Displaying publications 141 - 160 of 166 in total

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  1. Luo Y, Chang Y, Zhao Z, Xia J, Xu C, Bee YM, et al.
    Lancet Reg Health West Pac, 2023 Jun;35:100746.
    PMID: 37424694 DOI: 10.1016/j.lanwpc.2023.100746
    BACKGROUND: Technological advances make it possible to use device-supported, automated algorithms to aid basal insulin (BI) dosing titration in patients with type 2 diabetes.

    METHODS: A systematic review and meta-analysis of randomized controlled trials were performed to evaluate the efficacy, safety, and quality of life of automated BI titration versus conventional care. The literature in Medline, Embase, Web of Science, and the Cochrane databases from January 2000 to February 2022 were searched to identify relevant studies. Risk ratios (RRs), mean differences (MDs), and their 95% confidence intervals (CIs) were calculated using random-effect meta-analyses. Certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.

    FINDINGS: Six of the 7 eligible studies (889 patients) were included in meta-analyses. Low- to moderate-quality evidence suggests that patients who use automated BI titration versus conventional care may have a higher probability of reaching a target of HbA1c <7.0% (RR, 1.82 [95% CI, 1.16-2.86]); and a lower level of HbA1c (MD, -0.25% [95% CI, -0.43 to -0.06%]). No statistically significant differences were detected between the two groups in fasting glucose results, incidences of hypoglycemia, severe or nocturnal hypoglycemia, and quality of life, with low to very low certainty for all the evidence.

    INTERPRETATION: Automated BI titration is associated with small benefits in reducing HbA1c without increasing the risk of hypoglycemia. Future studies should explore patient attitudes and the cost-effectiveness of this approach.

    FUNDING: Sponsored by the Chinese Geriatric Endocrine Society.

