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The extent and origin of variation in the replication dynamics of complex DNA viruses is not well-defined. Here, we investigate the vaccinia virus (VACV) infection cycle at the single-cell level, quantifying the temporal dynamics of early and post(dna)-replicative phase gene expression across thousands of infections. We found that viral factors determine the initiation time of these phases, and this is influenced by the multiplicity of infection (MOI). In contrast, virus production dynamics are largely constrained by the host cell. Additionally, between-cell variability in infection start time and virus production rate were strongly influenced by MOI, providing evidence for cooperativity between infecting virions. Blocking programmed cell death by pan-caspase inhibition increased infection frequency but not virus production at the population level due to a concurrent attenuation of per-cell virus yield, suggesting a dual role for caspase signaling in VACV infection. Our findings provide key insights into the pivotal factors influencing heterogeneity in the infection cycle of a large DNA virus at the single-cell level. Author summary: The successful transmission and progression of a viral infection depends on the initial infectious virus dose, which in turn is defined by the efficiency of virus replication within host cells. Understanding what determines the productivity of individual cells, and the variability between them, is a central question in the emerging field of single-cell virology. Our study investigates the single-cell infection dynamics of vaccinia virus (VACV), a large, complex, DNA virus, revealing a profound influence of initial infectious dose on the timing and rate of progression of virus replication. Cells infected with a low dose take over three times longer to initiate virus production compared to those with a higher dose. However, the dynamics of the second phase of infection, de novo production of virus, are unperturbed by this variable: a higher infectious dose does not equate to a greater yield. Furthermore, we observed that the proportion of cells advancing to productive replication increases markedly with the virus dose. This effect is compounded by the suppression of apoptosis, a cell death process, suggesting that induction of apoptosis is effective in pruning the population of susceptible host cells. This has broad implications for the pathogenesis of viral diseases as the infectious dose will govern the window of opportunity for the host immune system to effectively respond to the infection. This research contributes to the broader field of single-cell virology by highlighting the complex relationship between virus dose and infection dynamics at the cellular level. [ABSTRACT FROM AUTHOR]

Archbishop Wulfstan of York's interpolation in the DE version of the Anglo‐Saxon Chronicle entry for the year 959 is out of character for both the churchman himself and for the pre‐Conquest period as a whole, as it is the only text from early England critical of King Edgar. This article shows that Wulfstan's complaints about Edgar, which focus on the king's policies related to Scandinavians in England, are rooted in the monarch's probable official employment of Scandinavians and in the law code IV Edgar. Ultimately, this article argues that Wulfstan's criticisms of Edgar are best understood in relation to the archbishop's notion that royal policy could have significant long‐term negative consequences, especially if such policy contravened Wulfstan's understanding of the will of God. [ABSTRACT FROM AUTHOR]

Despite efforts to improve targeting accuracy of the dorsolateral prefrontal cortex (DLPFC) as a repetitive transcranial magnetic stimulation (rTMS) target for Major Depressive Disorder (MDD), the heterogeneity in clinical response remains unexplained. We sought to compare the patterns of functional connectivity from the DLPFC treatment site in patients with MDD who were TMS responders to those who were TMS non-responders. Baseline anatomical T1 magnetic resonance imaging (MRI), resting-state functional MRI, and diffusion weighted imaging scans were obtained from 37 participants before they underwent a course of rTMS to left Brodmann area 46. A novel machine learning method was utilized to identify brain regions associated with each item of the Beck's Depression Inventory II (BDI-II), and for 26 participants who underwent rTMS treatment over the left Brodmann area 46, identify regions differentiating rTMS responders and non-responders. Nine parcels of the Human Connectome Project Multimodal Parcellation Atlas matched to at least three items of the Beck's Depression Inventory II (BDI-II) as predictors of response to rTMS, with many in the temporal, parietal and cingulate cortices. Additionally, pre-treatment mapping for 17 items of the BDI-II demonstrated significant variability in symptom to parcel mapping. When parcels associated with symptom presence and symptom resolution were compared, 15 parcels were uniquely associated with resolution (potential targets), and 12 parcels were associated with both symptom presence and resolution (blockers or biomarkers). Machine learning approaches show promise for the development of pathoanatomical diagnosis and treatment algorithms for MDD. Prospective studies are required to facilitate clinical translation. • Novel machine learning was used on MRI scans of individuals with depression. • It was found that Human Connectome Project parcels were found as predictors of response to TMS. • 12 parcels were found to be related to both symptom presence and resolution following TMS. • These could provide insight into new potential symptom-specific targets for TMS. [ABSTRACT FROM AUTHOR]

