Low Repeatability Research Articles

Immunologic, Molecular, and Clinical Profile of Patients with Chromosome 22q11.2 Duplications.

Duplication of chromosome 22q11.2 due to meiotic non-allelic homologous recombination results in a distinct syndrome, chromosome 22q11.2 duplication syndrome that has some overlapping phenotypic features with the corresponding 22q11.2 deletion syndrome. Literature on immunologic aspects of the duplication syndrome is limited. We conducted a retrospective study of 216 patients with this syndrome to better define the key features of the duplication syndrome. Single-center retrospective record review was performed. Data regarding demographics, clinical details, and immunological tests were compiled, extracted into a predetermined data collection form, and analyzed. This cohort comprised 113 (52.3%) males and 103 (47.7%) females. The majority (54.6%) of mapped duplications were between low copy repeat regions A-D (LCR22A to -D). Though T cell subsets were relatively preserved, switched memory B cells, immunoglobulins, and specific antibodies were each found to be decreased in a subset of the cohort. One-fifth (17/79, 21.5%) of patients had at least 2 low immunoglobulin values, and panhypogammaglobulinemia was found in 11.7% (9/79) cases. Four children were on regular immunoglobulin replacement therapy. Asthma and eczema were the predominant atopic symptoms in our cohort. Significant immunodeficiencies were observed in our cohort, particularly in B cells and antibodies. Our study expands the current clinical understanding and emphasizes the need of immunological studies and multidisciplinary approaches for these patients.

Repeatability of an attention bias test for sheep suggests variable influence of state and trait affect on behaviour.

Understanding the effects of repeated testing on behaviour is essential for behavioural tests that are re-applied to the same individuals for research and welfare assessment purposes. Assessing the repeatability of behaviour can also help us understand the influence of persistent traits vs transient states on animal responses during testing. This study examined the repeatability of behavioural responses in an attention bias test developed for sheep as a measure of affective state. Sheep were assessed in the attention bias test three times (n = 81 sheep), with testing occurring at intervals of 1 year then 2 weeks. During testing, individual sheep were exposed to a dog located behind a window for 3 s in a 4 × 4 m arena, then the dog was obscured from view, removed and sheep behaviours were recorded for 180 s. We hypothesised that behaviours in the test would have moderate-high repeatability but that the mean behavioural responses would change over consecutive trials as sheep habituated to the test environment. To estimate repeatability, data were modelled using restricted maximum likelihood linear mixed-effects models, fitting animal ID as a random effect. Vigilance behaviour, defined as having the head at or above shoulder height, was moderately repeatable (r = 0.58). Latency to eat (r = 0.20) and duration spent looking towards the previous location of the dog (attention to the dog wall) (r = 0.08) had low repeatability. Mean latency to eat did not differ significantly between trials (P = 0.2) and mean vigilance behaviour tended to decrease over the trials (P = 0.07). Mean duration of attention to the dog wall significantly decreased across the trials (P < 0.001), while mean zones crossed increased (P < 0.001), as did behaviours directed towards the exit door such as duration in proximity and pawing at the door. Overall, vigilance behaviour was moderately repeatable, suggesting it may have been driven by temperament or personality traits, while attention and feeding behaviours may have been more influenced by transient affective states or other factors, however further research is needed to better tease apart these potential effects. Sheep demonstrated some habituation to the test over consecutive trials. Care should therefore be taken during future application of the test to ensure all animals undergoing attention bias testing have equivalent experience for a valid interpretation of their relative behavioural responses.

