Miracle-dz/UniFAR-FTUs huggingface dataset:
The human sperm head spins with a conserved direction during swimming in 3D

In human sperm, head spinning is essential for sperm swimming and critical for fertilization. Measurement of head spinning has not been straightforward due to its symmetric head morphology, its translucent nature and fast 3D motion driven by its helical flagellum movement. Microscope image acquisition has been mostly restricted to 2D single focal plane images limited to head position tracing, in absence of head orientation and rotation in 3D. To date, human sperm spinning has been reported to be mono or bidirectional, and even intermittently changing direction. This variety in head spinning direction, however, appears to contradict observations of conserved helical beating of the human sperm flagellum. Here, we reconcile these observations by directly measuring the head spinning movement of freely swimming human sperm with multi-plane 4D microscopy. We show that 2D microscopy is unable to distinguish the spinning direction in human sperm. We evaluated the head spinning of 409 spermatozoa in four different conditions: in non-capacitating and capacitating solutions, for both aqueous and viscous media. All spinning spermatozoa, regardless of the experimental conditions spun counterclockwise (CCW) as seen from head-to-tail. Head spinning was suppressed in 57% of spermatozoa swimming in non-capacitating viscous media, though, interestingly, they recovered the CCW spinning after incubation in capacitating conditions within the same viscous medium. Our observations show that the spinning direction in human sperm is conserved, even when recovered from non-spin, indicating the presence of a robust and persistent helical driving mechanism powering the human sperm flagellum, thus of critical importance in future sperm motility assessments, human reproduction research and microorganism self-organised swimming.
Photoacoustic trace gas detection of ethane using a continuously tunable, continuous-wave optical parametric oscillator based on periodically poled lithium niobate

A 1.2 W, continuous-wave, continuously-tunable, singly-resonant optical parametric oscillator (OPO) (idler tuning range 3.0–3.8 μm), pumped by a 10 W continuous-wave Nd:YAG laser, is used in combination with a photoacoustic cell for the detection of ethane. An intracavity solid-state etalon (thickness 400 μm) was used to stabilize the OPO cavity and could be used to mode-hop tune the idler wavelength over 10 cm−1. The usefulness of the system was demonstrated by determining a detection limit for ethane down to 10 parts per trillion. The selectivity was achieved by making a 24 GHz wide pump laser scan over the ethane absorption line at 2996.9 cm−1, after which a Lorentzian fit determined the total area of the absorption signal. Both area value and peak value proved to be linearly depending on the ethane concentration.
Oblique wave groups in deep water

Oblique wave groups consist of waves whose straight parallel lines of constant phase are oblique to the straight parallel lines of constant group phase. Numerical solutions for periodic oblique wave groups with envelopes of permanent shape are calculated from the equations for irrotational three-dimensional deep-water motion with nonlinear upper free-surface conditions. Two distinct families of periodic wave groups are found, one in which the waves in each group are in phase with those in all other groups, and the other in which there is a phase difference of π between the waves in consecutive groups. It is shown that some analytical solutions for oblique wave groups calculated from the nonlinear Schrödinger equation are in error because they ignore the resonant forcing of certain harmonics in two dimensions. Particular attention is given to oblique wave groups whose group-to-wave angle is in the neighbourhood of the critical angle tan−1√½, corresponding to waves on the boundary wedge of the Kelvin ship-wave pattern.
PopStage

StageMix is a mixed video that is created by concatenating the segments from various performance videos of an identical song in a visually smooth manner by matching the main subject's silhouette presented in the frame. We introduce PopStage, which allows users to generate a StageMix automatically. PopStage is designed based on the StageMix Editing Guideline that we established by interviewing creators as well as observing their workflows. PopStage consists of two main steps: finding an editing path and generating a transition effect at a transition point. Using a reward function that favors visual connection and the optimality of transition timing across the videos, we obtain the optimal path that maximizes the sum of rewards through dynamic programming. Given the optimal path, PopStage then aligns the silhouettes of the main subject from the transitioning video pair to enhance the visual connection at the transition point. The virtual camera view is next optimized to remove the black areas that are often created due to the transformation needed for silhouette alignment, while reducing pixel loss. In this process, we enforce the view to be the maximum size while maintaining the temporal continuity across the frames. Experimental results show that PopStage can generate a StageMix of a similar quality to those produced by professional creators in a highly reduced production time.
3QNet

