Miracle-dz/UniFAR-FTUs huggingface dataset:
The social networks and structural variation of Mississippian sociopolitics in the southeastern United States

Significance An alternative approach to the use of sociotypological models in interpreting sociopolitical organization is presented. The development of analytical and conceptual strategies to compare and describe sociopolitical organizations is a cornerstone of anthropological inquiry. This study contributes to such disciplinary foci by presenting a formal, comparative approach to the study of sociopolitics, particularly contributing to discussions of the evolution and development of organizational complexity in small-scale, nonstate societies. Beyond archaeology however, this study demonstrates the value of a deep, historical perspective on the evolution of human networks more broadly and highlights the value of a productive relationship between contemporary social, economic, and political theory and the historical sciences for the investigation of both past and present societies. Network approaches in archaeology offer a promising avenue for facilitating bottom-up, comparative approaches to sociopolitical organization. While recent applications have focused primarily on migration and demographic trends, identity and identity politics, and the dynamics of geopolitical and regional interaction, little in the way of comparative sociopolitical organization has been attempted. In this study, I present an alternative approach to the use of sociotypological models across southern Appalachia. In particular, I demonstrate the value in employing network analyses as a mode of formally and quantitatively comparing the relational structures and organizations of sociopolitical landscapes; in this case, those traditionally characterized as constellations of chiefdoms. By approaching southern Appalachian histories through the relationships upon which social, political, and economic institutions were actually built, I move the study of southeastern political systems beyond the use of models that emphasize the behaviors of elites and the ruling class as inspired by the ethnographic and ethnohistoric records. To these ends, using a robust regional ceramic dataset, I compare network histories and political landscapes for the southern Appalachian region between ca. AD 800 and 1650. The results of these analyses contribute insights to the study of small-scale political organizations by demonstrating that (i) as chiefdoms developed, leaders drew on preexisting social and political conditions; (ii) while networks of chiefly interaction were defined by instability, wider networks of interaction were much more durable; and (iii) quantitative network analyses and qualitative ethnohistoric accounts can articulate with one another to shed light on indigenous political organization.
Processing bodies control the selective translation for optimal development of Arabidopsis young seedlings

Significance Photomorphogenic development allows young plant seedlings to acquire photosynthetic activities and growth competitiveness when they emerge from soil. More than 1,000 mRNAs are translationally inert in dark-grown seedlings but quickly engage in translation when seedlings are first exposed to light signals. However, why some mRNAs undergo selective translation, how the selective translation is regulated, and why it is important remain unknown. Our work fills in this missing gap by demonstrating that processing bodies function as mRNA reservoirs in dark-grown seedlings. Photoreceptors negate the function of a negative regulator CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1), thereby reducing the accumulation of processing bodies in light-grown seedlings to release thousands of mRNAs for translation, which explains in part the light-enhanced global translation in photomorphogenic seedlings. Germinated plant seeds buried in soil undergo skotomorphogenic development before emergence to reach the light environment. Young seedlings transitioning from dark to light undergo photomorphogenic development. During photomorphogenesis, light alters the transcriptome and enhances the translation of thousands of mRNAs during the dark-to-light transition in Arabidopsis young seedlings. About 1,500 of these mRNAs have comparable abundance before and after light treatment, which implies widespread translational repression in dark-grown seedlings. Processing bodies (p-bodies), the cytoplasmic granules found in diverse organisms, can balance the storage, degradation, and translation of mRNAs. However, the function of p-bodies in translation control remains largely unknown in plants. Here we found that an Arabidopsis mutant defective in p-body formation (Decapping 5; dcp5-1) showed reduced fitness under both dark and light conditions. Comparative transcriptome and translatome analyses of wild-type and dcp5-1 seedlings revealed that p-bodies can attenuate the premature translation of specific mRNAs in the dark, including those encoding enzymes for protochlorophyllide synthesis and PIN-LIKES3 for auxin-dependent apical hook opening. When the seedlings protrude from soil, light perception by photoreceptors triggers a reduced accumulation of p-bodies to release the translationally stalled mRNAs for active translation of mRNAs encoding proteins needed for photomorphogenesis. Our data support a key role for p-bodies in translation repression, an essential mechanism for proper skotomorphogenesis and timely photomorphogenesis in seedlings.
16S rRNA sequence embeddings: Meaningful numeric feature representations of nucleotide sequences that are convenient for downstream analyses

