Auxin plays a role in the adaptation of rice to anaerobic germination and seedling establishment.

Auxin is well known to stimulate coleoptile elongation and rapid seedling growth in the air. However, its role in regulating rice germination and seedling establishment under submergence is largely unknown. Previous studies revealed that excessive levels of indole-3-acetic acid(IAA) frequently cause the inhibition of plant growth and development. In this study, the high-level accumulation of endogenous IAA is observed under dark submergence, stimulating rice coleoptile elongation but limiting the root and primary leaf growth during anaerobic germination (AG). We found that oxygen and light can reduce IAA levels, promote the seedling establishment and enhance rice AG tolerance. miRNA microarray profiling and RNA gel blot analysis results show that the expression of miR167 is negatively regulated by submergence; it subsequently modulates the accumulation of free IAA through the miR167-ARF-GH3 pathway. The OsGH3-8 encodes an IAA-amido synthetase that functions to prevent free IAA accumulation. Reduced miR167 levels or overexpressing OsGH3-8 increase auxin metabolism, reduce endogenous levels of free IAA and enhance rice AG tolerance. Our studies reveal that poor seed germination and seedling growth inhibition resulting from excessive IAA accumulation would cause intolerance to submergence in rice, suggesting that a certain threshold level of auxin is essential for rice AG tolerance.

Scalable surveillance of e-cigarette products on Instagram and TikTok using computer vision.

INTRODUCTION: Instagram and TikTok, video-based social media platforms popular among adolescents, contain tobacco-related content despite the platforms' policies prohibiting substance-related posts. Prior research identified themes in e-cigarette-related social media posts using qualitative or text-based machine learning methods. We developed an image-based computer vision model to identify e-cigarette products in social media images and videos. METHODS: We created a dataset of 6,999 Instagram images labeled for 8 object classes: mod or pod devices, e-juice containers, packaging boxes, nicotine warning labels, e-juice flavors, e-cigarette brand names, and smoke clouds. We trained a DyHead object detection model using a Swin-Large backbone, evaluated the model's performance on 20 Instagram and TikTok videos, and applied the model to 14,072 e-cigarette-related promotional TikTok videos (2019-2022; 10,276,485 frames). RESULTS: The model achieved the following mean average precision scores on the image test set: e-juice container: 0.89; pod device: 0.67; mod device: 0.54; packaging box: 0.84; nicotine warning label: 0.86; e-cigarette brand name: 0.71; e-juice flavor name: 0.89; and smoke cloud: 0.46. The largest number of TikTok videos - 9,091 (65%) - contained smoke clouds, followed by mod and pod devices detected in 6,667 (47%) and 5,949 (42%) videos respectively. Prevalence of nicotine warning labels was the lowest, detected in 980 videos (7%). CONCLUSIONS: Deep learning-based object detection technology enables automated analysis of visual posts on social media. Our computer vision model can detect the presence of e-cigarettes products in images and videos, providing valuable surveillance data for tobacco regulatory science. IMPLICATIONS: Prior research identified themes in e-cigarette-related social media posts using qualitative or text-based machine learning methods. We developed an image-based computer vision model to identify e-cigarette products in social media images and videos.We trained a DyHead object detection model using a Swin-Large backbone, evaluated the model's performance on 20 Instagram and TikTok videos featuring at least two e-cigarette objects, and applied the model to 14,072 e-cigarette-related promotional TikTok videos (2019-2022; 10,276,485 frames).The deep learning model can be used for automated, scalable surveillance of image- and video-based e-cigarette-related promotional content on social media, providing valuable data for tobacco regulatory science. Social media platforms could use computer vision to identify tobacco-related imagery and remove it promptly, which could reduce adolescents' exposure to tobacco content online.

Identification of sugar response complex in the metallothionein OsMT2b gene promoter for enhancement of foreign protein production in transgenic rice.

KEY MESSAGE: A 146-bp sugar response complex MTSRC is identified in the promoter of rice metallothionein OsMT2b gene conferring high-level expression of luciferase reporter gene and bioactive recombinant haFGF in transgenic rice. A rice subfamily type 2 plant metallothionein (pMT) gene, OsMT2b, encoding a reactive oxygen species (ROS) scavenger protein, has been previously shown to exhibit the most abundant gene expression in young rice seedling. Expression of OsMT2b was found to be regulated negatively by ethylene and hydrogen peroxide in rice stem node under flooding stress, but little is known about its response to sugar depletion. In this study, transient expression assay and transgenic approach were employed to characterize the regulation of the OsMT2b gene expression in rice. We found that the expression of OsMT2b gene is induced by sugar starvation in both rice suspension cells and germinated embryos. Deletion analysis and functional assay of the OsMT2b promoter revealed that the 5'-flanking region of the OsMT2b between nucleotides - 351 and - 121, which contains the sugar response complex (- 266 to - 121, designated MTSRC) is responsible for high-level promoter activity under sugar starvation. It was also found that MTSRC significantly enhances the Act1 promoter activity in transgenic rice cells and seedlings. The modified Act1 promoter, Act1-MTSRC, was used to produce the recombinant human acidic fibroblast growth factor (haFGF) in rice cells. Our result shows that the bioactive recombinant haFGF is stably produced in transformed rice cell culture and yields are up to 2% of total medium proteins. Our studies reveal that MTSRC serves as a strong transcriptional activator and the Act1-MTSRC promoter can be applicable in establishing an efficient expression system for the high-level production of foreign proteins in transgenic rice cells and seedlings.