Since the development of 3D applications, the point cloud, as a spatial description easily acquired by sensors, has been widely used in multiple areas such as SLAM and 3D reconstruction. Point Cloud Compression (PCC) has also attracted more attention as a primary step before point cloud transferring and saving, where the geometry compression is an important component of PCC to compress the points geometrical structures. However, existing non-learning-based geometry compression methods are often limited by manually pre-defined compression rules. Though learning-based compression methods can significantly improve the algorithm performances by learning compression rules from data, they still have some defects. Voxel-based compression networks introduce precision errors due to the voxelized operations, while point-based methods may have relatively weak robustness and are mainly designed for sparse point clouds. In this work, we propose a novel learning-based point cloud compression framework named 3D Point Cloud Geometry Quantiation Compression Network (3QNet), which overcomes the robustness limitation of existing point-based methods and can handle dense points. By learning a codebook including common structural features from simple and sparse shapes, 3QNet can efficiently deal with multiple kinds of point clouds. According to experiments on object models, indoor scenes, and outdoor scans, 3QNet can achieve better compression performances than many representative methods.
LaplacianFusion

We propose LaplacianFusion, a novel approach that reconstructs detailed and controllable 3D clothed-human body shapes from an input depth or 3D point cloud sequence. The key idea of our approach is to use Laplacian coordinates, well-known differential coordinates that have been used for mesh editing, for representing the local structures contained in the input scans, instead of implicit 3D functions or vertex displacements used previously. Our approach reconstructs a controllable base mesh using SMPL, and learns a surface function that predicts Laplacian coordinates representing surface details on the base mesh. For a given pose, we first build and subdivide a base mesh, which is a deformed SMPL template, and then estimate Laplacian coordinates for the mesh vertices using the surface function. The final reconstruction for the pose is obtained by integrating the estimated Laplacian coordinates as a whole. Experimental results show that our approach based on Laplacian coordinates successfully reconstructs more visually pleasing shape details than previous methods. The approach also enables various surface detail manipulations, such as detail transfer and enhancement.
Knowledge Guided Two-player Reinforcement Learning for Cyber Attacks and Defenses

Cyber defense exercises are an important avenue to understand the technical capacity of organizations when faced with cyber-threats. Information derived from these exercises often leads to finding unseen methods to exploit vulnerabilities in an organization. These often lead to better defense mechanisms that can counter previously unknown exploits. With recent developments in cyber battle simulation platforms, we can generate a defense exercise environment and train reinforcement learning (RL) based autonomous agents to attack the system described by the simulated environment. In this paper, we describe a two-player game-based RL environment that simultaneously improves the performance of both the attacker and defender agents. We further accelerate the convergence of the RL agents by guiding them with expert knowledge from Cybersecurity Knowledge Graphs on attack and mitigation steps. We have implemented and integrated our proposed approaches into the CyberBattleSim system.
Rad5 participates in lesion bypass through its Rev1-binding and ubiquitin ligase domains, but not through its helicase function

DNA Damage Tolerance (DDT) functions to bypass replication-blocking lesions and is divided into two distinct pathways: error-prone Translesion Synthesis (TLS) and error-free Damage Avoidance (DA). Rad5 is a multifunctional protein that is involved in these DDT processes. Saccharomyces cerevisiae Rad5 contains three well defined domains: a RING domain that promotes PCNA polyubiquitination, a ssDNA-dependent ATPase/helicase domain, and a Rev1-binding domain. Both the RING domain and the ATPase/helicase domain are conserved in human Rad5 ortholog HLTF. In this study we used domain-specific mutants to address the contribution of each of the Rad5 domains to the lesion tolerance. We demonstrate that the two critical functions of Rad5 during DNA damage tolerance are the activation of template switching through polyubiquitination of PCNA and the recruitment of TLS polymerases, and that loss of one of those functions can be compensated by increased usage of the other. We also show that, unlike previously suggested, the helicase activity does not play any role in lesion tolerance.
Detecting potential mechanism of vitamin D in treating rheumatoid arthritis based on network pharmacology and molecular docking

Aim: Vitamin D plays a vital role in Rheumatoid arthritis (RA). However, the mechanism of vitamin D and rheumatism is still unclear. Therefore, a strategy based on network pharmacology and molecular docking was used to explore the mechanism of vitamin D and RA. Methods: The targets of RA were obtained from the GeneCards database and Therapeutic Targets Database, and the targets of vitamin D were obtained from the Drugbank database and STITCH database. Next, overlapping genes were identified by Venny, and further Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and molecular docking analyses were performed. Results: A total of 1,139 targets of RA and 201 targets of vitamin D were obtained. A total of 76 overlapping genes were identified by Venny. The enrichment analysis showed that cell proliferation, immune response, and apoptotic process were the critical biological processes of vitamin D in treating RA. Antifolate resistance, osteoclast differentiation, and the nuclear factor-kappa B (NF-κB) signalling pathway are fundamental mechanisms of vitamin D in treating RA. According to further molecular docking, ALB, TNF, CASP3, and TP53 may be important punctuation points or diagnostic markers for future RA treatment. Conclusion: By analysing overlapping genes of diseases and drugs, this study confirmed that ALB, TNF, CASP3, and TP53 may be essential markers or diagnostic markers for future RA treatment.
Temporal patterns in coral reef fish assemblages with varying disturbance levels: A tale of two National Parks in Hawai´i