Using a ResNet-18 Network to Detect Features of Alzheimer's Disease on Functional Magnetic Resonance Imaging: A Failed Replication. Among efforts is to predict the conversion of Mild Cognitive Impairment (MCI) to AD [[1]]. According to baseline diagnosis, 436 subjects were controls, 199 had Mild Cognitive Impairment (MCI), 88 had early MCI (EMCI), 37 had late MCI (LMCI), and 62 had Alzheimer's Disease (AD). The model is therefore likely recognizing the patients it has already encountered in the training set, rather than recognizing the features of MCI or AD. [Extracted from the article]

For over a century, neuroscientists have been working toward parcellating the human cortex into distinct neurobiological regions. Modern technologies offer many parcellation methods for healthy cortices acquired through magnetic resonance imaging. However, these methods are suboptimal for personalized neurosurgical application given that pathology and resection distort the cerebrum. We sought to overcome this problem by developing a novel connectivity‐based parcellation approach that can be applied at the single‐subject level. Utilizing normative diffusion data, we first developed a machine‐learning (ML) classifier to learn the typical structural connectivity patterns of healthy subjects. Specifically, the Glasser HCP atlas was utilized as a prior to calculate the streamline connectivity between each voxel and each parcel of the atlas. Using the resultant feature vector, we determined the parcel identity of each voxel in neurosurgical patients (n = 40) and thereby iteratively adjusted the prior. This approach enabled us to create patient‐specific maps independent of brain shape and pathological distortion. The supervised ML classifier re‐parcellated an average of 2.65% of cortical voxels across a healthy dataset (n = 178) and an average of 5.5% in neurosurgical patients. Our patient dataset consisted of subjects with supratentorial infiltrating gliomas operated on by the senior author who then assessed the validity and practical utility of the re‐parcellated diffusion data. We demonstrate a rapid and effective ML parcellation approach to parcellation of the human cortex during anatomical distortion. Our approach overcomes limitations of indiscriminately applying atlas‐based registration from healthy subjects by employing a voxel‐wise connectivity approach based on individual data. [ABSTRACT FROM AUTHOR]

It is common for the Judith tale to be connected to the festival of Hanukkah. In this context, mostly, an acknowledgment is made that this connection between Judith and Hanukkah is of medieval Jewish provenance. Furthermore, it is quite clear that LXX Judith neither makes reference to Hanukkah nor alludes to that specific festival. However, despite being an obviously ludic text, LXX Judith makes pointed references to specific dates (albeit seemingly out of context) and certain agricultural activities that when viewed from a purely Jewish context strongly imply periods engaged with other Jewish festivals. Indeed, as an example, a knowledgeable reader following the explicit time line set out in LXX Judith would be in no doubt that the meeting between Judith and Holofernes occurred sometime in Av. The reader would also understand that the primary theme of the narrative is the ultimate protection of the Holy Temple. This is not a tale about rededication but rather halting an enemy, focused on destroying the Temple. Nowhere in the text is there even a hint that the Second Temple has been desecrated or made unclean. It is portrayed as intact and functioning correctly in Jewish society. The subtle references to the month of Av are clearly appropriate because they remind the reader of the worst-case scenario should the enemies of the Jews not be stopped. The fact that (in the tale) the Second Temple is saved during the month of Av helps to negate the destruction of the First Temple at the same time of year. If interpreted correctly it would appear that the Judith tale as espoused in LXX Judith was originally intended to be associated with Tish‘a B’Av and not Hanukkah. [ABSTRACT FROM AUTHOR]

