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1829318 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=David L. Garrison awards_0_program_manager_nid=50534 awards_1_award_nid=764119 awards_1_award_number=OCE-1829378 awards_1_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1829378 awards_1_funder_name=NSF Division of Ocean Sciences awards_1_funding_acronym=NSF OCE awards_1_funding_source_nid=355 awards_1_program_manager=David L. Garrison awards_1_program_manager_nid=50534 cdm_data_type=Other comment=MOCNESS Net Data from R/V Atlantic Explorer cruise AE1918 PI: Amy Maas (BIOS) Co-PIs: Leocadio Blanco-Bercial (BIOS) & Ann Tarrant (WHOI) Version date: 13-Nov-2019 Noted after the cruise: original volumes (VOL) were wrong.
New column (NewVol) was added with real values after changing the calibration to 2.7.
The incorrect VOL column has been removed. Please notice that, contrary to regular mocness net numbering (0 to 8) the net count starts at 1 (1 to 9). Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.781508.1 infoUrl=https://www.bco-dmo.org/dataset/781508 institution=BCO-DMO instruments_0_acronym=MOC1 instruments_0_dataset_instrument_description=Seabird 9/11 unit attached to a 1 m MOCNESS, 150 micron mesh nets instruments_0_dataset_instrument_nid=781517 instruments_0_description=The Multiple Opening/Closing Net and Environmental Sensing System or MOCNESS is a family of net systems based on the Tucker Trawl principle. The MOCNESS-1 carries nine 1-m2 nets usually of 335 micrometer mesh and is intended for use with the macrozooplankton. All nets are black to reduce contrast with the background. A motor/toggle release assembly is mounted on the top portion of the frame and stainless steel cables with swaged fittings are used to attach the net bar to the toggle release. A stepping motor in a pressure compensated case filled with oil turns the escapement crankshaft of the toggle release which sequentially releases the nets to an open then closed position on command from the surface. -- from the MOCNESS Operations Manual (1999 + 2003). instruments_0_instrument_external_identifier=https://vocab.nerc.ac.uk/collection/L22/current/NETT0097/ instruments_0_instrument_name=MOCNESS1 instruments_0_instrument_nid=437 instruments_0_supplied_name=MOCNESS keywords_vocabulary=GCMD Science Keywords metadata_source=https://www.bco-dmo.org/api/dataset/781508 param_mapping={'781508': {'ISO_DateTime_UTC_start': 'flag - time'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/781508/parameters people_0_affiliation=Bermuda Institute of Ocean Sciences people_0_affiliation_acronym=BIOS people_0_person_name=Amy Maas people_0_person_nid=51589 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=Bermuda Institute of Ocean Sciences people_1_affiliation_acronym=BIOS people_1_person_name=Leocadio Blanco-Bercial people_1_person_nid=51108 people_1_role=Co-Principal Investigator people_1_role_type=originator people_2_affiliation=Woods Hole Oceanographic Institution people_2_affiliation_acronym=WHOI people_2_person_name=Ann M. Tarrant people_2_person_nid=51430 people_2_role=Co-Principal Investigator people_2_role_type=originator people_3_affiliation=Woods Hole Oceanographic Institution people_3_affiliation_acronym=WHOI BCO-DMO people_3_person_name=Shannon Rauch people_3_person_nid=51498 people_3_role=BCO-DMO Data Manager people_3_role_type=related project=Zooplankton Diel Rhythm projects_0_acronym=Zooplankton Diel Rhythm projects_0_description=NSF Award Abstract: The daily vertical migration (DMV) of zooplankton and fish across hundreds of meters between shallow and deep waters is a predominant pattern in pelagic ecosystems. This migration has consequences for biogeochemical cycling as it moves a substantial portion of fixed carbon and nitrogen (an estimated 15 to 40 % of the total global organic export) from the surface directly to depth where it feeds the midwater food chain and sequesters nutrients away from atmospheric mixing. Estimates and predictions of these fluxes are, however, poorly understood at present. New observations have shown that one source of uncertainty is due to the assumption that metabolic rates and processes do not vary over the course of the day, except based on changes in temperature and oxygen availability. Rates are, however, also driven by differences in feeding, swimming behavior, and underlying circadian cycles. The objective of this project is to improve the ability of scientists to understand and predict zooplankton contributions to the movement of carbon and nitrogen in the ocean by detailing daily changes in physiological processes of these organisms. By producing a set of respiration and excretion measurements over a daily time series, paired with simultaneously collected gene and protein expression patterns for an abundant vertically migratory species, the investigators will provide unprecedented and predictive insight into how changes in the environment affect the contribution of zooplankton to biogeochemical fluxes. The sampling design of the project will advance discovery and understanding by providing hands-on training opportunities to at least two undergraduate researchers. The project will broaden dissemination of the research via development of an educational module, focusing on rhythms in the ocean. The module will initially be piloted with the Bermuda Institute of Ocean Sciences (BIOS) summer camp students and then disseminated through the BIOS Explorer program, the Teacher Resources Page on the BIOS website, and published in a peer-reviewed educational journal. This project will characterize the metabolic consequences of daily physiological rhythms and DVM for a model zooplankton species, the abundant subtropical copepod Pleuromamma xiphias. Flux processes (oxygen consumption, carbon dioxide production, production of ammonium and fecal pellet production) will be interrogated using directed experiments testing the effects of temperature, feeding and circadian cycle. Circadian cycling will further be examined using transcriptomic and proteomic profiling. These experiments will be related to field samples taken at 6-h intervals over the course of the diel migration using an integrated suite of molecular and organismal metrics. Combined organismal, transcriptomic and proteomic profiles will provide an understanding of which metabolic pathways and associated flux products vary in relation to particular environmental variables (food, light cycle, temperature). Diel variation in metabolic rates will also be assessed across seasons and species using other important migratory groups (pteropod, euphausiid, and another copepod). The metabolic data will then be contextualized with abundance estimates from archived depth-stratified tows to allow scaling to community-level patterns and will be used to improve calculations of zooplankton contribution to particulate organic carbon, nitrogen and respiratory active flux. The results of this study will both improve our flux estimates and provide predictive insight into how various environmental variables influence the underlying physiological pathways generating carbon and nitrogen flux. Cruise reports are available from the completed cruises:SD031019AE1910AE1918 projects_0_end_date=2021-09 projects_0_geolocation=Bermuda projects_0_name=Collaborative Research: Diel physiological rhythms in a tropical oceanic copepod projects_0_project_nid=764114 projects_0_start_date=2018-10 sourceUrl=(local files) standard_name_vocabulary=CF Standard Name Table v55 subsetVariables=tow,date_start,time_start,time,cruise,Date time_coverage_end=2019-07-25T14:20:08Z time_coverage_start=2019-07-25T14:20:08Z version=1 xml_source=osprey2erddap.update_xml() v1.3

