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Response rates have been steadily declining over the last decades, making survey estimates vulnerable to nonresponse bias. To reduce the potential bias, two weighting approaches are commonly used in National Statistical Offices: the one-step and the two-step approaches. In this article, we focus on the one-step approach, whereby the design weights are modified in a single step with two simultaneous goals in mind: reduce the nonresponse bias and ensure the consistency between survey estimates and known population totals. In particular, we examine the properties of instrumental calibration, a special case of the one-step approach that has received a lot of attention in the literature in recent years. Despite the rich literature on the topic, there remain some important gaps that this article aims to fill. First, we give a set of sufficient conditions required for establishing the consistency of instrumental calibration estimators. Also, we show that the latter may suffer from a large bias when some of these conditions are violated. Results from a simulation study support our findings. Supplementary materials for this article are available online.

This paper experimentally analyzes how stepwise platform vibration (Baseline-S3, approximately 0.3–0.6 mm amplitude) alters the statistical structure of distance measurement errors in a dual-channel LIght Detection And Ranging (LiDAR) (0° and −3°) at a fixed horizontal distance of 1.5 m. The mean error remained at the 10−5 m level across all vibration stages, indicating negligible systematic bias. However, distribution-based metrics showed substantial amplification. The interquartile range (IQR) increased by approximately threefold from Baseline to S3, while the total error range expanded by roughly 4–11 times. The outlier ratio increased by about 1.5–2 times under high-vibration conditions. Both variance and root mean square error (RMSE) exhibited nonlinear growth with increasing vibration intensity. Two-way analysis of variance (ANOVA) revealed no statistically significant differences at the mean level (p>0.05), whereas variability-based indicators consistently demonstrated dispersion amplification. These findings indicate that LiDAR degradation under vibration is governed primarily by stochastic dispersion expansion and extreme-value behavior rather than systematic bias shift.

Traditional pharmacokinetic‐pharmacodynamic models assume cellular homogeneity, yet clinical observations reveal substantial response variability even among patients with similar plasma exposure. We hypothesized that cellular heterogeneity in drug transporter expression, coupled with nonlinear dose–response relationships, can amplify microscopic cellular variability into population‐level outcome variability. Using cobimetinib as an exemplar, we developed a proof‐of‐principle multiscale stochastic framework that couples deterministic systemic pharmacokinetics with cellular‐level stochastic differential equations. In this framework, transporter expression was modeled as log‐normally distributed across cells, generating heterogeneity in intracellular drug concentrations despite identical plasma exposure. Simulations showed that cellular heterogeneity can broaden the distribution of extinction times and produce population‐level outcomes that differ from those predicted by homogeneous or mean‐field formulations. Under the intermittent 21/7 regimen, extinction times were cycle‐structured and, in the extended simulations, were better described by a three‐component mixture than by a unimodal model, indicating schedule‐associated survival cohorts rather than a universal multimodal law. Across the simulations, treatment failure probability increased with population size while the amplification factor remained approximately constant, consistent with an intensive single‐cell property. Sensitivity analyses indicated that the coefficient of variation (CV) of transporter expression was a key determinant of outcome variability across the explored parameter space. These findings support the hypothesis that non‐genetic heterogeneity in drug uptake can contribute to variability in treatment response and apparent resistance. More broadly, this proof‐of‐principle framework highlights the value of stochastic cell‐level modeling for studying therapeutic response distributions when cellular heterogeneity and nonlinear pharmacodynamics are expected to play important roles. Study Highlights What Is the Current Knowledge on the Topic ○Traditional PK‐PD models use population‐averaged approaches that address inter‐patient variability but not intra‐tumor cellular heterogeneity in drug transporter expression. What Question Did This Study Address ○How does cellular‐level heterogeneity in drug transporter expression, coupled with nonlinear pharmacodynamics, affect therapeutic outcomes? What Does This Study Add to Our Knowledge ○Cellular transporter heterogeneity amplifies pharmacodynamic variance up to 1,000‐fold through nonlinear dose–response, creating cycle‐structured extinction time distributions under intermittent dosing and schedule‐associated survival cohorts. Across N = 100–2,000, treatment failure increased with population size while the amplification factor A remained approximately constant, consistent with an intensive single‐cell property. Transporter CV emerged as the strongest predictor of treatment failure across all parameter combinations. How Might This Change Drug Discovery, Development, and/or Therapeutics ○Stochastic cell‐level modeling should be incorporated into PK‐PD frameworks for targeted therapies. Single‐cell measurements of transporter heterogeneity could stratify patients, and combination therapies with uncorrelated transporter dependencies could reduce treatment failures.

