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Fig. 4 in Post-collection taphonomy, sampling effects and the role of the collector in palaeontological collections: A case study from an early Late Triassic bone accumulation in southernmost Brazil

Fig. 4. Comparison between the three institutions (A–C) and relationship with sampling pulses over the years. Histograms are aligned and calibrated with regards to timeline. The dashed rectangle in C indicates the period of collaboration between MCN/SEMA-RS and PUC-RS. Abbreviations: Ap, Abdala pulse; BMp, Bertoni-Machado pulse; dp, discovery pulse; PGPp, "Programa Pró-Guaíba" ("Pró-Guaíba" Program) pulse.

Fig. 6 in Post-collection taphonomy, sampling effects and the role of the collector in palaeontological collections: A case study from an early Late Triassic bone accumulation in southernmost Brazil

Fig. 6. Selected specimens from the three collections showing effects of sullegic (i.e., during sampling activity), trephic (i.e., from transport to preparation and storage) and "taxonomical" factors. A and B show two mandibles of traversodontid cynodonts, of which previously just two out of ten fragments were considered as such, while the rest as indeterminate fragments. In C, several specimens from a single original association, numbered separately, and now together again, still being able to provide taphonomic information. Some of them (e.g., rib fragments) had been associated with similar others and analyzed with systematic interest, losing the taphonomic information. D shows two parts of the same bone (D1, MCP-PV 4017; D2, MCP-PV 4028), a right femur, encountered already separated and isolated, and catalogued as two different specimens, part in D2 being identified as an indeterminate fragment.

Fig. 3 in Post-collection taphonomy, sampling effects and the role of the collector in palaeontological collections: A case study from an early Late Triassic bone accumulation in southernmost Brazil

Fig. 3. Results of the sampling by three institutions (A–C) schematized into the Voorhies Groups (Voorhies 1969, sensu Behrensmeyer 1975; modified), favouring biases in data interpretations and palaeoecological reconstructions. Abbreviations: ifr, indeterminate fragments; ith, isolated teeth; ND, not determinable; VG, Voorhies Groups.

Fig. 2 in Post-collection taphonomy, sampling effects and the role of the collector in palaeontological collections: A case study from an early Late Triassic bone accumulation in southernmost Brazil

Fig. 2. Timeline of the sampling activities carried out at the Schoenstatt site by the three institutions.

Fig. 1 in Post-collection taphonomy, sampling effects and the role of the collector in palaeontological collections: A case study from an early Late Triassic bone accumulation in southernmost Brazil

Fig. 1. Maps showing position of the Santa Maria Supersequence in South America (southern Brazil, Paraná Basin) (A) and the Rio Grande do Sul State (B). C. Location of the outcrops in which the Santacruzodon AZ has been recognized (stars).

Data from: Longer days, larger grays: Carryover effects of photoperiod and temperature in gray treefrogs, Hyla versicolor

Environmental conditions like temperature and photoperiod can strongly shape organisms' growth and development. For many ectotherms with complex life cycles, global change will cause their offspring to experience warmer conditions and earlier-season photoperiods, two variables that can induce conflicting responses. We experimentally manipulated photoperiod and temperature during gray treefrog (Hyla versicolor) larval development to examine effects at metamorphosis and during short (10-day) and long (56-day) periods post-metamorphosis. Both early- and late-season photoperiods (April and August) decreased age and size at metamorphosis relative to the average-season (June) photoperiod, while warmer temperatures decreased age but increased size at metamorphosis. Warmer larval temperatures reduced short-term juvenile growth but had no long-term effect. Conversely, photoperiod had no short-term carryover effect, but juveniles from early- and late-season larval photoperiods had lower long-term growth rates than juveniles from the average-season photoperiod. Similar responses to early- and late-season photoperiods may be due to reduced total daylight compared to average-season photoperiods. However, juveniles from late-season photoperiods selected cooler temperatures than early-season juveniles, suggesting not all effects of photoperiod were due to total light exposure. Our results indicate that despite both temperature and photoperiod affecting metamorphosis, the long-term effects of photoperiod may be much stronger than those of temperature.

