A comparison of extracorporeal side to side or end to side anastomosis following a laparoscopic right hemicolectomy for colon cancer.

BACKGROUND: This study aimed to investigate whether an extracorporeal side-to-side (SS) or end-to-side (ES) stapled anastomosis impacts short-term and long-term outcomes after an oncological laparoscopic right hemicolectomy. METHODS: A retrospective cohort study of prospectively collected data from two Victorian tertiary referral hospitals was performed. Patients who underwent oncological resection for colorectal cancer between February 2010 and September 2020 were selected from the colorectal neoplasia database. Patients were divided into two groups depending on the type of stapled anastomosis: Group 1 (functional end-to-end/side-to-side (SS)); and Group 2 (end-to-side (ES)). Primary outcomes were anastomotic leak, postoperative ileus, mortality and morbidity, length of stay post-surgery, readmission to hospital, and 30-day mortality. RESULTS: This large case series of 1040 patients (SS = 625, ES = 415) demonstrated that the type of stapling technique impacted operative duration and postoperative ileus rates. Patients in the SS group had a faster operation of 108 min rather than 130 min in the ES group (p < 0.001). The SS group were more likely to experience a post-operative ileus (p < 0.001) with no impact on length of stay (SS, 7 days versus ES, 7 days; p = 0.14). There were no differences between the two groups with respect to lymph node yield, lymph node ratio, anastomotic leaks, return to theatre, 30-day mortality and 5-year overall survival. DISCUSSION: The type of extracorporeal stapled anastomosis following an oncological laparoscopic right hemicolectomy has minimal impact on morbidity and survival outcomes; however, a side-to-side stapled anastomosis is more likely to be a faster operation with a higher postoperative ileus rate.

Improving Video Temporal Consistency via Broad Learning System.

Applying image-based processing methods to original videos on a framewise level breaks the temporal consistency between consecutive frames. Traditional video temporal consistency methods reconstruct an original frame containing flickers from corresponding nonflickering frames, but the inaccurate correspondence realized by optical flow restricts their practical use. In this article, we propose a temporally broad learning system (TBLS), an approach that enforces temporal consistency between frames. We establish the TBLS as a flat network comprising the input data, consisting of an original frame in an original video, a corresponding frame in the temporally inconsistent video on which the image-based technique was applied, and an output frame of the last original frame, as mapped features in feature nodes. Then, we refine extracted features by enhancing the mapped features as enhancement nodes with randomly generated weights. We then connect all extracted features to the output layer with a target weight vector. With the target weight vector, we can minimize the temporal information loss between consecutive frames and the video fidelity loss in the output videos. Finally, we remove the temporal inconsistency in the processed video and output a temporally consistent video. Besides, we propose an alternative incremental learning algorithm based on the increment of the mapped feature nodes, enhancement nodes, or input data to improve learning accuracy by a broad expansion. We demonstrate the superiority of our proposed TBLS by conducting extensive experiments.

Peracetic Acid: A Practical Alternative to Formalin for Disinfection of Extracted Human Teeth.

Extracted human teeth provide the closest approximation to teeth in situ and play important roles in dental education and materials research. Since extracted teeth are potentially infectious, the Centers for Disease Control recommend their sterilization by autoclaving or disinfection by formalin immersion to ensure safe handling. However, autoclaving is not recommended for teeth with amalgam fillings and formalin is hazardous. The goal of the present study was to investigate the potential of peracetic acid (PA) as an alternative method to achieve reliable disinfection of freshly extracted teeth. A total of 80 extracted teeth were collected for this study. Whole teeth were incubated in one of four solutions for defined periods of time: sterile water (2 weeks), formalin (2 weeks), PA 1000 ppm (2 weeks), and PA 2000 ppm (1 week). After sectioning, the crown and root fragments were transferred into separate tubes containing brain-heart infusion broth and incubated at 37 °C under anaerobic conditions for 72 h. Absence of broth turbidity was used to assess effectiveness of disinfection. No turbidity was observed in any of the formalin-treated or peracetic acid-treated samples, signifying complete disinfection. Our results indicate that PA can effectively disinfect extracted human teeth, providing a reliable alternative to formalin and autoclaving.