The issue of sustainability has attracted attention towards closing the traditional supply chain through different reprocessing options. This paper develops an analytical expression for measuring the bullwhip effect in a six echelon closed loop supply chain for recycling of products like paper, plastic. A first order auto regressive end customer demand is assumed with each supply chain participant employing an order-up-to (OUT) policy and Minimum Mean Square Error (MMSE) forecasting scheme. The model assists the closed loop supply chain entities in anticipating the downstream demand and suggests them to carefully select the value of auto regressive parameter so as to avoid any order-process instability in the closed loop supply chain. Stability analysis helps in determining the combination of degree of segregation at source, yield and auto regressive parameter for maintaining a stable system. Sensitivity analysis of replenishment lead-time combination could be utilized by management for designing an optimal recycling-distribution system, under the condition of constant accumulated lead-time. Further, the segregation analysis reveals that increase in the degree of segregation at the source reduces the bullwhip effect in the closed loop supply chain.

BackgroundAccumulating evidence indicates that some non-absorbed food additives, including emulsifiers carboxymethylcellulose (CMC) and polysorbate 80 (P80), can negatively impact intestinal microbiota, leading to microbiota encroachment, chronic low-grade intestinal inflammation and, subsequently, promotion of metabolic dysregulations. Detrimental impacts of emulsifier consumption on gut microbiota include depletion of the health-associated mucus-fortifying bacteria, Akkermansia muciniphila.ObjectiveInvestigate, in mice, the potential of administration of exogenous A. muciniphila as a means to protect against detrimental impacts of emulsifiers.ResultsDaily oral administration of A. muciniphila prevented phenotypic consequences of consumption of both CMC and P80, including hyperphagia, weight gain and dysglycaemia. A. muciniphila administration also counteracted the low-grade intestinal inflammation-induced CMC and P80. Furthermore, A. muciniphila supplementation prevented the proximal impacts of CMC and P80 on gut microbiota that are thought to drive low-grade chronic inflammation and metabolic dysregulations. Specifically, A. muciniphila prevented alterations in species composition and encroachment of gut microbiota that were otherwise induced by CMC and P80. Remarkably, we finally report that CMC and P80 altered the colonic transcriptome, while A. muciniphila largely protected against these alterations.ConclusionDaily administration of A. muciniphila protects against the detrimental impact of emulsifiers on both the microbiota and host. These results support the notion that use of A. muciniphila as a probiotic can help maintain intestinal and metabolic health amidst the broad array of modern stresses that can promote chronic inflammatory diseases.

Abstract In the context of social events reopening and economic relaunch, sanitary surveillance of SARS-CoV-2 infection is still required. Here, we evaluated the diagnostic performances of a rapid, extraction-free and connected reverse-transcription loop-mediated isothermal amplification (RT-LAMP) assay on saliva. Nasopharyngeal (NP) swabs and saliva from 443 outpatients were collected simultaneously and tested by reverse-transcription quantitative PCR (RT-qPCR) as reference standard test. Seventy-one individuals (16.0%) were positive by NP and/or salivary RT-qPCR. Sensitivity and specificity of salivary RT-LAMP were 85.9% (95%CI 77.8–94.0%) and 99.5% (98.7–100%), respectively. Performances were similar for symptomatic and asymptomatic participants. Moreover, SARS-CoV-2 genetic variants were analyzed and no dominant mutation in RT-LAMP primer region was observed during the period of the study. We demonstrated that this RT-LAMP test on self-collected saliva is reliable for SARS-CoV-2 detection. This simple connected test with optional automatic results transfer to health authorities is unique and opens the way to secure professional and social events in actual context of economics restart.

This paper examines the physical processes controlling how synoptic midlatitude temperature variability near the surface changes with climate. Because synoptic temperature variability is primarily generated by advection, it can be related to mean potential temperature gradients and mixing lengths near the surface. Scaling arguments show that the reduction of meridional potential temperature gradients that accompanies polar amplification of global warming leads to a reduction of the synoptic temperature variance near the surface. This is confirmed in simulations of a wide range of climates with an idealized GCM. In comprehensive climate simulations (CMIP5), Arctic amplification of global warming similarly entails a large-scale reduction of the near-surface temperature variance in Northern Hemisphere midlatitudes, especially in winter. The probability density functions of synoptic near-surface temperature variations in midlatitudes are statistically indistinguishable from Gaussian, both in reanalysis data and in a range of climates simulated with idealized and comprehensive GCMs. This indicates that changes in mean values and variances suffice to account for changes even in extreme synoptic temperature variations. Taken together, the results indicate that Arctic amplification of global warming leads to even less frequent cold outbreaks in Northern Hemisphere winter than a shift toward a warmer mean climate implies by itself.

Extrachromosomal DNA (ecDNA) is a common mode of oncogene amplification but is challenging to analyze. Here, we adapt CRISPR-CATCH, in vitro CRISPR-Cas9 treatment and pulsed field gel electrophoresis of agarose-entrapped genomic DNA, previously developed for bacterial chromosome segments, to isolate megabase-sized human ecDNAs. We demonstrate strong enrichment of ecDNA molecules containing EGFR , FGFR2 and MYC from human cancer cells and NRAS ecDNA from human metastatic melanoma with acquired therapeutic resistance. Targeted enrichment of ecDNA versus chromosomal DNA enabled phasing of genetic variants, identified the presence of an EGFRvIII mutation exclusively on ecDNAs and supported an excision model of ecDNA genesis in a glioblastoma model. CRISPR-CATCH followed by nanopore sequencing enabled single-molecule ecDNA methylation profiling and revealed hypomethylation of the EGFR promoter on ecDNAs. We distinguished heterogeneous ecDNA species within the same sample by size and sequence with base-pair resolution and discovered functionally specialized ecDNAs that amplify select enhancers or oncogene-coding sequences. CRISPR-CATCH is used to isolate extrachromosomal DNA (ecDNA) molecules containing oncogenes from human cancer cells. CRISPR-CATCH followed by nanopore sequencing allows for methylation profiling, highlighting differences from the native chromosomal loci.

