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Class IIa histone deacetylases (HDACs) have been linked to tumorigenesis in various cancers. Previously, we designed phenylhydroxamic acid LH4f as a potent class IIa HDAC inhibitor. However, it also unselectively inhibited class I and class IIb HDACs. To enhance the compound’s selectivity towards class IIa HDACs, the ortho-phenyl group from the selective HDAC7 inhibitor 1 is incorporated into ortho position of the phenylhydroxamic acid in LH4f. Compared to LH4f, most resulting compounds displayed substantially improved selectivity towards the class IIa HDACs. Notably, compound 7 g exhibited the strongest HDAC9 inhibition with an IC50 value of 40 nM. Molecular modelling further identified the key interactions of compound 7 g bound to HDAC9. Compound 7 g significantly inhibited several human cancer cells, induced apoptosis, modulated caspase-related proteins as well as p38, and caused DNA damage. These findings suggest the potential of class IIa HDAC inhibitors as lead compounds for the development of cancer therapeutics.

Dual-specificity tyrosine-regulated kinase 1 A (DYRK1A) is crucial in neurogenesis, synaptogenesis, and neuronal functions. Its dysregulation is linked to neurodegenerative disorders like Down syndrome and Alzheimer’s disease. Although the development of DYRK1A inhibitors has significantly advanced in recent years, the selectivity of these drugs remains a critical challenge, potentially impeding further progress. In this study, we utilised structure-based virtual screening (SBVS) from NCI library to discover novel DYRK1A inhibitors. The top-ranked compounds were then validated through enzymatic assays to assess their efficacy towards DYRK1A. Among them, NSC361563 emerged as a potent and selective DYRK1A inhibitor. It was shown to decrease tau phosphorylation at multiple sites, thereby enhancing tubulin stability. Moreover, NSC361563 diminished the formation of amyloid β and offered neuroprotective benefits against amyloid β-induced toxicity. Our research highlights the critical role of selective DYRK1A inhibitors in treating neurodegenerative diseases and presents a promising starting point for the development of targeted therapies.

Abstract Objective Our objective was to create a machine learning architecture capable of identifying obstructive sleep apnea (OSA) patterns in single-lead electrocardiography (ECG) signals, exhibiting exceptional performance when utilized in clinical data sets. Methods We conducted our research using a data set consisting of 1656 patients, representing a diverse demographic, from the sleep center of China Medical University Hospital. To detect apnea ECG segments and extract apnea features, we utilized the EfficientNet and some of its layers, respectively. Furthermore, we compared various training and data preprocessing techniques to enhance the model’s prediction, such as setting class and sample weights or employing overlapping and regular slicing. Finally, we tested our approach against other literature on the Apnea-ECG database. Results Our research found that the EfficientNet model achieved the best apnea segment detection using overlapping slicing and sample-weight settings, with an AUC of 0.917 and an accuracy of 0.855. For patient screening with AHI > 30, we combined the trained model with XGBoost, leading to an AUC of 0.975 and an accuracy of 0.928. Additional tests using PhysioNet data showed that our model is comparable in performance to existing models regarding its ability to screen OSA levels. Conclusions Our suggested architecture, coupled with training and preprocessing techniques, showed admirable performance with a diverse demographic dataset, bringing us closer to practical implementation in OSA diagnosis. Trial registration The data for this study were collected retrospectively from the China Medical University Hospital in Taiwan with approval from the institutional review board CMUH109-REC3-018.

Abstract This study aimed to evaluate the sensitivity of AI in screening acute leukemia and its capability to classify either physiological or pathological cells. Utilizing an acute leukemia orientation tube (ALOT), one of the protocols of Euroflow, flow cytometry efficiently identifies various forms of acute leukemia. However, the analysis of flow cytometry can be time-consuming work. This retrospective study included 241 patients who underwent flow cytometry examination using ALOT between 2017 and 2022. The collected flow cytometry data were used to train an artificial intelligence using deep learning. The trained AI demonstrated a 94.6% sensitivity in detecting acute myeloid leukemia (AML) patients and a 98.2% sensitivity for B-lymphoblastic leukemia (B-ALL) patients. The sensitivities of physiological cells were at least 80%, with variable performance for pathological cells. In conclusion, the AI, trained with ResNet-50 and EverFlow, shows promising results in identifying patients with AML and B-ALL, as well as classifying physiological cells.

Abstract Polygenic scores estimate genetic susceptibility to diseases. We systematically calculated polygenic scores across 457 phenotypes using genotyping array data from China Medical University Hospital. Logistic regression models assessed polygenic scores’ ability to predict disease traits. The polygenic score model with the highest accuracy, based on maximal area under the receiver operating characteristic curve (AUC), is provided on the GeneAnaBase website of the hospital. Our findings indicate 49 phenotypes with AUC greater than 0.6, predominantly linked to endocrine and metabolic diseases. Notably, hyperplasia of the prostate exhibited the highest disease prediction ability (P value = 1.01 × 10−19, AUC = 0.874), highlighting the potential of these polygenic scores in preventive medicine and diagnosis. This study offers a comprehensive evaluation of polygenic scores performance across diverse human traits, identifying promising applications for precision medicine and personalized healthcare, thereby inspiring further research and development in this field.

Abstract Automated coronary angiography assessment requires precise vessel segmentation, a task complicated by uneven contrast filling and background noise. Our research introduces an ensemble U-Net model, SE-RegUNet, designed to accurately segment coronary vessels using 100 labeled angiographies from angiographic images. SE-RegUNet incorporates RegNet encoders and squeeze-and-excitation blocks to enhance feature extraction. A dual-phase image preprocessing strategy further improves the model's performance, employing unsharp masking and contrast-limited adaptive histogram equalization. Following fivefold cross-validation and Ranger21 optimization, the SE-RegUNet 4GF model emerged as the most effective, evidenced by performance metrics such as a Dice score of 0.72 and an accuracy of 0.97. Its potential for real-world application is highlighted by its ability to process images at 41.6 frames per second. External validation on the DCA1 dataset demonstrated the model's consistent robustness, achieving a Dice score of 0.76 and an accuracy of 0.97. The SE-RegUNet 4GF model's precision in segmenting blood vessels in coronary angiographies showcases its remarkable efficiency and accuracy. However, further development and clinical testing are necessary before it can be routinely implemented in medical practice.

Abstract Large-artery atherosclerosis (LAA) is a leading cause of cerebrovascular disease. However, LAA diagnosis is costly and needs professional identification. Many metabolites have been identified as biomarkers of specific traits. However, there are inconsistent findings regarding suitable biomarkers for the prediction of LAA. In this study, we propose a new method integrates multiple machine learning algorithms and feature selection method to handle multidimensional data. Among the six machine learning models, logistic regression (LR) model exhibited the best prediction performance. The value of area under the receiver operating characteristic curve (AUC) was 0.92 when 62 features were incorporated in the external validation set for the LR model. In this model, LAA could be well predicted by clinical risk factors including body mass index, smoking, and medications for controlling diabetes, hypertension, and hyperlipidemia as well as metabolites involved in aminoacyl-tRNA biosynthesis and lipid metabolism. In addition, we found that 27 features were present among the five adopted models that could provide good results. If these 27 features were used in the LR model, an AUC value of 0.93 could be achieved. Our study has demonstrated the effectiveness of combining machine learning algorithms with recursive feature elimination and cross-validation methods for biomarker identification. Moreover, we have shown that using shared features can yield more reliable correlations than either model, which can be valuable for future identification of LAA.

