Sequential Sampling Research Articles

VIVALDI Cohort Profile: Using linked, routinely collected data and longitudinal blood sampling to characterise COVID-19 infections, vaccinations, and related outcomes in care home staff and residents in England.

VIVALDI (ISRCTN14447421) is a government-funded longitudinal open observational cohort study of staff and residents in care homes for older people in England. The study aimed to describe epidemiology (including seroprevalence) and immune responses to COVID-19 in a subset of care homes, in the context of extremely high mortality in this setting, in the first 12-18 months of the pandemic. Data linkage to routine health data was undertaken for all staff and residents and a subset of individuals who consented to sequential blood sampling to investigate SARS-CoV-2 immunity. This paper aims to describe the samples stored within the VIVALDI biobank and associated linked data, available for use by researchers. Over 70,000 individuals from 346 care homes were included in the data linkage cohort (1 st March 2020-31 st March 2023). 4971 samples from 2264 individuals (1415 staff, 827 residents) collected between 29 th October 2020 and 10 th March 2023 are stored. Amongst these samples, there was a maximum of seven per participant however, 217 (26.2%) residents and 551 (38.9%) staff participated in one round only. Key study findings include high COVID-19 seroprevalence among surviving residents, exceeding rates in community-dwelling peers. COVID-19 vaccinations generated robust immune responses in staff and residents which waned, supporting the need for booster vaccination, particularly in response to new variants. Prior infection significantly improved vaccine-induced immune responses, however protection from infection declined following Omicron variant emergence. This is a unique cohort of pre- and post-infection samples linked to data on COVID-19 infections, vaccinations, and outcomes. The cohort spans host immune response evolution to infection and vaccination in this rarely sampled population of frail older care home residents who are especially vulnerable to infection and severe outcomes. These samples can be used to investigate biological mechanisms behind disparate infection responses in older people and make a valuable contribution to research into ageing.

Effects of volume management on free flap perfusion and metabolism in a large animal model study.

Free flap failure represents a substantial clinical burden. The role of intraoperative volume management remains controversial, with valid studies lacking. Here, using a large animal model, we investigated the influence of volume management on free flap perfusion and metabolism. Autotransfer of a musculocutaneous gracilis flap was performed on 31 German domestic pigs, with arterial anastomosis and catheterization of the pedicle vein for sequential blood sampling. Flap reperfusion was followed by induction of a hemorrhagic shock with maintenance for 30 min and subsequent circulation stabilization with crystalloid solution, crystalloid solution and catecholamine, autotransfusion or colloidal solution. Flap perfusion and oxygenation were periodically assessed using hyperspectral imaging. Flap metabolism was assessed via periodic blood gas analyses. Hyperspectral imaging revealed no difference in either superficial or deep tissue oxygen saturation, tissue hemoglobin or tissue water content between the test groups at any time point. Blood gas analyses showed that lactate levels were significantly increased in the group that received crystalloid solution and catecholamine, after circulatory stabilization and up to 2 h after. We conclude that, in hemorrhagic shock, volume management impacts acid-base balance in free flaps. Crystalloid solutions with norepinephrine increase lactate levels, yet short-term effects on flap perfusion seem minimal, suggesting that vasopressors are not detrimental.

Cell-free DNA from ascites identifies clinically relevant variants and tumour evolution in patients with advanced ovarian cancer.