Gender and age detection assist convolutional neural networks in classification of thorax diseases.

Conventionally, convolutional neural networks (CNNs) have been used to identify and detect thorax diseases on chest x-ray images. To identify thorax diseases, CNNs typically learn two types of information: disease-specific features and generic anatomical features. CNNs focus on disease-specific features while ignoring the rest of the anatomical features during their operation. There is no evidence that generic anatomical features improve or worsen the performance of convolutional neural networks for thorax disease classification in the current research. As a consequence, the relevance of general anatomical features in boosting the performance of CNNs for thorax disease classification is investigated in this study. We employ a dual-stream CNN model to learn anatomical features before training the model for thorax disease classification. The dual-stream technique is used to compel the model to learn structural information because initial layers of CNNs often learn features of edges and boundaries. As a result, a dual-stream model with minimal layers learns structural and anatomical features as a priority. To make the technique more comprehensive, we first train the model to identify gender and age and then classify thorax diseases using the information acquired. Only when the model learns the anatomical features can it detect gender and age. We also use Non-negative Matrix Factorization (NMF) and Contrast Limited Adaptive Histogram Equalization (CLAHE) to pre-process the training data, which suppresses disease-related information while amplifying general anatomical features, allowing the model to acquire anatomical features considerably faster. Finally, the model that was earlier trained for gender and age detection is retrained for thorax disease classification using original data. The proposed technique increases the performance of convolutional neural networks for thorax disease classification, as per experiments on the Chest X-ray14 dataset. We can also see the significant parts of the image that contribute more for gender, age, and a certain thorax disease by visualizing the features. The proposed study achieves two goals: first, it produces novel gender and age identification results on chest X-ray images that may be used in biometrics, forensics, and anthropology, and second, it highlights the importance of general anatomical features in thorax disease classification. In comparison to state-of-the-art results, the proposed work also produces competitive results.

Globally and Locally Semantic Colorization via Exemplar-Based Broad-GAN.

Given a target grayscale image and a reference color image, exemplar-based image colorization aims to generate a visually natural-looking color image by transforming meaningful color information from the reference image to the target image. It remains a challenging problem due to the differences in semantic content between the target image and the reference image. In this paper, we present a novel globally and locally semantic colorization method called exemplar-based conditional broad-GAN, a broad generative adversarial network (GAN) framework, to deal with this limitation. Our colorization framework is composed of two sub-networks: the match sub-net and the colorization sub-net. We reconstruct the target image with a dictionary-based sparse representation in the match sub-net, where the dictionary consists of features extracted from the reference image. To enforce global-semantic and local-structure self-similarity constraints, global-local affinity energy is explored to constrain the sparse representation for matching consistency. Then, the matching information of the match sub-net is fed into the colorization sub-net as the perceptual information of the conditional broad-GAN to facilitate the personalized results. Finally, inspired by the observation that a broad learning system is able to extract semantic features efficiently, we further introduce a broad learning system into the conditional GAN and propose a novel loss, which substantially improves the training stability and the semantic similarity between the target image and the ground truth. Extensive experiments have shown that our colorization approach outperforms the state-of-the-art methods, both perceptually and semantically.

Multi-Input Dual-Stream Capsule Network for Improved Lung and Colon Cancer Classification.

