Uridine diphosphate glucuronosyltransferase 1A1 prevents the progression of liver injury.

BACKGROUND: Uridine diphosphate glucuronosyltransferase 1A1 (UGT1A1) plays a crucial role in metabolizing and detoxifying endogenous and exogenous substances. However, its contribution to the progression of liver damage remains unclear. AIM: To determine the role and mechanism of UGT1A1 in liver damage progression. METHODS: We investigated the relationship between UGT1A1 expression and liver injury through clinical research. Additionally, the impact and mechanism of UGT1A1 on the progression of liver injury was analyzed through a mouse model study. RESULTS: Patients with UGT1A1 gene mutations showed varying degrees of liver damage, while patients with acute-on-chronic liver failure (ACLF) exhibited relatively reduced levels of UGT1A1 protein in the liver as compared to patients with chronic hepatitis. This suggests that low UGT1A1 levels may be associated with the progression of liver damage. In mouse models of liver injury induced by carbon tetrachloride (CCl4) and concanavalin A (ConA), the hepatic levels of UGT1A1 protein were found to be increased. In mice with lipopolysaccharide or liver steatosis-mediated liver-injury progression, the hepatic protein levels of UGT1A1 were decreased, which is consistent with the observations in patients with ACLF. UGT1A1 knockout exacerbated CCl4- and ConA-induced liver injury, hepatocyte apoptosis and necroptosis in mice, intensified hepatocyte endoplasmic reticulum (ER) stress and oxidative stress, and disrupted lipid metabolism. CONCLUSION: UGT1A1 is upregulated as a compensatory response during liver injury, and interference with this upregulation process may worsen liver injury. UGT1A1 reduces ER stress, oxidative stress, and lipid metabolism disorder, thereby mitigating hepatocyte apoptosis and necroptosis.

Effect mechanism of capsaicin and dihydrocapsaicin in chili on the oxidative stability of myoglobin in duck meat.

BACKGROUND: Myoglobin (Mb) in duck meat is commonly over-oxidized when heated at high temperatures, which may worsen the color of the meat. Enhancing the oxidative stability of Mb is essential for improving the color of duck meat. Capsaicin and dihydrocapsaicin (CA-DI) in chili exhibit antioxidant properties. This study investigated the effects of CA-DI on the structure and oxidative damage of Mb by fluorescence spectroscopy, differential scanning calorimetry analysis and particle size in duck meat during heat treatment. RESULTS: When the ratio of CA-DI to Mb was 10:1 g kg-1 and heat-treated for 36 min, oxymyoglobin significantly increased, and metmyoglobin significantly decreased compared with the control group (P < 0.05). In parallel, the carbonyl content of Mb in the CA-DI group decreased by 43.40 ± 0.10%, the sulfhydryl content increased by 188 ± 0.21%, and the free radical scavenging activity of Mb was significantly enhanced (P < 0.05). Moreover, the addition of CA-DI resulted in a significant decrease in the particle size of the Mb surface (P < 0.05). When the ratio of CA-DI to Mb was 10:1 g kg-1, CA-DI enhanced the thermal stability and significantly increased the thermal denaturation temperature of Mb. The molecular docking results indicated that hydrophobic interactions and hydrogen bonds were involved in the binding of CA-DI to Mb. CONCLUSION: CA-DI could combine with Mb and improve the oxidation stability of Mb in duck meat. This suggested that CA-DI could be a potential natural antioxidant that improves the color of meat products. © 2024 Society of Chemical Industry.

Treatment outcome and germline predictive factors of ropeginterferon alpha-2b in myeloproliferative neoplasm patients.