  2. Gu C, Liang Y, Li J, Shao H, Jiang Y, Zhou X, et al.
    iScience, 2021 Dec 17;24(12):103439.
    PMID: 34988389 DOI: 10.1016/j.isci.2021.103439
    The highest plateau on Earth, Qinghai-Tibet Plateau, contains thousands of lakes with broad salinity and diverse and unique microbial communities. However, little is known about their co-occurring viruses. Herein, we identify 4,560 viral Operational Taxonomic Units (vOTUs) from six viromes of three saline lakes on Qinghai-Tibet Plateau, with less than 1% that could be classified. Most of the predicted vOTUs were associated with the dominant bacterial and archaeal phyla. Virus-encoded auxiliary metabolic genes suggest that viruses influence microbial metabolisms of carbon, nitrogen, sulfur, and lipid; the antibiotic resistance mediation; and their salinity adaption. The six viromes clustered together with the ice core viromes and bathypelagic ocean viromes and might represent a new viral habitat. This study has revealed the unique characteristics and potential ecological roles of DNA viromes in the lakes of the highest plateau and established a foundation for the recognition of the viral roles in plateau lake ecosystems.
  3. Lu M, Yao Y, Liu H, Zhang X, Li X, Liu Y, et al.
    JCI Insight, 2023 Dec 08;8(23).
    PMID: 37917215 DOI: 10.1172/jci.insight.175461
    Nipah virus (NiV), a bat-borne paramyxovirus, results in neurological and respiratory diseases with high mortality in humans and animals. Developing vaccines is crucial for fighting these diseases. Previously, only a few studies focused on the fusion (F) protein alone as the immunogen. Numerous NiV strains have been identified, including 2 representative strains from Malaysia (NiV-M) and Bangladesh (NiV-B), which differ significantly from each other. In this study, an F protein sequence with the potential to prevent different NiV strain infections was designed by bioinformatics analysis after an in-depth study of NiV sequences in GenBank. Then, a chimpanzee adenoviral vector vaccine and a DNA vaccine were developed. High levels of immune responses were detected after AdC68-F, pVAX1-F, and a prime-boost strategy (pVAX1-F/AdC68-F) in mice. After high titers of humoral responses were induced, the hamsters were challenged by the lethal NiV-M and NiV-B strains separately. The vaccinated hamsters did not show any clinical signs and survived 21 days after infection with either strain of NiV, and no virus was detected in different tissues. These results indicate that the vaccines provided complete protection against representative strains of NiV infection and have the potential to be developed as a broad-spectrum vaccine for human use.
  4. Xiao K, Zhai J, Feng Y, Zhou N, Zhang X, Zou JJ, et al.
    Nature, 2020 07;583(7815):286-289.
    PMID: 32380510 DOI: 10.1038/s41586-020-2313-x
    The current outbreak of coronavirus disease-2019 (COVID-19) poses unprecedented challenges to global health1. The new coronavirus responsible for this outbreak-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-shares high sequence identity to SARS-CoV and a bat coronavirus, RaTG132. Although bats may be the reservoir host for a variety of coronaviruses3,4, it remains unknown whether SARS-CoV-2 has additional host species. Here we show that a coronavirus, which we name pangolin-CoV, isolated from a Malayan pangolin has 100%, 98.6%, 97.8% and 90.7% amino acid identity with SARS-CoV-2 in the E, M, N and S proteins, respectively. In particular, the receptor-binding domain of the S protein of pangolin-CoV is almost identical to that of SARS-CoV-2, with one difference in a noncritical amino acid. Our comparative genomic analysis suggests that SARS-CoV-2 may have originated in the recombination of a virus similar to pangolin-CoV with one similar to RaTG13. Pangolin-CoV was detected in 17 out of the 25 Malayan pangolins that we analysed. Infected pangolins showed clinical signs and histological changes, and circulating antibodies against pangolin-CoV reacted with the S protein of SARS-CoV-2. The isolation of a coronavirus from pangolins that is closely related to SARS-CoV-2 suggests that these animals have the potential to act as an intermediate host of SARS-CoV-2. This newly identified coronavirus from pangolins-the most-trafficked mammal in the illegal wildlife trade-could represent a future threat to public health if wildlife trade is not effectively controlled.
  5. Sreekar R, Katabuchi M, Nakamura A, Corlett RT, Slik JWF, Fletcher C, et al.
    R Soc Open Sci, 2018 Sep;5(9):181168.
    PMID: 30839691 DOI: 10.1098/rsos.181168
    The relationship between β-diversity and latitude still remains to be a core question in ecology because of the lack of consensus between studies. One hypothesis for the lack of consensus between studies is that spatial scale changes the relationship between latitude and β-diversity. Here, we test this hypothesis using tree data from 15 large-scale forest plots (greater than or equal to 15 ha, diameter at breast height ≥ 1 cm) across a latitudinal gradient (3-30o) in the Asia-Pacific region. We found that the observed β-diversity decreased with increasing latitude when sampling local tree communities at small spatial scale (grain size ≤0.1 ha), but the observed β-diversity did not change with latitude when sampling at large spatial scales (greater than or equal to 0.25 ha). Differences in latitudinal β-diversity gradients across spatial scales were caused by pooled species richness (γ-diversity), which influenced observed β-diversity values at small spatial scales, but not at large spatial scales. Therefore, spatial scale changes the relationship between β-diversity, γ-diversity and latitude, and improving sample representativeness avoids the γ-dependence of β-diversity.
  6. Miller V, Jenkins DA, Dehghan M, Srichaikul K, Rangarajan S, Mente A, et al.
    Lancet Diabetes Endocrinol, 2024 May;12(5):330-338.
    PMID: 38588684 DOI: 10.1016/S2213-8587(24)00069-X
    BACKGROUND: The association between the glycaemic index and the glycaemic load with type 2 diabetes incidence is controversial. We aimed to evaluate this association in an international cohort with diverse glycaemic index and glycaemic load diets.

    METHODS: The PURE study is a prospective cohort study of 127 594 adults aged 35-70 years from 20 high-income, middle-income, and low-income countries. Diet was assessed at baseline using country-specific validated food frequency questionnaires. The glycaemic index and the glycaemic load were estimated on the basis of the intake of seven categories of carbohydrate-containing foods. Participants were categorised into quintiles of glycaemic index and glycaemic load. The primary outcome was incident type 2 diabetes. Multivariable Cox Frailty models with random intercepts for study centre were used to calculate hazard ratios (HRs).

