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AbstractOver decades, public procurement in Tanzania experienced critical reforms; however, not much is known about the reforms and hence there is a dearth of comprehensive reviews about them. The current study reviews existing literature relating to public procurement reforms, practices, and compliance in Tanzania. By employing a systematic literature review, the study draws upon 65 publications from Scopus and Google Scholar databases. Findings unveil that the implementation of public procurement laws and regulations has significantly improved transparency, accountability, and fairness in public procurement undertakings. The foundation for a well-organized institutional framework that emphasizes decentralization, standardization, and governance over public procurement has also been established by these reforms. Despite these positive contributions, certain reforms have introduced challenges due to interference and uncoordinated efforts that hamper public procurement activities. The study exclusively focuses on journal articles from Scopus and Google Scholar, excluding other publication forms like book reviews and conference proceedings. While acknowledging this limitation, the article serves as the pioneering systematic review profiling public procurement reforms in Tanzania, shedding light on professional dilemmas and compliance issues. Given the limited literature on the subject, this study enriches the existing knowledge and offers valuable insights for scholars, procurement practitioners, public entities, and stakeholders.

Plant electrophysiology has unveiled the involvement of electrical signals in the physiology and behavior of plants. Spontaneously generated bioelectric activity can be altered in response to changes in environmental conditions, suggesting that a plant’s electrome may possess a distinct signature associated with various stimuli. Analyzing electrical signals, particularly the electrome, in conjunction with Machine Learning (ML) techniques has emerged as a promising approach to classify characteristic electrical signals corresponding to each stimulus. This study aimed to characterize the electrome of common bean (Phaseolus vulgaris L.) cv. BRS-Expedito, subjected to different water availabilities, seeking patterns linked to these stimuli. For this purpose, bean plants in the vegetative stage were subjected to the following treatments: (I) distilled water; (II) half-strength Hoagland’s nutrient solution; (III) −2 MPa PEG solution; and (IV) −2 MPa NaCl solution. Electrical signals were recorded within a Faraday’s cage using the MP36 electronic system for data acquisition. Concurrently, plant water status was assessed by monitoring leaf turgor variation. Leaf temperature was additionally measured. Various analyses were conducted on the electrical time series data, including arithmetic average of voltage variation, skewness, kurtosis, Probability Density Function (PDF), autocorrelation, Power Spectral Density (PSD), Approximate Entropy (ApEn), Fast Fourier Transform (FFT), and Multiscale Approximate Entropy (ApEn(s)). Statistical analyses were performed on leaf temperature, voltage variation, skewness, kurtosis, PDF µ exponent, autocorrelation, PSD β exponent, and approximate entropy data. Machine Learning analyses were applied to identify classifiable patterns in the electrical time series. Characterization of the electrome of BRS-Expedito beans revealed stimulus-dependent profiles, even when alterations in water availability stimuli were similar in terms of quality and intensity. Additionally, it was observed that the bean electrome exhibits high levels of complexity, which are altered by different stimuli, with more intense and aversive stimuli leading to drastic reductions in complexity levels. Notably, one of the significant findings was the 100% accuracy of Small Vector Machine in detecting salt stress using electrome data. Furthermore, the study highlighted alterations in the plant electrome under low water potential before observable leaf turgor changes. This work demonstrates the potential use of the electrome as a physiological indicator of the water status in bean plants.

Abstract Background Expansion of genomic resources for the Pacific white shrimp (Litopenaeus vannamei), such as the construction of dense genetic linkage maps, is crucial for the application of genomic tools in order to improve economically relevant traits. Sexual dimorphism exists in Pacific white shrimp, and the mapping of the sex-determination region in this species may help in future reproductive applications. We have constructed male, female, and sex-averaged high-density genetic maps using a 50 K single-nucleotide polymorphism (SNP) array, followed by a genome-wide association study (GWAS) to identify genomic regions associated with sex in white shrimp. Results The genetic map yielded 15,256 SNPs assigned to 44 linkage groups (LG). The lengths of the male, female, and sex-averaged maps were 5,741.36, 5,461.20 and 5,525.26 cM, respectively. LG18 was found to be the largest for both sexes, whereas LG44 was the shortest for males and LG31 for females. A sex-determining region was found in LG31 with 21 statistically significant SNPs. The most important SNP was previously identified as a sex-linked marker and was able to identify 99% of the males and 88% of the females. Although other significant markers had a lower ability to determine sex, putative genes were intercepted or close to them. The oplophorus-luciferin 2-monooxygenase, serine/arginine repetitive matrix protein and spermine oxidase genes were identified as candidates with possible participation in important processes of sexual differentiation in shrimp. Conclusions Our results provide novel genomic resources for shrimp, including a high-density linkage map and new insights into the sex-determining region in L. vannamei, which may be usefulfor future genetics and reproduction applications.

This study contributes taxonomic information on the genus Eutimesius Roewer, 1913. Three new species are described: the sympatric species E. aroa sp. nov. and E. guaichia sp. nov. from Yaracuy state and E. canoabo sp. nov. from Carabobo state in Venezuela. The male of E. ephippiatus (Roewer, 1915) is described for the first time. Remarks are made on the distribution of E. ornatus, and a complimentary description of male genitalia is provided for E. simoni Roewer, 1913. New departmental records are added for E. ephippiatus and E. simoni. An updated distribution map and a key to the identification of the males of the species in the genus are presented.

Implementing insect monitoring systems provides an excellent opportunity to create accurate interventions for insect control. However, selecting the appropriate time for an intervention is still an open question due to the inherent difficulty of implementing on-site monitoring in real-time. A possible solution to enhance decision-making is to apply forecasting methods to predict insect abundance. However, another layer of complexity is added when other covariates are considered in the forecasting, such as climate time series collected along the monitoring system. Multiple combinations of climate time series and their lags can be used to build a forecasting method. Therefore, we propose a new approach to address this problem by combining statistics, machine learning, and time series embedding. We used two datasets containing a time series of aphids and climate data collected weekly in two municipalities in Southern Brazil for eight years. We conduct a simulation study based on a probabilistic autoregressive model with exogenous time series based on Poisson and negative binomial distributions to evaluate the performance of our approach. We pre-processed the data using our newly proposed approach and more straightforward approaches commonly used to train learning algorithms. We evaluate the performance of the selected algorithms by looking at the Pearson correlation and Root Mean Squared Error obtained using one-step-ahead forecasting. Based on Random Forests, Lasso-regularised linear regression, and LightGBM regression algorithms, we showed the feasibility of our novel approach, which yields competitive forecasts while automatically selecting insect abundances, climate time series and their lags to aid forecasting.

COVID-19 induces acute and persistent neurological symptoms in mild and severe cases. Proposed concomitant mechanisms include direct viral infection and strain, coagulopathy, hypoxia, and neuroinflammation. However, underlying molecular alterations associated with multiple neurological outcomes in both mild and severe cases are majorly unexplored. To illuminate possible mechanisms leading to COVID-19 neurological disease, we retrospectively investigated in detail a cohort of 35 COVID-19 mild and severe hospitalized patients presenting neurological alterations subject to clinically indicated cerebrospinal fluid (CSF) sampling. Clinical and neurological investigation, brain imaging, viral sequencing, and cerebrospinal CSF analyses were carried out. We found that COVID-19 patients presented heterogeneous neurological symptoms dissociated from lung burden. Nasal swab viral sequencing revealed a dominant strain at the time of the study, and we could not detect traces of SARS-CoV-2's spike protein in patients' CSF by multiple reaction monitoring analysis. Patients presented ubiquitous systemic hyper-inflammation and broad alterations in CSF proteomics related to inflammation, innate immunity, and hemostasis, irrespective of COVID-19 severity or neuroimaging alterations. Elevated CSF interleukin-6 (IL6) correlated with disease severity (sex-, age-, and comorbidity-adjusted mean Severe 24.5 pg/ml, 95% confidence interval (CI) 9.62–62.23 vs. Mild 3.91 pg/mL CI 1.5–10.3 patients, p = 0.019). CSF tumor necrosis factor-alpha (TNFα) and IL6 levels were higher in patients presenting pronounced neuroimaging alterations compared to those who did not (sex-, age-, and comorbidity-adjusted mean TNFα Pronounced 3.4, CI 2.4–4.4 vs. Non-Pronounced 2.0, CI 1.4–2.5, p = 0.022; IL6 Pronounced 33.11, CI 8.89–123.31 vs Non-Pronounced 6.22, CI 2.9–13.34, p = 0.046). Collectively, our findings put neuroinflammation as a possible driver of COVID-19 acute neurological disease in mild and severe cases.

Abstract Latent autoimmune diabetes in adults (LADA) is a heterogeneous disease characterized by autoantibodies against insulin producing pancreatic beta cells and initial lack of need for insulin treatment. The aim of the present study was to investigate if individuals with LADA have an altered gut microbiota relative to non-diabetic control subjects, individuals with type 1 diabetes (T1D), and individuals with type 2 diabetes (T2D). Bacterial community profiling was performed with primers targeting the variable region 4 of the 16S rRNA gene and sequenced. Amplicon sequence variants (ASVs) were generated with DADA2 and annotated to the SILVA database. The gut virome was sequenced, using a viral particle enrichment and metagenomics approach, assembled, and quantified to describe the composition of the viral community. Comparison of the bacterial alpha- and beta-diversity measures revealed that the gut bacteriome of individuals with LADA resembled that of individuals with T2D. Yet, specific genera were found to differ in abundance in individuals with LADA compared with T1D and T2D, indicating that LADA has unique taxonomical features. The virome composition reflected the stability of the most dominant order Caudovirales and the families Siphoviridae, Podoviridae, and Inoviridae, and the dominant family Microviridae. Further studies are needed to confirm these findings.

Abstract Background Visceral leishmaniasis (VL), or kala-azar, is a common comorbidity in patients with AIDS in endemic areas. Many patients continue to experiences relapses of VL despite virological control, but with immunological failure. These patients remain chronically symptomatic with hypersplenism, for example with anemia, leukopenia, and thrombocytopenia, and are at risk of severe co-infection due to low CD4+ count. Therefore, in this study, splenectomized patients with VL and HIV infection were investigated to understand why the CD4+ count fails to recover in these patients, evaluating the importance of spleen mass for hypersplenism and immunological failure. Methods From a retrospective open cohort of 13 patients who had previously undergone splenectomy as salvage therapy for relapsing VL, 11 patients with HIV infection were investigated. This study compared the patients’ complete blood cell count (CBC) and CD4+ and CD8+ cell counts before and after splenectomy with respect to spleen weight. Results CBC was substantially improved after splenectomy, indicating hypersplenism. However, to the best of our knowledge, this is the first study to show that spleen mass is strongly and negatively correlated with CD4+ cell count (ρ = −0.71, P = 0.015). Conclusions This finding was unexpected, as the spleen is the most extensive lymphoid tissue and T-lymphocyte source. After reviewing the literature and reasoning, we hypothesized that the immunological failure was secondary to CD4+ loss initially by apoptosis in the spleen induced by productive HIV infection and, subsequently, by pyroptosis sustained by parasitic infection in spleen macrophages. Graphical Abstract

In this work, the surfactant cetyltrimethylammonium bromide (CTAB) was applied to observe how increasing the surfactant's concentration will affect the MgO characteristics, such as the increase in vacancies. The samples were characterized by X-ray diffraction (XRD). For the MgO-0.025CTAB sample, the intensity of the (200) peak of MgO decreased by three. However, the MgO-2.5CTAB showed an increase in the peaks intensity. In addition to using Rietveld refinement, it is possible to observe the textural characteristics of the samples, with the introduction of CTAB, oxygen vacancies increased, and from the MgO to the MgO-0.025CTAB sample, there was a decrease in oxygen occupancy from 94% to 82% in the unit cell. Thermogravimetry (TG) analyses were used to understand the interactions between the support and the surfactant as the CTAB concentration increased. With the physisorption of N2, the behavior of the sample pores and specific area determination are verified. The introduction of CTAB caused the decrease of the specific area from 32 m2/g to 9 m2/g for the MgO and MgO-0.025CTAB samples. However, for a more concentrated surfactant, MgO-2.5CTAB, the specific area was 25 m2/g. Scanning electron microscopy made it possible to observe the increase in the roughness with CTAB presence.

Water reuse for irrigation is a common practice globally, serving as an alternative to clean water. Wastewater contains traces of heavy metals that accumulate in the soil and food chain, posing an environmental and public risk. This study investigated the effect of irrigation with treated domestic wastewater (TDW) emanating from a homogenous community on heavy metal accumulation in the soil irrigated for three recurring farming cycles, namely R1, R2, and R3. A greenhouse experiment was conducted involving plots irrigated with TDW (PTw) and plots irrigated with fresh water (PFw) in triplicate. Soil samples were collected at depths of 0–20, 20–40, and 40–60 cm. Results revealed that heavy metals Pb, Cu, Cr, Zn, Cd, and Ni remained within the WHO permissible limits in the PTw and PFw, except Cd at 40–60 cm after the R3 in the TPw. Irrigation with TDW caused a decrease in Pb and Cd with respect to the baseline levels by 86–91% and 88–96% respectively. Other heavy metals increased in the soil in the order of Cr>Cu>Ni>Zn at 0–20 cm, Cr>Cu>Zn>Ni at 20–40 cm, and Cr>Cu>Ni>Zn at 40–60 cm. Variations in heavy metal concentrations were inconsistent with farming cycles except for Cu, which increased in the order of 3.2±0.75, 4.4±0.66, and 4.8±1.23 mg/kg at 0–20 cm for R1, R2, and R3, respectively, and 3.4±0.66, 3.7±0.62, and 6.0±0.44 mg/kg at 20–40 cm in the same order. Pollution index values revealed that irrigation with TDW for three recurring farming cycles caused slight soil contamination (1≤PI

This systematic review focuses on an increasing subset of traumatic brain injury (TBI) survivors who develop post-traumatic parkinsonism (PTP), characterized by slowness of movement (bradykinesia), rigidity (stiffness), postural instability, and resting tremors caused by obstruction or damage to deep brain structures of the basal ganglia. PTP is rare, and one hypothesis to explain PTP rarity is that TBIs severe enough to affect deep brain structures are often lethal; however, with increasing survivability of TBIs, these numbers are expected to increase. The goal of this review is to raise awareness of an expected global increase of a subgroup of TBI patients who are treatment responsive and report therapeutic results aiding providers in diagnosing, educating, and treating PTP patients. Literature over the past 100 years was considered, and 44,663 peer-reviewed articles were identified. Inclusion criteria required a clinical indication of parkinsonian signs and TBI. Twenty-six case reports were ultimately included from which 36 individual patient data points were extracted for this review. Between 1980 and 2010, there has been an increase in reporting of PTP decade after decade. Forty-seven percent of PTP cases have 1?6 months of latency to symptom onset, and 83% of cases were male. PTP can occur with or without presence of brain lesions, and the most common type of injuries that cause PTP are motor vehicle accidents followed by falls. PTP patients are responsive to surgery or medication treatments. Further detail on PTP symptomology, treatment responsiveness, and injury types is provided.

Abstract The investigation of the effects of prenatal cocaine exposure (PCE) on offspring has been inconsistent, with few studies investigating biological outcomes in humans. We profiled genome-wide DNA methylation (DNAm) of umbilical cord blood (UCB) from newborns with (n = 35) and without (n = 47) PCE. We used DNAm data to (1) assess pediatric epigenetic clocks at birth and (2) to estimate epigenetic scores (ES) for lifetime disorders. We generated gestational epigenetic age estimates (DNAmGA) based on Knight and Bohlin epigenetic clocks. We also investigated the association between DNAmGA and UCB serum brain-derived neurotrophic factor (BDNF) levels. Considering the large-scale DNAm data availability and existing evidence regarding PCE as a risk for health problems later in life, we generated ES for tobacco smoking, psychosis, autism, diabetes, and obesity. A gene ontology (GO) analysis on the CpGs included in the ES with group differences was performed. PCE was associated with lower DNAmGA in newborns, and this effect remained significant when controlling for potential confounders, such as blood cell type composition predicted by DNAm and obstetric data. DNAmGA was negatively correlated with BDNF levels in the serum of UCB. Higher tobacco smoking, psychosis, and diabetes ES were found in the PCE group. The GO analysis revealed GABAergic synapses as a potential pathway altered by PCE. Our findings of decelerated DNAmGA and ES for adverse phenotypes associated with PCE, suggest that the effects of gestational cocaine exposure on the epigenetic landscape of human newborns are detectable at birth.

Abstract Suicide attempt (SA) risk is elevated in individuals with bipolar disorder (BD), and DNA methylation patterns may serve as possible biomarkers of SA. We conducted epigenome-wide association studies (EWAS) of blood DNA methylation associated with BD and SA. DNA methylation was measured at >700,000 positions in a discovery cohort of n = 84 adults with BD with a history of SA (BD/SA), n = 79 adults with BD without history of SA (BD/non-SA), and n = 76 non-psychiatric controls (CON). EWAS revealed six differentially methylated positions (DMPs) and seven differentially methylated regions (DMRs) between BD/SA and BD/non-SA, with multiple immune-related genes implicated. There were no epigenome-wide significant differences when BD/SA and BD/non-SA were each compared to CON, and patterns suggested that epigenetics differentiating BD/SA from BD/non-SA do not differentiate BD/non-SA from CON. Weighted gene co-methylation network analysis and trait enrichment analysis of the BD/SA vs. BD/non-SA contrast further corroborated immune system involvement, while gene ontology analysis implicated calcium signalling. In an independent replication cohort of n = 48 BD/SA and n = 47 BD/non-SA, fold changes at the discovery cohort’s significant sites showed moderate correlation across cohorts and agreement on direction. In both cohorts, classification accuracy for SA history among individuals with BD was highest when methylation at the significant CpG sites as well as information from clinical interviews were combined, with an AUC of 88.8% (CI = 83.8–93.8%) and 82.1% (CI = 73.6–90.5%) for the combined epigenetic-clinical classifier in the discovery and replication cohorts, respectively. Our results provide novel insight to the role of immune system functioning in SA and BD and also suggest that integrating information from multiple levels of analysis holds promise to improve risk assessment for SA in adults with BD.

Over the last three decades, stroke care has undergone significant transformations mainly driven by the introduction of reperfusion therapy and the organization of systems of care. Patients receiving treatment through a well-structured stroke service have a much higher chance of favorable outcomes, thereby decreasing both disability and mortality. In this article, we reviewed the scientific evidence for stroke reperfusion therapy, including thrombolysis and thrombectomy, and its implementation in the public health system in Brazil.

We investigate the topological phase transitions driven by band warping, λ, and a transverse magnetic field, B, for three-dimensional Weyl semimetals. First, we use the Chern number as a mathematical tool to derive the topological λ×B phase diagram. Next, we associate each of the topological sectors to a given angular momentum state of a rotating wave packet. Then we show how the position of the Weyl nodes can be manipulated by a transverse external magnetic field that ultimately quenches the wave packet rotation, first partially and then completely, thus resulting in a sequence of field-induced topological phase transitions. Finally, we calculate the current-induced magnetization and the anomalous Hall conductivity of a prototypical warped Weyl material. Both observables reflect the topological transitions associated with the wave packet rotation and can help to identify the elusive 3D quantum anomalous Hall effect in three-dimensional, warped Weyl materials.

IntroductionSleep and stress processes shape executive function. Evidence suggests that poor sleep regulation can lead to significant impairments in executive functions. Psychological stress can also directly impact a variety of executive functions, often leading to declines, but may additionally reduce executive function via its negative impact on sleep. Rates of perceived stress and poor sleep have skyrocketed in recent years. As such, it has become increasingly important to understand how daily stress exposures and sleep processes modulate executive functions.MethodsIn a remote 21-day app-based study, 227 participants completed sleep and stress assessments three times a day. They also completed three executive functioning tasks at various timepoints across the 21-day study interval that assessed cognitive inhibition (Emotional Stroop task), cognitive flexibility (Trail Making Test A and B), and working memory (Backwards Digit Span).ResultsParticipants with consistent sleep/wake schedules reported fewer acute stress events when compared to those with inconsistent sleep schedules. Those with greater sleep/wake regularity also had faster responses to self-relevant negative probes (vs. general negative and neutral) in the Stroop task. Further, variability in sleep/wake timing and reported acute stress exposures across the 21-day study interval interacted to predict performance on the Emotional Stroop task. Specifically, as the number of acute stress events experienced across the 21-day interval increased, participants with more regular sleep schedules had slower overall response times on the Stroop. Higher acute stress exposures led to specific response time delays to neutral and self-relevant negative probes for those with high sleep/wake regularity. We found no impact of the number of acute stress events or stress intensities on working memory span, Stroop accuracy, or Trails response time.DiscussionThese data may indicate that sleep/wake regularity preserves adaptive inhibitory control responses to cumulative acute stress.

ABSTRACT: Two trials were carried out to develop and validate linear regression equations for body composition prediction using Dual-energy X-ray absorptiometry (DEXA). In Trial 1, 300 Cobb500 male chickens raised from 1 to 42 d of age were scanned in DEXA to estimate total weight, fat mass, soft lean tissue (SLT) mass, bone mineral content (BMC), and fat percentage. DEXA estimates were compared to body ash, crude fat, SLT (sum of protein and water) and scale body weight. The dataset was split, with 70% used for prediction equations development and 30% for testing, and the 5k-fold cross-validation analysis was used to optimize the equations. The R2, mean absolute error (MAE), and root-mean-squared error (RMSE) were used as precision and accuracy indicators. A negative correlation (ρ = ˗0.27) was observed for ash content, while no correlation was observed for protein content (P > 0.05). Predictive linear equations were developed to assess broiler weight (R2 = 0.999, MAE = 25.12, RMSE = 38.99), fat mass (R2 = 0.981, MAE = 13.87, RMSE = 21.28), ash mass (R2 = 0.956, MAE = 3.98, RMSE = 5.61), SLT mass (R2 = 0.997, MAE = 35.73, RMSE = 52.45), water mass (R2 = 0.997, MAE = 29.56, RMSE = 43.94), protein mass (R2 = 0.989, MAE = 12.94, RMSE = 19.05), fat content (R2 = 0.855, MAE = 0.81, RMSE = 1.05), SLT content (R2 = 0.658, MAE = 1.01, RMSE = 1.28), and water content (R2 = 0.678, MAE = 0.99, RMSE = 1.27). All equations passed the test. In Trial 2, 395 Cobb500 male chickens were raised from 1 to 42 d of age and used for validation of prediction equations. The equations developed for weight, fat mass, ash mass, SLT mass, water mass, and protein mass were validated. In conclusion, DEXA was found to be an effective approach for measuring the body composition of broilers when using predictive equations validated in this study for estimate calibration.

Visceral leishmaniasis (VL) results from protozoa Leishmania infantum and L. donovani infection. This study investigated whether host factors would explain the relapses. First, susceptibility to amphotericin B of L. infantum isolates was evaluated in vitro. Then, clinical data and the lipid profile of patients with relapsing and non-relapsing VL were assessed. Susceptibility to amphotericin B was similar between the isolates. CD4+ lymphocytes were reduced in both groups of patients in the first episode and with relapsing VL. Still, the strongest blood cell indicator associated with relapses was low total lymphocyte counts. Total plasma cholesterol, high-density lipoprotein, low-density lipoprotein, and, uniquely, triglycerides of the six individuals in the first episode and twenty-three with relapsing VL were lower in relapsing patients than those in the first episode. Deceased patients had extremely low low-density lipoprotein. After CD4+ decreases, lymphocyte CD8+ reduction is the final stage of immunological failure. The lower lipid concentrations appear to be secondary to the depletion of fat stores by inflammation-induced cachexia and fat exhaustion provoked by the co-occurrence of both diseases, which can finally lead to death.

Metal halide perovskites have the potential to contribute to renewable energy needs as a high efficiency, low-cost alternative for photovoltaics. Initial power conversion efficiencies are superb, but improvements to the operational stability of perovskites are needed to enable extensive deployment. Mechanical stress is an important, but often misunderstood factor impacting chemical degradation and reliability during thermal cycling of perovskites. In this manuscript, we find that a commonly used equation based on the coefficient of thermal expansion (CTE) mismatch between perovskite and substrate fails to accurately predict residual stress following solution-based film formation. For example, despite similar CTEs there is a 60 MPa stress difference between narrow bandgap “SnPb perovskite” Cs0.25FA0.75Sn0.5Pb0.5I3 and “triple cation perovskite” Cs0.05MA0.16FA0.79Pb(I0.83Br0.17)3. A combination of in situ absorbance and substrate curvature measurements are used to demonstrate that partial attachment prior to the anneal can reduce residual stress and explain wide stress variations in perovskites.

The Armadillidae are the most diverse family within the Oniscidea, widely distributed around the world. To date, only seven species of the family are known from Colombia. After the examination of a collection from the Colombian departments of Atlántico, Bolívar, Cesar, Magdalena, Risaralda, Santander, and Sucre, eight species were recognized as belonging to the genus Ctenorillo, of which six are considered to be new to Science: C. binomio n. sp., C. humboldti n. sp., C. mincaensis n. sp., C. orientalis n. sp., C. papagayoensis n. sp., and C. tayrona n. sp. Moreover, the distribution knowledge of C. dazai and C. tuberosus has expanded. Ctenorillo species in Colombia are predominantly distributed in Tropical Dry Forest areas, which is one of the most endangered ecosystems in the world. Considering the new taxa presented here, allied with other Oniscidea groups, there is an urgent need to raise the awareness level regarding the conservation status of this ecosystem in the country.

Abstract Wildlife translocations are increasingly used to combat declining biodiversity worldwide. Successful translocation often hinges on coexistence between humans and wildlife, yet not all translocation efforts explicitly include human dimensions (e.g., economic incentives, education programs, and conflict reduction assistance). To evaluate the prevalence and associated outcomes of including human dimensions as objectives when planning translocations, we analyze 305 case studies from the IUCN’s Global Re-Introduction Perspectives Series. We find that fewer than half of all projects included human dimension objectives (42%), but that projects including human dimension objectives were associated with improved wildlife population outcomes (i.e., higher probability of survival, reproduction, or population growth). Translocation efforts were more likely to include human dimension objectives if they involved mammals, species with a history of local human conflict, and local stakeholders. Our findings underscore the importance of incorporating objectives related to human dimensions in translocation planning efforts to improve conservation success.

We examine predictors of COVID-19 cases in Native nations during the early months of the pandemic. We find that where Native American representation and Native American political power in state politics were greater, COVID-19 cases on tribal lands were fewer. We expand the literatures on descriptive representation and on tribal-state relations by demonstrating consequences of powerful Native American voices in the statehouse. We find that Native American voices on tribal lands are also vital. Tribal lands that had extensive networks of community-based health facilities and tribally controlled health facilities recorded fewer COVID-19 cases. The broader lesson here is that if Native nations are to protect their citizens, they need outside governments that support, not thwart. Our findings draw on unique, original quantitative analysis.

Abstract We calculate the primordial power spectrum of tensor perturbations, within the emergent universe scenario, incorporating a version of the Continuous Spontaneous Localization (CSL) model as a mechanism capable of: breaking the initial symmetries of the system, generating the perturbations, and also achieving the quantum-to-classical transition of such perturbations. We analyze how the CSL model modifies the characteristics of the B-mode CMB polarization power spectrum, and we explore their differences with current predictions from the standard concordance cosmological model. We have found that, regardless of the CSL mechanism, a confirmed detection of primordial B-modes that fits to a high degree of precision the shape of the spectrum predicted from the concordance $$\Lambda $$ Λ CDM model, would rule out one of the distinguishing features of the emergent universe. Namely, achieving a best fit to the data consistent with the suppression observed in the low multipoles of the angular power spectrum of the temperature anisotropy of the CMB. On the contrary, a confirmed detection that accurately exhibits a suppression of the low multipoles in the B-modes, would be a new feature that could be considered as a favorable evidence for the emergent scenario. In addition, we have been able to establish an upper bound on the collapse parameter of the specific CSL model used.

Los arrecifes coralinos mesofóticos hacen parte del objeto de conservación del Parque Nacional Natural Corales de Profundidad (PNNCPR). Un paso fundamental para el manejo de un área protegida es la caracterización de su riqueza específica, y uno de los grupos taxonómicos importantes en ambientes arrecifales son los foraminíferos bentónicos. Debido a que no existen investigaciones de este tipo para el PNNCPR, se consideró estudiar los géneros de foraminíferos bentónicos de las zonas mesofótica superior y media, y explorar una posible relación de dicha composición con sus ámbitos geográficos y batimétricos, así como con cambios ambientales. Los resultados permitieron concluir que una submuestra de 50 individuos con conchillas en buen estado, tomadas de diez muestras de 10 g, fue suficiente para estimar la composición de géneros presentes en la zona. La riqueza de géneros encontrada fue de 53, siendo Amphistegina, Quinqueloculina y Triloculina los que presentaron mayor frecuencia de aparición. No se encontraron diferencias significativas entre el conjunto de géneros de foraminíferos bentónicos de los estratos de profundidad superior (34-60 m) y medio (61-90 m). El conjunto de foraminíferos bentónicos del sector Bajo Calamarí difiere significativamente del encontrado en la localidad de Bajo Frijol. El análisis conjunto de la similaridad de muestras mediante clasificación y ordenación permitió identificar tres grupos congruentes con el sitio de muestreo, la época del año y el año de recolecta. El grupo de foraminíferos heterótrofos (Quinqueloculina, Triloculina, Cibicides, Discorbis, Rosalina, Poroeponides y Textularia) fue el más frecuente, seguido por el de los foraminíferos simbiontes (Amphistegina) y oportunistas (Elphidium). Los resultados obtenidos permiten sugerir que los foraminíferos bentónicos mesofóticos tienen potencial de ser bioindicadores para el programa de monitoreo del PNNCPR.

Based on the available literature and a review of collections of organisms, a checklist of 69 myriapod species was made for the Colombian Caribbean region; two symphyls, 15 Chilopods, and 52 Diplopods. In total, 20 families (one from Symphyla, five from Chilopoda, and 14 from Diplopoda), from 11 orders (one from Symphyla, three from Chilopoda, and seven from Diplopoda). Each species's geographical range by department, altitud, reference collection, and bibliographic source were included. The presence in Colombian collections of diplopod specimens that are new records of their taxonomic group for the region, such as Chondrodesmus cf. riparius (Chelodesmidae), two species of Fuhrmannodesmidae, three of Paradoxosomatidae and one of Lophoproctidae. Likewise, two species of Scolopendrellidae of the class Symphyla. This demonstrates the urgent need to complete the essential diversity inventories of the main groups of organisms in the face of the alarming environmental deterioration to which the Colombian Caribbean region is subjected.

Abstract Population studies have shown that traumatic brain injury (TBI) is associated with an increased risk for Parkinson’s disease (PD) and among U.S. Veterans with a history of TBI this risk is 56% higher. The most common type of TBI is mild (mTBI) and often occurs repeatedly among athletes, military personnel, and victims of domestic violence. PD is classically characterized by deficits in fine motor movement control resulting from progressive neurodegeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc) midbrain region. This neurodegeneration is preceded by the predictable spread of characteristic alpha synuclein (αSyn) protein inclusions. Whether repetitive mTBI (r-mTBI) can nucleate PD pathology or accelerate prodromal PD pathology remains unknown. To answer this question, an injury device was constructed to deliver a surgery-free r-mTBI to rats and human-like PD pathology was induced by intracranial injection of recombinant αSyn preformed fibrils. At the 3-month endpoint, the r-mTBI caused encephalomalacia throughout the brain reminiscent of neuroimaging findings in patients with a history of mTBI, accompanied by astrocyte expansion and microglial activation. The pathology associated most closely with PD, which includes dopaminergic neurodegeneration in the SNpc and Lewy body-like αSyn inclusion burden in the surviving neurons, was not produced de novo by r-mTBI nor was the fibril induced preexisting pathology accelerated. r-mTBI did however cause aggregation of phosphorylated Tau (pTau) protein in nigra of rats with and without preexisting PD-like pathology. pTau aggregation was also found to colocalize with PFF induced αSyn pathology without r-mTBI. These findings suggest that r-mTBI induced pTau aggregate deposition in dopaminergic neurons may create an environment conducive to αSyn pathology nucleation and may add to preexisting proteinaceous aggregate burden.

Heavy metals are necessary at low concentration for biological activity, but they are often toxic for microorganisms at high concentrations. Amplicon sequencing of 16S rRNA and 18S rRNA was used to investigate changes in the bacterial and microeukaryotic communities in an activated sludge bioreactor incrementally contaminated with nickel (Ni), copper (Cu), and zinc (Zn) with an IC50 value ranging from 0% to 100%, as previously determined, while an uncontaminated bioreactor served as a control. The chemical oxygen demand (COD) was on average 90% in the uncontaminated bioreactor but dropped to 49% when the heavy metal concentration was 100% IC50. The bacterial community in the uncontaminated bioreactor was dominated by Alphaproteobacteria (mostly Agrobacterium and Brevundimonas) when the heavy metal concentrations were low and Bacteroidetes (mostly Sphingobacterium) when the highest amounts of heavy metal concentrations were applied. The members of Ciliophora, Ascomycota, and Basidiomycota alternatively dominated in the uncontaminated bioreactor, while Ascomycota (mostly Fusarium) dominated in the contaminated bioreactor. The results revealed that increased concentrations of Ni, Cu, and Zn altered the bacterial and microeukaryotic communities and some putative metabolic functions.

