Fragment Size Research Articles

Wet inrush susceptibility assessment at the Deep Ore Zone mine using a random forest machine learning model

In cave mines, wet inrushes occur when there is an uncontrolled inflow of fine, wet material from drawpoints. Currently, uncertainty exists regarding the spatial-temporal pattern and severity of inrush incidents. This uncertainty arises from the limited understanding of wet inrush mechanisms within the complex conditions of a cave mine. In this study, the existing gaps in knowledge around the spatial and temporal patterns of inrush incidents were addressed using machine learning techniques. A random forest (RF) model was employed to analyse the inrush database collected at the Deep Ore Zone mine over several years. The conceptual understanding of inrush mechanisms and triggers, along with historical evidence, was employed to establish an initial set of key inrush variables to be used in the RF model. The developed RF model demonstrated promising performance with an accuracy of 85%. The feature importance results indicated that previous inrush history, fragment size, draw rate (short term and long term), differential draw index (short term and long term) and history of inrush at neighbouring drawpoints had the highest impact on inrush susceptibility. The insights gained provide an improved assessment of inrush susceptibility, thereby improving the strategies employed to mitigate inrush risk.

Novel empirical models to assess rock fragment size by drilling and blasting

Development of a comprehensive rock fragmentation model has long been a complicated task because several parameters can affect the rock fragment size of blasted rocks. The role of delay factor has not yet been clear enough to use in the empirical rock fragmentation model. In this study, first a simple new flexible delay function (Df) was found to evaluate the impact of delay factor (Δt) on the rock fragmentation. Then, the effect of in-situ rock mass properties, blasthole parameters, powder factor and delay factor on the rock fragment size were analyzed. After using the new delay function in the combination of the parameters affecting the rock fragment size, the correlation considerably increased. At the end, new empirical models were developed with high correlation of determination (R2), less root mean square error (RMSE) and less coefficient of variation (CV) with actual large scale results.

Quantifying mine waste rock physical weathering rate and processes for improved geomorphic post-mining landforms

Erodibility of landform surfaces depends on several factors and numerical methods are needed to predict erosion and landform evolution particularly for post-mining landscapes. Surface armouring caused by immobile coarse particles tends to reduce the erosion potential of landform surfaces significantly. However, the breakdown of such material through weathering could destabilise this armour and lead to high erosion rates. Hence, the surface erodibility of newly constructed landforms (here we focus on post-mining landforms) can rapidly change over a few years to decades. At present, it is difficult to predict with certainty the rate, or in some cases the dominant processes and pathways, of soil erodibility and soil production over post-mining landscape design lifetimes (typically 100–1000 years). To improve our understandings of soil evolution and its relationship to soil erosion, data is needed to determine the rate at which fine transportable material is produced from the weathering of larger, non-transportable particles, the resultant fragment size distribution together, and how that distribution evolves over time.Here, laboratory weathering experiments were conducted for four different materials from a single coal mine in the Bowen Basin, Queensland, Australia. Wetting and drying cycles were found to rapidly weather all materials. After 32 wet and dry cycles, all materials had a less coarse particle size distribution than at the start. Heating and cooling had no measurable influence on weathering. Due to the rapid reduction of particle sizes caused by high weathering rates, the materials examined would not provide surface armour capability. A new mathematical methodology was developed to determine the weathering parameters for an existing numerical model based on the weathering mechanism and particle size-dependent weathering rate. Although the materials were collected from the same geographical location, they undergo weathering through different mechanisms and rates. Size dependent weathering rate analysis showed that most samples have high weathering rates for large particles and lower weathering rates for smaller particles. The methods used here are simple and inexpensive and can be easily employed to assess mine rehabilitation materials' weathering and armour potential.

