Discover and publish cutting edge, open research.

Nick K. Jones1,2*, Lucy Rivett1,2*, Chris Workman3, Mark Ferris3, Ashley Shaw1, Cambridge COVID-19 Collaboration1,4, Paul J. Lehner1,4, Rob Howes5, Giles Wright3, Nicholas J. Matheson1,4,6¶, Michael P. Weekes1,7¶1 Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK2 Clinical Microbiology & Public Health Laboratory, Public Health England, Cambridge, UK3 Occupational Health and Wellbeing, Cambridge Biomedical Campus, Cambridge, UK4 Cambridge Institute of Therapeutic Immunology & Infectious Disease, University of Cambridge, Cambridge, UK5 Cambridge COVID-19 Testing Centre and AstraZeneca, Anne Mclaren Building, Cambridge, UK6 NHS Blood and Transplant, Cambridge, UK7 Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK*Joint first authorship¶Joint last authorshipCorrespondence: [email protected] UK has initiated mass COVID-19 immunisation, with healthcare workers (HCWs) given early priority because of the potential for workplace exposure and risk of onward transmission to patients. The UK’s Joint Committee on Vaccination and Immunisation has recommended maximising the number of people vaccinated with first doses at the expense of early booster vaccinations, based on single dose efficacy against symptomatic COVID-19 disease.1-3At the time of writing, three COVID-19 vaccines have been granted emergency use authorisation in the UK, including the BNT162b2 mRNA COVID-19 vaccine (Pfizer-BioNTech). A vital outstanding question is whether this vaccine prevents or promotes asymptomatic SARS-CoV-2 infection, rather than symptomatic COVID-19 disease, because sub-clinical infection following vaccination could continue to drive transmission. This is especially important because many UK HCWs have received this vaccine, and nosocomial COVID-19 infection has been a persistent problem.Through the implementation of a 24 h-turnaround PCR-based comprehensive HCW screening programme at Cambridge University Hospitals NHS Foundation Trust (CUHNFT), we previously demonstrated the frequent presence of pauci- and asymptomatic infection amongst HCWs during the UK’s first wave of the COVID-19 pandemic.4 Here, we evaluate the effect of first-dose BNT162b2 vaccination on test positivity rates and cycle threshold (Ct) values in the asymptomatic arm of our programme, which now offers weekly screening to all staff.Vaccination of HCWs at CUHNFT began on 8th December 2020, with mass vaccination from 8th January 2021. Here, we analyse data from the two weeks spanning 18thto 31st January 2021, during which: (a) the prevalence of COVID-19 amongst HCWs remained approximately constant; and (b) we screened comparable numbers of vaccinated and unvaccinated HCWs. Over this period, 4,408 (week 1) and 4,411 (week 2) PCR tests were performed from individuals reporting well to work. We stratified HCWs <12 days or > 12 days post-vaccination because this was the point at which protection against symptomatic infection began to appear in phase III clinical trial.226/3,252 (0·80%) tests from unvaccinated HCWs were positive (Ct<36), compared to 13/3,535 (0·37%) from HCWs <12 days post-vaccination and 4/1,989 (0·20%) tests from HCWs ≥12 days post-vaccination (p=0·023 and p=0·004, respectively; Fisher’s exact test, Figure). This suggests a four-fold decrease in the risk of asymptomatic SARS-CoV-2 infection amongst HCWs ≥12 days post-vaccination, compared to unvaccinated HCWs, with an intermediate effect amongst HCWs <12 days post-vaccination.A marked reduction in infections was also seen when analyses were repeated with: (a) inclusion of HCWs testing positive through both the symptomatic and asymptomatic arms of the programme (56/3,282 (1·71%) unvaccinated vs 8/1,997 (0·40%) ≥12 days post-vaccination, 4·3-fold reduction, p=0·00001); (b) inclusion of PCR tests which were positive at the limit of detection (Ct>36, 42/3,268 (1·29%) vs 15/2,000 (0·75%), 1·7-fold reduction, p=0·075); and (c) extension of the period of analysis to include six weeks from December 28th to February 7th 2021 (113/14,083 (0·80%) vs 5/4,872 (0·10%), 7·8-fold reduction, p=1x10-9). In addition, the median Ct value of positive tests showed a non-significant trend towards increase between unvaccinated HCWs and HCWs > 12 days post-vaccination (23·3 to 30·3, Figure), suggesting that samples from vaccinated individuals had lower viral loads.We therefore provide real-world evidence for a high level of protection against asymptomatic SARS-CoV-2 infection after a single dose of BNT162b2 vaccine, at a time of predominant transmission of the UK COVID-19 variant of concern 202012/01 (lineage B.1.1.7), and amongst a population with a relatively low frequency of prior infection (7.2% antibody positive).5This work was funded by a Wellcome Senior Clinical Research Fellowship to MPW (108070/Z/15/Z), a Wellcome Principal Research Fellowship to PJL (210688/Z/18/Z), and an MRC Clinician Scientist Fellowship (MR/P008801/1) and NHSBT workpackage (WPA15-02) to NJM. Funding was also received from Addenbrooke’s Charitable Trust and the Cambridge Biomedical Research Centre. We also acknowledge contributions from all staff at CUHNFT Occupational Health and Wellbeing and the Cambridge COVID-19 Testing Centre.