An efficient grafting method for phytoplasma transmission in Catharanthus roseus.

BACKGROUND: Phytoplasmas are parasitic plant pathogens that reside intracellularly within the sieve tube cells. Phytoplasmas induce various symptoms, including floral virescence, phyllody, leaf yellowing, and witches'-broom. Currently, it is challenging to culture phytoplasma in vitro. In the laboratory, phytoplasmas are generally maintained in alternative host plants, such as Catharanthus roseus. Grafting is used to transmit phytoplasmas among the alternative hosts. During the experiment, scions from infected plants are grafted onto healthy plants using a side grafting method. However, the practice has certain limitations, including its inability to be applied to small plants and its irregular disease incidence. RESULTS: Here, we demonstrate a new approach, penetration grafting, to overcome the limitations of side grafting. This grafting method allows phytoplasma to be efficiently and uniformly transmitted into the inoculated plants. No significant difference was observed in phytoplasma accumulation between both grafting techniques. However, penetration grafting allows rapid symptom development, saving waiting time and reducing space usage. CONCLUSIONS: This study provides a reliable and stable method for experiments that require grafting transmission.

The 2024 Taiwanese Presidential Election on social media: Identity, policy, and affective virality.

The 2024 Taiwanese Presidential Election is not just a critical geopolitical event, it also engages with themes of alternative candidacy, foreign policy, and affective polarization. At one point, a four-candidate race had emerged in a traditionally bipartisan election, with alternative candidates disrupting the dichotomy of Chinese vs. Taiwanese identity. Leveraging 911,510 posts and 101,600,047 engagements on social media, we analyze user discourse and engagement. First, we find traditional candidates derive more engagement on foreign policy and geopolitical issues, alternative candidates on domestic issues. Additionally, virality is generated by affective reasons, although in-group references generate more engagement than out-group references. Lastly, a puzzle is revealed where alternative candidates draw more homogeneous attention from national identity groups. Results suggest alternative candidacy can be generated by both positive and negative comparisons rooted in national identity.

Complex systems of secrecy: the offshore networks of oligarchs.

Following the invasion of Ukraine, the USA, UK, and EU governments-among others-sanctioned oligarchs close to Putin. This approach has come under scrutiny, as evidence has emerged of the oligarchs' successful evasion of these punishments. To address this problem, we analyze the role of an overlooked but highly influential group: the secretive professional intermediaries who create and administer the oligarchs' offshore financial empires. Drawing on the Offshore Leaks Database provided by the International Consortium of Investigative Journalists (ICIJ), we examine the ties linking offshore expert advisors (lawyers, accountants, and other wealth management professionals) to ultra-high-net-worth individuals from four countries: Russia, China, the USA, and Hong Kong. We find that resulting nation-level "oligarch networks" share a scale-free structure characterized by a heterogeneity of heavy-tailed degree distributions of wealth managers; however, network topologies diverge across clients from democratic versus autocratic regimes. While generally robust, scale-free networks are fragile when targeted by attacks on highly connected nodes. Our "knock-out" experiments pinpoint this vulnerability to the small group of wealth managers themselves, suggesting that sanctioning these professional intermediaries may be more effective and efficient in disrupting dark finance flows than sanctions on their wealthy clients. This vulnerability is especially pronounced amongst Russian oligarchs, who concentrate their offshore business in a handful of boutique wealth management firms. The distinctive patterns we identify suggest a new approach to sanctions, focused on expert intermediaries to disrupt the finances and alliances of their wealthy clients. More generally, our research contributes to the larger body of work on complexity science and the structures of secrecy.

Comparative analysis of social bots and humans during the COVID-19 pandemic.

Using more than 4 billion tweets and labels on more than 5 million users, this paper compares the behavior of humans and bots politically and semantically during the pandemic. Results reveal liberal bots are more central than humans in general, but less important than institutional humans as the elite circle grows smaller. Conservative bots are surprisingly absent when compared to prior work on political discourse, but are better than liberal bots at eliciting replies from humans, which suggest they may be perceived as human more frequently. In terms of topic and framing, conservative humans and bots disproportionately tweet about the Bill Gates and bio-weapons conspiracy, whereas the 5G conspiracy is bipartisan. Conservative humans selectively ignore mask-wearing and we observe prevalent out-group tweeting when discussing policy. We discuss and contrast how humans appear more centralized in health-related discourse as compared to political events, which suggests the importance of credibility and authenticity for public health in online information diffusion.