Data from: Transgenerational effects of doxycycline and anhydrotetracycline on the microbiome of the Australian sheep blowfly, Lucilia cuprina

Tetracyclines are a family of broad-spectrum antibiotics commonly used in agriculture, medicine, and research. However, exposure to tetracyclines is associated with a wide range of negative health outcomes. In some cases, these negative effects are transgenerational: when individuals are treated with tetracyclines, their untreated offspring exhibit phenotypic abnormalities. The causes of such transgenerational effects are not well-understood, but disruption of the microbiome and/or mitochondria may play an important role. Transgenerational effects from tetracyclines may threaten the success of an environmentally-friendly form of pest control, the release of transgenic males carrying a tetracycline-repressible female lethal gene. In this study, we investigated the direct and transgenerational effects of two tetracycline-class antibiotics, doxycycline (DOX) and anhydrotetracycline (ATC), on the blowfly Lucilia cuprina, a facultative parasite of sheep. To simulate the rearing conditions used in a male-only release program, blowflies were reared on diet alone, or diet plus DOX or ATC, for three generations, then reared for an additional fourth generation off tetracyclines. We used 16S amplicon sequencing and qPCR to examine whole-body microbiome composition and bacterial and mitochondrial DNA abundance in third and fourth generation flies. The microbiomes of third generation flies reared on DOX or ATC were similar in composition and diversity to the microbiomes of flies reared exclusively on the control diet. However, we found that the untreated fourth generation offspring of DOX- or ATC-treated flies displayed major shifts in microbiome composition relative to both their treated parents and untreated control groups. Our study supports a growing body of evidence that tetracyclines exert both direct and transgenerational effects on arthropods, and highlights the need to address these impacts in the context of insect pest management.

Code from: Enhancing data-limited assessments with random effects: A case study on Korea chub mackerel (Scomber japonicus)

<div> <div> <div> In a state-space framework, temporal variations in fishery-dependent processes can be modeled as random effects. This modeling flexibility makes state-space models (SSMs) powerful tools for data-limited assessments. Though SSMs enable the model-based inference of the unobserved processes, their flexibility can lead to overfitting and non-identifiability issues. To address these challenges, we developed a suite of state-space length-based age-structured models and applied them to the Korean chub mackerel (Scomber japonicus) stock. Our research demonstrated that incorporating temporal variations in fishery-dependent processes can rectify model mis-specification but may compromise robustness, which can be diagnosed through a series of model checking processes. To tackle non-identifiability, we used a non- degenerate estimator, implementing a gamma distribution as a penalty for the standard deviation parameters of observation errors. This penalty function enabled the simultaneous estimation of both process and observation error variances with minimal bias, a notably challenging task in SSMs. These results highlight the importance of model checking and the effectiveness of the penalized approach in estimating SSMs. Additionally, we discussed novel assessment outcomes for the mackerel stock. </div> </div> </div>

Psychedelic drug effects on reactivity of the paraventricular nucleus of the hypothalamus and threat responding behavior

Psychedelics have experienced renewed interest following studies suggesting potential therapeutic effects in patients with affective disorders. While clinical results look promising, the neurobiological mechanisms underlying acute and prolonged effects of psychedelics remain unclear. Many psychiatric disorders involve hypothalamic-pituitary-adrenal (HPA) axis dysfunction. The paraventricular nucleus of the hypothalamus (PVN) is a midline hypothalamic nucleus that plays an integral role in HPA stress reactivity, autonomic functioning, social behavior, and many other affective processes. We investigated the effect of psilocin, the psychoactive metabolite of psilocybin, on PVN reactivity in Sprague Dawley rats. Psilocin increased stimulus-independent activity as measured by c-Fos expression in the PVN of male and female rats. Psilocin also increased PVN reactivity (ΔF/F) to an aversive air-puff stimulus in males but not females. PVN reactivity was restored at 2- and 7-days post-injection with no group differences. Additionally, we found that prior psilocin injection did not affect PVN reactivity following acute restraint stress. Experimental groups were sub-classified by baseline threat responding and psilocin-induced increases in male PVN reactivity were found to be driven by baseline active threat responders. Overall, these data demonstrate that the PVN is a significant site of psychedelic drug action with implications for threat responding behavior.

opencc-by-4.0Jun 2024View details →

Effects of personalized music listening on post-stroke cognitive impairment: A randomized controlled trial