Effect of the Inter-Ring Delay Time on Rock Fragmentation: Field Tests at the Underground Mine

The effect of inter-ring delay time (IRDT) on rock fragmentation in the tunnel excavation blasting was studied at the Xinjiang Beizhan Iron Mine, China, to improve the rock fragmentation and optimize the blast design. Blasting tests were conducted with an IRDT of 50, 100, 150, 200, and 500 ms; each adjacent ring had an equal IRDT, and two replicate tests were conducted. The blasting plan with IRDT of 100 ms was the original blasting plan used in the mine. Two optimized blasting plans were proposed and implemented based on the experimental results, along with a control experiment using the original blasting plan. The fragment size of each blast test was measured and analyzed by the block-analyzed software. Both collision theoretical and field tests indicated that the IRDT plays an important role in rock fragmentation and that as the IRDT increases, the degree of rock fragmentation increases first and then decreases. For example, the fragment sizes X20, X50, and X80 showed an increase followed by a decrease; the percentage of large fragments (1-P750) showed a decline followed by a rise; the percentage of small fragments P25 showed an increase followed by a decline. The blasting plan with an IRDT of 150 ms had the most optimal rock fragmentation effect, with the lowest percentage of large fragments, the highest percentage of small fragments, and the smallest average fragment size of X50. Furthermore, the two optimized blasting plans demonstrated better control over blasting costs and rock fragmentation compared to the original blasting plan.

A novel intelligent stereo vision approach for blast-induced fragmentation size distribution: Case study at Golgohar open-pit mine, Iran

Rock fragmentation assessment is a critical aspect of evaluating blasting operations in the mining industry, offering insights for optimising procedures and subsequent mining processes. Traditional methods, such as sieving, while accurate, are costly and time-consuming. Digital image analysis methods have emerged as alternatives, yet they face challenges in accurately handling fragments of varying sizes. Recent advancements in computer vision, particularly deep learning techniques, offer promising solutions to automate and refine fragmentation analysis. This paper introduces a novel intelligent stereo vision approach utilising YOLOv8, an advanced deep learning model, for blast-induced fragmentation size distribution assessment at the Golgohar open-pit mine in Iran. By training YOLOv8 with an automated self-labelled dataset and evaluating its performance against real mine site data, this research aims to enhance the accuracy and efficiency of blast fragmentation analysis. The proposed method leverages stereo images and machine learning to provide precise measurements, leading to improved optimisation of blasting parameters and potential economic benefits compared to traditional methods. Through rigorous validation processes and case studies across diverse scenarios, the proposed approach demonstrates robustness and reliability in assessing blast fragmentation, offering a practical and efficient solution for the mining industry’s evolving needs.

Energy control and block performance optimization of bench blasting

In this study, rock-like model blast tests with varying toe burdens are conducted and the evolution of blast-induced fractures is analyzed using the digital image correlation (DIC) method. In addition, post-blast fragmentations are image-processed to quantitatively investigate the blasting performance. A three-dimensional numerical model is developed and validated against the experimental results. The effects of blasthole inclination (70°, 80°, and 90°) and short delays on fragment size distribution (FSD) are numerically investigated. Field trials are conducted to verify the numerical results. The experimental results reveal that the overall fragment size increases significantly in proportion to the toe burden. The explosion energy utilization rates range from 3.56 % to 13.16 %, with a tendency to initially increase and subsequently decrease. The numerical results demonstrate that fragments are more evenly distributed with a blasthole inclination of 70°, resulting in a remarkable improvement in rock fragmentation compared to a vertical blasthole. Compared to the toe burden, the influence of short delays on concrete fragmentation is insignificant. The field test results indicate that a narrower FSD range and stable pit walls are achieved by utilizing inclined blastholes in bench blasting. This study provides theoretical guidance for optimizing bench blasting parameters, which has practical significance for improving explosive energy utilization and production efficiency in open-pit mines.

