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Catfish fillets are produced from whole catfish through a series of processing operations including de‐heading, gutting, filleting, skinning, trimming, and freezing. Catfish processing facilities usually chill or freeze a certain number of catfish fillets as backup storage. Later, catfish fillets are pulled out of storage for further processing, where significant manual labor is needed to separate and flatten all the fillets for downstream processing, such as portioning, breading, and individually quick‐frozen (IQF). Due to the labor force shortage and increasing labor cost, there is a pressing need to automate the singulation task, thereby reducing labor dependence. Machine vision technology has been researched for automated quality evaluation of fish products. However, research is lacking on using machine vision for automated singulation of fish fillets. This study presents a novel machine vision system consisting of a color camera for the recognition of the folding status and orientations of catfish fillets toward realizing automated fillet singulation. A set of 400 images of catfish fillets in four different orientations was captured and annotated for each catfish fillet. Two deep learning‐based image segmentation models, that is, YOLOv8 and SegFormer‐B5, were trained on the dataset for catfish fillet recognition. YOLOv8 outperformed SegFormer in catfish recognition and achieved overall masked mAP (mean average precision) scores of 97.1% and 97.4% for underwater and out‐of‐water catfish fillets, respectively. The vision system combined with YOLOv8 has the potential to automate the recognition and subsequent handling operations of catfish fillets. Practical applications: The U.S. catfish industry is shrinking and facing great challenges because of international market competition and increasing production costs. The outbreak of COVID‐19 revealed a sharp deficiency in the labor force for the entire catfish industry, which has relied on manual labor for various processing operations. Mandatory lockdowns severely disrupted seafood supply chains and labor access. The tightening labor market has resulted in the delay of not only catfish processing but also production and distribution. It is imperative to increase the level of automation for processing operations such as IQF preparation process. At present, each processing facility needs 6–10 laborers for the manual catfish fillet IQF preparation process, implying that automating the process would potentially save hundreds of thousands of dollars in annual labor costs per processing line. The automation technology developed in this article has the potential to benefit the U.S. catfish processor by minimizing labor dependence and costs. [ABSTRACT FROM AUTHOR]

Highlights An automated system connects skewering operations for unattended kebab production. Separating and aligning meat cubes, vegetable slices, and shrimp (C-shape). Multi-machine mode for producing meat and vegetables, and shrimp and vegetable kebabs. Barbecue kebab skewers typically consist of various meat choices, including chicken, lamb, pork, or seafood, and vegetables such as onion and pepper. Traditionally, manual kebab-making is a time-consuming and labor-intensive process, which is considered to be replaced by semi-auto and full-auto skewering machines. Currently, semi-auto skewering machines still require two main manual preparation processes: align the small meat and vegetable pieces into lines for skewering operations; superpose the large pieces of meat and vegetables, then do skewering and cutting operations. Fully automated skewering machines also have two different strategies. The first one is to use rotating scrappers and cups with a respective depth to ensure only one item can be loaded into each cup. All the cups are arranged into sequential cup rows and cup lines for skewering operations. However, the cups are frequently left empty because the rotating scrapper design often blocks any items falling into cups. Thus, some processing facilities still need extra labor to manually fill these empty cups. Another solution is the pick-and-place method by using robot arms and real-time image processing equipment, which cannot process irregular food pieces, such as shrimps (C-shape). In this paper, a novel fully automated handling and feeding system has been developed to prepare and connect the skewering operations to establish unattended kebab production lines. The performances of singulation, handling, and feeding operations have been investigated with different parameter settings and food items. Besides, the presented machine system is the first realization of unattended kebab production lines to process shrimps (C-shape), and the first design of using horizontal skewering operation to produce meat and vegetable kebabs (cube+ square piece) and shrimp and vegetable kebabs (C-shape+ square piece). This study will be beneficial for developing more effective next-generation skewering technologies and better value-added meat and seafood products. [ABSTRACT FROM AUTHOR]

