Prognostic factors in lung transplantation after extracorporeal membrane oxygenation bridging therapy: a systematic review and meta-analysis.

Background: Extracorporeal membrane oxygenation (ECMO) has recently emerged as a critical support system for lung function in patients awaiting lung transplantation. This meta-analysis investigates the prognostic factors of lung transplantation following ECMO bridging therapy. Methods: A comprehensive search was conducted in PubMed, Cochrane Library, Embase, CINAHL, Web of Science, Scopus, and ProQuest databases from inception to August 11, 2023. Included were cohort or case-control studies focusing on prognostic factors of lung transplantation with ECMO bridging therapy. Data extraction was performed independently, and study quality was assessed. A meta-analysis was carried out using RevMan 5.4 and Stata17.0 software to aggregate mortality rates and pertinent prognostic factors of ECMO as a bridge to lung transplantation. Results: The search identified eight trials encompassing 1,086 participants. The prognosis of patients undergoing lung transplantation with ECMO bridging was significantly associated with several factors: prolonged ECMO support [odds ratio 1.07, 95% confidence interval (CI): 1.02-1.12, I2=77%], deterioration in liver and kidney function (odds ratio 3.62, 95% CI: 2.37-5.54, I2=0%), and complications during ECMO (odds ratio 2.24, 95% CI: 1.45-3.44, I2=5%). Conclusions: Prolonged ECMO support, declining liver and kidney functions, and complications during ECMO are vital prognostic factors in lung transplantation following ECMO bridging therapy.

Never-Ending Learning for Explainable Brain Computing.

Exploring the nature of human intelligence and behavior is a longstanding pursuit in cognitive neuroscience, driven by the accumulation of knowledge, information, and data across various studies. However, achieving a unified and transparent interpretation of findings presents formidable challenges. In response, an explainable brain computing framework is proposed that employs the never-ending learning paradigm, integrating evidence combination and fusion computing within a Knowledge-Information-Data (KID) architecture. The framework supports continuous brain cognition investigation, utilizing joint knowledge-driven forward inference and data-driven reverse inference, bolstered by the pre-trained language modeling techniques and the human-in-the-loop mechanisms. In particular, it incorporates internal evidence learning through multi-task functional neuroimaging analyses and external evidence learning via topic modeling of published neuroimaging studies, all of which involve human interactions at different stages. Based on two case studies, the intricate uncertainty surrounding brain localization in human reasoning is revealed. The present study also highlights the potential of systematization to advance explainable brain computing, offering a finer-grained understanding of brain activity patterns related to human intelligence.

Pulmonary rehabilitation protocols in urgent lung transplantation patients.

BACKGROUND: Prolonged invasive respiratory support and extracorporeal membrane oxygenation (ECMO) in patients requiring urgent lung transplantation (ULTx) present significant challenges to clinical practice due to severe underlying diseases and complex conditions. The aim of the study was to report the clinical outcomes of patients who received ULTx and followed the perioperative rehabilitation protocol implemented in a lung transplant center. METHODS: A retrospective analysis was conducted in ULTx patients who required preoperative invasive mechanical ventilation (IMV) and ECMO between January 2018 and January 2023. Data were retrieved from electronic medical records at our lung transplant center. RESULTS: Fourteen patients (mean age 57.43±10.97 years; 12 males, 2 females) underwent ULTx with bridging ECMO and IMV. The mean body mass index was 23.94±3.33 kg/m², and the mean Acute Physiology and Chronic Health Evaluation (APACHE) II score was 21.50±3.96. The Nutritional Risk Screening 2002 (NRS 2002) scores were ≥3. ULTx was performed after an 8.5-day waiting period (interquartile interval [IQR] 5.0-26.5 d). Following the surgeries, the average lengths of ECMO and IMV were 1.0 (IQR 1.0-2.0) d and 5.0 (IQR 3.0-7.3) d, respectively. The total length of hospital stay was 60.1±30.8 d, with an average intensive care unit stay of 38.3±22.9 d and post-operative hospitalization stay of 45.8±26.1 d. Two patients died within 30 d after ULTx, with a 30-day survival rate of 85.71%. CONCLUSION: Patients receiving ULTx showed an acceptable short-term survival rate, validating the practicality and safety of the treatment protocols implemented in our center.