As the prevalence of artemisinin-resistant Plasmodium falciparum malaria increases in the Greater Mekong subregion, emerging resistance to partner drugs in artemisinin combination therapies seriously threatens global efforts to treat and eliminate this disease. Molecular markers that predict failure of artemisinin combination therapy are urgently needed to monitor the spread of partner drug resistance, and to recommend alternative treatments in southeast Asia and beyond. We did a genome-wide association study of 297 P falciparum isolates from Cambodia to investigate the relationship of 11 630 exonic single-nucleotide polymorphisms (SNPs) and 43 copy number variations (CNVs) with in-vitro piperaquine 50% inhibitory concentrations (IC50s), and tested whether these genetic variants are markers of treatment failure with dihydroartemisinin–piperaquine. We then did a survival analysis of 133 patients to determine whether candidate molecular markers predicted parasite recrudescence following dihydroartemisinin–piperaquine treatment. Piperaquine IC50s increased significantly from 2011 to 2013 in three Cambodian provinces (2011 vs 2013 median IC50s: 20·0 nmol/L [IQR 13·7–29·0] vs 39·2 nmol/L [32·8–48·1] for Ratanakiri, 19·3 nmol/L [15·1–26·2] vs 66·2 nmol/L [49·9–83·0] for Preah Vihear, and 19·6 nmol/L [11·9–33·9] vs 81·1 nmol/L [61·3–113·1] for Pursat; all p≤10−3; Kruskal-Wallis test). Genome-wide analysis of SNPs identified a chromosome 13 region that associates with raised piperaquine IC50s. A non-synonymous SNP (encoding a Glu415Gly substitution) in this region, within a gene encoding an exonuclease, associates with parasite recrudescence following dihydroartemisinin–piperaquine treatment. Genome-wide analysis of CNVs revealed that a single copy of the mdr1 gene on chromosome 5 and a novel amplification of the plasmepsin 2 and plasmepsin 3 genes on chromosome 14 also associate with raised piperaquine IC50s. After adjusting for covariates, both exo-E415G and plasmepsin 2–3 markers significantly associate (p=3·0 × 10−8 and p=1·7 × 10−7, respectively) with decreased treatment efficacy (survival rates 0·38 [95% CI 0·25–0·51] and 0·41 [0·28–0·53], respectively). The exo-E415G SNP and plasmepsin 2–3 amplification are markers of piperaquine resistance and dihydroartemisinin–piperaquine failures in Cambodia, and can help monitor the spread of these phenotypes into other countries of the Greater Mekong subregion, and elucidate the mechanism of piperaquine resistance. Since plasmepsins are involved in the parasite’s haemoglobin-to-haemozoin conversion pathway, targeted by related antimalarials, plasmepsin 2–3 amplification probably mediates piperaquine resistance. Intramural Research Program of the US National Institute of Allergy and Infectious Diseases, National Institutes of Health, Wellcome Trust, Bill & Melinda Gates Foundation, Medical Research Council, and UK Department for International Development.

Background Osteoarthritis (OA) and rheumatoid arthritis (RA) are common joint disorders that are considered to be different diseases due to their unique molecular mechanisms and pathogenesis. Chemokines and their corresponding receptors have been well characterized in RA progression, but less so in OA pathogenesis. Methods The human primary synovial fibroblasts (SFs) were obtained from human OA and RA tissue samples. The Western blot and qPCR were performed to analyze the expression levels of CXCL1, as well as CXCL-promoted IL-6 expression in both OASFs and RASFs. The signal cascades that mediate the CXCL1-promoted IL-6 expression were identified by using chemical inhibitors, siRNAs, and shRNAs. Results Here, we found that both diseases feature elevated levels of CXCL1 and interleukin (IL)-6, an important proinflammatory cytokine that participates in OA and RA pathogenesis. In OASFs and RASFs, CXCL1 promoted IL-6 expression in a dose- and time-dependent manner. In OASFs and RASFs overexpressing CXCL1 or transduced with shRNA plasmid, IL-6 expression was markedly upregulated. CXCR2, c-Raf, and MAPKs were found to regulate CXCL1-induced IL-6 expression in OASFs and RASFs. Finally, CXCL1 triggered the transcriptional activities of c-Jun (which regulates the expression of proinflammatory proteins) in OASFs and RASFs. Conclusions Our present work suggests that the CXCL1/CXCR2 axis helps to orchestrate inflammatory responses in OA and RA SFs.