Advances in high-throughput sequencing have increased the availability of microbiome sequencing data that can be exploited to characterize microbiome community structure in situ. We explore using word and sentence embedding approaches for nucleotide sequences since they may be a suitable numerical representation for downstream machine learning applications (especially deep learning). This work involves first encoding (“embedding”) each sequence into a dense, low-dimensional, numeric vector space. Here, we use Skip-Gram word2vec to embed k-mers, obtained from 16S rRNA amplicon surveys, and then leverage an existing sentence embedding technique to embed all sequences belonging to specific body sites or samples. We demonstrate that these representations are biologically meaningful, and hence the embedding space can be exploited as a form of feature extraction for exploratory analysis. We show that sequence embeddings preserve relevant information about the sequencing data such as k-mer context, sequence taxonomy, and sample class. Specifically, the sequence embedding space resolved differences among phyla, as well as differences among genera within the same family. Distances between sequence embeddings had similar qualities to distances between alignment identities, and embedding multiple sequences can be thought of as generating a consensus sequence. Using sample embeddings for body site classification resulted in negligible performance loss compared to using OTU abundance data. Lastly, the k-mer embedding space captured distinct k-mer profiles that mapped to specific regions of the 16S rRNA gene and corresponded with particular body sites. Together, our results show that embedding sequences results in meaningful representations that can be used for exploratory analyses or for downstream machine learning applications that require numeric data. Moreover, because the embeddings are trained in an unsupervised manner, unlabeled data can be embedded and used to bolster supervised machine learning tasks. Author summary Improvements in the way genomes are sequenced have led to an abundance of microbiome data. With the right approaches, researchers use this data to thoroughly characterize how microbes interact with each other and their host, but sequencing data is of a form (sequences of letters) not ideal for many data analysis approaches. We therefore present an approach to transform sequencing data into arrays of numbers that can capture interesting qualities of the data at the sub-sequence, full-sequence, and sample levels. This allows us to measure the importance of certain microbial sequences with respect to the type of microbe and the condition of the host. Also, representing sequences in this way improves our ability to use other complicated modeling approaches. Using microbiome data from human samples, we show that our numeric representations captured differences between different types of microbes, as well as differences in the body site location from which the samples were collected.
The Evolution of Marine Larval Dispersal Kernels in Spatially Structured Habitats: Analytical Models, Individual-Based Simulations, and Comparisons with Empirical Estimates

Understanding the causes of larval dispersal is a major goal of marine ecology, yet most research focuses on proximate causes. Here we ask how ultimate, evolutionary causes affect dispersal. Building on Hamilton and May’s classic 1977 article “Dispersal in Stable Habitats,” we develop analytic and simulation models for the evolution of dispersal kernels in spatially structured habitats. First, we investigate dispersal in a world without edges and find that most offspring disperse as far as possible, opposite the pattern of empirical data. Adding edges to our model world leads to nearly all offspring dispersing short distances, again a mismatch with empirical data. Adding resource heterogeneity improves our results: most offspring disperse short distances with some dispersing longer distances. Finally, we simulate dispersal evolution in a real seascape in Belize and find that the simulated dispersal kernel and an empirical dispersal kernel from that seascape both have the same shape, with a high level of short-distance dispersal and a low level of long-distance dispersal. The novel contributions of this work are to provide a spatially explicit analytic extension of Hamilton and May’s 1977 work, to demonstrate that our spatially explicit simulations and analytic models provide equivalent results, and to use simulation approaches to investigate the evolution of dispersal kernel shape in spatially complex habitats. Our model could be modified in various ways to investigate dispersal evolution in other species and seascapes, providing new insights into patterns of marine larval dispersal.
Deep Brain Stimulation for Pain in the Modern Era: A Systematic Review.

BACKGROUND Deep brain stimulation (DBS) has been considered for patients with intractable pain syndromes since the 1950s. Although there is substantial experience reported in the literature, the indications are contested, especially in the United States where it remains off-label. Historically, the sensory-discriminative pain pathways were targeted. More recently, modulation of the affective sphere of pain has emerged as a plausible alternative. OBJECTIVE To systematically review the literature from studies that used contemporary DBS technology. Our aim is to summarize the current evidence of this therapy. METHODS A systematic search was conducted in the MEDLINE, EMBASE, and Cochrane libraries through July 2017 to review all studies using the current DBS technology primarily for pain treatment. Study characteristics including patient demographics, surgical technique, outcomes, and complications were collected. RESULTS Twenty-two articles were included in this review. In total, 228 patients were implanted with a definitive DBS system for pain. The most common targets used were periaqueductal/periventricular gray matter region, ventral posterior lateral/posterior medial thalamus, or both. Poststroke pain, phantom limb pain, and brachial plexus injury were the most common specific indications for DBS. Outcomes varied between studies and across chronic pain diagnoses. Two different groups of investigators targeting the affective sphere of pain have demonstrated improvements in quality of life measures without significant reductions in pain scores. CONCLUSION DBS outcomes for chronic pain are heterogeneous thus far. Future studies may focus on specific pain diagnosis rather than multiple syndromes and consider randomized placebo-controlled designs. DBS targeting the affective sphere of pain seems promising and deserves further investigation.
CALL FOR PAPERS Integrative and Translational Physiology: Inflammation and Immunity in Organ System Physiology TLR3 deficiency induces chronic inflammatory cardiomyopathy in resistant mice following coxsackievirus B3 infection: role for IL-4

Eric D. Abston, Michael J. Coronado, Adriana Bucek, Jennifer A. Onyimba, Jessica E. Brandt, J. Augusto Frisancho, Eunyong Kim, Djahida Bedja, Yoon-kyu Sung, Andrea J. Radtke, Kathleen L. Gabrielson, Wayne Mitzner, and DeLisa Fairweather Department of Environmental Health Sciences, Johns Hopkins University, Bloomberg School of Public Health and School of Medicine, Baltimore, Maryland; Department of Pathology, Johns Hopkins University, Bloomberg School of Public Health and School of Medicine, Baltimore, Maryland; and W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University, Bloomberg School of Public Health and School of Medicine, Baltimore Maryland
Increased risk of schizophrenia from additive interaction between infant motor developmental delay and obstetric complications: evidence from a population-based longitudinal study.

OBJECTIVE Obstetric complications and developmental delay are well-established risk factors for schizophrenia. The authors investigated whether these risk factors interact in an additive manner to further increase risk for schizophrenia. METHOD The study population encompassed all individuals born in Helsinki between 1962 and 1969 who had developmental records archived in the Helsinki City Archives. Through linkage between the Finnish Population Register, the Finnish Hospital Discharge Register, and the Child Health Archives, child health cards were traced for 189 individuals who had received a diagnosis of schizophrenia and 189 healthy comparison subjects, individually matched to case subjects on gender and year of birth. Child health cards from the Child Health Archives contain detailed prospective developmental data from birth as well as an indicator of fetal distress, as measured by the Apgar score. Detailed developmental data from the first year of life were extracted. RESULTS Delayed attainment of milestones in infancy significantly increased the risk of later development of schizophrenia in a dose-response manner. There was no significant main effect of obstetric complications on risk for schizophrenia and no significant association between obstetric complications and subsequent developmental delay. However, the additive effect of obstetric complications and delayed attainment of developmental milestones significantly increased the risk of schizophrenia beyond that associated with each factor independently (odds ratio=4.6, 95% confidence interval=1.3-17.2). CONCLUSIONS These data provide evidence that underlying neurodevelopmental vulnerability, as indexed by delayed attainment of milestones, combined with obstetric adversity significantly increases the risk of schizophrenia in adulthood.
Controlling the number of layers in graphene using the growth pressure

Monolayer graphene is commonly grown on Cu substrates due to the self-limiting nature of graphene synthesis by chemical vapor deposition (CVD). Consequently, the growth of multilayer graphene by CVD has proven to be relatively difficult. This study demonstrates that the number of layers in graphene synthesized on a copper substrate can be precisely set by controlling the partial pressure of hydrogen gas used in the CVD process. This study also shows that a pressure threshold exists for a distinct transition from monolayer to multilayer graphene growth. This threshold is shown to be the boundary where the graphene growth process on Cu by CVD is no longer a self-limiting process. In addition, the multilayer graphene synthesized through the pressure control method forms in the Volmer–Weber mode with an AB stacking structure.
Torus-Event-Based Fault Diagnosis for Stochastic Multirate Time-Varying Systems With Constrained Fault

In this paper, the torus-event-based fault detection and isolation (FDI) problem is investigated for a class of time-varying multirate systems. An ellipsoidal constraint is first adopted to describe the fault in a more practical pattern, and a novel torus-event-triggering scheme is proposed to improve the unilateral triggering mechanism. The aim is to design the torus-event-based fault detection filter and fault isolation estimators such that both the prescribed variance constraint on the estimation error and the desired <inline-formula> <tex-math notation="LaTeX">${H}_{\infty }$ </tex-math></inline-formula> performance on the disturbance are guaranteed over the finite horizon. Especially, the residual evaluation function is employed to detect the fault, and the residual matching function is developed to isolate the fault. Furthermore, three optimization problems are provided to seek separately the minimal parameters on the <inline-formula> <tex-math notation="LaTeX">${H}_{\infty }$ </tex-math></inline-formula> performance level, the upper bound of the estimation error variance, and the triggering torus. Finally, two simulation examples are utilized to show the effectiveness of the FDI scheme proposed in this paper.
Microglial activation in early Alzheimer trajectory is associated with higher gray matter volume