Salvinorin A (SA) exerts neuroprotection and improves neurological outcomes in ischemic stroke models in rodents. In this study, we investigated whether intranasal SA administration could improve neurological outcomes in a monkey ischemic stroke model. The stroke model was induced in adult male rhesus monkeys by occluding the middle cerebral artery M2 segment with an autologous blood clot. Eight adult rhesus monkeys were randomly administered SA or 10% dimethyl sulfoxide as control 20 min after ischemia. Magnetic resonance imaging was used to confirm the ischemia and extent of injury. Neurological function was evaluated using the Non-Human Primate Stroke Scale (NHPSS) over a 28-day observation period. SA significantly reduced infarct volume (3.9 ± 0.7 cm3 vs. 7.2 ± 1.0 cm3; P = 0.002), occupying effect (0.3 ± 0.2% vs. 1.4 ± 0.3%; P = 0.002), and diffusion limitation in the lesion (−28.2 ± 11.0% vs. −51.5 ± 7.1%; P = 0.012) when compared to the control group. SA significantly reduced the NHPSS scores to almost normal in a 28-day observation period as compared to the control group (P = 0.005). Intranasal SA reduces infarct volume and improves neurological outcomes in a rhesus monkey ischemic stroke model using autologous blood clot. [ABSTRACT FROM AUTHOR]

Dexamethasone has been illegally used as a growth-promoting agent to obtain an economic benefit from increased muscle development. An immunochromatographic assay was developed for the quantitative detection of dexamethasone using a probe based on upconversion luminescence nanoparticles. Lanthanide-doped upconversion nanoparticles were synthesized in a system comprising water and ethylene glycol. Various parameters, including the immunoreaction time, the structure of the coating hapten, and the type and concentration of surfactant, were optimized. Based on the optimal conditions, the assay exhibits good dynamic linear detection in the range of 0.05-5 ng/mL with an IC50 of 0.58 ng/mL. The detection limits for dexamethasone in tissue are 0.3 μg/kg. The assay worked well using a 30% methanol extraction solution, giving an average recovery of 84.5%. The assay strip can quantitate on-site using a portable upconversion luminescence reader with a cumulative analysis time of only 10 min, and its fluorescence decay after 6 months is < 25%. [ABSTRACT FROM AUTHOR]

Objective: To comprehensively investigate the predictive value of thyroid hormone sensitivity parameters for cervical lymph node metastasis in patients diagnosed with differentiated thyroid cancer (DTC) undergoing total thyroidectomy and neck lymph node dissection., Methods: A retrospective cohort study was conducted involving patients diagnosed with DTC and evaluated for cervical lymph node metastasis. Relevant demographic, tumour, lymph node and thyroid hormone sensitivity parameter data were extracted from medical records and laboratory reports. Thyroid hormone sensitivity parameters including thyroxine (T4), triiodothyronine (T3), thyroid-stimulating hormone (TSH), thyroglobulin (Tg), thyroglobulin antibodies (TgAbs), thyroid peroxidase antibody, thyroid hormone receptor α and TSH receptor antibody were assessed. Statistical analyses including descriptive statistics, comparative analysis, Pearson's correlation analysis, logistic regression analysis, receiver operating characteristic (ROC) analysis and construction of a multivariable prediction model based on machine learning using the xgbTree method were employed to evaluate the associations and predictive value of thyroid hormone sensitivity parameters for cervical lymph node metastasis., Results: The study revealed significant associations between several thyroid hormone sensitivity parameters and cervical lymph node metastasis in patients with DTC. Specifically, higher levels of T4, T3, Tg, TgAbs and TSH receptor antibody were associated with lymph node metastasis. Pearson's correlation analysis, logistic regression analysis and ROC analysis further underscored the predictive performance of these parameters, with strong overall discriminative abilities. The machine learning-based prediction model demonstrated promising performance with a high area under the curve (AUC) of 0.979., Conclusions: The findings provide compelling evidence for the predictive value of thyroid hormone sensitivity parameters, particularly T3, T4, Tg, TgAbs and TSH receptor antibody, in identifying and evaluating the likelihood of cervical lymph node metastasis in patients with DTC. These parameters hold potential implications for risk stratification, clinical decision-making and personalized management strategies, contributing to improved outcomes for patients at risk of lymph node metastasis.