Explore the vast range of titles available.

Artificial light at night (ALAN) is a major form of anthropogenic disturbance. ALAN attracts nocturnal invertebrates, which are a food source for nocturnal predators, including invasive species. Few studies quantify the effects of increased food availablity by ALAN on invasive vertebrate predators, and enhancement of food intake caused by ALAN may also be influenced by various environmental factors, such as proximitity to cities, moon phase, temperature, rainfall and wind speed. Revealing the potential impacts on invasive predators of ALAN-attracted invertebrates, and the influence of other factors on these effects, could provide important insights for the management of these predators. We constructed and supplied with artificial light field enclosures for invasive toads, and placed them at locations with different levels of ambient light pollution, in northeastern Australia. In addition, we determined the effect of rainfall, temperature, wind speed, and lunar phase on food intake in toads. We found that ALAN greatly increased the mass of gut contents of invasive toads compared to controls, but that the effect was increased in dark lunar phases, and when there were low ambient light pollution levels. Effects of rainfall, temperature and wind speed on food intake were comparatively weak. To avoid providing food resources to toads, management of ALAN in rural areas, and during dark lunar phases may be advisable. On the contrary, to effectively capture toads, trapping using lights as lures at such times and places should be more successful.

Neuropsychiatric disorders are diagnosed based on behavioral criteria, which makes the diagnosis challenging. Objective biomarkers such as neuroimaging are needed, and when coupled with machine learning, can assist the diagnostic decision and increase its reliability. Sixty-four schizophrenia, 36 autism spectrum disorder (ASD), and 106 typically developing individuals were analyzed. FreeSurfer was used to obtain the data from the participant’s brain scans. Six classifiers were utilized to classify the subjects. Subsequently, 26 ultra-high risk for psychosis (UHR) and 17 first-episode psychosis (FEP) subjects were run through the trained classifiers. Lastly, the classifiers’ output of the patient groups was correlated with their clinical severity. All six classifiers performed relatively well to distinguish the subject groups, especially support vector machine (SVM) and Logistic regression (LR). Cortical thickness and subcortical volume feature groups were most useful for the classification. LR and SVM were highly consistent with clinical indices of ASD. When UHR and FEP groups were run with the trained classifiers, majority of the cases were classified as schizophrenia, none as ASD. Overall, SVM and LR were the best performing classifiers. Cortical thickness and subcortical volume were most useful for the classification, compared to surface area. LR, SVM, and DT’s output were clinically informative. The trained classifiers were able to help predict the diagnostic category of both UHR and FEP Individuals.

A comparative analysis of animal behavior (e.g., male vs. female groups) has been widely used to elucidate behavior specific to one group since pre-Darwinian times. However, big data generated by new sensing technologies, e.g., GPS, makes it difficult for them to contrast group differences manually. This study introduces DeepHL, a deep learning-assisted platform for the comparative analysis of animal movement data, i.e., trajectories. This software uses a deep neural network based on an attention mechanism to automatically detect segments in trajectories that are characteristic of one group. It then highlights these segments in visualized trajectories, enabling biologists to focus on these segments, and helps them reveal the underlying meaning of the highlighted segments to facilitate formulating new hypotheses. We tested the platform on a variety of trajectories of worms, insects, mice, bears, and seabirds across a scale from millimeters to hundreds of kilometers, revealing new movement features of these animals. Comparative analysis of animal behaviour using locomotion data such as GPS data is difficult because the large amount of data makes it difficult to contrast group differences. Here the authors apply deep learning to detect and highlight trajectories characteristic of a group across scales of millimetres to hundreds of kilometres.

As cities around the world rapidly expand, there is an urgent need to implement the best development form to minimize the negative impacts of urbanization on native biodiversity. Two divergent forms for the expansion of cities are land‐sharing and land‐sparing developments. To date, their relative benefits for biodiversity conservation are poorly understood. We quantified the relative conservation benefits of land‐sharing and land‐sparing developments for butterflies and ground beetles in Tokyo, Japan. For each insect species, we determined which approach resulted in a larger total population size. At a higher level of urbanization (higher number of buildings in a landscape), land sparing rather than land sharing resulted in a higher total population size for the majority species of both taxa. However, at a lower level of urbanization, butterflies and ground beetles showed different responses to city development forms. Ground beetles had their highest total population sizes under land sparing, whereas for butterflies, especially open‐land and matrix‐dwelling species, larger populations were achieved under land sharing. The negative impacts of urbanization on biodiversity differ greatly between land‐sharing and land‐sparing development forms. We also revealed that the relative conservation benefits of land sharing and land sparing depend on the level of urbanization. Synthesis and applications. In areas that will be heavily urbanized in the future, city planners and policymakers should adopt approaches that follow a land‐sparing strategy and that keep large blocks of greenspace free from development. At lower levels of urbanization, on the other hand, as land sharing was suggested to be the better strategy for many butterfly species, a hybrid development form could be adopted that integrates areas of land sharing and land sparing, which might have the additional benefit of enhancing the delivery of some ecosystem services by bringing nature and people closer together in some areas.

Antipsychotic drugs are the mainstay in the treatment of schizophrenia. However, one-third of patients do not show adequate improvement in positive symptoms with non-clozapine antipsychotics. Additionally, approximately half of them show poor response to clozapine, electroconvulsive therapy, or other augmentation strategies. However, the development of novel treatment for these conditions is difficult due to the complex and heterogenous pathophysiology of treatment-resistant schizophrenia (TRS). Therefore, this review provides key findings, potential treatments, and a roadmap for future research in this area. First, we review the neurobiological pathophysiology of TRS, particularly the dopaminergic, glutamatergic, and GABAergic pathways. Next, the limitations of existing and promising treatments are presented. Specifically, this article focuses on the therapeutic potential of neuromodulation, including electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Finally, we propose multivariate analyses that integrate various perspectives of the pathogenesis, such as dopaminergic dysfunction and excitatory/inhibitory imbalance, thereby elucidating the heterogeneity of TRS that could not be obtained by conventional statistics. These analyses can in turn lead to a precision medicine approach with closed-loop neuromodulation targeting the detected pathophysiology of TRS.

Multisite magnetic resonance imaging (MRI) is increasingly used in clinical research and development. Measurement biases—caused by site differences in scanner/image‐acquisition protocols—negatively influence the reliability and reproducibility of image‐analysis methods. Harmonization can reduce bias and improve the reproducibility of multisite datasets. Herein, a traveling‐subject (TS) dataset including 56 T1‐weighted MRI scans of 20 healthy participants in three different MRI procedures—20, 19, and 17 subjects in Procedures 1, 2, and 3, respectively—was considered to compare the reproducibility of TS‐GLM, ComBat, and TS‐ComBat harmonization methods. The minimum participant count required for harmonization was determined, and the Cohen's d between different MRI procedures was evaluated as a measurement‐bias indicator. The measurement‐bias reduction realized with different methods was evaluated by comparing test–retest scans for 20 healthy participants. Moreover, the minimum subject count for harmonization was determined by comparing test–retest datasets. The results revealed that TS‐GLM and TS‐ComBat reduced measurement bias by up to 85 and 81.3%, respectively. Meanwhile, ComBat showed a reduction of only 59.0%. At least 6 TSs were required to harmonize data obtained from different MRI scanners, complying with the imaging protocol predetermined for multisite investigations and operated with similar scan parameters. The results indicate that TS‐based harmonization outperforms ComBat for measurement‐bias reduction and is optimal for MRI data in well‐prepared multisite investigations. One drawback is the small sample size used, potentially limiting the applicability of ComBat. Investigation on the number of subjects needed for a large‐scale study is an interesting future problem. Measurement biases‐caused by site differences in scanner/image‐acquisition protocols‐negatively influence the reliability and reproducibility of image‐analysis methods. Herein, a travelling‐subject (TS) dataset including 56 T1‐weighted MRI scans of 20 healthy participants in three different MRI procedures—20, 19, and 17 subjects in Procedures 1, 2, and 3, respectively—was considered to compare the reproducibility of TS‐GLM, ComBat, and TS‐ComBat harmonization methods. The results revealed that TS‐GLM and TS‐ComBat reduced measurement bias by up to 85 and 81.3%, respectively.