The emergence of targeted therapies has transformed ovarian cancer treatment. However, biomarker profiling for precision medicine is limited by access to quality, tumour-enriched tissue samples. The use of cell-free DNA (cfDNA) in ascites presents a potential solution to this challenge. In this study, next-generation sequencing was performed on ascites-derived cfDNA samples (26 samples from 15 human participants with ovarian cancer), with matched DNA from ascites-derived tumour cells (n = 5) and archived formalin-fixed paraffin-embedded (FFPE) tissue (n = 5). Similar tumour purity and variant detection were achieved with cfDNA compared to FFPE and ascites cell DNA. Analysis of large-scale genomic alterations, loss of heterozygosity and tumour mutation burden identified six cases of high genomic instability (including four with pathogenic BRCA1 and BRCA2 mutations). Copy number profiles and subclone prevalence changed between sequential ascites samples, particularly in a case where deletions and chromothripsis in Chr17p13.1 and Chr8q resulted in changes in clinically relevant TP53 and MYC variants over time. Ascites cfDNA identified clinically actionable information, concordant to tissue biopsies, enabling opportunistic molecular profiling. This advocates for analysis of ascites cfDNA in lieu of accessing tumour tissue via biopsy.

TLR2/NF-кB signaling may control expansion and function of regulatory T cells in patients with severe fever with thrombocytopenia syndrome (SFTS)

Severe fever with thrombocytopenia syndrome (SFTS) is a recently identified infectious ailment triggered by a new strain of bunyavirus. It is distinguished by elevated fatality rates, ranging from 12 % to 30 %. The mechanism underlying the development of severe illness caused by SFTS bunyavirus (SFTSV) is not yet fully understood. To evaluate the role of the TLR2 receptor pathway in regulating Treg function in the progression of SFTS disease and possible mechanisms, sequential serum samples from 29 patients with SFTS (15 mild, 14 severe cases) were examined. Flow cytometry was employed to scrutinize the phenotypic and functional characteristics of TLR2 expression on circulating CD4 T cells, CD8 T cells, and Tregs. In all admitted patients, the evaluation of correlations between the frequencies of the aforementioned cells and SFTS index (SFTSI) was conducted. For SFTS, the levels of TLR2 on CD4 T cells and Tregs were significantly heightened when compared to those in healthy subjects. Additionally, the expression of TLR2 on Tregs exhibited a positive correlation with Ki-67 expression in Tregs and the severity of disease. Additionally, compared with those in uninfected controls, the expression levels of NF-κB in Tregs were significantly increased. Collectively, Tregs may be activated and proliferate through the stimulation of the TLR2/NF-кB pathway in reaction to SFTSV infection.

Negativity bias in intergroup contact: Meta-analytical evidence that bad is stronger than good, especially when people have the opportunity and motivation to opt out of contact.

Seventy years of research on intergroup contact, or face-to-face interactions between members of opposing social groups, demonstrates that positive contact typically reduces prejudice and increases social cohesion. Extant syntheses, however, have not considered the full breadth of contact valence (positive/negative) and have treated self-selection as a threat to validity. This research bridges intergroup contact theory with sequential sampling models of impression formation to assess contact effects across all valences. From the premise that positive versus negative contact instigates differential resampling of outgroup experiences when self-selection is possible, we advance and meta-analytically test new predictions for the moderation of valenced contact effects and negativity bias as a function of people's opportunity and motivation to self-select in and out of contact. Our random-effects synthesis of positive and negative intergroup contact studies (238 independent samples, 936 nested effects; total N = 152,985) found significant valenced contact effects: Positive contact systematically associates with lower prejudice, and negative contact associates with higher prejudice. Critically, the detrimental effect of negative contact is significantly larger than the benefit of positive contact. This negativity bias is particularly pronounced under conditions in which one can self-select, is motivated to avoid contact, among male-dominated and prejudiced samples, in contact with stigmatized, low status, low socioeconomic status outgroups, along nonconcealable stigma, with nonintimate contact partners in informal settings and in collectivistic societies. Considering individuals' motivation and opportunity to self-select, together with contact valence, therefore offers a more nuanced and integrated platform to design contact-based interventions and policies across varied contact ecologies. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Longitudinal metabolite and protein trajectories prior to diabetes mellitus diagnosis in Danish blood donors: a nested case–control study

