Navitoclax safety, tolerability, and effect on biomarkers of senescence and neurodegeneration in aged nonhuman primates.

Alzheimer's disease (AD) is the most common global dementia and is universally fatal. Most late-stage AD disease-modifying therapies are intravenous and target amyloid beta (Aß), with only modest effects on disease progression: there remains a high unmet need for convenient, safe, and effective therapeutics. Senescent cells (SC) and the senescence-associated secretory phenotype (SASP) drive AD pathology and increase with AD severity. Preclinical senolytic studies have shown improvements in neuroinflammation, tau, Aß, and CNS damage; most were conducted in transgenic rodent models with uncertain human translational relevance. In this study, aged cynomolgus monkeys had significant elevation of biomarkers of senescence, SASP, and neurological damage. Intermittent treatment with the senolytic navitoclax induced modest reversible thrombocytopenia; no serious drug-related toxicity was noted. Navitoclax reduced several senescence and SASP biomarkers, with CSF concentrations sufficient for senolysis. Finally, navitoclax reduced TSPO-PET frontal cortex binding and showed trends of improvement in CSF biomarkers of neuroinflammation, neuronal damage, and synaptic dysfunction. Overall, navitoclax administration was safe and well tolerated in aged monkeys, inducing trends of biomarker changes relevant to human neurodegenerative disease.

Impact of diabetes on mortality and hospitalization after dementia diagnosis: Health insurance claims data analysis.

AIM: Japan faces a public health challenge of dementia, further complicated by the increasing complications from diabetes within its rapidly aging population. This study assesses the impact of diabetes on mortality and hospitalization among individuals aged ≥75 years with new dementia diagnoses. METHODS: We analyzed administrative claims data in Japan from 73 324 individuals aged ≥75 years with dementia, of whom 17% had comorbid diabetes. Dementia and diabetes were identified from the International Classification of Diseases, Tenth Revision codes. We used Kaplan-Meier survival analysis, Cox proportional hazards analysis, and population attributable fractions (PAFs) to evaluate the impact on mortality and hospitalization after dementia diagnosis. RESULTS: One-year mortality and 1-year hospitalization probabilities in individuals with dementia and diabetes (10.3% and 31.7%, respectively) were higher than those without diabetes (8.3% and 25.4%, respectively). The adjusted hazard ratios for individuals with diabetes, as compared to those without, were 1.126 (95% confidence interval [CI], 1.040-1.220) for mortality and 1.191 (95% CI, 1.140-1.245) for hospitalization. The PAFs from the comorbidity of dementia and diabetes were 2.2% for mortality and 3.1% for hospitalization. Subgroup analysis showed that the PAFs were highest in men aged 75-79 years and women aged 80-84 years for mortality and in individuals aged 75-79 for hospitalization. CONCLUSION: During the early postdiagnosis period, comorbid diabetes increases mortality and hospitalization risks in older adults with dementia. The variation in disease burden across age groups underscores the need for age-specific health care strategies to manage comorbid diabetes in individuals with dementia. Geriatr Gerontol Int 2024; 24: 773-781.

Association between milk consumption in middle age and frailty in later life: The Aichi Workers' cohort study.

AIM: Several studies have shown that dairy consumption in old age is effective in preventing frailty. However, there is a lack of evidence regarding the association between milk consumption during middle age and the development of frailty in old age. Therefore, we carried out an investigation to explore the association between milk consumption during middle age and development of frailty examined after over 15 years of follow up in a long-term cohort study in Japan. METHODS: We studied 265 participants aged 60-79 years (212 men and 53 women) in 2018, who participated in both the baseline survey in 2002 and the frailty assessment in 2018. The amount of milk consumption (g/day) at baseline was age- and energy-adjusted, and classified into three categories (no, low and high consumption: 0 g/day, ≤135.86 g/day, >135.86 g/day in men and 0 g/day, ≤126.44 g/day, >126.44 g/day in women). Odds ratios (OR) and 95% confidence intervals (CI) for prefrailty/frailty after adjusting for lifestyles at baseline, stratified by sex, were estimated using logistic regression analysis. RESULTS: The prevalence of prefrailty/frailty in 2018 was 37.7% and 28.3% in men and women, respectively. Milk consumption categories were inversely associated with the prevalence of prefrailty/frailty in men (OR 0.34, 95% CI 0.14-0.84 in low consumption; OR 0.31, 95% CI 0.10-0.95 in high consumption; P < 0.05), but not in women (OR 0.53, 95% CI 0.11-2.65; P = 0.44). CONCLUSIONS: In this study, milk intake in middle-aged men was inversely associated with the prevalence of prefrailty/frailty later in life. Geriatr Gerontol Int 2024; 24: 700-705.

External Validation of a Machine Learning Model for Schizophrenia Classification.

Background and Objective: Excellent generalizability is the precondition for the widespread practical implementation of machine learning models. In our previous study, we developed the schizophrenia classification model (SZ classifier) to identify potential schizophrenia patients in the Japanese population. The SZ classifier has exhibited impressive performance during internal validation. However, ensuring the robustness and generalizability of the SZ classifier requires external validation across independent sample sets. In this study, we aimed to present an external validation of the SZ classifier using outpatient data. Methods: The SZ classifier was trained by using online survey data, which incorporate demographic, health-related, and social comorbidity features. External validation was conducted using an outpatient sample set which is independent from the sample set during the model development phase. The model performance was assessed based on the sensitivity and misclassification rates for schizophrenia, bipolar disorder, and major depression patients. Results: The SZ classifier demonstrated a sensitivity of 0.75 when applied to schizophrenia patients. The misclassification rates were 59% and 55% for bipolar disorder and major depression patients, respectively. Conclusions: The SZ classifier currently encounters challenges in accurately determining the presence or absence of schizophrenia at the individual level. Prior to widespread practical implementation, enhancements are necessary to bolster the accuracy and diminish the misclassification rates. Despite the current limitations of the model, such as poor specificity for certain psychiatric disorders, there is potential for improvement if including multiple types of psychiatric disorders during model development.

Diel variations of airborne microbes and antibiotic resistance genes in Response to urban PM2.5 chemical properties during the heating season.

Among the components of fine particulate matter (PM2.5), the contributions of airborne microorganisms and antibiotic resistance genes (ARGs) to health risks have been overlooked. Airborne microbial dynamics exhibit a unique diurnal cycle due to environmental influences. However, the specific roles of PM2.5 chemical properties resulting from fossil fuel combustion in driving circadian fluctuations in microbial populations and ARGs remain unclear. This study explored the interactions between toxic components and microbial communities during the heating period to understand the variations in ARGs. Bacterial and fungal communities showed a higher susceptibility to diel variations in PM2.5 compared to their chemical properties. Mantel tests revealed that chemical properties and microbial community interactions contribute differently to ARG variations, both directly and indirectly, during circadian fluctuations. Our findings highlight that, during the daytime, the enrichment of pathogenic microorganisms and ARGs increases the risk of PM2.5 toxicity. Conversely, during the nighttime, the utilization of water-soluble ions by the fungal community increased, leading to a significant increase in fungal biomass. Notably, Aspergillus exhibited a significant correlation with mobile genetic elements and ARGs, implying that this genus is a crucial driver of airborne ARGs. This study provides novel insights into the interplay between the chemical composition, microbial communities, and ARGs in PM, underscoring the urgent need for a comprehensive understanding of effective air pollution control strategies.

Metabolomic analysis of dietary-restriction-induced attenuation of sarcopenia in prematurely aging DNA repair-deficient mice.