Introduction: Data‐driven approaches to transcranial magnetic stimulation (TMS) might yield more consistent and symptom‐specific results based on individualized functional connectivity analyses compared to previous traditional approaches due to more precise targeting. We provide a proof of concept for an agile target selection paradigm based on using connectomic methods that can be used to detect patient‐specific abnormal functional connectivity, guide treatment aimed at the most abnormal regions, and optimize the rapid development of new hypotheses for future study. Methods: We used the resting‐state functional MRI data of 28 patients with medically refractory generalized anxiety disorder to perform agile target selection based on abnormal functional connectivity patterns between the Default Mode Network (DMN) and Central Executive Network (CEN). The most abnormal areas of connectivity within these regions were selected for subsequent targeted TMS treatment by a machine learning based on an anomalous functional connectivity detection matrix. Areas with mostly hyperconnectivity were stimulated with continuous theta burst stimulation and the converse with intermittent theta burst stimulation. An image‐guided accelerated theta burst stimulation paradigm was used for treatment. Results: Areas 8Av and PGs demonstrated consistent abnormalities, particularly in the left hemisphere. Significant improvements were demonstrated in anxiety symptoms, and few, minor complications were reported (fatigue (n = 2) and headache (n = 1)). Conclusions: Our study suggests that a left‐lateralized DMN is likely the primary functional network disturbed in anxiety‐related disorders, which can be improved by identifying and targeting abnormal regions with a rapid, data‐driven, agile aTBS treatment on an individualized basis. [ABSTRACT FROM AUTHOR]

Understanding the relationship between host and pathogen is key to combatting disease. SMAD transcription factors, which transmit TGF-β superfamily signalling, mediate an array of outcomes during embryogenesis, inflammation, cancer, and immunity. Surprisingly, these activities can sometimes be directly opposed; for example, SMAD3 has been reported as tumour suppressor by arresting cell cycle progression but conversely promotes cancer metastasis. A growing body of literature has identified SMADs as prominent targets during viral and bacterial infection for modulating host signalling. During infection, the activity of SMAD-containing transcriptional complexes can be finely tuned by pathogens to enhance infectivity and spread. SMAD signalling can be modulated at many levels, such as upstream at the ligand and receptor, or by direct interactions with SMADs. These alterations can increase pathogen dissemination, induce fibrosis, over-activate, or attenuate the host immune response. Here, we summarise the diverse mechanisms by which pathogens have evolved to sway SMAD signalling in their favour. Understanding the intricacies of host–pathogen interactions through this lens may elucidate aspects of SMAD function in cancer development, homoeostasis, and immune signalling previously overlooked. These insights are an opportunity to identify novel TGF-β or BMP-targeted therapeutics for applications to infectious disease contexts. • Viral and bacterial pathogens modulate SMAD transcription factors during infection. • Different SMAD-containing transcription factor complexes are associated with distinct functional outcomes during infection. • Viral and bacterial modulation of SMAD activity provides novel insights into their regulation and functions. • SMAD transcription factors represent attractive targets for therapeutic interventions. [ABSTRACT FROM AUTHOR]

(Echocardiography 2011;28:921-924) [ABSTRACT FROM AUTHOR]

Abstract: Ethyl glucuronide (ethyl-β-d-6-glucosiduronic acid, EtG), a unique metabolite of ethanol, has received much recent attention as a sensitive and specific biological marker of ethanol consumption. Formed in the liver via conjugation of ethanol with activated glucuronate, EtG remains detectable in serum, plasma, and hair for days after ethanol abuse. Thus far, gas chromatography–mass spectrometry and enzyme-linked immunosorbent assays have been developed to detect trace quantities of EtG for forensic purposes, but reports of the nuclear magnetic resonance (NMR) properties of EtG have been scarce. Herein we present the first report of EtG determination using proton NMR spectroscopy. We collected 700-MHz proton spectra of liver extracts from rats treated with a 4-day binge ethanol protocol (average ethanol dose: 8.6g/kg/day). An unexpected signal (triplet, 1.24ppm) appeared in ethanol-treated liver extracts but not in control samples; based on chemical shift and multiplicity, we suspected EtG. We observed quantitative hydrolysis of the unknown species to ethanol while incubating our samples with β-glucuronidase, confirming that the methyl protons of EtG were responsible for the triplet at 1.24ppm. This study demonstrates that proton NMR spectroscopy is capable of detecting EtG and that future NMR-based metabolomic studies may encounter this metabolite of ethanol. [Copyright &y& Elsevier]