BACKGROUND: Studies have shown that some single nucleotide polymorphisms (SNPs) could serve as excellent markers in foretelling the treatment outcome of interferon (IFN) in myeloproliferative neoplasms (MPN). However, most work originated from western countries, and data from different ethnic populations have been lacking. METHODS: To gain insights, targeted sequencing was performed to detect myeloid-associated mutations and SNPs in eight loci across three genes (IFNL4, IFN-γ, and inosine triphosphate pyrophosphatase [ITPA]) to explore their predictive roles in our cohort of 21 ropeginterferon alpha-2b (ROPEG)-treated MPN patients, among whom real-time quantitative PCR was also performed periodically to monitor the JAK2V617F allele burden in 19 JAK2V617F-mutated cases. RESULTS: ELN response criteria were adopted to designate patients as good responders if they achieved complete hematological responses (CHR) within 1 year (CHR1) or attained major molecular responses (MMR), which occurred in 70% and 45% of the patients, respectively. IFNL4 and IFN-γ gene SNPs were infrequent in our population and were thus excluded from further analysis. Two ITPA SNPs rs6051702 A>C and rs1127354 C>A were associated with an inferior CHR1 rate and MMR rate, respectively. The former seemed to be linked to grade 2 or worse hepatotoxicity as well, although the comparison was of borderline significance only (50%, vs. 6.7% in those with common haplotype, p = 0.053). Twelve patients harbored 19 additional somatic mutations in 12 genes, but the trajectory of these mutations varied considerably and was not predictive of any response. CONCLUSIONS: Overall, this study provided valuable information on the ethnics- and genetics-based algorithm in the treatment of MPN.

The use of interventional procedures for cancer pain. A brief review.

CONTEXT: Pain is a common experience in people living with cancer. Concerns around opioid prescribing have seen a move toward a multi-modality management approach, which includes interventional pain procedures. PURPOSE: In this paper we discuss the interventional pain procedures used to treat cancer pain at two major tertiary centers in Australia. METHODS AND RESULTS: This expert review provides practical insights on cancer pain management from healthcare providers in different specialties. These insights can be used to guide the management of a wide range of cancer pain types. CONCLUSIONS: Furthermore, this review identifies the need for a systematic and comprehensive approach to the management of cancer pain that is broader than that of a single specialty. With recent advances in pain management procedures, an interdisciplinary approach is essential in order to provide an up to date, patient tailored approach to pain management. This review will help inform the development of a cancer pain intervention registry.

Motion sensitive network for action recognition in control and decision-making of autonomous systems.

Spatial-temporal modeling is crucial for action recognition in videos within the field of artificial intelligence. However, robustly extracting motion information remains a primary challenge due to temporal deformations of appearances and variations in motion frequencies between different actions. In order to address these issues, we propose an innovative and effective method called the Motion Sensitive Network (MSN), incorporating the theories of artificial neural networks and key concepts of autonomous system control and decision-making. Specifically, we employ an approach known as Spatial-Temporal Pyramid Motion Extraction (STP-ME) module, adjusting convolution kernel sizes and time intervals synchronously to gather motion information at different temporal scales, aligning with the learning and prediction characteristics of artificial neural networks. Additionally, we introduce a new module called Variable Scale Motion Excitation (DS-ME), utilizing a differential model to capture motion information in resonance with the flexibility of autonomous system control. Particularly, we employ a multi-scale deformable convolutional network to alter the motion scale of the target object before computing temporal differences across consecutive frames, providing theoretical support for the flexibility of autonomous systems. Temporal modeling is a crucial step in understanding environmental changes and actions within autonomous systems, and MSN, by integrating the advantages of Artificial Neural Networks (ANN) in this task, provides an effective framework for the future utilization of artificial neural networks in autonomous systems. We evaluate our proposed method on three challenging action recognition datasets (Kinetics-400, Something-Something V1, and Something-Something V2). The results indicate an improvement in accuracy ranging from 1.1% to 2.2% on the test set. When compared with state-of-the-art (SOTA) methods, the proposed approach achieves a maximum performance of 89.90%. In ablation experiments, the performance gain of this module also shows an increase ranging from 2% to 5.3%. The introduced Motion Sensitive Network (MSN) demonstrates significant potential in various challenging scenarios, providing an initial exploration into integrating artificial neural networks into the domain of autonomous systems.