Abstract Background Previous studies of do-not-resuscitate (DNR) or do-not-intubate (DNI) orders in stroke patients have primarily been conducted in North America or Europe. However, characteristics associated with DNR/DNI orders in stroke patients in Asia have not been reported. Methods Based on the Taiwan Stroke Registry, this nationwide cross-sectional study enrolled hospitalized stroke patients from 64 hospitals between 2006 and 2020. We identified characteristics associated with DNR/DNI orders using a two-level random effects model. Results Among the 114,825 patients, 5531 (4.82%) had DNR/DNI orders. Patients with acute ischemic stroke (AIS) had the highest likelihood of having DNR/DNI orders (adjusted odds ratio [aOR] 1.76, 95% confidence interval [CI] 1.61–1.93), followed by patients with intracerebral hemorrhage (ICH), and patients with subarachnoid hemorrhage (SAH) had the lowest likelihood (aOR 0.53, 95% CI 0.43–0.66). From 2006 to 2020, DNR/DNI orders increased in all three types of stroke. In patients with AIS, women were significantly more likely to have DNR/DNI orders (aOR 1.23, 95% CI 1.15–1.32), while patients who received intravenous alteplase had a lower likelihood (aOR 0.74, 95% CI 0.65–0.84). Patients with AIS who were cared for by religious hospitals (aOR 0.55, 95% CI 0.35–0.87) and patients with SAH who were cared for by medical centers (aOR 0.40, 95% CI 0.17–0.96) were significantly less likely to have DNR/DNI orders. Conclusions In Taiwan, DNR/DNI orders increased in stroke patients between 2006 and 2020. Hospital characteristics were found to play a significant role in the use of DNR/DNI orders.

Abstract 13‐Acetoxysarcocrassolide (13‐AC) is a marine cembranoid derived from the aquaculture soft coral of Lobophytum crassum. The cytotoxic effect of 13‐AC against leukemia cells was previously reported but its mechanism of action is still unexplored. In the current study, we showed that 13‐AC induced apoptosis of human acute lymphoblastic leukemia Molt4 cells, as evidenced by the cleavage of PARP and caspases, phosphatidylserine externalization, as well as the disruption of mitochondrial membrane potential. The use of N‐acetylcysteine (NAC), a reactive oxygen species (ROS) scavenger, attenuated the cytotoxic effect induced by 13‐AC. Molecular docking and thermal shift assay indicated that the cytotoxic mechanism of action of 13‐AC involved the inhibition of heat shock protein 90 (Hsp 90) activity by eliciting the level of Hsp 70 and topoisomerase IIα in Molt4 cells. 13‐AC also exhibited potent antitumor activity by reducing the tumor volume (48.3%) and weight (72.5%) in the in vivo Molt4 xenograft mice model. Our findings suggested that the marine cembranoid, 13‐AC, acted as a dual inhibitor of Hsp 90 and topoisomerase IIα, exerting more potent apoptotic activity via the enhancement of ROS generation.

Marine natural products offer immense potential for drug development, but the limited supply of marine organisms poses a significant challenge. Establishing aquaculture presents a sustainable solution for this challenge by facilitating the mass production of active ingredients while reducing our reliance on wild populations and harm to local environments. To fully utilize aquaculture as a source of biologically active products, a cell-free system was established to target molecular components with protein-modulating activity, including topoisomerase II, HDAC, and tubulin polymerization, using extracts from aquaculture corals. Subsequent in vitro studies were performed, including MTT assays, flow cytometry, confocal microscopy, and Western blotting, along with in vivo xenograft models, to verify the efficacy of the active extracts and further elucidate their cytotoxic mechanisms. Regulatory proteins were clarified using NGS and gene modification techniques. Molecular docking and SwissADME assays were performed to evaluate the drug-likeness and pharmacokinetic and medicinal chemistry-related properties of the small molecules. The extract from Lobophytum crassum (LCE) demonstrated potent broad-spectrum activity, exhibiting significant inhibition of tubulin polymerization, and showed low IC50 values against prostate cancer cells. Flow cytometry and Western blotting assays revealed that LCE induced apoptosis, as evidenced by the increased expression of apoptotic protein-cleaved caspase-3 and the populations of early and late apoptotic cells. In the xenograft tumor experiments, LCE significantly suppressed tumor growth and reduced the tumor volume (PC3: 43.9%; Du145: 49.2%) and weight (PC3: 48.8%; Du145: 7.8%). Additionally, LCE inhibited prostate cancer cell migration, and invasion upregulated the epithelial marker E-cadherin and suppressed EMT-related proteins. Furthermore, LCE effectively attenuated TGF-β-induced EMT in PC3 and Du145 cells. Bioactivity-guided fractionation and SwissADME validation confirmed that LCE’s main component, 13-acetoxysarcocrassolide (13-AC), holds greater potential for the development of anticancer drugs.

[This corrects the article DOI: 10.1371/journal.pone.0056704.].

Class II histone deacetylases (HDACs) are considered as potential targets to treat Alzheimer’s disease (AD). Previously, C-3 substituted phenothiazine-containing compounds with class II HDAC-inhibiting activities was found to promote neurite outgrowth. This study replaced phenothiazine moiety with phenoxazine that contains many C-3 and C-4 substituents. Some resulting compounds bearing the C-4 substituent on a phenoxazine ring displayed potent class II HDAC inhibitory activities. Structure-activity relationship (SAR) of these compounds that inhibited HDAC isoenzymes was disclosed. Molecular modelling analysis demonstrates that the potent activities of C-4 substituted compounds probably arise from π-π stacked interactions between these compounds and class IIa HDAC enzymes. One of these, compound 7d exhibited the most potent class II HDAC inhibition (IC50= 3–870 nM). Notably, it protected neuron cells from H2O2-induced neuron damage at sub-μM concentrations, but with no significant cytotoxicity. These findings show that compound 7d is a lead compound for further development of anti-neurodegenerative agents.

Inhibiting a specific target in cancer cells and reducing unwanted side effects has become a promising strategy in pancreatic cancer treatment. MAP4K4 is associated with pancreatic cancer development and correlates with poor clinical outcomes. By phosphorylating MKK4, proteins associated with cell apoptosis and survival are translated. Therefore, inhibiting MAP4K4 activity in pancreatic tumours is a new therapeutic strategy. Herein, we performed a structure-based virtual screening to identify MAP4K4 inhibitors and discovered the compound F389-0746 with a potent inhibition (IC50 120.7 nM). The results of kinase profiling revealed that F389-0746 was highly selective to MAP4K4 and less likely to cause side effects. Results of in vitro experiments showed that F389-0746 significantly suppressed cancer cell growth and viability. Results of in vivo experiments showed that F389-0746 displayed comparable tumour growth inhibition with the group treated with gemcitabine. These findings suggest that F389-0746 has promising potential to be further developed as a novel pancreatic cancer treatment.