Technological advances in three-dimensional skin tissue engineering

Abstract Tissue engineering is an enabling technology that can be used to repair, replace, and regenerate different types of biological tissues and holds great potential in various biomedical applications. As the first line of defense for the human body, the skin has a complex structure. When skin is injured by trauma or disease, the skin tissues may regenerate under natural conditions, though often resulting in irreversible and aesthetically unpleasant scarring. The development of skin tissue engineering strategies was reviewed. Although the traditional approaches to skin tissue engineering have made good progress, they are still unable to effectively deal with large-area injuries or produce full-thickness grafts. In vitro three-dimensional (3D) skin constructs are good skin equivalent substitutes and they have promoted many major innovative discoveries in biology and medicine. 3D skin manufacturing technology can be divided into two categories: scaffold-free and scaffold-based. The representatives of traditional scaffold-free approaches are transwell/Boyden chamber approach and organotypic 3D skin culture. Because of its low cost and high repeatability, the scaffold-free 3D skin model is currently commonly used for cytotoxicity analysis, cell biochemical analysis, and high-throughput cell function. At present, many drug experiments use artificial skin developed by traditional approaches to replace animal models. 3D bioprinting technology is a scaffold-based approach. As a novel tissue manufacturing technology, it can quickly design and build a multi-functional human skin model. This technology offers new opportunities to build tissues and organs layer by layer, and it is now used in regenerative medicine to meet the increasing need for tissues and organs suitable for transplantation. 3D bioprinting can generate skin substitutes with improved quality and high complexity for wound healing and in vitro disease modeling. In this review, we analyze different types of conventional techniques to engineer skin and compare them with 3D bioprinting. We also summarized different types of equipment, bioinks, and scaffolds used in 3D skin engineering. In these skin culture techniques, we focus on 3D skin bioprinting technology. While 3D bioprinting technology is still maturing and improvements to the techniques and protocols are required, this technology holds great promise in skin-related applications.

PIGNN-CFD: A physics-informed graph neural network for rapid predicting urban wind field defined on unstructured mesh

Urban wind field plays an important role in quantitative assessment of urban environment. Compared to field measurement and wind tunnel experiment, Computational Fluid Dynamics (CFD) simulation having the advantages of low cost, repeatability and reliable precision is becoming a common scheme to model flow field of one fixed urban scenario, but still faces the problems of time-consuming computation and lack of scalability for practical engineering application. This paper proposes PIGNN-CFD, a novel physics-informed graph neural network for rapid predicting urban wind field based on irregular unstructured mesh data of CFD simulation. Specifically, a CFD model employing the unsteady Reynolds-Averaged Navier-Stokes (RANS) equations with the standard k-ε turbulence model, is constructed and then numerically solved by OpenFOAM to simulate urban wind field defined on unstructured mesh. After being validated by publicly available wind tunnel test data provided by the Architectural Institute of Japan (AIJ), the proposed CFD model is employed to build the training and test sample sets of urban wind fields by simulating the wind blowing through various randomly generated small-scale urban scenes. A novel physics-informed graph neural network, both approximating the training data and automatically satisfying the RANS equations, is designed and trained to perform wind field inference on unstructured mesh graph, and then scaled up to predict wind fields of arbitrary large-scale urban scenes. The predicted wind field results of two urban environments at different scales show that the well-generalized PIGNN-CFD model runs 1–2 orders of magnitude faster than the CFD model on which it is trained, while obtaining the consistent computational accuracy.

Technical development and feasibility of a reusable vest to integrate cardiovascular magnetic resonance with electrocardiographic imaging

BackgroundElectrocardiographic imaging (ECGI) generates electrophysiological (EP) biomarkers while cardiovascular magnetic resonance (CMR) imaging provides data about myocardial structure, function and tissue substrate. Combining this information in one examination is desirable but requires an affordable, reusable, and high-throughput solution. We therefore developed the CMR-ECGI vest and carried out this technical development study to assess its feasibility and repeatability in vivo. MethodsCMR was prospectively performed at 3T on participants after collecting surface potentials using the locally designed and fabricated 256-lead ECGI vest. Epicardial maps were reconstructed to generate local EP parameters such as activation time (AT), repolarization time (RT) and activation recovery intervals (ARI). 20 intra- and inter-observer and 8 scan re-scan repeatability tests. Results77 participants were recruited: 27 young healthy volunteers (HV, 38.9 ± 8.5 years, 35% male) and 50 older persons (77.0 ± 0.1 years, 52% male). CMR-ECGI was achieved in all participants using the same reusable, washable vest without complications. Intra- and inter-observer variability was low (correlation coefficients [rs] across unipolar electrograms = 0.99 and 0.98 respectively) and scan re-scan repeatability was high (rs between 0.81 and 0.93). Compared to young HV, older persons had significantly longer RT (296.8 vs 289.3 ms, p = 0.002), ARI (249.8 vs 235.1 ms, p = 0.002) and local gradients of AT, RT and ARI (0.40 vs 0.34 ms/mm, p = 0,01; 0.92 vs 0.77 ms/mm, p = 0.03; and 1.12 vs 0.92 ms/mm, p = 0.01 respectively). ConclusionOur high-throughput CMR-ECGI solution is feasible and shows good reproducibility in younger and older participants. This new technology is now scalable for high throughput research to provide novel insights into arrhythmogenesis and potentially pave the way for more personalised risk stratification. Clinical trial registration: Title: Multimorbidity Life-Course Approach to Myocardial Health—A Cardiac Sub-Study of the MRC National Survey of Health and Development (NSHD) (MyoFit46). National Clinical Trials (NCT) number: NCT05455125. URL: https://clinicaltrials.gov/ct2/show/NCT05455125?term=MyoFit&draw=2&rank=1

Four decades of phenology in an alpine amphibian: trends, stasis, and climatic drivers

Strong phenological shifts in response to changes in climatic conditions have been reported for many species, including amphibians, which are expected to breed earlier. Phenological shifts in breeding are observed in a wide number of amphibian populations, but less is known about populations living at high elevations, which are predicted to be more sensitive to climate change than lowland populations. The goal of this study is to assess the main factors determining the timing of breeding in an alpine population of the common toad (Bufo bufo) and to describe the observed shifts in its breeding phenology. We modelled the effect of environmental variables on the start and peak dates of the breeding season using 39 years of individual-based data. In addition, we investigated the effect of the lunar cycle, as well as the individual variation in breeding phenology. Finally, to assess the individual heterogeneity in the timing of breeding, we calculated the repeatability of the timing of arrival at the breeding site. Breeding advanced to earlier dates in the first years of the study but the trend continued only until the mid 1990s, and stabilised afterwards. Overall, toads are now breeding on average around 30 days earlier than at the start of the study period. High temperatures and low snow cover in winter and spring, as well as reduced spring precipitation were all associated with earlier breeding. Additionally, we found evidence of males arriving on average before females at the breeding site but no clear and strong effect of the lunar cycle. We only found weak evidence of among-individual variation in shifts in the breeding phenology, as well as a low repeatability of arrival timing. Our findings show that the observed changes in breeding phenology are strongly associated with the environmental conditions. These results contribute to filling a knowledge gap on the effects of climate change on alpine amphibian populations. Moreover, we show that changes in phenology, especially in the mountains, can be hard to predict as local microclimatic conditions do not necessarily reflect the observed global climatic trends.

Hydrothermal assisted ultrasonic synthesis of MgFe-LDH as a simple and eco-friendly method for electrochemical detection of vitamin B6

A new eco-friendly electrochemical sensor with high sensitivity and selectivity has been introduced in the present work. The proposed sensor is a MgFe-layered double hydroxide (MgFe -LDH) synthesizing via a very simple method. This sensor for the first time was used to determine pyridoxine hydrochloride (vitamin B6) using the differential pulse voltammetry (DPV) technique. The morphology and chemical composition of the MgFe-LDH was recognized using field emission scanning electron microscope (FESEM), Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy, transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), energy dispersive spectroscopy (EDX), X-ray diffraction (XRD), and Brunauer-Emmett-Teller (BET). Under optimal conditions, the calibration curve was plotted using the DPV technique. The limit of detection (LOD) was 131 nM and a linear range of 900 nM–2300 μM was obtained for vitamin B6 oxidation. Therefore, the method is sensitive, simple, and specific with a short analysis time, and the main advantages of this sensor are easy synthesis, low detection limit, excellent stability, repeatability, and good selectivity in vitamin B6. This sensor has been successfully utilized in determining vitamin B6 in human plasma, rice flour, and tablet samples.

Assessing Continuous Glucose Monitor Alarm Use by Families of Children with Diabetes Seen at Riley Children’s Hospital

Background/Objective:A useful feature of continuous glucose monitors (CGM) is customizable alarms which alert persons with diabetes and their caregivers of current or pending blood sugar changes. However, there has been little work studying real-world CGM alarm settings and use in large clinical populations. We seek to understand CGM alarm use through analyses of CGM reports and user interviews.Methods:We analyzed data from two-week CGM reports obtained clinically to determine common alert/alarm settings and compared those to target blood sugar guidelines. We also studied families who are currently using or have never used CGM for diabetes management of their children aged 2-18 years through standardized surveys about diabetes technology and qualitative interviews investigating benefits and burdens associated with CGM use. Data were tabulated, and qualitative analyses were performed.Results:CGM download data from 140 children using the Dexcom® G6 was analyzed. The Low alarm was used by 122 participants (87%) with a median blood glucose of 74 mg/dL (range: 60-100) used as a threshold for alert. The High alarm was used by 101 participants (72%) with a median blood glucose of 274 mg/dL (range: 120-400) used as a threshold for alert. Low Repeat and High Repeat alarms were used by 48 (34%) and 35 (25%) participants, respectively. The most common themes revealed during interviews include the alarms were helpful during sleep, a low sugar is the most important information to be alerted about, and high sugar alarms can be disruptive to patients and caregivers.Conclusions and Potential Impact:We anticipate that identifying barriers to using CGM alarms will assist providers in efforts to instate customizable alerts and alarms. Setting CGM alarm best practices will help ensure children with diabetes and their caregivers are getting needed health data to optimize care and minimize feeling overwhelmed by constant alarms.