Whole Process Analysis and Fate Behavior of Microplastics in Urban Wastewater Treatment Plants, Including their Occurrence Forms, Components, and Removal Efficiency

Microplastics are among the most difficult new pollutants to remove in wastewater treatment plants. In order to explore the occurrence form, size distribution, composition, removal efficiency, migration law, and fate behavior characteristics of microplastic particles in sewage plants, taking a sewage treatment plant in Hohhot as an example, a total of 17 sampling sites were set up. The LAS X software counted the shape, abundance, and size of microplastics and conducted a full-process analysis. The results showed that： fibrous microplastics had the highest abundance and widest distribution and were the main form of existence, accounting for 61.8% of the total abundance； the size of microplastics ranged mainly between 0 and 1.00 mm, and among the four sizes, the abundance of microplastics 0.25 to 0.50 mm in China was the highest, accounting for 32.9%. Among the eight types of plastic components detected, polyester substances （PET, PBT）, cellulose, and polypropylene （PP） were the main components, accounting for 25%, 21%, and 17%, respectively. The influent abundance of the sewage plant was （73 ±5） n·L-1, the effluent abundance was （14 ±2） n·L-1, and the overall removal rate was （80.8 ±12.1）%. Among the three treatment stages of the sewage plant, only the primary treatment played a role in removal, and the abundance of microplastics surged in the secondary treatment. Different structures playing a major role in the removal of microplastics were fine grids （49.2 ±7.4）% and secondary sedimentation tanks （92.4 ±13.9）%. Microplastics mainly existed in the form of fibers, fragments, and films. The proportion of fibers was approximately 70%, and the size of fragments was mainly concentrated between 0.50 and 5.00 mm. Most fragments were in the range of 5.00 mm, accounting for 50%, making them the main form apart from fibrous. The film-like size was mostly concentrated in the range of less than 0.50 mm, accounting for more than 10%. Therefore, improving the removal of small-sized fibrous and film-like microplastics and large-sized fragmented microplastic particles can effectively reduce the pollution risk of microplastics in the environment caused by sewage plant drainage.

Low genetic differentiation despite high habitat fragmentation in an endemic and endangered species of Iridaceae from South America: implications for conservation

Abstract To conserve threatened species effectively, it is crucial to map the genetic variation of the remaining populations. Thus, using 15 microsatellites markers, from which 10 were specially developed for this study, we investigated genetic structure and gene flow patterns of Herbertia zebrina Deble, a critically endangered species endemic from grasslands of southern Brazil. We also investigated the degree of habitat fragmentation and the impacts on levels of genetic diversity, mating system and pollinators of the species. STRUCTURE and discriminant analysis of principal components identified the existence of three genetic clusters. Populations were not isolated by distance, and genetic differentiation among populations was low (7.0%). Migration rates were also low, but no evidence of genetic bottlenecks was found. However, effective population-scaled mutation rates (Θ) were < 1, suggesting that populations could be experiencing genetic drift, but the reason remains unknown. The results indicate that measurements of habitat fragmentation were not significantly correlated with genetic diversity estimates, which tend to increase with fragment size. H. zebrina was identified as an outcrossing species and specialized pollinators, such as Chalepogenus goeldianus and Lanthanomelissa betinae were rarely observed. Our findings suggest that genetic differentiation across multiple populations within the entire geographic distribution of H. zebrina is very low and populations may struggle to adapt to the current environmental and pollination changes. However, habitat fragmentation is still too recent to detect significant impacts on the levels of genetic variation. Thus, conservation plans are necessary to avoid further declines of this species.

Theoretical description of photoinduced electron transfer in donor-acceptor supramolecular complexes based on carbon buckybowls.

Herein, we explore, from a theoretical perspective, the nonradiative photoinduced processes (charge separation and energy transfer) within a family of donor-acceptor supramolecular complexes based on the electron-donor truxene-tetrathiafulvalene (truxTTF) derivative and a series of curved fullerene fragments (buckybowls) of different shapes and sizes (C30H12, C32H12, and C38H14) as electron acceptors that successfully combine with truxTTF via non-covalent interactions. The resulting supramolecular complexes (truxTTF·C30H12, truxTTF·C32H12, and truxTTF·C38H14) undergo charge-separation processes upon photoexcitation through charge-transfer states involving the donor and acceptor units. Despite the not so different size of the buckybowls, they present noticeable differences in the charge-separation efficiency owing to a complex decay post-photoexcitation mechanism involving several low-lying excited states of different natures (local and charge-transfer excitations), all closely spaced in energy. In this intricate scenario, we have adopted a theoretical approach combining electronic structure calculations at (time-dependent) density functional theory, a multistate multifragment diabatization method, the Marcus-Levitch-Jortner semiclassical rate expression, and a kinetic model to estimate the charge separation rate constants of the supramolecular heterodimers. Our outcomes highlight that the efficiency of the photoinduced charge-separation process increases with the extension of the buckybowl backbone. The supramolecular heterodimer with the largest buckybowl (truxTTF·C38H14) displays multiple and efficient electron-transfer pathways, providing a global photoinduced charge separation in the ultrafast time scale in line with the experimental findings. The study reported indicates that modifications in the shape and size of buckybowl systems can give rise to attractive novel acceptors for potential photovoltaic applications.

APEAch: Automated Pipeline for End-to-End Analysis of Epigenomic and Transcriptomic Data.

With the advent of next-generation sequencing (NGS), experimental techniques that capture the biological significance of DNA loci or RNA molecules have emerged as fundamental tools for studying the epigenome and transcriptional regulation on a genome-wide scale. The volume of the generated data and the underlying complexity regarding their analysis highlight the need for robust and easy-to-use computational analytic methods that can streamline the process and provide valuable biological insights. Our solution, aPEAch, is an automated pipeline that facilitates the end-to-end analysis of both DNA- and RNA-sequencing assays, including small RNA sequencing, from assessing the quality of the input sample files to answering meaningful biological questions by exploiting the rich information embedded in biological data. Our method is implemented in Python, based on a modular approach that enables users to choose the path and extent of the analysis and the representations of the results. The pipeline can process samples with single or multiple replicates in batches, allowing the ease of use and reproducibility of the analysis across all samples. aPEAch provides a variety of sample metrics such as quality control reports, fragment size distribution plots, and all intermediate output files, enabling the pipeline to be re-executed with different parameters or algorithms, along with the publication-ready visualization of the results. Furthermore, aPEAch seamlessly incorporates advanced unsupervised learning analyses by automating clustering optimization and visualization, thus providing invaluable insight into the underlying biological mechanisms.

Microstructural, Electrochemical, and Hot Corrosion Analysis of CoCrFeCuTi High Entropy Alloy Reinforced Titanium Matrix Composites synthesized by Microwave Sintering

CoCrFeCuTi High Entropy Alloy (HEA) is reinforced in Ti6Al6V2Sn alloy through microwave sintering-assisted powder metallurgy and its corrosion behaviour is investigated under different conditions. The ball-milled CoCrFeCuTi HEA powder exhibits 17 μm average particle size of irregular fragments with a single-phase BCC structure and is added as reinforcement in Ti alloy at 3, 6, 9, and 12 wt%. As more reinforcement is added, the α-Ti decreases and β-Ti increases which enhances the interfacial bonding. The pinning effects from reinforcements inhibit grain growth contributing to improved properties including higher relative density with less porosity. The 12 wt% composite showed remarkable microhardness of 734 HV which is increased by 43.8% over Ti alloy. The 12 wt% composite also achieved finer grains (0.345 μm) due to uniform internal heat generation from the process. Corrosion behaviour is assessed through electrochemical corrosion and hot corrosion analysis, with 12 wt% composite demonstrating 59.5% better corrosion resistance compared to Ti alloy. The induced corrosion products, formation of passivation films, and their mechanism are examined by morphological analysis.

Analysis of Calcaneal Avulsion Fractures Treated Surgically and Nonsurgically: A Retrospective Multicenter Study.