BACKGROUND: Sarcopenia is characterized by loss of skeletal muscle mass and function, and is a major risk factor for disability and independence in the elderly. Effective medication is not available. Dietary restriction (DR) has been found to attenuate aging and aging-related diseases, including sarcopenia, but the mechanism of both DR and sarcopenia are incompletely understood. METHODS: In this study, mice body weight, fore and all limb grip strength, and motor learning and coordination performance were first analysed to evaluate the DR effects on muscle functioning. Liquid chromatography-mass spectrometry (LC-MS) was utilized for the metabolomics study of the DR effects on sarcopenia in progeroid DNA repair-deficient Ercc1∆/- and Xpg-/- mice, to identify potential biomarkers for attenuation of sarcopenia. RESULTS: Muscle mass was significantly (P < 0.05) decreased (13-20%) by DR; however, the muscle quality was improved with retained fore limbs and all limbs grip strength in Ercc1∆/- and Xpg-/- mice. The LC-MS results revealed that metabolites and pathways related to oxidative-stress, that is, GSSG/GSH (P < 0.01); inflammation, that is, 9-HODE, 11-HETE (P < 0.05), PGE2, PGD2, and TXB2 (P < 0.01); and muscle growth (PGF2α) (P < 0.01) and regeneration stimulation (PGE2) (P < 0.05) are significantly downregulated by DR. On the other hand, anti-inflammatory indicator and several related metabolites, that is, ß-hydroxybutyrate (P < 0.01), 14,15-DiHETE (P < 0.0001), 8,9-EET, 12,13-DiHODE, and PGF1 (P < 0.05); consumption of sources of energy (i.e., muscle and liver glycogen); and energy production pathways, that is, glycolysis (glucose, glucose-6-P, fructose-6-P) (P < 0.01), tricarboxylic acid cycle (succinyl-CoA, malate) (P < 0.001), and gluconeogenesis-related metabolite, alanine (P < 0.01), are significantly upregulated by DR. The notably (P < 0.01) down-modulated muscle growth (PGF2α) and regeneration (PGE2) stimulation metabolite and the increased consumption of glycogen in muscle and liver may be related to the significantly (P < 0.01) lower body weight and muscle mass by DR. The downregulated oxidative stress, pro-inflammatory mediators, and upregulated anti-inflammatory metabolites resulted in a lower energy expenditure, which contributed to enhanced muscle quality together with upregulated energy production pathways by DR. The improved muscle quality may explain why grip strength is maintained and motor coordination and learning performance are improved by DR in Ercc1∆/- and Xpg-/- mice. CONCLUSIONS: This study provides fundamental supporting information on biomarkers and pathways related to the attenuation of sarcopenia, which might facilitate its diagnosis, prevention, and clinical therapy.

Efficacy of Biportal Endoscopic Decompression for Lumbar Spinal Stenosis: A Meta-Analysis With Single-Arm Analysis and Comparative Analysis With Microscopic Decompression and Uniportal Endoscopic Decompression.

BACKGROUND AND OBJECTIVE: Biportal endoscopic decompression is a minimally invasive surgical technique for lumbar spinal stenosis (LSS). This meta-analysis aimed to evaluate the efficacy and safety of biportal endoscopic decompression through both a single-arm analysis and a comparative analysis. METHODS: A comprehensive literature search was conducted to identify eligible studies reporting the outcomes of biportal endoscopic decompression for LSS. Single-arm analysis and comparisons with microscopic and uniportal endoscopic decompression were performed. Evaluated outcomes included visual analog scale (VAS) scores for back pain and leg pain, Oswestry Disability Index (ODI) scores, operation time, estimated blood loss, duration of hospital stay, and adverse events. RESULTS: Single-arm analysis demonstrated significant improvements in VAS back pain, VAS leg pain, and ODI scores after biportal endoscopic decompression at postoperative 1-day to 36-month follow-up (all P < .001), compared with preoperative levels. The pooled mean single-level operation time was 71.44 min, and the pooled mean hospital stay was 3.63 days. The overall adverse event rate was 4.0%, with dural tear being the most common complication (3.0%). Compared with microscopic decompression, biportal endoscopic decompression showed significantly lower VAS back pain at 1-month ( P < .001) and 6-month ( P < .001) follow-up; lower VAS leg pain at 1-month ( P = .045) follow-up; lower ODI scores at 3-month ( P < .001), 12-month ( P = .017), and >12-month ( P = .007) follow-up; lower estimated blood loss ( P = .003); and shorter hospital stay ( P < .001). Adverse event rates did not differ between the techniques. No significant differences were observed between biportal endoscopic and uniportal endoscopic decompression groups for most efficacy and safety outcomes. CONCLUSION: Biportal endoscopic decompression emerges as a safe and effective alternative for LSS, presenting potential advantages over the microscopic technique and comparable efficacy with the uniportal endoscopic technique.