Aims/hypothesisMetabolic risk factors and plasma biomarkers for diabetes have previously been shown to change prior to a clinical diabetes diagnosis. However, these markers only cover a small subset of molecular biomarkers linked to the disease. In this study, we aimed to profile a more comprehensive set of molecular biomarkers and explore their temporal association with incident diabetes.MethodsWe performed a targeted analysis of 54 proteins and 171 metabolites and lipoprotein particles measured in three sequential samples spanning up to 11 years of follow-up in 324 individuals with incident diabetes and 359 individuals without diabetes in the Danish Blood Donor Study (DBDS) matched for sex and birth year distribution. We used linear mixed-effects models to identify temporal changes before a diabetes diagnosis, either for any incident diabetes diagnosis or for type 1 and type 2 diabetes mellitus diagnoses specifically. We further performed linear and non-linear feature selection, adding 28 polygenic risk scores to the biomarker pool. We tested the time-to-event prediction gain of the biomarkers with the highest variable importance, compared with selected clinical covariates and plasma glucose.ResultsWe identified two proteins and 16 metabolites and lipoprotein particles whose levels changed temporally before diabetes diagnosis and for which the estimated marginal means were significant after FDR adjustment. Sixteen of these have not previously been described. Additionally, 75 biomarkers were consistently higher or lower in the years before a diabetes diagnosis. We identified a single temporal biomarker for type 1 diabetes, IL-17A/F, a cytokine that is associated with multiple other autoimmune diseases. Inclusion of 12 biomarkers improved the 10-year prediction of a diabetes diagnosis (i.e. the area under the receiver operating curve increased from 0.79 to 0.84), compared with clinical information and plasma glucose alone.Conclusions/interpretationSystemic molecular changes manifest in plasma several years before a diabetes diagnosis. A particular subset of biomarkers shows distinct, time-dependent patterns, offering potential as predictive markers for diabetes onset. Notably, these biomarkers show shared and distinct patterns between type 1 diabetes and type 2 diabetes. After independent replication, our findings may be used to develop new clinical prediction models.Graphical

Detection and consistency of mucosal fluid T lymphocyte phenotypes and their relationship with blood, age and gender

Innate and adaptive immune responses at mucosal surfaces play a role in protection against most infectious diseases. However, the relative importance either of mucosal versus systemic, or of cellular versus humoral immunity in protection against such infections remains unclear. We aimed to determine the relative percentages and reproducibility of detection of five major T lymphocyte phenotypes in stimulated whole mouth fluid (SWMF); to compare matched mucosal and blood phenotypes; to evaluate the consistency of phenotypes in SWMF over time; and to determine any associations with age or gender. Peripheral blood and SWMF samples were collected from 194 participants and sequential concomitant samples were collected from 27 of those and from 12 subjects living with HIV. CD3, CD4, CD8, Th1 and Th2 T lymphocyte phenotypes were determined by FACS. All the five T lymphocyte phenotypes were detected consistently by FACS in PBMC and SWMF with experimental replicates (N = 10; PBMC CV: 3–30%; SWMF CV: 12–36%). In longitudinal samples detection rates were reproducible in both fluids but variations were higher in SWMF (CV: 23–79.6%) than PBMC (CV: 9.7–75%). Statistically significant correlations of the percentages of all the T lymphocyte phenotypes except CD8 was seen between the two fluids. In PBMCs a negative correlation with age was found with CD3, CD4 and CD8 phenotypes, whilst a positive correlation was found in both SWMF and PBMC with the Th2 phenotype. CD3, CD4 and CD8 phenotypes in SWMF and PBMCs from an HIV-positive cohort were not significantly correlated in contrast with the HIV-negative controls. Our study provides a robust FACS protocol for the detection of the five major T lymphocyte phenotypes in SWMF which should prove useful for research with other mucosal fluids.