Calcaneal avulsion fractures (CAvFs) at the Achilles tendon insertion are among the more challenging fractures to treat. Although rare, they often require reoperation. The optimal treatment, including nonsurgical procedures and better implants for surgical procedures in the treatment of CAvFs, remains to be established. Therefore, our study aimed to (1) perform a descriptive evaluation of CAvFs, including cases managed nonsurgically, and (2) assess surgical procedures, including the incidence of complications and reoperation for surgically treated CAvFs. In this multicenter retrospective study, we collected data of patients with CAvFs treated at 9 hospitals from 2012 to 2022. We performed a descriptive study of CAvFs and compared postoperative complications and reoperation rates for multiple surgical techniques and implants. The size of the bone fragments was quantified. The data of 70 patients with CAvFs were analyzed; 20 patients were treated nonsurgically, and 50 were treated surgically. The mean age of patients was 68.5 years; 67% of the patients were female. Nineteen percent of the patients had diabetes, and 19% had osteoporosis. The incidence of postoperative complications was 30%, with infection in 14%, necrosis in 26%, and loss of reduction in 18%. The reoperation rate was 22%. Surgical techniques with use of cannulated cancellous screws were performed in 80% of the surgical cases. Cannulated cancellous screw (CCS) fixation alone resulted in a reoperation rate of 35%, whereas additional augmentation, including washers with CCS fixation, resulted in a reoperation rate of 10%. CCS fixation was successfully performed, although suture anchors were used in some cases with smaller fragments. CAvFs occurred more frequently in older women and had a high rate of postoperative complications. A combination of CCS with augmentation was more effective at reducing postoperative complications than CCS fixation alone, even when the bone fragment size was small. Therapeutic Level III. See Instructions for Authors for a complete description of levels of evidence.

Influence of real particle morphology on single particle crushing behavior of rockfill based on FDEM

Particle morphology is critical in affecting the crushing behavior of rockfill materials. In contrast, most current single particle simulations lack satisfactory morphology accuracy, and the resulting crushing modes deviate from observations to some extent. Therefore, we reconstruct the real particle morphology with the spherical harmonic (SH) method and employ the finite-discrete element method (FDEM) to simulate the one-dimensional (1D) compressive crushing process of basalt particles commonly used in rockfill. The influences of four main morphological parameters, i.e. sphericity, aspect ratio, roundness, and convexity, on the single particle strength and the crushing modes are discussed. The results show that with the SH degree set to 15 and a mesh number of 20,480, the FDEM models of reconstructed particles achieve sufficient morphology accuracy and high computational efficiency. Based on the model, the simulation results demonstrate that the aspect ratio has the most significant impact on single particle strength, followed by sphericity. In contrast, roundness and convexity have a weaker effect than the above two parameters. Also, it is revealed that single particle strength decreases with increasing aspect ratio and sphericity, while it increases with higher roundness and convexity. Furthermore, aspect ratio significantly changes the initial crushing position, sphericity dominates post-crushing fragment size and quantity, and roundness mainly affects post-crushing morphology. The model results have been employed in establishing a support vector regression (SVR)-based predicted model, exhibiting good predictive performance and advantages for the optimization of rockfill particles in engineering.

Strain rate effects on fragment morphology of ceramic alumina: A synchrotron-based study