Long-term ecological monitoring of coral reefs can reveal the state of the reef communities and responses of different reef components to various pulse and press disturbance events. Here, we describe long-term monitoring of reef fish assemblages from two U.S. National Parks in Hawai‘i, Kaloko-Honokōhau National Historical Park (KAHO) and Kalaupapa National Historical Park (KALA) over the past decade. These two parks experience different anthropogenic disturbances as KAHO is highly accessible with multiple types of adjacent land use while KALA is relatively inaccessible, surrounded by large expanses of native forest, and known for having the highest documented fish biomass within the main Hawaiian Islands. The fish assemblages in KAHO were numerically dominated by small-bodied damselfish Chromis spp. and herbivorous surgeonfishes Acanthurus nigrofuscus, Ctenochaetus strigosus and Zebrasoma flavescens, while those in KALA were numerically dominated by Chromis vanderbilti, A. nigrofuscus, Thalassoma duperrey and Paracirrhites arcatus. Multivariate control charts detected anomalies in the fish assemblages in some years. In KAHO, gradual shifts in the assemblages were detected in recent years due to changes (both increases and decreases) in relative abundances of numerically dominant species including Chromis agilis, C. vanderbilti, A. nigrofuscus, C. strigosus and Z. flavescens. There was a documented reduction in live coral cover in KAHO due to a bleaching event in 2015, and potential delayed effects of the coral mortality on the fish assemblages were found particularly in the North and South regions of the park. In KALA, increases in the abundances of Acanthurus (A. blochii, A. leucopareius, A. nigrofuscus, A. thompsoni and A. triostegus) and C. strigosus were found in 2014, likely due to a large recruitment event that had not been well reported. As localized thermal stress events were detected in both KAHO and KALA in 2019, continuous monitoring of these two parks is critical to assess how the coral-reef ecosystems under two different human-use scenarios respond to repeated heating events and whether there are immediate as well as delayed effects on reef organisms resulting from losses of live coral tissue and a subsequent decrease in structural complexity provided by the coral.
Red blood cell proteomics reveal remnant protein biosynthesis and folding pathways in PIEZO1-related hereditary xerocytosis

Hereditary xerocytosis is a dominant red cell membrane disorder characterized by an increased leak of potassium from the inside to outside the red blood cell membrane, associated with loss of water leading to red cell dehydration and chronic hemolysis. 90% of cases are related to heterozygous gain of function mutations in PIEZO1, encoding a mechanotransductor that translates a mechanical stimulus into a biological signaling. Data are still required to understand better PIEZO1-HX pathophysiology. Recent studies identified proteomics as an accurate and high-input tool to study erythroid progenitors and circulating red cell physiology. Here, we isolated red blood cells from 5 controls and 5 HX patients carrying an identified and pathogenic PIEZO1 mutation and performed a comparative deep proteomic analysis. A total of 603 proteins were identified among which 56 were differentially expressed (40 over expressed and 16 under expressed) between controls and HX with a homogenous expression profile within each group. We observed relevant modifications in the protein expression profile related to PIEZO1 mutations, identifying two main “knots”. The first contained both proteins of the chaperonin containing TCP1 complex involved in the assembly of unfolded proteins, and proteins involved in translation. The second contained proteins involved in ubiquitination. Deregulation of proteins involved in protein biosynthesis was also observed in in vitro-produced reticulocytes after Yoda1 exposure. Thus, our work identifies significant changes in the protein content of PIEZO1-HX erythrocytes, revealing a “PIEZO1 signature” and identifying potentially targetable pathways in this disease characterized by a heterogeneous clinical expression and contra-indication of splenectomy.
Flattening the COVID-19 curve: Emotions mediate the effects of a persuasive message on preventive action

Introduction Across four countries (Canada, USA, UK, and Italy), we explored the effects of persuasive messages on intended and actual preventive actions related to COVID-19, and the role of emotions as a potential mechanism for explaining these effects. Methods One thousand seventy-eight participants first reported their level of concern and emotions about COVID-19 and then received a positive persuasive text, negative persuasive text, or no text. After reading, participants reported their emotions about the pandemic and their willingness to take preventive action. One week following, the same participants reported the frequency with which they engaged in preventive action and behaviors that increased the risk of contracting COVID-19. Results Results revealed that the positive persuasive text significantly increased individuals’ willingness to and actual engagement in preventive action and reduced risky behaviors 1 week following the intervention compared to the control condition. Moreover, significant differences were found between the positive persuasive text condition and negative persuasive text condition whereby individuals who read the positive text were more willing and actually engaged in more preventive action compared to those who read the negative text. No differences were found, however, at the 1-week follow-up for social distancing and isolation behaviors. Results also revealed that specific discrete emotions mediated relations between the effects of the texts and preventive action (both willing and actual). Discussion This research highlights the power of educational interventions to prompt behavioral change and has implications for pandemic-related interventions, government policy on health promotion messages, and future research.
Immune landscape-based machine-learning–assisted subclassification, prognosis, and immunotherapy prediction for glioblastoma