    FINDINGS: During a median follow-up of 11·8 years (IQR 9·0-13·0), 7326 (5·7%) incident cases of type 2 diabetes occurred. In multivariable adjusted analyses, a diet with a higher glycaemic index was significantly associated with a higher risk of diabetes (quintile 5 vs quintile 1; HR 1·15 [95% CI 1·03-1·29]). Participants in the highest quintile of the glycaemic load had a higher risk of incident type 2 diabetes compared with those in the lowest quintile (HR 1·21, 95% CI 1·06-1·37). The glycaemic index was more strongly associated with diabetes among individuals with a higher BMI (quintile 5 vs quintile 1; HR 1·23 [95% CI 1·08-1·41]) than those with a lower BMI (quintile 5 vs quintile 1; 1·10 [0·87-1·39]; p interaction=0·030).

    INTERPRETATION: Diets with a high glycaemic index and a high glycaemic load were associated with a higher risk of incident type 2 diabetes in a multinational cohort spanning five continents. Our findings suggest that consuming low glycaemic index and low glycaemic load diets might prevent the development of type 2 diabetes.

    FUNDING: Full funding sources are listed at the end of the Article.

  7. Joundi RA, Hu B, Rangarajan S, Leong DP, Islam S, Smith EE, et al.
    Lancet, 2024 Jul 25.
    PMID: 39068950 DOI: 10.1016/S0140-6736(24)01050-X
    BACKGROUND: The focus of most epidemiological studies has been mortality or clinical events, with less information on activity limitations related to basic daily functions and their consequences. Standardised data from multiple countries at different economic levels in different regions of the world on activity limitations and their associations with clinical outcomes are sparse. We aimed to quantify the prevalence of activity limitations and use of assistive devices and the association of limitations with adverse outcomes in 25 countries grouped by different economic levels.

    METHODS: In this analysis, we obtained data from individuals in 25 high-income, middle-income, and low-income countries from the Prospective Urban Rural Epidemiological (PURE) study (175 660 participants). In the PURE study, individuals aged 35-70 years who intended to continue living in their current home for a further 4 years were invited to complete a questionnaire on activity limitations. Participant follow-up was planned once every 3 years either by telephone or in person. The activity limitation screen consisted of questions on self-reported difficulty with walking, grasping, bending, seeing close, seeing far, speaking, hearing, and use of assistive devices (gait, vision, and hearing aids). We estimated crude prevalence of self-reported activity limitations and use of assistive devices, and prevalence standardised by age and sex. We used logistic regression to additionally adjust prevalence for education and socioeconomic factors and to estimate the probability of activity limitations and assistive devices by age, sex, and country income. We used Cox frailty models to evaluate the association between each activity limitation with mortality and clinical events (cardiovascular disease, heart failure, pneumonia, falls, and cancer). The PURE study is registered with ClinicalTrials.gov, NCT03225586.

    FINDINGS: Between Jan 12, 2001, and May 6, 2019, 175 584 individuals completed at least one question on the activity limitation questionnaire (mean age 50·6 years [SD 9·8]; 103 625 [59%] women). Of the individuals who completed all questions, mean follow-up was 10·7 years (SD 4·4). The most common self-reported activity limitations were difficulty with bending (23 921 [13·6%] of 175 515 participants), seeing close (22 532 [13·4%] of 167 801 participants), and walking (22 805 [13·0%] of 175 554 participants); prevalence of limitations was higher with older age and among women. The prevalence of all limitations standardised by age and sex, with the exception of hearing, was highest in low-income countries and middle-income countries, and this remained consistent after adjustment for socioeconomic factors. The use of gait, visual, and hearing aids was lowest in low-income countries and middle-income countries, particularly among women. The prevalence of seeing close limitation was four times higher (6257 [16·5%] of 37 926 participants vs 717 [4·0%] of 18 039 participants) and the prevalence of seeing far limitation was five times higher (4003 [10·6%] of 37 923 participants vs 391 [2·2%] of 18 038 participants) in low-income countries than in high-income countries, but the prevalence of glasses use in low-income countries was half that in high-income countries. Walking limitation was most strongly associated with mortality (adjusted hazard ratio 1·32 [95% CI 1·25-1·39]) and most consistently associated with other clinical events, with other notable associations observed between seeing far limitation and mortality, grasping limitation and cardiovascular disease, bending limitation and falls, and between speaking limitation and stroke.