Objective To investigate the influence of microglial activation in the early stages of Alzheimer's disease trajectory, we assessed the relationship between microglial activation and gray matter volume and hippocampal volume in patients with mild cognitive impairment (MCI). Methods In this study, 55 participants (37 with early stages of MCI and 18 controls) underwent [11C]PBR28 PET, a marker of microglial activation; volumetric MRI to evaluate gray matter and hippocampal volumes as well as clinical and neuropsychometric evaluation. [11C]PBR28 VT (volume of distribution) was calculated using arterial input function and Logan graphical analysis. Gray matter volume and hippocampal volumes were calculated from MRI for each participant. Statistical parametric mapping software was used to perform voxel-wise correlations and biological parametric mapping analysis. Amyloid status was assessed using [18F]flutemetamol PET. Results Higher [11C]PBR28 VT in different cortical areas correlated with higher gray matter volume in both amyloid-positive and -negative MCI. In addition, higher hippocampal volume correlated with higher cortical [11C]PBR28 Logan VT. Conclusions In this in vivo study, we have demonstrated that microglial activation quantified using [11C]PBR28 PET was associated with higher gray matter volume and higher hippocampal volume in patients with MCI. This might suggest that microglial activation may not always be associated with neuronal damage, and indeed it may have a beneficial effect in the early stages of the Alzheimer trajectory. While further longitudinal studies are necessary, these findings have significant implications on therapeutic strategies targeting microglial activation.
What are the psychological effects of using synthetic cannabinoids? A systematic review

Background: Synthetic cannabinoids are, typically, full agonists at the cannabinoid CB1 receptor, and therefore considerably more potent than natural cannabis and may have correspondingly more serious psychological effects. Despite government sanctions against their production they continue to be available in ever-increasing varieties over the Internet. The psychological consequences of synthetic cannabinoid use are relatively unknown. Aim: The purpose of this study was to synthesise the available research on the psychological consequences of synthetic cannabinoid use. Method: A literature search of three databases was conducted in February 2018, including the following keywords: Spice, synthetic cannabis, cognition, affect, behaviour, psychosis, depression and anxiety. Results: Seventeen studies involving a variety of participants were eligible for inclusion: one controlled administration study, seven cross-sectional studies, five Internet surveys and four qualitative studies. The controlled administration study showed that, compared to placebo, synthetic cannabinoids acutely affected some aspects of cognitive functioning and subjective psychological ratings. Non-controlled, cross-sectional studies generally showed that synthetic cannabinoid users had lower performance on cognitive tasks and showed elevated symptomatology (e.g. paranoia) compared to both natural cannabis and non-cannabis users. Methodological limitations were noted across different study designs. There is limited research on how doses, frequency or type of synthetic cannabinoid influence outcomes. Conclusions: Acute synthetic cannabinoid use can result in a range of psychological outcomes and, when non-intoxicated, synthetic cannabinoid users appear to differ from natural cannabis and non-users on various affective and cognitive domains. As synthetic cannabinoid use is increasing in at-risk populations there is an urgent need for more and better research to inform users, professionals and policymakers.
Oxygenation Responses While Wearing the Elevation Training Mask During an Incremental Cycling Test

Abstract Romero-Arenas, S, López-Pérez, E, Colomer-Poveda, D, and Márquez, G. Oxygenation responses while wearing the elevation training mask during an incremental cycling test. J Strength Cond Res 35(7): 1897–1904, 2021—The Elevation Training Mask 2.0 (ETM) is a commercial training mask that purportedly simulates altitude training, although their effects have not been conclusively demonstrated. Therefore, the purpose of this study was to evaluate the influence of wearing the ETM on muscle and brain oxygenation responses during a maximal incremental cycling test, as well as the influence of this device on the heart rate (HR) response, perception of effort (rating of perceived exertion [RPE]), arterial oxygen saturation (SaO2), blood lactate (La+), and performance (POpeak). Fourteen active males completed an incremental cycling test to volitional exhaustion in 2 separate and counterbalanced conditions, wearing the mask set at 9,000 feet (i.e., 2743 m) and a control condition (CTR, without ETM). During the trial, muscle and cerebral oxygenation were monitored continuously using near-infrared spectroscopy. Heart rate, RPE, and SaO2 were also recorded from the beginning of the test until the volitional exhaustion. La+ was measured at the end of each test. Wearing the ETM significantly reduced the POpeak by −6.9 ± 6.6% (p = 0.002) and this was accompanied by lower La+ values (−12.8 ± 21.6%; p = 0.027). SaO2 was also significantly lower at maximal intensity in comparison with the CTR condition (−1.5 ± 0.3%; p = 0.028). However, both HR and RPE showed a similar trend during both sessions, as well as muscle oxygenation. Nevertheless, the mask caused an increase in brain oxygenation compared with the CTR condition (p < 0.05). In conclusion, our findings suggest that wearing the ETM causes a pronounced increase in O2Hb and tHb in the frontoparietal cortex without any change in the muscle oxygenation.