LDHA contributes to nicotine induced cardiac fibrosis through autophagy flux impairment.

Cardiac fibrosis is a typical feature of cardiac pathological remodeling, which is associated with adverse clinical outcomes and has no effective therapy. Nicotine is an important risk factor for cardiac fibrosis, yet its underlying molecular mechanism remains poorly understood. This study aimed to identify its potential molecular mechanism in nicotine-induced cardiac fibrosis. Our results showed nicotine exposure led to the proliferation and transformation of cardiac fibroblasts (CFs) into myofibroblasts (MFs) by impairing autophagy flux. Through the use of drug affinity responsive target stability (DARTS) assay, cellular thermal shift assay (CETSA), and surface plasmon resonance (SPR) technology, it was discovered that nicotine directly increased the stability and protein levels of lactate dehydrogenase A (LDHA) by binding to it. Nicotine treatment impaired autophagy flux by regulating the AMPK/mTOR signaling pathway, impeding the nuclear translocation of transcription factor EB (TFEB), and reducing the activity of cathepsin B (CTSB). In vivo, nicotine treatment exacerbated cardiac fibrosis induced in spontaneously hypertensive rats (SHR) and worsened cardiac function. Interestingly, the absence of LDHA reversed these effects both in vitro and in vivo. Our study identified LDHA as a novel nicotine-binding protein that plays a crucial role in mediating cardiac fibrosis by blocking autophagy flux. The findings suggest that LDHA could potentially serve as a promising target for the treatment of cardiac fibrosis.

HBI-8000 improves heart failure with preserved ejection fraction via the TGF-ß1/MAPK signalling pathway.

Heart failure with preserved ejection fraction (HFpEF) accounts for approximately 50% of total heart failure patients and is characterized by peripheral circulation, cardiac remodelling and comorbidities (such as advanced age, obesity, hypertension and diabetes) with limited treatment options. Chidamide (HBI-8000) is a domestically produced benzamide-based histone deacetylase isoform-selective inhibitor used for the treatment of relapsed refractory peripheral T-cell lymphomas. Based on our in vivo studies, we propose that HBI-8000 exerts its therapeutic effects by inhibiting myocardial fibrosis and myocardial hypertrophy in HFpEF patients. At the cellular level, we found that HBI-8000 inhibits AngII-induced proliferation and activation of CFs and downregulates the expression of fibrosis-related factors. In addition, we observed that the HFpEF group and AngII stimulation significantly increased the expression of TGF-ß1 as well as phosphorylated p38MAPK, JNK and ERK, whereas the expression of the above factors was significantly reduced after HBI-8000 treatment. Activation of the TGF-ß1/MAPK pathway promotes the development of fibrotic remodelling, and pretreatment with SB203580 (p38MAPK inhibitor) reverses this pathological change. In conclusion, our data suggest that HBI-8000 inhibits fibrosis by modulating the TGF-ß1/MAPK pathway thereby improving HFpEF. Therefore, HBI-8000 may become a new hope for the treatment of HFpEF patients.

Josephin domain containing 2 (JOSD2) promotes lung cancer by inhibiting LKB1 (Liver kinase B1) activity.

Non-small cell lung cancer (NSCLC) ranks as one of the leading causes of cancer-related deaths worldwide. Despite the prominence and effectiveness of kinase-target therapies in NSCLC treatment, these drugs are suitable for and beneficial to a mere ~30% of NSCLC patients. Consequently, the need for novel strategies addressing NSCLC remains pressing. Deubiquitinases (DUBs), a group of diverse enzymes with well-defined catalytic sites that are frequently overactivated in cancers and associated with tumorigenesis and regarded as promising therapeutic targets. Nevertheless, the mechanisms by which DUBs promote NSCLC remain poorly understood. Through a global analysis of the 97 DUBs' contribution to NSCLC survival possibilities using The Cancer Genome Atlas (TCGA) database, we found that high expression of Josephin Domain-containing protein 2 (JOSD2) predicted the poor prognosis of patients. Depletion of JOSD2 significantly impeded NSCLC growth in both cell/patient-derived xenografts in vivo. Mechanically, we found that JOSD2 restricts the kinase activity of LKB1, an important tumor suppressor generally inactivated in NSCLC, by removing K6-linked polyubiquitination, an action vital for maintaining the integrity of the LKB1-STRAD-MO25 complex. Notably, we identified the first small-molecule inhibitor of JOSD2, and observed that its pharmacological inhibition significantly arrested NSCLC proliferation in vitro/in vivo. Our findings highlight the vital role of JOSD2 in hindering LKB1 activity, underscoring the therapeutic potential of targeting JOSD2 in NSCLC, especially in those with inactivated LKB1, and presenting its inhibitors as a promising strategy for NSCLC treatment.

