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As the rate of crime decelerates in the developed world, the opposite phenomenon is being observed in the developing world, including Latin America and the Caribbean. Crime in Latin America and the Caribbean has been concentrated in urban settings, but the expertise for studying crime and providing guidance on policing remain heavily rooted in the developed world. A hindrance to studying crime in the developing world is the difficulty in obtaining official data, allowing for generalizations on where crime is concentrated to persist. This paper tackles two challenges facing crime analysis in the developing world: the availability of data and an examination of whether crime is concentrated in urban settings. We utilized newspaper archival data to study the spatial distribution of crime in Guyana, South America, across the landscape, and in relation to rural indigenous villages. Three spatial analysis tools, hotspot analysis, mean center, and standard deviation ellipse were used to examine the changing distribution of crime across 20 years. Based on 3900 reports of violent crime, our analyses suggest that the center of the gravity of crime changed over the years, spilling over to indigenous peoples’ landscapes. An examination of murder, where firearms and bladed weapons were the weapons of choice, suggests that these weapons moved beyond the coastal zone. The movement of weapons away from the coast raises concerns for the security of indigenous peoples and their associated wildlife. Our analysis suggests that policing measures should seek to extend towards Amerindian landscapes, and this is perhaps indicative of Latin American states with demographics similar to Guyana’s.

Pain is closely linked to alpha oscillations (8 < 13 Hz) which are thought to represent a supra-modal, top-down mediated gating mechanism that shapes sensory processing. Consequently, alpha oscillations might also shape the cerebral processing of nociceptive input and eventually the perception of pain. To test this mechanistic hypothesis, we designed a sham-controlled and double-blind electroencephalography (EEG)-based neurofeedback study. In a short-term neurofeedback training protocol, healthy participants learned to up- and down-regulate somatosensory alpha oscillations using attention. Subsequently, we investigated how this manipulation impacts experimental pain applied during neurofeedback. Using Bayesian statistics and mediation analysis, we aimed to test whether alpha oscillations mediate attention effects on pain perception. The results showed that attention and neurofeedback successfully up- and down-regulated the asymmetry of somatosensory alpha oscillations. However, attention and neurofeedback did not modulate pain ratings or related brain responses. Accordingly, somatosensory alpha oscillations did not mediate attention effects on pain perception. Thus, our results challenge the hypothesis that somatosensory alpha oscillations shape pain perception. A causal relationship between alpha oscillations and pain perception might not exist or be more complex than hypothesized. Trial registration: Following Stage 1 acceptance, the study was registered at ClinicalTrials.gov NCT05570695., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2025 Hohn et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Resting-state electroencephalography (rsEEG) holds promise as a biomarker of chronic pain. However, the impact of centrally acting analgesics like opioids, antiepileptics, and antidepressants on rsEEG remains unclear. This confounds and limits the interpretability of previous studies and questions the specificity of rsEEG biomarker candidates of chronic pain, especially for potential diagnostic biomarkers. We, therefore, aimed to elucidate the effects of opioids, antiepileptics, and antidepressants on common rsEEG biomarker candidates of chronic pain. To this end, we analyzed two large, independent rsEEG datasets, including 217 people with chronic pain. We performed preregistered multivariate Bayesian analyses to allow for the quantification and interpretation of evidence in favor of as well as against medication effects on EEG. We specifically evaluated the effects of different centrally acting analgesics on rsEEG features and controlled for the potential confounds of age, pain intensity, and depression. Results predominantly provided evidence against effects of centrally acting analgesics on peak alpha frequency, oscillatory power in different frequency bands, and connectivity-based network measures. Although these findings do not rule out any effects of analgesics on rsEEG, they argue against medium to large effects of centrally acting analgesics on rsEEG. These results help to interpret previous and future rsEEG findings in people with chronic pain and strengthen the validity of rsEEG biomarker candidates of chronic pain. Thus, the present findings can help to develop clinically valuable biomarkers of chronic pain. PERSPECTIVE: This study investigated the effects of centrally acting analgesics on brain-based biomarker candidates of chronic pain, as assessed by electroencephalography. The results predominantly provided evidence against effects on peak alpha frequency, oscillatory power, and connectivity-based network measures. This might help to develop clinically useful biomarkers of chronic pain. DATA AVAILABILITY: Datasets are available at https://osf.io/uzgxw/files/osfstorage., (Copyright © 2025 The Authors. Published by Elsevier Inc. All rights reserved.)