The recently described ‘papillary glioneuronal tumour’ is not currently included in the WHO classification of tumours of the CNS. We present the youngest recorded case to date, and only the 3rd documented in the paediatric population. The incorporation of this neoplasm into the WHO classification would facilitate its wider recognition, providing an opportunity to elucidate its natural history and determine an evidence-based approach to treatment.Copyright © 2002 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

Discusses the identity manifested in the image of the crucified Jesus as depicted in the cross. Image of Christ envisaged by contemporary theologians; Conflict on the image of Christ as powerful and meek; Analysis of the sacrifice made by Christ to save the world.

Focuses on the nature of Christian morality. Stories in the Old Testament which were morally reprehensible; Actions of Jesus Christ that characterize his morality; Distinctions of Christian morality.

Purpose: Current limitations in methodologies used throughout machine-learning to investigate feature importance in boosted tree modelling prevent the effective scaling to datasets with a large number of features, particularly when one is investigating both the magnitude and directionality of various features on the classification into a positive or negative class. This manuscript presents a novel methodology, "Hollow-tree Super" (HOTS), designed to resolve and visualize feature importance in boosted tree models involving a large number of features. Further, this methodology allows for accurate investigation of the directionality and magnitude various features have on classification and incorporates cross-validation to improve the accuracy and validity of the determined features of importance. Methods: Using the Iris dataset, we first highlight the characteristics of HOTS by comparing it to other commonly used techniques for feature importance, including Gini Importance, Partial Dependence Plots, and Permutation Importance, and explain how HOTS resolves the weaknesses present in these three strategies for investigating feature importance. We then demonstrate how HOTS can be utilized in high dimensional spaces such as neuroscientific setting, by taking 60 Schizophrenic subjects from the publicly available SchizConnect database and applying the method to determine which regions of the brain were most important for the positive and negative classification of schizophrenia as determined by the positive and negative syndrome scale (PANSS). Results: HOTS effectively replicated and supported the findings of feature importance for classification of the Iris dataset when compared to Gini importance, Partial Dependence Plots and Permutation importance, determining 'petal length' as the most important feature for positive and negative classification. When applied to the Schizconnect dataset, HOTS was able to resolve from 379 independent features, the top 10 most important features for classification, as well as their directionality for classification and magnitude compared to other features. Cross-validation supported that these same 10 features were consistently used in the decision-making process across multiple trees, and these features were localised primarily to the occipital and parietal cortices, commonly disturbed brain regions in those afflicted with Schizophrenia. Conclusion: HOTS effectively overcomes previous challenges of identifying feature importance at scale, and can be utilized across a swathe of disciplines. As computational power and data quantity continues to expand, it is imperative that a methodology is developed that is able to handle the demands of working with large datasets that contain a large number of features. This approach represents a unique way to investigate both the directionality and magnitude of feature importance when working at scale within a boosted tree model that can be easily visualized within commonly used software. [ABSTRACT FROM AUTHOR]

