Miracle-dz/UniFAR-FTUs huggingface dataset:
Predators as drivers of insect defenses

Insects have evolved various types of antipredator defenses. For example, many insects have evolved crypsis, and exhibit cryptic body colors and shapes for hiding from predators. Other insects produce toxins as a form of chemical defense against predators, and some toxic insects are aposematic, with conspicuous body colors for advertising their toxins. Insects can also develop hairs, spines or hard exoskeletons as morphological defenses to protect themselves from predation. In addition, insects can evolve behavioral defenses, in which insects exhibit autotomy or dropping, or feign death. This study investigated which predator types evoke these types of defenses, through a review of the effectiveness of antipredator defenses in insects against carnivorous animals that are commonly used as model predators in studies. These predators include other insects, spiders, fish, frogs, lizards, birds and mammals. The results provide the first step for clarifying the evolutionary drivers of antipredator defenses in insects. The following aspects should be considered for future studies: multiple predator species and sufficient replication, alternative prey and predator models, and tolerance to predators in insects.
The ecosystem service of sense of place: benefits for human well-being and biodiversity conservation

SUMMARY Assessing the cultural benefits provided by non-market ecosystem services can contribute previously unknown information to supplement conservation decision-making. The concept of sense of place embeds all dimensions of peoples’ perceptions and interpretations of the environment, such as attachment, identity or symbolic meaning, and has the potential to link social and ecological issues. This review contains: (1) an evaluation of the importance of sense of place as an ecosystem service; and (2) comprehensive discussion as to how incorporating sense of place in an evaluation can uncover potential benefits for both biodiversity conservation and human well-being. Sense of place provides physical and psychological benefits to people, and has neglected economic value. The biodiversity-related experiences are essential components of the service that need to be further explored. A conceptual framework was used to explore how the existing knowledge on sense of place derived from other fields can be used to inform conservation decision-making, but further research is needed to fill existing gaps in knowledge. This review contributes to a better understanding of the role biodiversity plays in human well-being, and should inform the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES).
Frontier Markets: Understanding the Risks

In the search for performance and diversification, an increasing number of investors are spicing up their portfolios with frontier market exchange-traded funds. Many factors have led them to gradually consider strategic allocations to these areas, not the least of which is the fact that emerging economies have become more correlated with developed economies. This study examines whether these small economies are suitable to the average investor in regard to the size of their markets, liquidity, and risk-adjusted performance. It is concluded that, for now, only their undeniable diversification benefits—an outcome that modern portfolio theory has taught us to highly value—tilt the odds in their favor. TOPICS: Exchange-traded funds and applications, frontier markets, risk management Key Findings • Frontier market exchange-traded funds (ETFs) are clearly distinct from their more-developed counterparts, unlike emerging markets, which have become increasingly coupled with developed countries over time. Frontier markets can add meaningful diversification to a portfolio. • The risk-adjusted performance of frontier market ETFs, however, significantly lags that of the SPDR S&P 500 ETF Trust (SPY), a fund used to assess the opportunity cost to invest in these countries in lieu of the United States. • Frontier market ETFs also exhibit high concentration ratios, which could subject them to significant cash outflows from redemptions by a small number of investors.
The Impact of a Forest Pathogen on the Endangered Golden-cheeked Warbler