Scene flow tracks the three-dimensional (3D) motion of each point in adjacent point clouds. It provides fundamental 3D motion perception for autonomous driving and server robot. Although the Red Green Blue Depth (RGBD) camera or Light Detection and Ranging (LiDAR) capture discrete 3D points in space, the objects and motions usually are continuous in the macro world. That is, the objects keep themselves consistent as they flow from the current frame to the next frame. Based on this insight, the Generative Adversarial Networks (GAN) is utilized to self-learn 3D scene flow with no need for ground truth. The fake point cloud of the second frame is synthesized from the predicted scene flow and the point cloud of the first frame. The adversarial training of the generator and discriminator is realized through synthesizing indistinguishable fake point cloud and discriminating the real point cloud and the synthesized fake point cloud. The experiments on Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI) scene flow dataset show that our method realizes promising results without ground truth. Just as human, the proposed method can identify the similar local structures of two adjacent frames even without knowing the ground truth scene flow. Then, the local correspondence can be correctly estimated, and further the scene flow is correctly estimated.   Corresponding author(s) Email: [email protected]

Leukocyte differential test is a widely performed clinical procedure for screening infectious diseases. Existing hematology analyzers require labor-intensive work and a panel of expensive reagents. Here we report an artificial-intelligence enabled reagent-free imaging hematology analyzer (AIRFIHA) modality that can accurately classify subpopulations of leukocytes with minimal sample preparation. AIRFIHA is realized through training a two-step residual neural network using label-free images of isolated leukocytes acquired from a custom-built quantitative phase microscope. By leveraging the rich information contained in quantitative phase images, we not only achieved high accuracy in differentiating B and T lymphocytes, but also classified CD4 and CD8 cells, therefore outperforming the classification accuracy of most current hematology analyzers. We validated the performance of AIRFIHA in a randomly selected test set and cross-validated it across all blood donors. Owing to its easy operation, low cost, and accurate discerning capability of complex leukocyte subpopulations, we envision AIRFIHA is clinically translatable and can also be deployed in resource-limited settings, e.g., during pandemic situations for the rapid screening of infectious diseases.  Corresponding author(s) Email:    [email protected],  [email protected]