Water and wastewater quality prediction: current trends and challenges in the implementation of artificial neural network.

Traditional freshwater supplies have been over-abstracted in the current global problem of water scarcity. Through the analysis of complex experimental and real-time data, to improve the activity of water and wastewater treatment (WWT) systems, an artificial neural network (ANN), a computational model inspired by the human brain, and its variants were created. This review paper focuses on recent trends and advances in modeling and simulating different water and wastewater systems using ANN. This study uses ANN in watershed management, impurity removal from wastewater, and wastewater treatment plants. According to the literature review, ANN can predict nonlinear, linear, and complex systems with high accuracy and well control. Finally, the limitations and future scope of ANNs were discussed. ANN proved itself in the prediction of various water and WWT processes. Still, implementation has practical challenges, which include a lack of data availability, poorly built models, timely updates in developed models, and low repeatability. The use of a proper toolbox, faster computing power, and proper domain knowledge makes the practical implementation of ANN successful. As a result, ANN can build a solid foundation for attracting and motivating investigators to work in this region in the forthcoming.

A semi-supervised learning approach with consistency regularization for tumor histopathological images analysis.

Manual inspection of histopathological images is important in clinical cancer diagnosis. Pathologists implement pathological diagnosis and prognostic evaluation through the microscopic examination of histopathological slices. This entire process is time-consuming, laborious, and challenging for pathologists. The modern use of whole-slide imaging, which scans histopathology slides to digital slices, and analysis using computer-aided diagnosis is an essential problem. To solve the problem of difficult labeling of histopathological data, and improve the flexibility of histopathological analysis in clinical applications, we herein propose a semi-supervised learning algorithm coupled with consistency regularization strategy, called"Semi- supervised Histopathology Analysis Network"(Semi-His-Net), for automated normal-versus-tumor and subtype classifications. Specifically, when inputted disturbing versions of the same image, the model should predict similar outputs. Based on this, the model itself can assign artificial labels to unlabeled data for subsequent model training, thereby effectively reducing the labeled data required for training. Our Semi-His-Net is able to classify patches from breast cancer histopathological images into normal tissue and three other different tumor subtypes, achieving an accuracy was 90%. The average AUC of cross-classification between tumors reached 0.893. To overcome the limitations of visual inspection by pathologists for histopathology images, such as long time and low repeatability, we have developed a deep learning-based framework (Semi-His-Net) for automatic classification subdivision of the subtypes contained in the whole pathological images. This learning-based framework has great potential to improve the efficiency and repeatability of histopathological image diagnosis.

Efficient cyanide sensing using plasmonic Ag/Fe3O4 nanoparticles.

In the line of our previous studies, we have reported a developed sensitive and selective probe for cyanide detection based on Ag/Fe3O4 nanoparticles (NPs) with an extremely low limit of detection at the level of ng per milliliter. Herein, we report the improvement of the easy-to-make magnetic silver nanoparticle-based sensor system for cyanide determination in an extended calibration range with higher selectivity and precision. As far as our knowledge is concerned, the detectable linear range from 1.0 nM to 160 μM (0.026 ng mL-1 to 4.16 μg mL-1) of the improved simple highly precise technique represents the widest assay that has been reported so far. The method is based on strong enhancement of scattered light of the plasmonic nanoparticles and simultaneously cyanide fluorescence quenching. Although the fluorescence of cyanide is highly selective and precise, its intensity is poor. On the other hand, the strongly enhanced Rayleigh signal has a low repeatability. We proposed a method to remove the interference and obtained an effective factor that is directly proportional to cyanide concentration utilizing both above signals simultaneously. In this work, Ag/Fe3O4 NPs have been synthesized easily using a green preparation method and the NPs were consequently characterized using powder XRD, UV-Vis absorption spectroscopy, transmission electron microscopy (TEM) and energy dispersive X-ray spectroscopy (EDX). A combination of absorption, Rayleigh and fluorescence characteristics were used for detection of cyanide in real samples and an overview of recently reported sensors for cyanide was also provided.

