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The functional role of oscillatory dynamics in neocortical circuits: A computational perspective
The dynamics of neuronal systems are characterized by hallmark features such as oscillations and synchrony. However, it has remained unclear whether these characteristics are epiphenomena or are exploited for computation. Due to the challenge of selectively interfering with oscillatory network dynamics in neuronal systems, we simulated recurrent networks of damped harmonic oscillators in which oscillatory activity is enforced in each node, a choice well supported by experimental findings. When trained on standard pattern recognition tasks, these harmonic oscillator recurrent networks (HORNs) outperformed nonoscillatory architectures with respect to learning speed, noise tolerance, and parameter efficiency. HORNs also reproduced a many characteristic features of neuronal systems, such as the cerebral cortex and the hippocampus. In trained HORNs, stimulus-induced interference patterns holistically represent the result of comparing sensory evidence with priors stored in recurrent connection weights, and learning-induced weight changes are compatible with Hebbian principles. Implementing additional features characteristic of natural networks, such as heterogeneous oscillation frequencies, inhomogeneous conduction delays, and network modularity, further enhanced HORN performance without requiring additional parameters. Taken together, our model allows us to give plausible a posteriori explanations for features of natural networks whose computational role has remained elusive. We conclude that neuronal systems are likely to exploit the unique dynamics of recurrent oscillator networks whose computational superiority critically depends on the oscillatory patterning of their nodal dynamics. Implementing the proposed computational principles in analog hardware is expected to enable the design of highly energy-efficient and self-adapting devices that could ideally complement existing digital technologies.
Improving paraffin precipitate inhibition using glycine and Palm-based Methyl Ester Sulfonate (MES) eco-friendly inhibitors
Oil fields located in cold environments and deep-sea locations often face challenges with paraffin wax buildup in pipelines during long-distance crude oil transportation. Various strategies have been employed to address this issue, with chemical methods being the most effective and economical. However, traditional chemical inhibitors present problems due to their high toxicity and low biodegradability, leading to increased operational costs and environmental concerns. This study focuses on developing an eco-friendly paraffin inhibitor system using three different concentrations of Glycine and Palm-based Methyl Ester Sulfonate (MES). Experiments were conducted on crude oil samples from the Dulang Oilfield. The experimental measurements include wax appearance temperature (WAT), pour point temperature (PPT), and rheological tests in the absence and presence of the proposed inhibitors. The results revealed that both Glycine and MES can effectively reduce WAT, viscosity, and yield point. Specifically, 10% Glycine was the best inhibitor, reducing WAT by 23.3%. However, MES (1%, 5%, and 10%) demonstrated greater overall effectiveness, with an average WAT reduction of 13.76% compared to Glycine’s 10.85%. MES also shows a better performance in reducing viscosity and yield stress. While PPT results were insignificant, MES is recommended as a flow improver rather than a pour point depressant. The successful development of these newly formulated chemical inhibitors promises an environmentally sustainable and economically efficient approach to maximizing oil production from mature fields while mitigating paraffin precipitation.
The LIM-domain-only protein LMO2 and its binding partner LDB1 are differentially required for class switch recombination
The LIM-domain-only protein LMO2 interacts with LDB1 in context-dependent multiprotein complexes and plays key roles in erythropoiesis and T cell leukemogenesis, but whether they have any roles in B cells is unclear. Through a CRISPR/Cas9-based loss-of-function screening, we identified LMO2 and LDB1 as factors for class switch recombination (CSR) in murine B cells. LMO2 contributes to CSR at least in part by promoting end joining of DNA double-strand breaks (DSBs) and inhibiting end resection. Although LDB1 stabilizes LMO2 proteins, it is not required for end joining but functions as a positive regulator of AID transcription independent of LMO2, and this function of LDB1 requires its dimerization domain. Moreover, LDB1 directly binds to and promotes the looping of the AID promoter to upstream enhancers through dimerization. Our study revealed the mechanistically separated roles of LMO2 and LDB1 in different steps of CSR for antibody diversification.
Association of preoperative body mass index with postoperative complications and survival for patients with gastric cancer: A systematic review and meta-analysis
Objective The relationship among body mass index (BMI), postoperative complications, and clinical outcomes in patients undergoing gastrectomy for gastric cancer remains unclear. This study aimed to evaluate this association using a meta-analysis. Method We conducted a systematic search of the PubMed, Embase, and Cochrane Library databases up to February 25, 2024. Patients were classified into underweight (<18.5 kg/m2), normal weight (18.5–25.0 kg/m2), and overweight (≥25.0 kg/m2) groups based on BMI categories. Meta-analysis was performed using a random-effects model. Additionally, exploratory sensitivity and subgroup analyses were performed. Results Twenty-two studies involving 41,144 patients with gastric cancer were included for quantitative analysis. Preoperative underweight (odds ratio [OR]: 1.26; 95% confidence interval [CI]: 1.03–1.55; P = 0.024) and overweight (OR: 1.19; 95%CI: 1.09–1.30; P <0.001) were associated with an increased risk of postoperative complications. Furthermore, preoperative underweight was associated with poorer overall survival (hazard ratio [HR]: 1.40; 95%CI: 1.28–1.53; P <0.001), whereas preoperative overweight was associated with better over-survival (HR: 0.82; 95%CI: 0.73–0.91; P <0.001). Furthermore, preoperative underweight was not associated with disease-free survival (HR: 1.48; 95%CI: 0.97–2.26; P = 0.069), whereas preoperative overweight was associated with longer disease-free survival (HR: 0.80; 95%CI: 0.70–0.91; P = 0.001). In terms of specific postoperative complications, preoperative underweight was associated with an increased risk of septic shock (OR: 3.40; 95%CI: 1.26–9.17; P = 0.015) and a reduced risk of fever (OR: 0.39; 95%CI: 0.18–0.83; P = 0.014). Preoperative overweight was associated with an increased risk of wound infections (OR: 1.78; 95%CI: 1.08–2.93; P = 0.023), intestinal fistula (OR: 5.23; 95%CI: 1.93–14.21; P = 0.001), arrhythmia (OR: 6.38; 95%CI: 1.70–24.01; P = 0.006), and pancreatic fistula (OR: 3.37; 95%CI: 1.14–9.96; P = 0.028). Conclusion This study revealed that both preoperative underweight and overweight status were associated with an increased risk of postoperative complications. Moreover, the postoperative survival outcomes were significantly better in overweight compared to that of underweight patients. Trial registration Registration: INPLASY202480004.
Coding relationship links RNA G-quadruplexes and protein RGG motifs in RNA-binding protein autoregulation
RNA G-quadruplexes (rG4s), the four-stranded structures formed by guanine-rich RNA sequences, are recognized by regions in RNA-binding proteins (RBPs) that are enriched in arginine-glycine repeats (RGG motifs). Importantly, arginine and glycine are encoded by guanine-rich codons, suggesting that some RGG motifs may both be encoded by and interact with rG4s in autogenous messenger RNAs (mRNAs). By analyzing transcriptome-wide rG4 datasets, we show that hundreds of RGG motifs in humans are at least partly encoded by rG4s, with an increased incidence for longer RGG motifs (~10 or more residues). Using randomized genetic codes, we demonstrate that the rG4/RGG coding relationship derives from the universal genetic code’s structure. Moreover, we show that proteins, which contain RGG motifs encoded by experimentally detected rG4s, are significantly enriched in RNA binding relative to all RGG-containing proteins. Finally, using enhanced crosslinking and immunoprecipitation (eCLIP) data, we identify several prominent RBPs, including FUS, FMRP, and G3BP1, which interact with autogenous mRNAs in regions where RGG motifs are encoded by rG4s. Our results define a physically realistic mechanism behind autogenous mRNA/protein interactions that is hardwired in the genetic code structure and may contribute to the establishment of autoregulatory feedback loops in the cell.
GorillaFACS: The Facial Action Coding System for the Gorilla spp.
The Facial Action Coding System (FACS) is an objective observation tool for measuring human facial behaviour. It avoids subjective attributions of meaning by objectively measuring independent movements linked to facial muscles, called Action Units (AUs). FACS has been adapted to 11 other taxa, including most apes, macaques and domestic animals, but not yet gorillas. To carry out cross species studies of facial expressions within and beyond apes, gorillas need to be included in such studies. Hence, we developed the GorillaFACS for the Gorilla spp. We followed similar methodology as previous FACS: First, we examined the facial muscular plan of the gorilla. Second, we analysed gorilla videos in a wide variety of contexts to identify their spontaneous facial movements. Third, we classified the individual facial movements according to appearance changes produced by the corresponding underlying musculature. A diverse repertoire of 42 facial movements was identified in the gorilla, including 28 AUs and 14 Action Descriptors, with several new movements not identified in the HumanFACS. Although some of the movements in gorillas differ from humans, the total number of AUs is comparable to the HumanFACS (32 AUs). Importantly, the gorilla’s range of facial movements was larger than expected, suggesting a more relevant role in social interactions than what was previously assumed. GorillaFACS is a scientific tool to measure facial movements, and thus, will allow us to better understand the gorilla’s expressions and communication. Furthermore, GorillaFACS has the potential be used as an important tool to evaluate this species welfare, particularly in settings of close proximity to humans.
Expert navigators deploy rational complexity–based decision precaching for large-scale real-world planning
Efficient planning is a distinctive hallmark of intelligence in humans, who routinely make rapid inferences over complex world contexts. However, studies investigating how humans accomplish this tend to focus on naive participants engaged in simplistic tasks with small state spaces, which do not reflect the intricacy, ecological validity, and human specialization in real-world planning. In this study, we examine the street-by-street route planning of London taxi drivers navigating across more than 26,000 streets in London (United Kingdom). We explore how planning unfolded dynamically over different phases of journey construction and identify theoretic principles by which these expert human planners rationally precache decisions at prioritized environment states in an early phase of the planning process. In particular, we find that measures of path complexity predict human mental sampling prioritization dynamics independent of alternative measures derived from the real spatial context being navigated. Our data provide real-world evidence for complexity-driven remote state access within internal models and precaching during human expert route planning in very large structured spaces.
Electroconvulsive shock and transcranial magnetic stimulation do not alter the survival or spine density of adult-born striatal neurons
Adult neurogenesis has most often been studied in the hippocampus and subventricular zone-olfactory bulb, where newborn neurons contribute to a variety of behaviors. A handful of studies have also investigated adult neurogenesis in other brain regions, but relatively little is known about the properties of neurons added to non-canonical areas. One such region is the striatum. Adult-born striatal neurons have been described in both rodents and humans, but the regulation of these neurons is poorly understood. Since striatal dysfunction occurs in Parkinson’s disease, which is amenable to neurostimulation therapies, we investigated whether electroconvulsive shock (ECS) or transcranial magnetic stimulation (rTMS) modulate neuroplasticity of adult-born striatal neurons. Adult-born cells were labelled in transgenic mice and 8 days later mice were given 10 stimulations over the course of 3 weeks. Adult-born striatal neurons were consistently observed in all groups. Their dendritic morphology and expression of DARPP32 and NeuN indicated a medium spiny neuron phenotype. However, neither ECS nor rTMS altered the number of new neurons, and both treatments also had no effect on the density of dendritic spines compared to unstimulated controls. These results suggest that neither ECS nor rTMS alter early neuronal survival or morphological plasticity at postsynaptic sites in the striatum.
Governing in the face of a global crisis: When do voters punish and reward incumbent governments?
The recent COVID-19 pandemic offers a rare opportunity to understand how citizens attribute responsibility for governments’ responses to unanticipated negative—and in this case, systemic—exogenous shocks. Classical accounts of responsibility are complicated when crises are pervasive, involve multiple valence dimensions, and where individuals can make relative assessments of performance. We fielded a conjoint experiment in 16 countries with 22,147 respondents. In this experiment, subjects made re-election decisions regarding 178,184 randomly assigned incumbent profiles. We find that incumbents’ performance along both health and economic dimensions drives these hypothetical reelection decisions. Using machine learning techniques, we find only muted heterogeneity in the magnitude and distribution of these treatment effects. This result suggests that these widely reported performance signals have consistent political effects across countries. In a complementary analysis, we also find that subjects’ intentions to vote for incumbent governments are positively correlated with subjective and relative evaluations of the government’s pandemic performance, along both health and economic dimensions. These results provide consistent evidence that evaluations of pandemic performance matter politically.
The liminal space between hope and grief: The phenomenon of uncertainty as experienced by people living with relapsing-remitting multiple sclerosis
Background People with the chronic disease Multiple Sclerosis are subjected to different degrees of profound uncertainty. Uncertainty has been linked to adverse psychological effects such as feelings of heightened vulnerability, avoidance of decision-making, fear, worry, anxiety disorders, and even depression. Research into Multiple Sclerosis has a predominant focus on the scientific, practical, and psychosocial issues of uncertainty. In comparison, existential uncertainty has been under-researched, even though it might pose a greater burden to those experiencing it. Objective To understand the lived experience of uncertainty for people living with relapsing-remitting Multiple Sclerosis. Methods This study followed a phenomenological research design, employing elements of both the Reflective Lifeworld Approach and Phenomenology of Practice. Seventeen people with a recent (<1 year) diagnosis of relapsing-remitting Multiple Sclerosis were included. In-depth interviews were conducted immediately after inclusion. Results The lived experience of uncertainty can be described as a stumbling motion across the liminal space between hope and grief while dealing with oscillating feelings of unrest concerning the body, self, and others. The following four constituents further illuminate the meaning of the phenomenon: Having to constantly (re)define unfamiliar and intangible bodily changes on one’s own; Unsteady navigating amidst a destabilization of the imagined life; Relating to others as a source of, mirror or buffer for uncertainty; Going through overwhelming fears and worries while clinging to one’s own logic. Conclusion Adding to existing qualitative and phenomenological research into MS and theories on uncertainty, this study portrays uncertainty as a multifaceted experience. The findings imply the need for a continuous attunement of healthcare practitioners to the expectations, fears, avoidance techniques, and other uniquely personal circumstances of people with Multiple Sclerosis.
Enhancing drug solubility through competitive adsorption on silica nanosurfaces with ultrahigh silanol densities
We develop a technology based on competitive adsorption between drug molecules and water, specifically designed to address the critical issue of poor drug solubility. By specially engineering silica nanosurfaces with ultrahigh densities of silanol, we significantly enhance their affinity for both drug molecules and water, with a notably greater increase in water affinity. Such surfaces can effectively adsorb a variety of drug molecules under dry conditions. Upon exposure to water, these surfaces preferentially bind to water molecules, initiating a competitive adsorption process with the drug molecules. This competitive process turns water molecules from obstacles into catalysts for drug dissolution by actively displacing drug molecules from the surface, causing their rapid desorption and potentially enhancing their solubility by two to three orders of magnitude. The method is general, applicable to a wide array of drugs, stable for long-time storage, cost-effective, and scalable for mass production. Consequently, it has the potential to emerge as a next-generation platform for drug formulation and delivery.
Evidence that flocking behavior is rewarded by singing, flock mates, and mu opioid receptors in the nucleus accumbens
It has been proposed that social groups are maintained both by reward resulting from positive social interactions and by the reduction of a negative state that would otherwise be caused by social separation. European starlings, Sturnus vulgaris, develop strong conditioned place preferences for places associated with the production of song in flocks outside the breeding season (gregarious song) and singers are motivated to rejoin the flock following removal. This indicates that the act of singing in flocks is associated with a positive affective state and raises the possibility that reward induced by song in flocks may play a role in flock maintenance. The goal of this study was to begin to test this hypothesis. We found that birds that sang full songs developed stronger conditioned place preferences than non-singing birds for places associated with flock mates, indicating that singers find the presence of flock mates to be rewarding. Regardless of song rate, the presence of flock mates also induced analgesia (a reflection of the reduction of a negative state). This form of analgesia has been shown to be an indirect measure of opioid release, suggesting that the presence of flock mates may induce opioid-mediated reward. Consistent with this possibility, the numbers of mu opioid receptor immunolabeled cells in the nucleus accumbens correlated positively with measurements of gregarious song and other social behaviors. Results suggest that both gregarious song and social contact promote flock cohesion and that opioids released onto mu opioid receptors in the nucleus accumbens may play an important role.
A carnitine transporter at the blood–brain barrier modulates sleep via glial lipid metabolism in <i>Drosophila</i>
To regulate brain function, peripheral compounds must traverse the blood–brain barrier (BBB), an interface between the brain and the circulatory system. To determine whether specific transport mechanisms are relevant for sleep, we conducted a BBB-specific inducible RNAi knockdown (iKD) screen for genes affecting sleep in Drosophila . We observed reduced sleep with knockdown of solute carrier CG6126 , a carnitine transporter, as determined by isotope flux. Our findings suggest that CG6126 regulation of sleep is through the role of the carnitine shuttle in regulating fatty acid metabolism as lipid droplets accumulate in the brains of CG6126 BBB iKD flies. Knocking down mitochondrial carnitine transferases in non-BBB glial cells mimicked the reduced sleep of the CG6126 BBB iKD flies, while bypassing the necessity of carnitine transport with dietary medium-chain fatty acids or palmitoylcarnitine rescued sleep. We propose that carnitine transport via CG6126 promotes brain fatty acid metabolism necessary for maintaining sleep.
The international trial of nasal oxygen therapy after cardiac surgery (NOTACS) in patients at high risk of postoperative pulmonary complications: Economic evaluation protocol and analysis plan
Introduction High-Flow Nasal Therapy (HFNT) is an innovative non-invasive form of respiratory support. Compared to standard oxygen therapy (SOT), there is an equipoise regarding the effect of HFNT on patient-centred outcomes among those at high risk of developing postoperative pulmonary complications after undergoing cardiac surgery. The NOTACS trial aims to determine the clinical and cost-effectiveness of HFNT compared to SOT within 90 days of surgery in the United Kingdom, Australia, and New Zealand. This protocol describes the methods and analyses planned for economic evaluation embedded within the ongoing NOTACS trial. Methods and analysis The economic evaluation will identify, measure and value resources and health outcomes in both trial arms and compare changes in costs with ‘days alive and at home’ and EQ-5D-5L quality adjusted life years (QALYs) from the perspective most relevant to the decision-making country. Results from pooling data across the trial will use health and social care sector perspective. All patient-specific data including hospital/community care and health outcomes will be collected prospectively. Unit costs will be sourced from national, published or local data. Missing data will be assessed, with values replaced depending on assumed mechanism of missingness, and impact of replacement on cost-effectiveness assessed. Costs and outcomes by trial arm will be presented as components and totals per patient using a range of descriptive statistics. Regression models for costs and effects will account for patient characteristics, quality of life and health service utilization at baseline. Uncertainty in parameters, sampling and heterogeneity will be addressed through deterministic, probabilistic and subgroup analyses to assess the impact of varying methods and assumptions for costs, outcomes and approaches used in base-case analysis. Results will be interpreted using recommended national cost-effectiveness thresholds. Registration details The study is registered with ISRCTN (ISRCTN14092678) on 13/05/2020. ISRCTN is a primary registry of the WHO ICTRP network and includes all items from the WHO Trial Registration data set.