Chronic pain is a prevalent and debilitating condition whose neural mechanisms are incompletely understood. An imbalance of cerebral excitation and inhibition (E/I), particularly in the medial prefrontal cortex (mPFC), is believed to represent a crucial mechanism in the development and maintenance of chronic pain. Thus, identifying a non-invasive, scalable marker of E/I could provide valuable insights into the neural mechanisms of chronic pain and aid in developing clinically useful biomarkers. Recently, the aperiodic component of the electroencephalography (EEG) power spectrum has been proposed to represent a non-invasive proxy for E/I. We, therefore, assessed the aperiodic component in the mPFC of resting-state EEG recordings in 149 people with chronic pain and 115 healthy participants. We found robust evidence against differences in the aperiodic component in the mPFC between people with chronic pain and healthy participants, and no correlation between the aperiodic component and pain intensity. These findings were consistent across different subtypes of chronic pain and were similarly found in a whole-brain analysis. Their robustness was supported by preregistration and multiverse analyses across many different methodological choices. Together, our results suggest that the EEG aperiodic component does not differentiate between people with chronic pain and healthy individuals. These findings and the rigorous methodological approach can guide future studies investigating non-invasive, scalable markers of cerebral dysfunction in people with chronic pain and beyond., Competing Interests: CG, EM, FB, LT, VH, HH, PZ, JG No competing interests declared, MP Reviewing editor, eLife, (© 2024, Gil Avila et al.)

Biological nitrogen fixation is a fundamental biogeochemical process that transforms molecular nitrogen into biologically available nitrogen via diazotrophic microbes. Diazotrophs anaerobically fix nitrogen using the nitrogenase enzyme which is arranged in three different gene clusters: (i) molybdenum nitrogenase ( nifHDK ) is the most abundant, followed by it's alternatives, (ii) vanadium nitrogenase ( vnfHDK ) and (iii) iron nitrogenase ( anfHDK ). Multiple databases have been constructed as resources for diazotrophic 'omics analysis; however, an integrated database based on whole genome references does not exist. Here, we present NF ix DB (Nitrogen Fixation DataBase), a comprehensive integrated whole genome based database for diazotrophs, which includes all nitrogenases ( nifHDK , vnfHDK , anfHDK ) and nitrogenase-like enzymes (e.g. nflHD ) linked to ribosomal RNA operons (16S-5S-23S). NF ix DB was computed using Hidden Markov Models (HMMs) against the entire whole genome based Genome Taxonomy Database (GTDB R214), providing searchable reference HMMs for all nitrogenase and nitrogenase-like genes, complete ribosomal RNA operons, both GTDB and NCBI/RefSeq taxonomy, and an SQL database for querying matches. We compared NF ix DB to nifH databases from Buckley, Zehr, Mise and FunGene finding extensive evidence of nifH , in addition to vnfH and nflH . NF ix DB contains >4000 verified nifHDK sequences contained on 50 unique phyla of bacteria and archaea. NF ix DB provides the first comprehensive nitrogenase database available to researchers unlocking diazotrophic microbial potential., (© The Author(s) 2024. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.)