    INTERPRETATION: The global prevalence of activity limitations is substantially higher in women than men and in low-income countries and middle-income countries compared with high-income countries, coupled with a much lower use of gait, visual, and hearing aids. Strategies are needed to prevent and mitigate activity limitations globally, with particular emphasis on low-income countries and women.

    FUNDING: Funding sources are listed at the end of the Article.

  8. Swank Z, Borberg E, Chen Y, Senussi Y, Chalise S, Manickas-Hill Z, et al.
    Clin Microbiol Infect, 2024 Dec;30(12):1599-1605.
    PMID: 39389851 DOI: 10.1016/j.cmi.2024.09.001
    OBJECTIVES: To determine the proportion of individuals with detectable antigen in plasma or serum after SARS-CoV-2 infection and the association of antigen detection with postacute sequelae of COVID-19 (PASC) symptoms.

    METHODS: Plasma and serum samples were collected from adults participating in four independent studies at different time points, ranging from several days up to 14 months post-SARS-CoV-2 infection. The primary outcome measure was to quantify SARS-CoV-2 antigens, including the S1 subunit of spike, full-length spike, and nucleocapsid, in participant samples. The presence of 34 commonly reported PASC symptoms during the postacute period was determined from participant surveys or chart reviews of electronic health records.

    RESULTS: Of the 1569 samples analysed from 706 individuals infected with SARS-CoV-2, 21% (95% CI, 18-24%) were positive for either S1, spike, or nucleocapsid. Spike was predominantly detected, and the highest proportion of samples was spike positive (20%; 95% CI, 18-22%) between 4 and 7 months postinfection. In total, 578 participants (82%) reported at least one of the 34 PASC symptoms included in our analysis ≥1 month postinfection. Cardiopulmonary, musculoskeletal, and neurologic symptoms had the highest reported prevalence in over half of all participants, and among those participants, 43% (95% CI, 40-45%) on average were antigen-positive. Among the participants who reported no ongoing symptoms (128, 18%), antigen was detected in 28 participants (21%). The presence of antigen was associated with the presence of one or more PASC symptoms, adjusting for sex, age, time postinfection, and cohort (OR, 1.8; 95% CI, 1.4-2.2).

    DISCUSSION: The findings of this multicohort study indicate that SARS-CoV-2 antigens can be detected in the blood of a substantial proportion of individuals up to 14 months after infection. While approximately one in five asymptomatic individuals was antigen-positive, roughly half of all individuals reporting ongoing cardiopulmonary, musculoskeletal, and neurologic symptoms were antigen-positive.

  9. Tang BH, Guan Z, Allegaert K, Wu YE, Manolis E, Leroux S, et al.
    Clin Pharmacokinet, 2021 11;60(11):1435-1448.
    PMID: 34041714 DOI: 10.1007/s40262-021-01033-x
    BACKGROUND: Population pharmacokinetic evaluations have been widely used in neonatal pharmacokinetic studies, while machine learning has become a popular approach to solving complex problems in the current era of big data.

    OBJECTIVE: The aim of this proof-of-concept study was to evaluate whether combining population pharmacokinetic and machine learning approaches could provide a more accurate prediction of the clearance of renally eliminated drugs in individual neonates.

    METHODS: Six drugs that are primarily eliminated by the kidneys were selected (vancomycin, latamoxef, cefepime, azlocillin, ceftazidime, and amoxicillin) as 'proof of concept' compounds. Individual estimates of clearance obtained from population pharmacokinetic models were used as reference clearances, and diverse machine learning methods and nested cross-validation were adopted and evaluated against these reference clearances. The predictive performance of these combined methods was compared with the performance of two other predictive methods: a covariate-based maturation model and a postmenstrual age and body weight scaling model. Relative error was used to evaluate the different methods.

    RESULTS: The extra tree regressor was selected as the best-fit machine learning method. Using the combined method, more than 95% of predictions for all six drugs had a relative error of < 50% and the mean relative error was reduced by an average of 44.3% and 71.3% compared with the other two predictive methods.

    CONCLUSION: A combined population pharmacokinetic and machine learning approach provided improved predictions of individual clearances of renally cleared drugs in neonates. For a new patient treated in clinical practice, individual clearance can be predicted a priori using our model code combined with demographic data.

  10. Wills C, Wang B, Fang S, Wang Y, Jin Y, Lutz J, et al.
    PLoS Comput Biol, 2021 Apr;17(4):e1008853.
    PMID: 33914731 DOI: 10.1371/journal.pcbi.1008853
    When Darwin visited the Galapagos archipelago, he observed that, in spite of the islands' physical similarity, members of species that had dispersed to them recently were beginning to diverge from each other. He postulated that these divergences must have resulted primarily from interactions with sets of other species that had also diverged across these otherwise similar islands. By extrapolation, if Darwin is correct, such complex interactions must be driving species divergences across all ecosystems. However, many current general ecological theories that predict observed distributions of species in ecosystems do not take the details of between-species interactions into account. Here we quantify, in sixteen forest diversity plots (FDPs) worldwide, highly significant negative density-dependent (NDD) components of both conspecific and heterospecific between-tree interactions that affect the trees' distributions, growth, recruitment, and mortality. These interactions decline smoothly in significance with increasing physical distance between trees. They also tend to decline in significance with increasing phylogenetic distance between the trees, but each FDP exhibits its own unique pattern of exceptions to this overall decline. Unique patterns of between-species interactions in ecosystems, of the general type that Darwin postulated, are likely to have contributed to the exceptions. We test the power of our null-model method by using a deliberately modified data set, and show that the method easily identifies the modifications. We examine how some of the exceptions, at the Wind River (USA) FDP, reveal new details of a known allelopathic effect of one of the Wind River gymnosperm species. Finally, we explore how similar analyses can be used to investigate details of many types of interactions in these complex ecosystems, and can provide clues to the evolution of these interactions.
  11. Mi C, Ma L, Yang M, Li X, Meiri S, Roll U, et al.
    Nat Commun, 2023 Mar 13;14(1):1389.
    PMID: 36914628 DOI: 10.1038/s41467-023-36987-y
    Protected Areas (PAs) are the cornerstone of biodiversity conservation. Here, we collated distributional data for >14,000 (~70% of) species of amphibians and reptiles (herpetofauna) to perform a global assessment of the conservation effectiveness of PAs using species distribution models. Our analyses reveal that >91% of herpetofauna species are currently distributed in PAs, and that this proportion will remain unaltered under future climate change. Indeed, loss of species' distributional ranges will be lower inside PAs than outside them. Therefore, the proportion of effectively protected species is predicted to increase. However, over 7.8% of species currently occur outside PAs, and large spatial conservation gaps remain, mainly across tropical and subtropical moist broadleaf forests, and across non-high-income countries. We also predict that more than 300 amphibian and 500 reptile species may go extinct under climate change over the course of the ongoing century. Our study highlights the importance of PAs in providing herpetofauna with refuge from climate change, and suggests ways to optimize PAs to better conserve biodiversity worldwide.
  12. Chen C, Granados A, Brodie JF, Kays R, Davies TJ, Liu R, et al.
    Conserv Biol, 2023 Nov 08.
    PMID: 37937455 DOI: 10.1111/cobi.14221
