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Purpose: This study aimed to compare the learning curves and early postoperative outcomes for conventional laparoscopic (CL) and single incision laparoscopic (SIL) right hemicolectomy (RHC).
Methods: This retrospective study included the initial 35 cases in each group. Learning curves were evaluated by the moving average of operative time, mean operative time of every five consecutive cases, and cumulative sum (CUSUM) analysis. The learning phase was considered overcome when the moving average of operative times reached a plateau, and when the mean operative time of every five consecutive cases reached a low point and subsequently did not vary by more than 30 minutes.
Results: Six patients with missing data in the CL RHC group were excluded from the analyses. According to the mean operative time of every five consecutive cases, learning phase of SIL and CL RHC was completed between 26 and 30 cases, and 16 and 20 cases, respectively. Moving average analysis revealed that approximately 31 (SIL) and 25 (CL) cases were needed to complete the learning phase, respectively. CUSUM analysis demonstrated that 10 (SIL) and two (CL) cases were required to reach a steady state of complication-free performance, respectively. Postoperative complications rate was higher in SIL than in CL group, but the difference was not statistically significant (17.1% vs. 3.4%).
Conclusion: The learning phase of SIL RHC is longer than that of CL RHC. Early oncological outcomes of both techniques were comparable. However, SIL RHC had a statistically insignificant higher complication rate than CL RHC during the learning phase.
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http://dx.doi.org/10.4174/astr.2015.88.5.269 | DOI Listing |
Alpha Psychiatry
August 2025
State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, 100875 Beijing, China.
Background: Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder marked by impaired interactions and restricted interests, the pathophysiology of which is not fully understood. The current study explored the potential therapeutic effects of transcranial direct current stimulation (tDCS) on the neurophysiological aspects of ASD, specifically focusing on the brain's excitatory/inhibitory (E/I) balance and behavioral outcomes, providing scientific guidance for ASD intervention.
Methods: Forty-two children with ASD were randomly divided into either an active tDCS or sham tDCS group.
Curr Med Imaging
May 2025
Department of Radiology, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China.
Background: Predicting the recurrence risk of NMIBC after TURBT is crucial for individualized clinical treatment.
Objective: The objective of this study is to evaluate the ability of radiomic feature analysis of intratumoral and peritumoral regions based on computed tomography (CT) imaging to predict recurrence in non-muscle-invasive bladder cancer (NMIBC) patients who underwent transurethral resection of bladder tumor (TURBT).
Methods: A total of 233 patients with NMIBC who underwent TURBT were retrospectively analyzed.
BMC Ecol Evol
September 2025
Lehrstuhl für Zoologie, TUM School of Life Sciences, Technical University of Munich, Liesel-Beckmann Strasse 4, Freising, 85354, Germany.
Accurate three-dimensional localisation of ultrasonic bat calls is essential for advancing behavioural and ecological research. I present a comprehensive, open-source simulation framework-Array WAH-for designing, evaluating, and optimising microphone arrays tailored to bioacoustic tracking. The tool incorporates biologically realistic signal generation, frequency-dependent propagation, and advanced Time Difference of Arrival (TDoA) localisation algorithms, enabling precise quantification of both positional and angular accuracy.
View Article and Find Full Text PDFInt J Biol Macromol
September 2025
Department of Computational Biology, Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), Okhla Phase III, New Delhi, 110020, India; Infosys Centre for Artificial Intelligence, Indraprastha Institute of Information Technology Delhi (IIIT-Delhi), Okhla Phase III, New Delhi, 110020, In
Understanding the structural and functional diversity of toxin proteins is critical for elucidating macromolecular behavior, mechanistic variability, and structure-driven bioactivity. Traditional approaches have primarily focused on binary toxicity prediction, offering limited resolution into distinct modes of action of toxins. Here, we present MultiTox, an ensemble stacking framework for the classification of toxin proteins based on their molecular mode of action: neurotoxins, cytotoxins, hemotoxins, and enterotoxins.
View Article and Find Full Text PDFBiomed Phys Eng Express
September 2025
electrical engineering department, Indian Institute of Technology Roorkee, Research wing, electrical department, Roorkee, uttrakhand, 247664, INDIA.
Imagined speech classification involves decoding brain signals to recognize verbalized thoughts or intentions without actual speech production. This technology has significant implications for individuals with speech impairments, offering a means to communicate through neural signals. The prime objective of this work is to propose an innovative machine learning (ML) based classification methodology that combines electroencephalogram (EEG) data augmentation using a sliding window technique with statistical feature extraction from the amplitude and phase spectrum of frequency domain EEG segments.
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