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This article presents an original, multi-depth soil-temperature monitoring system based on TMP117 digital sensors designed for deployment at several depths. The objective was to evaluate the system’s accuracy and applicability for building-energy performance assessment under contemporary climate conditions. Urban measurements at depths between 1.0 and 2.0 m were compared with ground temperatures derived using PN-EN 16798-5-1:2017-07 with Typical Meteorological Year (TMY) inputs and with observations from the Polish Institute of Meteorology and Water Management (IMWM). Standard inputs underestimated soil temperature on average by 1.1–2.3 °C (TMY) and 2.0–2.8 °C (IMWM), with the bias increasing with depth. For a ground-to-air heat-exchanger (GAHE) assessment, energy benefits estimated from standard inputs were lower in measurements by approximately 30–60% for pre-cooling and 70–86% for pre-heating. Measurements also revealed location-dependent differences between boreholes attributable to underground infrastructure. These findings indicate that non-local or outdated climate datasets can materially overestimate GAHE potential and confirm the need for local, multi-depth ground measurements and periodic updates of standard climate inputs to reflect urbanized conditions and climate change. The presented system constitutes a practical, scalable tool for engineers and designers of HVAC systems relying on ground heat exchange.

Nocturnal avian migration flyways remain an elusive concept, as we have largely lacked methods to map their full extent. We used the network of European weather radars to investigate nocturnal bird movements at the scale of the European flyway. We mapped the main migration directions and showed the intensity of movement across part of Europe by extracting biological information from 70 weather radar stations from northern Scandinavia to Portugal, during the autumn migration season of 2016. On average, over the 20 nights and all sites, 389 birds passed per 1 km transect per hour. The night with highest migration intensity showed an average of 1621 birds km–1 h–1 passing the radar stations, but there was considerable geographical and temporal variation in migration intensity. The highest intensity of migration was seen in central France. The overall migration directions showed strong southwest components. Migration dynamics were strongly related to synoptic wind conditions. A wind‐related mass migration event occurred immediately after a change in wind conditions, but quickly diminished even when supporting winds continued to prevail. This first continental‐scale study using the European network of weather radars demonstrates the wealth of information available and its potential for investigating large‐scale bird movements, with consequences for ecosystem function, nutrient transfer, human and livestock health, and civil and military aviation.

This review concentrates on the application of carbon-based materials in the development and fabrication of voltammetric sensors of antidepressant drugs used in the treatment of moderate to severe depression, anxiety disorders, personality disorders, and various phobias. Voltammetric techniques offer outstanding sensitivity and selectivity, accuracy, low detection limit, high reproducibility, instrumental simplicity, cost-effectiveness, and short time of direct determination of antidepressant drugs in pharmaceutical and clinical samples. Moreover, the combination of voltammetric approaches with the unique characteristics of carbon and its derivatives has led to the development of powerful electrochemical sensing tools for detecting antidepressant drugs, which are highly desirable in healthcare, environmental monitoring, and the pharmaceutical industry. In this review, carbon-based materials, such as glassy carbon and boron-doped diamond, and a wide spectrum of carbon nanoparticles, including graphene, graphene oxides, reduced graphene oxides, single-walled carbon nanotubes, and multi-walled carbon nanotubes were described in terms of the sensing performance of agomelatine, alprazolam, amitriptyline, aripiprazole, carbamazepine, citalopram, clomipramine, clozapine, clonazepam, desipramine, desvenlafaxine, doxepin, duloxetine, flunitrazepam, fluoxetine, fluvoxamine, imipramine, nifedipine, olanzapine, opipramol, paroxetine, quetiapine, serotonin, sertraline, sulpiride, thioridazine, trazodone, venlafaxine, and vortioxetine.

This article presents the current state of knowledge regarding electrochemical methods for determining the active substances within drugs that are used in the treatment of type 1 and type 2 diabetes. Electrochemical methods of analysis, due to their sensitivity and easiness, are a great alternative to other, usually more expensive analytical assays. The determination of active substances mentioned in this review is based on oxidation or reduction processes on the surface of the working electrode. A wide variety of working electrodes, often modified with materials such as nanoparticles or conducting polymers, have been used for the highly sensitive analysis of antidiabetic drugs. The presented assays allow us to determine the compounds of interest in various samples, such as pharmaceutical products or different human bodily fluids.

Background Short-read sequencing technologies have long been the work-horse of microbiome analysis. Continuing technological advances are making the application of long-read sequencing to metagenomic samples increasingly feasible. Results We demonstrate that whole bacterial chromosomes can be obtained from an enriched community, by application of MinION sequencing to a sample from an EBPR bioreactor, producing 6 Gb of sequence that assembles into multiple closed bacterial chromosomes. We provide a simple pipeline for processing such data, which includes a new approach to correcting erroneous frame-shifts. Conclusions Advances in long-read sequencing technology and corresponding algorithms will allow the routine extraction of whole chromosomes from environmental samples, providing a more detailed picture of individual members of a microbiome.

A novel electrochemical method for the determination of quinoline yellow (QY) was developed using the renewable amalgam film electrode (Hg(Ag)FE). The sensors used can be characterized by good stability and long lifespan. Irreversible QY reduction peaks were recorded in 0.05 mol L−1 HCl with a potential of about −630 mV. The use of the Hg(Ag)FE electrode with a regulated working surface allowed the QY limit of detection to be as low as 0.48 nmol L−1. The obtained result is the lowest in comparison to other voltammetric methods described in the literature. The effects of parameters such as the size of the working electrode surface, influence of the pH value, accumulation time, and potential were investigated to provide precision and high sensitivity of the performed measurements. This new procedure was applied for the highly sensitive determination of quinoline yellow in different beverages, pre-workout supplements, and throat lozenges. The process of sample preparation was relatively simple. Calculated recoveries (96–107%) suggest that the method can be considered accurate.

