Miracle-dz/UniFAR-FTUs huggingface dataset:
Acute appendicitis manifests as two microbiome state types with oral pathogens influencing severity

Mounting evidence suggests that acute appendicitis (AA) is not one but two diseases: complicated appendicitis, which is associated with necrosis leading to perforation or periappendicular abscess, and uncomplicated appendicitis, which does not necessarily result in perforation. Even though AA is the most frequent cause of surgery from abdominal pain, little is known about the origins and etiopathogenesis of this disease, much less regarding the different disease types. In this study, we investigated the microbiome of samples from the appendix, rectum and peritoneum of 60 children and adolescents with AA to assess the composition and potential function of bacteria, archaea and fungi. The analysis of the appendix microbial community revealed a shift depending on the severity of the AA. This shift was reflected by two major community state types that represented the complicated and uncomplicated cases. We could demonstrate that complicated, but not uncomplicated, appendicitis is associated with a significant local expansion of oral, bacterial pathogens in the appendix, most strongly influenced by necrotizing Fusobacterium spp. , Porphyromonas and Parvimonas. Uncomplicated appendicitis, however, was characterised by gut-associated microbiomes. Our findings support the hypothesis that two disease types exist in AA, which cannot be distinguished beyond doubt using standard clinical characterization methods or by analysis of the patient’s rectal microbiome. An advanced microbiome diagnosis, however, could improve non-surgical treatment of uncomplicated AA. Importance With a lifetime risk of up to 17%, acute appendicitis is one of the most frequent causes of emergency abdominal surgery in westernized countries. Latest literature reports suggests that appendicitis manifests in two disease types: complicated and uncomplicated appendicitis with different, yet unknown, etiopathogenesis. In this study, we investigated the microbial composition (bacteria, archaea and fungi) from 60 children and adolescents that were diagnosed with acute appendicitis. Appendix, rectal and peritoneal samples were analysed using amplicon and metagenomic sequencing. Our results suggest that acute appendicitis manifests in three microbial state types that reflect complicated and uncomplicated appendicitis as well as special cases that are caused by bacterial overgrowth. Strikingly, uncomplicated appendicitis appears to be caused by gut-associated pathogens while complicated appendicitis is driven by oral-associated microbes such as Fusobacterium sp. or Porphyromonas sp. The findings provided in our study are of special interest to understand the etiopathogenesis of both complicated and uncomplicated appendicitis.
The Paradoxical Role of Humanness in Aggression Toward Conversational Agents

ABSTRACT Conversational Agents (CAs) are becoming part of our everyday lives. About 10 percent of users display aggressive behavior toward CAs, such as swearing at them when they produce errors. We conducted two online experiments to understand user aggression toward CAs better. In the first experiment, 175 participants used either a humanlike CA or a non-humanlike CA. Both CAs worked without errors, and we observed no increased frustration or user aggression. The second experiment (with 201 participants) was the focus of this study; in it, both CAs produce a series of errors. The results show that frustration with errors drives aggression, and users with higher impulsivity are more likely to become aggressive when frustrated. The results also suggest that there are three pathways by which perceived humanness influences users’ aggression to CAs. First, perceived humanness directly increases the frustration with the CA when it produces errors. Second, perceived humanness increases service satisfaction which in turn reduces frustration. Third, perceived humanness influences the nature of aggression when users become frustrated (i.e., users are less likely to use highly offensive words with a more humanlike CA). Our research contributes to our theoretical understanding of the role of anthropomorphism in the interaction with machines, showing that designing a CA to be more humanlike is a double-edged sword—both increasing and decreasing the frustration that leads to aggression—and also a means to reduce the most severe aggression.
The role of neutrophil typing in homeostatic resilience protective model of inflammatory preconditioning