#JusticeforGeorgeFloyd: How Instagram facilitated the 2020 Black Lives Matter protests.

We present and analyze a database of 1.13 million public Instagram posts during the Black Lives Matter protests of 2020, which erupted in response to George Floyd's public murder by police on May 25. Our aim is to understand the growing role of visual media, focusing on a) the emergent opinion leaders and b) the subsequent press concerns regarding frames of legitimacy. We perform a comprehensive view of the spatial (where) and temporal (when) dynamics, the visual and textual content (what), and the user communities (who) that drove the social movement on Instagram. Results reveal the emergence of non-institutional opinion leaders such as meme groups, independent journalists, and fashion magazines, which contrasts with the institutionally reinforcing nature of Twitter. Visual analysis of 1.69 million photos show symbols of injustice are the most viral coverage, and moreover, actual protest coverage is framed positively, in contrast with combatant frames traditionally found from legacy media. Together, these factors helped facilitate the online movement through three phases, culminating with online international solidarity in #BlackOutTuesday. Through this case study, we demonstrate the precarious nature of protest journalism, and how content creators, journalists, and everyday users co-evolved with social media to shape one of America's largest-ever human rights movements.

Charting the Information and Misinformation Landscape to Characterize Misinfodemics on Social Media: COVID-19 Infodemiology Study at a Planetary Scale.

BACKGROUND: The novel coronavirus, also known as SARS-CoV-2, has come to define much of our lives since the beginning of 2020. During this time, countries around the world imposed lockdowns and social distancing measures. The physical movements of people ground to a halt, while their online interactions increased as they turned to engaging with each other virtually. As the means of communication shifted online, information consumption also shifted online. Governing authorities and health agencies have intentionally shifted their focus to use social media and online platforms to spread factual and timely information. However, this has also opened the gate for misinformation, contributing to and accelerating the phenomenon of misinfodemics. OBJECTIVE: We carried out an analysis of Twitter discourse on over 1 billion tweets related to COVID-19 over a year to identify and investigate prevalent misinformation narratives and trends. We also aimed to describe the Twitter audience that is more susceptible to health-related misinformation and the network mechanisms driving misinfodemics. METHODS: We leveraged a data set that we collected and made public, which contained over 1 billion tweets related to COVID-19 between January 2020 and April 2021. We created a subset of this larger data set by isolating tweets that included URLs with domains that had been identified by Media Bias/Fact Check as being prone to questionable and misinformation content. By leveraging clustering and topic modeling techniques, we identified major narratives, including health misinformation and conspiracies, which were present within this subset of tweets. RESULTS: Our focus was on a subset of 12,689,165 tweets that we determined were representative of COVID-19 misinformation narratives in our full data set. When analyzing tweets that shared content from domains known to be questionable or that promoted misinformation, we found that a few key misinformation narratives emerged about hydroxychloroquine and alternative medicines, US officials and governing agencies, and COVID-19 prevention measures. We further analyzed the misinformation retweet network and found that users who shared both questionable and conspiracy-related content were clustered more closely in the network than others, supporting the hypothesis that echo chambers can contribute to the spread of health misinfodemics. CONCLUSIONS: We presented a summary and analysis of the major misinformation discourse surrounding COVID-19 and those who promoted and engaged with it. While misinformation is not limited to social media platforms, we hope that our insights, particularly pertaining to health-related emergencies, will help pave the way for computational infodemiology to inform health surveillance and interventions.

Oscillatory behavior of microbubbles impacts efficacy of cellular drug delivery.

Drug-loaded microbubbles have been proven to be an effective strategy for non-invasive and local drug delivery when combined with ultrasound excitation for targeted drug release. Inertial cavitation is speculated to be a major mechanism for releasing drugs from drug-loaded microbubbles, but it results in lethal cellular pore damage that greatly limits its application. Thus, we investigated the cellular vesicle attachment and uptake to evaluate the efficiency of drug delivery by modulating the behaviors of targeted microbubble oscillation. The efficiency of vesicle attachment on the targeted cell membrane was 36.5 ± 15.9% and 3.8 ± 2.3% under stable and inertial cavitation, respectively. Further, stable cavitation enhanced cell permeability (26.8 ± 3.2%), maintained cell viability (90.8 ± 2.1%), and showed 7.9 ± 1.9-fold enhancement of in vivo vesicle release on tumor vessels. Therefore, our results reveal the ability to improve drug delivery via stable cavitation induced by targeted microbubbles. We propose that this strategy might be suitable for tissue repair or neuromodulation.