Confidence Is Influenced by Evidence Accumulation Time in Dynamical Decision Models

Confidence judgments are closely correlated with response times across a wide range of decision tasks. Sequential sampling models offer two competing explanations for the relationship between confidence and response time: According to some models, decision time directly influences confidence. Other models explain the correlation by linking subjective confidence computation to the decision process dynamics. In previous model comparisons, drift diffusion-based confidence models that do not explicitly consider decision time in the computation of confidence provided superior model fits compared to race models that directly included decision time in the internal computation of confidence. In the present study, we present support for the assumption that confidence explicitly takes decision time and post-decisional accumulation time into account. We propose the dynamical visibility, time, and evidence (dynaViTE) model, an extension of the dynamical weighted evidence and visibility (dynWEV) model. DynaViTE assumes that confidence is not solely based on the final amount of accumulated evidence but explicitly includes time in the computation of confidence. Model comparisons using four previously published data sets with different perceptual decision tasks showed a good model fit of dynaViTE, indicating that the relationship between confidence and response time is not only due to the close link in the accumulation process but also to an explicit inclusion of time in the computation of confidence.

Development of a sequential sampling plan for classifying Thrips tabaci (Thysanoptera: Thripidae) populations in onion fields.

Onion thrips, Thrips tabaci Lindeman, is a global pest of onion crops, causing substantial economic damage by diminishing bulb yields and transmitting plant pathogens. Insecticides are used to manage T. tabaci infestations with control decisions traditionally based on action thresholds that require visually counting thrips on a fixed, predetermined number of onion plants per field. However, this approach for treatment decisions is inefficient when thrips populations are well above or below the action threshold. The aim of this research was to develop a sequential sampling plan that would provide a rapid and reliable classification of thrips populations in commercial onion fields above or below prespecified management thresholds. The study was conducted in a total of 24 commercial onion fields in New York in 2021 and 2022. Taylor's power law and Wald's Sequential Probability Ratio Test were used in concert to develop each sampling plan. Simulated and historical field data of thrips populations were used to further validate the efficacy of each sampling plan. Results demonstrated the sequential sampling plan required an average of 78% fewer samples to make a control decision compared with the traditional fixed-sampling approach. Treatment decisions were reached in 72% of cases after inspecting only 10 plants, while only 6% of the cases required examining more than 25 plants. Comparisons with fixed-sample sizes ranging from 23 to 68 plants revealed a 96% agreement in decision-making and a 78% reduction in sampling effort when using the sequential sampling plans.

The Effects of COVID-19 in Kidney Transplantation: Evidence From Tissue Pathology.

The biological effects of SARS-CoV-2 infection in transplanted kidneys are uncertain with little pathological information. This single-center, prospective observational study evaluated kidney transplant biopsies from recipients of deceased donors with COVID-19, current recipients contracting SARS-CoV-2 Omicron variant in 2022, against prior BK virus (BKV) infection and uninfected (without SARS-CoV-2 or BKV) samples, as respective positive and negative comparators (n = 503 samples). We demonstrated nonvirus tubular injury in implanted tissue from infected donors and prevalent recipients with mild acute COVID-19 and acute kidney injury, excluding direct viral infection as a cause of kidney damage. COVID particles were absent in 4116 ultrastructural images of 295 renal tubules from 4 patients with acute COVID-19. No viral cytopathic effect, viral allograft nephropathy, or SARS-CoV-2 RNA was detected in acute tissues, nor in 128 sequential samples from infected donors or recipients with COVID-19. Following recipient COVID-19 (mean 16.8 ± 12.0 wk post-infection), the biopsy-prevalence of rejection was 33.0% (n = 100 biopsies) versus 13.4% for contemporaneous uninfected controls (n = 337; P < 0.001). Prior COVID-19 was an independent risk factor for incident rejection using multivariable generalized estimating equation adjusted for competing risks (odds ratio, 2.195; 95% confidence interval, 1.189-4.052; P = 0.012). Landmark and matched-pair analyses confirmed an association of SARS-CoV-2 with subsequent transplant rejection, with a similar pattern following BKV infection. Transplantation from COVID-19+ deceased donors yielded good recipient outcomes without evidence of viral tissue transmission. Acute kidney injury during COVID-19 was mediated by archetypical tubular injury and infection correlated with an increased risk of subsequent rejection.