Genome-wide association studies (GWAS) have identified many loci associated with body mass index (BMI) in many different populations. Variants in the FTO locus are reported to be one of the strongest genetic predictors of obesity. Recent publications pointed also to a topologically associated domain (TAD) which is identified as a novel region affecting BMI. The TAD area encompasses the IRXB cluster (IRX3, IRX5, IRX6), FTO and RPGRIP1L genes. In this study, we investigated the relationship between variation of the FTO and IRX genes and obesity in Poles. We presented a case-control association analysis (normal versus overweight and/or obesity group) of Polish adult individuals (N = 5418). We determined whether or not the chromosomal region 16:53 500 000-55 500 000 contains polymorphic variants which are correlated with BMI in Polish population, including sex and age stratified analysis. The obtained results showed that the problem of weight-height abnormalities differently affects populations of Polish women and men (χ2 = 187.1; p<0.0001). From 353 SNPs enrolled to this study, 86 were statistically significant (highest χ2 = 15.72; p = 7.35E-05 observed for rs1558902). Linkage disequilibrium (LD) analysis revealed 61 blocks in the tested region of chromosome 16, with 24 SNPs located within the same block (block 8) of approximately 40 kb, in almost complete LD (|D'|>0.98, r2>0.80). We confirmed presence of the genetic susceptibility loci located in intron 1 of the FTO gene, which were correlated with BMI in our study group. For the first time, our analyses revealed strong association of FTO intronic variants (block 8) with overweight in group of men only. We have also identified association of the IRX region with overweight and/or obesity in Polish individuals. Our study demonstrated how tested SNPs make differential contributions to obesity and overweight risk. We revealed sex dependent differences in the distribution of tested loci which are associated with BMI in the population of Poles.

Background A major limitation of current predictive prognostic models in patients with COVID-19 is the heterogeneity of population in terms of disease stage and duration. This study aims at identifying a panel of clinical and laboratory parameters that at day-5 of symptoms onset could predict disease progression in hospitalized patients with COVID-19. Methods Prospective cohort study on hospitalized adult patients with COVID-19. Patient-level epidemiological, clinical, and laboratory data were collected at fixed time-points: day 5, 10, and 15 from symptoms onset. COVID-19 progression was defined as in-hospital death and/or transfer to ICU and/or respiratory failure (PaO 2 /FiO 2 ratio < 200) within day-11 of symptoms onset. Multivariate regression was performed to identify predictors of COVID-19 progression. A model assessed at day-5 of symptoms onset including male sex, age > 65 years, dyspnoea, cardiovascular disease, and at least three abnormal laboratory parameters among CRP (> 80 U/L), ALT (> 40 U/L), NLR (> 4.5), LDH (> 250 U/L), and CK (> 80 U/L) was proposed. Discrimination power was assessed by computing area under the receiver operating characteristic (AUC) values. Results A total of 235 patients with COVID-19 were prospectively included in a 3-month period. The majority of patients were male (148, 63%) and the mean age was 71 (SD 15.9). One hundred and ninety patients (81%) suffered from at least one underlying illness, most frequently cardiovascular disease (47%), neurological/psychiatric disorders (35%), and diabetes (21%). Among them 88 (37%) experienced COVID-19 progression. The proposed model showed an AUC of 0.73 (95% CI 0.66–0.81) for predicting disease progression by day-11. Conclusion An easy-to-use panel of laboratory/clinical parameters computed at day-5 of symptoms onset predicts, with fair discrimination ability, COVID-19 progression. Assessment of these features at day-5 of symptoms onset could facilitate clinicians’ decision making. The model can also play a role as a tool to increase homogeneity of population in clinical trials on COVID-19 treatment in hospitalized patients.

Colorectal cancer (CRC) is one of the foremost causes of cancer-related deaths. Lately, a close connection between the course of CRC and the intestinal microbiota has been revealed. Vitamin K 2 (VK 2 ) is a bacterially derived compound that plays a crucial role in the human body. Its significant anti-cancer properties may result, inter alia, from a quinone ring possessing a specific chemical structure found in many chemotherapeutics. VK 2 can be supplied to our body exogenously, i.e., through dietary supplements or fermented food (e.g., yellow cheese, fermented soybeans -Natto), and endogenously, i.e., through the production of bacteria that constantly colonize the human microbiome of the large intestine. This paper focuses on endogenous K 2 synthesized by the most active members of the human gut microbiome. This analysis tested 86 intestinally derived bacterial strains, among which the largest VK 2 producers (Lactobacillus, Bifidobacterium, Bacillus) were selected. Moreover, based on the chosen VK 2 -MK4 homolog, the potential of VK 2 penetration into Caco-2 cells in an aqueous environment without the coexistence of fats, pancreatic enzymes, or bile salts has been displayed. The influence of three VK 2 homologs: VK 2 -MK4, VK 2 -MK7 and VK 2 -MK9 on apoptosis and necrosis of Caco-2 cells was tested proving the lack of their harmful effects on the tested cells. Moreover, the unique role of long-chain homologs (VK 2 -MK9 and VK 2 -MK7) in inhibiting the secretion of pro-inflammatory cytokines such as IL-8 (for Caco-2 tissue) and IL-6 and TNFα (for RAW 264.7) has been documented.

There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce.