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PurposeThe purpose of this study was to evaluate RB1 expression and survival across ovarian carcinoma histotypes and how co-occurrence of BRCA1 or BRCA2 (BRCA) alterations and RB1 loss influences survival in tubo-ovarian high-grade serous carcinoma (HGSC).Experimental designRB1 protein expression was classified by immunohistochemistry in ovarian carcinomas of 7,436 patients from the Ovarian Tumor Tissue Analysis consortium. We examined RB1 expression and germline BRCA status in a subset of 1,134 HGSC, and related genotype to overall survival (OS), tumor-infiltrating CD8+ lymphocytes, and transcriptomic subtypes. Using CRISPR-Cas9, we deleted RB1 in HGSC cells with and without BRCA1 alterations to model co-loss with treatment response. We performed whole-genome and transcriptome data analyses on 126 patients with primary HGSC to characterize tumors with concurrent BRCA deficiency and RB1 loss.ResultsRB1 loss was associated with longer OS in HGSC but with poorer prognosis in endometrioid ovarian carcinoma. Patients with HGSC harboring both RB1 loss and pathogenic germline BRCA variants had superior OS compared with patients with either alteration alone, and their median OS was three times longer than those without pathogenic BRCA variants and retained RB1 expression (9.3 vs. 3.1 years). Enhanced sensitivity to cisplatin and paclitaxel was seen in BRCA1-altered cells with RB1 knockout. Combined RB1 loss and BRCA deficiency correlated with transcriptional markers of enhanced IFN response, cell-cycle deregulation, and reduced epithelial-mesenchymal transition. CD8+ lymphocytes were most prevalent in BRCA-deficient HGSC with co-loss of RB1.ConclusionsCo-occurrence of RB1 loss and BRCA deficiency was associated with exceptionally long survival in patients with HGSC, potentially due to better treatment response and immune stimulation.

The auditory steady state response (ASSR) arises when periodic sounds evoke stable responses in auditory networks that reflect the acoustic characteristics of the stimuli, such as the amplitude of the sound envelope. Larger for some stimulus rates than others, the ASSR in the human electroencephalogram (EEG) is notably maximal for sounds modulated in amplitude at 40 Hz. To investigate the local circuit underpinnings of the large ASSR to 40 Hz amplitude-modulated (AM) sounds, we acquired skull EEG and local field potential (LFP) recordings from primary auditory cortex (A1) in the rat during the presentation of 20, 30, 40, 50, and 80 Hz AM tones. 40 Hz AM tones elicited the largest ASSR from the EEG acquired above auditory cortex and the LFP acquired from each cortical layer in A1. The large ASSR in the EEG to 40 Hz AM tones was not due to larger instantaneous amplitude of the signals or to greater phase alignment of the LFP across the cortical layers. Instead, it resulted from decreased latency variability (or enhanced temporal consistency) of the 40 Hz response. Statistical models indicate the EEG signal was best predicted by LFPs in either the most superficial or deep cortical layers, suggesting deep layer coordinators of the ASSR. Overall, our results indicate that the recruitment of non-uniform but more temporally consistent responses across A1 layers underlie the larger ASSR to amplitude-modulated tones at 40 Hz.