Lung and colon cancers are two of the most common causes of death and morbidity in humans. One of the most important aspects of appropriate treatment is the histopathological diagnosis of such cancers. As a result, the main goal of this study is to use a multi-input capsule network and digital histopathology images to build an enhanced computerized diagnosis system for detecting squamous cell carcinomas and adenocarcinomas of the lungs, as well as adenocarcinomas of the colon. Two convolutional layer blocks are used in the proposed multi-input capsule network. The CLB (Convolutional Layers Block) employs traditional convolutional layers, whereas the SCLB (Separable Convolutional Layers Block) employs separable convolutional layers. The CLB block takes unprocessed histopathology images as input, whereas the SCLB block takes uniquely pre-processed histopathological images. The pre-processing method uses color balancing, gamma correction, image sharpening, and multi-scale fusion as the major processes because histopathology slide images are typically red blue. All three channels (Red, Green, and Blue) are adequately compensated during the color balancing phase. The dual-input technique aids the model's ability to learn features more effectively. On the benchmark LC25000 dataset, the empirical analysis indicates a significant improvement in classification results. The proposed model provides cutting-edge performance in all classes, with 99.58% overall accuracy for lung and colon abnormalities based on histopathological images.

Log odds of positive lymph nodes is prognostically equivalent to lymph node ratio in non-metastatic colon cancer.

BACKGROUND: Globally, colorectal cancer (CRC) is the third and second leading cancer in men and women respectively with 600,000 deaths per year. Traditionally, clinicians have relied solely on nodal disease involvement, and measurements such as lymph node ratio (LNR; the ratio of metastatic/positive lymph nodes to total number of lymph nodes examined), when determining patient prognosis in CRC. The log odds of positive lymph nodes (LODDS) is a logistic transformation formula that uses pathologic lymph node data to stratify survival differences among patients within a single stage of disease. This formula allows clinicians to identify whether patients with clinically aggressive tumours fall into higher-risk groups regardless of nodal positivity and can potentially guide adjuvant treatment modalities. The aim of this study was to investigate whether LODDS in colon cancer provides better prognostication compared to LNR. METHODS: A retrospective study of patients on the prospectively maintained Cabrini Monash University Department of Surgery colorectal neoplasia database, incorporating data from hospitals in Melbourne Australia, identified patients entered between January 2010 and March 2016. Association of LODDS and LNR with clinical variables were analysed. Disease-free (DFS) and overall (OS) survival were investigated with Cox regression and Kaplan-Meier survival analyses. RESULTS: There were 862 treatment episodes identified in the database (402 male, 47%). The median patient age was 73 (range 22-100 years). There were 799 colonic cancers and 63 rectosigmoid cancers. The lymph node yield (LNY) was suboptimal (< 12) in 168 patients (19.5%) (p = 0.05). The 5-year OS for the different LNR groups were 86, 91 and 61% (p < 0.001) for LNR0 (655 episodes), LNR1 (128 episodes) and LNR2 (78 episodes), respectively. For LODDS, they were 85, 91 and 61% (p < 0.001) in LODDS0 (569 episodes), LODDS1 (217 episodes) and LODDS2 (75 episodes) groups (p < 0.001). Overall survival rates were comparable between the LNR and LODDS group and for LNY < 12 and stage III patients when each were sub-grouped by LODDS and LNR. CONCLUSION: This study has shown for that the prognostic impact of LODDS is comparable to LNR for colon cancer patients. Accordingly, LNR is recommended for prognostication given its ease of calculation.

Monitoring Bioaccumulation (in Gills and Muscle Tissues), Hematology, and Genotoxic Alteration in Ctenopharyngodon idella Exposed to Selected Heavy Metals.