Background and purpose: Previous studies have suggested that music listening has the potential to positively affect mood and cognitive functions in individuals with <a name="_Hlk140153246"></a>post-stroke cognitive impairment (PSCI), with a preference for self-selected music likely to yield better outcomes. However, there is insufficient clinical evidence to suggest the use of music listening in routine rehabilitation care to treat PSCI. This randomized control trial (RCT) aims to investigate the effects of personalized music listening on mood improvement, <a name="_Hlk140153263"></a>activities of daily living (ADLs), and cognitive functions in individuals with PSCI. Materials and methods: A total of 34 patients with PSCI were randomly assigned to either the music group or the control group. Patients in the music group underwent a three-month personalized music-listening intervention. The intervention involved listening to a personalized playlist tailored to each individual's cultural, ethnic, and social background, life experiences, and personal music preferences. In contrast, the control group patients listened to white noise as a placebo. Cognitive function, neurological function, mood, and ADLs were assessed. Results: After three months of treatment, the music group showed significantly higher <a name="_Hlk140153278"></a>Montreal Cognitive Assessment (MoCA) scores compared to the control group (p=0.027), particularly in the domains of delayed memory (p=0.019) and orientation (p=0.023). Moreover, the music group demonstrated significantly better scores in <a name="_Hlk140153297"></a>National Institute of Health Stroke Scale (NIHSS) (p=0.008), <a name="_Hlk140153304"></a>Barthel Index (BI) (p=0.019), and <a name="_Hlk140153315"></a>Zarit Caregiver Burden Interview (ZBI) (p=0.008) compared to the control group. No effects were found on mood as measured by the Hamilton Rating Scale for Anxiety (HAMA) and the Hamilton depression scale (HAMD).

opencc-by-4.0Sep 2022View details →

Figure 1 in Effect of degree of water stress on growth and fecundity of velvetleaf (Abutilon theophrOsti) using soil moisture sensors

Figure 1. Soil moisture content in pots was measured using (A) Meter Group 5TM moisture sensors and (B) Em50 data loggers to determine degree of water stress on Abutilon threophrasti in a greenhouse study conducted at the University of Nebraska–Lincoln.

Data from: Status-dependent metabolic effects of social interactions in a group-living fish

Social interactions can sometimes be a source of stress, but social companions can also ameliorate and buffer against stress. Stress and metabolism are closely linked, but the degree to which social companions modulate metabolic responses during stressful situations—and whether such effects differ depending on social rank—is poorly understood. To investigate this question, we studied Neolamprologus pulcher, a group-living cichlid fish endemic to Lake Tanganyika, and measured the metabolic responses of dominant and subordinate individuals when they were either visible or concealed from one another. When individuals could see each other, subordinates had lower maximum metabolic rates and tended to take longer to recover following an exhaustive chase compared to dominants. In contrast, metabolic responses of dominants and subordinates did not differ when individuals could not see one another. These findings suggest that the presence of a dominant individual has negative metabolic consequences for subordinates, even in stable social groups with strong prosocial relationships.

opencc-by-4.0Jun 2024View details →

Supplement to "Discriminating non-stationary flood hazard effects via probabilistic estimation of sparse residuals from rescued and rated stage–discharge data"

