Search

This study developed and evaluated a model for assessing pain during the surgical period using photoplethysmogram data from 242 patients. Pain levels were measured at 2 min intervals using a numerical rating scale or clinical criteria: preoperative, before and after intubation, before and after skin incision, and postoperative. Key features from the photoplethysmography waveform were extracted to build XGBoost-based models for intraoperative and postoperative pain assessment. The combined perioperative model was compared with a commercial surgical pain index, yielding area under the receiver operating characteristics curve scores of 0.819 and 0.927 for intraoperative and postoperative periods, respectively, compared to the commercial index's scores of 0.829 and 0.577. These results highlight the models' effectiveness in pain assessment throughout the surgical process, identifying waveform skewness and diastolic phase rate decrease as critical for intraoperative pain assessment and systolic phase area or baseline fluctuation as significant for postoperative pain assessment. Clinical trial registration: Registration name: Clinical Research Information Service (CRIS). Registration site: http://cris.nih.go.kr. Number: KCT0005840. Principal Investigator: Dr. Byung-Moon Choi. Date of registration: January 28, 2021 [ABSTRACT FROM AUTHOR]

Purpose: This multicenter, open-label, phase II trial evaluated the efficacy and safety of bortezomib combined with dexamethasone for the treatment of relapsed/refractory cutaneous T-cell lymphoma (CTCL) in previously treated patients across 14 institutions in South Korea. Materials and Methods: Between September 2017 and July 2020, 29 patients with histologically confirmed CTCL received treatment, consisting of eight 4-week cycles of induction therapy followed by maintenance therapy, contingent upon response, for up to one year. The primary endpoint was the proportion of patients achieving an objective global response. Results: Thirteen of the 29 patients (44.8%) achieved an objective global response, including two complete responses. The median progression-free survival (PFS) was 5.8 months, with responders showing a median PFS of 14.0 months. Treatment-emergent adverse events were generally mild, with a low incidence of peripheral neuropathy and hematologic toxicities. Despite the trend toward shorter PFS in patients with higher mutation burdens, genomic profiling before and after treatment showed no significant emergence of new mutations indicative of disease progression. Conclusion: This study supports the use of bortezomib and dexamethasone as a viable and safe treatment option for previously treated CTCL, demonstrating substantial efficacy and manageability in adverse effects. Further research with a larger cohort is suggested to validate these findings and explore the prognostic value of mutation profiles. [ABSTRACT FROM AUTHOR]

Machine learning (ML) is currently being widely studied and applied in data analysis and prediction in various fields, including laboratory medicine. To comprehensively evaluate the application of ML in laboratory medicine, we reviewed the literature on ML applications in laboratory medicine published between February 2014 and March 2024. A PubMed search using a search string yielded 779 articles on the topic, among which 144 articles were selected for this review. These articles were analyzed to extract and categorize related fields within laboratory medicine, research objectives, specimen types, data types, ML models, evaluation metrics, and sample sizes. Sankey diagrams and pie charts were used to illustrate the relationships between categories and the proportions within each category. We found that most studies involving the application of ML in laboratory medicine were designed to improve efficiency through automation or expand the roles of clinical laboratories. The most common ML models used are convolutional neural networks, multilayer perceptrons, and tree-based models, which are primarily selected based on the type of input data. Our findings suggest that, as the technology evolves, ML will rise in prominence in laboratory medicine as a tool for expanding research activities. Nonetheless, expertise in ML applications should be improved to effectively utilize this technology. [ABSTRACT FROM AUTHOR]

Abstract This study developed and evaluated a model for assessing pain during the surgical period using photoplethysmogram data from 242 patients. Pain levels were measured at 2 min intervals using a numerical rating scale or clinical criteria: preoperative, before and after intubation, before and after skin incision, and postoperative. Key features from the photoplethysmography waveform were extracted to build XGBoost-based models for intraoperative and postoperative pain assessment. The combined perioperative model was compared with a commercial surgical pain index, yielding area under the receiver operating characteristics curve scores of 0.819 and 0.927 for intraoperative and postoperative periods, respectively, compared to the commercial index’s scores of 0.829 and 0.577. These results highlight the models’ effectiveness in pain assessment throughout the surgical process, identifying waveform skewness and diastolic phase rate decrease as critical for intraoperative pain assessment and systolic phase area or baseline fluctuation as significant for postoperative pain assessment. Clinical trial registration: Registration name: Clinical Research Information Service (CRIS). Registration site: http://cris.nih.go.kr . Number: KCT0005840. Principal Investigator: Dr. Byung-Moon Choi. Date of registration: January 28, 2021

Abstract Toxic protein aggregates are associated with various neurodegenerative diseases, including Huntington’s disease (HD). Since no current treatment delays the progression of HD, we develop a mechanistic approach to prevent mutant huntingtin (mHttex1) aggregation. Here, we engineer the ATP-independent cytosolic chaperone PEX19, which targets peroxisomal membrane proteins to peroxisomes, to remove mHttex1 aggregates. Using yeast toxicity-based screening with a random mutant library, we identify two yeast PEX19 variants and engineer equivalent mutations into human PEX19 (hsPEX19). These variants effectively delay mHttex1 aggregation in vitro and in cellular HD models. The mutated hydrophobic residue in the α4 helix of hsPEX19 variants binds to the N17 domain of mHttex1, thereby inhibiting the initial aggregation process. Overexpression of the hsPEX19-FV variant rescues HD-associated phenotypes in primary striatal neurons and in Drosophila. Overall, our data reveal that engineering ATP-independent membrane protein chaperones is a promising therapeutic approach for rational targeting of mHttex1 aggregation in HD.