Dynamic (600–1000 s−1) and quasi-static (0.001–0.01 s−1) compression experiments are conducted on a high-purity alumina ceramic using a split Hopkinson pressure bar and a material test system, respectively. The postmortem fragments of ceramic samples at different strain rates are then characterized via synchrotron micro computed tomography (CT). The three-dimensional (3D) morphologies of fragments are quantified using the gyration tensor analysis after proper segmentation of CT images. The mean fragment size decreases in a power-law form while the mean shape indices (sphericity, elongation index and flatness index) increase in a logarithmic-linear form, with increasing strain rates. In addition, the fragment size and shape distributions are all found to follow the Weibull probability distribution. To reveal the underlying mechanisms of such strain rate effects, high-speed optical and X-ray imaging are implemented to capture the fracture process of ceramic samples under quasi-static and dynamic compression. Primary and secondary wing cracks (PWCs/SWCs) control the fracture and fragmentation of the ceramic under both loading conditions. Compared to quasi-static loading, a considerably larger number of SWCs are produced under dynamic loading, and pronounced branching and bridging occur among the PWCs, which prevent the PWCs from coalescing into axial splitting cracks. Consequently, crack networks composed of high-density wing cracks break the sample into finer and more isotropic fragments, consistent with CT characterizations. Scanning electron microscopy is utilized to analyze the micro damage modes of ceramic samples. Transgranular fracture dominates the grain-scale damage and contributes to the higher dynamic fracture resistance of the alumina under dynamic loading, as a result of more homogeneous nucleation and growth of micro cracks.

On estimating the size of informative fragments in the sea surface images

The paper proposes a solution to one of the problems arising in the construction of modern traffic safety systems in marine areas, namely, estimating the size of informative fragments in the image, which it seems advisable to use when detecting foreign objects on the sea surface image. It is proposed to estimate the size of informative fragments based on calculating the average distance between the contours of the wave elements visible in the image, such as their crests, depressions, etc. The contours of these wave elements are determined based on the Canny operator. The estimation of the sizes of informative fragments is performed along the columns and rows of the analyzed image. Computational experiments have been carried out to illustrate the developed algorithm efficiency. The obtained estimates of the sizes of informative fragments of sea surface images seem appropriate to use in their analysis, in particular, when solving problems of detecting foreign objects on sea surface images.

Comprehensive study on collision patterns of viscous droplets impacting on a heated particle

The collision process involving droplets and heated particles has gained significant attention due to its wide industrial relevance. This study utilizes a high-speed photography to investigate the collision dynamics between viscous droplets and heated particles. The research identifies six distinct collision patterns. In the bubble-breakup mode, the particle experiences the greatest temperature drop, resulting in the most substantial heat transfer. The particle temperature plays a crucial role in determining collision behavior when the Reynolds number exceeds 100 and the Weber number exceeds 55. The maximum spreading area demonstrates a linear relationship with the Weber number, while it reaches a peak and stabilizes with Reynolds numbers in the deposition regime. Contact angle fluctuations are caused by the instability of the contact line. The liquid film thickness exhibits linear and power growth phases, followed by a rapid decrease in the bubble-breakup regime. While the branch-breakup pattern sees smaller fragmented droplet sizes, the atomization-breakup pattern sees flow velocity rise with both Reynolds and Weber numbers. The predicted wavelength of the disturbance in the atomization regime, based on Rayleigh-Taylor instability theory, aligns well with the experimental measurements. The residence time correlates positively with the Weber number.

Deep learning model integrating cfDNA methylation and fragment size profiles for lung cancer diagnosis

Detecting aberrant cell-free DNA (cfDNA) methylation is a promising strategy for lung cancer diagnosis. In this study, our aim is to identify methylation markers to distinguish patients with lung cancer from healthy individuals. Additionally, we sought to develop a deep learning model incorporating cfDNA methylation and fragment size profiles. To achieve this, we utilized methylation data collected from The Cancer Genome Atlas and Gene Expression Omnibus databases. Then we generated methylated DNA immunoprecipitation sequencing and genome-wide Enzymatic Methyl-seq (EM-seq) form lung cancer tissue and plasma. Using these data, we selected 366 methylation markers. A targeted EM-seq panel was designed using the selected markers, and 142 lung cancer and 56 healthy samples were produced with the panel. Additionally, cfDNA samples from healthy individuals and lung cancer patients were diluted to evaluate sensitivity. Its lung cancer detection performance reached an accuracy of 81.5% and an area under the receiver operating characteristic curve of 0.87. In the serial dilution experiment, we achieved tumor fraction detection of 1% at 98% specificity and 0.1% at 80% specificity. In conclusion, we successfully developed and validated a combination of methylation panel and a deep learning model that can distinguish between patients with lung cancer and healthy individuals.