This supplement contains the data and script associated with “Sparse hydrometric data rescue for exploratory analyses of conveyance-driven flood hazard trends and controls,” which has been submitted to a journal for consideration. This supplement is deposited on Zenodo.   Code, Data, and Attribute Descriptions   Uploaded are five directories (indicated in bold font, with their contents detailed below) containing input data and various outputs of the analyses performed for our case study on the Pulangi River at Lumayong (Philippines). Please consider this description equivalent to an omnibus README file for the deposited files. Note that we collected and rescued the hydrometric data herein from the archives of the Water Projects Division (WPD) of the Philippine Department of Public Works and Highways (DPWH).   ●      Pln_R_code contains (1) Pln_RC.R, the R script file, and (2) 240601_Pln_RC.RData, which stores objects generated from the script based on the last execution (on 1 June 2024). The script consists of admittedly too many lines of code (e.g., for data wrangling, formal analyses, and producing figures used in the manuscript) that should have been split into multiple .R files. Apologies. Please be guided by the outline and the comments and kindly reach out lest issues with the code arise.   ●      Pln_GH_PDFs contains the scanned gaugekeeper’s reports of gauge heights (“stages”).    ○      The name of each file varies. For example, Pln-GH-1100.pdf contains daily stage readings for all months in the year 2011. But, if the last two digits are not zeroes, as in Pln-GH-1204.pdf, they refer to the month of that year; in this case, for example, the PDF file contains stage data for the month of April in the year 2012. ○      Each scanned sheet contains sub-daily (with readings at “AM,” “NOON,” and “PM”) and mean daily stages for a given month. ○      Also indicated are the gaugekeeper’s remarks on the daily weather (e.g., “fair,” “cloudy”). Under inclement weather, the gaugekeeper would note the duration of rainfall and its intensity and might, at times, record extra stage readings.   ●      Pln_DM_PDFs contains the following PDF files and a sub-directory: ○      Pln-DM-<XXXXXX>.pdf contains the scanned log for each direct stage—discharge measurement, otherwise known as “gaugings.” Each file is named according to the date of gauging (YYMMDD). For example, the log for the gauging performed on 24 February 2011 can be found in the file Pln-DM-110224.pdf. Data from these gaugings are summarized in Pln-DM-filtered.csv in the Pln_In_CSVs directory. ■      The readability of each file varies based on the original quality of the original paper-format data. ■      The first page in each file contains, on the left side, a summary of the gauging data and metadata (e.g., date of measurement, number of gauging verticals or “sections” used, method of crossing or measuring the cross-section), and on the right side, the velocity—area readings at each gauging vertical. ■      The second page in each file contains the plotted cross-section of the channel at the time of measurement. ○      Pln-RC.pdf contains various other paper-format data and some annotations relevant to the historical rating at the station. ■      P. 1: The hydrographic engineer’s comment (dated 19 January 2012) on the evaluation of the discharge data, specifically detailing the periods of validity of the rating curves developed for different sub-periods of monitoring. ■      PP. 2—3: A summary table of all the gaugings performed from 1983 to 2010 whose logs were no longer retrievable (and hence not included as a DM-PDF file in this directory). ■      PP. 4—5: Plots of the official stage—discharge rating curves developed by DPWH hydrographers. ■      PP. 6—8: Rating tables used to convert daily mean stages to deterministic discharge estimates. Two of these rating tables were digitized and can be found in the Pln_RatingTables sub-directory in Pln_In_CSVs. ■      PP. 9—22: Daily stage (m) and its corresponding daily discharge (L/s) for the 2004—2010 sub-period. The stages were digitized and included in Pln-H_arch.csv in the Pln_In_CSVs directory. ○      Pln_DM_unused contains the PDF files of logs (including data and metadata) corresponding to the gaugings that were excluded from our analysis following our filtering step for gauging location consistency.   ●      Pln_In_CSVs contains the following CSV files and two sub-directories; these files were used as inputs to the R script for formal analyses: ○      Pln-H_arch.csv contains the mean daily stage values [“H_bar_arch”] (m) for every day in the 2004—2020 sub-period [“Date”] (YYYY-MM-DD). The stages in this file are already corrected for gross errors. ○      Pln-DM-filtered.csv contains the following information on the gaugings performed on the Pulangi at Lumayong (1983—2020): (i) date [“Date”] (YYYY-MM-DD); (ii) stage [“H”] (m); (iii) discharge in L/s [“Q_lps”] and m3/s [“Q_cms”]; (iv) wetted area [“A_sqm”] (m2); (v) mean flow velocity [“Vel_mps”] (m/s); (vi) channel width [“W_m”] (m); (vii) mean flow depth [“D_ave_m”] (m); (viii) location of the measurement cross-section with respect to the staff gauge, with negative values meaning downstream of the gauge and positive values meaning upstream of the gauge [“XS_loc_wrt_gage”]; (ix) maximum flow depth [“Max_Depth_m”] (m); and (x) minimum streambed elevation [“MINSBE”] (m). Note that this file includes only gaugings that passed our filtering step for measurement location consistency. ○      Pln-DM_oview.csv contains information on the temporal coverage (bounded by “Start_date” and “End_date”) of the available hydrometric data from the station archives. ○      Pln-H_sample_GrossE_corr.csv contains a sample sub-period (2017-06-15 through 2017-11-30) and the corresponding values of stages (m), uncorrected [“H_uncorrected”] and corrected for gross errors [“H_corrected”]. This CSV file was used as an input to the R script to produce one of the figures in the manuscript.  ○      Pln-XS-csv.csv contains data on the gauging transects: gauging ID [“GaugingID”]; date [“Date”] (YYYY-MM-DD); lateral distance from a fixed initial point [“Lat_distance”] (m); width of the gauging vertical [“Width_vert..m.”] (m); depth relative to the water surface [“Depth..m.”] (m); stage at the gauging vertical [“H_m_vert..m.”] (m); and elevation with respect to a fixed arbitrary datum at the station [“Elev..m.”] (m). ○      Pln_Rating_Tables contains two rating tables, Pln-DM - RatingTable_A.csv and Pln-DM - RatingTable_B.csv, prepared and used by DPWH hydrographers for converting stage values to deterministic discharge estimates for the Pulangi River at Lumayong for the 1980s—early 2000s sub-period. Each rating table contains columns for stage [“H”], discharge in L/s [“Q_lps”], and discharge in m3/s [“Q_cms”]. ○      Pln_Q_rated contains two CSV files: Pulangi.csv has the columns “YEAR”, “DAY”, and every month of the year [“JAN” through “DEC”] for the 1983—2003 sub-period, with the values under each month column indicating the deterministic discharge estimates in L/s; Pulangi_trunc.csv contains similarly formatted data, but for the 2009—2010 sub-period.   ●      Pln_Out_CSVs contains two CSV files, the primary outputs of the hydrometric data rescue effort. ○      Pln_Q_recon.csv contains the reconstructed discharge time series (1983—2020) and its associated uncertainties at the 95% credibility interval. It has the following columns: date [“Date”] (YYYY-MM-DD); daily stage [“H”] (m); lower bound of the discharge estimate [“Q_lwr”] (m3/s); median discharge estimate [“Q_med”] (m3/s); and the upper bound of the discharge estimate [“Q_upr”] (m3/s). Pln_H_recon.csv contains the reconstructed and quality-controlled stage time series (1983—2020). It has the following columns: date [“Date”] (YYYY-MM-DD); mean daily stage that has been corrected for gross errors, but not yet filtered through other quality checks [“H_bar_arch”] (m); quality check for low outliers [“Low_Outlier”] (TRUE/FALSE); quality check for flatliners [“Flatliner”] (TRUE/FALSE); difference between the stage values on day i and day i-1 [“Daily_Step”] (m); quality check for large steps [“Large_Step”] (TRUE/FALSE); and the corrected and quality-controlled mean daily stage values [“H”] (m).