The Impact of a Forest Pathogen on the Endangered Golden-cheeked Warbler. (May 2012) Laura Roe Stewart, B.S., Michigan State University Chair of Advisory Committee: Dr. Michael L. Morrison Oak wilt is a fatal disease of oaks caused by the fungus Ceratocystis fagacearum. Loss or degradation of habitat due to the disease may negatively affect the federally endangered golden-cheeked warbler (Setophaga chrysoparia). To assess the impact of oak wilt on golden-cheeked warblers, I investigated its influence on habitat selection and quality. I used remote sensing to estimate the amount of potential golden-cheeked warbler habitat currently affected by oak wilt, to predict the amount of potential habitat likely to be affected in the near future, and to assess the current probability of warbler occupancy in areas affected by oak wilt historically. I also quantified vegetative characteristics to assess overstory vegetation and regeneration in areas affected by the disease. I found proportional occupancy and territory density in unaffected areas to be, respectively, 3.5 and 1.8 times that of affected areas. Pairing success was 27% lower for territories containing oak wilt but fledging success was not affected. I estimated that 6.9% of potential golden-cheeked warbler habitat and 7.7% of the total area within my study region was affected by oak wilt in 2008. By 2018, I predicted that 13.3% of potential golden-cheeked warbler habitat and 16.0% of the study region would be
Identifying the Misshapen Head: Craniosynostosis and Related Disorders

Pediatric care providers, pediatricians, pediatric subspecialty physicians, and other health care providers should be able to recognize children with abnormal head shapes that occur as a result of both synostotic and deformational processes. The purpose of this clinical report is to review the characteristic head shape changes, as well as secondary craniofacial characteristics, that occur in the setting of the various primary craniosynostoses and deformations. As an introduction, the physiology and genetics of skull growth as well as the pathophysiology underlying craniosynostosis are reviewed. This is followed by a description of each type of primary craniosynostosis (metopic, unicoronal, bicoronal, sagittal, lambdoid, and frontosphenoidal) and their resultant head shape changes, with an emphasis on differentiating conditions that require surgical correction from those (bathrocephaly, deformational plagiocephaly/brachycephaly, and neonatal intensive care unit-associated skill deformation, known as NICUcephaly) that do not. The report ends with a brief discussion of microcephaly as it relates to craniosynostosis as well as fontanelle closure. The intent is to improve pediatric care providers’ recognition and timely referral for craniosynostosis and their differentiation of synostotic from deformational and other nonoperative head shape changes.
Drug-Drug Interaction Classification Using Attention Based Neural Networks

Drug-drug interaction (DDI) identification is the task of identifying potential interactions between drugs when administered simultaneously. The interactions can be synergetic or antagonistic as one drug can affect the other. Adverse drug reactions caused by antagonistic DDI can pose a serious threat to health and potentially lead to greater increase in health care expenditure. Multiple excellent resources for DDI already exist, although unable to keep up with the exponential increase in published biomedical literature. Most existing systems rely on handcrafted features to extract and classify the relationships between drugs. In this paper, we present a deep learning method of stacked bidirectional Long Short Term Memory (Bi-LSTM) and Convolutional neural (CNN) networks that utilize word embeddings, part-of-speech tags and distance embeddings respectively to perform the DDI extraction task and aid the drug development cycle and drug repurposing. Furthermore, the model uses attention mechanism to better focus on importance of all the hidden states of the Bi-LSTM layers. Experimental results show that our method can better avoid misclassifications of instances with a minimal preprocessing.
The Case for Factor Investing in China A Shares

The Chinese A share market has recently attracted great interest from global investors because of its size and increased importance to the global financial market. The A share market has unique market characteristics and a regulatory environment that make it challenging for institutional investors. The article examines the efficacies of factor strategies by applying well-known equity factors in China A. It demonstrates that traditional factor strategies, with proper design, can deliver attractive risk-adjusted return relative to the cap-weighted benchmark. From the authors’ review of the past literature along with their empirical study, they find that some characteristics of the Chinese stock market influence factor performance and factor strategy design. Notably, the traditional price momentum factor did not work in China A. Instead, a sentiment factor based on return reversal and analyst information can better capture local investors’ behavioral patterns. In addition to carrying out their empirical study, the authors look into a large body of academic research for economic and behavioral explanations of factor anomalies. Their findings provide strong support for factor-based investment strategies in Chinese A shares. TOPICS: Analysis of individual factors/risk premia, factor-based models, style investing, emerging markets Key Findings • The China A stock market has unique characteristics and a regulatory environment that influence factor performance and factor strategy design. • The authors review the academic research on factor investing, discuss the economic and behavioral fundamentals, and show evidence of the factor anomalies in the China A shares. They show that size, value, low vol, and quality factors can deliver attractive excess returns over the cap-weighted benchmark. • The study also finds that the traditional momentum factor failed to deliver positive excess return in the testing period. A sentiment factor is shown to robustly deliver excess returns and may more accurately capture the behavioral patterns that are unique to local market investors.
Long-term Results of Surgery for Colorectal Liver Metastases in Terms of Primary Tumour Location and Clinical Risk Factors