BackgroundSince OpenAI released ChatGPT, with its strong capability in handling natural tasks and its user-friendly interface, it has garnered significant attention. ObjectiveA prospective analysis is required to evaluate the accuracy and appropriateness of medication consultation responses generated by ChatGPT. MethodsA prospective cross-sectional study was conducted by the pharmacy department of a medical center in Taiwan. The test data set comprised retrospective medication consultation questions collected from February 1, 2023, to February 28, 2023, along with common questions about drug-herb interactions. Two distinct sets of questions were tested: real-world medication consultation questions and common questions about interactions between traditional Chinese and Western medicines. We used the conventional double-review mechanism. The appropriateness of each response from ChatGPT was assessed by 2 experienced pharmacists. In the event of a discrepancy between the assessments, a third pharmacist stepped in to make the final decision. ResultsOf 293 real-world medication consultation questions, a random selection of 80 was used to evaluate ChatGPT’s performance. ChatGPT exhibited a higher appropriateness rate in responding to public medication consultation questions compared to those asked by health care providers in a hospital setting (31/51, 61% vs 20/51, 39%; P=.01). ConclusionsThe findings from this study suggest that ChatGPT could potentially be used for answering basic medication consultation questions. Our analysis of the erroneous information allowed us to identify potential medical risks associated with certain questions; this problem deserves our close attention.

Bruton tyrosine kinase (BTK) is linked to multiple signalling pathways that regulate cellular survival, activation, and proliferation. A covalent BTK inhibitor has shown favourable outcomes for treating B cell malignant leukaemia. However, covalent inhibitors require a high reactive warhead that may contribute to unexpected toxicity, poor selectivity, or reduced effectiveness in solid tumours. Herein, we report the identification of a novel noncovalent BTK inhibitor. The binding interactions (i.e. interactions from known BTK inhibitors) for the BTK binding site were identified and incorporated into a structure-based virtual screening (SBVS). Top-rank compounds were selected and testing revealed a BTK inhibitor with >50% inhibition at 10 µM concentration. Examining analogues revealed further BTK inhibitors. When tested across solid tumour cell lines, one inhibitor showed favourable inhibitory activity, suggesting its potential for targeting BTK malignant tumours. This inhibitor could serve as a basis for developing an effective BTK inhibitor targeting solid cancers.

Abstract Targeting the programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) axis with monoclonal antibodies (mAbs) represents a crucial breakthrough in anticancer therapy, but mAbs are limited by their poor oral bioavailability, adverse events in multiple organ systems, and primary, adaptive, and acquired resistance, amongst other issues. More recently, the advent of small molecule inhibitors that target the PD-1/PD-L1 axis have shown promising cellular inhibitory activity and the potential to counteract the disadvantages of mAbs. In this study, structure-based virtual screening identified small molecule inhibitors that effectively inhibited the PD-1/PD-L1 interaction. Six of those small molecule inhibitors were applied to cell-based experiments targeting PD-1: CH-1, CH-2, CH-3, CH-4, CH-5, and CH-6. Of all 6, CH-4 displayed the lowest cytotoxicity and strongest inhibitory activity towards the PD-1/PD-L1 interaction. The experiments revealed that CH-4 inhibited the interaction of soluble form PD-L1 (sPD-L1) with PD-1 surface protein expressed by KG-1 cells. Investigations into CH-4 analogs revealed that CH-4.7 effectively blocked the PD-1/sPD-L1 interaction, but sustained the secretion of interleukin-2 and interferon-γ by Jurkat cells. Our experiments revealed a novel small molecule inhibitor that blocks the interaction of PD-1/sPD-L1 and potentially offers an alternative PD-1 target for immune checkpoint therapy.

Objective This study evaluated short-term (1-month) and long-term (1-year) mortality risks associated with the glomerular filtration rate (eGFR) on admission for patients with intracerebral hemorrhage. Methods From the Taiwan Stroke Registry data from April 2006 to December 2016, we identified and stratified patients with intracerebral hemorrhage into five subgroups by the eGFR level on admission: ≥90, 60–89, 30–59, 15–29, and Results Both the 1-month and 1-year mortality rates progressively increased with the decrease in eGFR levels. The 1-month mortality rate in patients with eGFR < 15 mL/min/1.73 m2 or on dialysis was approximately 5.5-fold greater than that in patients with eGFR ≥ 90 mL/min/1.73 m2 (8.31 versus 1.50 per 1000 person-days), with an adjusted hazard ratio (HR) of 4.59 [95% confidence interval (CI) = 2.71–7.78]. Similarly, the 1-year mortality in patients with eGFR < 15 mL/min/1.73 m2 or on dialysis was 7.5 times that in patients with eGFR ≥ 90 mL/min/1.73 m2 (2.34 versus 0.31 per 1000 person-days), with an adjusted HR of 4.54 (95% CI 2.95–6.98). Conclusion Impairment of renal function is an independent risk factor for mortality in patients with intracerebral hemorrhage in a gradual way. The eGFR level is a prognostic indicator for patients with intracerebral hemorrhage.

BackgroundTaiwan has insufficient nursing resources due to the high turnover rate of health care providers. Therefore, reducing the heavy workload of these employees is essential. Herein, speech transcription, which has various potential clinical applications, was employed for the documentation of nursing records. The requirement of including only one speaker per transcription facilitated data collection and system development. Moreover, authorization from patients was unnecessary. ObjectiveThe aim of this study was to construct a speech recognition system for nursing records such that health care providers can complete nursing records without typing or with only a few edits. MethodsNursing records in Taiwan are mainly written in Mandarin, with technical terms and abbreviations presented in both Mandarin and English. Therefore, the training set consisted of English code-switching information. Next, transfer learning (TL) and meta-TL (MTL) methods, which perform favorably in code-switching scenarios, were applied. ResultsAs of September 2021, the China Medical University Hospital Artificial Intelligence Speech (CMaiSpeech) data set was established by manually annotating approximately 100 hours of recordings from 525 speakers. The word error rate (WER) of the benchmark model of syllable-based TL was 29.54% in code-switching. The WER of the proposed model of syllable-based MTL was 22.20% in code-switching. The test set comprised 17,247 words. Moreover, in a clinical case, the proposed model of syllable-based MTL yielded a WER of 31.06% in code-switching. The clinical test set contained 1159 words. ConclusionsThis paper has two main contributions. First, the CMaiSpeech data set—a Mandarin-English corpus—has been established. Health care providers in Taiwan are often compelled to use a mixture of Mandarin and English in nursing records. Second, an automatic speech recognition system for nursing record document conversion was proposed. The proposed system can shorten the work handover time and further reduce the workload of health care providers.

ObjectiveTo implement an all-day online artificial intelligence (AI)-assisted detection of ST-elevation myocardial infarction (STEMI) by prehospital 12-lead electrocardiograms (ECGs) to facilitate patient triage for timely reperfusion therapy.MethodsThe proposed AI model combines a convolutional neural network and long short-term memory (CNN-LSTM) to predict STEMI on prehospital 12-lead ECGs obtained from mini-12-lead ECG devices equipped in ambulance vehicles in Central Taiwan. Emergency medical technicians (EMTs) from the 14 AI-implemented fire stations performed the on-site 12-lead ECG examinations using the mini portable device. The 12-lead ECG signals were transmitted to the AI center of China Medical University Hospital to classify the recordings as “STEMI” or “Not STEMI”. In 11 non-AI fire stations, the ECG data were transmitted to a secure network and read by available on-line emergency physicians. The response time was defined as the time interval between the ECG transmission and ECG interpretation feedback.ResultsBetween July 17, 2021, and March 26, 2022, the AI model classified 362 prehospital 12-lead ECGs obtained from 275 consecutive patients who had called the 119 dispatch centers of fire stations in Central Taiwan for symptoms of chest pain or shortness of breath. The AI's response time to the EMTs in ambulance vehicles was 37.2 ± 11.3 s, which was shorter than the online physicians' response time from 11 other fire stations with no AI implementation (113.2 ± 369.4 s, P < 0.001) after analyzing another set of 335 prehospital 12-lead ECGs. The evaluation metrics including accuracy, precision, specificity, recall, area under the receiver operating characteristic curve, and F1 score to assess the overall AI performance in the remote detection of STEMI were 0.992, 0.889, 0.994, 0.941, 0.997, and 0.914, respectively. During the study period, the AI model promptly identified 10 STEMI patients who underwent primary percutaneous coronary intervention (PPCI) with a median contact-to-door time of 18.5 (IQR: 16–20.8) minutes.ConclusionImplementation of an all-day real-time AI-assisted remote detection of STEMI on prehospital 12-lead ECGs in the field is feasible with a high diagnostic accuracy rate. This approach may help minimize preventable delays in contact-to-treatment times for STEMI patients who require PPCI.