Effect of Gestational Hypertension on Neonatal Hemoglobin Level

This study aims to determine the effect of gestational hypertension on neonatal hemoglobin levels. This cohort study was performed on 150 pregnant women, 60 of whom had gestational hypertension and 90 were healthy. Participants were selected using sequential and quota non-probability sampling methods, respectively. The data were collected from interviews and examination forms. The newborns’ umbilical cords were clamped 30-60 sec after the delivery in both groups. Umbilical cord blood samples were taken to determine neonatal hemoglobin levels and sent to the laboratory immediately. Independent t-test was used to compare the two groups in terms of mean hemoglobin; general linear model with an identical link function was used to compare the two groups in terms of mean hemoglobin, considering the effect of confounding variables. SPSS software version 25 was used for the statistical analysis of the data. The statistical significance level in this study was considered to be 0.05. The mean neonatal hemoglobin level in women with gestational hypertension was significantly higher than that in the healthy group (16.73±1.81 gr/dl vs. 15.56±1.79, P&lt;0.001). This difference remained significant after adjusting for demographic and background variables as well as medical records of the participants (P=0.008). The results revealed the hemoglobin level of newborns of mothers who had gestational hypertension, was higher than newborns of healthy mothers. Therefore, performing proper screening tests and knowledge of the hemoglobin level in these infants routinely helps the healthcare staff to prevent, decide and provide more and more useful services.

Multi-objective hull form optimization utilizing sequential sampling optimization method

With advancements in computer technology, Computational fluid dynamics (CFD) theory provides a numerical tool for evaluating the comprehensive hydrodynamic performance of ships. On this basis, the Simulation-based design (SBD) technology based on the static sampling method (SSM) which is termed as SBD-SSM in this paper is recognized as a hull form optimization method with significant advantages. However, in the SBD-SSM method, the excessive pursuit of the global accuracy of the surrogate model leads to the need for more CFD evaluations. Consequently, this demands the substantiality of computing resources and diminishes optimization efficiency. We apply a novel hull form optimization method based on the Sequential Sampling-based Optimization (SBO) method to address this challenge. Furthermore, to strike an appropriate balance between prediction value and uncertainty while finding optimal solutions, we employ the adaptive sampling method known as Pseudo Expected Improvement Matrix (PEIM). By integrating SBO with PEIM, we introduce the SBO-PEIM optimization method, initially applied through mathematical optimization functions to verify its feasibility in optimization. Subsequently, we apply this method to optimize the total resistance and wake performance of the KCS ship. Our findings demonstrate that the SBO-PEIM method achieves higher prediction accuracy in near-optimal solutions than the SBD-SSM method, enhancing optimization efficiency by at least 17.5%. It validates the efficacy of the SBO-PEIM approach in addressing real-world engineering optimization challenges.

A multicenter study of asymmetric and symmetric dimethylarginine as predictors of mortality risk in hospitalized COVID-19 patients

