Miracle-dz/UniFAR-FTUs huggingface dataset:
Fine-grained Correlation Loss for Regression

Regression learning is classic and fundamental for medical image analysis. It provides the continuous mapping for many critical applications, like the attribute estimation, object detection, segmentation and non-rigid registration. However, previous studies mainly took the case-wise criteria, like the mean square errors, as the optimization objectives. They ignored the very important population-wise correlation criterion, which is exactly the final evaluation metric in many tasks. In this work, we propose to revisit the classic regression tasks with novel investigations on directly optimizing the fine-grained correlation losses. We mainly explore two complementary correlation indexes as learnable losses: Pearson linear correlation (PLC) and Spearman rank correlation (SRC). The contributions of this paper are two folds. First, for the PLC on global level, we propose a strategy to make it robust against the outliers and regularize the key distribution factors. These efforts significantly stabilize the learning and magnify the efficacy of PLC. Second, for the SRC on local level, we propose a coarse-to-fine scheme to ease the learning of the exact ranking order among samples. Specifically, we convert the learning for the ranking of samples into the learning of similarity relationships among samples. We extensively validate our method on two typical ultrasound image regression tasks, including the image quality assessment and bio-metric measurement. Experiments prove that, with the fine-grained guidance in directly optimizing the correlation, the regression performances are significantly improved. Our proposed correlation losses are general and can be extended to more important applications.
Dissecting Self-Supervised Learning Methods for Surgical Computer Vision

The field of surgical computer vision has undergone considerable breakthroughs in recent years with the rising popularity of deep neural network-based methods. However, standard fully-supervised approaches for training such models require vast amounts of annotated data, imposing a prohibitively high cost; especially in the clinical domain. Self-Supervised Learning (SSL) methods, which have begun to gain traction in the general computer vision community, represent a potential solution to these annotation costs, allowing to learn useful representations from only unlabeled data. Still, the effectiveness of SSL methods in more complex and impactful domains, such as medicine and surgery, remains limited and unexplored. In this work, we address this critical need by investigating four state-of-the-art SSL methods (MoCo v2, SimCLR, DINO, SwAV) in the context of surgical computer vision. We present an extensive analysis of the performance of these methods on the Cholec80 dataset for two fundamental and popular tasks in surgical context understanding, phase recognition and tool presence detection. We examine their parameterization, then their behavior with respect to training data quantities in semi-supervised settings. Correct transfer of these methods to surgery, as described and conducted in this work, leads to substantial performance gains over generic uses of SSL - up to 7.4% on phase recognition and 20% on tool presence detection - as well as state-of-the-art semi-supervised phase recognition approaches by up to 14%. Further results obtained on a highly diverse selection of surgical datasets exhibit strong generalization properties. The code is available at https://github.com/CAMMA-public/SelfSupSurg.
Direct and spillover effects of a new tramway line on the commercial vitality of peripheral streets. A synthetic-control approach

In cities, the creation of public transport infrastructure such as light rails can cause changes on a very detailed spatial scale, with different stories unfolding next to each other within a same urban neighborhood. We study the direct effect of a light rail line built in Florence (Italy) on the retail density of the street where it was built and and its spillover effect on other streets in the treated street's neighborhood. To this aim, we investigate the use of the Synthetic Control Group (SCG) methods in panel comparative case studies where interference between the treated and the untreated units is plausible, an issue still little researched in the SCG methodological literature. We frame our discussion in the potential outcomes approach. Under a partial interference assumption, we formally define relevant direct and spillover causal effects. We also consider the ``unrealized'' spillover effect on the treated street in the hypothetical scenario that another street in the treated unit's neighborhood had been assigned to the intervention.
Many-particle covalency, ionicity, and atomicity revisited for a few simple example molecules

We analyze two-particle binding factors of H2, LiH, and HeH+ molecules/ions with the help of our original exact diagonalization ab initio approach. The interelectronic correlations are taken into account rigorously within the second quantization scheme for restricted basis of renormalized single-particle wave functions, i.e., with their size readjusted in the correlated state. This allows us to determine the many-particle covalency and ionicity factors in a natural and intuitive manner in terms of the microscopic single-particle and interaction parameters, also determined within our method. We discuss the limitations of those basic characteristics and introduce the concept of atomicity, corresponding to the Mott and Hubbard criterion concerning localization threshold in many-particle systems. This addition introduces an atomic ingredient into the electron states and thus removes a spurious behavior of covalency with the increasing interatomic distance, as well as provides a more complete physical interpretation of bonding.
Lightweight Authentication and Key Agreement for Smart Metering in Smart Energy Networks