Patterns of psychotropic drug prescriptions and general practice consultations among community-dwelling older people with dementia during the first two years of the COVID-19 pandemic.

BACKGROUND: The COVID-19 pandemic and subsequent lockdown measures had serious implications for community-dwelling older people with dementia. While the short-term impacts of the pandemic on this population have been well studied, there is limited research on its long-term impacts. Quantifying the long-term impacts may provide insights into whether healthcare adaptations are needed after the acute phase of the pandemic to balance infection prevention measures with healthcare provision. This study aims to examine patterns of psychotropic drug prescriptions and general practice consultations in community-dwelling older people with dementia during the first two years of the pandemic. METHODS: We utilised routine electronic health records from three Dutch academic general practice research networks located in the North, East, and South, between 2019 and 2021. We (1) compared the weekly prescription rates of five groups of psychotropic drugs and two groups of tracer drugs, and weekly general practice consultation rates per 1000 participants, between the first two years of the pandemic and the pre-pandemic phase, (2) calculated changes in these rates during three lockdowns and two relaxation phases relative to the corresponding weeks in 2019, and (3) employed interrupted time series analyses for the prescription rates. Analyses were performed for each region separately. RESULTS: The study population sizes in the North, East, and South between 2019 and 2021 were 1726 to 1916, 93 to 117, and 904 to 960, respectively. Data from the East was excluded from the statistical analyses due to the limited sample size. During the first two years of the pandemic, the prescription rates of psychotropic drugs were either lower or similar to those in the pre-pandemic phase, with differences varying from -2.6‰ to -10.2‰. In contrast, consultation rates during the pandemic were higher than in the pre-pandemic phase, increasing by around 38‰. CONCLUSIONS: This study demonstrates a decrease in psychotropic drug prescriptions, but an increase in general practice consultations among community-dwelling older people with dementia during the first two years of the pandemic. However, reasons for the decrease in psychotropic drug prescriptions are unclear due to limited information on the presence of neuropsychiatric symptoms and the appropriateness of prescribing.

Error simulation of atmospheric scattered radiance and its influence on slant visibility based on the SBDART model and Monte Carlo method.

Atmospheric scattered radiance is an important factor affecting slant visibility measurement in the daytime. This paper explores atmospheric scattered radiance errors and their influence on slant visibility measurements. Considering the difficulty in error synthesis of the radiative transfer equation, an error simulation scheme based on the Monte Carlo method is proposed. An error simulation and error analysis for atmospheric scattered radiance was carried out based on the Santa Barbara DISTORT atmospheric radiative transfer (SBDART) model and the Monte Carlo method. The error in aerosol parameters including the single-scattering albedo (SSA), the asymmetry factor, and the aerosol optical depth (AOD), was simulated by a random number and random error under different normal distributions, and the error influence of aerosol parameters on the error in the solar irradiance and 33-layer atmosphere scattered radiance is discussed in detail. The maximum relative deviations of the output scattered radiance at a certain slant direction are 5.98%, 1.47%, and 2.35%, when SSA, the asymmetry factor, and the AOD obey the normal distribution of (0, 5). The error sensitivity analysis also confirms that the SSA is the most sensitive factor affecting atmospheric scattered radiance and the total solar irradiance. Then, according to the error synthesis theory, we investigated the error transfer effect of three error sources related to the atmosphere based on the contrast ratio between the object and the background. The simulation results show that the error in the contrast ratio caused by solar irradiance and scattered radiance is lower than 6.2% and 2.84%, indicating the main role in contributing to the error transfer of slant visibility. Further, the comprehensive process of the error transfer in slant visibility measurements was demonstrated by a set of lidar experiments and the SBDART model. The results provide a reliable theoretical basis for the measurement of atmospheric scattered radiance and slant visibility, which is of great significance to improve the measurement accuracy of slant visibility.