BackgroundThe clinical dementia rating (CDR) scale is commonly used to diagnose dementia due to Alzheimer’s disease (AD). The sum of boxes of the CDR (CDR-SB) has recently been emphasized and applied to interventional trials for tracing the progression of cognitive impairment (CI) in the early stages of AD. We aimed to study the influence of baseline CDR-SB on disease progression to dementia or reversion to normal cognition (NC).Materials and methodsThe baseline CDR < 1 cohort registered from September 2015 to August 2020 with longitudinal follow-up in the History-based Artificial Intelligence Clinical Dementia Diagnostic System (HAICDDS) database was retrospectively analyzed for the rates of conversion to CDR ≥ 1. A Cox regression model was applied to study the influence of CDR-SB levels on progression, adjusting for age, education, sex, neuropsychological tests, neuropsychiatric symptoms, parkinsonism, and multiple vascular risk factors.ResultsA total of 1,827 participants were analyzed, including 1,258 (68.9%) non-converters, and 569 (31.1%) converters with mean follow-up of 2.1 (range 0.4–5.5) and 1.8 (range 0.3–5.0) years, respectively. Conversion rates increased with increasing CDR-SB scores. Compared to a CDR-SB score of 0, the hazard ratios (HR) for conversion to dementia were 1.51, 1.91, 2.58, 2.13, 3.46, 3.85, 3.19, 5.12, and 5.22 for CDR-SB scores of 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, and ≥4.5, respectively (all p < 0.05 except for CDR-SB score = 0.5). In addition, older age, lower education, lower cognitive performance, and a history of diabetes also increased conversion rates. Furthermore, reversions to NC were 12.5, 5.6, 0.9, and 0% for CDR-SB scores of 0.5, 1.0–2.0, 2.5–3.5 and ≥4.0, respectively (p < 0.001).ConclusionCDR-SB in predementia or very mild dementia (VMD) stages highly predicts progression to dementia or reversion to NC. Therefore, CDR-SB could be a good candidate for tracing the effectiveness of pharmacological and non-pharmacological interventions in populations without dementia.

Abstract Acute leukemia is a highly heterogeneous disease; therefore, combination therapy is commonly used for patient treatment. Drug–drug interaction is a major concern of combined therapy; hence, dual/multi-target inhibitors have become a dominant approach for cancer drug development. HDACs and HSP90 are involved in the activation of various oncogenic signaling pathways, including PI3K/AKT/mTOR, JAK/STAT, and RAF/MEK/ERK, which are also highly enriched in acute leukemia gene expression profiles. Therefore, we suggest that dual HDAC and HSP90 inhibitors could represent a novel therapeutic approach for acute leukemia. MPT0G449 is a dual effect inhibitor, and it showed cytotoxic effectiveness in acute leukemia cells. Molecular docking analysis indicated that MPT0G449 possessed dual HDAC and HSP90 inhibitory abilities. Furthermore, MPT0G449 induced G2 arrest and caspase-mediated cell apoptosis in acute leukemia cells. The oncogenic signaling molecules AKT, mTOR, STAT3, STAT5, MEK, and ERK were significantly downregulated after MPT0G449 treatment in HL-60 and MOLT-4 cells. In vivo xenograft models confirmed the antitumor activity and showed the upregulation of acetyl-histone H3 and HSP70, biomarkers of pan-HDAC and HSP90 inhibition, with MPT0G449 treatment. These findings suggest that the dual inhibition of HDAC and HSP90 can suppress the expression of oncogenic pathways in acute leukemia, and MPT0G449 represents a novel therapeutic for anticancer treatment.

Abstract Eradicating influenza A virus (IAV) is difficult, due to its genetic drift and reassortment ability. As the infectious cycle is initiated by the influenza glycoprotein, hemagglutinin (HA), which mediates the binding of virions to terminal sialic acids moieties, HA is a tempting target of anti-influenza inhibitors. However, the complexity of the HA structure has prevented delineation of the structural characterization of the HA protein–ligand complex. Our computational strategy efficiently analyzed > 200,000 records of compounds held in the United States National Cancer Institute (NCI) database and identified potential HA inhibitors, by modeling the sialic acid (SA) receptor binding site (RBS) for the HA structure. Our modeling revealed that compound NSC85561 showed significant antiviral activity against the IAV H1N1 strain with EC50 values ranging from 2.31 to 2.53 µM and negligible cytotoxicity (CC50 > 700 µM). Using the NSC85561 compound as the template to generate 12 derivatives, robust bioassay results revealed the strongest antiviral efficacies with NSC47715 and NSC7223. Virtual screening clearly identified three SA receptor binding site inhibitors that were successfully validated in experimental data. Thus, our computational strategy has identified SA receptor binding site inhibitors against HA that show IAV-associated antiviral activity.

The STE20 kinase family is a complex signalling cascade that regulates cytoskeletal organisation and modulates the stress response. This signalling cascade includes various kinase mediators, such as TAOK1 and MAP4K5. The dysregulation of the STE20 kinase pathway is linked with cancer malignancy. A small-molecule inhibitor targeting the STE20 kinase pathway has therapeutic potential. In this study, a structure-based virtual screening (SBVS) approach was used to identify potential dual TAOK1 and MAP4K5 inhibitors. Enzymatic assays confirmed three potential dual inhibitors (>50% inhibition) from our virtual screening, and analysis of the TAOK1 and MAP4K5 binding sites indicated common interactions for dual inhibition. Compound 1 revealed potent inhibition of colorectal and lung cancer cell lines. Furthermore, compound 1 arrested cancer cells in the G0/G1 phase, which suggests the induction of apoptosis. Altogether, we show that the STE20 signalling mediators TAOK1 and MAP4K5 are promising targets for drug research.