Neurosurgeons have limited tools in their armamentarium to visualize critical brain networks during surgical planning. Quicktome was designed using machine-learning to generate robust visualization of important brain networks that can be used with standard neuronavigation to minimize those deficits. We sought to see whether Quicktome could help localize important cerebral networks and tracts during intracerebral surgery. We report on all patients who underwent keyhole intracranial surgery with available Quicktome-enabled neuronavigation. We retrospectively analyzed the locations of the lesions and determined functional networks at risks, including chief executive network, default mode network, salience, corticospinal/sensorimotor, language, neglect, and visual networks. We report on the postoperative neurologic outcomes of the patients and retrospectively determined whether the outcomes could be explained by Quicktome's functional localizations. Fifteen high-risk patients underwent craniotomies for intra-axial tumors, with the exception of one meningioma and one case of leukoencephalopathy. Eight patients were male. The median age was 49.6 years. Quicktome was readily integrated in our existing navigation system in every case. New postoperative neurologic deficits occurred in 8 patients. All new deficits, except for one resulting from a postoperative stroke, were expected and could be explained by preoperative findings by Quicktome. In addition, in those who did not have new neurologic deficits, Quicktome offered explanations for their outcomes. Quicktome helps to visualize complex functional connectomic networks and tracts by seamlessly integrating into existing neuronavigation platforms. The added information may assist in reducing neurological deficits and offer explanations for postsurgical outcomes. [ABSTRACT FROM AUTHOR]

This article focuses on a study regarding the oral health of a group of non-institutionalised mentally handicapped adults in Great Britain, published in the December 1991 issue of the journal "Community Dentistry and Oral Epidemiology." In 1989, 350 of the 418 mentally handicapped adults attending social services day centres were examined. Diagnosis of dental caries was mainly visual. Assessments of plaque, gingivitis and calculus were made by mouth sextant. The whole study population had a mean age of 33.92. There was identification cohort of severely affected individuals, who had particularly poor plaque control and severe gingivitis.

Judgement is a higher-order brain function utilized in the evaluation process of problem solving. However, heterogeneity in the task methodology based on the many definitions of judgement and its expansive and nuanced applications have prevented the identification of a unified cortical model at a level of granularity necessary for clinical translation. Forty-six task-based fMRI studies were used to generate activation-likelihood estimations (ALE) across moral, social, risky, and interpersonal judgement paradigms. Cortical parcellations overlapping these ALEs were used to delineate patterns in neurocognitive network engagement for the four judgement tasks. Moral judgement involved the bilateral superior frontal gyri, right temporal gyri, and left parietal lobe. Social judgement demonstrated a left-dominant frontoparietal network with engagement of right-sided temporal limbic regions. Moral and social judgement tasks evoked mutual engagement of the bilateral DMN. Both interpersonal and risk judgement were shown to involve a right-sided frontoparietal network with accompanying engagement of the left insular cortex, converging at the right-sided CEN. Cortical activation in normophysiological judgement function followed two separable patterns involving the large-scale neurocognitive networks. Specifically, the DMN was found to subserve judgement centered around social inferences and moral cognition, while the CEN subserved tasks involving probabilistic reasoning, risk estimation, and strategic contemplation. [ABSTRACT FROM AUTHOR]

The pleiotropic hormone leptin has a pivotal role in regulating energy balance by inhibiting hunger and increasing energy expenditure. Homozygous mutations found in the leptin gene are associated with extreme obesity, marked hyperphagia, and impaired immune function. Although these mutations have been characterized in vivo, a detailed understanding of how they affect leptin structure and function remains elusive. In the current work, we used NMR, differential scanning calorimetry, molecular dynamics simulations, and bioinformatics calculations to characterize the effects of these mutations on leptin structure and function and binding to its cognate receptor. We found that mutations identified in patients with congenital leptin deficiency not only cause leptin misfolding or aggregation, but also cause changes in the dynamics of leptin residues on the receptor-binding interface. Therefore, we infer that mutationinduced leptin deficiency may arise from several distinct mechanisms including (i) blockade of leptin receptor interface II, (ii) decreased affinity in the second step of leptin's interaction with its receptor, (iii) leptin destabilization, and (iv) unsuccessful threading through the covalent loop, leading to leptin misfolding/ aggregation. We propose that this expanded framework for understanding the mechanisms underlying leptin deficiency arising from genetic mutations may be useful in designing therapeutics for leptin-associated disorders. [ABSTRACT FROM AUTHOR]