The longitudinal patterns of psychotropic drug prescriptions for subpopulations of community-dwelling older people with dementia: electronic health records based retrospective study.

BACKGROUND: Studies focusing on patterns of psychotropic drug prescriptions (PDPs) for subpopulations of community-dwelling older people with dementia are lacking. OBJECTIVE: The aim of this study was to identify the longitudinal patterns of PDPs in subpopulations. METHODS: This retrospective study used electronic health records from general practitioners (GPs) in the Netherlands. People (N = 1278) firstly diagnosed with dementia between 2013 and 2015, aged 65 years or older, were selected and categorized into four subpopulations: community-dwelling (CD) group throughout follow-up, ultimately admitted to nursing homes (NH) group, ultimately died (DIE) group, and ultimately deregistered for unclear reasons (DeR) group. Generalised estimating equations were used to estimate the patterns of psychotropic drug prescriptions, after the diagnosis of dementia for a five-year follow-up, and 0-3 months before institutionalisation or death. RESULTS: Over the five-year follow-up, antipsychotic prescriptions increased steadily in CD (OR = 1.07 [1.04-1.10]), NH (OR = 1.10 [1.04-1.15]), and DIE (OR = 1.05 [1.02-1.08]) groups. Similarly, prescriptions of antidepressants also showed upward trends in CD (OR = 1.04 [1.02-1.06]), NH (OR = 1.10 [1.02-1.18]), and DIE (OR = 1.04 [1.00-1.08]) groups. The other psychotropic drugs did not show clear changes over time in most of the subpopulations. In the three months before institutionalisation, antipsychotic prescriptions increased (OR = 2.12 [1.26-3.57]) in the NH group compared to prior periods. Likewise, before death, prescriptions of antipsychotics (OR = 1.74 [1.28-2.38]) and hypnotics and sedatives (OR = 2.11 [1.54-2.90]) increased in the DIE group, while anti-dementia drug prescriptions decreased (OR = 0.42 [0.26-0.69]). CONCLUSIONS: After community-dwelling older people are diagnosed with dementia, all subpopulations' prescriptions of antipsychotics and antidepressants increase continuously during the follow-up. While we cannot judge whether these prescriptions are appropriate, GPs might consider a more reluctant use of psychotropic drugs and use alternative psychosocial interventions. Additionally, antipsychotic prescriptions rise considerably shortly before institutionalisation or death, which might reflect that older people experience more neuropsychiatric symptoms during this period.

SDHA/B reduction promotes hepatocellular carcinoma by facilitating the deNEDDylation of cullin1 and stabilizing YAP/TAZ.

BACKGROUND AND AIMS: Succinate dehydrogenase enzyme (SDH) is frequently diminished in samples from patients with hepatocellular carcinoma (HCC), and SDH reduction is associated with elevated succinate level and poor prognosis in patients with HCC. However, the underlying mechanisms of how impaired SDH activity promotes HCC remain unclear. APPROACH AND RESULTS: In this study, we observed remarkable downregulations of SDH subunits A and B (SDHA/B) in chronic liver injury-induced murine HCC models and patient samples. Subsequent RNA sequencing, hematoxylin and eosin staining, and immunohistochemistry analyses of HCC samples revealed that Yes-associated protein (YAP) and transcriptional coactivator with PDZ-binding motif (TAZ) were significantly upregulated in HCC, with their levels inversely correlating with that of SDHA/B. YAP/TAZ stability was greatly enhanced in SDHA/B-depleted HCC cells along with accumulation of succinate. Further mechanistic analyses demonstrated that impaired activity of SDHA/B resulted in succinate accumulation, which facilitated the deNEDDylation of cullin1 and therefore disrupted the E3 ubiquitin ligase SCF ß-TrCP complex, consequently leading to YAP/TAZ stabilization and activation in HCC cells. The accelerated in vitro cell proliferation and in vivo tumor growth caused by SDHA/B reduction or succinate exposure were largely dependent on the aberrant activation of YAP/TAZ. CONCLUSIONS: Our study demonstrated that SDHA/B reduction promotes HCC proliferation by preventing the proteasomal degradation of YAP/TAZ through modulating cullin1 NEDDylation, thus binding SDH-deficient HCC cells to YAP/TAZ pathway and rendering these cells vulnerable to YAP/TAZ inhibition. Our findings warrant further investigation on the therapeutic effects of targeting YAP/TAZ in patients with HCC displaying reduced SDHA/B or elevated succinate levels.