Abstract Background Despite the fact that histone deacetylase (HDAC) inhibitors have been tested to treat various cardiovascular diseases, the effects of selective HDAC6 inhibitor ACY1215 on infarct size during cardiac ischemia-reperfusion (IR) injury still remain unknown. In the present study we aimed to investigate the effects of ACY1215 on infarct size in rats with cardiac IR injury, as well as to examine the association between HDAC6 inhibitors and the gene expression of hypoxia inducible factor-1α (HIF-1α), a key regulator of cellular responses to hypoxia. Methods By using computational analysis of high-throughput expression profiling dataset, the association between HDAC inhibitors (pan-HDAC inhibitors panobinostat and vorinostat, and HDAC6 inhibitor ISOX) and their effects on HIF-1α gene-expression were evaluated. The male Wistar rats treated with ligation of left coronary artery followed by reperfusion were used as a cardiac IR model. ACY1215 (50 mg/kg), pan-HDAC inhibitor MPT0E028 (25 mg/kg), and vehicle were intraperitoneally injected within 5 min before reperfusion. The infarct size in rat myocardium was determined by 2,3,5-triphenyltetrazolium chloride staining. The serum levels of transforming growth factor-β (TGF-β) and C-reactive protein (CRP) were also determined. Results The high-throughput gene expression assay showed that treatment of ISOX was associated with a more decreased gene expression of HIF-1α than that of panobinostat and vorinostat. Compared to control rats, ACY1215-treated rats had a smaller infarct size (49.75 ± 9.36% vs. 19.22 ± 1.70%, p

Purpose Atrial fibrillation (AF) is a significant independent risk factor for 1-year mortality in patients with first acute ischemic stroke (AIS). The CHA2DS2-VASc score was initially developed to assess the risk of stroke in patients with AF. Recently, this scoring system has been demonstrated to have clinical value for predicting long-term clinical outcomes in AIS but the evidence is insufficient. This large-scale prospective cohort study investigated the independent predictive value of the score in such patients. Methods We included patients with AIS from the Taiwan Stroke Registry (TSR) during 2006–2016 as the present study population. Patients were divided into those with high (≥2) and low (Results A total of 62,227 patients with AIS were enrolled. The median age was 70.3 years, and 59% of the patients were women. After confounding factors were controlled, patients with high CHA2DS2-VASc scores had significantly higher incidence of 1-year MACCEs (adjusted hazard ratio [HR] = 1.63; 95% confidence interval [CI] = 1.52, 1.76), re-stroke (adjusted HR = 1.28; 95% CI = 1.16, 1.42), and all-cause mortality (adjusted HR = 2.03; 95% CI = 1.83, 2.24) than those with low CHA2DS2-VASc scores did. In the comparison between AF and non-AF groups, the AF group had increased MACCEs (adjusted HR = 1.74; 95% CI = 1.60, 1.89), myocardial infarction (adjusted HR = 4.86; 95% CI = 2.07, 11.4), re-stroke (adjusted HR = 1.47; 95% CI = 1.26, 1.71), and all-cause mortality (adjusted HR = 1.90; 95% CI = 1.72, 2.10). The Kaplan–Meier curve revealed that both CHA2DS2-VASc scores and AF were independent risk predictors for 1-year MACCEs and mortality. Conclusions The CHA2DS2-VASc score and AF appeared to consistently predict 1-year MACCEs of AIS patients and provide more accurate risk stratification. Therefore, increased use of the CHA2DS2-VASc score may help improve the holistic clinical assessment of AIS patients with or without AF.

Objectives: The Clinical Dementia Rating (CDR) Scale is the gold standard for the staging of dementia due to Alzheimer's disease (AD). However, the application of CDR for the staging of subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in AD remains controversial. This study aimed to use the sum of boxes of the CDR (CDR-SB) plus an SCD single questionnaire to operationally determine the different stages of cognitive impairment (CI) due to AD and non-AD.Methods: This was a two-phase study, and we retrospectively analyzed the Show Chwan Dementia registry database using the data selected from 2015 to 2020. Individuals with normal cognition (NC), SCD, MCI, and mild dementia (MD) due to AD or non-AD with a CDR < 2 were included in the analysis.Results: A total of 6,946 individuals were studied, including 875, 1,009, 1,585, and 3,447 with NC, SCD, MCI, and MD, respectively. The cutoff scores of CDR-SB for NC/SCD, SCD/MCI, and MCI/dementia were 0/0.5, 0.5/1.0, and 2.5/3.0, respectively. The receiver operating characteristic (ROC) analysis showed that the area under the curve (AUC) values of the test groups were 0.85, 0.90, and 0.92 for discriminating NC from SCD, SCD from MCI, and MCI from dementia, respectively. Compared with the Cognitive Abilities Screening Instrument or the Montreal Cognitive Assessment, the use of CDR-SB is less influenced by age and education.Conclusion: Our study showed that the operational determination of SCD, MCI, and dementia using the CDR-SB is practical and can be applied in clinical settings and research on CI or dementia.

Alternative splicing (AS) is a process that enables the generation of multiple protein isoforms with different biological properties from a single mRNA. Cancer cells often use the maneuverability conferred by AS to produce proteins that contribute to growth and survival. In our previous studies, we identified that amiloride modulates AS in cancer cells. However, the effective concentration of amiloride required to modulate AS is too high for use in cancer treatment. In this study, we used computational algorithms to screen potential amiloride derivatives for their ability to regulate AS in cancer cells. We found that 3,5‐diamino‐6‐chloro‐N‐(N‐(2,6‐dichlorobenzoyl)carbamimidoyl)pyrazine‐2‐carboxamide (BS008) can regulate AS of apoptotic gene transcripts, including HIPK3, SMAC, and BCL‐X, at a lower concentration than amiloride. This splicing regulation involved various splicing factors, and it was accompanied by a change in the phosphorylation state of serine/arginine‐rich proteins (SR proteins). RNA sequencing was performed to reveal that AS of many other apoptotic gene transcripts, such as AATF, ATM, AIFM1, NFKB1, and API5, was also modulated by BS008. In vivo experiments further indicated that treatment of tumor‐bearing mice with BS008 resulted in a marked decrease in tumor size. BS008 also had inhibitory effects in vitro, either alone or in a synergistic combination with the cytotoxic chemotherapeutic agents sorafenib and nilotinib. BS008 enabled sorafenib dose reduction without compromising antitumor activity. These findings suggest that BS008 may possess therapeutic potential for cancer treatment.

Abstract Protein ubiquitination is an important mechanism for regulating the activity and levels of proteins under physiological conditions. Loss of regulation by protein ubiquitination leads to various diseases, such as cancer. Two types of enzymes, namely, E1/E2/E3 ligases and deubiquitinases, are responsible for controlling protein ubiquitination. The ubiquitin-specific peptidases (USPs) are the main members of the deubiquitinase family. Many studies have addressed the roles of USPs in various diseases. An increasing number of studies have indicated that USPs are critical for cancer progression, and some USPs have been used as targets to develop inhibitors for cancer prevention. Herein we collect and organize most of the recent studies on the roles of USPs in cancer progression and discuss the development of USP inhibitors for cancer therapy in the future.

The biochemical identification of carotid artery stenosis (CAS) is still a challenge. Hence, 349 male subjects (176 normal controls and 173 stroke patients with extracranial CAS ≥ 50% diameter stenosis) were recruited. Blood samples were collected 14 days after stroke onset with no acute illness. Carotid plaque score (≥2, ≥5 and ≥8) was used to define CAS severity. Serum metabolites were analyzed using a targeted Absolute IDQ®p180 kit. Results showed hypertension, diabetes, smoking, and alcohol consumption were more common, but levels of diastolic blood pressure, HDL-C, LDL-C, and cholesterol were lower in CAS patients than controls (p < 0.05), suggesting intensive medical treatment for CAS. PCA and PLS-DA did not demonstrate clear separation between controls and CAS patients. Decision tree and random forest showed that acylcarnitine species (C4, C14:1, C18), amino acids and biogenic amines (SDMA), and glycerophospholipids (PC aa C36:6, PC ae C34:3) contributed to the prediction of CAS. Metabolite panel analysis showed high specificity (0.923 ± 0.081, 0.906 ± 0.086 and 0.881 ± 0.109) but low sensitivity (0.230 ± 0.166, 0.240 ± 0.176 and 0.271 ± 0.169) in the detection of CAS (≥2, ≥5 and ≥8, respectively). The present study suggests that metabolomics profiles could help in differentiating between controls and CAS patients and in monitoring the progression of CAS.