We show that pressure applied to twisted WSe_{2} can enhance the many-body gap and region of stability of a fractional Chern insulator at filling ν=1/3. Our results are based on exact diagonalization of a continuum model, whose pressure dependence is obtained through ab initio methods. We interpret our results in terms of a magic line in the pressure-vs-twist angle phase diagram: along the magic line, the bandwidth of the topmost moiré valence band is minimized while simultaneously its quantum geometry resembles that of an ideal Chern band. We expect our results to generalize to other twisted transition metal dichalcogenide homobilayers.

IntroductionThe influence of intestinal microbiota, particularly lactic-acid bacteria, on digestion and nutrient metabolic activities has been extensively studied. In this research, we investigated the effects of supplementing the feed of rainbow trout (O. mykiss) with P. acidilactici or L. lactis probiotics. A Control group without probiotic supplementation was also included. The study aimed to evaluate growth, feed conversion indices, free amino acid levels in serum and feces, and the relative gene expression of amino acid solute carrier transporters (SLC).MethodsRainbow trout weighing 73.9±10 g were fed with a basal commercial diet supplemented with mono-strains of P. acidilactici or L. lactis at a dosage of 5 x 108 CFU per gram of feed for 60 days. The trout were reared in 100-liter tanks with independent closed recirculation systems, with a water replacement rate of 80% of the total volume daily and a controlled temperature of 15 ± 0.3 °C. The proximate composition of the basal diet consisted of crude protein (49.8%), fat (32.1%), fiber (1.31%), ash (13%), and moisture (8.3%) on a dry matter basis. The diet was provided at a rate of 2% of bodyweight per day.ResultsNo significant differences (p > 0.05) were observed in growth and feed conversion indices between the experimental groups. However, significant differences in free amino acid levels in feces and serum samples (p ≤ 0.05) were observed. The P. acidilactici group exhibited significantly higher levels of glutamate, lysine, proline, and tyrosine in feces samples, and higher levels of arginine, iso/leucine, phenylalanine, proline, serine, threonine, and valine in serum samples compared to the Control group. Additionally, the supplemented probiotic groups showed significant downregulation (p ≤ 0.05) of theslc6a19 and slc7a9 genes, which encode transporters for neutral and cationic amino acids.DiscussionThe autochthonous rainbow trout strain, P. acidilactici, demonstrated more pronounced effects on amino acid levels in feces and serum compared to the non-autochthonous L. lactis strain. However, the increased amino acid levels, particularly in the serum, resulting from P. acidilactici supplementation, did not lead to improved trout growth or feed conversion. Nonetheless, lactic-acid bacteria supplementation induced measurable metabolic effects, as evidenced by elevated levels of specific amino acids in the serum and feces.Future research should focus on evaluating these probiotic effects using specialized diets and considering the observed metabolic effects in this study.

Understanding how insect‐derived biomaterials interact with light has led to new advances and interdisciplinary insights in entomology and physics. Leafhoppers are insects that coat themselves with highly ordered biological nanostructures known as brochosomes. Brochosomes are thought to provide a range of protective properties to leafhoppers, such as hydrophobicity and antireflectivity, which has inspired the development of synthetic brochosomes that mimic their structures. Despite recent progress, the high antireflective properties of brochosome structures are not fully understood. Herein, a combination of experiments and computational modeling is used to understand the structure‐, material‐, and polarization‐dependent optical properties of brochosomes modeled on the geometries found in three leafhopper species. The results qualitatively represent that light interference interaction with nanostructures naturally occurring in brochosomes is responsible for the spectral tuning and the asymmetric line shape of the reflectance spectra. Whereas prior work has focused on the computational modeling of idealized pitted particles, this work shows that light–matter interactions with brochosome structures can be tuned by varying the geometry of their cage‐like nanoscale features and by changing the arrangement of multiparticle assemblies. Broadly, this work establishes principles for the guided design of new optically active materials inspired by these unique insect nanostructures.

Abstract A growing body of evidence shows that some ungulates alternate between migratory and nonmigratory behaviors over time. Yet it remains unclear whether such short‐term behavioral changes can help explain reported declines in ungulate migration worldwide, as opposed to long‐term demographic changes. Furthermore, advances in tracking technology reveal that a simple distinction between migration and nonmigration may not sufficiently describe all individual behaviors. To better understand the dynamics and drivers of ungulate switching behavior, we investigated 14 years of movement data from 361 elk in 20 herds across the Greater Yellowstone Ecosystem (GYE). First, we categorized yearly individual behaviors using a clustering algorithm that identified similar migratory tactics across a continuum of behaviors. Then, we tested seven hypotheses to explain why some ungulates switch behaviors, and we evaluated how behavioral changes affected the proportions of different behaviors across the system. We identified four distinct behavioral tactics: residents (4.8% of elk‐years), short‐distance migrants (53.7%), elevational migrants (21.9%) and long‐distance migrants (19.6%). Of the 20 herds, 18 were partially migratory, and 5 had all four movement tactics present. We observed switches between migratory tactics in all sets of consecutive years during our study period, with an average of 22.5% of individual elk changing movement tactics from one year to the next. Elk in herds with higher movement tactic diversity were significantly more likely to switch tactics and often responded more effectively to adverse environmental conditions, compared to those in herds with low movement tactic diversity. During our study period, switching increased the prevalence of both short‐ and long‐distance migrants, decreased the prevalence of elevational migrants, and had no effect on the prevalence of residents. Our findings suggest that rather than contributing to the declining migratory behavior found in the GYE, switching behavior may enable greater resiliency to continuously changing environmental and anthropogenic conditions.

Some financial disruptions that started in California, U.S., in March 2023, resulting in the closure of several medium-size U.S. banks, shed new light on the role of liquidity in business cycle dynamics. In the normal path of the business cycle, liquidity and output mutually interact. Small shocks generally lead to mean reversion through market forces, as a low degree of liquidity dissipation does not significantly disrupt the economic dynamics. However, larger shocks and greater liquidity dissipation arising from runs on financial institutions and contagion effects can trigger tipping points, financial disruptions, and economic downturns. The latter poses severe challenges for Central Banks, which during normal times, usually maintain a hands-off approach with soft regulation and monitoring, allowing the market to operate. However, in severe times of liquidity dissipation, they must swiftly restore liquidity flows and rebuild trust in stability to avoid further disruptions and meltdowns. In this paper, we present a nonlinear model of the liquidity–macro interaction and econometrically explore those types of dynamic features with data from the U.S. economy. Guided by a theoretical model, we use nonlinear econometric methods of a Smooth Transition Regression type to study those features, which provide and suggest further regulation and monitoring guidelines and institutional enforcement of rules.

