The petrous bone contains significantly higher amounts of DNA than any other human bone. Because of highly destructive sampling and because it is not always part of the recovered remains, the need for alternative sources of DNA is important. To identify additional optimal bone types, petrous bones were compared to femurs, tali, and calcanei sampled from 66 adult skeletons from two distinct modern-era Christian cemeteries. An extraction method employing full demineralization was used to obtain DNA, real-time PCR quantification to ascertain DNA quantity and degradation, and a commercial forensic short tandem repeats (STR) PCR amplification kit to determine genetic profiles. Statistical analysis was performed to explore the differences in DNA yield, DNA degradation, and success of STR amplification. A systematic studies exploring intra-skeletal variability in DNA preservation including various excavation sites differing by time period and geographical position are rare, and the second part of the investigation was based on a comparison of both archaeological sites, which allowed us to compare the effect of different post-mortem intervals and environmental conditions on DNA preservation. The older burial site in Črnomelj was active between the 13th and 18th century, whereas the more recent Polje burial was in use from the 16th to 19th century, creating different temporal and geographical environments. Results for the Črnomelj burial site revealed that the petrous bone outperformed all other bone types studied, except the calcaneus. At the Polje archeological site calcanei, tali, and femurs yielded the same STR typing success as petrous bones. The results obtained highlight the importance of careful bone sample selection for DNA analysis of aged skeletal remains. In addition to petrous bones, calcanei were found to be an alternative source of DNA when older burial sites are investigated. When more recent burial sites are processed, calcanei, tali, and femurs should be sampled besides petrous bones, not only because they exhibited good performance, but also because of easier sampling and easier grinding in the case of trabecular bones. This study contributes valuable insights into the potential use of various skeletal types as a source of DNA for investigation of aged skeletal remains, and it offers practical implications for forensic and archaeological investigations.

Limited field samplings result in significant uncertainties in regional and global estimates of lake carbon dioxide (CO2) emissions. However, quantitative analysis of uncertainty in regional lake CO2 emission estimates remains unclear. In this study, we utilized satellite data to estimate carbon dioxide flux from 113 eastern China lakes, revealing substantial spatial and temporal variations in flux, averaging 18.07 ± 81.83 mg m-2 d-1. Additionally, satellite-estimated total CO2 effluxes indicated previous upscaling studies had overestimated total CO2 effluxes from these studied lakes by approximately 3-11 times, primarily due to substantial variations in lake CO2 fluxes. Insufficient sampling resolution resulted in considerable uncertainty in upscaling estimations. Temporal variations in carbon dioxide contributed greater upscaling uncertainties than spatial variations in carbon dioxide. To capture the dynamics of lake CO2, increasing the number of sampling points and events is necessary as lake size decreases and trophic state increases. Finally, we propose a prediction for the optimal sampling resolution based on lake area and trophic state, recommending an average of 5 points per lake and bi-monthly sampling as the ideal resolution for similar shallow eutrophic lakes. This approach has been validated as effective in lakes across North America and Europe. We believe that future global-scale lake carbon budget estimates would benefit from field observations conducted at more reasonable sampling points and frequency.

The arcing-involved pulsating coagulation mode with both active and blank periods is essential for modern electrosurgery. This paper begins with a comprehensive introduction to such a pulsating mode, followed by its implementation challenges. Then, an industrial-scale low-speed microcontroller unit (MCU), TMS320F28379D, is utilized to exemplify the proposed output sampling and data-transferring strategy on a gallium nitride (GaN)-based high-frequency inverter that enables coagulation mode with interweaved active periods and blank periods. The inverter prototype fills the active period with 390 kHz sinusoids of amplitude ranging from hundreds to thousands of Volts, while maintaining null outputs during blank periods. The strategy of sampling the above-mentioned sinusoidal outputs, coupled with their data transfer facilitated by direct memory access (DMA), is also articulated for subsequential power computation. Besides that, a novel nonfixed duty cycle approach, featuring an alterable number of sinusoids as the active period, is proposed and integrated into the GaN-based inverter to enhance mode safety. Finally, the power tracking performance of the mode is evaluated initially on resistive load, secondarily on resistive plus capacitive load (R-C), and thirdly on fresh biotissue with the appearance of electrical arcing. The existing necessity of the null blank periods is examined at the end of the paper.