Background: The placenta is a transient organ critical for fetal development. Disruptions of normal placental functions can impact health throughout an individual’s entire life. Although being recognized by the NIH Human Placenta Project as an important organ, the placenta remains understudied, partly because of a lack of non-invasive tools for longitudinally evaluation for key aspects of placental functionalities. Objective: Our goal is to create a non-invasive preclinical imaging pipeline that can longitudinally probe murine placental health in vivo. We use advanced imaging processing schemes to establish functional biomarkers for non-invasive longitudinal evaluation of placental development. Methodology: We implement dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and analysis pipeline to quantify uterine contraction and placental perfusion dynamics. We use optic flow and time-frequency analysis to quantify and characterize contraction-related placental motion. Our novel imaging and analysis pipeline uses subcutaneous administration of gadolinium for steepest slope-based perfusion evaluation, enabling non-invasive longitudinal monitoring. Results: We demonstrate that the placenta exhibits spatially asymmetric contractile motion that develops from E14.5 to E17.5. Additionally, we see that placental perfusion, perfusion delivery rate, and substrate delivery all increase from E14.5 to E17.5, with the High Perfusion Chamber (HPC) leading the placental changes that occur from E14.5 to E17.5 Discussion: We advance the placental perfusion chamber paradigm with a novel, physiologically based threshold model for chamber localization and demonstrate spatially varying placental chambers using multiple functional metrics that assess mouse placental development and remodeling throughout gestation. Conclusion: Our pipeline enables the non-invasive, longitudinal assessment of multiple placenta functions from a single imaging session. Our pipeline serves as a key toolbox for advancing research in mouse models of placental disease and disorder.

What is the connection between the cultural evolution of a language and the rapid processing response to that language in the brains of individual learners? In an iterated communication study that was conducted previously, participants were asked to communicate temporal concepts such as "tomorrow," "day after," "year," and "past" using vertical movements recorded on a touch screen. Over time, participants developed simple artificial 'languages' that used space metaphorically to communicate in nuanced ways about time. Some conventions appeared rapidly and universally (e.g., using larger vertical movements to convey greater temporal durations). Other conventions required extensive social interaction and exhibited idiosyncratic variation (e.g., using vertical location to convey past or future). Here we investigate whether the brain's response during acquisition of such a language reflects the process by which the language's conventions originally evolved. We recorded participants' EEG as they learned one of these artificial space-time languages. Overall, the brain response to this artificial communication system was language-like, with, for instance, violations to the system's conventions eliciting an N400-like component. Over the course of learning, participants' brain responses developed in ways that paralleled the process by which the language had originally evolved, with early neural sensitivity to violations of a rapidly-evolving universal convention, and slowly developing neural sensitivity to an idiosyncratic convention that required slow social negotiation to emerge. This study opens up exciting avenues of future work to disentangle how neural biases influence learning and transmission in the emergence of structure in language.

Fragile X syndrome (FXS) is caused by the loss of fragile X messenger ribonucleoprotein (FMRP), a translational regulator that binds the transcripts of proteins involved in synaptic function and plasticity. Dysregulated protein synthesis is a central effect of FMRP loss, however, direct translational modulation has not been leveraged in the treatment of FXS. Thus, we examined the effect of the translational modulator integrated stress response inhibitor (ISRIB) in treating synaptic and behavioral symptoms of FXS. We show that FMRP loss dysregulates synaptic protein abundance, stabilizing dendritic spines through increased PSD-95 levels while preventing spine maturation through reduced glutamate receptor accumulation, thus leading to the formation of dense, immature dendritic spines, characteristic of FXS patients and Fmr1 knockout (KO) mice. ISRIB rescues these deficits and improves social recognition in Fmr1 KO mice. These findings highlight the therapeutic potential of targeting core translational mechanisms in FXS and neurodevelopmental disorders more broadly.

Substantial global attention is focused on how to reduce the risk of future pandemics. Reducing this risk requires investment in prevention, preparedness, and response. Although preparedness and response have received significant focus, prevention, especially the prevention of zoonotic spillover, remains largely absent from global conversations. This oversight is due in part to the lack of a clear definition of prevention and lack of guidance on how to achieve it. To address this gap, we elucidate the mechanisms linking environmental change and zoonotic spillover using spillover of viruses from bats as a case study. We identify ecological interventions that can disrupt these spillover mechanisms and propose policy frameworks for their implementation. Recognizing that pandemics originate in ecological systems, we advocate for integrating ecological approaches alongside biomedical approaches in a comprehensive and balanced pandemic prevention strategy.

An important issue in the semantic memory literature concerns the relative importance of experience-based sensorimotor versus language corpus-based distributional information in conceptual representations. Here we examine how each sort of information is associated with the EEG response to words in a property verification task in which participants indicated whether or not a property term (such as ”red”) is typically obtained for a concept term (such as ”APPLE”). To define and measure each type of information, we operationalized distributional and sensorimotor information using cosine distance measurements derived from GloVe Embeddings and Lancaster Sensorimotor Norms respectively. We then modeled single-trial EEG responses to property words in a property verification task using regression models. Our findings indicate that semantic processing in this task simultaneously incorporates distributional and sensorimotor information, and their contribution is shaped by task-relevant linguistic context. We aim for our study to contribute to a critical examination of such information operationalizations and also encourage a systematic evaluation of their performance across tasks, particularly forEEG measurements.

Recent studies link surprisal —a measure of conditional probability of words in context—to the N400 component size in event-related potentials (ERP), supporting a role for predictive coding in language comprehension. An alternative account argues that N400 variations are better explained by a retrieval mechanism sensitive to the semantic similarity between a word and its preceding context. Because jokes often rely on the presence of unexpected words that relate to the prior context multiple ways, they afford observation of the relative importance of contextual predictability and contextual similarity. We employed state-of-the-art machine learning to assess the surprisal and contextual semantic similarity of critical words in jokes and control stimuli. Using regression models to predict ERP, we found contextual similarity best explains N400 and P600 responses, supporting the semantic similarity account. Additionally, jokes elicit enhanced N400 and P600 responses that go beyond that attributable to their surprisal and contextual semantic similarity.

Judgements about others' behavior is often made based on the relative rank of that behavior. We investigated this in the new domain of pro-environmental behavior, specifically for the categories of energy and water consumption, food (meat) consumption and transport choice. Using unimodal and bimodal distributions, we experimentally manipulated three fictional individuals' (common points) rank positions while keeping their absolute frequency of behaviors constant. Consistent with previous literature, participants' judgements about these people's pro-environmental behavior differed based on their rank position. Rank effects were not moderated by the perceived Importance of others' behavior, the perceived Visibility of the behavior, or the perceived level of Control. The results of this experiment are in line with a Decision by Sampling account of judgments of pro-environmental behavior, and set a foundation for future research seeking to conduct behavioral interventions (such as rank-based nudges) within this domain. Prior to this, however, future studies should investigate whether the smaller effect sizes found in this experiment, compared to those seen in previous research, are attributable to methodological differences, or the domain itself.

Abstract Various techniques using fluorescent reporter probes have been developed, such as GFP transgenic mouse lines that are used to detect spatial–temporal expression levels of genes. Although GFP expression is largely considered non-toxic, recent reports have indicated that under certain conditions GFP can display cellular toxicity. We hereby report the nuclear toxicity of H2B-GFP using a K14 specific Tet-on reporter mouse system. Using this system, GFP accumulates in the nucleus of all K14 expressing cells, such as the ocular surface epithelia and ocular adnexa. Expression of high levels of nuclear GFP during embryonic stages led to an eye open-at-birth (EOB) phenotype and abnormal ocular adnexa development and during adult and aging stages showed notable toxicity to ocular tissues. Other tissues, such as skin, also presented multiple defects associated with H2B-GFP expression. This toxicity was found to be concentration dependent, with homozygous mice presenting extremely high toxicity, while heterozygous mice presented limited toxicity. Upon induction, the accumulation of H2B-GFP in the nucleus of homozygous mice led to apoptosis within 2 weeks. This study therefore shows that although the use of nuclear GFP reporter mice is a valuable tool, at high levels, nuclear GFP can be toxic, leading to cell death and affecting tissue function.