Introduction As a malignant brain tumor, glioblastoma (GBM) is characterized by intratumor heterogeneity, a worse prognosis, and highly invasive, lethal, and refractory natures. Immunotherapy has been becoming a promising strategy to treat diverse cancers. It has been known that there are highly heterogeneous immunosuppressive microenvironments among different GBM molecular subtypes that mainly include classical (CL), mesenchymal (MES), and proneural (PN), respectively. Therefore, an in-depth understanding of immune landscapes among them is essential for identifying novel immune markers of GBM. Methods and results In the present study, based on collecting the largest number of 109 immune signatures, we aim to achieve a precise diagnosis, prognosis, and immunotherapy prediction for GBM by performing a comprehensive immunogenomic analysis. Firstly, machine-learning (ML) methods were proposed to evaluate the diagnostic values of these immune signatures, and the optimal classifier was constructed for accurate recognition of three GBM subtypes with robust and promising performance. The prognostic values of these signatures were then confirmed, and a risk score was established to divide all GBM patients into high-, medium-, and low-risk groups with a high predictive accuracy for overall survival (OS). Therefore, complete differential analysis across GBM subtypes was performed in terms of the immune characteristics along with clinicopathological and molecular features, which indicates that MES shows much higher immune heterogeneity compared to CL and PN but has significantly better immunotherapy responses, although MES patients may have an immunosuppressive microenvironment and be more proinflammatory and invasive. Finally, the MES subtype is proved to be more sensitive to 17-AAG, docetaxel, and erlotinib using drug sensitivity analysis and three compounds of AS-703026, PD-0325901, and MEK1-2-inhibitor might be potential therapeutic agents. Conclusion Overall, the findings of this research could help enhance our understanding of the tumor immune microenvironment and provide new insights for improving the prognosis and immunotherapy of GBM patients.
PDLIM2 is highly expressed in Breast Cancer tumour-associated macrophages and is required for M2 macrophage polarization

The PDZ-LIM domain-containing protein 2 (PDLIM2) regulates cell polarity and the protein stability of key transcription factors in epithelial and hemopoietic cells. We previously reported that PDLIM2 is more highly expressed in Triple Negative Breast Cancer (TNBC) than in other breast cancer types or normal breast tissue. In the course of the TNBC study, it was noted that PDLIM2 was highly expressed in the stroma of PDLIM2-expressing tumours. Here, we investigated the phenotype of these stromal cells and whether any infiltrating immune population was linked to PDLIM2 expression. We found that high PDLIM2 expression in breast tumours was associated with higher levels of infiltrating M2 macrophages, but was not associated with infiltrating T cell sub-populations. We then tested whether PDLIM2 contributes to macrophage differentiation or function by using cultures of bone marrow-derived macrophages from wildtype and Pdlim2 knockout mice. This demonstrated that PDLIM2 is required for naïve macrophage migration and for the full adoption of IL-4-induced M2 polarization, including expression of M2 phenotypic markers, cell adhesion and cell migration. TLR4-, TLR3- or IFNγ-induced M1 macrophage activity was less dependent on PDLIM2. Finally, analysis of publicly available breast cancer datasets showed that high PDLIM2 expression is associated with increased M2 macrophage infiltration. We conclude that PDLIM2 expression influences the tumour associated stroma and, in particular, M2 macrophage infiltration that may contribute to the progression of TNBC or other subsets of breast cancer.
How prominent science communicators on YouTube understand the impact of their work

YouTube is rapidly becoming one of the major places that people around the world engage with science, in turn making prominent science communicators on YouTube some of the most impactful and known faces in science communication. However, while much is known about the viewership habits of YouTube audiences, little is known about the motivations, thinking and ideas of impact of the science communicators working on YouTube. The current study qualitatively explored these questions one-on-one interviews with prominent science communicators working on YouTube (n = 20). We explore their responses in six key areas: their understanding of and relationship with their audience; their attitude toward impact metrics; their attitude toward comments; their understanding of impact; their reasons for creating content; and what it is like working under the algorithm. Key findings include a wide variety of opinions about the metrics provided by YouTube; a near unanimous assertion of the value of comments; a somewhat deficit model approach to their communication work; and a polarized attitude to working under the algorithm.