Background/Aim: The aim of the study was to evaluate the influence of primary tumour location and clinical risk factors for long-term results of surgery for colorectal liver metastases (CLMs). Patients and Methods: Overall survival (OS) and recurrence-free survival (RFS) were evaluated in 636 patients. Patients were divided by tumour location (right-/left-sided colorectal cancer: RCRC/LCRC; rectal cancer), and age, gender, number and size of CLMs, type of liver surgery and interval from primary operation were evaluated. Results: One-, 3- and 5-year OS and RFS were independent of primary tumour location (p<0.59). CLM diameter was negatively associated with OS for the whole cohort (p<0.002), and RCRC (p<0.03) and LCRC (p<0.04) groups, as well as for RFS of those with LCRC (p<0.04). CLM number was negatively associated with RFS for the whole cohort (p<0.0001), RCRC (p<0.02), LCRC (p<0.0001) and RC (p<0.02). Radiofrequency ablation and combined procedures led to worse OS for the whole cohort (p<0.03), and to worse RFS for the whole cohort (p<0.0003) and for those with LCRC (p<0.03). A shorter interval between primary colorectal cancer surgery and CLMs procedure was risky for poor OS and RFS of patients with CLMs from RCRC (p<0.05), LCRC (p<0.05) and RC (p<0.02). Conclusion: Primary tumour location together with clinical risk factors are important for long-term results of surgery CLMs.
Centromeric repeats of the Western European house mouse I: high sequence diversity among monomers at local and global spatial scales

Previous work found that the centromeric repeats of the Western European house mouse (Mus musculus domesticus) are composed predominantly of a 120 bp monomer that is shared by the X and autosomes. Polymorphism in length and sequence was also reported. Here I quantified the length and sequence polymorphism of the centromeric repeats found on the X and autosomes. The levels of local and global sequence variation were also compared. I found three length variants: a 64mer, 112mer and 120mer with relative frequencies of 2.4%, 8.6%, and 89%, respectively. There was substantial sequence variation within all three length variants with a rank-order of: 64mer < 120mer < 112mer. The 64mer was never found alone on long Sanger traces, and was arranged predominantly as a 176 bp higher-order repeat composed of a 64/112mer dimer. Reanalysis of archived ChIP-seq reads found that all three length variants were enriched with the foundational centromere protein CENP-A, but the enrichment was far higher for the 120mer. This pattern indicates that only the 120mer contributes substantially to the functional centromeres, i.e., to the kinetochore-binding, centric cores of the centromeric repeat arrays. Despite only moderate sequence divergence among random pairs of 120mers (averaging 5.9%), other measures of sequence diversity were exceptionally high: i) variant richness (numerical diversity) –on average, one new sequence variant was observed every 4th additional monomer randomly sampled (in N = 7.2 × 103 monomers), and ii) variant evenness –all of the nearly 2 × 103 observed sequence variants were at low frequency, with the most common variant having a frequency of only 5.7%. I next used long Sanger trace data from the Mouse Genome Project to assess the pattern of monomer diversity among neighboring 120mers. Unexpectedly, side-by-side monomers were rarely identical in sequence, and sequence divergence between these neighbors was nearly as high as that between random pairs taken from the genome-wide pool of all 120mers. I also used long Sanger traces to determine sequence variation among neighborhoods of 5 contiguous 120 bp monomers. Sequence diversity within these small regions typically spanned most of the entire range of that found genome-wide. Despite high sequence variation within these neighborhoods, the density of monomers with functional binding motifs for CENP-B (i.e., b-boxes with sequence NTTCGNNNNANNCGGGN) was strongly conserved at about 50%. The overarching pattern of monomer structure at the centromeric repeats of this subspecies is: i) high homogeneity in the density CENP-B binding sites, and ii) high heterogeneity in monomer sequence at both local and global levels.
SynapsEM: Computer-Assisted Synapse Morphometry

The structural features of a synapse, in part, determine its output. Synapses are extremely small and tightly packed with vesicles and other organelles. Visualizing synaptic structure requires imaging by electron microscopy, and the features in micrographs must be quantified using morphometry. Three parameters are typically assessed from each specimen: 1) the sizes of individual vesicles and organelles, 2) the absolute number and densities of organelles, and 3) distances between organelles and key features at synapses such as active zone membranes and dense projections. For data to be valid, the analysis must be repeated from hundreds or thousands of images from several biological replicates, a daunting task. Here we report a custom computer program to analyze these features: SynapsEM. In short, we developed macros for ImageJ/Fiji to record x,y-coordinates of segmented structures; the coordinates are then exported as text files. Independent investigators can reload the images and text files to confirm or re-evaluate the segmentation using ImageJ. The Matlab program calculates and reports key synaptic parameters from the coordinates. Since the values are calculated, rather than measured from each micrograph, other parameters can be extracted in Matlab by additional scripting. Thus, this program can accelerate morphometry of synapses and promote a more comprehensive analysis of synaptic ultrastructure.
Release probability increases towards distal dendrites boosting high-frequency signal transfer

Dendritic integration of synaptic inputs entangles their increased electrotonic attenuation at distal dendrites, which can be counterbalanced by the increased synaptic receptor density. However, during sustained network activity the influence of individual synapses depends on their release properties. How these properties are distributed along dendrites remains poorly understood. Here, we employed classical optical quantal analyses and a genetically encoded optical glutamate sensor in acute hippocampal slices to monitor release at CA3-CA1 synapses. We find that their release probability increases with greater distances from the soma. Similar-fidelity synapses tend to group together whereas release probability shows no trends regarding the within-branch position. Simulations with a realistic CA1 pyramidal cell hosting stochastic synapses suggest that the observed trends boost signal transfer fidelity, particularly at higher input frequencies. Because high-frequency bursting has been associated with learning, the release probability pattern we have found may play a key role in memory trace formation.
Diagnostic accuracy at the first episode of psychosis in Uganda.

Background: Correct clinical diagnosis at the first episode of psychosis may be difficult due to many non-specific symptoms. We determined the factors associated with a correct diagnosis among patients with a first episode of psychosis in Uganda. Methods: A cross-sectional study design was performed at the national psychiatric referral and teaching hospital in Uganda. Treatment naive participants aged 18 to 60 years with a diagnosis of a psychotic disorder were included. Patients with organic disorders like HIV/AIDS, syphilis and substance use disorders were excluded. The MINI International neuropsychiatric inventory was administered to confirm the clinical diagnosis. Concordance was based on the percentage agreement and kappa statistic between the admission chart diagnosis and the MINI diagnosis. Results: 178 participants with the first episode of psychosis were included in the final analysis. The agreement between the MINI diagnosis and clinician diagnosis was 0.385, (P < 0.001) with a concordance of 49.5%. After controlling for nationality and the household source of income, duration of untreated psychosis, p-value 0.028( 95%CI: 0.07-0.89), living with a primary family member, p-value 0.038(95%CI:0.95-2.86) and the cadre of the clinician who made the initial diagnosis[Medical officer, p-value 0.011( 95%CI: 0.18-0.80) were associated with a correct diagnosis. Conclusion: There was low agreement between clinician diagnoses and MINI diagnoses at the first episode of psychosis. Improved training of staff while considering the duration of untreated psychosis and the living arrangements of the patient may improve diagnostic accuracy in this population.
Diagnostic power of resting‐state fMRI for detection of network connectivity in Alzheimer's disease and mild cognitive impairment: A systematic review

Resting‐state fMRI (rs‐fMRI) detects functional connectivity (FC) abnormalities that occur in the brains of patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI). FC of the default mode network (DMN) is commonly impaired in AD and MCI. We conducted a systematic review aimed at determining the diagnostic power of rs‐fMRI to identify FC abnormalities in the DMN of patients with AD or MCI compared with healthy controls (HCs) using machine learning (ML) methods. Multimodal support vector machine (SVM) algorithm was the commonest form of ML method utilized. Multiple kernel approach can be utilized to aid in the classification by incorporating various discriminating features, such as FC graphs based on “nodes” and “edges” together with structural MRI‐based regional cortical thickness and gray matter volume. Other multimodal features include neuropsychiatric testing scores, DTI features, and regional cerebral blood flow. Among AD patients, the posterior cingulate cortex (PCC)/Precuneus was noted to be a highly affected hub of the DMN that demonstrated overall reduced FC. Whereas reduced DMN FC between the PCC and anterior cingulate cortex (ACC) was observed in MCI patients. Evidence indicates that the nodes of the DMN can offer moderate to high diagnostic power to distinguish AD and MCI patients. Nevertheless, various concerns over the homogeneity of data based on patient selection, scanner effects, and the variable usage of classifiers and algorithms pose a challenge for ML‐based image interpretation of rs‐fMRI datasets to become a mainstream option for diagnosing AD and predicting the conversion of HC/MCI to AD.
CDK2 activity determines the timing of cell-cycle commitment and sequential DNA replication

To enter the cell cycle, mammalian cells must cross a point of no return (the commitment point), after which they proceed through the cell cycle regardless of changes in external signaling. This process is tightly regulated by the cyclin-dependent kinases (CDKs) and downstream molecules such as retinoblastoma (Rb). Here we show that CDK2 activity coordinates the timing of cell-cycle commitment and DNA replication. CDK4/6 activation initiates Rb phosphorylation and E2F activity, causing a gradual increase in CDK2 activity. Once CDK2 activity reaches a threshold level, CDK2 triggers the commitment point by maintaining Rb phosphorylation and subsequently initiates DNA replication. While the timing of the commitment point is tightly coupled with DNA replication, our experiments, which acutely increased CDK2 activity, suggest that the timing of the commitment point is before DNA replication. These findings highlight how cells utilize a safety mechanism to maintain genome stability by protecting against incomplete DNA replication.
Linking short-term behavior and personalities to feeding and mating rates in female water striders

In systems of strong sexual conflict, male harassment can constrain female feeding, which can limit fecundity. Female responses to harassment can depend on the social context or differ between individuals, and could be based on social or intrinsic behavioral cues at different spatio-temporal scales. Using experimental groupings of stream water striders (Aquarius remigis), we examined individual behavioral differences and effects of sex ratio on 4 aspects of female behavior: 1) habitat use and 2) activity, which lead to differences in 3) feeding rates and 4) mating rates. We compared effects of the immediate social environment, immediate female habitat use and activity, and consistent female behavioral tendencies (personalities) on feeding and mating probabilities, and asked if population sex ratio affected the relationships among these behaviors. We found that individual females did differ significantly in all 4 behaviors. Population sex ratio strongly influenced average female habitat use, feeding, and mating behaviors, and female feeding and mating behaviors were predicted by a combination of moment-to-moment female behavioral state, moment-to-moment social factors, and consistent individual female behavioral differences. Furthermore, habitat use tendencies correlated significantly with activity tendencies, and habitat use and activity tendencies predicted mating probabilities, but not feeding probabilities. Our study elucidates the specific individual-level behavioral mechanisms that lead to observed population-level patterns and emphasizes the benefits of studying behavior at multiple spatial and temporal scales.