Mortality of patients hospitalized with COVID-19 has remained high during the consecutive SARS-CoV-2 pandemic waves. Early discrimination of patients at high mortality risk is crucial for optimal patient care. Symmetric (SDMA) and asymmetric dimethylarginine (ADMA) have been proposed as possible biomarkers to improve risk prediction of COVID-19 patients. We measured SDMA, ADMA, and other L-arginine-related metabolites in 180 patients admitted with COVID-19 in four German university hospitals as compared to 127 healthy controls. Patients were treated according to accepted clinical guidelines and followed-up until death or hospital discharge. Classical inflammatory markers (leukocytes, CRP, PCT), renal function (eGFR), and clinical scores (SOFA) were taken from hospital records. In a small subgroup of 23 COVID-19 patients, sequential blood samples were available and analyzed for biomarker trends over time until 14 days after admission. Patients had significantly elevated SDMA, ADMA, and L-ornithine and lower L-citrulline concentrations than controls. Within COVID-19 patients, SDMA and ADMA were significantly higher in non-survivors (n = 41, 22.8%) than in survivors. In ROC analysis, the optimal cut-off to discriminate non-survivors from survivors was 0.579 µmol/L for SDMA and 0.599 µmol/L for ADMA (both p < 0.001). High SDMA and ADMA were associated with odds ratios for death of 11.45 (3.37–38.87) and 5.95 (2.63–13.45), respectively. Analysis of SDMA and ADMA allowed discrimination of a high-risk (mortality, 43.7%), medium-risk (15.1%), and low-risk group (3.6%); risk prediction was significantly improved over classical laboratory markers. We conclude that analysis of ADMA and SDMA after hospital admission significantly improves risk prediction in COVID-19.

Promoter profiles in plasma CfDNA exhibits a potential utility of predicting the efficacy of neoadjuvant chemotherapy in breast cancer patients

BackgroundGene expression profiles in breast tissue biopsies contain information related to chemotherapy efficacy. The promoter profiles in cell-free DNA (cfDNA) carrying gene expression information of the original tissues may be used to predict the response to neoadjuvant chemotherapy in breast cancer as a non-invasive biomarker. In this study, the feasibility of the promoter profiles in plasma cfDNA was evaluated as a novel clinical model for noninvasively predicting the efficacy of neoadjuvant chemotherapy in breast cancer.MethodFirst of all, global chromatin (5 Mb windows), sub-compartments and promoter profiles in plasma cfDNA samples from 94 patients with breast cancer before neoadjuvant chemotherapy (pCR = 31 vs. non-pCR = 63) were analyzed, and then classifiers were developed for predicting the efficacy of neoadjuvant chemotherapy in breast cancer. Further, the promoter profile changes in sequential cfDNA samples from 30 patients (pCR = 8 vs. non-pCR = 22) during neoadjuvant chemotherapy were analyzed to explore the potential benefits of cfDNA promoter profile changes as a novel potential biomarker for predicting the treatment efficacy.ResultsThe results showed significantly distinct promoter profile in plasma cfDNA of pCR patients compared with non-pCR patients before neoadjuvant chemotherapy. The classifier based on promoter profiles in a Random Forest model produced the largest area under the curve of 0.980 (95% CI: 0.978–0.983). After neoadjuvant chemotherapy, 332 genes with significantly differential promoter profile changes in sequential cfDNA samples of pCR patients was observed, compared with non-pCR patients, and their functions were closely related to treatment response.ConclusionThese results suggest that promoter profiles in plasma cfDNA may be a powerful, non-invasive tool for predicting the efficacy of neoadjuvant chemotherapy breast cancer patients before treatment, and the on-treatment cfDNA promoter profiles have potential benefits for predicting the treatment efficacy.

A pressure-triggered isobaric sequential liquid sampling system for full-ocean-depth: Design and field deployment

Collecting pressure-retaining deep-sea liquid samples is important for the research on in-situ environment and life. A pressure-triggered isobaric sequential liquid sampling system (PTISLSS) was developed for the collection of seawater at target depths. The sampling system comprises six independent seawater collection modules, each containing a titanium sample container and a pre-charged accumulator. A motor-driven sampling mechanism was designed to open and close the fluid channels at depth. Theoretical studies have indicated that the mechanism can generate a contact pressures of up to 160 MPa to ensure the sealing of the samples. The relationship between the pressure of pre-charged gas and the volume of fluid sample has been derived considering the effects of seal friction. The sampling system was built for full-ocean-depth sampling operation and the reliability of the system was tested at a pressure of 120 MPa. The field test was conducted in the West Philippine Basin on a recent scientific research cruise. Pressurized seawater from depths of 2000 to 4500 meters was recovered, and the pressure-retaining rate exceeded 93.5%. The developed sampling system presents satisfactory performance and high operational efficiency, and it will have a wide range of applications in the field of large-scale deep-sea sampling.