The aim of this study was to explore whether different durations of canine-assisted intervention (CAI) influenced the beneficial effects of CAI on anxiety, stress, depression, and the well-being of higher education (HE) students. Eighty-eight participants took part in an exploratory randomised control trial (RCT) and were assigned to the 2, 5, and 10-min CAI groups who interacted with a canine, or a control group who watched an unrelated slideshow. Pre- and post-intervention anxiety, stress, depression, and well-being levels were measured. Additionally, the type of interaction between humans and canines was recorded as well as participants’ views of the canines’ neoteny (juvenile features) to explore whether interaction activity and canine features have an impact on the beneficial positive effects of CAI. The results showed no differences in the duration of CAI in reducing anxiety, stress, and depression, meaning a 2-min CAI session was as effective as a 10-min session. The results also found individual intervention activities between humans and canines did not predict a reduction in anxiety, stress, depression, or an increase in general well-being. Additionally, a negative correlation was found between the cuteness of the canine and anxiety, and between the cuddliness of the canine and stress, although these results should be interpreted with caution due to high canine trait scores. Overall, this study used a CAI and control group to explore the differences between a single 2, 5, and 10-min CAI sessions in HE students and demonstrated a 2-min CAI session was as effective as a longer 10-min CAI session in supporting the mental health of HE students, by reducing anxiety, stress, and depression levels in the treatment group.

Computational tools, particularly AI, are becoming more ubiquitous in scientific research; but what impact do they have on the environment?[Graphic: see text]

Abstract Tumour-host immune interactions lead to complex changes in the tumour microenvironment (TME), impacting progression, metastasis and response to therapy. While it is clear that cancer cells can have the capacity to alter immune landscapes, our understanding of this process is incomplete. Herein we show that endocytic trafficking at the plasma membrane, mediated by the small GTPase ARF6, enables melanoma cells to impose an immunosuppressive TME that accelerates tumour development. This ARF6-dependent TME is vulnerable to immune checkpoint blockade therapy (ICB) but in murine melanoma, loss of Arf6 causes resistance to ICB. Likewise, downregulation of ARF6 in patient tumours correlates with inferior overall survival after ICB. Mechanistically, these phenotypes are at least partially explained by ARF6-dependent recycling, which controls plasma membrane density of the interferon-gamma receptor. Collectively, our findings reveal the importance of endomembrane trafficking in outfitting tumour cells with the ability to shape their immune microenvironment and respond to immunotherapy.

Abstract The auditory steady state response (ASSR) arises when periodic sounds evoke stable responses in auditory networks that reflect the acoustic characteristics of the stimuli, such as the amplitude of the sound envelope. Larger for some stimulus rates than others, the ASSR in the human electroencephalogram (EEG) is notably maximal for sounds modulated in amplitude at 40 Hz. To investigate the local circuit underpinnings of the large ASSR to 40 Hz amplitude-modulated (AM) sounds, we acquired skull EEG and local field potential (LFP) recordings from primary auditory cortex (A1) in the rat during the presentation of 20, 30, 40, 50, and 80 Hz AM tones. 40 Hz AM tones elicited the largest ASSR from the EEG acquired above auditory cortex and the LFP acquired from each cortical layer in A1. The large ASSR in the EEG to 40 Hz AM tones was not due to larger instantaneous amplitude of the signals or to greater phase alignment of the LFP across the cortical layers. Instead, it resulted from decreased latency variability (or enhanced temporal consistency) of the 40 Hz response. Statistical models indicate the EEG signal was best predicted by LFPs in either the most superficial or deep cortical layers, suggesting deep layer coordinators of the ASSR. Overall, our results indicate that the recruitment of non-uniform but more temporally consistent responses across A1 layers underlie the larger ASSR to amplitude-modulated tones at 40 Hz.

Abstract Theoretical accounts of the N400 are divided as to whether the amplitude of the N400 response to a stimulus reflects the extent to which the stimulus was predicted, the extent to which the stimulus is semantically similar to its preceding context, or both. We use state-of-the-art machine learning tools to investigate which of these three accounts is best supported by the evidence. GPT-3, a neural language model trained to compute the conditional probability of any word based on the words that precede it, was used to operationalize contextual predictability. In particular, we used an information-theoretic construct known as surprisal (the negative logarithm of the conditional probability). Contextual semantic similarity was operationalized by using two high-quality co-occurrence-derived vector-based meaning representations for words: GloVe and fastText. The cosine between the vector representation of the sentence frame and final word was used to derive contextual cosine similarity estimates. A series of regression models were constructed, where these variables, along with cloze probability and plausibility ratings, were used to predict single trial N400 amplitudes recorded from healthy adults as they read sentences whose final word varied in its predictability, plausibility, and semantic relationship to the likeliest sentence completion. Statistical model comparison indicated GPT-3 surprisal provided the best account of N400 amplitude and suggested that apparently disparate N400 effects of expectancy, plausibility, and contextual semantic similarity can be reduced to variation in the predictability of words. The results are argued to support predictive coding in the human language network.

Did you know that only 7.7% of new Learning Developers are taught how to conduct a one-to-one tutorial, and only 38.5% are taught how to lead a workshop? (all data according to our survey: Coulson & Crofts, 2023). Despite this, nearly half (45.6%) of new Learning Developers have had the opportunity to complete a Postgraduate Certificate (PG Cert) in Teaching in Higher Education, which is not tailored for such an expert role. Kate and Matt met at #ALDCon23 in Portsmouth and discussed how new community members develop their expertise. Matt is a new Learning Developer, and Kate has worked in Learning Development for over a decade; they recognised that there was a gap in the ALDinHE CPD provision and agreed to find out if this was true. This presentation outlined the results of a survey they designed and shared with the ALDinHE community in November 2023. This online survey asked new and established Learning Developers about their experiences of CPD, including what was useful, what they experienced and what would have benefitted them. The survey showed a clear gap in Continued Professional Development (CPD) provision for Learning Developers. Kate and Matt are now in the process of designing a CPD framework that not only meets the needs of new Learning Developers but also enhances the skills and knowledge of more experienced colleagues. Participants had the opportunity to contribute their own experiences of CPD to the group to enhance further the quantitative data collected in the survey. As part of this session and beyond, Kate and Matt are keen to include community members in the design process, including being critical friends, designing and contributing resources and teaching development sessions within the framework.

The ALDinHE Artificial Intelligence (AI) Community of Practice (CoP) was established in the summer of 2023. It has an international membership of over 200 Learning Developers. The CoP meets monthly to discuss an AI-related topic. Since its inception, topics have included organisational approaches to AI, AI in assessment, maths and statistics, and the use of AI in Learning Development tutorials. The group is keen to create an opportunity to share current projects, approaches, and thinking. This wildcard session replicated a world café-style event on a smaller scale. It required a large room. Tables were hosted by colleagues from Abertay University, Bournemouth University, De Montfort University, the University of Manchester, the University of Northampton, and Spurgeon’s College. Each host led a 15-minute session, sharing their AI-related project with delegates seated around the table, which included a short presentation followed by an opportunity for delegates to share their views and exchange ideas. After 15 minutes, the delegates moved to another table. Within the hour, the delegates rotated around three tables. It was hoped that delegates would attend the session to expand their understanding of AI. Delegates who use AI in their day-to-day work had an opportunity to share their experiences, while delegates who were less experienced could expand their understanding and discuss with their peers the challenges and opportunities that AI brings to Learning Development.

In recent years, Generative Artificial Intelligence (Gen AI) has become the topic of debate within higher education generally, within institutions (their official response and approach), within subject areas (how to utilise within subject teaching) and within the professional sphere of Learning Development. In the summer of 2023, an Association for Learning Development in Higher Education (ALDinHE) Community of Practice was established, and now, it has over 200 members from the UK, Europe, North America, Australia, and New Zealand. This group meets monthly to discuss all aspects of Gen AI, and this mini keynote will share how Learning Developers are engaging (or not) with Gen AI. The session will be open and friendly. Designed to enable colleagues to discuss their challenges, avoidance or how they embrace AI within their practice. Prompt Questions 1) Are you engaging with Artificial Intelligence (AI)? If so, how? If not, why not? 2) Should Learning Developers be engaging with AI? If so, how? 3) What could ALDinHE do to support your (potential) engagement with AI?

