Hepatitis-B virus (HBV) co-infection among people living with HIV (PLWH) is highly endemic in South Africa. Despite the availability of an effective vaccine for the last four decades, chronic HBV infection is a major cause of morbidity and mortality among PLWH. Although the incidence of most opportunistic infections has been reduced in individuals with HIV since the implementation of the universal test and treat program in South Africa, HBV co-infection among PLWH is still accounting for high morbidity and mortality.This cross-sectional descriptive survey was conducted in King Sabata Dalindyebo sub-district municipality in the Eastern Cape Province of South Africa to determine the prevalence of HBV co-infection among PLWH.3 (inter-quadrantile range = 307 to 715) and there was no significant association between HBV co-infection and CD4 count.Two-thirds (65.5%) of the 602 PLWH who participated in the study had been screened for HBV co-infection. The mean age of the participants was 38.8±10.5 years and the majority (75.1%) were female. The prevalence of HBV co-infection among PLWH was 12.2%; among males were three times more frequently than females . The median CD4 count of participants was 508 cell/mmThere is a high prevalence of HBV co-infection among PLWH in the Mthatha region of South Africa. The high prevalence of HBV co-infection indicates the need for routine screening for hepatitis B among PLWH in South Africa. Globally an estimated 10% of people infected with the human immunodeficiency virus (HIV) have chronic hepatitis B virus (HBV) co-infection. Around one-third of those chronically infected die as a result of serious liver diseaseThe HIV epidemic is accountable for higher risk of HBV transmission and HIV-infected people are at about six times higher risk of developing chronic HBV infection than their HIV-negative counterpartsHBV co-infection among PLWH remains a major health concern in sub-Saharan Africa, including South AfricaDespite the availability of safe and effective vaccines over the last three decades, chronic HBV infection is a major cause of morbidity and mortality. The vaccine has been freely available in South Africa as part of the childhood expanded program on immunizations (EPI) since April 1995 This cross-sectional descriptive survey of HBV co-infection among PLWH is part of the baseline data of the prospective cohort study, which evaluates the effect of substance use on adherence to ART and co-morbidity among PLWH who use PHC services in Mthatha. The study was conducted at the HIV Outpatient Clinic at Ngangelizwe and Mbekweni Community Health Centre at King Sabata Dalindyebo (KSD) sub-district municipality in the Eastern Cape Province of South Africa. Mthatha is the main town in the KSD sub-district municipality. IsiXhosa is the dominant language of communication and most people depend on social welfare grants and state facilities for health care services.The recruitment goal of the cohort study was to enrol 600 patients who visited the HIV clinic (between 15 June to 15 August 2018); they were invited to participate in this study. Eligible subjects included HIV-infected adults (≥18 years) who had been on ART for more than six months. Patients who were severely ill or refused consent to participate were not included in the study. A flow chart of study participants is demonstrated in A structured questionnaire was administered by trained research assistants. The questionnaire included questions on age, sex, history of present or past self-described smoking, alcohol, and other substance use. National Health Laboratory-based fully automated chemiluminescent micro particle immunoassay (Abbott Architect HBsAg QT) was used for the detection and quantitation of hepatitis B surface antigen (HBsAg).CD4 count, and viral load results from the last 12 months were retrieved from clinical records.Descriptive statistical analysis was performed using SPSS version 18. Categorical data were reported as frequency and percentages and scale data were reported as mean and standard deviation or median and interquartile ranges if not normally distributed. Differences in demographic and clinical characteristics between patients with and without HBV infection were assessed using the chi-squared or Fisher's exact test for categorical variables and p-value <0.05 considered at significance level.Six hundred and two HIV-infected patients participated in the baseline cohort study. After 208 (32.4%) patients had been excluded because no clinical records of HBV screening were available, the remaining 394 (65.6%) were analysed for the prevalence of HBV co-infection. The mean age of the participants was 37.8 years (SD±10.5). Most participants were female (75.1%), unemployed (70.8%), and had an education level of secondary school (85.2%). Majority of patient were on first line TEE (Tenofovir + Emtricitabine + Efavirenz) ART regimen, except four patients were on protease based second line ART regimen. The prevalence of HBV co-infection among PLWH was 12.2% and males had a three times higher infection rate than females, with a statistically significant difference . Most HBV co-infection among PLWH occurred in the age group between 26 and 45 years. People younger than 36 years had the lower proportion of HBV co-infection compare to older counterpart, but the difference was not statistically significant (OR=0.85 95%CI 0.46-1.56 P=0.8). Substance use  were reported among PLWH but there was no significant association between HBV co-infection and substance use. The median CD4 count of participants was 508 cell/mm3, with an inter-quadrantile range of 307 to715. The prevalence of HBV co-infection was marginally higher among PLWH who had an HIV viral load of ≥ 1000 copies/ml. The box an d whisker plot in The study reported that HBV co-infection is common among PLWH. The prevalence of HBV co-infection among PLWH was similar to that found in a systemic review and meta-analysis by Bigna et al (2018) Despite the World Health Organization's recommendation of baseline screening of HBV in a country where the prevalence is higher than 2%, about one-third (32.4%) of the participants had not been screened for HBV co-infection. Recently American and European guidelines also recommended routine screening of HBV infection among newly diagnosed HIV patients There is a large reservoir of chronic HBV infection in sub-Saharan AfricaA significant gender difference (p = 0.001) in the prevalence of HBV co-infection among PLWH was demonstrated in the current study. The HBV co-infection was three times higher among males than among females. Most studies conducted in South Africa demonstrated a similar trend of male-predominance of HV/HIV co-infectionAndrogens can also affect the development of the HBV through their direct binding to the Androgen Response Elements (AR) in the enhancer of the virus. This effect generates increased viral titers in serum of male subjects. Also, the presence of estrogen can affect the host's response. For instance, the natural estrogen known as 17-beta estradiol can reduce the synthesis of the cytokine Interleukin-6 by Kupffer cellsImportantly, we found that the mean age of HBV co-infected among PLWH was 37.8 years and about 90% of them were above 25 years of age. People born before 1995 (older than 25 years) had a high prevalence of HBV co-infection and this age distribution may reflect the protective effect of childhood HBV vaccination. Since 1995 the hepatitis-B vaccine has been part of the EPI in South Africa3. The current study findings are in alignment, with a slightly higher prevalence of HV co-infection among PLWH who presented with a CD4 count of fewer than 200 cells/mm3 and high viral load (≥1000 copies/ml)It is well documented that the natural history of HBV infection can be influenced by the presence of HIV and the severity of immunosuppressionFurthermore, the study stated that substance  use was reported among PLWH but there was no significant association between HBV co-infection and substance use. These findings contradicted the previous studies who reported the association between substance use HBV co-infection in this group of the populationThe researchers acknowledge several limitations. About one-third of patients were excluded because no clinical records of HBV screening were available. Patients presenting with severe illness were excluded from the study; the prevalence of HBV co-infection among this group could be different. Furthermore, the sample was derived from a selected population of PLWH who were PHC users in a local context.There was a high prevalence of HBV co-infection among PLWH attending PHC settings in the Mthatha region of South Africa. Despite the high burden of HBV co-infection, routine screening of HBV among PLWH in PHC settings was not done. Therefore, a comprehensive and integrated HBV screening program is recommended for adequate management and follow-up of hepatitis B infection among PLWH. Primary prevention through vaccination is showing results by decreasing HBV co-infection among people born after 1995. The policymaker is advised to scale up vaccination coverage to interrupt the transmission of HBV infection among PLWH.


Chronic HBV infection evolves through different phases. Interactions between viral replication and the host immune response in the liver underlie the pathogenesis of this disease. The aim of this study was to directly visualize the HBV replication intermediates at a single-cell resolution inscribed on morphological changes corresponding to disease activity.in situ hybridization assays.A set of archived formalin-fixed paraffin-embedded liver needle biopsies from treatment-naïve patients were collected and categorized into phases according to the American Association for the Study of the Liver Diseases (AASLD) guidelines. HBV RNA and DNA were detected using The hepatocytes were ubiquitously infected in subjects with immune tolerance, and their percentage was gradually decreased in immune-active and inactive chronic hepatitis B phases. HBV-infected hepatocytes were prone to localize close to fibrous septa. The subcellular distribution of signals was able to distinguish hepatocytes with productive infection from those harboring HBV integrants and transcriptionally inactive covalently closed circular DNAs. A smaller number of hepatocytes with productive infection and more harboring transcriptionally inactive covalently closed circular DNA or HBV integrants became apparent in the inactive chronic hepatitis B phase.in situ characteristics of viral-host interactions for each phase is described, which sheds light on the nature of viral replication and disease pathogenesis among the phases of chronic HBV infection.An atlas of   Our findings revealed that both the number of infected hepatocytes and the in-cell state of viral replication are distinct, particularly in 2 extreme phases, the immune-tolerant (IT) and inactive chronic hepatitis B (IC) phases. An atlas of in situ characteristics of viral-host interaction for each phase is described, which contributes to our knowledge of intrahepatic viral replication and disease pathogenesis across the course of chronic HBV infection.In most studies, the amounts of different viral intermediates are usually quantified using bulk nucleic acids extracted from liver specimens. These lose the spatial information offered by tissue architectures and ignore the complexity of cell-to-cell heterogeneity.In this study, all the patients were diagnosed with chronic HBV infection according to the American Association for the Study of the Liver Diseases (AASLD) guidelines.In situ hybridization was performed on routine paraffin sections of the liver needle biopsies. The probes used in this study can cover the full length of the A–D genotype of the HBV genome, with high sensitivity for single-molecule nucleic acid detection and reliable specificityhttp://links.lww.com/HC9/A227). The V-HBV-536207-O4 and V-HBV-536207-04-sense probes were synthesized to hybridize with the HBV DNA plus and minus strands, respectively, by Advanced Cell Diagnostics. The experimental procedures were adapted and modified based on the manufacturer’s instruction of RNAscope2.5 HD Detection Reagent Kit-RED . Upon detecting the HBV RNA, to remove DNA, the section was predigested with RNase-free DNase I (Takara) for 30 minutes at 37°C after Protease Plus treatment, then subjected to hybridization with V-HBV-536207-O4. The HBV minus-strand was directly probed with V-HBV-536207-04-sense that would not bind to the HBV RNA. After adding the V-HBV-536207-04-sense probe, the sample was incubated at 95°C for 5 minutes to denature the dsDNA to improve the efficiency of annealing of the probe to the target. The probes in the tissue were finally visualized using the Fast Red dye substrate, and the cell nucleus was counterstained with Gill’s hematoxylin I. Sections with obscure signals were not included in further image analyses.K-VIEWER, version 1 was used to preview the whole slice and capture images in randomly selected nonrepetitive fields under ×200 magnification. Qupath, version 0.3.0 was used to count all hepatocytes,p-value <0.05 was considered statistically significant. Photoshop CS6 was used to improve the contrast between signals and noise in histological images.Data are expressed as means and SDs, or medians and interquartile ranges. GraphPad Prism, version 8.0.2 was used to analyze the data and generate figures. Nonparametric tests, including the Mann-Whitney test, Wilcoxon matched-pairs signed-rank test, and Kruskal-Wallis 1-way ANOVA followed by the Dunn test, if appropriate, were performed using SPSS 19.0. All tests were 2-tailed, and a http://links.lww.com/HC9/A228). We microscopically observed >1300 nonrepetitive fields, including 940 hepatic lobular areas, over 200 fields around the portal triads and central vein areas, and 200 fibrous septa. In subjects in the IT phase with an HBV-productive infection, the signals were widespread across the lobules and were ubiquitous in almost every hepatocyte. In most cases in the latter 3 phases, the HBV RNA and DNA signals were scattered and irregularly distributed in the tissue.We screened hundreds of archived formalin-fixed paraffin-embedded liver needle biopsies and detected HBV RNA and HBV DNA in connective tissue sections. A preliminary evaluation confirmed that the HBV RNA and DNA signals were strictly distributed in hepatocytes and not in other cell types, suggesting high specificity in our experimental approach. The nonspecific staining sections and those with low signal-to-noise ratios had been excluded from further analysis. HBV RNA and DNA were successfully detected on the liver needle biopsy sections from a total of 47 patients, including 7 subjects in the IT phase, 16 patients in the HBeAg+IA phase, 7 patients in the IC phase, and 17 patients in the HBeAg−IA phase , n=7], which was significantly higher than that in the HBeAg+IA , IC , or HBeAg−IA phases  , we compared the regions within 100 μm, which contained roughly 5 rows of hepatocytes, around the portal areas and central veins. We found that HBV RNA-positive and DNA-positive cells can be scattered or aggregated in the tissues, regardless of whether they were located close to the portal triad or the central vein , we further evaluated the spatial relationship between HBV RNA-positive or DNA-positive hepatocytes and the histological features of fibrosis by comparing the positive cells located within 100 μm around the fibrotic septa and those within the 100–200 μm range. We found that positive cells tended to gather around the fibrotic septa . The relationship between intrahepatic HBV DNA/RNA signals and fibrosis stage was not significant.Furthermore, in patients in the HBeAg+IA and HBeAg−IA phases, we analyzed the relationship between necroinflammation and HBV-positive cells in areas close to the portal vein, close to the central vein, or in intralobular hepatic cords Figure D. We fouAfter browsing >50,000 HBV RNA-positive and DNA-positive hepatocytes, we summarized the subcellular distribution of their signals into several patterns, which correspond to the biogenesis of viral nucleic acids according to the HBV life cycle. Polygonal-shaped cells with well-defined cell borders that are easily visualized owing to the diffuse “sand-like” fine granular signals in the cytoplasm represented hepatocytes with an active viral infection, with HBV nucleocapsid-associated associated pregenomic RNA or relaxed circular DNA. In some infected hepatocytes, HBV RNA signals appeared similar to puncta that are localized to the cytoplasm or close to the nuclear membrane. This distribution could be due to the translation of the HBV integrant mRNA, which utilizes certain cellular machinery. HBV DNA also had similar patterns of subcellular distribution. Signals that are uniquely retained within the nucleus as puncta or appear like several dots are highly indicative of the covalently closed circular DNA (cccDNA) or HBV DNA that may be integrated into the human genome. However, some HBV RNA-positive cells were also identified to have signals that were predominantly confined within the nucleus or annexed to the nucleus, which were reproduced but not understood Figure A. In mos16pt?>When comparing all phases, we found that the percentage of cells containing only nuclear HBV DNA signals was significantly higher in the IC phase than in the IT and HBeAg+IA phases Figures . This inCirculating HBsAg is comprised of cccDNA and integrated HBV DNA origins, whereas HBV replication is only dependent on the cccDNA. We examined the relationship between intrahepatic HBV DNA-positive and RNA-positive signals and the levels of circulating viral biomarkers in clinical use, such as HBsAg and HBV DNA. As expected, the percentage of total HBV DNA-positive hepatocytes was positively correlated with serum HBV DNA load and HBsAg titer, and the percentage of total HBV RNA-positive hepatocytes was positively correlated with serum HBsAg titer. When stratified with the pattern of the subcellular distribution, the percentages of cytoplasmic HBV DNA-positive and RNA-positive hepatocytes exhibited much better correlation with serum HBV DNA load. These results further indicate that the cytoplasmic HBV signals are the source of productive HBV infection. In contrast, nuclear HBV signals and serum viral biomarkers were negatively correlated, which supported the notion that the nuclear HBV signals were less relevant to HBV production Figure B.In situ hybridization has its inherent advantages, including the illustration of critical viral replication intermediates and their spatial relationship to pathobiological changes observed from liver biopsies.The natural history of chronic hepatitis B is crucial in understanding the development of this disease. Observation of liver biopsy specimens through microscopy is a very direct way to visualize viral replication by correlating the morphological changes with disease progression.in situ hybridization approach (data not shown).Pieces of evidence in this study do not support the vulnerability of human hepatocytes to HBV infection is influenced by oxygen, and nutrient metabolism and detoxification, especially since infected cells and the functional zonation of the liver do not have an apparent spatial relationship.in situ hybridization suggest that the expansion of HBV-integrated hepatocytes may be the result of expansion induced by liver homeostasis or may indicate preconditions of dysplasia.The persistence of cccDNA is a hurdle to the cure of chronic hepatitis B. In addition, HBV integration is also an important source of HBsAg, making it difficult to achieve a functional cure.In this study, we developed probes for the plus and minus strands of HBV to visualize its transcription products as well as the relaxed circular DNA in the cytoplasm and to distinguish hepatocytes that harbor cccDNA or HBV integrants. Hepatocytes with productive HBV infection could be defined as being positive for both cytoplasmic HBV RNA and HBV DNA, which can easily be seen due to their polygonal pattern. Hepatocytes harboring HBV integrants could be defined as having a single nuclear dot when hybridized with the HBV DNA probe and several cytoplasmic puncta when hybridized with the HBV RNA probe. Hepatocytes harboring transcriptionally inactive cccDNA or HBV integrants could be defined as having a single nuclear dot when hybridized with an HBV DNA probe and no signal when hybridized with an HBV RNA probe .Constrained by the limited access to liver biopsy tissues of untreated patients and their geographic locations, we only included 47 patients diagnosed with chronic HBV genotypes B and C infections. Although we did not perform molecular biological verification, our interpretation of the characteristics of HBV signal distribution in the liver is consistent with the findings of current studies and the characteristics in the liver of patients after antiviral therapy.in situ hybridization in routine histological evaluation of chronic hepatitis B, which offers substantial information on viral replication. Our findings helped us understand the viral-host interaction and the relationship between anatomical structures and disease stages across the natural course of chronic HBV infection.Therefore, we advocate including


The noise statistics of real-world camera images are challenging for any denoising algorithm. Here, I describe a modified version of a bionic algorithm that improves the quality of real-word noisy camera images from a publicly available image dataset. In the first step, an adaptive local averaging filter was executed for each pixel to remove moderate sensor noise while preserving fine image details and object contours. In the second step, image sharpness was enhanced by means of an unsharp mask filter to generate output images that are close to ground-truth images (multiple averages of static camera images). The performance of this denoising algorithm was compared with five popular denoising methods: bm3d, wavelet, non-local means (NL-means), total variation (TV) denoising and bilateral filter. Results show that the two-step filter had a performance that was similar to NL-means and TV filtering. Bm3d had the best denoising performance but sometimes led to blurry images. This novel two-step filter only depends on a single parameter that can be obtained from global image statistics. To reduce computation time, denoising was restricted to the Y channel of YUV-transformed images and four image segments were simultaneously processed in parallel on a multi-core processor. The astonishing visual abilities of some insect species observable under extremely dim light conditions have attracted the attention of researchers for many years ,2,3. Nochttps://github.com/csjunxu/PolyU-Real-World-Noisy-Images-Dataset, accessed on 1 March 2023) and contains 40 different scenes captured using five cameras from the three leading camera manufactures: Canon EOS ; Nikon (D800); and Sony (A7 II). This image dataset consists of 100 images and was used in this study to test the performance of a modified version of the bionic night vision algorithm described by )Th) that can be derived from global image statistics (see Equation (1)). In contrast, several parameters need to be carefully adjusted for all other filters applied in this study. For example, the NL-means filter adjusts a smoothing parameter and four other parameters  that affect denoising performance and image sharpness. Using Equation (1), it was possible to calculate the Th for ALA denoising in a way that enhanced the quality of real-world noisy images exhibiting various levels of noise and different degrees of image brightness. To account for differences in image statistics, it was necessary to take the median image brightness and a kind of noise estimate into account for the calculation of the Th parameter for ALA denoising (see Equation (1)).A major benefit of the ALA filter is that it only depends on a single threshold parameter . Recently, image denoising based on the ALA filter was successfully implemented on a Trenz Electronic FPGA hardware platform for denoising high-resolution 16-Bit mammography images (the prototype is shown in The ALA denoising described in this study is computationally demanding because the pixel-wise calculation of the diameter restricts local averaging to a small image region. To increase the processing speed, denoising was only performed on the brightness channel of YUV-transformed images. This saved 2/3 of the processing time compared to denoising all color channels of RGB images with different noise statistics that need to be taken into account for high-quality image denoising . AnotherALA image denoising relies on a single threshold parameter and operates in the spatial domain to successfully remove sensor noise from real-world camera images exhibiting various noise and brightness levels. In combination with an image-sharpening filter, this two-step image denoising method enhanced the quality of real-world images that were taken with different camera models in various light conditions. Compared to all other filters applied in this study, only one threshold parameter is required for effective noise removal using the ALA filter. The calculation of this threshold parameter only takes image brightness and an estimate of image noise into account. The denoising performance of this two-step filter is comparable to NL-means and TV denoising after visual inspection of filtered images. Compared to bm3d filtering, the two-step filter removed noise less effectively, but conserved image sharpness better. This led to similar SSIM values for both filters when ground-truth images were compared with denoised ones. In conclusion, the two-step filter exhibited good denoising performance on noisy real-world camera images, but did not perform better than more mathematically complex noise filters. ALA denoising was executed on a multi-core processor on the Y channel of YUV-transformed images, which reduced the computation time and simplified the noise estimation. This rather simple denoising algorithm also runs on FPGA hardware, which allows image processing to be executed in parallel at the level of adjacent pixels.


This case study examines using a 40-gene expression profile (40-GEP) as an independent predictor of metastatic risk in a 74-year-old male with cutaneous squamous cell carcinoma on the scalp. The patient's previous medical history included melanoma and non-melanoma skin cancers. While conventional staging methods, such as the American Joint Committee on Cancer 8th edition (AJCC8) and Brigham and Women's Hospital (BWH) staging, indicated a higher metastatic risk, the 40-GEP testing classified the patient as low risk (Class 1 result) for metastasis within three years. The patient underwent successful Mohs surgery with no evidence of perineural invasion. This case highlights the discrepancy between current staging techniques and gene expression profile testing, demonstrating the potential of the 40-GEP as a more accurate predictor of metastatic risk. The study contributes to the growing body of literature on the use of gene expression profile testing in cutaneous cancers, emphasizing the need for further research in this area to improve patient care outcomes using 40-GEP testing. Staging and categorization for cutaneous cancers act as guides to help in managing treatment options. As of now, there are several staging and categorization types used to predict the best course of action for curative procedural interventions. These methods include appropriate use criteria (AUC) for Mohs surgery , the AmeA 74-year-old male presented to the office for a Mohs procedure on a cutaneous SCC on the right superior parietal scalp Figure . The patOur case highlights a discrepancy in current staging techniques and the results of 40-GEP testing. In this case, our patient had an AJCC8 staging was T3  . This meThe 40-GEP test stratifies primary cSCC patients having one or more clinicopathologic risk factors into three biological risk groups based on risk for regional, nodal, or distant metastasis  [In this case, a more accurate assessment of the state of disease was attained through 40-GEP testing. Traditional staging methods, including AJCC8 and BWH, overestimated our patient’s risk profile. More research needs to be completed surrounding gene testing and metastatic risk. Our goal with this case is to contribute to the growing body of literature surrounding the use of gene expression profile testing in cutaneous cancer.


This study examined the efficiency of hybrid deep neural network and multivariate water quality forecasting model in aquaculture ecosystem. Accurate forecasting of critical water quality parameters can allow for timely identification of possible problem areas and enable decision-makers to take pre-emptive remedial actions that can significantly improve water quality management in aquaculture industry. A novel hybrid deep learning neural network multivariate water quality parameters forecasting model is developed with the aid of ensemble empirical mode decomposition (EEMD) method, deep learning long-short term memory (LSTM) neural network (NN), and multivariate linear regression (MLR) method. The presented water quality forecasting model (shortened as EEMD–MLR–LSTM NN model) is developed using multivariate time-series water quality sensor data collected from Loch Duart company, a Salmon offshore aquaculture farm based around Scourie, northwest Scotland. The performance of the novel hybrid water quality forecasting model is validated by comparing the forecast result with measured water quality parameters data and the real Phytoplankton data count from the aquaculture farm. The forecast accuracy of the results suggests that the novel hybrid water quality forecasting model can be used as a valuable support tool for water quality management in aquaculture industries. Many countries worldwide have documented occurrences of HABs, and their frequency may increase due to global warming and human impact on marine environments. The international community is alarmed by HABs because they not only endanger human health and marine ecosystems but also have a detrimental impact on local and regional economies. Studies have shown that precision aquaculture system can be adopted for early detection of HAB and allow ample time for aquafarmers and decision-makers to take precautionary measures2. However, continuous and accurate water quality parameters measurement using conventional methods is usually an expensive and labour-intensive process3. With the conventional sampling and testing techniques, aquaculture water quality parameters are usually approximated through laboratory analyses which are both expensive and time-consuming. These conventional aquaculture water quality monitoring and management techniques involve the collection of water samples from the relevant site of interest, water sample storage and transportation to the laboratory, as well as chemical tests and analysis at the laboratory. All these processes from water sample collection to laboratory analysis require the usage of expensive equipment and a fair amount of time before obtaining the actual water quality parameter results. In the course of these tedious and time-consuming processes, room for inefficiency and error usually arises4. This delays any corrective measures that can be taken. A precision aquaculture system relies not only on sophisticated online water quality monitoring of farm but using the data to design early warning systems5. If the water quality parameters dataset is automatically monitored and analysed through the artificial neural network (ANN) technique.A precision aquaculture system requires an efficient system for quick decision making using continuous water quality parameter data2. Therefore, it is essential to devise new aquaculture water quality data variation trends analysis and forecasting approaches and methodologies to promote high productive aquaculture businesses. Several studies have attempted to devise ways of coping with water quality contamination using both conventional numerical modelling methods, least squares support vector regression (LSSVR), NNs methods like Radial Basis Function NN (RBFNN), Back Propagation NN (BPNN) algorithms, and machine learning methods to forecast future water quality changes9. However, addressing the seasonal variation of aquaculture water quality for high yield aquaculture industry, a temporal dimension to the data analysis must be considered to guarantee an effective and efficient aquaculture water quality parameters dataset analysis and prediction of future water quality parameters. Hence, multivariate statistical approaches such as Principal Component Analysis (PCA) has been applied to determine relationship among various water quality parameters10. These geo-statistical approaches that have been applied include multivariate interpolation, multiple linear regression analysis, transitional probability, kriging, etc.11. Some of the algorithms applied for water quality parameters dataset analysis and forecasting also include Artificial Intelligence (AI) approaches such as Bayesian Networks (BN)12, Support Vector Regression (SVR)13, Neuro-Fuzzy Inference10, Decision Support System (DSS), Auto-Regressive Moving Average (ARMA)14, hybrid Sparse Auto-encoder (SAE) and LSTM (SAE-LSTM), SAE and BPNN (SAE-BPNN)15, and piecewise multivariate imputation (PWIMP) method16. However, the challenge with traditional numerical and geo-statistical approaches, LSSVR, NNs such as RBFNN and BPNN techniques is the inherent weakness of long-term dependency problem. Similarly, research has shown that the non-linear nature of water quality parameters dataset makes it rather complicated to map input/output (I/O) dataset and forecast future water quality parameters17. But further studies have shown that deep learning long-short term memory (LSTM) NN can overcome the above-mentioned weakness and can provide efficient applicability and reliability for aquaculture water quality parameter prediction22. Additionally, combining ensemble empirical mode decomposition (EEMD) method with deep learning LSTM NN has demonstrated clear advantages over traditional LSTM NNs in terms of improved water quality parameter prediction accuracy in the aquaculture environment21.Research has shown that the adverse effects of aquaculture water quality pollution can be efficiently tackled with the automation of water quality parameters dataset analysed and timely prediction of water qualityIn seeking solution to the above-mentioned challenges associated with tackling the prevailing water quality contamination in aquaculture industry, more research must be done in areas of effectiveness, efficiency, prediction accuracy, reliability and usability of the existing water quality prediction models and management methodologies in the precision aquaculture ecosystem. In this study, a novel hybrid deep learning-based forecasting model for aquaculture industry is proposed. The proposed forecasting model combines the EEMD and multivariate regression methods to decompose, learn the temporal dimensional features of the measured water quality parameters dataset signals, and establish a relationship among the different parameters before applying deep learning LSTM NN to predict the water quality. This will allow the decision-makers in aquaculture industry to better understand and manage water contamination in aquaculture environment and improve the farm productivity. In this paper we present the design of a precision aquaculture system that monitors water quality data at an aquaculture site (Loch Duart) using a dedicated Multi-parameter Trilux sensor developed by Chelsea Technologies Ltd which monitors and measures only three key Algal parameters such as Chlorophyll-a (measured at two different excitations—CHL470 and CHL530), and Turbidity. This data forms the basis for the multivariate prediction model that can predict the occurrence of HAP events at the Salmon aquafarm.The rest of the paper is organised as follows. Section presents the "23. The sensor deployment took place at one of their sheltered sites along the coast. The sensor probes installation location is depicted in Fig. Loch Duart is an independent Scottish salmon aquafarm industry, which has its’ headquarter in Scourie, Sutherland in north-west Scotland. The Salmon farming company owns and operates 8 sea-sites see Fig.  and 2 ha25. These water quality parameters are Chlorophyll-a (470 nm), Turbidity, and Chlorophyll-a (530 nm).The TriLux multi-parameter fluorometer  minutes using the TriLux sensor. The collected time series dataset for Chlorophyll-a (470), Chlorophyll-a 530), and Turbidity parameters using Chelsea Technologies’ TriLux multi-parameter sensor are plotted as line graphs in Fig. 30, and TGenerally, the 470 channel measures chlorophyll fluorescence from direct excitation of chlorophyll-a that usually strongly correlate with phytoplankton biomass in freshwater. On the other hand, CHL530 channel measures Chlorophyll fluorescence from the excitation of an accessory pigment that is found in cyanobacteria. Under normal conditions with no cyanobacteria present, there is likely to be a low level of CHL530 fluorescence emission that tracks with the CHL470 emission because Chlorophyll-a does absorb some green light (at 530 nm). Therefore, when there is a cyanobacteria bloom occurrence in the aquaculture water body, it is expected to notice a divergence in these signals. The high correlations between these three data signals and the cyanobacteria in freshwater, as shown in Section "27 is applied to achieve a better estimation effect that can accurately approximate the missing data values. In data analysis, linear interpolation algorithm takes the ratio of two known data-points and one unknown data-point as a linear relationship. Therefore, to obtain the missing, unknown water quality parameter value, linear interpolation technique applies the slope of the presumed line to compute the time-series dataset increment. Hence, the dataset is completed.Non-linear, non-stationary water quality parameters time-series dataset defects usually result in excessive deviation between the measured original water quality parameters values and the forecast results. The basis of accurate time-series analysis and the development of effective and reliable predictive models is high-quality sample data. To provide concise, accurate dataset for the forecasting model and improve forecasting accuracy, the measured water quality parameters dataset was carefully pre-processed. Usually, the issue of missing data is inevitable with automatic water quality sensor monitoring systems. In this case, the water quality parameters such as Chlorophyll-a (470), Chlorophyll-a (530), and Turbidity were automatically measured throughout the days and nights at 10 min’ intervals. To fill in any missing data, filling-in approach called linear interpolation algorithmThe nature of the measured parameters.An installed automated freshwater TriLux multi-parameters sensor monitoring system at the Loch Duart Salmon offshore aquaculture farms measures time series water quality parameters at a constant time interval everyday which can be denoted as For any missing time series water quality parameters data at any given moment, the linear interpolation algorithm firstly finds the two closest moments entclass1pt{minima28 has been widely used as a data analysing technique, which is also described as the quotient of co-variance and standard deviation between two variables. The Pearson’s correlation coefficient system was used after cleaning and pre-processing the TriLux multi-parameters sensor measured time series water quality parameters, to analyse the existing correlations between the required parameters. Table This study applied the Pearson’s correlation coefficient technique to analyse the existing correlations between the TriLux multi-parameters sensor measured time series aquaculture water quality parameters such as Chlorophyll-a (470), Chlorophyll-a (530), Turbidity, and the Phytoplankton data count at the Loch Duart Salmon offshore aquaculture farms. To better understand the existing correlations between two variables, the Pearson’s correlation coefficient techniqueBoth Table On the other hand, Turbidity maintains an extremely strong positive correlation of 0.9251 with CHL470 and 0.9741 with CHL530 as shown in both Table 30. The multivariate linear regression method is a technique widely applied to estimate any linear relationship that exists between one or more independent variables and a dependent variable. In this study, the multivariate linear regression was applied to model and establish the relationship between the multiple independent water quality parameters and the dependent parameter. A general multivariate linear regression equation represented by the model below was used:Studies have shown that statistical methods like regression models are the best tools for studying any existing relationship between independent and dependent variables, especially with a diminutive data sizeBy applying Matrix form, the above multiple linear regression equations can be represented as shown below:31, the regression coefficients The matrix From the known regression coefficient Therefore, given a historical water quality parameters dataset, The EEMD method and deep learning LSTM NN were merged to form the Hybrid multivariate water quality parameters forecasting model. The basic implementation processes of EEMD method and LSTM deep learning NN technique are described in detail in Sections "27. Therefore, the actual underlying components of the water quality time series data can be represented by the ensemble mean. In other words, EEMD method sums up the components and adopts the average as the true decomposition results. Finally, the result of decomposition solves the mode mixing drawbacks associated with conventional EMD method. It is a useful method for extracting underlying and crucial components from the water quality time series data.EEMD is a noise-assisted time-series dataset analysis method. In EEMD technique of time-series dataset analysis, Gaussian white noise is added to enable the separation of contrasting time-series scales, which in turn, leads to improved decomposition efficiency of the EMD method. The introduced white-noise comprises of components of disparate scale which would systematically fill the entire time–frequency space. The disparate scale components of the signal are spontaneously projected onto proper scales of reference initiated by the Gaussian white-noise as the systematically distributed white-noise is introduced to the signal. Since all the decomposed components of the introduced Gaussian white-noise consists of both the signal and the introduced white noise, all the individual trials usually end up with noisy results. However, the white-noise can be almost completely cancelled out with the aid of ensemble mean of whole trials because the white-noise in each of the trials are unique in different trialsFor the CHL470, CHL530, and Turbidity time-series data, the EEMD method follows certain procedure which can be described as follows.Stage 1: Initialize an ensemble number Stage 2: Perform the Stage 3: Determine all the local minima and maxima of Stage 4: Compute the mean Stage 5: Calculate the difference Stage 6: If the properties of the intrinsic mode function (IMF) are satisfied by the The two properties of IMF are described as follows: (i) the number of the zero crossing and extrema must either equal or differ at most by 1 over the entire data Stage 7: Separate the residue Let the residue Stage 8: By adding a different noise in each trial, repeatedly execute Stage 2 to Stage 7 until Stage 9: Determine the Therefore, the original Chlorophyll-a time series data is efficiently decomposed through EEMD method into 32. Equations below illustrates the calculation processes involved in deep learning LSTM NN architecture.Deep Learning LSTM NN is a special type of Recurrent NN (RNN) with significant improvement and the ability to learn long-term dependencies which gives it an advantage over other ANNs such as BPNN, RBFNN, etc. RNN is a deep learning model specifically designed to handle the analysis and processing time-series datasets. Figure Forget gate equation:shown in  through shown in .Input gate equations:Output gate equations:Cell state equation:The proposed hybrid EEMD-LSTM deep learning NN based water quality parameters forecasting model is shown in Fig. 1,1, LSTM1,2, …, LSTMm,1, up to LSTMm,n). Individual hidden layer of the stacked LSTM is equipped with numerous memory cells which earns the proposed forecasting model deep learning NN technique.Then, each IMF and residual item is normalized and used for forecasting at the hidden layer of the deep learning LSTM NN as demonstrated in Fig. For the evaluation of the proposed hybrid EEMD-LSTM deep learning water quality prediction model, four performance evaluation metrics were introduced to evaluate its prediction accuracy. These metrics include MAE, MSE, RMSE, and MAPE. The mathematical formulae are expressed as follows:In , 21), , , and 2323 above,33. During the data signals decomposition process, summation of the low-frequency IMFs was used to extract the EEMD trend. Finally, the EEMD technique extracts strongly correlated set of sub-band signals which are used in decomposition process of the novel hybrid forecasting model.An hourly centred moving average values is applied in this study to the real water quality parameters time-series dataset from Loch Duart Salmon offshore aquaculture farms. Additionally, decomposing the TriLux multi-parameter sensor measured Chlorophyll-a (470), Turbidity, and Chlorophyll-a (530) contents time-series data with the EEMD technique is an integral part of the developed novel hybrid forecasting model. The EEMD method is a reliable and efficient technique for non-stationary, non-linear time-series signal decomposition. The steps involved in EEMD technique of time-series data signal decomposition processes as described in Section "The pre-processed real measured dataset is divided into two sets: seventy-five percent (75%) as a learning data sample (training dataset) and twenty-five percent (25%) for testing of the proposed novel hybrid forecasting model. Figure The forecast results were compared with the real monitored water quality parameters data from the Salmon offshore aquaculture farms. Figure The improved forecasting accuracy of the proposed novel hybrid forecasting model is due to the applied EEMD technique which allows the forecasting model to reflect the temporal characteristics of the measured time-series Chlorophyll-a (470), Turbidity, and Chlorophyll-a 530) concentration dataset. This is achieved with the aid of the multi-feature selection process used by the EEMD technique which enables the selection of a set of stable IMFs which strongly correlate with the actual measured Chlorophyll-a (470), Turbidity, and Chlorophyll-a (530) data and integrate them into inputs for the deep learning LSTM NN. The forecast error statistics of the proposed novel hybrid model were obtained from , 21), , , and 2323 for MA0 concent15. The tabulated error statistics indicate that our proposed novel hybrid EEMD–MLR–LSTM NN model outperformed the other closely related hybrid models as shown in Table 15, the hybrid SAE-LSTM model demonstrated the least error in terms of prediction accuracy. However, the tabulated error statistics in Table In Table This study presents the development of a novel hybrid water quality forecasting model based on monitored TriLux multi-parameter sensor water quality parameters through the application of specialised EEMD method, MLR, and deep learning LSTM NN. The actual experimental real water quality data from Loch Duart Salmon aquaculture farms show that the proposed model provides useful future water condition forecast outcome with high accuracy. The forecast result in Fig.


Ultra-thin choledochoscopes and holmium laser lithotripsy were used more frequently in the LATEST group . Enhanced surgical techniques (correction of the cystic duct-CBD junction and the trans-infundibular approach) were also performed more frequently in the LATEST group. More patients in the LATEST group received transcystic LBDE . The LATEST group had significantly higher stone clearance rates , reduced post-operative morbidity and shorter post-operative hospital stay . Conclusions: LATEST describes four key factors that can be used when performing LBDE. The adoption of LATEST in LBDE is associated with an increased stone clearance, a higher transcystic exploration rate and reduced post-operative morbidity.Single-stage management of choledocholithiasis with concomitant gallstones consists of performing either laparoscopic bile duct exploration (LBDE) or intra-operative endoscopic retrograde cholangiopancreatography at the same time as laparoscopic cholecystectomy. Transductal LBDE is associated with significantly higher post-operative morbidity, longer operative times and longer hospital stay when compared to transcystic LBDE. The aim of this study was to report the transcystic exploration rate and post-operative outcomes from LBDE before and after implementation of the LATEST  principles. Methods: A retrospective review of 481 consecutive patients between February 1998 and July 2021 was performed. Patients were assigned into two groups determined by whether they were operated before or after the implementation of LATEST. Data collected included pre-operative demographic information, medical co-morbidity, pre-operative investigations, and intra-operative findings . Outcomes of this study were the transcystic exploration rate, stone clearance rate, conversion to open surgery, post-operative morbidity and mortality, and length of post-operative hospital stay. Results: The The online version contains supplementary material available at 10.1007/s00464-022-09667-z. Common bile duct (CBD) stones are present in up to 15% of patients with symptomatic gallstones . Single-Biliary Surgery 2.0 and Leveraging Access to Technology and Enhanced Surgical Technique (LATEST) in LBDE  and abdominal imaging. Data collected included pre-operative demographic information, medical co-morbidity, pre-operative investigations, intra-operative findings  and post-operative outcomes. Clinical presentation was classified as pancreatitis, hyperbilirubinaemia, deranged LFTs and dilated CBD (≥ 8 mm on pre-operative imaging). Pancreatitis was diagnosed as per the Atlanta classification [A retrospective review of a prospectively collected database of 481 consecutive patients who underwent LBDE at a single centre between February 1998 and July 2021 was performed. Ethical approval was not required for this type of study. All operations were performed or supervised by the senior surgeon (AI). After review of medical records, all patients were assigned into two groups determined by whether they were operated before or after the implementation of LATEST. Patients who underwent LBDE between February 1998 and February 2014 were grouped as ‘Outcomes of this study were the transcystic exploration rate, stone clearance rate, conversion to open surgery, post-operative morbidity and mortality and length of post-operative hospital stay. Stone clearance was confirmed by choledochoscopy or completion cholangiogram if a proximal view of the intra-hepatic ducts was not obtained intra-operatively. Failure of LBDE was defined as patients who required conversion to open surgery or those with retained CBD stones known intra-operatively (failure to extract stones during procedure) or diagnosed within 12 months of surgery. Patients with retained stones were managed with post-operative ERCP. Bile leaks were graded according to the 2011 International Study Group of Liver Surgery (ISGLS) classification [LATEST group, the transcystic route was the approach of choice and attempted first routinely, whereas in the pre-LATEST group, the transcystic route was attempted only in selected cases .The surgical approach to the bile duct was either transductal via choledochotomy or transcystic and has previously been described , 21–23. Patients were positioned using the French technique for all operations, with the surgeon standing between the legs and the assistant to the left side of the patient . LaparosOur technique for transductal LBDE has previously been described.  The CBD Prior to 2014, intra-operative cholangiogram and transcystic access for LBDE was attempted with the gallbladder still attached to the liver. Transcystic LBDE would generally only be attempted if there was favourable anatomy, and the cystic duct was dilated. Even then, the opening of the cystic duct would have to be gently dilated using Maryland or Johan forceps in order to accommodate the 5-mm flexible choledochoscope. After 2014, once the critical view of safety had been achieved and the cystic artery ligated, the gallbladder was fully mobilised from the liver. The cystic duct was carefully skeletonised down to its junction with the bile duct, and the infundibular-cystic duct junction was then retracted through the abdominal wall using an Endoloop  and Endo Close™  to create the optimal cysticocholedochal angle.  Since 20(1) Ultra-thin (~ 3 mm) choledochoscopes (supplementary file: video 1). A non-dilated cystic duct would usually preclude transcystic access using a 5-mm choledochoscope. The use of thinner, more flexible and readily available single-use choledochoscopes enabled transcystic access even when the cystic duct was not dilated  Lithotripsy-Assisted Bile duct Exploration by Laparoendoscopy (LABEL) (supplementary file: video 2). We have previously shown that the use of lithotripsy techniques as an adjunct to LBDE has increased transcystic exploration rates  Correction of the cysticocholedochal angle (supplementary file: video 3). Following dissection of Calot’s triangle, having satisfactorily achieved the critical view of safety and ligation of the cystic artery, the gallbladder was fully mobilised from the liver. The cystic duct was completely skeletonised to the cysticocholedochal junction and the infundibular-cystic duct junction retracted through the abdominal wall  Trans-infundibular approach (TIA) to the CBD (supplementary file: video 4). A frozen hepatic hilum secondary to chronic inflammation and fibrosis is encountered in approximate 5% of patients who are undergoing LBDE  and GraphPad Prism 9  statistical package.Normally distributed continuous data are reported as mean (with standard deviation), whereas skewed or ordinal data are reported as medians (with inter-quartile range). Categorical variables are expressed as number and/or frequencies (%). Statistical analysis of categorical data was performed using Chi-square or Fisher’s exact tests, while the unpaired t test or Mann–Whitney test were used for parametric or nonparametric continuous data where appropriate. A pre-LATEST group contained 237 patients who underwent LBDE prior to February 2014 and the LATEST group comprised of 244 patients who were operated on after February 2014. The two groups were similar in age and gender (Table pre-LATEST group had significantly higher pre-operative American Society of Anaesthesiologists (ASA) scores when compared to the LATEST group (p = 0.0113). This was likely due to proportionately more patients having ischaemic heart disease and hypertension, however, only the difference in hypertension between the two groups reached significance. A related finding was that significantly more patients were taking anti-platelet medication in the pre-LATEST group (p = 0.0436). All other major co-morbidities were similar between the two groups. The proportion of patients presenting with deranged LFTs and pancreatitis were similar between the two groups. More patients in the pre-LATEST group presented with hyperbilirubinaemia ; however, pre-operative bilirubin was not significantly different between the two groups . Pre-operative ALP, but not ALT, and pre-operative CBD diameter was also significantly higher in the pre-LATEST group. Within the whole series, 91 (19%) patients had undergone failed ERCP prior to surgery. Failure to cannulate the CBD was the reason for failure in 19 (4%) patients, whereas in 72 (15%) patients there was failure of stone extraction. There were significantly more patients who underwent a failed pre-operative ERCP prior to LBDE within the pre-LATEST group. From the 48 (20.3%) patients within the pre-LATEST group who had a pre-operative ERCP with failed stone extraction, only three (6%) went on to have transcystic LBDE. In contrast, within the LATEST group, 24 (9.8%) patients had an unsuccessful pre-operative ERCP due to failed stone extraction, however, 16 (67%) went on to have transcystic clearance laparoscopically (p < 0.0001).For the study period, 481 patients were eligible and included for analysis. The pre-LATEST and LATEST groups are summarised in Table LATEST group when compared with the pre-LATEST group . Although the median number of stones were similar between the two groups, the median size of the largest stone was slightly larger in the pre-LATEST group . Due to uptake and availability at our institution, ultra-thin choledochoscopes were also used much more frequently in the LATEST group . Of those that underwent transcystic LBDE, an ultra-thin choledochoscope was not used in any patients within the pre-LATEST group (n = 26), but was used in 210 (46.7%) patients in the LATEST group (p < 0.0001). Within the last 100 patients of the series, 94 underwent transcystic LBDE, and of those, 67 (71%) patients underwent transcystic exploration with an ultra-thin choledochoscope. Similarly, the LABEL technique was only available at our institution after implementation of the LATEST principles. LABEL was used in 45 (18.4%) patients within the LATEST group compared to none in the pre-LATEST group (p < 0.0001). Enhanced surgical techniques were also performed more frequently in the LATEST group. Correction of the cystic duct-common bile duct junction, using the technique as described, was implemented prior to 2014. It was adopted in just 38 (16.0%) patients within the pre-LATEST group compared to all 244 patients within the LATEST group (p < 0.0001). TIA to the CBD was only described after February 2014 and was used in 13 (5.3%) patients within the LATEST group. In all these patients, a complete  cholecystectomy was achieved after clarification of the anatomy. The approach to the CBD was significantly different between the two groups, with the transcystic route being achieved in just 26 (11%) patients in the pre-LATEST group compared to 210 (86.1%) patients in the LATEST group (p < 0.0001). A direct consequence of the reduction in transductal exploration was observed as reduced requirement for T-tube drainage , antegrade stent use  and intra-abdominal drain use  within the LATEST group. Operative times were similar between the two groups (p = 0.3647).Intra-operative data for the LATEST group , and there was a trend towards increased post-operative ERCP use in the pre-LATEST group, although this did not reach significance . The reasons for failure of LBDE with their relative frequencies are summarised in Table LATEST group. Specifically, there was less bile leak  and post-procedural pancreatitis  within the LATEST group. There were no CBD injuries secondary to laser lithotripsy in either group. As expected, median length of post-operative hospital stay was significantly reduced in the LATEST group .Post-operative outcome data for the two groups are displayed in Table At our institution, the adoption of LATEST in LBDE was associated with an increased stone clearance rate and a higher proportion of patients who received transcystic exploration, resulting in significantly improved post-operative outcomes. Choledocholithiasis is a common condition and this paradigm shift in practice has led to reduced post-operative morbidity  and shorter post-operative hospital stay.Biliary Surgery 2.0 and Leveraging Access to Technology and Enhanced Surgical Technique (LATEST) in LBDE [Leveraging access to technology includes using thinner and more flexible choledochoscopes combined with fragmentation techniques such as laser or electrohydraulic lithotripsy. Prior to lithotripsy techniques, transcystic LBDE was limited to smaller CBD stones that were amenable to flushing into the duodenum or extraction via the cystic duct. In 2017, we published our initial results using holmium laser lithotripsy (HLL) during what we coined as the Lithotripsy-Assisted Bile duct Exploration by Laparoendoscopy (LABEL) technique [Enhanced surgical technique refers to full mobilisation of the gallbladder followed by complete dissection of the cystic duct to the cysticocholedochal junction. The cystic duct is then retracted through the abdominal wall to create an optimal 90° cystic duct-common bile duct angle prior to attempting cannulation [During the evolution of LBDE at our institution over that last 23 years, we have changed practice and adapted the technique in order to increase the transcystic exploration rate. We recently proposed the concepts of  in LBDE , 17, 28.echnique . Since technique . Withoutechnique –31. Moreechnique , 32. Oveechnique . Similarechnique , 34. Enhnulation . Enhancenulation .LATEST group, the negative exploration (negative choledochoscopy) rate was almost double compared to the pre-LATEST era, with these patients having a very low incidence of post-operative morbidity. The lower threshold to perform transcystic choledochoscopy in such equivocal cases should be weighed up against the extra cost of the disposable ultra-thin choledochoscope .The benefits of transcystic, over transductal, LBDE have been well described at our institution and in the literature –15. The Our technique to correct the cysticocholedochal angle, as described, involves the following sequence: (1) dissection of Calot’s triangle to achieve the critical view of safety followed by ligation of the cystic artery (2) mobilisation of the gallbladder from the liver 3) complete skeletonization of the cystic duct to the cysticocholedochal junction (4) retraction of the infundibular-cystic duct junction through the abdominal wall  was performed using the trans-infundibular approach (TIA) to the bile duct in February 2014. This date was chosen to define the LATEST era. Another major limitation of a ‘before and after’ study of a single series is that any learning curve associated with the procedure is likely to have an effect on outcomes. Even without any significant change to practice, the second half of a series will likely yield better outcomes when compared to the first half, which may contain part or all of the learning curve. This sample selection could have introduced bias, however, the cohort of patients from this study represents an ‘all-comers’ series who unselectively underwent LBDE at our institution. Despite a learning curve in transductal and transcystic LBDE, the former requiring advanced skills in laparoscopic suturing and the latter advanced skills in laparoendoscopy, this study demonstrates that four principles have been largely responsible for increasing the rate of transcystic LBDE, which is independent to its learning curve. Further research is required to determine the optimal treatment strategy for managing choledocholithiasis with concomitant gallstones. Most of the available randomised trial data is dated, with the LBDE arms mainly performing transductal clearance . Prospective randomised studies comparing contemporary (mainly transcystic) LBDE to alternative laparoendoscopic strategies (namely pre-operative ERCP followed by laparoscopic cholecystectomy and laparoscopic cholecystectomy with intra-operative ERCP) should be the focus of future research.Leveraging Access to Technology and Enhanced Surgical Technique describe four key factors that can be used when performing LBDE. The adoption of LATEST in LBDE is associated with an increased stone clearance and a higher transcystic exploration rate. It is well known that patients undergoing transcystic, rather than transductal, LBDE for choledocholithiasis with concomitant gallstones have significantly improved outcomes. Transcystic clearance rates over 90% can be achieved in high volume centres and the primary goal of surgeons undertaking LBDE should be to clear the bile duct transcystically.Supplementary file1 (MP4 34843 KB)Supplementary file2 (MP4 70000 KB)Supplementary file3 (MP4 65110 KB)Supplementary file4 (MP4 62086 KB)Below is the link to the electronic supplementary material.


Perspective, we discuss criteria for defining a new disease entity or variant of a recognized disease or disorder. We do so in the context of the current topography of the BCR::ABL-negative myeloproliferative neoplasms (MPNs) where two new variants are reported: clonal megakaryocyte dysplasia with normal blood values (CMD-NBV) and clonal megakaryocyte dysplasia with isolated thrombocytosis (CMD-IT). The cardinal feature of these variants is bone marrow megakaryocyte hyperplasia and atypia corresponding the WHO histological criteria for primary myelofibrosis (myelofibrosis-type megakaryocyte dysplasia-MTMD). Persons with these new variants have a different disease course and features from others in the MPN domain. In a broader context we suggest myelofibrosis-type megakaryocyte dysplasia defines a spectrum of related MPN variants including CMD-NBV, CMD-IT, pre-fibrotic myelofibrosis and overt myelofibrosis, which differ from polycythemia vera and essential thrombocythemia. Our proposal needs external validation and we stress the need for a consensus definition of the megakaryocyte dysplasia which is the hallmark of these disorders.In this  Subjects with CMD-NBV had a significantly higher incidence of post-diagnosis thrombosis compared with persons with ET or PV (3.9 events per 100 subject-years versus 1.7 and 2.7). In contrast, subjects with CMD-IT had a significantly lower risk of thrombosis compared with persons with ET or pre-fibrotic MF [1.03  events per 100 subject-years versus 3.09 and 2.09].None of the 15 subjects with CMD-NBV had signs of disease progression after a median follow-up of more than 8 years, Subjects with CMD-IT lived longer than those with pre-fibrotic MF and those with overt- MF  0.23, 0.75], CALR mutations and a lower JAK2V617F allele burden compared with persons with PMF. They also have a lower frequency of genetic variants correlated with risk of developing PMF such as the 46/1 haplotype and VEGFA rs3025039 polymorphism [Distinguishing features of the new variants we propose are of considerable clinical import. Moreover, they reinforce the concept of the MPNs as a spectrum of disorders promoted by specific constitutive and genetic features. For example, subjects with CMD-IT are more often female, have a higher frequency of type-2/type-2-like CMD-NBV is a special disease variant characterized by lack of hematological abnormalities or marginally elevated blood values. Subjects are mostly diagnosed in the context of thromboses. 13 of our 15 subjects with CMD-NBV had a synchronous symptomatic thrombotic event including portal vein thrombosis, Budd-Chiari syndrome, peripheral arterial thrombosis, myocardial infarction, spleen infarction or an incidentally detected portal cavernoma at diagnosis.CMD-NBV forces us to rethink the generalizability of diagnostic reasoning in MPNs. The WHO criteria for the classical MPNs starts with considering an abnormal hematological value. In contrast, in CMD-NBV the diagnosis is triggered by clinical features. Positive predictive value of MPN diagnosis depends on patient- and practice setting-related co-variates. This results in a high level of uncertainty in CMD-NBV diagnostic reasoning requiring ad hoc rules to guide physicians to move from a circumstantial diagnostic metric to a metric based on clinical features, histology and genetics, and suggests the real frequency of CMD-NBV may be much greater than thought.myelofibrosis-type megakaryocyte dysplasia (MTMD) and to highlight its relevance we conceptualize that this morphology identifies a disease category among MPNs.A further advancement in the MPN field of the introduction of the new disease variants is that they share the histological megakaryocyte characteristics typical of PMF, and that megakaryocyte morphology deviation was a major criterion to diagnose them. To define these megakaryocyte characteristics we now propose to introduce the term The theory of MTMD has been accepted in the 2022 WHO  and InteGATA1 mutations selectively decrease GATA1 in megakaryocytes and induce myelofibrosis in mice and a bone marrow histology like primary myelofibrosis in humans [This MTMD paradigm, born from an acute morphological vision, is now supported by biological evidence. In fact, hypo-morphic n humans . Also, mn humans . Recentln humans . Finallyn humans .The MTMD concept contrasts with megakaryocyte dysplasia in other myeloid disorders such as myelodysplastic syndromes (MDS). Histological criteria distinguishing megakaryocyte dysplasia in MDS from that in PMF is proposed but unvalidated . A usefuMPN, unclassifiable addressed us to hypothesize a broad category of MPNs bearing different phenotypes may be included in an unique category according to the megakaryocyte morphology. Agreeing on MTMD as a category needs standardization of relevant bone marrow features. Since the histological assessment of bone marrow in MPNs remains constrained by a reliance on subjective and qualitative criteria, we emphasize the use of more precise methods. Computational methods designed to systematically capture the key morphological characteristics of megakaryocytes were proved able to associate with particular MPN subtypes [In conclusion, the recognition of 2 new variants of MPN including subjects previously considered under the rubric of subtypes , 14. Thi


Mueller matrix (MM) microscopy has proven to be a powerful tool for probing microstructural characteristics of biological samples down to subwavelength scale. However, in clinical practice, doctors usually rely on bright-field microscopy images of stained tissue slides to identify characteristic features of specific diseases and make accurate diagnosis. Cross-modality translation based on polarization imaging helps to improve the efficiency and stability in analyzing sample properties from different modalities for pathologists.In this work, we propose a computational image translation technique based on deep learning to enable bright-field microscopy contrast using snapshot Stokes images of stained pathological tissue slides. Taking Stokes images as input instead of MM images allows the translated bright-field images to be unaffected by variations of light source and samples.We adopted CycleGAN as the translation model to avoid requirements on co-registered image pairs in the training. This method can generate images that are equivalent to the bright-field images with different staining styles on the same region.Pathological slices of liver and breast tissues with hematoxylin and eosin staining and lung tissues with two types of immunohistochemistry staining, i.e., thyroid transcription factor-1 and Ki-67, were used to demonstrate the effectiveness of our method. The output results were evaluated by four image quality assessment methods.By comparing the cross-modality translation performance with MM images, we found that the Stokes images, with the advantages of faster acquisition and independence from light intensity and image registration, can be well translated to bright-field images. Pathologists need to access them in different ways, which may require preparing multiple imaging systems or changing hardware. Cross-modality translation techniques can blend microscopy and computation to transform images between microscopic imaging systems.,Bright-field microscopy is often considered the gold standard in histological analysis. It is often combined with other microscopic modalities to probe the sample from different levels. Some previous studies have reached the transformation to bright-field contrast from other microscopic modalities, e.g., holographic microscopy.–––In addition to only simply transforming between different microscopic modalities, deep learning-based cross-modality microscopic translation can also algorithmically create a physical transformation on a sample, e.g., for virtual staining of label-free tissue samples.In summary, we measured already-existing tissue slides for model training and no other preliminaries are required. We adopted deep learning from the point-of-data-driven method, statistical mapping between image domains of snapshot MM microscopy, and bright-field microscopy aiming at the cross-modality microscopic translation. Our contributions can be summarized as follows.•We propose a “bright-field snapshot MM microscopy” method that transforms Stokes images obtained by MM microscopy to bright-field microscopy images. It is demonstrated on paired images of H&E stained breast and liver tissues. This method is not sensitive to the incident polarization states of light and resolutions of polarimetric images, which makes the system more robust and practical.•We demonstrate that the transformation performance using Stokes images as input is close to the results of MM images. The Stokes polarimetry is unaffected by system and sample instabilities and allows faster image acquisition compared to MM polarimetry, so it is superior for improving the system stability and transformation efficiency in MM microscopy.•We employ the cycle generative adversarial network (CycleGAN)We organize the sections in this paper as follows. Section 22.1For image collections, we used the dual DoFP polarimeter-based full MM microscopy (DoFPs-MMM).2.2,,–To validate the method on different tissues, we collected liver samples from 50 patients, breast samples from 22 patients and lung samples from 9 patients. Each patient represents a subject. The polarimetric properties of these samples have been analyzed in previous studies.2.3MM contains all polarimetric properties about the samples. Considering the comprehensiveness of the information, we utilized all elements in MM. There is a significant correlation among the 16 elements in the MM, leading to unnecessary data duplication (redundancy).The Stokes images were obtained by a single shot using DOFPs-MMM. The decomposed MM images and Stokes images were used as input, respectively, and the bright-field images were used as ground truth. When performing cross-modality translation on images of H&E stained slices, paired images were required to verify the transformation performance of the model. A speeded-up robust feature algorithm-based feature point detection image registration technique2.4Before training a cross-modality translation deep learning model, a dataset containing a large amount of polarimetric images and bright-field images needs to be built first. Paired images were used for breast tissues and liver tissues, while unpaired images were used for lung tissues. The patches in the training set and the patches in the test set did not overlap with each other and were from different patients. The division of the dataset is given in the “training” and “testing” columns of The experiments were carried out on a desktop computer, of which the operating system is Ubuntu 18.04 with kernel 5.4.0. We used PyTorch 1.12.1 and Python 3.8.5 to train models and implemented them on two NVIDIA Geforce RTX 2080Ti cards. Each model was trained with a batch size of 4 for 100 epochs, where the first 50 epochs were with the initial learning rate and the last 50 epochs linearly decayed learning rate to zero.3Aiming at the task of cross-modality translation from polarimetric images (including MM images and Stokes images) to bright-field images, we used the CycleGAN model,CycleGAN contains both generators and discriminators. The generator Similarly, the translation of a bright-field image to a polarimetric image contains both the adversarial loss of The architecture of the cross-modality translation model adopts ResNet-based on a generator with nine residual blocks, which also performs downsampling and upsampling operations, as shown in Polarimetric images (including MM and Stokes images) represent the polarization properties of a sample, which are closely associated with its microscopic structures. The contrast of bright-field microscopy images is caused by the light attenuation in different regions of microstructures. Therefore, there is a strong correlation between the input data (polarimetric images) and the generated data (bright-field images). Compared to bright-field microscopy, polarization-based measurement methods have the capability to detect high-dimensional information and specific structural characteristics. The proposed cross-modality translation model is able to extract key features relevant to microscopic structures from the input high-dimensional polarimetric data and then gradually reconstruct the bright-field image based on them.44.1We first applied the proposed model on the liver and breast sample images acquired by illuminating with single 45 deg linear incident polarization state. It could validate the feasibility of CycleGAN on the task of cross-modality translation from Stokes images to bright-field images by paired images of the two samples. An input source image ,Then we separately selected the Stokes images obtained from six SOPs shown in We also translated the MM images to bright-field images for comparison with the generated results of Stokes images. We fed images processed by PCA with the first channel and the first three channels into our model. The output bright-field images were evaluated quantitatively, as given in We need to train the models separately for liver and breast tissues, which requires a large amount of data and consumes computational resources. Transfer learning enables applying knowledge or patterns learned on a domain to a different but related domain.The history of training losses can reveal the performance of the deep model during the training phase. Our goal is to generate bright-field images that match the target as closely as possible. The pixel-wise similarity loss . TTF-1 is a nuclei marker with preferential expression in thyroid, lung, and brain structures of diencephalic origin. It is frequently used in the search for the primary origin of metastatic endocrine tumors.The results of similarity evaluation are listed in 5In this work, we presented a cross-modality translation method that can obtain bright-field image of different staining styles in snapshot Stokes imaging. It is not only time-, labor-, and cost-saving but also avoids errors caused by light intensity instability and image misregistration in the MMM. The application is based on CycleGAN without pixel-wise paired examples in the training. This can reduce the workload in the data preparation and is especially essential when the equivalent ground truth is difficult to acquire or even unavailable. We first used MM and bright-field microscopy to capture images in the same region of stained sections to demonstrate the performance of the deep learning model, and then used the two microscopic devices to take H&E stained sections and IHC stained adjacent sections respectively to achieve cross-modality translation with computational staining on Ki-67 and TTF-1 IHC staining styles. Using this approach, a DoFP polarimeter-based MMM can simultaneously acquire polarimetric images and bright-field images of multiple staining styles in the same FOV in a single shot. In the experiments, we trained and tested on a collection of stokes images at both There are many other unexplored possibilities for cross-modality translation based on polarimetric images. It has been demonstrated that the wavelength of light has an effect on the polarimetric properties of the sample.


Improving the existent effective treatments of depression is a promising way to optimise the effects of psychological treatments. Here we examine the effects of adding a rehabilitation type of imagery based on exergames and dynamic simulations to a short behavioural activation treatment of depression. We investigate the acceptability and the efficacy of an exergame-augmented dynamic imagery intervention added to behavioural activation treatment and associated mechanisms of change.In a two-arm pilot randomised controlled trial, the acceptability and preliminary efficacy of an exergame-augmented dynamic imagery intervention added to behavioural activation treatment for depressed individuals will be assessed. Participants (age 18–65) meeting criteria for depression are recruited by media and local announcements. 110 participants will be randomly allocated to behavioural activation plus imagery group or to standard behavioural activation group. The primary outcome is depressive symptom severity (Beck Depression Inventory II) and secondary outcomes are anhedonia, apathy and behavioural activation and avoidance. The outcomes are assessed at baseline, mid treatment, posttreatment and 3-month follow-up. Moderation and mediation analyses will be explored. An intention-to-treat approach with additional per-protocol analysis will be used for data analysis. Major depressive disorder (MDD) is a common mental health problem that results in severe impairment of the life of affected individuals . AlthougFinding efficient ways to treat depression has always been a preoccupation for both researchers and clinicians. Despite significant efforts, the efficacy of treatments for depression did not significantly improve in time . TargetiMental rehearsal interventions are considered promising stand-alone or added-on treatments for depression –9. RecenWe suggest that a major source of potential improvements for mental imagery interventions comes from paying more attention to the contribution of the ongoing states of the sensorimotor and affective brain systems  to mental simulations. Considering the characteristics of the sensorimotor and affective brain systems involved in the mental construction of those experiences results in several advantages for imagery interventions. First, the differences in the states of the sensorial, affective, and motor systems recruited for simulation should be considered during imagery interventions for depressed individuals. For instance, depressed individuals show large differences in the state of modality-specific brain systems, having attenuated excitation of the motor cortex , 13 and Here we propose that we may use these advantages and significantly improve imagery interventions by focusing on enhancing the embodiment of mental rehearsal in imagery-based treatments for depressed individuals. A large body of research suggests that the effect of mental simulations on emotion and behaviour heavily depends on their embodiments, or the efficient recruitment of specific sensorimotor and affective modalities in mental simulations by attention, verbal, and memory controls . For ins™ games). Previous research showed that using exergaming results in the augmentation of motor (kinesthetic) imagery [A promising way to support the embodiment of simulations of action in depressed individuals is by using remote kinematics in the form of exergaming  requires mimicry of simulated movements . Previou stimuli . Similar stimuli  motor le stimuli  and beha stimuli . Moreove stimuli .Given that imagery methods added to behavioural activation treatments are promising for the treatment of depression , 9 and tdynamic simulation routine: how to support mental imagery of activities through gestures, language, and attention. Then, the patients undergo an exergame for 5 to 10 minutes and an “actfulness” exercise focusing on feelings of movement and motor simulation. After the exercise, the participants dynamically imagine a planned activity. In session two, patients are thought to restructure action memories by focusing on movements. Deficient action simulations are rehabilitated by (a) partial movements ; (b) linguistic supports . Thus, it is a rehearsal training that mixes actual and mental practice [gestures, language, and episodic memory as controls of simulation, and is applied to promote the use of motor simulations in everyday life.Starting from the idea that action cognition and motor imagery deficits are stable alterations in depressed individuals –43 we usto open; ), (c) ento open; ), and  on severity of depressive symptoms. Second, we investigate whether adding the dynamic imagery intervention to behavioural activation treatment has any effect on secondary outcomes such as anhedonia, apathy, and vividness of imagery. Third, we investigate the moderators and mediators of the effects of the intervention.™). We recruit participants by online media, advertisements, and by contacting local psychiatrists. After the online screening and baseline assessment, participants are randomised to either BA or BA plus T-RAC. Then the participants are enrolled in the treatment. Participants complete a weekly assessment, one assessment of mediators at week six, one assessment after treatment and one assessment at three months. The consort flow for the Study is presented in The study is a two-arm phase II randomised controlled trial (RCT) with a parallel design to compare a short behavioural activation (BA) treatment with BA plus dynamic imagery enhanced by exergames . Informed consent is required from participants before enrollment in the study. The results will be submitted for publication in peer-reviewed journals and presented at conferences.Trial registration number. This trial was registered in the Clinical Trials Register: NCT05625230.The recruitment of the participants will follow the CONSORT chart that will guide the flow of the participants. 110 participants will be recruited so that the study will have sufficient power to detect the differences at a 20% attrition rate. Participants will be selected through announcements about the study both online and at the local clinics. Participants are invited to complete an online screening questionnaire, including the PHQ-9 scale and questions for checking the eligibility criteria. Participants with a PHQ-9 score of ten or higher are programmed for the SCID-5-CV interview administered by telephone or face-to-face. Participants who are eligible will be randomly assigned (using Redcap) to one of the two groups: (1) behavioural activation (BA) or (2) BA plus rehabilitation of action simulations (BA Plus T-RAC).Participants allocated to the behavioural activation arm will undergo a standard BA treatment. A therapist will administer the treatment for 8 sessions based on a manual built on the behavioural treatment protocol described by Martell et al.  and usedThe inclusion criteria were age from 18 to 65, a score of 10 or higher on the PHQ-9 and a diagnosis of depression based on clinical interview. The exclusion criteria were: significant intellectual impairment; meeting criteria for a current psychotic or substance abuse disorder; history of mania/hypomania; significant changes in the dose of antidepressant medication during the past month; receiving psychological therapy; and the presence of suicidal intent.We assess the suicidal ideation and intent at all assessments points of the study. Suicidal ideation is measured by the PHQ-9 item 9, BDI II, and clinical interview. If suicidal thoughts are reported, the C-SSRS interview is applied . If suicDepressive symptom severity is assessed with the Beck Depression Inventory-II (BDI-II) [(BDI-II) . BDI-II (BDI-II) . Psychom(BDI-II) , 56.Depressive symptoms severity is assessed with the Patient Health Questionnaire- 9 [naire- 9 . PHQ-9 sDepression remission is measured using The Structured Clinical Interview for DSM-5 Clinician Version [SCID-5-CV; Depression response is assessed based on BDI II scores. To identify responders to treatment we compute the reliable change index. A reliable change index of more than 1.96 will classify a participant as a responder [esponder .Anhedonia severity is assessed with the Snaith-Hamilton Pleasure Scale [re Scale  SHAPS isApathy level is assessed with the Apathy-Motivation Index [on Index . AMI is on Index .Anxiety severity is assessed with the Generalised Anxiety Scale 7 [GAD-7; 7 GAD-7; . GAD-7 iHealth and disability level outcome is assessed with The World Health Organisation Disability Assessment Schedule (WHODAS 2.0) 12 –Self-Report Version WHODAS 12), [DAS 12), . WHODAS Adverse and unwanted effects of the experimental intervention are assessed using the Negative Effects Questionnaire [ionnaire . NEQ is ionnaire .The vividness of motor imagery is assessed using the Vividness of Motor Imagery Questionnaire-2 (VMIQ-2) [(VMIQ-2) . The viv(VMIQ-2) , 67.The level of rewards is assessed with “The environmental and reward observation scale” (EROS); [ (EROS); . EROS coThe level of rumination is assessed with the Ruminative Response Scale-SV [Scale-SV . ParticiActivation and avoidance is assessed using the Behavioral Activation for Depression Scale—Short Form (BADS-SF) [BADS-SF) . BADS-SFWorking memory is assessed with a Backward digit span task. Participants are given a series of digits and asked to repeat them backward. The score is based on how many numbers participants are able to repeat. A higher score indicates better working memory. Pairs of the sequences are read aloud to participants. The subsequent set of sequences will be one digit longer if both are successfully repeated and one digit shorter if none of the pair’s sequences is correctly repeated. The following pair of sequences will have the same length if one of the pair’s sequences is incorrectly repeated while the other sequence is correctly repeated [repeated .Executive functioning is assessed with the verbal fluency test. In the verbal fluency test, participants are asked to say as many words as possible with a given letter  for 1 minute.Verb fluency. In the verb fluency task, participants are asked to produce as many verbs as possible for one minute. The participant’s score in each task is the number of total correct words.Acceptability ratings. Acceptability is measured as satisfaction with the intervention, intention to continue and the intention to recommend the intervention assessed on a 5-points Likert scale. Drop-out rates are analysed as well.Affect and behaviour monitoring scale. Changes in functioning, emotions, behaviour profile, efficacy, and difficulty of simulation are assessed. For each item, the score ranges from 1  to 7 (very much).The sample size was established using G*Power and selecting the difference between two independent means. Forty-four participants per arm will be required to obtain a 90% statistical power. This estimation is based on previous studies targeting robust processes in depressed individuals (rumination) and between-treatment effect size of Cohen’s d = 0.7. Assuming a dropout rate of 20%, 55 patients are required in each treatment arm, resulting in a total of 110 participants.Multiple imputation methods will be selected to address the missing data. All randomised patients will be included in intention-to-treat analyses (ITT). Per-protocol analysis will be conducted separately. Analyses will be computed with an alpha significance level of 5% and two-tailed analyses. Analyses will be performed using IBM SPSS. Comparisons will be computed at a 5% significance level, and BDI II is the primary outcome variable considered as continuous variables. Differences between groups at the posttest will be analysed with a mixed ANOVA having group as the main effect and group *time as an interaction effect. Subgroup analyses will be conducted for anhedonia, apathy, motor imagery, and rumination. F-statistics and p values will be reported for main and interaction effects. The results will be considered as supporting evidence if the F test of the interaction effect is statistically significant (group*time interaction term). Potential mediators of treatment effects will be analysed exploratorily using Hayes model 4 analyses for the primary (depression severity) and secondary outcomes . Hayes model 1 will be used to analyse the moderation. Between group effect sizes will be calculated based on Cohen’s d. Treatment completers will be analysed using per protocol analyses. Participants are considered "remitted" if they no longer fulfil the SCID-5 criteria for major depression episodes.™ exergames and imagery interventions were well received by various clinical and non-clinical populations in previous RCTs. Similarly, behavioural activation treatment is a well-received and efficient treatment of depression. Study results are disseminated through presentations at conferences and publications in major outlets for psychology. Local therapists will be trained to deliver behavioural activation. The public will know about the results available on the website and in the media.Participants and the public are not involved in the development of the study design. The intervention was modified based on piloting the procedures with healthy individuals and case studies of patients with depression. Based on the feedback from initial testing, procedures were modified to increase acceptability. Both XboxKinectThe study is the first to evaluate an exergame-augmented dynamic imagery intervention added to behavioural activation treatment. It is expected that adding the exergame-augmented dynamic imagery intervention will increase the acceptability of the treatment and decrease the severity of depression, anhedonia, and apathy. We also expect, based on moderation analyses, that this effect to be more pronounced in participants with difficulties of motor imagery at baseline. We further investigate mediators of the treatment effect on the severity of depression and secondary outcomes.™) and will overcome the deficiencies in vividness of imagery and the recruitment of motor networks in imagery. If efficient it may work through different mechanisms than the standard BA treatment.This study is the first to investigate the added benefit of exergame-augmented dynamic motor imagery intervention to behavioural activation treatment. There is an expected advantage that this intervention will make the treatment more accepted  it is a theory-driven intervention which could show an efficacy advantage, (2) it includes attractive exergames that may show additional benefits  (3) we included a clinician administered semi-structured interview (SCID-5-CV), (4) we planned for a mid-treatment assessment to evaluate mechanisms of change. At session six, the participants will complete measures of the mechanisms of change, which will be carried out based on temporal precedence criteria , (5) assThere are several limitations of the study: (1) it is not a large scale RCT some limitations being related to the small sample size, (2) as the sample size was determined based on post-treatment differences, moderation and mediation analyses being underpowered, (3) participants with high risk of suicide will be excluded based on a score C-SSRS scale , limitinThis study investigates the acceptability, feasibility, and preliminary efficacy of adding an exergame-augmented dynamic imagery rehabilitative intervention to behavioural activation treatment. Thus, an ecological rehabilitative intervention for action cognition is available. This study increases our knowledge of highly available treatments with increased accessibility for individuals with depression.S1 Checklist(DOC)Click here for additional data file.S1 Fig(DOC)Click here for additional data file.S1 File(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file.