Health and environmental problems arising from metals present in the aquatic ecosystem are very well known. The present study investigated toxicological effects of LC15 of metals such as copper, chromium, and lead for 24, 48, 72, and 96 h on hematological indices, RBC nucleus and cell morphology, and gill and muscle tissues of grass carp (Ctenopharyngodon idella). Experimental dose concentrations of copper were 1.5, 1.4, 1.2, and 1 mgL-1. Similarly, dose concentrations of chromium were 25.5, 22.5, 20, and 18 mgL-1 while those of lead were 250, 235, 225, and 216 mgL-1, respectively. Maximum decrease in the concentration of Hb, RBCs, and monocytes was observed against chromium, while maximum increase in the concentration of lymphocytes was reported against lead. Abnormalities such as single and double micronuclei, deformed nucleus, nuclear shift, irregular nucleus, deformed cells, microcyte cells, and vacuolated and swollen cells were observed. Gill tissues absorbed maximum concentration of lead followed by chromium and copper. Muscle tissues also absorbed maximum concentration of lead followed by chromium and copper, respectively. Histological alterations such as epithelial lifting, interlamellar spaces, club gill filaments, gill bridging, curling filaments, swelling and fusion of cells, irregular cells, destruction of epithelial cells, cellular necrosis, and inflammatory cells were observed in gill tissues while inflammation and necrosis of muscle fibers, degeneration of muscle fibers, edema of muscle bundles, zig-zag of muscle fibers, and lesions were observed in muscle tissues of fish exposed with different doses of these heavy metals, indicating the toxicity of metals to aquatic fauna as well as to human being via food chain.

Contralateral lumbosacral plexopathy following lumbar microdiscectomy.

We describe the unique case of a 51-year-old lady who developed a contralateral lumbosacral plexopathy two days after a lumbar microdiscectomy. This is the first report to date of this complication occurring following this procedure. We review the literature regarding lumbosacral plexopathy and discuss the evidence base behind investigating and managing this condition and the potential pathophysiological mechanisms which underlie its development. We draw comparisons with the more widely recognised post-operative brachial neuritis, characterised by delayed onset brachial plexopathy developing after cervical decompression, and propose an immune-mediated inflammatory mechanism linking the two conditions.

The role of preoperative CEA in the management of colorectal cancer: A cohort study from two cancer centres.

BACKGROUND: The primary aim of this study was to investigate whether a preoperative elevation in serum CEA is an independent prognostic factor for both 5-year overall and disease-free survival within an Australian patient cohort. MATERIALS AND METHODS: A retrospective study of a prospectively maintained colorectal neoplasia database for patients between January 2010 and June 2016 was performed. Patients were categorized into two groups according to the preoperative serum CEA level: low (<2.5), high CEA (≥2.5), and elevated (≥5 ng/ml); and further stratified by disease stage. Inclusion criteria were patients having had a resection for either a colonic or upper third rectal adenocarcinoma and with a preoperative CEA value. Data on patient demographics, mortality, and morbidity and survival were compiled. Five-year estimates of overall (OS) and disease-free survival (DFS) were assessed. RESULTS: 623 patients met the inclusion criteria. The median patient age was 73 (range 22-97) and 55% female (n = 340). There were 572 colonic cancers and 51 rectal cancers. The median follow-up time was 25 months (range 1-71). Eight patients (1%) had a local recurrence and 62 patients (10%) had evidence of metastatic disease after the initial curative resection. The 5-year OS and DFS rates for patients with CEA level <2.5 ng/ml were 85% and 86% respectively, which were higher than those with CEA level ≥2.5 ng/ml (73% and 79% respectively). Independent predictors of recurrence were a CEA ≥5 ng/ml (HR 1.8; 95% CI 1.09-3.00; p = 0.002) and stage II (HR 5.33; 95% CI 1.59-17.90; p = 0.007) and stage III (HR 10.91; 95% CI 3.34-35.60; p=<0.001). A CEA ≥5 ng/ml was associated with a higher risk of death (HR 1.79; 95% CI 1.00-3.19; p = 0.046). CONCLUSION: Preoperative CEA levels were associated with age, BMI, ASA and tumour stage. Overall, CEA remains a reliable predictor of recurrence and survival after curative surgery in patients with colorectal cancer.

A Review of Modern Control Strategies for Clinical Evaluation of Propofol Anesthesia Administration Employing Hypnosis Level Regulation.