Arctic terrestrial invertebrate biodiversity is generally poorly known, but the archipelago of Svalbard has one of the most up-to-date inventories of its terrestrial and freshwater faunas of any Arctic region, offering a baseline for long term monitoring of invertebrate communities in space and time. Since the most recent review of the Svalbard invertebrate fauna was produced in 2014, knowledge of this fauna has developed and this inventory is here critically revised and updated. Our aims are (1) to critically review the inventory based on current taxonomic knowledge, (2) publish the complete species inventory, including cross-referencing to the relevant publications, in an open access data archive (GBIF), and (3) highlight the particular advantages that working in Svalbard may bring for scientists working on terrestrial, freshwater, and cryospheric environments. The inventory contains a total 1091 valid species names or interim names. A gap analysis in the Barcode of Life Data Systems reveals that 50% of the species currently documented from Svalbard lack COI (Cytochrome c oxidase subunit 1) barcode reference sequences in this database. Gaps in our knowledge of the Svalbard fauna and how these may be resolved are discussed.

BackgroundExplanations for why social media users propagate misinformation include failure of classical reasoning (over-reliance on intuitive heuristics), motivated reasoning (conforming to group opinion), and personality traits (e.g., narcissism). However, there is a lack of consensus on which explanation is most predictive of misinformation spread. Previous work is also limited by not distinguishing between passive (i.e., “liking”) and active (i.e., “retweeting”) propagation behaviors.MethodsTo examine this issue, 858 Twitter users were recruited to engage in a Twitter simulation task in which they were shown real tweets on public health topics (e.g., COVID-19 vaccines) and given the option to “like”, “reply”, “retweet”, “quote”, or select “no engagement”. Survey assessments were then given to measure variables corresponding to explanations for: classical reasoning [cognitive reflective thinking (CRT)], motivated reasoning (religiosity, political conservatism, and trust in medical science), and personality traits (openness to new experiences, conscientiousness, empathy, narcissism).ResultsCognitive reflective thinking, conscientiousness, openness, and emotional concern empathy were all negatively associated with liking misinformation, but not significantly associated with retweeting it. Trust in medical scientists was negatively associated with retweeting misinformation, while grandiose narcissism and religiosity were positively associated. An exploratory analysis on engagement with misinformation corrections shows that conscientiousness, openness, and CRT were negatively associated with liking corrections while political liberalism, trust in medical scientists, religiosity, and grandiose narcissism were positively associated. Grandiose narcissism was the only factor positively associated with retweeting corrections.DiscussionFindings support an inhibitory role for classical reasoning in the passive spread of misinformation (e.g., “liking”), and a major role for narcissistic tendencies and motivated reasoning in active propagating behaviors (“retweeting”). Results further suggest differences in passive and active propagation, as multiple factors influence liking behavior while retweeting is primarily influenced by two factors. Implications for ecologically valid study designs are also discussed to account for greater nuance in social media behaviors in experimental research.

Summary: Macrophages are major host cells for the protozoan Leishmania parasite. Depending on their activation state, they either contribute to the detection and elimination of Leishmania spp. or promote parasite resilience. Here, we report that the activation of the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) in macrophages plays a pivotal role in the progression of Leishmania infantum infection by controlling inflammation and redox balance of macrophages. We also highlight the involvement of the NOX2/reactive oxygen species (ROS) axis in early Nrf2 activation and, subsequently, prostaglandin E2 (PGE2)/EP2r signaling in the sustenance of Nrf2 activation upon infection. Moreover, we establish a ferroptosis-like process within macrophages as a cell death program of L. infantum and the protective effect of Nrf2 in macrophages against L. infantum death. Altogether, these results identify Nrf2 as a critical factor for the susceptibility of L. infantum infection, highlighting Nrf2 as a promising pharmacological target for the development of therapeutic approaches for the treatment of visceral leishmaniasis.

