Survival analysis of mortality and development of lupus nephritis in patients with systemic lupus erythematosus up to 40-years of follow-up

OBJECTIVES: Patients with systemic lupus erythematosus (SLE) have increased mortality compared with age and sex-matched controls. Lupus nephritis (LN) is a severe manifestation of SLE and an important cause of death. We carried out a retrospective survival analysis to investigate factors that could influence risk of mortality and LN in a large multi-ethnic cohort of patients with SLE. METHODS: By careful review of medical records, we identified 496 patients with SLE for whom we had complete information regarding period of observation and occurrence of death and nephritis. Patients were stratified into groups according to sex, ethnicity, age at start of follow-up and time-period of diagnosis. Kaplan-Meier analysis was used to investigate differences between the groups. RESULTS: Of 496 patients in the study, 91(18.3%) died, 165(33.3%) developed LN and 33(6.7%) developed end-stage renal failure. There was no difference between men and women in either mortality or development of LN. Caucasian patients were significantly less likely to develop LN than other ethnic groups (p< 0.0001) but not less likely to die. Patients diagnosed before the median age of 28 years were significantly more likely to develop LN (p< 0.0001) but significantly less likely to die (p= 0.0039) during the period of observation. There has been a significant improvement in survival between patients diagnosed between 1978-1989 and those diagnosed between 2006-11 (p= 0.019). CONCLUSION: In our cohort, non-Caucasian ethnicity and younger age at diagnosis are associated with risk of developing LN. There is evidence of improvement in survival of patients with SLE over time

Factors associated with cardiovascular events in systemic lupus erythematosus in a monocentric cohort with up to 40 years of follow-up

OBJECTIVES: Systemic lupus erythematosus (SLE) is associated with an increased cardiovascular risk. Several traditional and disease-specific risk factors have been shown to correlate with the occurrence of cardiovascular events (CVE) in patients with SLE. However, results of previous studies are diverse. The objectives of this study were to report number, type and those factors associated with CVE in patients with SLE in a large, single-center, ethnically diverse cohort with a long follow-up duration. METHODS: Medical records of patients treated at the Lupus Clinic at University College London Hospital (UCLH) between 1979 and 2020 were retrospectively reviewed. Data about CVE, traditional cardiovascular risk factors, demographic and disease features, and treatment history were collected. Only patients with complete available information were included in the study. Regression analyses were performed to identify factors associated with CVE. RESULTS: Four hundred and nineteen patients were included in the study. Maximum follow-up length was 40 years. Seventy-one (17%) patients had at least one CVE. Multivariable analysis showed that only antiphospholipid antibody positivity (p-value<0.001) was associated with CVE. When analysing different types of CVE, antiphospholipid antibodies were specifically associated with both venous thromboembolic events (p-value<0.001) and cerebrovascular events (p-value=0.007). Dedicated subanalyses revealed that cumulative glucocorticoid dose (p-value=0.010) and a diagnosis of SLE before 2000 (p-value<0.001) were significantly associated with CVE. CONCLUSIONS: Cardiovascular disease is highly prevalent among patients with SLE and is associated with antiphospholipid antibodies, glucocorticoid therapy, and diagnosis before 2000

Continuous flow synthesis of N,O-dimethyl-N\u27-nitroisourea monitored by inline FTIR: comparing machine learning and kinetic modeling for optimization

The synthesis of N,O-Dimethyl-N\u27-nitroisourea, crucial intermediates in pesticide manufacturing, was explored through a substitution reaction between O-methyl-N-nitroisourea and methylamine within a novel continuous flow microreactor system, featuring FTIR inline analysis for real-time monitoring. This study embarked on a comparative analysis between two optimization approaches: the contemporary machine learning-based Bayesian optimization and the traditional kinetic modeling. Remarkably, both strategies obtained a similar yield of approximately 83 % under equivalent reaction parameters---specifically, an initial reactant concentration of 0.2 mol/L, a reaction temperature of 40 °C, a molar ratio of reactants at 5:1, and a residence time of 240 minutes. The Bayesian optimization method demonstrated a notable efficiency, achieving optimal conditions within a mere 20 experiments, in contrast to the kinetic modeling approach, which required a more laborious effort for model formulation and validation. Despite the long-standing reliance on kinetic modeling for its detailed insights into reaction dynamics, our findings suggest its relative inefficiency in optimization tasks compared to the machine learning-based alternative. This study not only highlights the potential of integrating advanced machine learning methods into chemical process optimization but also sets the stage for further exploration into efficient, data-driven approaches in chemical synthesis

FlowBO: A Flow Chemistry Bayesian Optimization Framework Benchmarked by Kinetic Models

The applications of flow chemistry (continuous flow reactions) in the synthesis of pharmaceuticals and fine chemicals require more advanced optimization algorithms to guide laboratory-scale and industry-scale optimization. Although several Bayesian Optimization (BO) frameworks have been developed, they are rarely equipped with state-of-the-art noise-handling acquisition functions and have not been benchmarked by multiple real-world continuous flow kinetic models. In this study, we developed FlowBO for flow chemistry, equipped with the recently-developed MOO algorithm qNEHVI that can better handle experimental noise and make parallel recommendations. Also, five kinetic models built from experimental results, including four series reactions, were used as benchmarks for FlowBO and two other recognized BO frameworks. The results show that FlowBO outperforms in all four series reaction cases with optimization results >99.9% for conversion and selectivity. At the same time, FlowBO offers a range of optimum advantages with a wide choice of temperature, residence time, and reactant concentration, facilitating process optimization for subsequent steps (i.e. separation)

Optimizing telescoped heterogeneous catalysis with noise-resilient multi-objective Bayesian optimization

This study evaluates the noise resilience of multi-objective Bayesian optimization (MOBO) algorithms in chemical synthesis, an aspect critical for processes like telescoped reactions and heterogeneous catalysis but seldom systematically assessed. Through simulation experiments on amidation, acylation, and SNAr reactions under varying noise levels, we identify the qNEHVI acquisition function as notably proficient in handling noise. Subsequently, qNEHVI is employed to optimize a two-step heterogeneous catalysis for the continuous-flow synthesis of hexafluoroisopropanol. Achieving considerable optimization within just 20 experimental runs, we report an E-factor of 0.3744 and a conversion rate of 76.20%, with optimal conditions set at 5.00 sccm and 35.00℃ for the first step, and 80.00 sccm and 170℃ for the second. This research highlights qNEHVI\u27s potential in noisy multi-objective optimization and its practical utility in refining complex synthesis processes

A Series of Zr-Based Bulk Metallic Glasses with Room Temperature Plasticity

A group of plastic Zr-Al-Ni-Cu bulk metallic glasses (BMGs) with low Zr content was developed and their thermal and mechanical properties were investigated. The results show that these Zr-based BMGs have a single crystallization event for all heating rates in the studied temperature region. The glass transition temperature Tg decreases with increasing Zr content for all heating rates. There are two melting procedures for the BMGs whose Zr content is less than 52 at %, while three melting procedures for the other Zr-based BMGs. The second melting procedure is split into two melting procedures for Zr52.5Al12.2Ni12.6Cu22.7 and Zr53Al11.6Ni11.7Cu23.7 BMGs, while the first melting procedure is split into two melting procedures for the other BMGs. The activation energy decreases with increasing sensitivity index β for the studied Zr-based BMGs. The plastic strain εp is in the region of 0.2%–19.1% for these Zr-based BMGs. Both yield strength σy and fracture strength σf are smallest for Zr55Al8.9Ni7.3Cu28.8 BMG whose εp is largest among all studied Zr-based BMGs and reaches up to 19.1%. In addition, the mechanism for the large difference of the plasticity among the studied Zr-based BMGs is also discussed

Discovery of LAH-1 as potent c-Met inhibitor for the treatment of non-small cell lung cancer

ABSTRCTDysregulated HGF/c-Met pathway has been implicated in multiple human cancers and has become an attractive target for cancer intervention. Herein, we report the discovery of N-(3-fluoro-4-((2-(3-hydroxyazetidine-1-carboxamido)pyridin-4-yl)oxy)phenyl)-1-(4-fluorophenyl)-4-methyl-6-oxo-1,6-dihydropyridazine-3-carboxamide (LAH-1), which demonstrated nanomolar MET kinase activity as well as desirable antiproliferative activity, especially against EBC-1 cells. Mechanism studies confirmed the effects of LAH-1 on modulation of HGF/c-Met pathway, induction of cell apoptosis, inhibition on colony formation as well as cell migration and invasion. In addition, LAH-1 also showed desirable in vitro ADME properties as well as acceptable in vivo PK parameters. The design, synthesis, and characterisation of LAH-1 are described herein

Licochalcone A suppresses the proliferation of sarcoma HT-1080 cells, as a selective R132C mutant IDH1 inhibitor

IDH1 mutations are closely related to the development and progression of various human cancers, such as glioblastoma, sarcoma, and acute myeloid leukemia. By screening dozens of reported natural compounds using both wild-type and mutant IDH1 enzymatic assays, we discovered Licochalcone A is a selective inhibitor to the R132C-mutant IDH1 with an IC50 value of 5.176 μM, and inhibits the proliferation of sarcoma HT-1080 cells with an IC50 value of 10.75 μM. Suggested by the molecular docking results, Licochalcone A might occupy the allosteric pocket between the two monomers of IDH1 homodimer, and the R132H mutation was unfavorable for the binding of Licochalcone A with the IDH1 protein, as compared to the R132C mutation. Revealed by the RNA-Seq data analysis, the Cell Cycle pathway was the most over-represented pathway for HT-1080 cells treated with Licochalcone A. Consistent with these results, Licochalcone A induced apoptosis and cell cycle arrest of HT-1080 cells, while it showed minimal effect against the proliferation of normal RCTEC cells. The discovery of Licochalcone A as a mutation-selective IDH1 inhibitor can serve as a promising starting point for the development of mutation-selective anti-tumor lead compounds targeting IDH1

Design, synthesis and evaluation of 2, 6, 8-substituted Imidazopyridine derivatives as potent PI3Kα inhibitors

AbstractInhibition of PI3K pathway has become a desirable strategy for cancer treatment. In this work, a series of 2, 6, 8-substituted Imidazo[1,2-a]pyridine derivatives were designed and screened for their activities against PI3Kα and a panel of PI3Kα-addicted cancer cells. Among them, compound 35 was identified as a PI3Kα inhibitor with nanomolar potency as well as acceptable antiproliferative activity. Flow cytometry analysis confirmed 35 induced cell cycle arrest and apoptosis in T47D cells. In addition, it also showed desirable in vitro ADME properties. The design, synthesis, and SAR exploration of 35 are described within