Smart meters (SMs) are considered as foundational part of the smart metering infrastructure (SMI) in smart energy networks (SENs). SM is a digital device that makes use of two-way communication between consumer and utility to exchange, manage and control energy consumptions within a home. However, despite all the features, an SM raises several security-related concerns. For instance, how to exchange data between the legal entities (e.g., SM and utility server) while maintaining privacy of the consumer. To address these concerns, authentication and key agreement in SMI can provide important security properties that not only to maintain a trust between the legitimate entities but also to satisfy other security services. This work presents a lightweight authentication and key agreement that enables trust, anonymity, integrity and adequate security in the domain of SEN. The proposed scheme employs hybrid cryptography to facilitate mutual trust (authentication), dynamic session key, integrity, and anonymity. We justify the feasibility of the proposed scheme with a test-bed using 802.15. 4 based device (i.e., SM). Moreover, through the security and performance analysis, we show that the proposed scheme is more effective and energy efficient compared to the previous schemes.
Critical Success Factor for Implementing Vocational Blended Learning

Blended learning provides many benefits to the flexibility of time, place and situation constraints. The research’s objectives was describing the factors that determine the successful implementation of blended learning in vocational higher education. The research used a qualitative approach, data collected through observations and interviews by questionnare based on the CSFs indicators refers to TAM and Kliger. Data analysis was inductive method. The result provided an illustration that the success of vocational blended learning implementation was largely determined by the selection of instructional models that are inline with learning achievement target. The effectiveness of blended learning required the existence of policy support, readiness of IT infrastructure. Changing lecturer’s culture by utilizing ICT can also encourage the accelerated process of successful implementation. It can concluded that determinant factor of successful implementation of blended learning in vocational education is determined by teacher’s ability in mastering the pedagogical knowledge of designing instructional models.
Three Social-Mediated Publics in Digital Activism: A Network Perspective of Social Media Public Segmentation

This study provides a network perspective to segment social-mediated publics in digital activism based on social media users’ influence on the information dissemination process. We used social network analysis to segment publics based on their information sharing behaviors in the case of the Chinese #MeToo movement in 2018 on Sina Weibo. Besides, we conducted a content analysis to reveal the characteristics of each type of publics. We have identified three meaningful social-mediated publics in the Chinese #MeToo movement on Sina Weibo: (1) the provoking public, who plays an essential role in initiating the discussion; (2) the bridging public, which contributes to spreading the discussion to various groups of people; and (3) the powerful public, who has the advantages of the first two segments of publics and is the most powerful one in the formation and development of the online discussion. Three publics have different characteristics. The provoking public (e.g., media and internet celebrities) typically has many followers and is interested in various social issues. The bridging public has fewer followers (e.g., grassroots individuals) but tends to have a special interest in the issue and actively uses social media. The powerful public has a large number of followers, a particular interest in this issue, and is active on social media. This public segmentation provides a relatively new perspective to understand publics in digital activism in societies with strict social norms and media censorship. Limitations and future research are discussed.
Protective Effects of Bacillus Subtilis Fermentation Extract Against Ochratoxin A-induced Nephrotoxicity and Immunotoxicity in Broiler Chickens

Abstract Introduction Ochratoxin A (OTA) is a mycotoxin notably produced by Aspergillus and Penicillium spp. Bacillus subtilis fermentation extract (BSFE) contains specific enzymes which hydrolyse OTA. This study evaluated the efficiency of BSFE in ameliorating the immunotoxic and nephrotoxic effects of OTA in broiler chickens. Material and Methods Day-old broiler chicks were divided equally into four groups of ten: control, OTA (0.5 mg/kg feed), BSFE product (1 mL/L water) and OTA + BSFE at the same concentrations. The chicks were vaccinated against avian influenza, Newcastle disease, and infectious bronchitis, and lymphoproliferation was induced in all birds by phytohaemagglutinin-P (PHA-P). Serum samples were taken before sacrifice and organ tissue samples were taken after, in which renal function biomarkers were assayed and the presence of OTA residue was evaluated by high-performance thin-layer chromatography. Protein markers of apoptosis were determined by qPCR, and tissue lesions were examined histopathologically. Results Exposure to OTA significantly decreased the antibody response to the vaccines and the lymphoproliferative response to PHA-P, and significantly elevated the renal function indicators: serum urea, uric acid and creatinine. It also induced oxidative stress (reduced catalase activity and glutathione concentration), lipid peroxidation (increased malondialdehyde content), apoptosis (increased Bax and Caspase-3 and decreased Bcl-2 gene levels) and pathological lesions in kidney, bursa of Fabricius, spleen and thymus tissue. Residues of OTA were detected in the serum and tissue. BSFE mitigated most of these toxic effects. Conclusion BSFE counters OTA-induced immunotoxicity and nephrotoxicity because of its content of carboxypeptidase and protease enzymes.
TE invasion fuels molecular adaptation in laboratory populations of Drosophila melanogaster