Behavioral nudges prevent loan delinquencies at scale: A 13-million-person field experiment
Americans collectively hold over $1.6 trillion in student loan debt, and over the last decade millions of borrowers have defaulted on loans, with serious consequences for their financial health. In a 13-million-person field experiment with the U.S. Department of Education, we tested the effectiveness of different email interventions to inform borrowers about alternative repayment options after a missed loan payment. Our interventions tested whether sending monthly behaviorally-informed emails, providing follow-up reminders, framing benefits in percentage (vs. dollar) terms, and providing just one recommended action step at a time (vs. two) affected borrower outcomes. We find that i) behaviorally-informed emails reduce estimated 60-d delinquencies by 0.42 pp, ii) reminders boost the efficacy of such emails by 0.57 pp, iii) describing potential savings in percentage terms is more effective than describing these benefits in dollar terms, reducing estimated delinquencies by 0.14 pp, and iv) encouraging two actions (i.e., enrollment in income-driven repayment plans and auto debit programs) repeatedly across two emails is marginally more effective than encouraging one action at-a-time across two emails, reducing estimated delinquencies by 0.05 pp. Overall, if scaled to all 13-million borrowers in our experiment, we estimate that our best-performing intervention would have averted approximately 79,800 60-d delinquencies. Our findings i) highlight the benefits of describing potential savings in percentage terms, which may magnify perceived savings for recipients, ii) underscore the risks of oversimplification, and iii) demonstrate that nudges can be an effective, low-cost complement to other policies for reducing delinquencies and supporting borrowers with student loan debt.
Smart home technology to support engagement in everyday activities while ageing: A focus group study with current and future generations of older adults
Despite the potential of smart home technologies (SHT) to support everyday activities, the implementation rate of such technology in the homes of older adults remains low. The overall aim of this study was to explore factors involved in the decision-making process in adopting SHT among current and future generations of older adults. We also aimed to identify and understand barriers and facilitators that can better support older adults’ engagement in everyday activities. Focus group discussions were used to explore the perspectives of people from diverse age groups (30–39, 50–59, and 70-79-year-olds). Three focus groups met twice at a lab designed as a two-room home equipped with SHT. Our findings revealed that the participants’ decision-making process for adopting SHT involved designs that must be adapted to the changing physical abilities and diverse needs of users. Some conditions, such as ideas for re-invention, were identified after the integration of SHT. Concerns about reliability, complicated interfaces, and value to the user influenced the decision to adopt SHT, highlighting the importance of these factors for successful implementation. Some participants did not fully understand what SHT is nor perceive its benefits, but they expressed a desire to acquire the skills and knowledge to operate SHT. Furthermore, participants desired SHT that can support an active lifestyle. The perceived advantages of SHT include enhancing the sense of security and safety, which can facilitate engagement in everyday activity. Some participants experienced a positive impact on quality of life, related to comfortable living with the implementation of SHT. Adults across age groups perceive that SHT can enhance engagement in everyday activity and the sense of safety and security. However, it is essential to identify solutions for better usability. More collaborative efforts involving diverse stakeholders are vital to bridge the disconnect between SHT design and users’ needs and preferences.
Spreading dynamics of information on online social networks
Social media is profoundly changing our society with its unprecedented spreading power. Due to the complexity of human behaviors and the diversity of massive messages, the information-spreading dynamics are complicated, and the reported mechanisms are different and even controversial. Based on data from mainstream social media platforms, including WeChat, Weibo, and Twitter, cumulatively encompassing a total of 7.45 billion users, we uncover a ubiquitous mechanism that the information-spreading dynamics are basically driven by the interplay of social reinforcement and social weakening effects. Accordingly, we propose a concise equation, which, surprisingly, can well describe all the empirical large-scale spreading trajectories. Our theory resolves a number of controversial claims and satisfactorily explains many phenomena previously observed. It also reveals that the highly clustered nature of social networks can lead to rapid and high-frequency information bursts with relatively small coverage per burst. This vital feature enables social media to have a high capacity and diversity for information dissemination, beneficial for its ecological development.