Patients with intracranial artery stenosis show high incidence of stroke. Angiography reports contain rich but underutilized information that can enable the detection of cerebrovascular diseases. This study evaluated various natural language processing (NLP) techniques to accurately identify eleven intracranial artery stenosis from angiography reports. Three NLP models, including a rule-based model, a recurrent neural network (RNN), and a contextualized language model, XLNet, were developed and evaluated by internal–external cross-validation. In this study, angiography reports from two independent medical centers (9614 for training and internal validation testing and 315 as external validation) were assessed. The internal testing results showed that XLNet had the best performance, with a receiver operating characteristic curve (AUROC) ranging from 0.97 to 0.99 using eleven targeted arteries. The rule-based model attained an AUROC from 0.92 to 0.96, and the RNN long short-term memory model attained an AUROC from 0.95 to 0.97. The study showed the potential application of NLP techniques such as the XLNet model for the routine and automatic screening of patients with high risk of intracranial artery stenosis using angiography reports. However, the NLP models were investigated based on relatively small sample sizes with very different report writing styles and a prevalence of stenosis case distributions, revealing challenges for model generalization.

Xestoquinone is a polycyclic quinone-type metabolite with a reported antitumor effect. We tested the cytotoxic activity of xestoquinone on a series of hematological cancer cell lines. The antileukemic effect of xestoquinone was evaluated in vitro and in vivo. This marine metabolite suppressed the proliferation of Molt-4, K562, and Sup-T1 cells with IC50 values of 2.95 ± 0.21, 6.22 ± 0.21, and 8.58 ± 0.60 µM, respectively, as demonstrated by MTT assay. In the cell-free system, it inhibited the activity of topoisomerase I (Topo I) and II (Topo II) by 50% after treatment with 0.235 and 0.094 μM, respectively. The flow cytometric analysis indicated that the cytotoxic effect of xestoquinone was mediated through the induction of multiple apoptotic pathways in Molt-4 cells. The pretreatment of Molt-4 cells with N-acetyl cysteine (NAC) diminished the disruption of the mitochondrial membrane potential (MMP) and apoptosis, as well as retaining the expression of both Topo I and II. In the nude mice xenograft model, the administration of xestoquinone (1 μg/g) significantly attenuated tumor growth by 31.2% compared with the solvent control. Molecular docking, Western blotting, and thermal shift assay verified the catalytic inhibitory activity of xestoquinone by high binding affinity to HSP-90 and Topo I/II. Our findings indicated that xestoquinone targeted leukemia cancer cells through multiple pathways, suggesting its potential application as an antileukemic drug lead.

It was shown that mixed lineage kinase 1 (MLK1) regulates pancreatic cancer growth; however, its role in prostate cancer remains unclear. We showed that MLK1 is a tumor marker in prostate cancer by analyzing clinical gene expression data and identified a novel MLK1 inhibitor (NSC14465) from the compound library of the National Cancer Institute (NCI) using a MLK1 protein structure. The inhibitory effects of MLK1 were validated by an in vitro kinase assay and by monitoring phosphorylation signaling, and the anti-proliferation function was shown in several prostate and pancreatic cancer cell lines. We also demonstrated anti-tumor ability and prevention of cancer-related weight loss in a syngeneic orthotopic mouse model of pancreatic cancer that mimicked the tumor growth environment in the pancreas. Our results demonstrate that the MLK1 inhibitor is an anti-tumor agent for malignant prostate and pancreatic cancers.

Abstract Histone deacetylases (HDAC) contain eighteen isoforms that can be divided into four classes. Of these isoform enzymes, class IIa (containing HDAC4, 5, 7 and 9) target unique substrates, some of which are client proteins associated with epigenetic control. Class IIa HDACs are reportedly associated with some neuronal disorders, making HDACs therapeutic targets for treating neurodegenerative diseases. Additionally, some reported HDAC inhibitors contain hydroxamate moiety that chelates with zinc ion to become the cofactor of HDAC enzymes. However, the hydroxamate functional group is shown to cause undesirable effects and has poor pharmacokinetic profile. This study used in silico virtual screening methodology to identify several nonhydroxamate compounds, obtained from National Cancer Institute database, which potentially inhibited HDAC4. Comparisons of the enzyme inhibitory activity against a panel of HDAC isoforms revealed these compounds had strong inhibitory activity against class IIa HDACs, but weak inhibitory activity against class I HDACs. Further analysis revealed that a single residue affects the cavity size between class I and class IIa HDACs, thus contributing to the selectivity of HDAC inhibitors discovered in this study. The discovery of these inhibitors presents the possibility of developing new therapeutic treatments that can circumvent the problems seen in traditional hydroxamate-based drugs.

Restenosis and destructive vascular remodeling are the main reasons for treatment failure in patients undergoing percutaneous coronary intervention (PCI). In this study, we explored the efficacy of magnolol (a traditional Chinese medicine) in the treatment of restenosis. The results of this study showed that the activities of thrombin and PAR-1 (protease-activated receptor 1) were significantly decreased by the treatment of magnolol. Based on protein docking analysis, magnolol exhibits its potential to bind to the PAR-1 active site. In addition, thrombin-induced connective tissue growth factor (CTGF) expression and the upstream of CTGF such as JNK-1 (but not JNK-2), c-Jun, and AP-1 were distinctly inhibited by magnolol (50 μM) in vascular smooth muscle cells (VSMC). For the functional assay, magnolol (50 μM) significantly inhibited the migration of VSMC, and rats treated with magnolol (13 mg/kg/day) after balloon angioplasty has observed a significant reduction in the formation of common arterial neointima. In conclusion, we identified a novel mechanism by which magnolol acts as the thrombin activity inhibitor and may be the PAR-1 antagonist. In accordance with these functions, magnolol could decrease thrombin-induced CTGF expression in VSMCs via PAR-1/JNK-1/AP-1 signaling.

Alzheimer’s disease (AD), which is among the most prevalent neurodegenerative diseases, manifests as increasing memory loss and cognitive decline. Tau phosphorylation and aggregation are strongly linked to neurodegeneration, as well as associated with chronic neuroinflammatory processes. The anti-inflammation effects of natural products have led to wide recognition of their potential for use in treating and preventing AD. This study investigated whether eupatin, a polymethoxyflavonoid found in Artemisia species, has inhibitory effects on neuroinflammation and tau phosphorylation. We treated mouse macrophages and microglia cells with lipopolysaccharides (LPSs) to activate inflammatory signals, and we treated neuronal cells with a protein phosphatase 2A inhibitor, okadaic acid (OA), or transfection with pRK5-EGFP-Tau P301L plasmid to induce tau phosphorylation. The results indicated that eupatin significantly reduced the LPS-induced protein expression and phosphorylation of p65 and inducible nitric oxide synthase as well as downstream products interleukin 6 and nitrite, respectively. Furthermore, eupatin markedly inhibited the expression of phospho-tau in response to OA treatment and plasmid transfection. We discovered that this inhibition was achieved through the inhibition of glycogen synthase kinase 3β (GSK3β), and molecular docking results suggested that eupatin can sufficiently bind to the GSK3β active site. Our results demonstrate that eupatin has neuroprotective effects, making it suitable for AD treatment.