Tam Hunt [1], Jonathan SchoolerUniversity of California Santa Barbara Synchronization, harmonization, vibrations, or simply resonance in its most general sense seems to have an integral relationship with consciousness itself. One of the possible “neural correlates of consciousness” in mammalian brains is a combination of gamma, beta and theta synchrony. More broadly, we see similar kinds of resonance patterns in living and non-living structures of many types. What clues can resonance provide about the nature of consciousness more generally? This paper provides an overview of resonating structures in the fields of neuroscience, biology and physics and attempts to coalesce these data into a solution to what we see as the “easy part” of the Hard Problem, which is generally known as the “combination problem” or the “binding problem.” The combination problem asks: how do micro-conscious entities combine into a higher-level macro-consciousness? The proposed solution in the context of mammalian consciousness suggests that a shared resonance is what allows different parts of the brain to achieve a phase transition in the speed and bandwidth of information flows between the constituent parts. This phase transition allows for richer varieties of consciousness to arise, with the character and content of that consciousness in each moment determined by the particular set of constituent neurons. We also offer more general insights into the ontology of consciousness and suggest that consciousness manifests as a relatively smooth continuum of increasing richness in all physical processes, distinguishing our view from emergentist materialism. We refer to this approach as a (general) resonance theory of consciousness and offer some responses to Chalmers’ questions about the different kinds of “combination problem.”  At the heart of the universe is a steady, insistent beat: the sound of cycles in sync…. [T]hese feats of synchrony occur spontaneously, almost as if nature has an eerie yearning for order. Steven Strogatz, Sync: How Order Emerges From Chaos in the Universe, Nature and Daily Life (2003) If you want to find the secrets of the universe, think in terms of energy, frequency and vibration.Nikola Tesla (1942) I.               Introduction Is there an “easy part” and a “hard part” to the Hard Problem of consciousness? In this paper, we suggest that there is. The harder part is arriving at a philosophical position with respect to the relationship of matter and mind. This paper is about the “easy part” of the Hard Problem but we address the “hard part” briefly in this introduction.  We have both arrived, after much deliberation, at the position of panpsychism or panexperientialism (all matter has at least some associated mind/experience and vice versa). This is the view that all things and processes have both mental and physical aspects. Matter and mind are two sides of the same coin.  Panpsychism is one of many possible approaches that addresses the “hard part” of the Hard Problem. We adopt this position for all the reasons various authors have listed (Chalmers 1996, Griffin 1997, Hunt 2011, Goff 2017). This first step is particularly powerful if we adopt the Whiteheadian version of panpsychism (Whitehead 1929).  Reaching a position on this fundamental question of how mind relates to matter must be based on a “weight of plausibility” approach, rather than on definitive evidence, because establishing definitive evidence with respect to the presence of mind/experience is difficult. We must generally rely on examining various “behavioral correlates of consciousness” in judging whether entities other than ourselves are conscious – even with respect to other humans—since the only consciousness we can know with certainty is our own. Positing that matter and mind are two sides of the same coin explains the problem of consciousness insofar as it avoids the problems of emergence because under this approach consciousness doesn’t emerge. Consciousness is, rather, always present, at some level, even in the simplest of processes, but it “complexifies” as matter complexifies, and vice versa. Consciousness starts very simple and becomes more complex and rich under the right conditions, which in our proposed framework rely on resonance mechanisms. Matter and mind are two sides of the coin. Neither is primary; they are coequal.  We acknowledge the challenges of adopting this perspective, but encourage readers to consider the many compelling reasons to consider it that are reviewed elsewhere (Chalmers 1996, Griffin 1998, Hunt 2011, Goff 2017, Schooler, Schooler, & Hunt, 2011; Schooler, 2015).  Taking a position on the overarching ontology is the first step in addressing the Hard Problem. But this leads to the related questions: at what level of organization does consciousness reside in any particular process? Is a rock conscious? A chair? An ant? A bacterium? Or are only the smaller constituents, such as atoms or molecules, of these entities conscious? And if there is some degree of consciousness even in atoms and molecules, as panpsychism suggests (albeit of a very rudimentary nature, an important point to remember), how do these micro-conscious entities combine into the higher-level and obvious consciousness we witness in entities like humans and other mammals?  This set of questions is known as the “combination problem,” another now-classic problem in the philosophy of mind, and is what we describe here as the “easy part” of the Hard Problem. Our characterization of this part of the problem as “easy”[2] is, of course, more than a little tongue in cheek. The authors have discussed frequently with each other what part of the Hard Problem should be labeled the easier part and which the harder part. Regardless of the labels we choose, however, this paper focuses on our suggested solution to the combination problem.  Various solutions to the combination problem have been proposed but none have gained widespread acceptance. This paper further elaborates a proposed solution to the combination problem that we first described in Hunt 2011 and Schooler, Hunt, and Schooler 2011. The proposed solution rests on the idea of resonance, a shared vibratory frequency, which can also be called synchrony or field coherence. We will generally use resonance and “sync,” short for synchrony, interchangeably in this paper. We describe the approach as a general resonance theory of consciousness or just “general resonance theory” (GRT). GRT is a field theory of consciousness wherein the various specific fields associated with matter and energy are the seat of conscious awareness.  A summary of our approach appears in Appendix 1.  All things in our universe are constantly in motion, in process. Even objects that appear to be stationary are in fact vibrating, oscillating, resonating, at specific frequencies. So all things are actually processes. Resonance is a specific type of motion, characterized by synchronized oscillation between two states.  An interesting phenomenon occurs when different vibrating processes come into proximity: they will often start vibrating together at the same frequency. They “sync up,” sometimes in ways that can seem mysterious, and allow for richer and faster information and energy flows (Figure 1 offers a schematic). Examining this phenomenon leads to potentially deep insights about the nature of consciousness in both the human/mammalian context but also at a deeper ontological level.

Cannabis sativa is an extraordinarily versatile species. Hemp and its cousin marijuana, both C. sativa, have been used for millennia as a source of fibre, oil and for medicinal, spiritual and recreational purposes. Because the consumption of Cannabis can have psychoactive effects, the plant has been widely banned throughout the last century. In the past decade, evidence of its medicinal properties did lead to the relaxation of legislation in many countries around the world. Consequently, the genetics and development of Cannabis as well as Cannabis-derived products are the subject of renewed attention.Here, we review the biology of C. sativa, including recent insights from taxonomy, morphology and genomics, with an emphasis on the genetics of cannabinoid synthesis. Because the female Cannabis flower is of special interest as the site of cannabinoid synthesis, we explore flower development, flowering time well as the species’ unique sex determination system in detail. Furthermore, we outline the tremendous medicinal, engineering, and environmental opportunities that Cannabis bears. Together, the picture emerges that our understanding of Cannabis biology currently progresses at an unusual speed. A future challenge will be to preserve the multi-purpose nature of Cannabis, and to harness its medicinal properties and sustainability advantages simultaneously.