There are multiple habitats in the oral cavity with bacteria, fungi, viruses, and protozoa residing in, which together constitute the oral micro-ecosystem. These microflorae in the oral cavity primarily include saliva, supragingival dental plaque, subgingival dental plaque, submucosal plaque around implants, plaque in root canals, and plaque on the mucosal surface. The interest and knowledge of the microbiome have dynamically increased with the advancement of technology. Therefore, a reliable, feasible, and practical sampling strategy for the oral microbiome is required for the investigation. This paper introduced the sampling strategy of oral microorganisms, consisting of sample collection, transport, processing, and storage. The materials and devices involved in this study are all commonly used in clinical practice or laboratory. The feasibility and reliability of the sampling methods described in this paper have been verified by multiple studies.

This article proposes a performance measure to evaluate the detection performance of a control chart with a given sampling strategy for finite or small samples sequence and prove that the CUSUM control chart with dynamic non-random control limit and a given sampling strategy can be optimal under the measure. Numerical simulations and real data for an earthquake are provided to illustrate that for different sampling strategies, the CUSUM chart will have different monitoring performance in change-point detection. Among the six sampling strategies that take only a part of samples, the numerical comparing results illustrate that the uniform sampling strategy (uniformly dispersed sampling strategy) has the best monitoring effect.

BACKGROUND: The performance of automatic liver segmentation and manual sampling MRI strategies needs be compared to determine interchangeability.
OBJECTIVE: To compare automatic liver segmentation and manual sampling strategies (manual whole liver segmentation and standardized manual region of interest) for performance in quantifying liver volume and MRI-proton density fat fraction (MRI-PDFF), identifying steatosis grade, and time burden.
METHODS: Fifty patients with obesity who underwent liver biopsy and MRI between December 2017 and November 2018 were included. Sampling strategies included automatic and manual whole liver segmentation and 4 and 9 large regions of interest. Intraclass correlation coefficient (ICC), Bland-Altman, linear regression, receiver operating characteristic curve, and Pearson correlation analyses were performed.
RESULTS: Automatic whole liver segmentation liver volume and manual whole liver segmentation liver volume showed excellent agreement (ICC=0.97), high correlation (R2=0.96), and low bias (3.7%, 95% limits of agreement, -4.8%, 12.2%) in liver volume. There was the best agreement (ICC=0.99), highest correlation (R2=1.00), and minimum bias (0.84%, 95% limits of agreement, -0.20%, 1.89%) between automated whole liver segmentation MRI-PDFF and manual whole liver segmentation MRI-PDFF. There was no difference of each paired comparison of receiver operating characteristic curves for detecting steatosis (P=0.07-1.00). The minimum time burden for automatic whole liver segmentation was 0.32 s (0.32-0.33 s).
CONCLUSIONS: Automatic measurement has similar effects to manual measurement in quantifying liver volume, MRI-PDFF, and detecting steatosis. Time burden of automatic whole liver segmentation is minimal among all sampling strategies. Manual measurement can be replaced by automatic measurement to improve quantitative efficiency.

BACKGROUND: Non-Cartesian magnetic resonance imaging trajectories at golden angle increments have the advantage of allowing motion correction and gating using intermediate real-time reconstructions. However, when the acquired data are cardiac binned for cine imaging, trajectories can cluster together at certain heart rates (HR) causing image artifacts. Here, we demonstrate an approach to reduce clustering by inserting additional angular increments within the trajectory, and optimizing them while still allowing for intermediate reconstructions.
METHODS: Three acquisition models were simulated under constant and variable HR: golden angle (Mtrd), random additional angles (Mrnd), and optimized additional angles (Mopt). The standard deviations of trajectory angular differences (STAD) were compared through their interquartile ranges (IQR) and the Kolmogorov-Smirnov test (significance level: p = 0.05). Agreement between an image reconstructed with uniform sampling and images from Mtrd, Mrnd, and Mopt was analyzed using the structural similarity index measure (SSIM). Mtrd and Mopt were compared in three adults at high, low, and no HR variability.
RESULTS: STADs from Mtrd were significantly different (p < 0.05) from Mopt and Mrnd. STAD (IQR × 10-2 rad) showed that Mopt (0.5) and Mrnd (0.5) reduced clustering relative to Mtrd (1.9) at constant HR. For variable HR, Mopt (0.5) and Mrnd (0.5) outperformed Mtrd (0.9). The SSIM (IQR) showed that Mopt (0.011) produced the best image quality, followed by Mrnd (0.014), and Mtrd (0.030). Mopt outperformed Mtrd at reduced HR variability in in-vivo studies. At high HR variability, both models performed well.
CONCLUSIONS: This approach reduces clustering in k-space and improves image quality.