IL11-mediated stromal cell activation may not be the master regulator of pro-fibrotic signaling downstream of TGFß.

Fibrotic diseases, such as idiopathic pulmonary fibrosis (IPF) and systemic scleroderma (SSc), are commonly associated with high morbidity and mortality, thereby representing a significant unmet medical need. Interleukin 11 (IL11)-mediated cell activation has been identified as a central mechanism for promoting fibrosis downstream of TGFß. IL11 signaling has recently been reported to promote fibroblast-to-myofibroblast transition, thus leading to various pro-fibrotic phenotypic changes. We confirmed increased mRNA expression of IL11 and IL11Rα in fibrotic diseases by OMICs approaches and in situ hybridization. However, the vital role of IL11 as a driver for fibrosis was not recapitulated. While induction of IL11 secretion was observed downstream of TGFß signaling in human lung fibroblasts and epithelial cells, the cellular responses induced by IL11 was quantitatively and qualitatively inferior to that of TGFß at the transcriptional and translational levels. IL11 blocking antibodies inhibited IL11Rα-proximal STAT3 activation but failed to block TGFß-induced profibrotic signals. In summary, our results challenge the concept of IL11 blockade as a strategy for providing transformative treatment for fibrosis.

Exploring Extracellular Matrix Crosslinking as a Therapeutic Approach to Fibrosis.

The extracellular matrix (ECM) provides structural support for tissues and regulatory signals for resident cells. ECM requires a careful balance between protein accumulation and degradation for homeostasis. Disruption of this balance can lead to pathological processes such as fibrosis in organs across the body. Post-translational crosslinking modifications to ECM proteins such as collagens alter ECM structure and function. Dysregulation of crosslinking enzymes as well as changes in crosslinking composition are prevalent in fibrosis. Because of the crucial roles these ECM crosslinking pathways play in disease, the enzymes that govern crosslinking events are being explored as therapeutic targets for fibrosis. Here, we review in depth the molecular mechanisms underlying ECM crosslinking, how ECM crosslinking contributes to fibrosis, and the therapeutic strategies being explored to target ECM crosslinking in fibrosis to restore normal tissue structure and function.

Effects of hypoxic compound exercise to promote HIF-1α expression on cardiac pumping function, sleep activity behavior, and exercise capacity in Drosophila.

Alteration of HIF-1α expression levels under hypoxic conditions affects the sequence of its downstream target genes thereby producing different effects. In order to investigate whether the effect of hypoxic compound exercise (HE) on HIF-1α expression alters cardiac pumping function, myocardial structure, and exercise capacity, we developed a suitable model of hypoxic exercise using Drosophila, a model organism, and additionally investigated the effect of hypoxic compound exercise on nocturnal sleep and activity behavior. The results showed that hypoxic compound exercise at 6% oxygen concentration for five consecutive days, lasting 1 h per day, significantly improved the cardiac stress resistance of Drosophila. The hypoxic complex exercise promoted the whole-body HIF-1α expression in Drosophila, and improved the jumping ability, climbing ability, moving speed, and moving distance. The expression of HIF-1α in the heart was increased after hypoxic exercise, which made a closer arrangement of myofilaments, an increase in the diameter of cardiac tubules, and an increase in the pumping function of the heart. The hypoxic compound exercise improved the sleep quality of Drosophila by increasing its nocturnal sleep time, the number of deep sleeps, and decreasing its nocturnal awakenings and activities. Therefore, we conclude that hypoxic compound exercise promoted the expression of HIF-1α to enhance the exercise capacity and heart pumping function of Drosophila, and improved the quality of sleep.

High-Throughput Extracellular Matrix Proteomics of Human Lungs Enabled by Photocleavable Surfactant and diaPASEF.