Abstract 2530: The role of low complexity repeats in the evolution, structure and function of biomolecular condensate

Abstract 2530: The role of low complexity repeats in the evolution, structure and function of biomolecular condensate

Potentiometric Testing of Soil by Printed Nobel Metal Thick Film Electrode

Analysis of precision farming in soil includes monitoring the main nutrient contents such as nitrogen, phosphate, and potassium on agricultural land before farming activities are carried out. The electrochemical soil detectors are extensively used to detect the nutrient of soil due to their low cost, repeatability, multiplexing, and quick response. In this study AuPt based thick film electrodes are fabricated for detecting NPK using electrochemical techniques. The electrochemical response is monitored in the soil contains urea, KCl and DAP and it shows the good response of DAP. To know the least detection of DAP, concentration varied from 7.5 mM to 500 nM is measured and it is found that the electrode can detect even at 500 nm. The limit of detection is calculated by using the concentration 1 μM to 10 μM and value shows 291 nM can be detected. The surface morphology of the electrode is captured in SEM before and after voltammeter experiments.

Estimation of genetic parameters and single-step genome-wide association studies for milk urea nitrogen in Holstein cattle.

The main objectives of this study were to estimate genetic parameters for milk urea nitrogen (MUN) in Holstein cattle and to conduct a single-step (ss)GWAS to identify candidate genes associated with MUN. Phenotypic measurements from 24,435 Holstein cows were collected from March 2013 to July 2019 in 9 dairy farms located in the Beijing area, China. A total of 2,029 cows were genotyped using the Illumina 150K Bovine Bead Chip, containing 121,188 SNP. A single-trait repeatability model was used to evaluate the genetic background of MUN. We found that MUN is a trait with low heritability (0.06 ± 0.004) and repeatability (0.12). Considering similar milk production levels, a lower MUN concentration indicates higher nitrogen digestibility. The genetic correlations between MUN and milk yield, net energy concentration, fat percentage, protein percentage, and lactose percentage were positive and ranged from 0.02 to 0.26. The genetic correlation between MUN and somatic cell score (SCS) was negative (-0.18), indicating that animals with higher MUN levels tend to have lower SCS. Both ssGWAS and pathway enrichment analyses were used to explore the genetic mechanisms underlying MUN. A total of 18 SNP (located on BTA11, BTA12, BTA14, BTA17, and BTA18) were found to be significantly associated with MUN. The genes CFAP77, CAMSAP1, CACNA1B, ADGRB1, FARP1, and INTU are considered to be candidate genes for MUN. These candidate genes are associated with important biological processes such as protein and lipid metabolism and binding to specific proteins. This set of candidate genes, metabolic pathways, and their functions provide a better understanding of the genomic architecture and physiological mechanisms underlying MUN in Holstein cattle.

Direct Replication in Psychological Assessment Research

Direct Replication in Psychological Assessment Research

Human genomic data have different statistical properties than the data of randomised controlled trials.

Madole & Harden argue that the Mendelian reshuffling of genes and genomes is analogous to randomised controlled trials. We are not convinced by their arguments. First, their recipe for meeting the demands on randomised experiments is inherently inconsistent. Second, disequilibrium across chromosomes conflicts with their assumption of statistical independence. Third, the genome-wide association study (GWAS) method has many pitfalls, including low repeatability.

Research and Development of Intelligent Drying Detection Technology for Machine-Made Sand

This paper aims to develop a high precision variable dielectric constant capacitor detector for mechanical sand water content testing. The non-contact on-line test method can effectively solve the problems of low repeatability of test data, large hysteresis error and poor linearity due to the non-uniform water content. In terms of hardware, CAV444 is a high-precision integrated chip, which matches the corresponding test circuit. The system communicates with PC through serial interface and implements the man-machine interface of PC system based on VS. Secondly, the distribution map method is used to measure the water content of machine-made sand, and the error analysis is carried out. The test shows that the output of the capacitive hygrometer is 0-5 V. The delay time should not exceed 0.15%. The repetition rate was within 0.33%. The measurement accuracy of this method is less than 3.52%.