Synthetic antioxidants, including synthetic phenolic antioxidants (SPAs), amine antioxidants (AAs), and organophosphite antioxidants (OPAs), are essential additives for preventing oxidative aging in various industrial and consumer products. Increasing attention has been paid to the environmental contamination caused by these chemicals, but our understanding of synthetic antioxidants is generally limited compared to other emerging contaminants such as plasticizers and flame retardants. Many people spend a significant portion (normally greater than 80%) of their time indoors, meaning that they experience widespread and persistent exposure to indoor contaminants. Thus, this Perspective focuses on the problem of synthetic antioxidants as indoor environmental contaminants. The wide application of antioxidants in commercial products and their demonstrated toxicity make them an important family of indoor contaminants of emerging concern. However, significant knowledge gaps still need to be bridged: novel synthetic antioxidants and their related transformation products need to be identified in indoor environments, different dust sampling strategies should be employed to evaluate human exposure to these contaminants, geographic scope and sampling scope of research on indoor contamination should be broadened, and the partition coefficients of synthetic antioxidants among different media need to be investigated.

The world\'s largest rivers are home to diverse, endemic, and threatened fish species. However, their sheer sizes make large-scale biomonitoring challenging. While environmental DNA (eDNA) metabarcoding has become an established monitoring approach in smaller freshwater ecosystems, its suitability for large rivers may be challenged by the sheer extent of their cross sections (>1 km wide and tens of meters deep). Here, we sampled fish eDNA from multiple vertical layers and horizontal locations from two cross sections of the lower reach of the Yangtze River in China. Over half of the ASVs (amplicon sequence variants) were detected in only a single combination of the vertical layers and horizontal locations, with ∼7% across all combinations. We estimated the need to sample >100 L of water across the cross-sectional profiles to achieve ASV richness saturation, which translates to ∼60 L of water at the species level. No consistent pattern emerged for prioritizing certain depth and horizontal samples, yet we underline the importance of sampling and integrating different layers and locations simultaneously. Our study highlights the significance of spatially stratified sampling and sampling volumes when using eDNA approaches. Specifically, we developed and tested a scalable and broadly applicable strategy that advances the monitoring and conservation of large rivers.

Phytophthora cinnamomi is a destructive soilborne pathogen causing Phytophthora root rot on avocados worldwide. Little is known about the effect of root sampling time, root quantification method (quantitative real-time PCR [qPCR] versus baiting), and tree sample pooling strategies on the quantification of the pathogen in roots in avocado orchard trees. This was investigated in six avocado orchards in two climatically different production regions (Mooketsi and Letaba) in the Limpopo Province, South Africa, over a 2-year period. Two different tree sample pooling strategies, consisting of either a four-pooled group (four groups each containing five pooled trees) or a single-pooled group (20 trees pooled) per 1 ha, were both shown to be suitable for quantifying P. cinnamomi in tree roots using qPCR or root baiting. P. cinnamomi root quantities from the two tree sample pooling strategies were significantly correlated for both quantification methods. Both quantification methods were suitable for quantifying the pathogen in roots, although qPCR was superior to root baiting at identifying significant differences in P. cinnamomi quantities among root sampling time points. The effect of sampling time was dependent on the investigated year. In 2017, root quantities, which were only evaluated using qPCR, did not reveal a consistent trend of a specific sampling time yielding the highest root quantities for most of the orchards. However, five of the orchards in 2018, based on the qPCR analyses, contained significantly higher P. cinnamomi root quantities in May (late autumn) than in March (early autumn), August (late winter), and October/November (late spring). In 2018, P. cinnamomi root DNA quantities were significantly positively correlated with the number of soil temperature hours at 20 to 24 and 20 to 29°C 2 months preceding the root sampling dates and negatively correlated with the number of hours at 15 to 19°C 2 months preceding root sampling. Our study has identified P. cinnamomi root quantification methods and tree sample pooling strategies, which will be useful for understanding the biology of the pathogen and when disease management strategies should be in place.