Atmospheric visibility prediction by using the DBN deep learning model and principal component analysis.

Measuring and predicting atmospheric visibility is important scientific research that has practical significance for urban air pollution control and public transport safety. We propose a deep learning model that uses principal component analysis and a deep belief network (DBN) to effectively predict atmospheric visibility in short- and long-term sequences. First, using a visibility meter, particle spectrometer, and ground meteorological station data from 2016 to 2019, the principal component analysis method was adopted to determine the influence of atmospheric meteorological and environmental parameters on atmospheric visibility, and an input dataset applicable to atmospheric visibility prediction was constructed. On the basis of deep belief network theory, network structure parameters, including data preprocessing, the number of hidden layers, the number of nodes, and activation and weight functions, are simulated and analyzed. A deep belief network model suitable for atmospheric visibility prediction is established, where a double hidden layer is adopted with the node numbers 70 and 50, and the Z-score method is used for normalization processing with the tanh activation function and Adam optimizer. The average accuracy of atmospheric visibility prediction by the deep belief network reached 0.84, and the coefficient of determination reached 0.96; these results are significantly superior to those of the back propagation (BP) neural network and convolutional neural network (CNN), thus verifying the feasibility and effectiveness of the established deep belief network for predicting atmospheric visibility. Finally, a deep belief network model based on time series is used to predict the short- and long-term trends of atmospheric visibility. The results show that the model has good visibility prediction results within 3 days and has an accuracy rate of 0.79. Covering the visibility change evaluations of different weather conditions, the model demonstrates good practicability. The established deep learning network model provides an effective and feasible technical solution for the prediction of atmospheric meteorology and environmental parameters, which enjoys a wide range of application prospects in highway transportation, navigation, sea and air, meteorology, and environmental research.

Time trends in psychotropic drug prescriptions in Dutch nursing home residents with dementia between 2003 and 2018.

OBJECTIVE: Several European studies investigated the trends in psychotropic drug prescriptions (PDPs) among nursing home (NH) residents and reported a decline in antipsychotics prescriptions. Since the Dutch long-term care system differs from other European systems (e.g. higher threshold for NH admission and trained elderly care physicians), this study explores the trends in PDPs in Dutch NH residents with dementia. METHODS: The study used data from nine studies, comprising two cross-sectional studies, one cohort study, and six cluster-randomized controlled trials, collected in Dutch NHs between 2003 and 2018. With multilevel logistic regression analysis, NHs as a random effect, we estimated the trends in PDPs overall and for five specific psychotropic drug groups (antipsychotics, antidepressants, anxiolytics, hypnotics, and anti-dementia drugs), adjusting for confounders: age, gender, severity of dementia, severity of neuropsychiatric symptoms, and length of stay in NHs. RESULTS: The absolute prescription rate of antipsychotics was 37.5% in 2003 and decreased (OR = 0.947, 95% CI [0.926, 0.970]) every year. The absolute prescription rate of anti-dementia drugs was 0.8% in 2003 and increased (OR = 1.162, 95% CI [1.105, 1.223]) per year. The absolute rate of overall PDPs declined from 62.7% in 2003 to 40.4% in 2018. CONCLUSIONS: Among Dutch NH residents with dementia, the odds of antipsychotics prescriptions decreased by 5.3% per year while the odds of anti-dementia drug prescriptions increased by 16.2%. There were no distinct trends in antidepressants, anxiolytics, and hypnotics prescriptions. However, overall PDPs were still high. The PDPs in NH residents remain an issue of concern.

cGAS and cancer therapy: a double-edged sword.