Fig. 8 in In situ experiments on the effect of low pH on the ultrastructure of the seagrasses Cymodocea nodosa and Posidonia oceanica Abstract

Fig. 8: A-H. TEM micrographs of young epidermal cells of C. nodosa after three weeks transfer at S2 area. A. Surface view of epidermal cells. They are disorganized and most of the organelles are not easily seen. B. Epidermal cell with wavy cell walls and a central nucleus with loose and partially disrupted nuclear membrane. C. A group of peripherally distributed mitochondria containing a rather amorphous mass of destroyed cristae. D. Dictyosome with rounded and loose cisternae. E. Disorganized chloroplasts with remnants of thylakoids and starch grains. F. Cortical cytoplasmic area with disorganized mitochondria and inflated ER fragments. G. Higher magnification of inflated fragments of RER with attached electron-dense material. H. ER membrane-like network with projecting edges filled with electron-dense material. Scale bars = 2 μm (A), 1μm (B) 0.5μm (C), 0.2 (D, E, F) and 0.1 (G, H).

Fig. 6 in In situ experiments on the effect of low pH on the ultrastructure of the seagrasses Cymodocea nodosa and Posidonia oceanica Abstract

Fig. 6: A-E. TEM micrographs of young epidermal cells of C. nodosa after three weeks transfer at S1 area. A. Group of epidermal cells that appear empty, with most of the cell elements disorganized and distorted. B. Higher magnification of a nucleus with condensed masses of chromatin which covered most of the nucleoplasm. The nuclear membrane appears loose and discontinuous. C. Cytoplasmic area showing dictyosomes with few cisternae and numerous swollen fragments of rough ER (RER) D. Fragmented ER membranes traversing the cortical cytoplasm. E. Disorganized chloroplasts with large starch grains surrounded by a system of electron-dense elongated or round plastoglobuli. Mitochondria with a few broken and sometimes dilated cristae are also observed. Scale bars = 1 μm (A), 0.5μm (B, C, E) and 0.2μm (D).