Amphibians globally suffer from emerging infectious diseases like chytridiomycosis caused by the continuously spreading chytrid fungi. One is Batrachochytrium salamandrivorans (Bsal) and its disease ‒ the 'salamander plague' ‒ which is lethal to several caudate taxa. Recently introduced into Western Europe, long distance dispersal of Bsal, likely through human mediation, has been reported. Herein we study if Alpine salamanders (Salamandra atra and S. lanzai) are yet affected by the salamander plague in the wild. Members of the genus Salamandra are highly susceptible to Bsal leading to the lethal disease. Moreover, ecological modelling has shown that the Alps and Dinarides, where Alpine salamanders occur, are generally suitable for Bsal. We analysed skin swabs of 818 individuals of Alpine salamanders and syntopic amphibians at 40 sites between 2017 to 2022. Further, we compiled those with published data from 319 individuals from 13 sites concluding that Bsal infections were not detected. Our results suggest that the salamander plague so far is absent from the geographic ranges of Alpine salamanders. That means that there is still a chance to timely implement surveillance strategies. Among others, we recommend prevention measures, citizen science approaches, and ex situ conservation breeding of endemic salamandrid lineages., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Böning et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Motivation: MerCat2 ("Mer-Catenate2") is a versatile, parallel, scalable and modular property software package for robustly analyzing features in omics data. Using massively parallel sequencing raw reads, assembled contigs, and protein sequences from any platform as input, MerCat2 performs k -mer counting of any length k , resulting in feature abundance counts tables, quality control reports, protein feature metrics, and graphical representation (i.e. principal component analysis (PCA))., Results: MerCat2 allows for direct analysis of data properties in a database-independent manner that initializes all data, which other profilers and assembly-based methods cannot perform. MerCat2 represents an integrated tool to illuminate omics data within a sample for rapid cross-examination and comparisons., Availability and Implementation: MerCat2 is written in Python and distributed under a BSD-3 license. The source code of MerCat2 is freely available at https://github.com/raw-lab/mercat2. MerCat2 is compatible with Python 3 on Mac OS X and Linux. MerCat2 can also be easily installed using bioconda: mamba create -n mercat2 -c conda-forge -c bioconda mercat2., Competing Interests: The authors declare no conflicts of interest. R.A.W. III is the CEO of RAW Molecular Systems (RAW) LLC, but no financial support, IP, or others from RAW LLC were used or contributed to the study., (© The Author(s) 2024. Published by Oxford University Press.)

Biomarker discovery in neurological and psychiatric disorders critically depends on reproducible and transparent methods applied to large-scale datasets. Electroencephalography (EEG) is a promising tool for identifying biomarkers. However, recording, preprocessing, and analysis of EEG data is time-consuming and researcher-dependent. Therefore, we developed DISCOVER-EEG, an open and fully automated pipeline that enables easy and fast preprocessing, analysis, and visualization of resting state EEG data. Data in the Brain Imaging Data Structure (BIDS) standard are automatically preprocessed, and physiologically meaningful features of brain function (including oscillatory power, connectivity, and network characteristics) are extracted and visualized using two open-source and widely used Matlab toolboxes (EEGLAB and FieldTrip). We tested the pipeline in two large, openly available datasets containing EEG recordings of healthy participants and patients with a psychiatric condition. Additionally, we performed an exploratory analysis that could inspire the development of biomarkers for healthy aging. Thus, the DISCOVER-EEG pipeline facilitates the aggregation, reuse, and analysis of large EEG datasets, promoting open and reproducible research on brain function., (© 2023. Springer Nature Limited.)

Pain emerges from the integration of sensory information about threats and contextual information such as an individual's expectations. However, how sensory and contextual effects on pain are served by the brain is not fully understood so far. To address this question, we applied brief painful stimuli to 40 healthy human participants and independently varied stimulus intensity and expectations. Concurrently, we recorded electroencephalography. We assessed local oscillatory brain activity and interregional functional connectivity in a network of six brain regions playing key roles in the processing of pain. We found that sensory information predominantly influenced local brain oscillations. In contrast, expectations exclusively influenced interregional connectivity. Specifically, expectations altered connectivity at alpha (8 to 12 hertz) frequencies from prefrontal to somatosensory cortex. Moreover, discrepancies between sensory information and expectations, i.e., prediction errors, influenced connectivity at gamma (60 to 100 hertz) frequencies. These findings reveal how fundamentally different brain mechanisms serve sensory and contextual effects on pain.

Abstract: Chronic pain is a major healthcare issue posing a large burden on individuals and society. Converging lines of evidence indicate that chronic pain is associated with substantial changes of brain structure and function. However, it remains unclear which neuronal measures relate to changes of clinical parameters over time and could thus monitor chronic pain and treatment responses. We therefore performed a longitudinal study in which we assessed clinical characteristics and resting-state electroencephalography data of 41 patients with chronic pain before and 6 months after interdisciplinary multimodal pain therapy. We specifically assessed electroencephalography measures that have previously been shown to differ between patients with chronic pain and healthy people. These included the dominant peak frequency; the amplitudes of neuronal oscillations at theta, alpha, beta, and gamma frequencies; as well as graph theory-based measures of brain network organization. The results show that pain intensity, pain-related disability, and depression were significantly improved after interdisciplinary multimodal pain therapy. Bayesian hypothesis testing indicated that these clinical changes were not related to changes of the dominant peak frequency or amplitudes of oscillations at any frequency band. Clinical changes were, however, associated with an increase in global network efficiency at theta frequencies. Thus, changes in chronic pain might be reflected by global network changes in the theta band. These longitudinal insights further the understanding of the brain mechanisms of chronic pain. Beyond, they might help to identify biomarkers for the monitoring of chronic pain., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association for the Study of Pain.)

Any departure from graphene's flatness leads to the emergence of artificial gauge fields that act on the motion of the Dirac fermions through an associated pseudomagnetic field. Here, we demonstrate the tunability of strong gauge fields in nonlocal experiments using a large planar graphene sheet that conforms to the deformation of a piezoelectric layer by a surface acoustic wave. The acoustic wave induces a longitudinal and a giant synthetic Hall voltage in the absence of external magnetic fields. The superposition of a synthetic Hall potential and a conventional Hall voltage can annihilate the sample's transverse potential at large external magnetic fields. Surface acoustic waves thus provide a promising and facile avenue for the exploitation of gauge fields in large planar graphene systems.

The perception of pain is shaped by somatosensory information about threat. However, pain is also influenced by an individual's expectations. Such expectations can result in clinically relevant modulations and abnormalities of pain. In the brain, sensory information, expectations (predictions), and discrepancies thereof (prediction errors) are signaled by an extended network of brain areas which generate evoked potentials and oscillatory responses at different latencies and frequencies. However, a comprehensive picture of how evoked and oscillatory brain responses signal sensory information, predictions, and prediction errors in the processing of pain is lacking so far. Here, we therefore applied brief painful stimuli to 48 healthy human participants and independently modulated sensory information (stimulus intensity) and expectations of pain intensity while measuring brain activity using electroencephalography (EEG). Pain ratings confirmed that pain intensity was shaped by both sensory information and expectations. In contrast, Bayesian analyses revealed that stimulus-induced EEG responses at different latencies (the N1, N2, and P2 components) and frequencies (alpha, beta, and gamma oscillations) were shaped by sensory information but not by expectations. Expectations, however, shaped alpha and beta oscillations before the painful stimuli. These findings indicate that commonly analyzed EEG responses to painful stimuli are more involved in signaling sensory information than in signaling expectations or mismatches of sensory information and expectations. Moreover, they indicate that the effects of expectations on pain are served by brain mechanisms which differ from those conveying effects of sensory information on pain., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Abstract: Chronic pain is a highly prevalent and severely disabling disease that is associated with substantial changes of brain function. Such changes have mostly been observed when analyzing static measures of resting-state brain activity. However, brain activity varies over time, and it is increasingly recognized that the temporal dynamics of brain activity provide behaviorally relevant information in different neuropsychiatric disorders. Here, we therefore investigated whether the temporal dynamics of brain function are altered in chronic pain. To this end, we applied microstate analysis to eyes-open and eyes-closed resting-state electroencephalography data of 101 patients suffering from chronic pain and 88 age- and sex-matched healthy controls. Microstate analysis describes electroencephalography activity as a sequence of a limited number of topographies termed microstates that remain stable for tens of milliseconds. Our results revealed that sequences of 5 microstates, labelled with the letters A to E, consistently described resting-state brain activity in both groups in the eyes-closed condition. Bayesian analysis of the temporal characteristics of microstates revealed that microstate D has a less predominant role in patients than in controls. As microstate D has previously been related to attentional networks and functions, these abnormalities might relate to dysfunctional attentional processes in chronic pain. Subgroup analyses replicated microstate D changes in patients with chronic back pain, while patients with chronic widespread pain did not show microstates alterations. Together, these findings add to the understanding of the pathophysiology of chronic pain and point to changes of brain dynamics specific to certain types of chronic pain., (Copyright © 2021 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the International Association for the Study of Pain.)