IntroductionHuman-derived induced pluripotent stem cell (iPSC) models of brain promise to advance our understanding of neurotoxic consequences of drug use. However, how well these models recapitulate the actual genomic landscape and cell function, as well as the drug-induced alterations, remains to be established. New in vitro models of drug exposure are needed to advance our understanding of how to protect or reverse molecular changes related to substance use disorders.MethodsWe engineered a novel induced pluripotent stem cell-derived model of neural progenitor cells and neurons from cultured postmortem human skin fibroblasts, and directly compared these to isogenic brain tissue from the donor source. We assessed the maturity of the cell models across differentiation from stem cells to neurons using RNA cell type and maturity deconvolution analyses as well as DNA methylation epigenetic clocks trained on adult and fetal human tissue. As proof-of-concept of this model’s utility for substance use disorder studies, we compared morphine- and cocaine-treated neurons to gene expression signatures in postmortem Opioid Use Disorder (OUD) and Cocaine Use Disorder (CUD) brains, respectively.ResultsWithin each human subject (N = 2, 2 clones each), brain frontal cortex epigenetic age parallels that of skin fibroblasts and closely approximates the donor’s chronological age; stem cell induction from fibroblast cells effectively sets the epigenetic clock to an embryonic age; and differentiation of stem cells to neural progenitor cells and then to neurons progressively matures the cells via DNA methylation and RNA gene expression readouts. In neurons derived from an individual who died of opioid overdose, morphine treatment induced alterations in gene expression similar to those previously observed in OUD ex-vivo brain tissue, including differential expression of the immediate early gene EGR1, which is known to be dysregulated by opioid use.DiscussionIn summary, we introduce an iPSC model generated from human postmortem fibroblasts that can be directly compared to corresponding isogenic brain tissue and can be used to model perturbagen exposure such as that seen in opioid use disorder. Future studies with this and other postmortem-derived brain cellular models, including cerebral organoids, can be an invaluable tool for understanding mechanisms of drug-induced brain alterations.

Customer churn prediction is a valuable task in many industries. In telecommunications it presents great challenges, given the high dimensionality of the data, and how difficult it is to identify underlying frustration signatures, which may represent an important driver regarding future churn behaviour. Here, we propose a novel Bayesian hierarchical joint model that is able to characterise customer profiles based on how many events take place within different television watching journeys, and how long it takes between events. The model drastically reduces the dimensionality of the data from thousands of observations per customer to 11 customer-level parameter estimates and random effects. We test our methodology using data from 40 BT customers (20 active and 20 who eventually cancelled their subscription) whose TV watching behaviours were recorded from October to December 2019, totalling approximately half a million observations. Employing different machine learning techniques using the parameter estimates and random effects from the Bayesian hierarchical model as features yielded up to 92% accuracy predicting churn, associated with 100% true positive rates and false positive rates as low as 14% on a validation set. Our proposed methodology represents an efficient way of reducing the dimensionality of the data, while at the same time maintaining high descriptive and predictive capabilities. We provide code to implement the Bayesian model at https://github.com/rafamoral/profiling_tv_watching_behaviour.

Abstract We propose a novel realization for the natural extrapolation of the continuous spontaneous localization (CSL) model, in order to account for the origin of primordial inhomogeneities during inflation. This particular model is based on three main elements: (i) the semiclassical gravity framework, (ii) a collapse-generating operator associated to a relativistic invariant scalar of the energy-momentum tensor, and (iii) an extension of the CSL parameter(s) as a function of the spacetime curvature. Furthermore, employing standard cosmological perturbation theory at linear order, and for a reasonable range within the parameter space of the model, we obtain a nearly scale invariant power spectrum consistent with recent observational CMB data. This opens a vast landscape of different options for the application of the CSL model to the cosmological context, and possibly sheds light on searches for a full covariant version of the CSL theory.

Abstract In this work we analyze how the spectrum of primordial scalar perturbations is modified, within the emergent universe scenario, when a particular version of the Continuous Spontaneous Localization (CSL) model is incorporated as the generating mechanism of initial perturbations, providing also an explanation to the quantum-to-classical transition of such perturbations. On the other hand, a phase of super-inflation, prior to slow-roll inflation, is a characteristic feature of the emergent universe hypothesis. In recent works, it was shown that the super-inflation phase could generically induce a suppression of the temperature anisotropies of the CMB at large angular scales. We study here under what conditions the CSL maintains or modifies these characteristics of the emergent universe and their compatibility with the CMB observations.

IntroductionTo understand mechanisms and identify potential targets for intervention in the current crisis of opioid use disorder (OUD), postmortem brains represent an under-utilized resource. To refine previously reported gene signatures of neurobiological alterations in OUD from the dorsolateral prefrontal cortex (Brodmann Area 9, BA9), we explored the role of microRNAs (miRNA) as powerful epigenetic regulators of gene function.MethodsBuilding on the growing appreciation that miRNAs can cross the blood-brain barrier, we carried out miRNA profiling in same-subject postmortem samples from BA9 and blood tissues.ResultsmiRNA–mRNA network analysis showed that even though miRNAs identified in BA9 and blood were fairly distinct, their target genes and corresponding enriched pathways overlapped strongly. Among the dominant enriched biological processes were tissue development and morphogenesis, and MAPK signaling pathways. These findings point to robust, redundant, and systemic opioid-induced miRNA dysregulation with a potential functional impact on transcriptomic changes. Further, using correlation network analysis, we identified cell-type specific miRNA targets, specifically in astrocytes, neurons, and endothelial cells, associated with OUD transcriptomic dysregulation. Finally, leveraging a collection of control brain transcriptomes from the Genotype-Tissue Expression (GTEx) project, we identified a correlation of OUD miRNA targets with TGF beta, hypoxia, angiogenesis, coagulation, immune system, and inflammatory pathways.DiscussionThese findings support previous reports of neurovascular and immune system alterations as a consequence of opioid abuse and shed new light on miRNA network regulators of cellular response to opioid drugs.

