Trait response of three Baltic Sea spring dinoflagellates to temperature, salinity, and light gradients

Climate change is driving Baltic Sea shifts, with predictions for decrease in salinity and increase in temperature and light limitation. Understanding the responses of the spring phytoplankton community to these shifts is essential to assess potential changes in the Baltic Sea biogeochemical cycles and functioning. In this study we use a high-throughput well-plate setup to experimentally define growth and the light acquisition traits over gradients of salinity, temperature and irradiance for three dinoflagellates commonly occurring during spring in the Baltic Sea, Apocalathium malmogiense, Gymnodinium corollarium and Heterocapsa arctica subsp. frigida. By analysing the response of cell volume, growth, and light-acquisition traits to temperature and salinity gradients, we showed that each of the three dinoflagellates have their own niches and preferences and are affected differently by small changes in salinity and temperature. A. malmogiense has a more generalist strategy, its growth being less affected by temperature, salinity, and light gradients in comparison to the other tested dinoflagellates, with G. corollarium growth being more sensitive to higher light intensities. On the other hand, G. corollarium light acquisition traits seem to be less sensitive to changes in temperature and salinity than those of A. malmogiense and H. arctica subsp. frigida. We contextualized our experimental findings using data collected on ships-of-opportunity between 1993-2011 over natural temperature and salinity gradients in the Baltic Sea. The Apocalathium complex and H. arctica subsp. frigida were mostly found in temperatures<10°C and salinities 4-10 ‰, matching the temperature and salinity gradients used in our experiments. Our results illustrate that trait information can complement phytoplankton monitoring observations, providing powerful tools to answer questions related to species’ capacity to adapt and compete under a changing environment

Towards Phytoplankton Parasite Detection Using Autoencoders

Phytoplankton parasites are largely understudied microbial components with a potentially significant ecological impact on phytoplankton bloom dynamics. To better understand their impact, we need improved detection methods to integrate phytoplankton parasite interactions in monitoring aquatic ecosystems. Automated imaging devices usually produce high amount of phytoplankton image data, while the occurrence of anomalous phytoplankton data is rare. Thus, we propose an unsupervised anomaly detection system based on the similarity of the original and autoencoder-reconstructed samples. With this approach, we were able to reach an overall F1 score of 0.75 in nine phytoplankton species, which could be further improved by species-specific fine-tuning. The proposed unsupervised approach was further compared with the supervised Faster R-CNN based object detector. With this supervised approach and the model trained on plankton species and anomalies, we were able to reach the highest F1 score of 0.86. However, the unsupervised approach is expected to be more universal as it can detect also unknown anomalies and it does not require any annotated anomalous data that may not be always available in sufficient quantities. Although other studies have dealt with plankton anomaly detection in terms of non-plankton particles, or air bubble detection, our paper is according to our best knowledge the first one which focuses on automated anomaly detection considering putative phytoplankton parasites or infections

Dataset from a mesocosm experiment on brownification in the Baltic Sea

Refers to Brownification affects phytoplankton community composition but not primary productivity in eutrophic coastal waters: A mesocosm experiment in the Baltic Sea Science of The Total Environment, Volume 841, 1 October 2022, Pages 156510 Kristian Spilling, Eero Asmala, Noora Haavisto, Lumi Haraguchi, Kaisa Kraft, Anne-Mari Lehto, Aleksandra M. Lewandowska, Joanna Norkko, Jonna Piiparinen, Jukka Seppälä, Mari Vanharanta, Anu Vehmaa, Pasi Ylöstalo, Timo TamminenClimate change is projected to cause brownification of some coastal seas due to increased runoff of terrestrially derived organic matter. We carried out a mesocosm experiment over 15 days to test the effect of this on the planktonic ecosystem. The experiment was set up in 2.2 m3 plastic bags moored outside the Tvärminne Zoological Station at the SW coast of Finland. We used four treatments, each with three replicates: control (Contr) without any manipulation; addition of a commercially available organic carbon additive called HuminFeed (Hum; 2 mg L−1); addition of inorganic nutrients (Nutr; 5.7 µM NH4 and 0.65µM PO4); and a final treatment of combined Nutr and Hum (Nutr+Hum) additions. Water samples were taken daily, and measured variables included water transparency, organic and inorganic nutrient pools, chlorophyll a (Chla), primary and bacterial production and particle counts by flow cytometry.Peer reviewe

First application of IFCB high-frequency imaging-in-flow cytometry to investigate bloom-forming filamentous cyanobacteria in the Baltic Sea

Cyanobacteria are an important part of phytoplankton communities, however, they are also known for forming massive blooms with potentially deleterious effects on recreational use, human and animal health, and ecosystem functioning. Emerging high-frequency imaging flow cytometry applications, such as Imaging FlowCytobot (IFCB), are crucial in furthering our understanding of the factors driving bloom dynamics, since these applications provide community composition information at frequencies impossible to attain using conventional monitoring methods. However, the proof of applicability of automated imaging applications for studying dynamics of filamentous cyanobacteria is still scarce. In this study we present the first results of IFCB applied to a Baltic Sea cyanobacterial bloom community using a continuous flow-through setup. Our main aim was to demonstrate the pros and cons of the IFCB in identifying filamentous cyanobacterial taxa and in estimating their biomass. Selected environmental parameters (water temperature, wind speed and salinity) were included, in order to demonstrate the dynamics of the system the cyanobacteria occur in and the possibilities for analyzing high-frequency phytoplankton observations against changes in the environment. In order to compare the IFCB results with conventional monitoring methods, filamentous cyanobacteria were enumerated from water samples using light microscopical analysis. Two common bloom forming filamentous cyanobacteria in the Baltic Sea, Aphanizomenon flosaquae and Dolichospermum spp. dominated the bloom, followed by an increase in Oscillatoriales abundance. The IFCB results compared well with the results of the light microscopical analysis, especially in the case of Dolichospermum. Aphanizomenon biomass varied slightly between the methods and the Oscillatoriales results deviated the most. Bloom formation was initiated as water temperature increased to over 15°C and terminated as the wind speed increased, dispersing the bloom. Community shifts were closely related to movements of the water mass. We demonstrate how using a high-frequency imaging flow cytometry application can help understand the development of cyanobacteria summer blooms