13-Acetoxysarcocrassolide (13-AC), a marine cytotoxic product isolated from the alcyonacean coral Lobophytum crassum, exhibited potent antitumor and immunostimulant effects as reported in previous studies. However, the 13-AC antitumor mechanism of action against oral cancer cells remains unclear. The activity of 13-AC against Ca9-22 cancer cells was determined using MTT assay, flow cytometric analysis, immunofluorescence, immunoprecipitation, Western blotting, and siRNA. 13-AC induced apoptosis in oral cancer cells Ca9-22 through the disruption of mitochondrial membrane potential (MMP) and the stimulation of reactive oxygen species (ROS) generation. It increased the expression of apoptosis- and DNA damage-related proteins in a concentration- and time-dependent manner. It exerted potent antitumor effect against oral cancer cells, as demonstrated by the in vivo xenograft animal model. It significantly reduced the tumor volume (55.29%) and tumor weight (90.33%). The pretreatment of Ca9-22 cells with N-acetylcysteine (NAC) inhibited ROS production resulting in the attenuation of the cytotoxic activity of 13-AC. The induction of the Keap1-Nrf2 pathway and the promotion of p62/SQSTM1 were observed in Ca9-22 cells treated with 13-AC. The knockdown of p62 expression by siRNA transfection significantly attenuated the effect of 13-AC on the inhibition of cell viability. Our results indicate that 13-AC exerted its cytotoxic activity through the promotion of ROS generation and the suppression of the antioxidant enzyme activity. The apoptotic effect of 13-AC was found to be mediated through the interruption of the Keap1/Nrf2/p62/SQSTM1 pathway, suggesting its potential future application as an anticancer agent.

This study proposes a novel three-port bidirectional converter with a three-winding coupled inductor and applies it to a photovoltaic (PV) system to step up the PV system output to a dc bus or dc load while charging the battery. When the PV output is insufficient, battery voltage is stepped up to the dc bus voltage, and when the dc bus has excess energy, it is stepped down to charge the battery. Thus, a three-port bidirectional high step-up/step-down converter is achieved. A three-winding common core coupled inductor is designed and implemented in the converter, and a full-wave doubler circuit is used on the high-voltage side to achieve a high step-up effect. Power switches and diodes in the circuit are shared to achieve bidirectional operation. The output capacitors recover secondary-side leakage inductance energy in the step-up mode, and the third winding can be used to recover primary-side leakage inductance energy to reduce the voltage spike on switching in order to improve the converter’s conversion efficiency. A 500-W three-port bidirectional converter is implemented to verify the feasibility and practicability of the proposed topology. According to the measurement results, the highest efficiency of the PV step-up mode is 95.3%, the highest efficiency of the battery step-up mode is 94.1%, and the highest efficiency of the step-down mode is 94.8%.

The JAK2/STAT signaling pathway mediates cytokine receptor signals that are involved in cell growth, survival and homeostasis. JAK2 is a member of the Janus kinase (JAK) family and aberrant JAK2/STAT is involved with various diseases, making the pathway a therapeutic target. The similarity between the ATP binding site of protein kinases has made development of specific inhibitors difficult. Current JAK2 inhibitors are not selective and produce unwanted side effects. It is thought that increasing selectivity of kinase inhibitors may reduce the side effects seen with current treatment options. Thus, there is a great need for a selective JAK inhibitor. In this study, we identified a JAK2 specific inhibitor. We first identified key pharmacological interactions in the JAK2 binding site by analyzing known JAK2 inhibitors. Then, we performed structure-based virtual screening and filtered compounds based on their pharmacological interactions and identified compound NSC13626 as a potential JAK2 inhibitor. Results of enzymatic assays revealed that against a panel of kinases, compound NSC13626 is a JAK2 inhibitor and has high selectivity toward the JAK2 and JAK3 isozymes. Our cellular assays revealed that compound NSC13626 inhibits colorectal cancer cell (CRC) growth by downregulating phosphorylation of STAT3 and arresting the cell cycle in the S phase. Thus, we believe that compound NSC13626 has potential to be further optimized as a selective JAK2 drug.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with multiple etiologies. Beta-amyloid (Aβ) self-aggregation and overexpression of class IIa histone deacetylases (HDACs) are strongly implicated with AD pathogenesis. In this study, a series of novel diarylheptanoid derivatives were designed, synthesized and evaluated for use as dual Aβ self-aggregation and class IIa HDAC inhibitors. Among these compounds, 4j, 5c, and 5e displayed effective inhibitions for Aβ self-aggregation, HDAC5 activity and HDAC7 activity with IC50 values of

The combination cancer therapy is a new strategy to circumvent drug resistance for the treatment of high metastasis and advanced malignancies. Herein, we developed a synthesized compound MPT0B451 that display inhibitory effect against histone deacetylase (HDAC) 6 and tubulin assembly. Our data demonstrated that MPT0B451 significantly inhibited cancer cell growths in HL-60 and PC-3 cells due to inhibition of HDAC activity. MPT0B451 also markedly increased caspase-mediated apoptosis in these cells. The cell cycle analysis showed mitotic arrest induced by MPT0B451 with enhanced expression of G2/M transition proteins. Moreover, molecular docking analysis supported MPT0B451 as a dual HDAC6 and tubulin inhibitor. Finally, MPT0B451 led to tumor growth inhibition (TGI) in HL-60 and PC-3 xenograft models. These findings indicated that MPT0B451 has dual inhibition effects for HDAC6 and tubulin, and also contributed to G2/M arrest followed by apoptotic induction. Together, our results suggested that MPT0B451 may serve as a potent anti-cancer treatment regimen in human prostate cancer and acute myeloid leukemia.

5-Demethyltangeretin (5-DTAN), an autohydrolysis product of tangeretin (TAN) found in citrus peel, exhibited more potent anti-proliferative activity in human cancer cells than TAN itself. In this study, we investigated the anti-tumor promoting effect and underlying molecular mechanism of 5-DTAN on 7,12-dimethyl-benz(a)anthracene (DMBA)-induced and 12-O-tetradecanoylphorbol-13-acetate (TPA)-promoted skin carcinogenesis. Application of 5-DTAN prior to each TPA-treatment was more effective than that of TAN on reducing the number, incidence and size of papillomas in DMBA-initiated mouse skin. Moreover, 5-DTAN suppressed cyclooxygenase-2 (COX-2) protein expression more strongly than TAN through interfering with phosphatidylinositiol 3-kinase (PI3K)/Akt signaling and further activation of transcription factor NF-κB. Taken together, these results revealed for the first time the in vivo chemopreventive efficacy of 5-DTAN on inhibition of skin carcinogenesis through promoting apoptosis and molecular interactions with residues of PI3K, COX-2, and AKT that may potentially serve as a novel functional agent capable of preventing inflammation-associated tumorigenesis.

Acute hepatopancreatic necrosis disease (AHPND) is a newly emergent penaeid shrimp disease which can cause 70–100% mortality in Penaeus vannamei and Penaeus monodon, and has resulted in enormous economic losses since its appearance. AHPND is caused by the specific strains of Vibrio parahaemolyticus that harbor the pVA1 plasmid and express PirAvp and PirBvp toxins. These two toxins have been reported to form a binary complex. When both are present, they lead to the death of shrimp epithelial cells in the hepatopancreas and cause the typical histological symptoms of AHPND. However, the binding mode of PirAvp and PirBvp has not yet been determined. Here, we used isothermal titration calorimetry (ITC) to measure the binding affinity of PirAvp and PirBvp. Since the dissociation constant (Kd = 7.33 ± 1.20 μM) was considered too low to form a sufficiently stable complex for X-ray crystallographic analysis, we used alternative methods to investigate PirAvp-PirBvp interaction, first by using gel filtration to evaluate the molecular weight of the PirAvp/PirBvp complex, and then by using cross-linking and hydrogen-deuterium exchange (HDX) mass spectrometry to further understand the interaction interface between PirAvp and PirBvp. Based on these results, we propose a heterotetrameric interaction model of this binary toxin complex. This model provides insight of how conformational changes might activate the PirBvp N-terminal pore-forming domain and should be helpful for devising effective anti-AHPND strategies in the future.