Assessment of change in antimicrobial susceptibility pattern of bacteria causing orthopaedic infections by sequential sampling: A prospective cohort study

BackgroundManagement of Orthopaedic wound infections often depend on isolation of bacteria species (spp.) and its subsequent antimicrobial susceptibility testing (AST). However, the susceptibility to antibiotics may change over time in the same bacterial spp. particularly after initiation of antibiotic therapy. Repeating AST through sequential sampling can be used for the early detection of changes in antimicrobial susceptibility pattern. However, the recommendations about the optimal frequency of repeat AST for same bacterial spp. isolates from same patient to detect the changes in susceptibility patterns are still not established. Furthermore, no prospective research is available to address the crucial issue. Thus, we aimed this study to evaluate the need of repeat AST through sequential samples from the same site. MethodsAST was performed on same bacterial spp. isolates from three sequential samples using Kirby-Bauer disc diffusion method. Considering day 1 as control/baseline, changes in antimicrobial susceptibility pattern was interpreted on two sequential instances (on day 3 and day5). Changes were categorized into favorable & unfavorable and major & minor change categories. ResultsThe overall change in antimicrobial susceptibility pattern was 28 % on instance 1(on day3) and 36.1 % at instance 2 (on day 5). Susceptible to resistance phenotypic change was 14.9 % at instance 1 and 9.2 % at instance 2.A higher percentage change per case in antimicrobial susceptibility pattern was observed at instance 2. Predominant changes were towards the direction of favorable antimicrobial susceptibility pattern. ConclusionThe risk of change in antimicrobial susceptibility potential was over 10 % at both the instances. Furthermore, it was higher at instance 2 i.e., at day5, therefore a repeat sequential antimicrobial susceptibility testing would be recommended at later instance.

Applying sequential adaptive strategies for sampling animal populations: An empirical study

AbstractTraditional sampling methods may prove inadequate when dealing with spatially clustered populations or when studying rare events or traits that are not easily detectable across the target population. When both scenarios occur simultaneously, adaptive sampling strategies can represent a viable option to enhance the detectability of cases of interest. This paper delves into the application of a novel class of sequential adaptive sampling strategies to animal surveys. These strategies, originally proposed for human population tuberculosis prevalence surveys, allow oversampling of the rare interest variables while managing on‐field constraints. This ensures that the unfixed sample size, typical of adaptive sampling, does not compromise overall cost‐effectiveness. We explore a strategy within this class that integrates an adaptive component into a Poisson sequential selection. The aim is twofold: to intensify the detection of cases by exploiting the spatial clustering and to provide a flexible framework for managing logistics and budget constraints. To illustrate the strengths and weaknesses of this Poisson‐based sequential adaptive sampling strategy compared to traditional sampling methods, a simulation study was conducted on a blue‐winged teal population in Florida, USA. The results showcase the benefits of the proposed strategy and open avenues for future methodological and practical improvements.

Comparison of probabilistic structural reliability methods for ultimate limit state assessment of wind turbines

The probabilistic design of offshore wind turbines aims to ensure structural safety in a cost-effective way. This involves conducting structural reliability assessments for different design options and considering different structural responses. There are several structural reliability methods, and this paper will apply and compare different approaches in some simplified case studies. In particular, the well known environmental contour method will be compared to a more novel approach based on sequential sampling and Gaussian processes regression for an ultimate limit state case study on the maximum flapwise blade root bending moment. For one of the case studies, results will also be compared to results from a brute force simulation approach. Interestingly, the comparison is very different from the two case studies. In one of the cases the environmental contours method agrees well with the sequential sampling method but in the other, results vary considerably. Probably, this can be explained by the violation of some of the assumptions associated with the environmental contour approach, i.e. that the short-term variability of the response is large compared to the long-term variability of the environmental conditions. Results from this simple comparison study suggests that the sequential sampling method can be a robust and computationally effective approach for structural reliability assessment.