Preconditioning High-Strength Boulders for TBM Tunnelling by Ground Drilling and Blasting

A spherical weathering body, also called a boulder, is an element of complex geological strata and presents a significant challenge to tunnelling by a tunnel-boring machine (TBM). In this study, ground-based drilling and blasting were used to precondition boulders. To determine the specific charge needed for preconditioning blasting, model blasts were conducted, and the relationships among the specific charge, fragment size, and overburden depth in the model blasts were investigated. The determined specific charge from the model blasts was then modified by considering the overburden depth and used to precondition the boulders for practical TBM tunnelling. The results indicate the following: (1) model blasts were effective in determining the correct specific charge and predicting boulder fragment sizes resulting from blasting; (2) the boulders met in practical TBM tunnelling were successfully preconditioned by using the determined specific charge; (3) the determined specific charge was 3.26 kg/m3, corresponding to an average fragment size 4.5 cm with an overburden of zero and increased with increasing overburden; (4) fragment sizes were dependent on both the specific charge and overburden depth. Our conclusions can be used to accurately determine the specific charge instead of empirical formulas.

The development of novel genome-SSRs, multiplex PCR panels, and allelic ladders for parentage identification in Tachypleus tridentatus

Tachypleus tridentatus, one of the oldest animal species on Earth, with significant biological and ecological value, its population sizes have declined due to overfishing. Stock enhancement technology has been used to protect T. tridentatus, however, its efficiency needs to be addressed. In the present study, a parentage identification system was developed. We identified 235,336 SSRs and 182,394 primer pairs were designed. Out of 321 synthesized primers, 14 highly polymorphic primers were selected to reveal the genetic diversity of 110 T. tridentatus. SSRs were amplified with the 14 developed primers, which were fluorescently labeled, and the resulting PCR products were analyzed using the ABI DNA Analyzer 3730xl. The number of alleles per locus, the polymorphism information content, the observed heterozygosity, and the expected heterozygosity ranged from 7 to 48, 0.581 to 0.963, 0.636 to 0.909, and 0.645 to 0.969, respectively. The cumulative exclusion probability with both unknown parents, with only unknown parents, or with both known parents was >99.9999% for the 14 loci. Furthermore, to facilitate data exchange across laboratories and platforms, multiplex PCR detection, SSR fragment size ladders, and parentage identification were employed. Out of the 14 primers, 6 optimal primers were selected for multiplex PCR validation, and two sets of triplex systems were established. Three thousand clones for 160 alleles of the six primers were selected for plasmid extraction and sequencing, and 600 correct plasmids were obtained for new T. tridentatus SSR fragment size ladder construction. Two pairs of parents with 12 offspring each were used for parentage identification by the multiplex PCR systems and ladders, the cumulative average exclusion probability of these 6 primers reached 99.9999% among parents and their offsprings, and was 0% in nonparent-offspring group. The parentage identification system constructed in this study can serve as a tool for monitoring the survival rates of T. tridentatus in stock enhancement programs.

Current Uses and Pitfalls of Liquid Biopsy in NSCLC

Liquid biopsy has emerged as an important tool in the diagnosis and management of lung and other cancers. Various analytes and analytical methods have been studied, including genomic testing by next-generation sequencing (NGS) and non-NGS approaches, including those examining methylation or DNA fragment size. Liquid biopsy, especially from plasma or blood, has several advantages over percutaneous or endoscopic tissue biopsy. It is less invasive, can be used serially for monitoring, and better reflects tumoural heterogeneity across metastatic sites, as opposed to a single area of the biopsied tumour. Herein, we highlight the current uses of liquid biopsy using circulating tumour DNA (ctDNA) analysis in routine clinical practice and potential pitfalls.