Identification of diabetic retinopathy lesions in fundus images by integrating CNN and vision mamba models
Diabetic retinopathy, a retinal disorder resulting from diabetes mellitus, is a prominent cause of visual degradation and loss among the global population. Therefore, the identification and classification of diabetic retinopathy are of utmost importance in the clinical diagnosis and therapy. Currently, these duties are extensively carried out by manual examination utilizing the human visual system. Nevertheless, manual examination is sometimes arduous, time-consuming, and prone to errors. Deep learning-based methods have recently demonstrated encouraging results in several areas, such as image categorization and natural language mining. The majority of deep learning techniques developed for medical image analysis rely on convolutional modules to extract the inherent structure of images within a certain local receptive field. Furthermore, transformer-based models have been utilized to tackle medical image processing problems by capitalizing on global connections among distant pixels in the images. Considering these analyses, this work presents a comprehensive deep learning model that combines convolutional neural network and vision mamba models. This model is designed to accurately identify and classify diabetic retinopathy lesions displayed in fundus images. Furthermore, the vision mamba component incorporates the bidirectional state space method and positional embedding to enable the location sensitivity of visual data samples and meet the conditions for global relationship context. An evaluation of the suggested method was carried out by comparison experiments between state-of-the-art algorithms and the proposed methodology. Empirical findings demonstrate that the suggested methodology surpasses the most advanced algorithms on the datasets that are accessible openly. Hence, the suggested approach may be regarded as a helpful tool for therapeutic processes.
Light signal regulates endoreduplication and tomato fruit expansion through the SlPIF1a-SlTLFP8-SlCDKB2 module
Light serves as an energy source for cell division and expansion during fruit development. Cell expansion significantly influences fruit size and is closely linked to endoreduplication, a unique cell cycle variation characterized by DNA replication without cytokinesis. Paradoxically, under conditions of ample photosynthates, light signaling suppresses cell expansion. The intricate regulation of endoreduplication in response to light signaling during fruit development has remained an intriguing question. Here, our study revealed that Tubby-like F-box protein 8 (SlTLFP8) orchestrated endoreduplication to facilitate fruit cell expansion. As an Skp1-Cullin-F-box (SCF)-type E3 ligase, SlTLFP8 promoted the ubiquitination and subsequent degradation of CYCLIN-DEPENDENT KINASE B2 (SlCDKB2), thereby elevating DNA ploidy. The light signaling component PHYTOCHROME-INTERACTING FACTOR 1a (SlPIF1a), identified as a pivotal negative regulator in the plant’s light response, was found to directly interact with the promoter of the SlTLFP8 gene, thereby stimulating its transcriptional activation. Indeed, SlPIF1a contributed to a faster expansion rate of tomato fruit during nighttime. Altogether, our results elucidate the connection between light signals and fruit size regulation through endoreduplication.
Beyond the jab: Unravelling the complexities of vaccine adoption for East Coast Fever in rural Kenya
East Coast Fever (ECF) is one of the leading causes of livestock mortality and reduced productivity across Eastern Africa, and while a live vaccine against it known as the Infection and Treatment Method has existed for three decades now, its adoption by affected communities remains low. This study sought to provide a detailed examination of the dynamics that shape Infection Treatment Method (ITM) vaccine adoption behaviours. The study examined individual, socio-cultural and ecological- level factors influencing ITM adoption using the socio-ecological model. Analyzing data obtained from 18 focus group discussions, 30 in-depth interviews with livestock keepers, and 25 key informant interviews conducted with community stakeholders, the study identified factors associated with vaccine adoption within pastoralist communities in rural Kenya. These factors included knowledge and awareness of the Infection Treatment Method vaccine, its cost, livestock keepers’ perceptions of East Coast fever relative to other livestock diseases, wildlife-livestock interactions, climate as contributing factors, and wildlife-livestock interactions influencing ECF risk and severity. Overall, the study findings emphasize the need for multifaceted strategies to increase vaccine adoption among livestock keepers.