    Reliable maps of species distributions are fundamental for biodiversity research and conservation. The International Union for Conservation of Nature (IUCN) range maps are widely recognized as authoritative representations of species' geographic limits, yet they might not always align with actual occurrence data. In recent area of habitat (AOH) maps, areas that are not habitat have been removed from IUCN ranges to reduce commission errors, but their concordance with actual species occurrence also remains untested. We tested concordance between occurrences recorded in camera trap surveys and predicted occurrences from the IUCN and AOH maps for 510 medium- to large-bodied mammalian species in 80 camera trap sampling areas. Across all areas, cameras detected only 39% of species expected to occur based on IUCN ranges and AOH maps; 85% of the IUCN only mismatches occurred within 200 km of range edges. Only 4% of species occurrences were detected by cameras outside IUCN ranges. The probability of mismatches between cameras and the IUCN range was significantly higher for smaller-bodied mammals and habitat specialists in the Neotropics and Indomalaya and in areas with shorter canopy forests. Our findings suggest that range and AOH maps rarely underrepresent areas where species occur, but they may more often overrepresent ranges by including areas where a species may be absent, particularly at range edges. We suggest that combining range maps with data from ground-based biodiversity sensors, such as camera traps, provides a richer knowledge base for conservation mapping and planning.
  13. Porwal P, Pachade S, Kokare M, Deshmukh G, Son J, Bae W, et al.
    Med Image Anal, 2020 01;59:101561.
    PMID: 31671320 DOI: 10.1016/j.media.2019.101561
    Diabetic Retinopathy (DR) is the most common cause of avoidable vision loss, predominantly affecting the working-age population across the globe. Screening for DR, coupled with timely consultation and treatment, is a globally trusted policy to avoid vision loss. However, implementation of DR screening programs is challenging due to the scarcity of medical professionals able to screen a growing global diabetic population at risk for DR. Computer-aided disease diagnosis in retinal image analysis could provide a sustainable approach for such large-scale screening effort. The recent scientific advances in computing capacity and machine learning approaches provide an avenue for biomedical scientists to reach this goal. Aiming to advance the state-of-the-art in automatic DR diagnosis, a grand challenge on "Diabetic Retinopathy - Segmentation and Grading" was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI - 2018). In this paper, we report the set-up and results of this challenge that is primarily based on Indian Diabetic Retinopathy Image Dataset (IDRiD). There were three principal sub-challenges: lesion segmentation, disease severity grading, and localization of retinal landmarks and segmentation. These multiple tasks in this challenge allow to test the generalizability of algorithms, and this is what makes it different from existing ones. It received a positive response from the scientific community with 148 submissions from 495 registrations effectively entered in this challenge. This paper outlines the challenge, its organization, the dataset used, evaluation methods and results of top-performing participating solutions. The top-performing approaches utilized a blend of clinical information, data augmentation, and an ensemble of models. These findings have the potential to enable new developments in retinal image analysis and image-based DR screening in particular.
  14. Rohner K, Marlais M, Ahn YH, Ali A, Alsharief A, Novak AB, et al.
    Nephrol Dial Transplant, 2024 Jul 31;39(8):1299-1309.
    PMID: 38211969 DOI: 10.1093/ndt/gfae009
    BACKGROUND: Immunoglobulin A vasculitis with nephritis (IgAVN) is the most common vasculitis in children. Due to a lack of evidence, treatment recommendations are based on expert opinion, resulting in variation. The aim of this study was to describe the clinical presentation, treatment and outcome of an extremely large cohort of children with biopsy-proven IgAVN in order to identify prognostic risk factors and signals of treatment efficacy.