Our objective was to test whether p53 expression status is associated with survival for women diagnosed with the most common ovarian carcinoma histotypes (high-grade serous carcinoma [HGSC], endometrioid carcinoma [EC], and clear cell carcinoma [CCC]) using a large multi-institutional cohort from the Ovarian Tumor Tissue Analysis (OTTA) consortium. p53 expression was assessed on 6,678 cases represented on tissue microarrays from 25 participating OTTA study sites using a previously validated immunohistochemical (IHC) assay as a surrogate for the presence and functional effect of TP53 mutations. Three abnormal expression patterns (overexpression, complete absence, and cytoplasmic) and the normal (wild type) pattern were recorded. Survival analyses were performed by histotype. The frequency of abnormal p53 expression was 93.4% (4,630/4,957) in HGSC compared to 11.9% (116/973) in EC and 11.5% (86/748) in CCC. In HGSC, there were no differences in overall survival across the abnormal p53 expression patterns. However, in EC and CCC, abnormal p53 expression was associated with an increased risk of death for women diagnosed with EC in multivariate analysis compared to normal p53 as the reference (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.36-3.47, p = 0.0011) and with CCC (HR = 1.57, 95% CI 1.11-2.22, p = 0.012). Abnormal p53 was also associated with shorter overall survival in The International Federation of Gynecology and Obstetrics stage I/II EC and CCC. Our study provides further evidence that functional groups of TP53 mutations assessed by abnormal surrogate p53 IHC patterns are not associated with survival in HGSC. In contrast, we validate that abnormal p53 IHC is a strong independent prognostic marker for EC and demonstrate for the first time an independent prognostic association of abnormal p53 IHC with overall survival in patients with CCC.

BackgroundCyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo-ovarian high-grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large-scale, histotype-specific validation has been performed. The hypothesis was that high-level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC.MethodsWithin the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated.ResultsHigh-level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high-level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08-1.47, p = .034, and HR, 1.18; 95% CI, 1.05-1.32, p = .015, respectively). This was also true for cases with combined high-level amplification/overexpression (HR, 1.26; 95% CI, 1.09-1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1-SD increase; 95% CI, 0.94-1.06; p = .58). CCNE1 high-level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss.ConclusionThis study provides large-scale validation that CCNE1 high-level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.

Abstract Substantial global attention is focused on how to reduce the risk of future pandemics. Reducing this risk requires investment in prevention, preparedness, and response. Although preparedness and response have received significant focus, prevention, especially the prevention of zoonotic spillover, remains largely absent from global conversations. This oversight is due in part to the lack of a clear definition of prevention and lack of guidance on how to achieve it. To address this gap, we elucidate the mechanisms linking environmental change and zoonotic spillover using spillover of viruses from bats as a case study. We identify ecological interventions that can disrupt these spillover mechanisms and propose policy frameworks for their implementation. Recognizing that pandemics originate in ecological systems, we advocate for integrating ecological approaches alongside biomedical approaches in a comprehensive and balanced pandemic prevention strategy.

Abstract Diminishing natural resources and increasing climatic volatility are impacting agri-food systems, prompting the need for sustainable and resilient alternatives. Python farming is well established in Asia but has received little attention from mainstream agricultural scientists. We measured growth rates in two species of large pythons (Malayopython reticulatus and Python bivittatus) in farms in Thailand and Vietnam and conducted feeding experiments to examine production efficiencies. Pythons grew rapidly over a 12-month period, and females grew faster than males. Food intake and growth rates early in life were strong predictors of total lifetime growth, with daily mass increments ranging from 0.24 to 19.7 g/day for M. reticulatus and 0.24 to 42.6 g/day for P. bivittatus, depending on food intake. Pythons that fasted for up to 4.2 months lost an average of 0.004% of their body mass per day, and resumed rapid growth as soon as feeding recommenced. Mean food conversion rate for dressed carcasses was 4.1%, with useable products (dressed carcass, skin, fat, gall bladder) comprising 82% of the mass of live animals. In terms of food and protein conversion ratios, pythons outperform all mainstream agricultural species studied to date. The ability of fasting pythons to regulate metabolic processes and maintain body condition enhances food security in volatile environments, suggesting that python farming may offer a flexible and efficient response to global food insecurity.