Towards Phytoplankton Parasite Detection Using Autoencoders

Phytoplankton parasites are largely understudied microbial components with a potentially significant ecological influence on phytoplankton bloom dynamics. To better understand the impact of phytoplankton parasites, improved detection methods are needed to integrate phytoplankton parasite interactions into monitoring of aquatic ecosystems. Automated imaging devices commonly produce vast amounts of phytoplankton image data, but the occurrence of anomalous phytoplankton data in such datasets is rare. Thus, we propose an unsupervised anomaly detection system based on the similarity between the original and autoencoder-reconstructed samples. With this approach, we were able to reach an overall F1 score of 0.75 in nine phytoplankton species, which could be further improved by species-specific fine-tuning. The proposed unsupervised approach was further compared with the supervised Faster R-CNN-based object detector. Using this supervised approach and the model trained on plankton species and anomalies, we were able to reach a highest F1 score of 0.86. However, the unsupervised approach is expected to be more universal as it can also detect unknown anomalies and it does not require any annotated anomalous data that may not always be available in sufficient quantities. Although other studies have dealt with plankton anomaly detection in terms of non-plankton particles or air bubble detection, our paper is, according to our best knowledge, the first that focuses on automated anomaly detection considering putative phytoplankton parasites or infections

Genome-Wide Association Study for Incident Myocardial Infarction and Coronary Heart Disease in Prospective Cohort Studies: The CHARGE Consortium

Background Data are limited on genome-wide association studies (GWAS) for incident coronary heart disease (CHD). Moreover, it is not known whether genetic variants identified to date also associate with risk of CHD in a prospective setting. Methods We performed a two-stageGWAS analysis of incident myocardial infarction (MI) and CHD in a total of 64,297 individuals (including 3898MI cases, 5465 CHD cases). SNPs that passed an arbitrary threshold of 5×10-6 in Stage I were taken to Stage II for further discovery. Furthermore, in an analysis of prognosis, we studied whether known SNPs from former GWAS were associated with totalmortality in individuals who experienced MI during follow-up. Results In Stage I 15 loci passed the threshold of 5×10-6; 8 loci for MI and 8 loci for CHD, for which one locus overlapped and none were reported in previous GWAS meta-analyses. We took 60 SNPs representing these 15 loci to Stage II of discovery. Four SNPs near QKI showed nominally significant association with MI (p-value<8.8×10-3) and three exceeded the genome-wide significance threshold when Stage I and Stage II results were combined (top SNP rs6941513: p = 6.2×10-9). Despite excellent power, the 9p21 locus SNP (rs1333049) was only modestly associated with MI (HR = 1.09, p-value = 0.02) and marginally with CHD (HR = 1.06, p-value = 0.08). Among an inception cohort of those who experienced MI during follow-up, the risk allele of rs1333049 was associated with a decreased risk of subsequent mortality (HR = 0.90, p-value = 3.2×10-3). Conclusions QKI represents a novel locus that may serve as a predictor of incident CHD in prospective studies. The association of the 9p21 locus both with increased risk of first myocardial infarction and longer survival after MI highlights the importance of study design in investigating genetic determinants of complex disorders

The microbiome of the human lower airways : a next generation sequencing perspective

Abstract For a long time, the human lower airways were considered a sterile environment where the presence of microorganisms, typically revealed by culturing, was interpreted as an abnormal health state. More recently, high-throughput sequencing-based studies have led to a shift in this perception towards the notion that even in healthy conditions the lower airways show either transient presence or even permanent colonization by microorganisms. However, challenges related to low biomass and contamination in samples still remain, and the composition, structure and dynamics of such putative microbial communities are unclear. Here, we review the evidence for the presence of microbial communities in the human lower airways, in healthy subjects and within the context of medical conditions of interest. We also provide an overview of the methodology pertinent to high-throughput sequencing studies, specifically those based on amplicon sequencing, including a discussion of good practices and common pitfalls

Pharmacokinetic aspects of retinal drug delivery

Drug delivery to the posterior eye segment is an important challenge in ophthalmology, because many diseases affect the retina and choroid leading to impaired vision or blindness. Currently, intravitreal injections are the method of choice to administer drugs to the retina, but this approach is applicable only in selected cases (e.g. anti-VEGF antibodies and soluble receptors). There are two basic approaches that can be adopted to improve retinal drug delivery: prolonged and/or retina targeted delivery of intravitreal drugs and use of other routes of drug administration, such as periocular, suprachoroidal, sub-retinal, systemic, or topical. Properties of the administration route, drug and delivery system determine the efficacy and safety of these approaches. Pharmacokinetic and pharmacodynamic factors determine the required dosing rates and doses that are needed for drug action. In addition, tolerability factors limit the use of many materials in ocular drug delivery. This review article provides a critical discussion of retinal drug delivery, particularly from the pharmacokinetic point of view. This article does not include an extensive review of drug delivery technologies, because they have already been reviewed several times recently. Instead, we aim to provide a systematic and quantitative view on the pharmacokinetic factors in drug delivery to the posterior eye segment. This review is based on the literature and unpublished data from the authors' laboratory.Peer reviewe

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes.

OBJECTIVE: Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS: We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS: Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS: We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis