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Cyclophosphamide(CHOP) is a widely used chemotherapeutic agent belonging to the class of alkylating agents. It primarily inhibits the proliferation of tumor cells by interfering with DNA replication and transcription. CHOP has been approved for the treatment of various types of malignant tumors. The aim of this research is to assess adverse events linked to CHOP using real-world data. This research collected and analyzed adverse event reports associated with CHOP from the FAERS(US Food and Drug Administration Adverse Event Reporting System) database spanning from the first quarter of 2004 to the third quarter of 2024. This study leveraged the FAERS database, extracting reports submitted exclusively by healthcare professionals where CHOP was designated as the primary suspect (PS). Four risk signal detection methods were employed: Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multiitem Gamma Poisson Shrinker (MGPS), to conduct a comprehensive analysis of CHOP-related ADRs. A total of 3,625 adverse event reports with CHOP as the primary suspect drug were obtained. Across 25 system organ classes (SOCs), four positive Preferred Terms(PTs) signals were detected. The most significant signal in SOCs was \"blood and lymphatic system disorders\" (ROR = 6.64, 95% CI 6.49-6.79), while the most significant PTs signal was \"high grade B-cell lymphoma Burkitt-like lymphoma recurrent\" (ROR = 613.63, 95% CI 123.85-3040.40). This study provides compelling evidence of the presence of CHOP seven unexpected off-label AEs were also observed, such as mucoepidermoid carcinoma, hypotelorism of orbit, breakthrough COVID-19, airway remodeling, meningitis enteroviral, acute graft versus host disease, and gastrosplenic fistula. Additionally, the combination of CHOP and radiotherapy increased the risk of several severe AEs, such as hemorrhagic cystitis. These findings highlight the importance of caution when prescribing CHOP to high-risk individuals with a history of meningitis, cystitis or airway obstruction.

β-Carotene has extensive applications in the food, pharmaceutical, and cosmetics industries. Traditional chemical synthesis methods face challenges such as byproduct residues and high costs, whereas natural extraction is constrained by low yields and complex processes. Recent advancements in synthetic biology and metabolic engineering have paved the way for the heterologous biosynthesis of β-carotene in microorganisms. Owing to its rapid growth, convenience of genetic manipulation, and suitability for producing apocarotenoids, Escherichia coli is an ideal host for the production of β-carotene and its derivatives, as exemplified by the record production of multiple apocarotenoids in engineered E. coli strains. Here, we summarize the metabolic engineering strategies employed to produce β-carotene in E. coli, including manipulation of the endogenous MEP pathway, introduction of the hybrid MVA pathway, modulation of central carbon metabolism, modification of the cell membrane, and fermentation process optimization. As β-carotene acts as a biosynthetic hub for many carotenoids and apocarotenoids, we also highlighted the importance of efficient β-carotene production for the sustainable preparation of these compounds. This review aims to provide theoretical insights for designing talented β-carotene producers and laying the foundation for the sustainable manufacturing of valuable carotenoids and apocarotenoids.

To further explore the anti-inflammatory components of the seeds of Dolichos lablab L., a comprehensive phytochemical investigation was conducted using diverse chromatographic and spectrometric technologies, as well as chemical reactions. As a result, ten previously unreported terpenoid glycosides, namely dolilabterpenosides A, B, C1–C3, D, E, and F1–F3 (1–10), along with four known analogues (11–14), initially identified from Dolichos genus, were obtained. In addition, the lipopolysaccharide (LPS)-induced RAW264.7 cell model was employed to detect the expression levels of nitric oxide (NO), inflammatory cytokines tumour necrosis factor (TNF)-α and interleukin (IL)-1β to assess the anti-inflammatory activities of the obtained compounds. The results of bioactive assay showed that compounds 1, 4–7, and 10–12 showed significant inhibitory activity on NO release in RAW264.7 cells in a dose-dependent manner, and all of them were demonstrated to inhibit the increase in TNF-α and IL-Iβ levels in the supernatant of RAW264.7 cells stimulated by LPS.

L-ornithine L-aspartate (LOLA) is indicated for reducing blood ammonia levels and alleviating symptoms of hepatobiliary disorders. Data mining of adverse events associated with LOLA was carried out in the FDA Adverse Event Reporting System database. The aim was to explore its potential medication risks and offer more reasonable and safe references for clinical medication. This study retrieved and extracted adverse event reports related to LOLA from the FAERS database from 2004Q1 to 2024Q3. The main method utilized was the reporting odds ratio for the detection of risk signals related to LOLA. In total, 413 adverse event reports where LOLA was the primary suspect drug were recognized, and a sum of 670 adverse events were reported. These reports mainly came from patients aged 40–65 and older. Most of these reports were submitted by healthcare professionals. After screening LOLA, 323 positive risk signals for AEs were found, which were distributed across 25 system organ classes. Among these, hepatobiliary disorders topped the list. Specifically, 84 positive risk signals were identified for liver-related AEs, which is in line with the adverse reactions about LOLA published by the FDA. The risk of hepatobiliary disorders was not described in the manual, but this study found that the positive signal risk for the hepatobiliary system is the highest. This research underscores the substantial influence of LOLA on hepatobiliary disorders, stressing the necessity for vigilant monitoring of potential liver toxicity. Besides concentrating on the short-term adverse reactions after LOLA administration, it is also crucial to conduct in-depth research on its long-term safety. This study provides suggestions and directions for the rational and safe clinical application of LOLA. Prospective studies in the future are required to further investigate the occurrence of relevant adverse events.

Vorapaxar is a platelet protease-activated receptor-1 antagonist that can inhibit thrombin- and thrombin receptor agonist peptide-induced platelet aggregation. This study aims to explore the potential medication risks of vorapaxar through data mining of its related adverse events, thereby providing a more rational and safe reference for clinical medication. In this study, adverse event reports related to Vorapaxar were retrieved and extracted from the FAERS database covering the 2004 Q1to 2024 Q4. The primary method employed was the reporting odds ratio (ROR) approach, which was used to detect risk signals associated with Vorapaxar. A total of 185 adverse event reports were included in this study, among which male cases accounted for 52%, higher than the proportion of female cases. Most reports were submitted by consumers, and the majority of these reports originated from the United States. Screening of Vorapaxar identified 162 preferred terms (PTs), most of which were consistent with the adverse reaction information of Vorapaxar already published by the U.S. Food and Drug Administration (FDA). The adverse events involved 19 organ systems. Reports on vascular diseases, neurological diseases, and other conditions were numerous with strong signals, which were consistent with the drug instructions. Among them, vascular diseases had the highest risk of positive signals, including various hemorrhagic events and vascular structural/functional abnormalities. These findings suggest that clinical practice should be alert to adverse reactions in the vascular system, especially bleeding and severe vascular structural abnormalities.

Abstract Chimeric antigen receptor (CAR)-modified T-cell therapy has achieved remarkable success in the treatment of acute lymphoblastic leukemia (ALL). Measurable/minimal residual disease (MRD) monitoring plays a significant role in the prognostication and management of patients undergoing CAR-T-cell therapy. Common MRD detection methods include flow cytometry (FCM), polymerase chain reaction (PCR), and next-generation sequencing (NGS), and each method has advantages and limitations. It has been well documented that MRD positivity predicts a poor prognosis and even disease relapse. Thus, how to perform prognostic evaluations, stratify risk based on MRD status, and apply MRD monitoring to guide individual therapeutic decisions have important implications in clinical practice. This review assesses the common and novel MRD assessment methods. In addition, we emphasize the critical role of MRD as a prognostic biomarker and summarize the latest studies regarding MRD-directed combination therapy with CAR-T-cell therapy and allogeneic hematopoietic stem cell transplantation (allo-HSCT), as well as other therapeutic strategies to improve treatment effect. Furthermore, this review discusses current challenges and strategies for MRD detection in the setting of disease relapse after targeted therapy.

Abstract Background: Hematological malignancies are a heterogeneous group of diseases caused by disruptions in normal hematopoietic function. This study aimed to evaluate the global burden of hematological malignancies, including Hodgkin lymphoma (HL), non-Hodgkin lymphoma (NHL), multiple myeloma (MM), and leukemia, with a focus on comparing China and the United States (US). Methods: Data from the GLOBOCAN 2022 and Global Burden of Disease (GBD) 2021 were used to estimate the incidence and mortality of hematological malignancies. This study analyzed the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR), and estimated annual percentage change (EAPC) to compare trends over time, and risk factors were also assessed. Results: In 2022, there were 1,311,104 new cases and 700,205 deaths from hematological malignancies worldwide. Among them, there were 197,438 new cases and 110,367 deaths in China, whereas in the US, there were 181,894 new cases and 58,283 deaths. NHL was the most common type of hematological malignancy, followed by leukemia, MM, and HL globally. Males had higher incidence and mortality rates than females. Compared with China, the US had higher ASIR (30.65 vs. 9.51 per 100,000) and ASMR (7.33 vs. 4.73 per 100,000) in 2022. Additionally, the ASIR and ASMR were higher in very high human development index (HDI) countries than in low HDI countries. The incidence of NHL and MM has increased over time, whereas the incidence of HL and leukemia has decreased worldwide. The ASMRs for all types of hematological malignancies, except for MM, have been declining. Furthermore, we identified risk factors contributing to hematological malignancy disability-adjusted life years (DALYs) and deaths, including smoking, high body mass index, and occupational exposure to benzene or formaldehyde. The predicted number of new cases of and deaths from hematological malignancies gradually increased from 2022 to 2050. Conclusions: This study highlights the serious burden of hematological malignancies worldwide, in China, and in the US, emphasizing the urgency for effective prevention and treatment strategies.

More than 80 years have passed since zooarchaeology first began in China in the early 1930s. Currently, this discipline is one of the most active fields in Chinese archaeology, engaging with other sub-disciplines such as archaeogenetics, archaeobotany, and stable isotopic studies. But how did we end up like this? This paper explores this question by surveying existing zooarchaeological publications from the Neolithic to Pre-Han periods (c. 8000–202 bc ). Results show that journals are the most popular publishing type, followed by archaeological reports. Postgraduate theses are also taken into account. With consideration of publication numbers, three chronological periods can be recognised. These phases are associated with political/social events of the twentieth century in China. While the majority of articles concern basic identification, there has been an increasing interest on human-animal interactions during recent years. In addition, while central China is the overwhelming focus of zooarchaeological research, some areas may have been overlooked.

Air temperature (Ta) is essential for studying surface processes and human activities, particularly agricultural cultivation, which is strongly influenced by temperature. Remote sensing techniques that integrate multi-source data can estimate Ta with a high degree of accuracy, overcoming the shortcomings of traditional measurements due to spatial heterogeneity. Based on in situ measurements in Guangdong Province from 2012 to 2018, this study applied three machine learning (ML) models and fused multi-source datasets to evaluate the performance of four data combinations in Ta estimation. Correlations of covariates were compared, focusing on rice planting areas (RA). The results showed that (1) The fusion of multi-source data improved the accuracy of model estimations, where the best performance was achieved by the random forest (RF) model combined with the ERA5 combination, with the highest R2 reaching 0.956, the MAE value of 0.996 °C, and the RMSE of 1.365 °C; (2) total precipitation (TP), wind speed (WD), normalized difference vegetation index (NDVI), and land surface temperature (LST) were significant covariates for long-term Ta estimations; (3) Rice planting improved the model performance in estimating Ta, and model accuracy decreased during the crop rotation in summer. This study provides a reference for the selection of temperature estimation models and covariate datasets. It offers a case for subsequent ML studies on remote sensing of temperatures over agricultural areas and the impact of agricultural cultivation on global warming.

This paper investigates the robust control problem of the speed tension and screw down system of Reversible Cold Strip Rolling Mill (RCSRM). A finite-time observer is proposed to observe the uncertainties of the system. Based on the finite time observer, a fractional-order backstepping sliding mode controller is designed for each sub-system of the speed tension and screw down system of RCSRM. The Particle Swarm Optimization (PSO) algorithm is used to optimize the main parameters of the designed controller. By Lyapunov stability, the tracking error of the system can converge to the neighbourhood of the equilibrium point in a finite time. Finally, simulation research is carried out on the actual data of a 1422 mm RCSRM, and the effectiveness of the designed controller is verified.