Cyclic guanosine monophosphate-adenosine monophosphate adenosine synthetase (cGAS) is a DNA sensor that detects and binds to cytosolic DNA to generate cyclic GMP-AMP (cGAMP). As a second messenger, cGAMP mainly activates the adapter protein STING, which induces the production of type I interferons (IFNs) and inflammatory cytokines. Mounting evidence shows that cGAS is extensively involved in the innate immune response, senescence, and tumor immunity, thereby exhibiting a tumor-suppressive function, most of which is mediated by the STING pathway. In contrast, cGAS can also act as an oncogenic factor, mostly by increasing genomic instability through inhibitory effects on DNA repair, suggesting its utility as an antitumor target. This article reviews the roles and the underlying mechanisms of cGAS in cancer, particularly focusing on its dual roles in carcinogenesis and tumor progression, which are probably attributable to its classical and nonclassical functions, as well as approaches targeting cGAS for cancer therapy.

AKR1C1 connects autophagy and oxidative stress by interacting with SQSTM1 in a catalytic-independent manner.

Targeting autophagy might be a promising anticancer strategy; however, the dual roles of autophagy in cancer development and malignancy remain unclear. NSCLC (non-small cell lung cancer) cells harbour high levels of SQSTM1 (sequestosome 1), the autophagy receptor that is critical for the dual roles of autophagy. Therefore, mechanistic insights into SQSTM1 modulation may point towards better approaches to treat NSCLC. Herein, we used multiple autophagy flux models and autophagy readouts to show that aldo-keto reductase family 1 member C1 (AKR1C1), which is highly expressed in NSCLC, promotes autophagy by directly binding to SQSTM1 in a catalytic-independent manner. This interaction may be strengthened by reactive oxygen species (ROS), important autophagy inducers. Further mechanistic research demonstrated that AKR1C1 interacts with SQSTM1 to augment SQSTM1 oligomerization, contributing to the SQSTM1 affinity for binding cargo. Collectively, our data reveal a catalytic-independent role of AKR1C1 for interacting with SQSTM1 and promoting autophagy. All these findings not only reveal a novel functional role of AKR1C1 in the autophagy process but also indicate that modulation of the AKR1C1-SQSTM1 interaction may be a new strategy for targeting autophagy.

Fingolimod exerts in vitro anticancer activity against hepatocellular carcinoma cell lines via YAP/TAZ suppression.

Hepatocellular carcinoma (HCC) remains a notably global health challenge with high mortality rates and poor prognosis. The deregulation of the Hippo signalling pathway, especially the overexpression and activation of downstream effector Yes-associated protein (YAP), has been demonstrated to result in the rapid malignant evolution of HCC. In this context, multiple efforts have been dedicated to targeting YAP for HCC therapy, but effective YAP inhibitors are still lacking. In this study, through a YAP-TEAD (8×GTIIC) luciferase reporter assay, we identified fingolimod, an immunomodulatory drug approved for the treatment of multiple sclerosis, as a novel YAP inhibitor. Fingolimod suppressed the proliferation of HCC cell lines by downregulating the protein levels as well as the trans-activating function of YAP. Overall, our current study not only identifies fingolimod as a novel YAP-targeting in hibitor, but also indicates that this clinically-approved drug could be utilized as a potential and feasible therapeutic drug for HCC.

The calcimimetic agent cinacalcet inhibits hepatocellular carcinoma via YAP/TAZ suppression.

The lack of effective strategies remains a pivotal challenge for hepatocellular carcinoma (HCC) treatment. YAP/ TAZ is a promising target for effective drugs against HCC. In this study, we profiled the regulatory effect of 98 drugs on transcriptional activity of YAP/TAZ and identified the calcimimetic agent cinacalcet as a potent YAP inhibitor. Cinacalcet inhibited YAP expression in HCC models at both transcriptional and protein levels, and ultimately arrested cell proliferation of HCC. Overexpression of YAP weakened the anticancer efficacy of cinacalcet, indicating that YAP was responsible for the antineoplastic activity of cinacalcet. Collectively, this study suggested cinacalcet as a feasible anticancer drug for HCC via its inhibition on YAP/TAZ.

Design, synthesis and biological evaluation of quinazoline derivatives as potent and selective FGFR4 inhibitors.