Background: The novel coronavirus 2019 (COVID-19) has caused severe panic among people worldwide. In Italy, a nationwide state of alert was declared on January 31st, leading to the confinement of the entire population from March 11 to May 18, 2020. Isolation and quarantine measures cause psychological problems, especially for individuals who are recognized as being vulnerable. Parental bonding and attachment styles play a role in the programming of the stress response system. Here, we hypothesize that the response to restricted social contact and mobility due to the pandemic has detrimental effects on mental-psychological health and that this relationship is, at least in part, modulated by parental bonding and attachment relationships that are experienced at an early age.Methods: A sample of 68 volunteer University students was screened for psychopathological symptoms (SCL-90-R and STAI-Y), stress perception (PSS), attachment style (RQ), and parental care and overcontrol (PBI) 6 months before the confinement. In the same subjects, psychopathological symptoms and stress perception were measured again during confinement.Results: Overall, psychological health and stress management deteriorated across the entire sample during confinement. Specifically, a significant increase in phobic anxiety, depression, psychological distress, and perceived stress was observed. Notably, parental bonding and attachment styles modulated the psychological status during the lockdown. Individuals with secure attachment and high levels of parental care (high care) showed increased levels of state anxiety and perceived stress in phase 2, compared with phase 1. In contrast, individuals with insecure attachment and low levels of parental care (low care) already showed a high rate of state anxiety and perceived stress in phase 1 that did not increase further during phase 2.Conclusion: The general deterioration of psychological health in the entire sample demonstrates the pervasiveness of this stressor, a decline that is partially modulated by attachment style and parental bonding. These results implicated disparate sensitivities to environmental changes in the high- and low care groups during the lockdown, the former of which shows the greatest flexibility in the response to environment, suggesting adequate and functional response to stress in high care individuals, which is not observable in the low care group.

Pearson correlations (r) between study variables (N = 155).

Summary of the existing methods for estimating the attachment kernel Ak. Nonparametric methods are methods that do not assume a functional form for Ak.Summary of the existing attachment kernel estimation methods.