The prefrontal deficits in psychiatric disorders have been investigated using functional neuroimaging tools; however, no studies have tested the related characteristics across psychiatric disorders considering various demographic and clinical confounders. We analyzed 1558 functional brain measurements using a functional near-infrared spectroscopy during a verbal fluency task from 1200 participants with three disease spectra [196 schizophrenia, 189 bipolar disorder (BPD), and 394 major depressive disorder (MDD)] and 369 healthy controls along with demographic characteristics (age, gender, premorbid IQ, and handedness), task performance during the measurements, clinical assessments, and medication equivalent doses (chlorpromazine, diazepam, biperiden, and imipramine) in a consistent manner. The association between brain functions and demographic and clinical variables was tested using a general linear mixed model (GLMM). Then, the direction of relationship between brain activity and symptom severity, controlling for any other associations, was estimated using a model comparison of structural equation models (SEMs). The GLMM showed a shared functional deficit of brain activity and a schizophrenia-specific delayed activity timing in the prefrontal cortex (false discovery rate-corrected < 0.05). Comparison of SEMs showed that brain activity was associated with the global assessment of functioning scores in the left inferior frontal gyrus opercularis (IFGOp) in BPD group and the bilateral superior temporal gyrus and middle temporal gyrus, and the left superior frontal gyrus, inferior frontal gyrus triangularis, and IFGOp in MDD group. This cross-disease large-sample neuroimaging study with high-quality clinical data reveals a robust relationship between prefrontal function and behavioral outcomes across three major psychiatric disorders.

Epidemiological studies have revealed that schizophrenia is highly heritable. However, genetic studies have not fully elucidated its etiology. Accumulating evidence suggests that epigenetic alterations may provide an additional explanation of its pathophysiology. We investigated the methylation profiles of DNA in peripheral blood cells from 18 patients with first-episode schizophrenia (FESZ) and from 15 normal controls. Schizophrenia patients were confined to those at the stage of first-episode psychosis. We analyzed the DNA methylation status of 27,578 CpG sites by means of the Illumina Infinium HumanMethylation27 BeadChip array. Differentially methylated CpG sites, which were particularly abundant within CpG islands, were enriched in genes related to the nuclear lumen, to transcription factor binding, and to nucleotide binding. We also observed differential methylation of the promoters of HTR1E and COMTD1, which are functionally related to genes found to be differentially methylated in schizophrenia patients in previous studies. Our results indicate the site-specific epigenetic alterations in patients with FESZ.

There is growing concern over the loss of grassland and forest species worldwide due to land use changes. In Japan, young forest plantations provide important habitats for grassland species. However, the decline in forest logging frequency has led to a decrease in the area of young plantations, which may in turn cause a decline in the number of grassland species. Power line corridors in forest plantations can act as habitats for early and late successional species, as they contain vegetation in diverse stages. This study evaluated the importance of these corridor zones as habitats for early and late successional butterflies in Japan. The species richness and abundance of butterflies were recorded in power line corridors, young plantations, forest roads, and mature plantations. Vegetation height and food resource availability for larvae and adult butterflies were also measured. The species richness and abundance of those of late successional butterflies were highest in power line corridors and young plantations, and lowest in mature plantations; and early successional butterflies and food resource availability were highest in power line corridors, and lowest in mature plantations. The species richness and abundance of butterflies within power line corridors were largely explained by vegetation height and food resource availability. Our results indicate that power line corridors within conifer plantations provide important habitats for early and late successional butterflies.Implications for insect conservationIncreasing the habitat value of power line corridors through appropriate vegetation management can have an important role in preserving insect species.

Scavenging is a common feeding behavior that provides ecosystem services by removing potentially infectious waste from the landscape. The importance of facultative scavenging is often overlooked, but likely becomes especially important in ecosystems without obligate scavengers. Here, we investigated the ecological function of vertebrate facultative scavengers in removing ungulate carcasses from Japanese forests that lack obligate scavengers. We found that mammals detected carcasses first more often than birds, and that raccoon dogs ( Nyctereutes procyonoides ) were the most frequent scavenger to first detect carcasses. However, we found no evidence of there being species that signal the location of carrion to other species via social cues. Instead, higher temperatures promoted earlier detection of the carcasses by scavengers, likely related to increased olfactory signals. The carcasses were completely consumed on average in 7.0 days, reasonably similar to other systems regardless of habitat, indicating that facultative scavengers are providing ecosystem services. Larger carcasses tended to take longer to deplete, but carcasses were consumed faster in warmer temperatures. Our results indicate that facultative scavengers were capable of consuming carrion and contributing ecosystem services in a forest ecosystem that lacks obligate scavengers.