Sepsis is a systemic inflammatory response syndrome (SIRS) characterized by a dysregulated host response to infection that results in organ dysfunction. The response of neutrophils to early inflammation is critical, interferon regulatory factors 4 (IRF4) and interferon regulatory factors 5 (IRF5) are expressed in most cell types of the immune system, but the relationship between the role of IRF4 and IRF5 in preconditioning-protected septic peritonitis mouse model and neutrophils response remains unknown. In this study, we used an E.coli-induced septic peritonitis mouse model and zebrafish model to explore the relationship between neutrophil inflammation and IRF subtype changes in the process of septic peritonitis. Mechanistically, we found that the protein complex formed by polymorphonuclear neutrophils (PMN) and IRF5/MyD88 can secrete pro-inflammatory factors and directly kill invading bacteria. Author Summary Numerous animal and clinical sepsis studies have shown that markedly impaired recruitment of neutrophils to sites of infection and failure to clear bacteria contribute to excessive inflammation and increased mortality in sepsis. In our previous work, we established an Escherichia coli (E.coli) lethal septic peritonitis model and a preconditioning-protected septic peritonitis mouse model. In the early stage of septic peritonitis, a large number of PMN infiltrate the peritoneal cavity, which produces an inflammatory response to invasive bacteria. In this study, the switching process between pro-inflammatory and anti-inflammatory attracted our attention. Our research shows that IRF5-IRF4 regulatory axis leads to a PMN phenotype switch in sepsis and the expression of IRF5 and IRF4 was related to PMN pro-inflammatory (N1 type) and anti-inflammatory (N2 type) phenotypes, respectively.
Polypyrimidine Tract-Binding Protein 1 and hnRNP A1 recognize unique features of the Sm site in U7 snRNA

U7 snRNA is a 60-nucleotide component of U7 snRNP, a multi-subunit endonuclease that cleaves precursors of metazoan replication-dependent histone mRNAs at the 3’ end, hence generating mature histone mRNAs. The Sm site in U7 snRNA differs from the Sm site in spliceosomal snRNAs and promotes the assembly of a unique Sm ring containing Lsm10 and Lsm11 instead of SmD1 and SmD2 found in the spliceosomal snRNPs. The assembly of the spliceosomal Sm ring depends on the SMN complex, with one of its nine subunits, Gemin5, recognizing the spliceosomal Sm site. While the assembly of the U7-specific Sm ring also requires the SMN complex, the unusual Sm site of U7 snRNA is not recognized by Gemin5, and the identity of its counterpart that performs this function in biogenesis of U7 snRNP, has not been determined. Here, we looked for proteins that bind U7 snRNA but not to its mutant altered within the Sm site. We identified Polypyrimidine Tract-Binding Protein 1 (PTBP1) as the main protein that meets this specificity. Binding of PTBP1 to U7 snRNA also depends on the upstream CUCUUU motif that base pairs with histone pre-mRNAs and defines substrate specificity of U7 snRNP. Thus, PTBP1 simultaneously recognizes two functionally essential and highly conserved sites within U7 snRNA. In addition to PTBP1, U7 snRNA interacts with hnRNP A1, which recognizes a different part of the U7-specific Sm site. Interestingly, the two proteins can form with U7 snRNA a larger complex, which also contains SMN protein, a subunit of the SMN complex. Altogether, these results raise the possibility that PTBP1 and hnRNP A1 act collectively to substitute for Gemin5 in the assembly of U7-specific Sm ring.
The minimum intervention principle of optimal control relates the uncontrolled manifold to muscle synergies