Eutectic solvent mediated synthesis of carbonated CoFe-LDH nanorods: The effect of interlayer anion (Cl−, SO42−, CO32−) variants for comparing the bifunctional electrochemical sensing application

The unabated usage of priority anthropogenic stressors is a serious concern in the global environmental context. Pharmaceutical drugs such as furazolidone (FL) and nilutamide (NL) have far-reaching repercussions due to the presence of the reactive nitroaromatic moiety. Despite the widespread awareness regarding the dangers posed by nitroaromatic drugs, the promises to alleviate the environmental consequences of drug pollution are often unmet. Accordingly, implementing practices to monitor their presence in various media is a highly desirable, but challenging undertaking. With the advent of deep eutectic solvent-assisted synthesis, it has become possible to fabricate LDH-based sensor materials with minimal energy inputs in a sustainable and scalable manner. In this work, we have framed a series of CoFe-LDH electrocatalysts utilizing deep eutectic solvent-assisted hydrothermal strategies for the simultaneous detection of FL and NL. The CoFe-LDHs intercalated with three distinct anions, namely, (i) Cl−, (ii) SO42−, and (iii) CO32− are compared so as to establish a relationship between anion intercalation and electrochemical activity. Amongst the prepared electrodes, the CF-LDH-ii/SPCE displays highly appreciable selectivity, linear response range (0.09–237.9 μM), low detetion limits (FL = 1.2 nM and NL = 3.8 nM), high sensitivity (FL = 29.71 μA μM⁻1 cm⁻2 and NL = 19.29 μA μM⁻1 cm⁻2), good reproducibility and repeatability towards FL and NL in water and urine samples. Thus, with tailored gallery anions, the proposed electrocatalyst establishes enhanced electrocatalytic performance for the real-time analysis of pharmaceutical contaminants.

Порівняльний аналіз коефіцієнтів аеродинамічного носового опору за даними передньої та задньої активної риноманометрії

The paper deals with a comparative analysis of aerodynamic nose drag coefficients based on the data of front and rear active rhinomanometry. Functional disorders of nasal breathing in the future lead to further complications of the upper and lower respiratory system, reduce the quality of life and lead to other pathological conditions. The diagnosis of such disorders is complicated by the low prevalence of nasal breathing testing tools (rhinomanometers) in medical practice and the peculiarities of functional research methods, which are particularly related to the low repeatability of results and the lack of a clear correlation between diagnostic data and the patient's objective feelings. The obtained data on the total coefficients of aerodynamic nasal resistance, which are determined using the methods of front and rear active rhinomanometry, correspond quite clearly to each other within 12%. The values of the total coefficients of nasal resistance, obtained by the method of posterior rhinomanometry, in all typical cases differ to a lesser extent. The perspective of the work is to gather statistical data to determine the features of nasal breathing testing to obtain accurate personalized values of nasal resistance coefficients in different breathing modes, taking into account individual variability.

Development and applications of chromosome-specific cytogenetic BAC-FISH probes in Larimichthys crocea

Large yellow croaker Larimichthys crocea (Richardson) is an important member in family Sciaenidae, and one of most productive mariculture fishes in China. Fluorescence in situ hybridization is a useful tool for cytogenetics and genomics research. Here, we demonstrated that bacterial artificial chromosome (BAC) clones could be used to identify individual chromosomes in large yellow croaker, and also to study chromosome evolution in the related species. By using BAC paired-end sequencing and sequence alignment, 435 BAC clones were anchored to 24 pseudochromosomes of large yellow croaker genome. Among them, 72 BAC clones with low repeat content were selected and passed PCR test, and then grouped by chromosome for FISH test. As a results, there were 67 BAC clones, 2 to 3 BAC clones per chromosome, generated specific and stable signal at expected position. Then, a dual-color FISH probe cocktail composed of 48 of these BAC clones was formulated and used to hybridize metaphase chromosome spreads, resulting in distinct signal patterns on each chromosome pair, which help to distinguish all chromosomes in the metaphase spreads of large yellow croaker. The chromosome-specific BAC-FISH probes were also applied to a close relative of large yellow croaker, Collichthys lucidus, demonstrating that its Y chromosome originated from the fusion of Chr.1 and Chr.7. Thus, our study provides the first set of chromosome-specific FISH probes in family Sciaenidae, which will play an important role in cytogenetics and genomics research in the family.