Regulating the depth of hypnosis during surgery is one of the major objectives of an anesthesia infusion system. Continuous administration of Propofol infusion during surgical procedures is essential but it unduly increases the load of an anesthetist working in a multitasking scenario in the operation theatre. Manual and target controlled infusion systems are not appropriate to handle instabilities like blood pressure and heart rate changes arising due to interpatient and intrapatient variability. Patient safety, large interindividual variability, and less postoperative effects are the main factors motivating automation in anesthesia administration. The idea of automated system for Propofol infusion excites control engineers to come up with more sophisticated systems that can handle optimum delivery of anesthetic drugs during surgery and avoid postoperative effects. A linear control technique is applied initially using three compartmental pharmacokinetic and pharmacodynamic models. Later on, sliding mode control and model predicative control achieve considerable results with nonlinear sigmoid model. Chattering and uncertainties are further improved by employing adaptive fuzzy control and H∞ control. The proposed sliding mode control scheme can easily handle the nonlinearities and achieve an optimum hypnosis level as compared to linear control schemes, hence preventing mishaps such as underdosing and overdosing of anesthesia.

A Comparative Analysis of PID, Lead, Lag, Lead-Lag, and Cascaded Lead Controllers for a Drug Infusion System.

Goal: The aim of this paper is to conduct a comprehensive comparative analysis between five different controllers for a drug infusion system in total intravenous anesthesia (TIVA) administration. Methods: The proposed method models a dilution chamber with first order exponential decay characteristics to represent the pharmacokinetic decay of a drug. The dilution chamber is integrated with five different control techniques with a simulation-based comparative analysis performed between them. The design process is conducted using MATLAB SISOTOOL. Results: The findings show that each controller has its own merits and demerits. The results generated using MATLAB signify and confirm the effectiveness of PI and cascaded lead controllers, with cascaded lead controller as the best control technique to automate and control the propofol delivery. Conclusion: In this paper, different control techniques for measurement-based feedback-controlled propofol delivery is confirmed with promising results. Significance: The comparative analysis showed that this drug infusion platform, merged with the proper control technique, will perform eminently in the field of total intravenous anesthesia.

Control Law Design for Propofol Infusion to Regulate Depth of Hypnosis: A Nonlinear Control Strategy.

Maintaining the depth of hypnosis (DOH) during surgery is one of the major objectives of anesthesia infusion system. Continuous administration of Propofol infusion during surgical procedures is essential but increases the undue load of an anesthetist in operating room working in a multitasking setup. Manual and target controlled infusion (TCI) systems are not good at handling instabilities like blood pressure changes and heart rate variability arising due to interpatient variability. Patient safety, large interindividual variability, and less postoperative effects are the main factors to motivate automation in anesthesia. The idea of automated system for Propofol infusion excites the control engineers to come up with a more sophisticated and safe system that handles optimum delivery of drug during surgery and avoids postoperative effects. In contrast to most of the investigations with linear control strategies, the originality of this research work lies in employing a nonlinear control technique, backstepping, to track the desired hypnosis level of patients during surgery. This effort is envisioned to unleash the true capabilities of this nonlinear control technique for anesthesia systems used today in biomedical field. The working of the designed controller is studied on the real dataset of five patients undergoing surgery. The controller tracks the desired hypnosis level within the acceptable range for surgery.

Impact of geographic disparity on liver allocation for hepatocellular cancer in the United States.

BACKGROUND & AIMS: Liver allocation for hepatocellular cancer (HCC) is undergoing constant re-evaluation in the United States, but the impact of geographic differences in organ access has not been examined. METHODS: From February 28th, 2002 until November 20th, 2009, 9730 adult patients with T2 HCC and 326 Beyond Milan HCC patients were studied using the UNOS database. Kaplan-Meier survival curves were generated and log-rank tests were used to test for differences in survival curves. RESULTS: Length of waiting time and presence/absence of loco-regional therapy in T2 HCC patients did not significantly impact transplant recipient (p=0.65) and graft survival (p=0.74) (Fig. 1B). Regions with median waiting times >6 months performed more loco-regional therapy (Fig. 1D) and had significantly higher waiting list dropout rates (Regions 1: p=0.01; 5: p<0.001, and 9: p<0.001). T2 HCC post-transplant outcomes were not significantly different between UNOS regions (Fig. 2) or between T2 and Beyond Milan HCC patients (transplant recipient p=0.37, and graft p=0.72 survival) (Fig. 1C). The Beyond Milan cohort had significantly greater dropout/death (p=0.007) and a worse overall survival trend (p=0.11) (Fig. 1C). CONCLUSIONS: Analysis of the UNOS database shows inhomogeneous access to liver transplantation in the United States. Regions with longer waiting times had significantly higher T2 HCC dropout rates (Table 2), and used more loco-regional therapy (Fig. 1D). Conversely, T2 HCC patients had uniform liver transplant outcomes despite geographic differences (Fig. 2). Beyond Milan HCC patients showed significantly greater dropout/death (p=0.007) and a worse overall survival trend in an intent-to-treat analysis (p=0.11) (Fig. 1C).