Quantum chemistry must evolve if it wants to fully leverage the benefits of the internet age, where the world wide web offers a vast tapestry of tools that enable users to communicate and interact with complex data at the speed and convenience of a button press. The Open Chemistry project has developed an open source framework that offers an end-to-end solution for producing, sharing, and visualizing quantum chemical data interactively on the web using an array of modern tools and approaches. These tools build on some of the best open source community projects such as Jupyter for interactive online notebooks, coupled with 3D accelerated visualization, state-of-the-art computational chemistry codes including NWChem and Psi4 and emerging machine learning and data mining tools such as ChemML and ANI. They offer flexible formats to import and export data, along with approaches to compare computational and experimental data.

This paper responds to one by Graham Martin and colleagues, who offered a critique of my previous publications on masks for the lay public in the Covid-19 pandemic. I address their charges that my co-authors and I had misapplied the precautionary principle; drawn conclusions that were not supported by empirical research; and failed to take account of potential harms. But before that, I remind Martin et al that the evidence on mask wearing goes beyond the contested trials and observational studies they place centre stage. I set out some key findings from basic science, epidemiology, mathematical modelling, case studies and natural experiments, and use this rich and diverse body of evidence as the backdrop for my rebuttal of their narrowly-framed objections. I challenge my critics’ apparent assumption that a particular kind of systematic review should be valorised over narrative and real-world evidence, since stories are crucial to both our scientific understanding and our moral imagination. I conclude by thanking my academic adversaries for the intellectual sparring match, but exhort them to remember our professional accountability to a society in crisis. It is time to lay straw men to rest and engage, scientifically and morally, with the dreadful tragedy that is unfolding across the world.

This Supporting information includes interactive plots, videos, and data captured while performing evaluation and validation experiments for our paper. 

The construct of wellbeing has been criticised as a neoliberal construction of western individualism that ignores wider systemic issues including increasing burden of chronic disease, widening inequality, concerns over environmental degradation and anthropogenic climate change. While these criticisms overlook recent developments, there remains a need for biopsychosocial models that extend theoretical grounding beyond individual wellbeing, incorporating overlapping contextual issues relating to community and environment. Our first GENIAL model \cite{Kemp_2017} provided a more expansive view of pathways to longevity in the context of individual health and wellbeing, emphasising bidirectional links to positive social ties and the impact of sociocultural factors. In this paper, we build on these ideas and propose GENIAL 2.0, focusing on intersecting individual-community-environmental contributions to health and wellbeing, and laying an evidence-based, theoretical framework on which future research and innovative therapeutic innovations could be based. We suggest that our transdisciplinary model of wellbeing - focusing on individual, community and environmental contributions to personal wellbeing - will help to move the research field forward. In reconceptualising wellbeing, GENIAL 2.0 bridges the gap between psychological science and population health health systems, and presents opportunities for enhancing the health and wellbeing of people living with chronic conditions. Implications for future generations including the very survival of our species are discussed.  

Floral plantings are promoted to foster ecological intensification of agriculture through provisioning of ecosystem services. However, a comprehensive assessment of the effectiveness of different floral plantings, their characteristics and consequences for crop yield across global regions is lacking. Here we quantified the impacts of flower strips and hedgerows on pest control and pollination services in adjacent crops using a global dataset of 529 sites. Flower strips, but not hedgerows, enhanced pest control services in adjacent fields by 16% on average. However, effects on crop pollination and yield were more variable. Our synthesis identifies several important drivers of variability in effectiveness of plantings: pollination services declined exponentially with distance from plantings, and perennial and older flower strips with higher flowering plant diversity enhanced pollination more effectively. These findings provide promising pathways to optimize floral plantings to more effectively contribute to ecosystem service delivery and ecological intensification of agriculture in the future.

Researchers' ability to accurately screen fossil and subfossil specimens for preservation of DNA and protein sequences remains limited. Thermal exposure and geologic age are usable proxies for sequence preservation on a broad scale but are of nominal use for specimens of similar depositional environments. Cell and tissue biomolecular histology is thus proposed as a novel proxy for determining sequence preservation potential of ancient specimens with improved accuracy. Biomolecular histology as a proxy is hypothesized to elucidate why fossils/subfossils of some depositional environments preserve sequences while others do not and to facilitate selection of ancient specimens for use in molecular studies.