A reusable QCM biosensor with stable antifouling nano-coating for on-site reagent-free rapid detection of E. coli O157:H7 in food products

Numerous biosensors have shown exceptional analytical performance under laboratory conditions, yet only a few are capable of on-site use with complex, non-model samples while exhibiting reliable analytical performance. Here, we present a new portable biosensor for the rapid (30 min) and accurate detection of bacterial agents in “real-world” food samples, which are originally in either solid or liquid form. The biosensor combines well-established quartz crystal microbalance (QCM) technology, with innovative terpolymer brush nano-coatings on the sensing surface to efficiently reduce non-specific fouling from food samples. Following reagent-free sample preparation, where solid food samples are homogenized, we validated the sensor's detection capabilities on native pathogenic Escherichia coli O157:H7 (E. coli O157:H7) in hamburgers, Czech dumplings, and milk. We achieved limits of detection (LOD), as low as 7.5 × 102 CFU/mL in milk, a value approaching fundamental QCM limits, using a simple direct detection assay format. The biosensor's exceptional reusability was demonstrated through 60 sequential hamburger sample injections, resulting in only a minor LOD shift toward the end of series. A 10-min sonication treatment during sample preparation significantly enhanced sensitivity for E. coli O157:H7 in hamburgers and dumplings, yielding LODs as low as 3.1 × 10³ CFU/mL and 2.6 × 10⁴ CFU/mL, respectively. For on-site analysis, we integrated the nano-coated sensing chip into a custom-built four-channel portable QCM biosensor with an optimized microfluidic system, which can be produced on a scale suitable for practical deployment.

نمط الحساسية للمضادات الحيوية من السلالات البكتيرية الممرضة الشائعة المعزولة من المرضى المصابين بعدوى الجهاز التنفسي السفلي (LRTI)

Lower respiratory tract infections LRTIs are quickly becoming the most prevalent infectious disorders affecting people. This investigation focused on characterizing the current shift in the bacterial strains causing the infections of respiratory tract among patients and their antimicrobial sensitivity pattern since antibiotic resistance has developed in all major pathogens. In the microbiology lab of the Department of Biology Sciences / University of Baghdad, a cross- sectional research using non-probability sequential sampling method was carried out. Respiratory sputum samples taken from individuals with lower respiratory tract infections and collected 149 bacterial isolates. M. catarrhalis, S. pneumonia and H. influenzae were the bacterial pathogens diagnosed by VITEK 2 system and then gathered for further investigation. Frequencies along with percentages were calculated for categorical parameters including microorganism, age and gender. Continuous data like age was presented as mean + standard deviation SD. We used chi-square test for data analysis the value of Chi Square was deemed significant when the p value was P&lt;0.05 . The pathogen that was identified most often was M. catarrhalis 60.4 percent, or 90 patients, followed by H. influenza 28.1 %, or 42 patients and S. pneumonia 11.4 %, or 17 patients. Levofloxacin had a greater sensitivity to S. pneumoniae n=17, 11.4%. Meropenem 42 28.2% was more effective against H. influenza. The M. catarrhalis pattern showed a 57% sensitivity to Co-amoxiclav, a 49% sensitivity to Ceftriaxone, and a 34.9% sensitivity to Erythromycin susceptibility. M. catarrhalis, H. influenzae and S. pneumoniae were the most frequently isolated bacteria from LRTIs. We found that the M. catarrhalis strain was highly resistant to moxifloxacin 49.7% and co-trimaxazole 53.7%. Co-amoxiclav resistance in S. pneumoniae was 8.1%, while Moxifloxacin resistance in H. influenzae was 5.4%.