Objective To explore the clinical value, latest research progress, and clinical controversy of total neoadjuvant therapy (TNT) in locally advanced rectal cancer (LARC). Method We searched and reviewed on the latest literatures about studies of the clinical research of TNT in LARC. Results TNT could make the tumor downstage rapidly and improve the patients’ treatment compliance. In terms of organ preservation rate, 3-year disease-free survival and pathological complete remission rate, TNT had advantages and was a especial potential treatment strategy compared with traditional methods. Conclusions TNT decreases local recurrence rate and improves the long-term survival. For LARC patients with strong desire for organ preservation, TNT is a good treatment choice and has the value of clinical promotion.
Esophageal cancer (EC) is the eighth dangerous cancer in the world. As the global population ages, the management of elderly patients with EC poses a challenge as they have many aging-associated diseases and physiological changes. In addition, the data on the tolerability of cancer treatment and the use of combined therapies in the patients to guide their treatment are limited. In this paper, we reviewed the literatures and discussed the effect of surgical resection and the potential complications of elderly patients. We reviewed the basic principles of combined therapy and the potential benefits of chemotherapy or chemoradiotherapy for patients and focused on the management of elderly patients with EC as well as the role of comprehensive assessment for aging to provide treatment options for elderly patients.
Objective To search through the Cochrane database of systematic reviews using the flag new search option to find out whether this strategy helps update revivews. Methods We chose the New search option in the advanced search in The Cochrane Library on Wiley InterScience (Issue 1, 2009), and input all hit citations to the ProCite software. We then looked through the `What’s new`,`History`, as well as `Appendices` on hit reviews in the Cochrane library one by one, and then added these related contents to thef ield of the ProCite in order to analyze the results. Results A total of 140 systematic reviews had the flag new search. Among them, the total new search frequency were 274, meaning frequency was 1.96/1; updated within two years were 58 (41.43); there were 61 reviews with `Appendices` (43.57%). The status of the chosen database among the 61 reviews with `Appendices` was as follows: most were from MEDLINE (56 reviews, 91.80%), next EMBASE (47 reviews, 77.05 %), and finally CENTRAL (45 reviews, 73.7%). Among the reviews with `Appendices`, most of them were not correctly labeled. Conclusion Although some Cochrane systematic reviews are updated in a timely fashion, there is some incomplete information, although it may be still helpful for researchers to look for new studies.
Giant thoracic tumor is currently one of the diagnostic and therapeutic challenges of thoracic surgery, with no established guideline or standard for diagnosis and treatment. The quality control of individualized surgical strategy and perioperative management with multi-disciplinary participation is the key to ensure the safety and improve the prognosis of patients. Based on the clinical experience of our institution and others, we hereby discussed and summarized the basic principles, surgical strategies and perioperative management of giant thoracic tumor, aiming to provide a reference of quality control.
Severe bee stings can trigger a systemic inflammatory response and multi-organ dysfunction, potentially resulting in fatality. Acute kidney injury (AKI) is a frequent complication in patients with severe bee stings, and conventional comprehensive treatment combined with various blood purification therapies is commonly employed in clinical practice to promptly manage the condition and reduce the average hospital stay duration. This article primarily delves into the significance of enhanced clinical nursing care for patients with bee stings-induced AKI undergoing blood purification therapy. Specifically, it underscores the importance of patient education regarding treatment-related considerations, nursing techniques for vascular access during treatment, potential complications, and corresponding nursing interventions.
Motor imagery (MI), motion intention of the specific body without actual movements, has attracted wide attention in fields as neuroscience. Classification algorithms for motor imagery electroencephalogram (MI-EEG) signals are able to distinguish different MI tasks based on the physiological information contained by the EEG signals, especially the features extracted from them. In recent years, there have been some new advances in classification algorithms for MI-EEG signals in terms of classifiers versus machine learning strategies. In terms of classifiers, traditional machine learning classifiers have been improved by some researchers, deep learning and Riemannian geometry classifiers have been widely applied as well. In terms of machine learning strategies, ensemble learning, adaptive learning, and transfer learning strategies have been utilized to improve classification accuracies or reach other targets. This paper reviewed the progress of classification algorithms for MI-EEG signals, summarized and evaluated the existing classifiers and machine learning strategies, to provide new ideas for developing classification algorithms with higher performance.