Aberrant activation of the fibroblast growth factor 19-fibroblast growth factor receptor 4 (FGF19-FGFR4) signaling pathway has been proved to promote hepatocellular carcinoma (HCC) proliferation. It is assumed that the first FGFR4 inhibitor BLU9931 did not enter clinical studies, presumably due to its rapid metabolism in liver microsomes. Here, we report the development of series of quinazoline derivatives based on FGFR4 inhibitor BLU9931 through structural modification of its solvent region pocket to minimize its potential metabolic liability. Among them, compound 35a exhibited comparable or superior kinase inhibitory activity (IC50 = 8.5 nM) and selectivity in cells. More importantly, compound 35a improved liver microsomes stability compared to BLU9931. Cellular mechanistic studies demonstrated that 35a induced apoptosis via the FGFR4 signaling pathway blockage. In addition, the computational simulation revealed the possible binding mode to FGFR4 protein, which provides a plausible explanation of high potent and metabolic stability.

The role of cGAS-STING signalling in liver diseases.

The recently identified novel cytosolic DNA sensor cyclic GMP-AMP synthase (cGAS) activates the downstream adaptor protein stimulator of interferon genes (STING) by catalysing the synthesis of cyclic GMP-AMP. This in turn initiates an innate immune response through the release of various cytokines, including type I interferon. Foreign DNA (microbial infection) or endogenous DNA (nuclear or mitochondrial leakage) can serve as cGAS ligands and lead to the activation of cGAS-STING signalling. Therefore, the cGAS-STING pathway plays essential roles in infectious diseases, sterile inflammation, tumours, and autoimmune diseases. In addition, cGAS-STING signalling affects the progression of liver inflammation through other mechanisms, such as autophagy and metabolism. In this review, we summarise recent advances in our understanding of the role of cGAS-STING signalling in the innate immune modulation of different liver diseases. Furthermore, we discuss the therapeutic potential of targeting the cGAS-STING pathway in the treatment of liver diseases.

Deubiquitinase JOSD2 stabilizes YAP/TAZ to promote cholangiocarcinoma progression.

Cholangiocarcinoma (CCA) has emerged as an intractable cancer with scanty therapeutic regimens. The aberrant activation of Yes-associated protein (YAP) and transcriptional co-activator with PDZ-binding motif (TAZ) are reported to be common in CCA patients. However, the underpinning mechanism remains poorly understood. Deubiquitinase (DUB) is regarded as a main orchestrator in maintaining protein homeostasis. Here, we identified Josephin domain-containing protein 2 (JOSD2) as an essential DUB of YAP/TAZ that sustained the protein level through cleavage of polyubiquitin chains in a deubiquitinase activity-dependent manner. The depletion of JOSD2 promoted YAP/TAZ proteasomal degradation and significantly impeded CCA proliferation in vitro and in vivo. Further analysis has highlighted the positive correlation between JOSD2 and YAP abundance in CCA patient samples. Collectively, this study uncovers the regulatory effects of JOSD2 on YAP/TAZ protein stabilities and profiles its contribution in CCA malignant progression, which may provide a potential intervention target for YAP/TAZ-related CCA patients.

Targeting slug-mediated non-canonical activation of c-Met to overcome chemo-resistance in metastatic ovarian cancer cells.

Metastasis-associated drug resistance accounts for high mortality in ovarian cancer and remains to be a major barrier for effective treatment. In this study, SKOV3/T4, a metastatic subpopulation of ovarian cancer SKOV3 cells, was enriched to explore potential interventions against metastatic-associated drug resistance. Quantitative genomic and functional analyses were performed and found that slug was significantly increased in the SKOV3/T4 subpopulation and contributed to the high resistance of SKOV3/T4. Further studies showed that slug activated c-Met in a ligand-independent manner due to elevated levels of fibronectin and provoked integrin α V function, which was confirmed by the significant correlation of slug and p-Met levels in 121 ovarian cancer patient samples. Intriguingly, c-Met inhibitor(s) exhibited greatly enhanced anti-cancer effects in slug-positive ovarian cancer models both in vitro and in vivo. Additionally, IHC analyses revealed that slug levels were highly correlated with reduced survival of ovarian cancer patients. Taken together, this study not only uncovers the critical roles of slug in drug resistance in ovarian cancer but also highlights a promising therapeutic strategy by targeting the noncanonical activation of c-Met in slug-positive ovarian cancer patients with poor prognosis.