CCNA2 and NEK2 regulate glioblastoma progression by targeting the cell cycle.

Glioblastoma (GBM) is characterized by significant heterogeneity, leading to poor survival outcomes for patients, despite the implementation of comprehensive treatment strategies. The roles of cyclin A2 (CCNA2) and NIMA related kinase 2 (NEK2) have been extensively studied in numerous cancers, but their specific functions in GBM remain to be elucidated. The present study aimed to investigate the potential molecular mechanisms of CCNA2 and NEK2 in GBM. CCNA2 and NEK2 expression and prognosis in glioma were evaluated by bioinformatics methods. In addition, the distribution of CCNA2 and NEK2 expression in GBM subsets was determined using pseudo-time analysis and tricycle position of single-cell sequencing. Gene Expression Omnibus and Kyoto Encyclopedia of Genes and Genome databases were employed and enrichment analyses were conducted to investigate potential signaling pathways in GBM subsets and a nomogram was established to predict 1-, 2- and 3-year overall survival probability in GBM. CCNA2 and NEK2 expression levels were further validated by western blot analysis and immunohistochemical staining in GBM samples. High expression of CCNA2 and NEK2 in glioma indicates poor clinical outcomes. Single-cell sequencing of GBM revealed that these genes were upregulated in a subset of positive neural progenitor cells (P-NPCs), which showed significant proliferation and progression properties and may activate G2M checkpoint pathways. A comprehensive nomogram predicts 1-, 2- and 3-year overall survival probability in GBM by considering P-NPCs, age, chemotherapy and radiotherapy scores. CCNA2 and NEK2 regulate glioblastoma progression by targeting the cell cycle, thus indicating the potential of novel therapy directed to CCNA2 and NEK2 in GBM.

Ten-year epidemiology and risk factors of cytomegalovirus infection in hematopoietic stem cell transplantation patients in Taiwan.

BACKGROUND: Cytomegalovirus (CMV) can cause infection and critical diseases in hematopoietic stem cell transplantation (HSCT) recipients. This study aimed to explore the cumulative incidence and risk factors for CMV infection and disease among HSCT recipients in Taiwan. METHODS: This retrospective cohort study using the Taiwan Blood and Marrow Transplantation Registry (TBMTR) included HSCT recipients between 2009 and 2018 in Taiwan. The primary outcome was cumulative incidence of CMV infection or disease at day 100 after HSCT. Secondary outcomes included day 180 cumulative incidence of CMV infection or disease, infection sites, risk factors for CMV infection or disease, survival analysis, and overall survival after CMV infection and disease. RESULTS: There were 4394 HSCT recipients included in the study (2044 auto-HSCT and 2350 allo-HSCT). The cumulative incidence of CMV infection and disease was significantly higher in allo-HSCT than in auto-HSCT patients at day 100 (53.7% vs. 6.0%, P < 0.0001 and 6.1% vs. 0.9%, P < 0.0001). Use of ATG (HR 1.819, p < 0.0001), recipient CMV serostatus positive (HR 2.631, p < 0.0001) and acute GVHD grades ≥ II (HR 1.563, p < 0.0001) were risk factors for CMV infection, while matched donor (HR 0.856, p = 0.0180) and myeloablative conditioning (MAC) (HR 0.674, p < 0.0001) were protective factors. CONCLUSION: The study revealed a significant disparity in terms of the incidence, risk factors, and clinical outcomes of CMV infection and disease between auto and allo-HSCT patients. These findings underscore the importance of considering these factors in the management of HSCT recipients to improve outcomes related to CMV infections.

Transversus Thoracic Muscle Plane Block For Postoperative Pain in Pediatric Cardiac Surgery: A Systematic Review And Meta-Analysis of Randomized And Observational Studies.