Zhenzhu Xiaoji Decoction Induces Autophagy and Apoptosis Cell Death in Liver Cancer Cells through AKT/mTOR and JAK2/STAT3 Signaling Pathway.

Background: Liver cancer is one of the most common digestive tumors. The prescription Zhenzhu Xiaoji decoction (ZZXJD) has a certain effect on the growth and survival of primary liver cancer. Object: This article aimed to explore the effect and molecular mechanism of ZZXJD on liver cancer SMMC-7721 cells. Method: The research groups were divided into the model group, ZZXJD group, and cisplatin group. SMMC-7721 cells were treated with different concentrations of ZZXJD-medicated serum for 24 h and 48 h. The cell viability was measured with CCK8 assay, and cell morphology was observed by fluorescence microscope and transmission electron microscope (TEM). Western blot, RT-PCR, and gene chip were used to determine the protein expression level and gene expression level of cells and tumor tissues. Results: ZZXJD inhibited the proliferation activity of SMMC-7721 cells in a concentration- and time-dependent manner. The morphological changes of the cell showed apoptosis and autophagy. The gene expression of protein kinase B (AKT), mammalian target of rapamycin (mTOR), Janus kinase 2 (JAK2), and signal transducer and activator of transcription 3(STAT3) were downregulated compared with the model group(p < 0.05). The nude mice experiments confirmed that ZZXJD inhibited the growth of tumors in tumor-bearing mice, and the effect increased with the increase of concentration. Conclusion: ZZXJD induced autophagy and apoptosis of liver cancer cells via inhibiting AKT/mTOR signaling pathway and JAK2/STAT3 signaling pathway, thereby affecting the growth and survival of liver cancer cells.

Robust phase-based texture descriptor for classification of breast ultrasound images.

BACKGROUND: Classification of breast ultrasound (BUS) images is an important step in the computer-aided diagnosis (CAD) system for breast cancer. In this paper, a novel phase-based texture descriptor is proposed for efficient and robust classifiers to discriminate benign and malignant tumors in BUS images. METHOD: The proposed descriptor, namely the phased congruency-based binary pattern (PCBP) is an oriented local texture descriptor that combines the phase congruency (PC) approach with the local binary pattern (LBP). The support vector machine (SVM) is further applied for the tumor classification. To verify the efficiency of the proposed PCBP texture descriptor, we compare the PCBP with other three state-of-art texture descriptors, and experiments are carried out on a BUS image database including 138 cases. The receiver operating characteristic (ROC) analysis is firstly performed and seven criteria are utilized to evaluate the classification performance using different texture descriptors. Then, in order to verify the robustness of the PCBP against illumination variations, we train the SVM classifier on texture features obtained from the original BUS images, and use this classifier to deal with the texture features extracted from BUS images with different illumination conditions (i.e., contrast-improved, gamma-corrected and histogram-equalized). The area under ROC curve (AUC) index is used as the figure of merit to evaluate the classification performances. RESULTS AND CONCLUSIONS: The proposed PCBP texture descriptor achieves the highest values (i.e. 0.894) and the least variations in respect of the AUC index, regardless of the gray-scale variations. It's revealed in the experimental results that classifications of BUS images with the proposed PCBP texture descriptor are efficient and robust, which may be potentially useful for breast ultrasound CADs.

[Studies on purification of total saponins from the leaves of Acanthopanax trifoliatus by macroporous adsorption resin].

OBJECTIVE: To study the enrichment and purification of total saponins from the leaves of A. trifoliatus. METHODS: Using the total saponins from the leaves of A. trifoliantus as the standard index, we examinad the capability of static adsorption and desorption to select the optimum macroporous adsportion resin. Then we studied the purification technological parameters such as pH value, the dynamic adorption speed of flow, the best type quantity, the eluent density and so on. RESULTS: The optimum purification conditions were as follows: the type of macroporous adsorption resin was AB-8, the pH value of absorbing solution was 5-6, the absorbing velocity of flow was 1.0 mL/min, the concentration of ethanol as elutent was 70%, the proportion of the amount of absorbing solution and resins was 4:1, the proportion of the amount of elutent and resins was 4:1, the eluting velocity of flow was 2.0 mL/min.