Chinese medical journal
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Chinese medical journal · Feb 2021
Gene mutations of esophageal squamous cell carcinoma based on next-generation sequencing.
Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive cancers without effective therapy. To explore potential molecular targets in ESCC, we quantified the mutation spectrum and explored the relationship between gene mutation and clinicopathological characteristics and programmed death-ligand 1 (PD-L1) expression. ⋯ Our research initially constructed gene mutation profile related to surgically resected ESCC in high-incidence areas to explore the mechanism underlying ESCC development and potential therapeutic targets.
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Chinese medical journal · Feb 2021
Neuromodulatory therapies for patients with prolonged disorders of consciousness.
Reviving patients with prolonged disorders of consciousness (DOCs) has always been focused and challenging in medical research. Owing to the limited effectiveness of available medicine, recent research has increasingly turned towards neuromodulatory therapies, involving the stimulation of neural circuits. We summarised the progression of research regarding neuromodulatory therapies in the field of DOCs, compared the differences among different studies, in an attempt to explore optimal stimulation patterns and parameters, and analyzed the major limitations of the relevant studies to facilitate future research. ⋯ Neuromodulatory techniques were used as trial therapies for DOCs wherein their curative effects were controversial. The difficulties in detecting residual consciousness, the confounding effect between the natural course of the disease and therapeutic effect, and the heterogeneity across patients are the major limitations. Large-sample, well-designed studies, and innovations for both treatment and assessment are anticipated in future research.
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Chinese medical journal · Feb 2021
Establishment and clinical application value of an automatic diagnosis platform for rectal cancer T-staging based on a deep neural network.
Colorectal cancer is harmful to the patient's life. The treatment of patients is determined by accurate preoperative staging. Magnetic resonance imaging (MRI) played an important role in the preoperative examination of patients with rectal cancer, and artificial intelligence (AI) in the learning of images made significant achievements in recent years. Introducing AI into MRI recognition, a stable platform for image recognition and judgment can be established in a short period. This study aimed to establish an automatic diagnostic platform for predicting preoperative T staging of rectal cancer through a deep neural network. ⋯ Faster R-CNN AI might be an effective and objective method to build the platform for predicting rectal cancer T-staging.