Fig. 5 in In situ experiments on the effect of low pH on the ultrastructure of the seagrasses Cymodocea nodosa and Posidonia oceanica Abstract

Fig. 5: A-C. TEM micrographs of young epidermal cells of P. oceanica after one week transfer at S2 area. A. Epidermal cell with increased number of chloroplasts and mitochondria. B. Chloroplast with oval-shaped and rod-like plastoglobuli around starch grains. Mitochondria with very few fragmented cristae are also visible. C. Dictyosomes and fragmented ER network extended along the cell periphery. Scale bars = 1 μm (A), and 0.5μm (B, C).

Fig. 9 in In situ experiments on the effect of low pH on the ultrastructure of the seagrasses Cymodocea nodosa and Posidonia oceanica Abstract

Fig. 9: A-F. TEM micrographs of young epidermal cells of P. oceanica after three weeks transfer at S2 area. A. Group of epidermal cells that appear distorted, with wavy cell walls. B. Part of an epidermal cell with a central nucleus with disorganized nuclear membrane. The nucleus is surrounded by remnants of cell organelles and an electron-dense ER network. C. Chloroplasts with remnants of thylakoids and plastoglobuli, and disorganized mitochondria. Both appear empty and destroyed. D. Starch grains from disorganized chloroplasts appear dispersed in the cytoplasm. E. Cytoplasmic area with structures of ER network connected and/or filled with electron-dense material. F. Higher magnification of inflated, swollen RER cisternae, filled with electron-dense material. Scale bars = 2 μm (A), 1μm (B) 0.2 (C, D, E,) and 0.1 (F).

Fig. 1 in In situ experiments on the effect of low pH on the ultrastructure of the seagrasses Cymodocea nodosa and Posidonia oceanica Abstract

Fig. 1: A-E. TEM micrographs of young epidermal cells of C. nodosa control material. A. Paradermal section of an epidermal cell. Note its orthogonal shape, the dense cytoplasm, and the large nucleus occupying most of the cell space. B. Higher magnification of the peripheral part of the cell of Fig. A, showing the cell wall and cortical endoplasmic reticulum (ER). C. Cytoplasmic area taken from a plant transferred for one week to S1 area. Note the increased number of mitochondria, dictyosomes and ER, compared to the control. D. Epidermal cell after transfer for one week from S1. It shows a prominent central nucleus, undifferentiated chloroplasts with few grana and an increased number of mitochondria and ER membranes. E. Higher magnification of a cortical cytoplasmic area of a cell like D showing an extended ER network distributed in the cell periphery. Scale bars = 2 μm (A), 1μm (D) and 0.2μm (B, C, E).

Fig. 3 in In situ experiments on the effect of low pH on the ultrastructure of the seagrasses Cymodocea nodosa and Posidonia oceanica Abstract

Fig. 3: A-E. Interphase epidermal cells of young leaves under different pH levels. In all figures, green represents tubulin immunofluorescence and blue represents Hoechst staining of DNA. A. Transfer of CN to pH 7.8 for 1 week: thick MT bundles showing a slightly aberrant orientation. B. Transfer of PO to pH 7.8 for 1 week: MT bundles oriented perpendicularly to the long leaf axis. C. Transfer of CN to pH 6.8 for 1 week: fragmented MT bundles with slightly aberrant orientations. D. Transfer of CN to pH 7.8 for 3 weeks: short, fragmented, and curved MT bundles with aberrant orientations. E. Transfer of PO at pH 7.8 for 3 weeks: depolymerization and disassembly of interphase MTs with loss of proper orientation. Scale bar = 10 μm.

Fig. 4 in In situ experiments on the effect of low pH on the ultrastructure of the seagrasses Cymodocea nodosa and Posidonia oceanica Abstract

Fig. 4: A-C. TEM micrographs of young epidermal cells of C. nodosa after one week transfer at S2 area. A. Epidermal cell with undifferentiated chloroplasts and increased number of mitochondria. B. Higher magnification of a chloroplast with a few developing grana. C. Higher magnification of a mitochondrion with very few cristae. Scale bars = 0.5 μm (A, B, C).