DNA mimicry is a direct and effective strategy by which the mimic competes with DNA for the DNA binding sites on other proteins. Until now, only about a dozen proteins have been shown to function via this strategy, including the DNA mimic protein DMP19 from Neisseria meningitides. We have shown previously that DMP19 dimer prevents the operator DNA from binding to the transcription factor NHTF. Here, we provide new evidence that DMP19 monomer can also interact with the Neisseria nucleoid-associated protein HU. Using BS3 crosslinking, gel filtration and isothermal titration calorimetry assays, we found that DMP19 uses its monomeric form to interact with the Neisseria HU dimer. Crosslinking conjugated mass spectrometry was used to investigate the binding mode of DMP19 monomer and HU dimer. Finally, an electrophoretic mobility shift assay (EMSA) confirmed that the DNA binding affinity of HU is affected by DMP19. These results showed that DMP19 is bifunctional in the gene regulation of Neisseria through its variable oligomeric forms.

Precision medicine considers an individual's unique physiological characteristics as strongly influential in disease vulnerability and in response to specific therapies. Predicting an individual's susceptibility to developing an illness, making an accurate diagnosis, maximizing therapeutic effects, and minimizing adverse effects for treatment are essential in precision medicine. We introduced model-based precision medicine optimization approaches, including pathogenesis, biomarker detection, and drug target discovery, for treating presynaptic dopamine overactivity. Three classes of one-hit and two-hit enzyme defects were detected as the causes of disease states by the optimization approach of pathogenesis. The cluster analysis and support vector machine was used to detect optimal biomarkers in order to discriminate the accurate etiology from three classes of disease states. Finally, the fuzzy decision-making method was employed to discover common and specific drug targets for each classified disease state. We observed that more accurate diagnoses achieved higher satisfaction grades and dosed fewer enzyme targets to treat the disease. Furthermore, satisfaction grades for common drugs were lower than for specific ones, but common drugs could simultaneously treat several disease states that had different etiologies.

Model-based optimization approaches are valuable in developing new drugs for human metabolic disorders. The core objective in most optimal drug designs is positive therapeutic effects. In this study, we considered the effects of therapeutic, adverse, and target variation simultaneously. A fuzzy optimization method was applied to formulate a multiobjective drug design problem for detecting enzyme targets in the presynaptic dopamine metabolic network to remedy two types of enzymopathies caused by deficiencies of vesicular monoamine transporter 2 (VMAT2) and tyrosine hydroxylase (TH). The fuzzy membership approach transforms a two-stage drug discovery problem into a unified decision-making problem. We developed a nested hybrid differential evolution algorithm to efficiently identify a set of potential drug targets. Furthermore, we also simulated the effects of current clinical drugs for Parkinson's disease (PD) in this model and tried to clarify the possible causes of neurotoxic and neuroprotective effects. The optimal drug design could yield 100% satisfaction grade when both therapeutic effect and the number of targets were considered in the objective. This scenario required regulating one to three and one or two enzyme targets for 50%-95% and 50%-100% VMAT2 and TH deficiencies, respectively. However, their corresponding adverse and target variation effect grades were less satisfactory. For the most severe deficiencies of VMAT2 and TH, a compromise design could be obtained when the effects of therapeutic, adverse, and target variation were simultaneously applied to the optimal drug discovery problem. Such a trade-off design followed the no free lunch theorem for optimization; that is, a more serious dopamine deficiency required more enzyme targets and lower satisfaction grade. In addition, the therapeutic effects of current clinical medications for PD could be enhanced in combination with new enzyme targets. The increase of toxic metabolites after treatment might be the cause of neurotoxic effects of some current PD medications.

Areca nut (AN) is a popular carcinogen used by about 0.6-1.2 billion people worldwide. Although AN contains apoptosis-inducing ingredients, we previously demonstrated that both AN extract (ANE) and its 30-100 kDa fraction (ANE 30-100K) predominantly induce autophagic cell death in both normal and malignant cells. In this study, we further explored the action mechanism of ANE 30-100K-induced autophagy (AIA) in Jurkat T lymphocytes and carcinoma cell lines including OECM-1 (mouth), CE81T/VGH (esophagus), SCC25 (tongue), and SCC-15 (tongue). The results showed that chemical- and small hairpin RNA (shRNA)-mediated inhibition of AMP-activated protein kinase (AMPK) resulted in the attenuation of AIA in Jurkat T but not in OECM-1 cells. Knockdown of Atg5 and Beclin 1 expressions ameliorated AIA in OECM-1/CE81T/VGH/Jurkat T and OECM-1/SCC25/SCC-15, respectively. Furthermore, ANE 30-100K could activate caspase-3 after inhibition of Beclin 1 expression in OECM-1/SCC25/SCC15 cells. Meanwhile, AMPK was demonstrated to be the upstream activator of the extracellular-regulated kinase (ERK) in Jurkat T cells, and inhibition of MEK attenuated AIA in Jurkat T/OECM-1/CE81T/VGH cells. Finally, we also found that multiple myeloma RPMI8226, lymphoma U937, and SCC15 cells survived from long-term non-cytotoxic ANE 30-100K treatment exhibited stronger resistance against serum deprivation through upregulated autophagy. Collectively, our studies indicate that Beclin-1 and Atg5 but not AMPK are commonly required for AIA, and MEK/ERK pathway is involved in AIA. Meanwhile, it is also suggested that long-term AN usage might increase the resistance of survived tumor cells against serum-limited conditions.

In aquaculture, shrimp farming is a popular field. The benefits of shrimp farming include a relatively short grow-out time, high sale price, and good cost recovery. However, outbreaks of serious diseases inflict serious losses, and acute hepatopancreatic necrosis disease (AHPND) is an emerging challenge to this industry. In South American white shrimp (Penaeus vannamei) and grass shrimp (Penaeus monodon), this disease has a 70–100% mortality. The pathogenic agent of AHPND is a specific strain of Vibrio parahaemolyticus which contains PirAvp and PirBvp toxins encoded in the pVA1 plasmid. PirAvp and PirBvp have been shown to cause the typical histological symptoms of AHPND in infected shrimps, and in this review, we will focus on our structural understanding of these toxins. By analyzing their structures, a possible cytotoxic mechanism, as well as strategies for anti-AHPND drug design, is proposed.

Hispidulin is a naturally occurring flavone known to have various Central nervous system (CNS) activities. Proposed synthetic approaches to synthesizing hispidulin have proven unsatisfactory due to their low feasibility and poor overall yields. To solve these problems, this study developed a novel scheme for synthesizing hispidulin, which had an improved overall yield as well as more concise reaction steps compared to previous methods reported. Additionally, using the same synthetic strategy, d-labelled hispidulin was synthesized to investigate its metabolic stability against human liver microsome. This work may produce new chemical entities for enriching the library of hispidulin-derived compounds.