The nervous system uses muscle activation patterns to perform successful motor tasks, and motor tasks inevitably satisfy the laws of mechanics. The number of muscles usually exceeds the degrees of freedom of the task such that multiple combinations of muscle activities satisfy mechanical demands. A low-dimensional space usually explains a large variance in the muscle activations, leading to the hypothesis that muscle redundancy is solved by neurally coordinated muscle synergies. In addition to synergies, motor task mechanics also enforce a structure on muscle activity. Muscles satisfy multiple non-negotiable mechanical demands of equilibrium, stability, force, and respect the constraints. The redundancy in the muscle architecture is the degree of freedom available after accounting for the necessary mechanics. In this study, I investigate how task mechanics structure muscle activities by using a biomechanical model of an index finger in contact and published measurements of seven muscle activities during a fingertip force production task. I derive a map from muscle activities to complete task mechanics with the necessary conditions of equilibrium, stability, and force. By invoking the uncontrolled manifold hypothesis, I show that the variability in muscle activities is channeled in the task-irrelevant directions, which is given by the null space of the map from muscle activations to task variables. Furthermore, I show that the principal component that explains maximum variance in muscle activations is oriented along the task-irrelevant direction with the highest projected variance, suggesting that the maximal principal directions correspond to the task-irrelevant subspace rather than the task-relevant directions. This study has consequences for understanding muscular redundancy and synergy, and also provides direct evidence that the simplified biomechanical models satisfy mechanical requirements.
Habitat loss weakens the positive relationship between grassland plant richness and above-ground biomass

Habitat loss and fragmentation per se have been shown to be a major threat to global biodiversity and ecosystem function. However, little is known about how habitat loss and fragmentation per se alters the relationship between biodiversity and ecosystem function (BEF relationship) in the natural landscape context. Based on 130 landscapes identified by a stratified random sampling in the agro-pastoral ecotone of northern China, we investigated the effects of landscape context (habitat loss and fragmentation per se) on plant richness, above-ground biomass, and the relationship between them in grassland communities using a structural equation model. We found that habitat loss directly decreased plant richness and hence decreased above-ground biomass, while fragmentation per se directly increased plant richness and hence increased above-ground biomass. Fragmentation per se also directly decreased soil water content and hence decreased above-ground biomass. Meanwhile, habitat loss decreased the magnitude of the positive relationship between plant richness and above-ground biomass by reducing the percentage of grassland specialists in the community, while fragmentation per se had no significant modulating effect on this relationship. These results demonstrate that habitat loss and fragmentation per se have inconsistent effects on biodiversity and ecosystem function, with the BEF relationship being modulated by landscape context. Our findings emphasise that habitat loss rather than fragmentation per se can weaken the positive BEF relationship by decreasing the degree of habitat specialisation of the community. Highlights BEF relationship is moderated by landscape context in fragmented landscapes. Habitat loss and fragmentation per se have inconsistent effects. Habitat loss can weaken the positive BEF relationship via reducing the percentage of grassland specialists in the community.
Digging deeper into pain – an ethological behavior assay correlating well-being in mice with human pain experience

The pressing need for safer, more efficacious analgesics is felt worldwide. Pre-clinical tests in animal models of painful conditions represent one of the earliest checkpoints novel therapeutics must negotiate before consideration for human use. Traditionally, the pain status of laboratory animals has been inferred from evoked nociceptive assays which measure their responses to noxious stimuli. The disconnect between how pain is tested in laboratory animals and how it is experienced by humans may in part explain the shortcomings of current pain medications and highlights a need for refinement. Here, we survey human chronic pain patients who assert that everyday aspects of life, such as cleaning and leaving the house, are affected by their on-going level of pain. Accordingly, we test the impact of painful conditions on an ethological behavior of mice, digging. Stable digging behavior was observed over time in naïve mice of both sexes. By contrast, deficits in digging were seen following acute knee inflammation. The analgesia conferred by meloxicam and gabapentin was compared in the monosodium iodoacetate knee osteoarthritis model, meloxicam more effectively ameliorating digging deficits, in line with human patients finding meloxicam more effective. Lastly, in a visceral pain model, the decrease in digging behavior correlated with the extent of disease. Ultimately, we make a case for adopting ethological assays, such as digging, in studies of pain in laboratory animals, which we believe to be more representative of the human experience of pain and thus valuable in assessing clinical potential of novel analgesics in animals.
Hippocampal hub failure is linked to long-term memory impairment in anti-NMDA-receptor encephalitis - Insights from structural connectome graph theoretical network analysis