Transposable elements are mobile genetic parasites that frequently invade new host genomes through horizontal transfer. Invading TEs often exhibit a burst of transposition, followed by reduced transposition rates as repression evolves in the host. We recreated the horizontal transfer of P-element DNA transposons into a D. melanogaster host, and followed the expansion of TE copies and evolution of host repression in replicate laboratory populations reared at different temperatures. We observed that while populations maintained at high temperatures rapidly go extinct after TE invasion, those maintained at lower temperatures persist, allowing for TE spread and the evolution of host repression. We also surprisingly discovered that invaded populations experienced recurrent insertion of P-elements into a specific long non-coding RNA, lncRNA:CR43651, and that these insertion alleles are segregating at unusually high frequency in experimental populations, indicative of positive selection. We propose that, in addition to driving the evolution of repression, transpositional bursts of invading TEs can drive molecular adaptation.
Zooanthroponotic transmission of SARS-CoV-2 and host-specific viral mutations revealed by genome-wide phylogenetic analysis

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a generalist virus, infecting and evolving in numerous mammals, including captive and companion animals, free-ranging wildlife, and humans. Transmission among non-human species poses a risk for the establishment of SARS-CoV-2 reservoirs, makes eradication difficult, and provides the virus with opportunities for new evolutionary trajectories, including the selection of adaptive mutations and the emergence of new variant lineages. Here, we use publicly available viral genome sequences and phylogenetic analysis to systematically investigate the transmission of SARS-CoV-2 between human and non-human species and to identify mutations associated with each species. We found the highest frequency of animal-to-human transmission from mink, compared with lower transmission from other sampled species (cat, dog, and deer). Although inferred transmission events could be limited by sampling biases, our results provide a useful baseline for further studies. Using genome-wide association studies, no single nucleotide variants (SNVs) were significantly associated with cats and dogs, potentially due to small sample sizes. However, we identified three SNVs statistically associated with mink and 26 with deer. Of these SNVs, ~⅔ were plausibly introduced into these animal species from local human populations, while the remaining ~⅓ were more likely derived in animal populations and are thus top candidates for experimental studies of species-specific adaptation. Together, our results highlight the importance of studying animal-associated SARS-CoV-2 mutations to assess their potential impact on human and animal health.
Superinfection exclusion creates spatially distinct influenza virus populations

Influenza viruses can interact during coinfections, allowing viral fitness to be altered by genome complementation and competition, and increasing population diversity through reassortment. However, opportunities for these interactions are limited, as coinfection is blocked shortly after primary infection by a process known as superinfection exclusion (SIE). We asked whether SIE, which occurs at the level of individual cells, could limit within-host interactions between populations of influenza viruses as they spread across regions of cells. We first created a simplified model of within-host spread by infecting monolayers of cells with two isogenic influenza A viruses, each encoding a different fluorophore, and measuring the proportion of coinfected cells. In this system SIE begins within 2-4 hours of primary infection, with the kinetics of onset defined by the dose of primary virus. We then asked how SIE controls opportunities for coinfection as viruses spread across a monolayer of cells. We observed that viruses spreading from a single coinfected focus continued to coinfect cells as they spread, as all new infections were of cells that had not yet established SIE. In contrast, viruses spreading towards each other from separately infected foci could only establish minimal regions of coinfection before SIE blocked further coinfection. This patterning was recapitulated in the lungs of infected mice and is likely to apply to other viruses that exhibit SIE. It suggests that the kinetics of SIE onset separate a spreading infection into discrete regions, within which interactions between virus populations can occur freely, and between which they are blocked. Importance Viral fitness and diversity are altered by genome interactions, which occur when multiple viruses coinfect a cell. This has been extensively studied for influenza A viruses (IAV), which use genome reassortment to adapt to new hosts and create pandemic strains, and whose replication can be compromised by the acquisition of defective-interfering RNAs. Coinfection of an individual cell by IAV is restricted by the gradual onset of superinfection exclusion (SIE). Replication of IAVs within host organisms involve the asynchronous replication of viruses as they spread to infect multiple cells. We found that under these circumstances, SIE creates spatially separated sub-populations of IAV, between which there are limited opportunities for genome interactions. Our work suggests SIE will cause many viruses to segregate into distinct subpopulations within their hosts, constraining the effects of genome interactions on their fitness and evolution.
Extracellular Vesicle Formation in Cryptococcus deuterogattii Impacts Fungal Virulence and Requires the NOP16 Gene

Small molecules are components of fungal extracellular vesicles (EVs), but their biological roles are only superficially known. NOP16 is a eukaryotic gene that is required for the activity of benzimidazoles against Cryptococcus deuterogattii. In this study, during the phenotypic characterization of C. deuterogattii mutants lacking NOP16 expression, we observed that this gene was required for EV production. ABSTRACT Small molecules are components of fungal extracellular vesicles (EVs), but their biological roles are only superficially known. NOP16 is a eukaryotic gene that is required for the activity of benzimidazoles against Cryptococcus deuterogattii. In this study, during the phenotypic characterization of C. deuterogattii mutants lacking NOP16 expression, we observed that this gene was required for EV production. Analysis of the small molecule composition of EVs produced by wild-type cells and two independent nop16Δ mutants revealed that the deletion of NOP16 resulted not only in a reduced number of EVs but also an altered small molecule composition. In a Galleria mellonella model of infection, the nop16Δ mutants were hypovirulent. The hypovirulent phenotype was reverted when EVs produced by wild-type cells, but not mutant EVs, were coinjected with the nop16Δ cells in G. mellonella. These results reveal a role for NOP16 in EV biogenesis and cargo, and also indicate that the composition of EVs is determinant for cryptococcal virulence.
Relating neighborhood deprivation to childhood obesity in the ABCD Study®: evidence for theories of neuroinflammation and neuronal stress

Objective We evaluated whether the relationships between area deprivation (ADI), body mass index (BMI) and brain structure (e.g., cortical thickness, subcortical volume) during pre-adolescence supported the neuroinflammation (NI) and/or neuronal stress (NS) theories of overeating. The NI theory proposes that ADI causes structural alteration in the brain due to the neuroinflammatory effects of overeating unhealthy foods. The NS theory proposes that ADI-related stress negatively impacts brain structure, which causes stress-related overeating and subsequent obesity. Methods Data were gathered from the Adolescent Brain Cognitive DevelopmentSM Study® (9-12-years-old; n=2872, 51.3% female). Linear mixed-effects models identified brain regions that were associated with both ADI and BMI; longitudinal mediation models assessed potential causal pathways. The NI model included ADI and BMI at 9/10-years-old and brain data at 11/12-years-old. The NS model included ADI and brain data at 9/10-years-old and BMI at 11/12-years-old. Results In the NI model, BMI at 9/10-years-old positively mediated the relationship between AD and cortical thinning in the cuneus, lingual, and paracentral gyrus and larger volume of the Ventral DC at 11/12-years-old. In the NS model, cortical thinning in the lateral orbitofrontal cortex, lingual gyrus and larger volume of the Ventral DC at 9/10-years-old partially mediated the relationship between ADI and BMI at 11/12-years-old. Conclusion Greater area deprivation may indicate fewer access to resources that support healthy development, like nutritious food and non-stressful environments. Our findings provide evidence in support of the neuroinflammation and stress theories of overeating, specifically, with greater ADI influencing health outcomes of obesity via brain structure alterations.
Fmrp regulates neuronal balance in embryonic motor circuit formation

Motor behavior requires the balanced production and integration of a variety of neural cell types. Motor neurons are positioned in discrete locations in the ventral spinal cord, targeting specific muscles to drive locomotive contractions. Specialized spinal interneurons modulate and synchronize motor neuron activity to achieve coordinated motor output. Changes in the ratios of spinal interneurons could drastically alter motor output by tipping the balance of inhibition and excitation onto target motor neurons. Importantly, individuals with Fragile X syndrome (FXS) and associated autism spectrum disorders often have significant motor challenges, including repetitive behaviors and epilepsy. FXS stems from the transcriptional silencing of the gene Fragile X Messenger Ribonucleoprotein 1 (FMR1), which encodes an RNA binding protein that is implicated in a multitude of crucial neurodevelopmental processes, including cell specification. We find that zebrafish fmr1 mutants generate surplus ventral lateral descending (VeLD) interneurons, an early-born cell derived from the pMN domain. These GABAergic interneurons are also associated with changes in synaptogenesis, as fmr1 mutants show increased early expression of the scaffold Gephyrin, but these postsynaptic sites fail to mature. Our work shows that Fmrp regulates the proportionate production of neurons that comprise early embryonic motor circuits. As VeLD interneurons are hypothesized to act as central pattern generators driving the earliest spontaneous movements, this imbalance could profoundly influence the formation and long-term function of motor circuits driving locomotion.