    METHODS: Retrospective data were collected on 1148 children with biopsy-proven IgAVN between 2005 and 2019 from 41 international paediatric nephrology centres across 25 countries and analysed using multivariate analysis. The primary outcome was estimated glomerular filtration rate (eGFR) and persistent proteinuria at last follow-up.

    RESULTS: The median follow-up was 3.7 years (interquartile range 2-6.2). At last follow-up, 29% of patients had an eGFR <90 mL/min/1.73 m2, 36% had proteinuria and 3% had chronic kidney disease stage 4-5. Older age, lower eGFR at onset, hypertension and histological features of tubular atrophy and segmental sclerosis were predictors of poor outcome. There was no evidence to support any specific second-line immunosuppressive regimen being superior to others, even when further analysing subgroups of children with reduced kidney function, nephrotic syndrome or hypoalbuminemia at onset. Delayed start of immunosuppressive treatment was associated with a lower eGFR at last follow-up.

    CONCLUSION: In this large retrospective cohort, key features associated with disease outcome are highlighted. Importantly, there was no evidence to support that any specific immunosuppressive treatments were superior to others. Further discovery science and well-conducted clinical trials are needed to define accurate treatment and improve outcomes of IgAVN.

  15. Chu C, Lutz JA, Král K, Vrška T, Yin X, Myers JA, et al.
    Ecol Lett, 2019 Feb;22(2):245-255.
    PMID: 30548766 DOI: 10.1111/ele.13175
    Climate is widely recognised as an important determinant of the latitudinal diversity gradient. However, most existing studies make no distinction between direct and indirect effects of climate, which substantially hinders our understanding of how climate constrains biodiversity globally. Using data from 35 large forest plots, we test hypothesised relationships amongst climate, topography, forest structural attributes (stem abundance, tree size variation and stand basal area) and tree species richness to better understand drivers of latitudinal tree diversity patterns. Climate influences tree richness both directly, with more species in warm, moist, aseasonal climates and indirectly, with more species at higher stem abundance. These results imply direct limitation of species diversity by climatic stress and more rapid (co-)evolution and narrower niche partitioning in warm climates. They also support the idea that increased numbers of individuals associated with high primary productivity are partitioned to support a greater number of species.
  16. Cui Y, Hada K, Kawashima T, Kino M, Lin W, Mizuno Y, et al.
    Nature, 2023 Sep;621(7980):711-715.
    PMID: 37758892 DOI: 10.1038/s41586-023-06479-6
    The nearby radio galaxy M87 offers a unique opportunity to explore the connections between the central supermassive black hole and relativistic jets. Previous studies of the inner region of M87 revealed a wide opening angle for the jet originating near the black hole1-4. The Event Horizon Telescope resolved the central radio source and found an asymmetric ring structure consistent with expectations from general relativity5. With a baseline of 17 years of observations, there was a shift in the jet's transverse position, possibly arising from an 8- to 10-year quasi-periodicity3. However, the origin of this sideways shift remains unclear. Here we report an analysis of radio observations over 22 years that suggests a period of about 11 years for the variation in the position angle of the jet. We infer that we are seeing a spinning black hole that induces the Lense-Thirring precession of a misaligned accretion disk. Similar jet precession may commonly occur in other active galactic nuclei but has been challenging to detect owing to the small magnitude and long period of the variation.
  17. Zhong Y, Chu C, Myers JA, Gilbert GS, Lutz JA, Stillhard J, et al.
    Nat Commun, 2021 May 25;12(1):3137.
    PMID: 34035260 DOI: 10.1038/s41467-021-23236-3
    Arbuscular mycorrhizal (AM) and ectomycorrhizal (EcM) associations are critical for host-tree performance. However, how mycorrhizal associations correlate with the latitudinal tree beta-diversity remains untested. Using a global dataset of 45 forest plots representing 2,804,270 trees across 3840 species, we test how AM and EcM trees contribute to total beta-diversity and its components (turnover and nestedness) of all trees. We find AM rather than EcM trees predominantly contribute to decreasing total beta-diversity and turnover and increasing nestedness with increasing latitude, probably because wide distributions of EcM trees do not generate strong compositional differences among localities. Environmental variables, especially temperature and precipitation, are strongly correlated with beta-diversity patterns for both AM trees and all trees rather than EcM trees. Results support our hypotheses that latitudinal beta-diversity patterns and environmental effects on these patterns are highly dependent on mycorrhizal types. Our findings highlight the importance of AM-dominated forests for conserving global forest biodiversity.
  18. Page DB, Broeckx G, Jahangir CA, Verbandt S, Gupta RR, Thagaard J, et al.
    J Pathol, 2023 Aug;260(5):514-532.
    PMID: 37608771 DOI: 10.1002/path.6165
    Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.
  19. Thagaard J, Broeckx G, Page DB, Jahangir CA, Verbandt S, Kos Z, et al.
    J Pathol, 2023 Aug;260(5):498-513.
    PMID: 37608772 DOI: 10.1002/path.6155
    The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
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