IntroductionConsistent with World Health Organization (WHO) advice [1], UK Infection Protection Control guidance recommends that healthcare workers (HCWs) caring for patients with coronavirus disease 2019 (COVID-19) should use fluid resistant surgical masks type IIR (FRSMs) as respiratory protective equipment (RPE), unless aerosol generating procedures (AGPs) are being undertaken or are likely, when a filtering face piece 3 (FFP3) respirator should be used [2]. In a recent update, an FFP3 respirator is recommended if “an unacceptable risk of transmission remains following rigorous application of the hierarchy of control” [3]. Conversely, guidance from the Centers for Disease Control and Prevention (CDC) recommends that HCWs caring for patients with COVID-19 should use an N95 or higher level respirator [4]. WHO guidance suggests that a respirator, such as FFP3, may be used for HCWs in the absence of AGPs if availability or cost is not an issue [1].A recent systematic review undertaken for PHE concluded that: “patients with SARS-CoV-2 infection who are breathing, talking or coughing generate both respiratory droplets and aerosols, but FRSM (and where required, eye protection) are considered to provide adequate staff protection” [5]. Nevertheless, FFP3 respirators are more effective in preventing aerosol transmission than FRSMs, and observational data suggests that they may improve protection for HCWs [6]. It has therefore been suggested that respirators should be considered as a means of affording the best available protection [7], and some organisations have decided to provide FFP3 (or equivalent) respirators to HCWs caring for COVID-19 patients, despite a lack of mandate from local or national guidelines [8].Data from the HCW testing programme at Cambridge University Hospitals NHS Foundation Trust (CUHNFT) during the first wave of the UK severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic indicated a higher incidence of infection amongst HCWs caring for patients with COVID-19, compared with those who did not [9]. Subsequent studies have confirmed this observation [10, 11]. This disparity persisted at CUHNFT in December 2020, despite control measures consistent with PHE guidance and audits indicating good compliance. The CUHNFT infection control committee therefore implemented a change of RPE for staff on “red” (COVID-19) wards from FRSMs to FFP3 respirators. In this study, we analyse the incidence of SARS-CoV-2 infection in HCWs before and after this transition.

Background and Purpose: Fibroblast Growth Factor (FGF), VEGFR2, and CSF1R signalling pathways play a key role in the pathogenesis of multiple sclerosis (MS). Selective inhibition of FGFR by infigratinib in MOG35-55-induced EAE prevented severe first clinical episodes by 40%; inflammation and neurodegeneration were reduced, and remyelination was enhanced. Multi-kinase inhibition of FGFR1-3, CSF1R and VEGFR2 by AZD4547 may be more efficient in reducing inflammation, neurodegeneration and regeneration in the disease model. Experimental Approach: Female C57BL/6J mice were treated with AZD4547 (6.25 mg kg-1 or 12.5 mg kg-1) orally or placebo over 10 days either from time of EAE induction (prevention experiment) or onset of symptoms (suppression experiment). Effects on inflammation, neurodegeneration and remyelination were assessed at the peak of the disease (day 18/20 p.i.) and the chronic phase of EAE (day 41/42 p.i.). Key Results: In the prevention experiment, treatment with AZD4547 prevented severe first clinical episodes by 66.7 or 84.6% respectively. Mice treated with 12.5 mg kg-1 of AZD4547 hardly showed any symptoms in the chronic phase of EAE. In the suppression experiment, treatment with AZD4547 resulted in a long-lasting reduction of severe symptoms by 91 or 100%. Inflammation and demyelination were reduced, and axonal density, numbers of oligodendrocytes and their precursor cells, and remyelinated axons were increased in both experimental approaches. Conclusion and Implications: Multi-kinase inhibition by AZD4547 in a well-tolerated dose of 1 mg kg-1 in humans may be a promising approach to reduce inflammation and neurodegeneration, to slow down disease progression and support remyelination in patients.

In the invaded areas, it is believed that invasive species reduce their investment in defense due to the absence of natural enemies. This study explored the defense strategies of invasive plants through research on the invasive species. Field investigation indicated that invasive plants have a driving effect on herbivorous pests, and the frequency of leaf damages of native plant reaches a peak at 2–3 m distance from the invasive species. A feeding preference assay with two generalist herbivorous insects (native insect Spodoptera litura and invasive insect Spodoptera frugiperda) showed that the invasive plants have a stronger antifeedant effect on generalist herbivores than native plants. By analyzing the content of secondary metabolites in the leaves of three invasive plants (Sphagneticola trilobata, Mikania micrantha, Ipomoea cairica) and three native plants (Ipomoea nil, Paederia foetida, Polygonum chinense), the leaves of invasive plants had higher concentrations of substances associated with defenses, including total phenols, flavonoids, jasmonic acid, tannin, H2O2, and total antioxidant capacity, and lower soluble protein concentrations than the native plants. After leaf damage, compared to native plants, the leaves of invasive plants showed an overall increase in substances associated with defense, except for soluble sugar. These results suggest that invasive plants maintain active defense strategies in invaded areas, and these strategies may alter the distribution patterns of herbivorous insects in a manner that facilitates invasion.