Comparative effectiveness research in the United States: a catalyst for innovation.

Recent calls for value in the US healthcare system have spurred an increase in comparative effectiveness research, which generates evidence on competing treatment options to inform healthcare stakeholders. As a large healthcare purchaser, the federal government has made several significant investments in comparative effectiveness research. Notably, in 2009 the American Recovery and Reinvestment Act allocated $1.1 billion for comparative effectiveness research, and in 2010 the Patient Protection and Affordable Care Act established a federal institute to organize the federal investment in comparative effectiveness research going forward. Over the past several years, comparative effectiveness research from the public and private sectors has begun to provide a foundation for innovation within the insurance and life sciences industries. Health plans and other payers are experimenting with nuanced coverage and reimbursement policies informed by comparative effectiveness evidence. Anticipating changes in payer, patient, and provider behaviors, drug manufacturers are refocusing their efforts on the development of novel and better-differentiated medications. As more comparative research becomes available in the future, continued innovation in payer and manufacturer strategies appears likely.

Polyacrylamide gel electrophoresis separation and detection of polyamidoamine dendrimers possessing various cores and terminal groups.

Detection and separation of polyamidoamine dendrimers possessing various cores and surface groups was studied by polyacrylamide gel electrophoresis. Although many dyes and staining techniques were able to detect dendrimers on polyacrylamide gels, Coomassie Blue was found to be the most sensitive and convenient. Amine and hydroxyl terminated dendrimers were best separated under acidic conditions, while dendrimers with carboxyl surfaces required alkaline buffers. Some dendrimers were very susceptible to diffusion that could occur during their separation, staining or destaining steps. In the absence of an appropriate fixation step, dendrimers could be resolved by using small pore size gels and low voltage or current. Increasing core lengths did not significantly affect migration of a given dendrimer generation but exhibited improved separation and staining characteristics. Polyacrylamide gel electrophoresis was found to be a rapid, inexpensive, and reliable procedure to characterize many different water-soluble dendritic macromolecules.

A simple polyacrylamide gel electrophoresis procedure for separation of polyamidoamine dendrimers.

A simple, inexpensive, and rapid electrophoresis technique was developed for use as a routine tool for evaluating purity of polyamidoamine (PAMAM) dendrimers. A variety of factors influencing migration of generations 0-7 dendrimers on nongradient polyacrylamide gels were evaluated. The low generation dendrimers were found to be very sensitive to diffusion during or after electrophoresis. The proposed method incorporates steps that minimize diffusion, in order to obtain improved resolution and sensitivity, especially for the lower-molecular-weight dendrimers. This was accomplished by inclusion of a dendrimer fixation step with glutaraldehyde and performing the electrophoresis separation, fixation, staining, and destaining at 4 degrees C. PAMAM dendrimer separation was studied under basic and acidic conditions. Electrophoresis under acidic conditions gave increased resolution and sensitivity over separation at alkaline pH. Oligomers and trailing generations could be clearly separated and visualized under these conditions. The smallest PAMAM dendrimer, generation 0, was visible at 1.5 microg under the optimized acidic conditions. With slight modifications, this technique should be applicable to separation of other water-soluble dendrimers.