Introduction Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes and the hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization of global and local network changes and their relationship with clinical deficits in NMDAR encephalitis. Objective To investigate changes in structural connectivity and network efficiency in NMDAR encephalitis by use of probabilistic whole-brain tractography and graph theoretical analysis of structural brain networks. Methods Structural networks from sixty-one NMDAR encephalitis patients in the post-acute stage (median time from acute hospital discharge: 18 months) and sixty-one age- and sex-matched healthy controls (HC) were analyzed using diffusion-weighted imaging (DWI)-based probabilistic anatomically-constrained tractography and spherical deconvolution-informed filtering of tractograms. We calculated global, modular, and nodal graph measures indicative of structural connectivity and network reorganization with special focus on default-mode network, medial temporal lobe, and hippocampus. Pathologically altered metrics were included in multiple regression analyses to investigate their potential association with clinical course, disease severity, and cognitive outcome. Results Patients with NMDAR encephalitis showed regular global graph metrics, but bilateral reductions of hippocampal node strength (left: p=0.049; right: p=0.013) and increased node strength of right precuneus (p=0.013) compared to HC. Betweenness centrality was decreased for left-sided entorhinal cortex (p=0.042) and left caudal middle frontal gyrus (p = 0.037). Correlation analyses showed a significant association between reduced left hippocampal node strength and verbal long-term memory impairment (p=0.021) Conclusion Focal network property changes of the medial temporal lobes indicate hippocampal hub failure that is associated with memory impairment in NMDAR encephalitis at the post-acute stage, while global structural network properties remain unaltered. Graph theory analysis provides new pathophysiological insight into structural network changes and their association with persistent cognitive deficits in NMDAR encephalitis.
Design of Cyclic Peptides Targeting Protein–Protein Interactions Using AlphaFold

More than 930,000 protein-protein interactions (PPIs) have been identified in recent years, but their physicochemical properties differ from conventional drug targets, complicating the use of conventional small molecules as modalities. Cyclic peptides are a promising modality for targeting protein-protein interactions (PPIs), but it is difficult to predict the structure of a target protein-cyclic peptide complex or to design a cyclic peptide sequence that binds to the target protein using computational methods. Recently, AlphaFold with a cyclic offset has enabled predicting the structure of cyclic peptides, thereby enabling de novo cyclic peptide designs. We developed a cyclic peptide complex offset to enable the structural prediction of target proteins and cyclic peptide complexes and found AlphaFold2 with a cyclic peptide complex offset can predict structures with high accuracy. We also applied the cyclic peptide complex offset to the binder hallucination protocol of AfDesign, a de novo protein design method using AlphaFold, and we could design a high predicted local-distance difference test and lower separated binding energy per unit interface area than the native MDM2/p53 structure. Furthermore, the method was applied to 12 other protein-peptide complexes and one protein-protein complex. Our approach shows that it is possible to design putative cyclic peptide sequences targeting PPI.
Insights into RAG evolution from the identification of “missing link” family A RAGL transposons

A series of “molecular domestication” events are thought to have converted an invertebrate RAG-like (RAGL) transposase into the RAG1-RAG2 (RAG) recombinase, a critical enzyme for adaptive immunity in jawed vertebrates. The timing and order of these events is not well understood, in part because of a dearth of information regarding the invertebrate RAGL-A transposon family. In contrast to the abundant and divergent RAGL-B transposon family, RAGL-A most closely resembles RAG and is represented by a single orphan RAG1-like (RAG1L) gene in the genome of the hemichordate Ptychodera flava (PflRAG1L-A). Here, we provide evidence for the existence of complete RAGL-A transposons in the genomes of P. flava and several echinoderms. The predicted RAG1L-A and RAG2L-A proteins encoded by these transposons intermingle sequence features of jawed vertebrate RAG and RAGL-B transposases, leading to a prediction of DNA binding, catalytic, and transposition activities that are a hybrid of RAG and RAGL-B. Similarly, the terminal inverted repeats (TIRs) of the RAGL-A transposons combine features of both RAGL-B transposon TIRs and RAG recombination signal sequences. Unlike all previously described RAG2L proteins, PflRAG2L-A and echinoderm RAG2L-A contain an acidic hinge region, which we demonstrate is capable of efficiently inhibiting RAG-mediated transposition. Our findings provide evidence for a critical intermediate in RAG evolution and argue that certain adaptations thought to be specific to jawed vertebrates (e.g., the RAG2 acidic hinge) actually arose in invertebrates, thereby focusing attention on other adaptations as the pivotal steps in the completion of RAG domestication in jawed vertebrates.
KVRangeDB: Rangeueries for A Hash-based Key-value Device