Despite the rapid development and application of species distribution models (SDMs) to predict species responses to climate-driven ecosystem changes, we have a limited understanding of model predictive performance under novel environmental conditions. We aimed to address this gap using a simulation experiment to evaluate how novel ecosystem conditions and species movement influence SDM predictability. We leveraged observed sea surface temperature responses in the California Current and Northeast U.S. Shelf large marine ecosystems (LMEs) and prescribed species-response curves to simulate the distribution of a resident but mobile ectotherm, and a seasonally migrating ectotherm in each LME. For each LME and species archetype, we fitted boosted regression tree SDMs using data from 1985-2004 and then predicted the monthly probability of presence from 2005-2020 and calculated the environmental novelty of prediction month conditions. Generally, climate-driven ocean warming resulted in increasing environmental novelty over time, though patterns varied seasonally as warming caused novel conditions to increase over time in the summer and fall and decrease in the winter and spring as novel, cool conditions became more rare. Overall, predictive performance declined as novelty increased and occurred before prediction conditions became distinguishable from observation conditions. There were also unexpected increases in performance under novel environmental conditions when these novel conditions occurred at optimum species-response curve temperatures. These results highlight that environmental novelty may not always pose prediction challenges and will depend on where novel conditions map onto species-response curves. As SDM applications expand, there will be an ongoing need to maximize data quantity and quality to more fully characterize a species’ fundamental niche, explore environmental novelty relative to species-response curves, and continue to improve methods for quantifying and communicating model uncertainty. These efforts will open opportunities for model improvement and support stakeholders’ capacity to understand and integrate predictions into decision-making processes.

Diabetes, a prevalent chronic disease, poses significant challenges in healthcare management worldwide. This study presents a comprehensive analysis of a dataset comprising 1,000,000 instances with 12 features and a prediction variable that indicates the presence or absence of type 1,2 and 3 diabetic diagnoses in a different age group patient depending on weight factors, family history, and other genetic factors. This research deployed sophisticated data mining techniques and machine learning algorithms to help in understanding potential risk factors and predictors of the disease by examining the intricate interplay among demographic, clinical, and lifestyle variables. This dissertation also investigates the deep analysis of type 1, type 2, and type 3 medicines that are being used for different age groups of patients (children, young, and older). This study represents a significant contribution to diabetes research, offering valuable insights into the complex dynamics of the disease. The significance of data mining tools and prediction algorithms, the research endeavors to advance our understanding of diabetes etiology, risk assessment, and management strategies, ultimately contributing to improved patient outcomes and healthcare decision-making.

Objective: The aim of our study is to examine the relationship between adenomyosis and chronic endometritis and to discuss its possible effects on pathogenesis. Design: Prospective analysis of previous patients’ pathology specimens Setting: A tertiary university hospital’s department of obstetrics and gynecology. Patients: Patients who underwent hysterectomy at were divided into two groups according to the presence or absence of adenomyosis. A propensity score matching analysis was performed to minimize selection bias in patient groups. A total of 146, 73 patients in each group, were included in the study. Methods: The previous specimens of the patients were re-evaluated with the CD38 immunohistochemistry staining method. A positive diagnosis of CE was made in the presence of plasma cells. In particular, basal endometrial thickness was measured in endo-myometrial transition zones. Main outcome measures and Results: The adenomyosis group was significantly younger than the group without adenomyosis (47.14 ± 4.24 vs. 50.36 ± 7.02, p = 0.012). 17 (11.6%) patients in the adenomyosis group were diagnosed with chronic endometritis, while 7 (4.8%) patients in the control group were diagnosed with chronic endometritis, and a statistically significant difference was found (p<0.05). Basal endometrium could be measured in a total of 112 (76.7%) patients, while basal endometrial loss was observed in 34 (23.3%) patients. Chronic endometritis was found in 16 (47%) of the patients with basal endometrial loss. The baseline endometrial thickness of 112 (76.7%) of the patients could be measured, but only 8 (7.1%) of them had chronic endometritis. There was a statistically significant difference between the groups (p<0.001). In multivariate analysis, there was a statistically significant relationship between basal endometrial loss and CE. Conclusion(s): A significant relationship was observed between adenomyosis and chronic endometritis.

Snowmelt is a critical water resource in the Sierra Nevada impacting populations in California and Nevada. In this region, forest managers use treatments like selective thinning to encourage resilient ecosystems but rarely prioritize snowpack retention due to a lack of simple recommendations and the importance of other management objectives like wildfire mitigation and wildlife habitat. We use light detection and ranging (lidar) data collected over multiple snow accumulation seasons in the Sagehen Creek Basin, central Sierra Nevada in California, USA, to investigate how snowpack accumulation and ablation are affected by forest structure metrics at coarse, stand-scales (e.g., fraction of vegetation, or fVEG) and fine, tree-scales (e.g., a modified leaf area index, and the ratio of gap-width to average tree height). Using a newly developed lidar point cloud filtering method and an “open-area reference” approach, we show that for each 10% decrease in fVEG there is a ~30% increase in snow accumulation and a ~15% decrease in ablation rate at the Sagehen field site. To understand variability around these relationships, we use a random forest analysis to demonstrate that areas with fVEG greater than ~30% have the greatest potential increased accumulation response after forest removal. This spatial information allows us to assess the utility of completed and planned forest restoration strategies in targeting areas with the highest potential snowpack response. Our new lidar processing methods and reference-based approach are easily transferrable to other areas where they could improve decision support and increase water availability from landscape-scale forest restoration projects.

Mangrove and seaweed ecosystems, as integral components of blue carbon habitats, play pivotal roles in global carbon sequestration and coastal protection, showcasing unique environmental dynamics and biological diversity. This study explores seaweed and mangrove-associated bacterial communities and their functional dynamics in Goa coastal habitats, highlighting their critical ecological roles within blue carbon habitats. Physicochemical analysis revealed contrasting environmental conditions, with the seaweed ecosystem experiencing stable marine influences and the mangrove ecosystem subject to dynamic terrestrial-aquatic interactions. Elevated levels of pathogenic bacteria in both ecosystems indicate significant pollution from anthropogenic activities. Advanced metagenomic techniques, including Illumina’s 16S V3-V4 amplicon sequencing, were employed to assess bacterial diversity. The seaweed ecosystems were predominated by Proteobacteria, Cyanobacteria, and Actinobacteria, crucial for nutrient cycling and organic matter decomposition. In contrast, mangrove ecosystems displayed a more complex microbiota, represented by Firmicutes, adapted to anaerobic conditions. Core microbiome analysis revealed the prevalence of the pathogen Pleurocapsa in seaweeds, suggesting ecosystem health decline, while mangrove microbiomes showed the dominance of genera such as Bacillus and Clostridium, which are key in processing organic material under low-oxygen conditions. Notably, Clostridium levels indicated faecal contamination, underscoring the impact of external pollution. Functional pathway analysis conducted with PICRUSt2 analysis elucidated the metabolic specializations of the microbiomes. Seaweed-associated microbiomes excelled in carbohydrate metabolism, cellular growth and death and environmental information processing, whereas mangrove microbiomes showed advanced capabilities in carbohydrate metabolism, xenobiotics biodegradation and complex organic compound metabolism such as terpenoids and polyketides, reflecting complex microbial dynamics and pollution in mangroves. The findings emphasize the urgent need for effective conservation strategies to protect these vital ecosystems against the rising threats of anthropogenic pressures pollution, and climate change. An enhanced understanding of microbial dynamics and functional capabilities is essential for implementing informed management practices, ensuring the conservation and restoration of these critical blue carbon ecosystems.

Gold recycling from secondary sources provides an economically viable and sustainable approach to meet the increasing global demand for this precious metal. However, gold resources are inherently scarce. To address this issue, the present study presents an innovative solution: sulfhydryl-functionalized magnetic metal-organic framework nanorobots (MNR-MOF-DMSA). These nanorobots are designed for swift, efficient, and selective capture of Au(III) trace amounts from complex aqueous mixtures. MNR-MOF-DMSA showed an ultra-high adsorption capacity, better selectivity, and reusability with long-term stability, as it can selectively extract over 94% of Au(III) from complex e-waste leachate, and the adsorption capacity can reach 1716 mg g-1 (at pH 5 in 3 hours) in harsh acidic condition followed Langmuir model. In addition, after conducting a detailed mechanistic analysis, it was discovered that the selective adsorption behaviors observed were due to the combined effect of several factors, including the reduction of sulfhydryl groups, the coordination interactions between amide groups and Au(III) ions, as well as the electrostatic interactions between protonated amino and AuCl4- ions. It is also worth mentioning that the better catalytic properties of the developed hybrid MOF (MNR-MOF-DMSA-Au) were due to the reduction of Au(III) to Au(0). This study proposes new ways to recover and reuse gold e-waste for a sustainable future, as well as environmental protection and remediation.

Background: Natural Killer (NK) cells play a critical role in host defense. Studying human NK immunobiology is mainly focused on using in vitro assays with limited NK cells from peripheral blood. It is challenging to study human NK cell biology in vivo due to potential ethical issues in human study and the lack of suitable animal models. Developing a suitable animal model to study human NK cell biology in vivo is critical to support NK-based clinical immunotherapy. Results: Here, we develop a novel method to study human NK cells in vivo by using hu-BLT (humanized bone marrow-liver-thymus) mice that constitutively express human IL-15 (henceforth, hu-BLT-IL15). We also compare human NK cells between hu-BLT-IL15 and hu-BLT mice without IL-15 expression by a newly developed approach for the rapid propagating of primary human NK cells from various sources (including peripheral blood, spleen, and bone marrow). NK cells from hu-BLT-IL15 show superior number, purity, and cytotoxicity (including natural cytotoxicity and antibody-dependent cellular cytotoxicity [ADCC]), compared with NK cells from hu-BLT. Unexpectedly, we also identify a significantly increased percentage of NK-like T cells (CD3+ CD16+ CD56+) from hu-BLT-IL15, indicating that IL-15 signaling enhances both NK and NKT cell development. Conclusions: A better understanding of the immunobiology of the NK-like T cells in the hu-BLT-IL15 mouse model may provide critical information for determining the clinical value of these cells in predicting disease progression. Thus, we propose that the hu-BLT-IL15 mouse model in combination with the 721.221-mIL21 feeder cell expansion system can serve as a superior model to study human NK and NK-like T cells in comparison with hu-BLT.

Issues surrounding gender equality are – and should be - front and centre in the water resources community, and other STEM fields. Very necessarily, the focus tends to remain on recruitment and inclusivity offering support for students and early career academics. The leaky pipeline concept used to describe the incremental loss of women from STEM fields with career duration results in a disproportionate loss of women, creating a parallel problem where highly qualified, top tier academics are disproportionately lost from the system after significant financial and personnel investment by institutions is made. Ultimately, the leaky pipeline undermines the extensive investment of the hydrology and other STEM communities in equity, diversity, inclusion, and accessibility (EDIA) recruitment and retention programs by cutting short career ambitions and the trajectories of diverse top performing individuals, resulting in no net benefit of EDIA policy investments. Addressing this critical gender gap requires the attention and support of the hydrology community of practice with specific focus on generating opportunities for advancement, confronting systemic and structural biases, and improving education around allyship. Institutions and professional organizations need to consciously grow diversity in leadership and recognize and outwardly manage the perception of academic excellence around slow research and education that attracts increased diversity. Supporting allyship, reducing competitiveness among community members, and reinforcing collaboration will not only attract, but retain, a higher proportion of diversity in the hydrology community, academia, and STEM professions in general. It is time for the water resources (and other STEM) communities to demand broader accountability and recognition of the barriers to women, implement and reward more diverse definitions of research excellence, and offer allyship training to the community of practice at large.

Rationale: Mass spectrometry (MS) is introduced to high school students in the UK in many pre-university course syllabi. As such, we have identified the use of MS as a key technique that should be taught practically to undergraduates from the outset of their studies. This mini‑review describes how we introduce and develop students’ use of MS throughout our three‑year undergraduate spiral curriculum practical program, using atmospheric pressure chemical ionisation MS (APCI/MS). Methods: We have used an Advion Expression L spectrometer, fitted with an atmospheric solids analysis probe or a Plate Express TLC sampler for sample introduction. Results: We have successfully demonstrated the use of APCI-MS in a range of practicals and experiments covering organic and organometallic chemistries, with large cohorts of students gaining hands‑on instrumental experience in authentic research settings. Conclusions: APCI-MS has proven to be an easy-to-use and valuable addition to our undergraduate practical course. The robustness of the spectrometer enables routine use by large cohorts of students with minimal supervision, and routine maintenance can be carried out by non-specialist technicians. Students can readily process and interpret results for a series of routine analyses, as well as demonstrate uses in problem-solving exercises.

Aim: A population-based pharmacokinetic (PK) modeling approach (PopPK) was used to investigate the impact of Roux-en-Y gastric bypass (RYGB) on the PK of (R)- and (S)-carvedilol. We aimed to optimize carvedilol dosing for these patients utilizing a pharmacokinetic/pharmacodynamic (PK/PD) link model. Methods: PopPK models were developed utilizing data from 52 subjects, including non-obese, obese, and post-RYGB patients who received rac-carvedilol orally. Covariate analysis included anthropometric and laboratory data, history of RYGB surgery, CYP2D6 and CYP3A4 in vivo activity, and relative intestinal abundance of major drug-metabolizing enzymes and transporters. A direct effect inhibitory Emax pharmacodynamic model was linked to the PK model of (S)-carvedilol to simulate the changes in exercise-induced heart rate. Results: A two-compartmental model with linear elimination and parallel first-order absorptions best described (S)-carvedilol PK. RYGB led to a twofold reduction in relative oral bioavailability compared to non-operated subjects, along with delayed absorption of both enantiomers. The intestinal ABCC2 mRNA expression increases the time to reach the maximum plasma concentration. The reduced exposure (AUC) of (S)-carvedilol post-RYGB corresponded to a 33% decrease in the predicted area under the effect curve (AUEC) for the 24-hour beta-blocker response. Simulation results suggested that a 50 mg daily dose in post-RYGB patients achieved comparable AUC and AUEC to 25 mg dose in non-operated subjects. Conclusion: Integrated PK/PD modeling indicated that standard dosage regimens for non-operated subjects do not provide equivalent beta-blocking activity in RYGB patients. This study highlights the importance of personalized dosing strategies to attain desired therapeutic outcomes in this patient cohort.