Background and objectives: We aim to verify the use of ML algorithms to predict patient outcome using a relatively small dataset and to create a nomogram to assess in-hospital mortality of patients with COVID-19. Methods: A database of 200 COVID-19 patients admitted to the Clinical Hospital of State University of Campinas (UNICAMP) was used in this analysis. Patient features were divided into three categories: clinical, chest abnormalities, and body composition characteristics acquired by computerized tomography. These features were evaluated independently and combined to predict patient outcomes. To minimize performance fluctuations due to low sample number, reduce possible bias related to outliers, and evaluate the uncertainties generated by the small dataset, we developed a shuffling technique, a modified version of the Monte Carlo Cross Validation, creating several subgroups for training the algorithm and complementary testing subgroups. The following ML algorithms were tested: random forest, boosted decision trees, logistic regression, support vector machines, and neural networks. Performance was evaluated by analyzing Receiver operating characteristic (ROC) curves. The importance of each feature in the determination of the outcome predictability was also studied and a nomogram was created based on the most important features selected by the exclusion test. Results: Among the different sets of features, clinical variables age, lymphocyte number and weight were the most valuable features for prognosis prediction. However, we observed that skeletal muscle radiodensity and presence of pleural effusion were also important for outcome determination. Integrating these independent predictors was successfully developed to accurately predict mortality in COVID-19 in hospital patients. A nomogram based on these five features was created to predict COVID-19 mortality in hospitalized patients. The area under the ROC curve was 0.86 ± 0.04. Conclusion: ML algorithms can be reliable for the prediction of COVID-19-related in-hospital mortality, even when using a relatively small dataset. The success of ML techniques in smaller datasets broadens the applicability of these methods in several problems in the medical area. In addition, feature importance analysis allowed us to determine the most important variables for the prediction tasks resulting in a nomogram with good accuracy and clinical utility in predicting COVID-19 in-hospital mortality.

Abstract Sugarcane (Saccharum sp.) is a tropical and subtropical C4 plant with a high photosynthetic and carbon assimilation efficiency that stores sucrose. Culm biomass is also composed of bagasse fibre, a by‐product of the sugarcane industry. This high‐yielding grass, high in sucrose and lignocellulosic biomass, is considered an optimal feedstock as an alternative to fossil fuels and to produce a broad range of high‐value biomaterials. The ideal sugarcane production system would optimise the relative production of sugar and these new products. Multi‐omics correlation analysis was used to generate a global view of the essential metabolic pathways identifying critical genes involved in carbon partitioning during different stages of development. This research employed an unprecedented metabolic and transcriptomic dataset of 360 samples from a selection of 1440 culms of 24 genotypes at five different development stages. Chemical composition and metabolome analysis showed an increase through the culm development of lignin, sucrose, carbon, and amino acids such as aspartic acid, serine, alanine, methionine, threonine 3‐cyano‐L‐alanine, and citric acid. Transcriptome analysis revealed functionalities such as transcription, nucleotide transport and metabolism, and the biosynthesis of amino acids that are highly activated during the immature stage and highly down‐regulated during the most mature age.

Mesophotic coral ecosystems (MCEs) shelter unique communities. Coral zooxanthellae in these environments feature a low photosynthesis rate; therefore zooplankton becomes MCEs’ primary food source. These MCEs have not been studied enough due to the high cost of current assessment technologies, so these endeavours remain a challenge. The purpose of this work was to study the zooplankton community associated to the MCEs on seamount Bajo Frijol, within the Corales de Profundidad National Natural Park (off the Colombian Caribbean coast) and to compare its composition with that from shallower parts of the water column. Three samples were taken, filtering 24 L of seawater (via a mesh of size 45 μm) at each station with a device designed to collect zooplankton right on top of the reef substrate. Taxonomic composition, density and relative abundance were obtained. A resemblance analysis was performed, complemented with a cluster, an MDS and a modified Kandoorp test. The analysis showed clear differences between the water column samples from those taken close to the reef. It also showed the separation of the community into two large groups: north and center-south, both with unique species.

Understanding the structure and dynamics of enzymes is important for a number of applications. Here, the authors report on the crystal structure of vanillic acid decarboxylase, and show how the dynamics of the UbiD superfamily enzymes relate to the covalent catalysis of aromatic (de)carboxylation.

Data from the 2019 Minnesota Student Survey, consisting of 166,176 students ranging in age from 10 to 18 years, were used to investigate patterns of adolescent suicidal ideation and attempt through the lens of Minority Stress Theory (MST). Through a conjunctive analysis of case configurations (CACC), the current study demonstrates that adolescent suicidal ideation and attempt cluster significantly among specific situational profiles defined by the unique combination of variable attributes. Students most likely to indicate suicidal ideation were generally sexual minority females in high school who experienced cyberbullying, parental abuse, dating violence, and sexual abuse. Students least likely to report suicidal ideation were generally non-sexual minorities in elementary school who nearly never experienced parental abuse, dating violence, or sexual abuse. Results regarding adolescent suicide attempt indicate analogous results. The current findings highlight the importance of furthering research on contextual predictors of adolescent suicidality, with particular emphasis on sexual minority adolescents.

Abstract Genome-wide screenings of “essential genes”, i.e., genes required for an organism or cell survival, have been traditionally conducted in vitro in cancer cell lines, limiting the translation of results to other tissues and non-cancerous cells. Recently, an in vivo screening was conducted in adult mouse striatum tissue, providing the first genome-wide dataset of essential genes in neuronal cells. Here, we aim to investigate the role of essential genes in brain development and disease risk with a comprehensive set of bioinformatics tools, including integration with transcriptomic data from developing human brain, publicly available data from genome-wide association studies, de novo mutation datasets for different neuropsychiatric disorders, and case–control transcriptomic data from postmortem brain tissues. For the first time, we found that the expression of neuronal essential genes (NEGs) increases before birth during the early development of human brain and maintains a relatively high expression after birth. On the contrary, common essential genes from cancer cell line screenings (ACEGs) tend to be expressed at high levels during development but quickly drop after birth. Both gene sets were enriched in neurodevelopmental disorders, but only NEGs were robustly associated with neuropsychiatric disorders risk genes. Finally, NEGs were more likely to show differential expression in the brains of neuropsychiatric disorders patients than ACEGs. Overall, genome-wide central nervous system screening of essential genes can provide new insights into neuropsychiatric diseases.

Los mamíferos medianos y grandes se encuentran dentro de los grupos de especies de mayor uso por comunidades locales, a la vez que juegan un papel fundamental en los ecosistemas. En la región Caribe colombiana se han realizado algunos esfuerzos para documentar dichos usos, pero aún quedan impor-tantes vacíos de información necesarios para su conservación. En este estudio se evaluaron los usos y la percepción local de las amenazas sobre los mamíferos medianos y grandes del Distrito de Cartagena de Indias. Entre los meses de abril y agosto del 2017 se realizaron 103 entrevistas semiestructuradas para obtener información relacionada con los diferentes usos de estas especies en ocho corregimientos y tres barrios ubicados en la periferia de la zona urbana de la ciudad. El 61 % de los entrevistados reportó usos asociados al consumo, el 11 % para venta y el 5 % como mascotas. Las dos especies más consumidas fue-ron el conejo (Sylvilagus sp., 55 %) y la guartinaja (Cuniculus paca, 26 %); los órdenes más utilizados como mascotas fueron Primates y Rodentia. Los entrevistados identificaron la cacería, los atropellos en las carreteras y la destrucción del hábitat como las mayores amenazas.