The extracellular matrix (ECM) is a complex assembly of proteins that provide interstitial scaffolding and elastic recoil for human lungs. The pulmonary extracellular matrix is increasingly recognized as an independent bioactive entity, by creating biochemical and mechanical signals that influence disease pathogenesis, making it an attractive therapeutic target. However, the pulmonary ECM proteome ("matrisome") remains challenging to analyze by mass spectrometry due to its inherent biophysical properties and relatively low abundance. Here, we introduce a strategy designed for rapid and efficient characterization of the human pulmonary ECM using the photocleavable surfactant Azo. We coupled this approach with trapped ion mobility MS with diaPASEF to maximize the depth of matrisome coverage. Using this strategy, we identify nearly 400 unique matrisome proteins with excellent reproducibility that are known to be important in lung biology, including key core matrisome proteins.

Prevalence, severity, and risk factors of cancer-related fatigue among working cancer survivors: a systematic review and meta-analysis.

PURPOSE: The aim of this study is to evaluate the prevalence, severity, and risk factors of cancer-related fatigue among currently working cancer survivors. METHODS: We searched the PubMed, Embase, Scopus, CINAHL, Cochrane Library, and ICHUSHI databases. The risk of bias was evaluated independently using the Risk of Bias Assessment Tool for Non-randomized Studies (RoBANS). A meta-analysis was conducted to determine the prevalence, severity, and related factors associated with cancer-related fatigue among currently working cancer survivors. RESULTS: Our meta-analysis included 18 studies and revealed that 42.2% of currently working cancer survivors experience cancer-related fatigue. The fatigue severity in this group was significantly higher than that in workers without cancer (absolute standardized mean difference (SMD) = 0.67), but lower than that in cancer survivors who had previously worked and were not currently working (absolute SMD = 0.72). Distress was identified as a potential risk factor for cancer-related fatigue in working cancer survivors (partial correlation coefficient = 0.38). CONCLUSIONS: The high prevalence of cancer-related fatigue among employed cancer survivors underscores the need for targeted workplace interventions and fatigue management strategies. While the severity of fatigue is less than that seen in non-working survivors, the comparison with the general working population highlights a significant health disparity. The association between distress and fatigue suggests the necessity for a holistic approach to fatigue management that considers both physical and mental factors in working cancer survivors. IMPLICATIONS FOR CANCER SURVIVORS: Our findings highlight the critical need for healthcare professionals and employers to monitor fatigue levels among working cancer survivors and offer appropriate support.

Can feature structure improve model's precision? A novel prediction method using artificial image and image identification.

Objectives: This study aimed to develop an approach to enhance the model precision by artificial images. Materials and Methods: Given an epidemiological study designed to predict 1 response using f features with M samples, each feature was converted into a pixel with certain value. Permutated these pixels into F orders, resulting in F distinct artificial image sample sets. Based on the experience of image recognition techniques, appropriate training images results in higher precision model. In the preliminary experiment, a binary response was predicted by 76 features, the sample set included 223 patients and 1776 healthy controls. Results: We randomly selected 10 000 artificial sample sets to train the model. Models' performance (area under the receiver operating characteristic curve values) depicted a bell-shaped distribution. Conclusion: The model construction strategy developed in the research has potential to capture feature order related information and enhance model predictability.

Modulated synthesis of cesium phosphomolybdate encapsulated in hierarchical porous UiO-66 for catalysing alkene epoxidation.

The hybrid composite of cesium phosphomolybdate (CsPM) encapsulated in hierarchical porous UiO-66 (HP-UiO-66) was synthesized using a modulated solvothermal method. A variety of characterization results demonstrated that the pore size distribution of CsPM@HP-UiO-66 is broader than traditional microporous CsPM@UiO-66 and cesium phosphomolybdate clusters are uniformly distributed in the octahedral cages of HP-UiO-66. The catalytic properties of the hybrid composite were investigated in alkene epoxidation reaction with tert-butyl hydroperoxide (t-BuOOH) as an oxidant. CsPM@HP-UiO-66 showed much higher catalytic activity for the alkene epoxidation reaction in comparison with the reference catalysts and could be easily reused by centrifugation and recycled for at least ten runs without significant loss in catalytic activity. The superior catalytic activity and stability of the hybrid composite CsPM@HP-UiO-66 should be mainly attributed to the hierarchical pores in the support HP-UiO-66 promoting the diffusion of alkene molecules, the uniform distribution of highly active CsPM clusters in the octahedral cages of HP-UiO-66, the introduction of cesium cations to form the insoluble cesium phosphomolybdate and the strong metal-support interactions (SMSI) between the CsPM clusters and the HP-UiO-66 framework.

Classifying Schizophrenia Cases by Artificial Neural Network Using Japanese Web-Based Survey Data: Case-Control Study.

BACKGROUND: In Japan, challenges were reported in accurately estimating the prevalence of schizophrenia among the general population. Retrieving previous studies, we investigated that patients with schizophrenia were more likely to experience poor subjective well-being and various physical, psychiatric, and social comorbidities. These factors might have great potential for precisely classifying schizophrenia cases in order to estimate the prevalence. Machine learning has shown a positive impact on many fields, including epidemiology, due to its high-precision modeling capability. It has been applied in research on mental disorders. However, few studies have applied machine learning technology to the precise classification of schizophrenia cases by variables of demographic and health-related backgrounds, especially using large-scale web-based surveys. OBJECTIVE: The aim of the study is to construct an artificial neural network (ANN) model that can accurately classify schizophrenia cases from large-scale Japanese web-based survey data and to verify the generalizability of the model. METHODS: Data were obtained from a large Japanese internet research pooled panel (Rakuten Insight, Inc) in 2021. A total of 223 individuals, aged 20-75 years, having schizophrenia, and 1776 healthy controls were included. Answers to the questions in a web-based survey were formatted as 1 response variable (self-report diagnosed with schizophrenia) and multiple feature variables (demographic, health-related backgrounds, physical comorbidities, psychiatric comorbidities, and social comorbidities). An ANN was applied to construct a model for classifying schizophrenia cases. Logistic regression (LR) was used as a reference. The performances of the models and algorithms were then compared. RESULTS: The model trained by the ANN performed better than LR in terms of area under the receiver operating characteristic curve (0.86 vs 0.78), accuracy (0.93 vs 0.91), and specificity (0.96 vs 0.94), while the model trained by LR showed better sensitivity (0.63 vs 0.56). Comparing the performances of the ANN and LR, the ANN was better in terms of area under the receiver operating characteristic curve (bootstrapping: 0.847 vs 0.773 and cross-validation: 0.81 vs 0.72), while LR performed better in terms of accuracy (0.894 vs 0.856). Sleep medication use, age, household income, and employment type were the top 4 variables in terms of importance. CONCLUSIONS: This study constructed an ANN model to classify schizophrenia cases using web-based survey data. Our model showed a high internal validity. The findings are expected to provide evidence for estimating the prevalence of schizophrenia in the Japanese population and informing future epidemiological studies.

Association of psychological factors with advanced-level functional competency: Findings from the Aichi workers' cohort study, 2002-2019.

Objective: This study examined the longitudinal association of perceived stress, ikigai, and having someone one can count on in middle age with the advanced-level functional competency in older age, which is crucial for the maintenance of independent life among older adults. The issue is especially relevant in super-aged countries like contemporary Japan, where more and more older people live in a household consisting only of older people. Methods: Data were collected in 2019 from a total of 1692 retirees of the Aichi Workers' Cohort Study participants in which baseline survey including psychological factors was conducted during their employment in 2002. Japan Science and Technology Agency Index of Competence (JST-IC) was used to measure the advanced-level functional competency. Multivariable-adjusted odds ratios (ORs) were obtained for having low JST-IC in later life by the degrees of psychological factors reported in the middle age adjusting for the presence of depressive mood in 2019. Results: Those who were not sure about ikigai (OR: 2.02, 95 % CI: 1.33 to 3.08) and who have no one to count on (OR: 2.19, 95 % CI: 1.52 to 3.16) in the middle age were significantly associated with low JST-IC after retirement. Having much stress was significantly inversely associated with a low JST-IC (OR: 0.69, 95 % CI: 0.50 to 0.97). Conclusion: Having ikigai and someone reliable, and stress during middle age might play a role in preventing impaired advanced-level functional competency. Improved ikigai and increased social interaction and support might improve functional competency. Further research might explore avenues for improving ikigai.

Experiment and Computational Study on Pd-Catalyzed Methoxyiminoacyl-Directed γ-Alkoxylation of Alkylamides.

The direct alkoxylation of amides has been accomplished via methoxyiminoacyl (MIA)-mediated Pd-catalyzed C-H functionalization. A diverse array of alkylamide substrates is amenable to this protocol, providing γ-C(sp3)-alkoxylation of alkylamide derivatives with good to high efficiency. Two aspects of the research were completed to explore the reaction mechanism. On the one hand, the result of the kinetic isotopic effect experiment and control experiment indicated that reductive elimination is a rate-limiting step. On the other hand, density functional theory calculations demonstrated that a concerted Sn2 reductive elimination mechanism pathway is prior. Finally, the MIA group could be efficiently hydrogenated and protected in a one-pot procedure, which provides a short synthetic route to γ-methoxy amino acid derivatives.

Visible-light-promoted organic-dye-catalyzed sulfonylation/cyclization to access indolo[2,1-a]isoquinoline derivatives.

An efficient visible-light-promoted organic-dye-catalyzed radical cascade cyclization was developed for the rapid synthesis of sulfonyl-substituted indolo[2,1-a]isoquinolines and benzimidazo[2,1-a]isoquinolin-6(5H)-ones. Using the economical and environmentally benign Eosin B as the photocatalyst, a wide range of indolo[2,1-a]isoquinoline derivatives were obtained in moderate to good yields. Mechanistic studies indicate that a sulfonyl radical pathway is involved in this reaction. Compared with previous works, this protocol has the advantages of being metal- and base-free, using visible light as a traceless energy source, simple operation and mild reaction conditions, all of which make this methodology more attractive.

Boosting the catalysis of cesium phosphomolybdate encapsulated in hierarchical porous UiO-66 by microenvironment modulation for epoxidation of alkenes.

The chemical microenvironment of polyoxometalates (POMs) encapsulated in metal-organic frameworks (MOFs) presents a significant influence on their catalytic performance, which can be easily regulated by the linker functional group alteration or metal substitution in MOFs. Herein, a series of cesium phosphomolybdate (CsPM) encapsulated in hierarchical porous UiO-66-X composites (CsPM@HP-UiO-66-X, X = H, 2CH3, or 2OH, where X represents the alterable group grafted onto the linker benzene ring) were successfully synthesized through a one pot modulated solvothermal method. The catalytic performances of the obtained materials were explored in alkene epoxidation reaction with tert-butyl hydroperoxide (t-BuOOH). CsPM@HP-UiO-66-2CH3 showed relatively high catalytic activity, stability, and epoxidation selectivity in cyclooctene epoxidation among the CsPM@HP-UiO-66-X composites. Moreover, CsPM@HP-UiO-66-2CH3 was effective in the epoxidation of numerous alkenes, especially cyclic alkenes. The superior catalytic activity of CsPM@HP-UiO-66-2CH3 is mainly attributed to the modulation of the microenvironment surrounding CsPM active sites by introducing a hydrophobic methyl group. Meanwhile, the size-matched effect, the introduction of cesium cations, and the strong metal-support interactions (SMSIs) between CsPM and HP-UiO-66-2CH3 play a crucial role in the stability of CsPM@HP-UiO-66-2CH3.

Metal- and additive-free radical-triggered nitration/cyclization to construct indolo[2,1-α]isoquinoline and benzimidazo[2,1-a]isoquinolin-6(5H)-one derivatives using t-BuONO as nitro reagents.

An efficient metal- and additive-free nitro radical-triggered addition/cyclization of 2-aryl-N-acryloyl indoles/2-arylbenzimidazoles for the synthesis of nitro-substituted indolo[2,1-α]isoquinoline and benzimidazo[2,1-a]isoquinolin-6(5H)-one derivatives has been developed. The commercially available and low-cost t-BuONO was used as a nitro reagent. Due to mild reaction conditions, a variety of functional groups could be tolerated to give the corresponding products in moderate to good yields. Moreover, this nitration process could be scaled-up and the nitro group could be readily converted into the amino group, which may find applications in synthetic and medicinal chemistry.