OBJECTIVES: Pediatric patients undergoing cardiac surgery usually experience significant surgical pain. Additionally, the effect of poor surgical analgesia creates a pain continuum that extends to the postoperative period. Transversus thoracic muscle plane block (TTMPB) is a novel plane block technique that can provide analgesia to the anterior chest wall. The analgesic role of TTMPB in pediatric cardiac surgery is still uncertain. A meta-analysis was conducted to determine the analgesic efficacy of this procedure. DESIGN AND SETTING: Systematic review and meta-analysis. PubMed, Embase, Web of Science, CENTRAL, WanFang Data, and the China National Knowledge Infrastructure were searched to November 2023, and the Grading of Recommendations Assessment, Development, and Evaluation approach was followed to evaluate the certainty of evidence. PARTICIPANTS: Eligible studies enrolled pediatric patients from 2 months to 12 years old scheduled to undergo cardiac surgery, and randomized them to receive a TTMPB or no block/sham block. MEASUREMENTS AND MAIN RESULTS: Six studies that enrolled 601 pediatric patients were included. Low-certainty evidence from randomized trials showed that, compared with no block or sham block, TTMPB in pediatric patients undergoing cardiac surgery may reduce postoperative modified objective pain score at 12 hours (weighted mean difference [WMD] -2.20, 95% CI -2.73 to -1.68) and 24 hours (WMD -1.76, 95% CI -2.09 to -1.42), intraoperative opioid consumption (WMD -3.83, 95% CI -5.90 to -1.76 µg/kg), postoperative opioid consumption (WMD -2.51, 95% CI -2.84 to -2.18 µg/kg), length of intensive care unit (ICU) stay (WMD -5.56, 95% CI -8.30 to -2.83 hours), and extubation time (WMD -2.13, 95% CI -4.21 to -0.05 hours). Retrospective studies provided very low certainty that the results were consistent with the randomized trials. CONCLUSION: Very low- to low-certainty evidence showed that TTMPB in pediatric patients undergoing cardiac surgery may reduce postoperative pain, opioid consumption, ICU length of stay, and extubation time.

Leveraging neuro-inspired AI accelerator for high-speed computing in 6G networks.

The field of wireless communication is currently being pushed to new boundaries with the emergence of 6G technology. This advanced technology requires substantially increased data rates and processing speeds while simultaneously requiring energy-efficient solutions for real-world practicality. In this work, we apply a neuroscience-inspired machine learning model called echo state network (ESN) to the critical task of symbol detection in massive MIMO-OFDM systems, a key technology for 6G networks. Our work encompasses the design of a hardware-accelerated reservoir neuron architecture to speed up the ESN-based symbol detector. The design is then validated through a proof of concept on the Xilinx Virtex-7 FPGA board in real-world scenarios. The experiment results show the great performance and scalability of our symbol detector design across a range of MIMO configurations, compared with traditional MIMO symbol detection methods like linear minimum mean square error. Our findings also confirm the performance and feasibility of our entire system, reflected in low bit error rates, low resource utilization, and high throughput.

Evaluation of the Risk Prediction Models in Predicting Kidney Outcomes in Antiglomerular Basement Membrane Disease.

Introduction: A previous study showed that the renal risk score (RRS) was transferrable to antiglomerular basement membrane (anti-GBM) disease and proposed a risk stratification according to the need of renal replacement therapy (RRT) and the percentage of normal glomeruli (N). Herein, we analyzed the risk factors associated with kidney outcomes in patients with biopsy-proven anti-GBM disease and evaluated these 2 prognosis systems. Methods: A total of 120 patients with biopsy-proven anti-GBM disease with complete clinicopathologic and outcome data were analyzed. Results: The median time to kidney biopsy was 41 days (interquartile range [IQR]: 22-63 days). RRT and N were the only independent predictors of end-stage kidney disease (ESKD). Patients with N ≥10% were more likely to achieve ESKD-free outcomes, even in the subcohort of patients who underwent posttreatment biopsies (P < 0.001). N and serum creatinine at presentation (cut-off values 750 µmol/l and 1300 µmol/l) were 2 independent factors for predicting kidney recovery. The RRS and the risk stratification tool exhibited predictive value for ESKD and could be transferred to patients with kidney biopsy following treatment (Harrell's C statistic [C] = 0.738 and C = 0.817, respectively). However, a cross-over of outcomes among groups was observed in the risk stratification tool in long-term follow-up, when patients with RRT and N ≥10% achieved better kidney outcomes than those without RRT but N <10%. Conclusion: Normal glomeruli percentage, even posttreatment, was a strong indicator for kidney outcomes, especially on long-term prognosis. Serum creatinine is a predictor for kidney recovery, independent of biopsy findings. The risk stratification tool for kidney survival was transferrable to patients with anti-GBM disease with biopsy following treatment in our cohort; however, this needs further validations for long-term outcomes.

First Family Case of Hemoglobinopathy Titusville in China with Falsely Low SpO2 and Unmeasurable SaO2.

BACKGROUND: Normal hemoglobin is a tetrameric structure, consisting of two alpha-globin chains and two nonalpha (beta, gamma, delta) chains. Hemoglobinopathies occur when the presence of gene mutations affect the molecular structure or expression of the globin chains. METHODS: We reported the case of a 9-year-old Chinese girl who presented with abnormal low oxygen saturation values on pulse oximetry and no oximetry results were obtained during blood gas analysis (BGA). RESULTS: High-performance liquid chromatography (HPLC) and capillary electrophoresis demonstrated that the presence of a low oxygen affinity hemoglobin variant, characterized as hemoglobin Titusville, was proven by gene sequencing. The patient's mother and aunt also carry the hemoglobin variant, representing the first Chinese family case reported. CONCLUSIONS: Hemoglobin Titusville is a rare genetic hemoglobin structural defect. early diagnosis can help patients and clinicians avoid unnecessary anxiety and costly or excessive clinical investigations.

Leave No Photon Behind: Artificial Intelligence in Multiscale Physics of Photocatalyst and Photoreactor Design.

Although solar fuels photocatalysis offers the promise of converting carbon dioxide directly with sunlight as commercially scalable solutions have remained elusive over the past few decades, despite significant advancements in photocatalysis band-gap engineering and atomic site activity. The primary challenge lies not in the discovery of new catalyst materials, which are abundant, but in overcoming the bottlenecks related to material-photoreactor synergy. These factors include achieving photogeneration and charge-carrier recombination at reactive sites, utilizing high mass transfer efficiency supports, maximizing solar collection, and achieving uniform light distribution within a reactor. Addressing this multi-dimensional problem necessitates harnessing machine learning techniques to analyze real-world data from photoreactors and material properties. In this perspective, the challenges are outlined associated with each bottleneck factor, review relevant data analysis studies, and assess the requirements for developing a comprehensive solution that can unlock the full potential of solar fuels photocatalysis technology. Physics-informed machine learning (or Physics Neural Networks) may be the key to advancing this important area from disparate data towards optimal reactor solutions.

Establishment and Validation of a Transdermal Drug Delivery System for the Anti-Depressant Drug Citalopram Hydrobromide.

To enhance the bioavailability and antihypertensive effect of the anti-depressant drug citalopram hydrobromide (CTH) we developed a sustained-release transdermal delivery system containing CTH. A transdermal diffusion meter was first used to determine the optimal formulation of the CTH transdermal drug delivery system (TDDS). Then, based on the determined formulation, a sustained-release patch was prepared; its physical characteristics, including quality, stickiness, and appearance, were evaluated, and its pharmacokinetics and irritation to the skin were evaluated by applying it to rabbits and rats. The optimal formulation of the CTH TDDS was 49.2% hydroxypropyl methyl cellulose K100M, 32.8% polyvinylpyrrolidone K30, 16% oleic acid-azone, and 2% polyacrylic acid resin II. The system continuously released an effective dose of CTH for 24 h and significantly enhanced its bioavailability, with a higher area under the curve, good stability, and no skin irritation. The developed CTH TDDS possessed a sustained-release effect and good characteristics and pharmacokinetics; therefore, it has the potential for clinical application as an antidepressant.

Employing hybrid deep learning for near-real-time forecasts of sensor-based algal parameters in a Microcystis bloom-dominated lake.

Harmful cyanobacterial blooms (CyanoHABs) are increasingly impacting the ecosystem of lakes, reservoirs and estuaries globally. The integration of real-time monitoring and deep learning technology has opened up new horizons for early warnings of CyanoHABs. However, unlike traditional methods such as pigment quantification or microscopy counting, the high-frequency data from in-situ fluorometric sensors display unpredictable fluctuations and variability, posing a challenge for predictive models to discern underlying trends within the time-series sequence. This study introduces a hybrid framework for near-real-time CyanoHABs predictions in a cyanobacterium Microcystis-dominated lake - Lake Dianchi, China. The proposed model was validated using hourly Chlorophyll-a (Chl a) concentrations and algal cell densities. Our results demonstrate that applying decomposition-based singular spectrum analysis (SSA) significantly enhances the prediction accuracy of subsequent CyanoHABs models, particularly in the case of temporal convolutional network (TCN). Comparative experiments revealed that the SSA-TCN model outperforms other SSA-based deep learning models for predicting Chl a (R2 = 0.45-0.93, RMSE = 2.29-5.89 µg/L) and algal cell density (R2 = 0.63-0.89, RMSE = 9489.39-16,015.37 cells/mL) at one to four steps ahead predictions. The forecast of bloom intensities achieved a remarkable accuracy of 98.56 % and an average precision rate of 94.04 % ± 0.05 %. In addition, scenarios involving various input combinations of environmental factors demonstrated that water temperature emerged as the most effective driver for CyanoHABs predictions, with a mean RMSE of 2.94 ± 0.12 µg/L, MAE of 1.55 ± 0.09 µg/L, and R2 of 0.83 ± 0.01. Overall, the newly developed approach underscores the potential of a well-designed hybrid deep-learning framework for accurately predicting sensor-based algal parameters. It offers novel perspectives for managing CyanoHABs through online monitoring and artificial intelligence in aquatic ecosystems.

Progress on fluorescent RNA and fluorescent NA-based biosensing technology.

Fluorescent RNA is a kind of emerging RNA labeling technique that can be used for in situ labeling and imaging of RNA in live cells, which plays an important role in understanding the function and regulation mechanism of RNA. Biosensing technology based on fluorescent RNA can be applied in dynamic detection of small molecule metabolites and proteins in real time, offering valuable tools for basic life science research and biomedical sensing technology development. In this review, we introduce the development of genetically encoded fluorescent RNA, and the application of fluorescent RNA in RNA imaging and biosensing technology based on fluorescent RNA in biosensing in live cell. Meanwhile, we discuss the direction and challenge of future development of fluorescent RNA technology to provide valuable insights for further development and application of this technology in relevant fields.

Global acute-on-chronic liver failure trends during 2012-2022: A bibliometric study.

Introduction: Acute-on-chronic liver failure (ACLF) is a clinical syndrome with high short-term mortality. ACLF has been increasingly studied in recent years; however, a bibliometric analysis of the entire ACLF field has not been conducted. This study assesses current global trends and hotspots in ACLF research. Materials and methods: The core Web of Science database was searched for all ACLF-related publications conducted during 2012-2022. The data included information on the author, country, author keywords, publication year, citation frequency, and references. Microsoft Excel was used to collate the data and calculate percentages. VOSviewer software was used for citation and density visualization analysis. Histogram rendering was performed using GraphPad Prism Version 8.0 and R software was used to supplement the analysis. Result: A total of 1609 ACLF-related articles from 67 different countries were identified. China contributed the most literature, followed by the United States. However, Chinese literature only had the 4th highest number of citations, indicating that cooperation with other countries needs to be strengthened. The Journal of Hepatology had the highest number of ACLF-related citations. Prognosis was one of the most common author keywords, which may highlight current research hotspots. Bacterial infection was a common keyword and was closely related to prognosis. Conclusion: This bibliometric analysis suggests that future research hotspots will focus on the interplay among bacterial infection, organ failure, and prognosis.

Measurements of particle extinction coefficients at 1064†nm with lidar: temperature dependence of rotational Raman channels.

Aerosol intensive optical properties, including lidar ratio and particle depolarization ratio, are of vital importance for aerosol typing. However, aerosol intensive optical properties at near-infrared wavelength are less exploited by atmospheric lidar measurements, because of the comparably small backscatter cross section of Raman-scattering and a low efficiency of signal detection compared to what is commonly available at 355 nm and 532 nm. To obtain accurate optical properties of aerosols at near-infrared wavelength, we considered three factors: Raman-spectra selection, detector selection, and interference-filter optimization. Rotational Raman scattering has been chosen for Raman signal detection, because of the higher cross-section compared to vibrational Raman scattering. The optimization of the properties of the interference filter are based on a comprehensive consideration of both signal-to-noise ratio and temperature dependence of the simulated lidar signals. The interference filter that has eventually been chosen uses the central wavelength at 1056 nm and a filter bandwidth (full-width-at-half-maximum) of 6 nm. We built a 3-channel 1064-nm rotational Raman lidar. In this paper two methods are proposed to test the temperature dependence of the signal-detection unit and to evaluate the quality of the Raman signals. We performed two measurements to test the quality of the detection channel: cirrus clouds in the free troposphere and aerosols in the planetary boundary layer. Our analysis of the measured Raman signals shows a negligible temperature dependence of the Raman signals in our system. For cirrus measurements, the Raman signal profile did not show crosstalk even for the case of strong elastic backscatter from clouds, which was about 100 times larger than Rayleigh scattering in the case considered here. The cirrus-mean extinction-to-backscatter ratio (lidar ratio) was 27.8 ± 10.0 sr (1064 nm) at a height of 10.5-11.5 km above ground. For the aerosols in the planetary boundary layer, we found the mean lidar ratio of 38.9 ± 7.0 sr at a height of 1.0-3.0 km above ground.

A Novel Score Based on Controlled Attenuation Parameter Accurately Predicts Hepatic Steatosis in Individuals With Metabolic Dysfunction Associated Steatotic Liver Disease: A Derivation and Independent Validation Study.

INTRODUCTION: In metabolic dysfunction-associated steatotic liver disease, the diagnostic efficacy of controlled attenuation parameter (CAP) was not very accurate in evaluating liver fat content. The aim of this study was to develop a score, based on CAP and conventional clinical parameters, to improve the diagnostic performance of CAP regarding liver fat content. METHODS: A total of 373 participants from 2 independent Chinese cohorts were included and divided into derivation (n = 191), internal validation (n = 75), and external validation (n = 107) cohorts. Based on the significant difference index between the 2 groups defined by the magnetic resonance imaging-proton density fat fraction (MRI-PDFF) in derivation cohort, the optimal model (CAP-BMI-AST score [CBST]) was screened by the number of parameters and the area under the receiver operating characteristic curve (AUROC). In the internal and external validation cohorts, the AUROC and corresponding 95% confidence intervals (CIs) were used to compare the diagnostic performance of CBST with that of CAP. RESULTS: We constructed the CBST = -14.27962 + 0.05431 × CAP - 0.14266 × body mass index + 0.01715 × aspartate aminotransferase. When MRI-PDFF was ≥20%, ≥10%, and ≥5%, the AUROC for CBST was 0.77 (95% CI 0.70-0.83), 0.89 (95% CI 0.83-0.94), and 0.93 (95% CI 0.88-0.98), which was higher than that for CAP respectively. In the internal validation cohort, the AUROC for CBST was 0.80 (95% CI 0.70-0.90), 0.95 (95% CI 0.91-1.00), and 0.98 (95% CI 0.94-1.00). The optimal thresholds of CBST were -0.5345, -1.7404, and -1.9959 for detecting MRI-PDFF ≥20%, ≥10%, and ≥5%, respectively. DISCUSSION: The CBST score can accurately evaluate liver steatosis and is superior to the CAP.

Clinical observation on 90 cases of primary dysmenorrhea treated by buccal acupuncture therapy: a randomized controlled study.

OBJECTIVE: To explore the short-term and long-term efficacy of buccal acupuncture therapy in the treatment of patients with primary dysmenorrhea (PD). METHODS: A total of 90 patients with PD who were admitted to the Second Affiliated Hospital of Zhejiang University of Traditional Chinese Medicine from January 2020 to December 2021 were included in this study and randomly divided into three groups, including the observation group, the control group, and the placebo group, with 30 patients in each group. Patients in the observation group were treated according to the syndrome types of Traditional Chinese Medicine, those in the control group were treated with Saridon, and those in the placebo group received a placebo. The visual analog scale (VAS) scores of these patients were evaluated at different time points (before treatment, 5 min after needle retention, 30 min after needle retention, 1 h after treatment, 2 h after treatment, 1 d after treatment, and 2 d after treatment). The Cox Menstrual Symptom Scale (CMSS) scores were assessed before the treatment and after three courses of treatment. Besides, these two scales were also evaluated during follow-up. Moreover, the pain score and adverse reactions of these patients were assessed during treatment. RESULTS: After treatment, the VAS and CMSS scores in the observation group decreased significantly (P < 0.05) 5 and 30 min after needle retention and after treatment. CONCLUSION: Buccal acupuncture therapy is verified to have short-term efficacy in the treatment of PD. In addition, this therapy has an immediate analgesic effect and long-term efficacy in reducing the severity and frequency of PD.

Neutrophil-to-lymphocyte ratio associated with symptomatic saccular unruptured intracranial aneurysm.

BACKGROUND AND PURPOSE: Whether symptomatic unruptured intracranial aneurysms (UIAs) lead to change in circulating inflammation remains unclear. This study aims to evaluate the role of hematological inflammatory indicators in predicting symptomatic UIA. METHODS: Adult patients diagnosed with saccular intracranial aneurysm from March 2019 to September 2023 were recruited retrospectively. Clinical and laboratory data, including the white blood cells (WBC), neutral counts (NEUT), lymphocyte counts (LYM), and monocyte counts (MONO) of each patient, were collected. The neutrophil-to-lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR) were calculated as NLR = NEUT/LYM, LMR = LYM/MONO, SII = PLT*NEUT/LYM. The hematological inflammatory indicators were compared in symptomatic saccular and asymptomatic UIA patients. Multivariable logistic regression analyses were performed to explore the factors predicting symptomatic UIA. RESULTS: One hundred and fifty UIA patients with a mean age of 58.5 ± 12.4 were included, of which 68% were females. The NLR and LMR were significantly associated with symptomatic UIA, and the association remained in small UIAs (< 7 mm). The multiple logistic regression analysis showed that NLR was independently associated with symptomatic UIA. On ROC curve analysis, the optimal cutoff value of NLR to differentiate symptomatic from asymptomatic was 2.38. In addition, LMR was significantly associated with symptomatic UIA smaller than 7 mm. CONCLUSION: There was a significant correlation between NLR and symptomatic UIA. The NLR was independently associated with symptomatic UIA.