Key-value (KV) software has proven useful to a wide variety of applications including analytics, time-series databases, and distributed ile systems. To satisfy the requirements of diverse workloads, KV stores have been carefully tailored to best match the performance characteristics of underlying solid-state block devices. Emerging KV storage device is a promising technology for both simplifying the KV software stack and improving the performance of persistent storage-based applications. However, while providing fast, predictable put and get operations, existing KV storage devices don’t natively support range queries which are critical to all three types of applications described above. In this paper, we present KVRangeDB, a software layer that enables processing range queries for existing hash-based KV solid-state disks (KVSSDs). As an efort to adapt to the performance characteristics of emerging KVSSDs, KVRangeDB implements log-structured merge tree key index that reduces compaction I/O, merges keys when possible, and provides separate caches for indexes and values. We evaluated the KVRangeDB under a set of representative workloads, and compared its performance with two existing database solutions: a Rocksdb variant ported to work with the KVSSD, and Wisckey, a key-value database that is carefully tuned for conventional block devices. On ilesystem aging workloads, KVRangeDB outperforms Wisckey by 23.7x in terms of throughput and reduce CPU usage and external write ampliications by 14.3x and 9.8x, respectively.
Evolutionary Counterfactual Visual Explanation

The increasing success of deep learning models in recent years comes with the drawback of increasing model complexity. Due to the complexity, model insights are hard to obtain. However, understanding the underlying reasoning for a proposed decision becomes crucial in critical settings. Counterfactual explanations are among the most popular methods to interpret predictions of so-called black-box machine learning models. They provide a form of explanation intuitive to human thinking by building ”what-if” scenarios. Despite their popularity for interpreting tabular data, they find limited adaption in the visual domain. Current approaches to image counterfactuals rely heavily on access to model parameters, additional training data, or surrogate models. However, access to additional information might not always be feasible. We, therefore, propose an evolutionary-based method for counterfactual image generation with a custom mutation operator based on data augmentation to overcome these limitations. We show that generating image counterfactuals solemnly on an input instance and access to the prediction function is possible and performs on par with existing methods.
Representing Death in the News: Journalism, Media and Mortality

Recent years have seen a renewed interest in the relationship between the news, media and death. Driven by a perceived ubiquity of death and dying on television, in newspapers and on the internet, many scholars have attempted to more closely examine aspects of this coverage. The result is that there now exists a large body of scholarly work on death in the news, yet what has been lacking is a comprehensive synthesis of the field. This book seeks to close this gap by analyzing the scholarship on death in the news by way of a thematic approach. It provides a historical overview, looks at the conditions of production, content and reception, and also analyzes emerging trends in the representation of death online. This fascinating account provides a much needed overview of what we currently know about death in the news and provides food for thought for future studies in the field.
PROCEEDINGS OF THE TWENTY-EIGHTH ANNUAL KECK RESEARCH SYMPOSIUM IN GEOLOGY April 2015

Climate conditions in the Weddell Sea during the Pleistocene can be inferred from sediment cores by examining the abundance of foraminifera species and mineral fragments. In particular, Neogloboquadrina incompta is a useful temperature proxy and the abundance of terrigenous sediments is an indication of ice rafting. Using percent abundances enables correlation with other climate studies and with a global δ 18 O isotope stack. The proxies examined indicate at least four oscillations between cold and warm conditions related to global glacial and interglacial stages.