Chronic pain is a major health care problem. A better mechanistic understanding and new treatment approaches are urgently needed. In the brain, pain has been associated with neural oscillations at alpha and gamma frequencies, which can be targeted using transcranial alternating current stimulation (tACS). Thus, we investigated the potential of tACS to modulate pain and pain-related autonomic activity in an experimental model of chronic pain in 29 healthy participants. In 6 recording sessions, participants completed a tonic heat pain paradigm and simultaneously received tACS over prefrontal or somatosensory cortices at alpha or gamma frequencies or sham tACS. Concurrently, pain ratings and autonomic responses were collected. Using the present setup, tACS did not modulate pain or autonomic responses. Bayesian statistics confirmed a lack of tACS effects in most conditions. The only exception was alpha tACS over somatosensory cortex where evidence was inconclusive. Taken together, we did not find significant tACS effects on tonic experimental pain in healthy humans. Based on our present and previous findings, further studies might apply refined stimulation protocols targeting somatosensory alpha oscillations. TRIAL REGISTRATION: The study protocol was pre-registered at ClinicalTrials.gov (NCT03805854). PERSPECTIVE: Modulating brain oscillations is a promising approach for the treatment of pain. We therefore applied transcranial alternating current stimulation (tACS) to modulate experimental pain in healthy participants. However, tACS did not modulate pain, autonomic responses, or EEG oscillations. These findings help to shape future tACS studies for the treatment of pain., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

A recent study by Lee et al. showed that a dynamic functional connectivity pattern induced by tonic experimental pain might serve as a biomarker of chronic pain. The study illustrates key topics in translational neuroscience: the differentiation of biomarker functions, the multimodal integration of biomarkers, and the functional relevance of dynamic connectivity., Competing Interests: Declaration of Interests No interests are declared., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

With the further development of highly automated vehicles, drivers will engage in non-related tasks while being driven. Still, drivers have to take over control when requested by the car. Here, the question arises, how potentially distracted drivers get back into the control-loop quickly and safely when the car requests a takeover. To investigate effective human-machine interactions, a mobile, versatile, and cost-efficient setup is needed. Here, we describe a virtual reality toolkit for the Unity 3D game engine containing all the necessary code and assets to enable fast adaptations to various human-machine interaction experiments, including closely monitoring the subject. The presented project contains all the needed functionalities for realistic traffic behavior, cars, pedestrians, and a large, open-source, scriptable, and modular VR environment. It covers roughly 25 km 2 , a package of 125 animated pedestrians, and numerous vehicles, including motorbikes, trucks, and cars. It also contains all the needed nature assets to make it both highly dynamic and realistic. The presented repository contains a C++ library made for LoopAR that enables force feedback for gaming steering wheels as a fully supported component. It also includes all necessary scripts for eye-tracking in the used devices. All the main functions are integrated into the graphical user interface of the Unity ® editor or are available as prefab variants to ease the use of the embedded functionalities. This project's primary purpose is to serve as an open-access, cost-efficient toolkit that enables interested researchers to conduct realistic virtual reality research studies without costly and immobile simulators. To ensure the accessibility and usability of the mentioned toolkit, we performed a user experience report, also included in this paper.

Soil nitrification, mediated mainly by ammonia oxidizing archaea (AOA) and bacteria (AOB), converts ammonium (NH 4 + ) to nitrite (NO 2 - ) and thence nitrate (NO 3 - ). To better understand ecological differences between AOA and AOB, we investigated the nitrification kinetics of AOA and AOB under eight replicated cropped and unmanaged ecosystems (including two fertilized natural systems) along a long-term management intensity gradient in the upper U.S. Midwest. For five of eight ecosystems, AOB but not AOA exhibited Haldane kinetics (inhibited by high NH 4 + additions), especially in perennial and successional systems. In contrast, AOA predominantly exhibited Michaelis-Menten kinetics, suggesting greater resistance to high nitrogen inputs than AOB. These responses suggest the potential for NH 4 + -induced niche differentiation between AOA and AOB. Additionally, long-term fertilization significantly enhanced maximum nitrification rates ( V max ) in the early successional systems for both AOA and AOB, but not in the deciduous forest systems. This was likely due to pH suppression of nitrification in the acidic forest soils, corroborated by a positive correlation of V max with soil pH but not with amoA gene abundance. Results also demonstrated that soil nitrification potentials were relatively stable, as there were no seasonal differences. Overall, results suggest that (1) NH 4 + inhibition of AOB but not AOA could be another factor contributing to niche differentiation between AOA and AOB in soil, and (2) nitrification by both AOA and AOB can be significantly promoted by long-term nitrogen inputs., (Copyright © 2020 Liang, Ouyang, Tiemann and Robertson.)