SDDSynergy: Learning Important Molecular Substructures for Explainable Anticancer Drug Synergy Prediction.

Drug combination therapies are well-established strategies for the treatment of cancer with low toxicity and fewer adverse effects. Computational drug synergy prediction approaches can accelerate the discovery of novel combination therapies, but the existing methods do not explicitly consider the key role of important substructures in producing synergistic effects. To this end, we propose a significant substructure-aware anticancer drug synergy prediction method, named SDDSynergy, to adaptively identify critical functional groups in drug synergy. SDDSynergy splits the task of predicting drug synergy into predicting the effect of individual substructures on cancer cell lines and highlights the impact of important substructures through a novel drug-cell line attention mechanism. And a substructure pair attention mechanism is incorporated to capture the information on internal substructure pairs interaction in drug combinations, which aids in predicting synergy. The substructures of different sizes and shapes are directly obtained from the molecular graph of the drugs by multilayer substructure information passing networks. Extensive experiments on three real-world data sets demonstrate that SDDSynergy outperforms other state-of-the-art methods. We also verify that many of the novel drug combinations predicted by SDDSynergy are supported by previous studies or clinical trials through an in-depth literature survey.

Structurally Diverse Bisbenzylisoquinoline Alkaloids with Antiadipogenic Activity through PPARγ Downregulation from the Embryo of Nelumbo nucifera Seeds.

Six undescribed and six known bisbenzylisoquinoline alkaloids were isolated from the embryo of Nelumbo nucifera seeds. Their structures were fully characterized by a combination of 1H, 13C NMR, 2D NMR, and HRESIMS analyses, as well as ECD computational calculations. The antiadipogenic activity of 11 alkaloids was observed in a dose-responsive manner, leading to the suppression of lipid accumulation in 3T3-L1 cells. Luciferase assay and Western blot analysis showed that the active alkaloids downregulated peroxisome proliferator-activated receptor gamma (PPARγ, a key antiadipogenic receptor) expression in 3T3-L1 cells. Analysis of the structure-activity relationship unveiled that a 1R,1'S configuration in bisbenzylisoquinoline alkaloids led to a notable enhancement in antiadipogenic activity. The resistance level against lipid accumulation highlighted a consistent pattern with the suppressive effect on the PPARγ expression. These activity results indicate that alkaloids from the embryo of N. nucifera seeds have a potential of antiobesity effects through PPARγ downregulation.

Ultra-performance liquid chromatography-quadrupole time-of-flight mass combined with UNIFI to study the mechanism of Tao Hong Si Wu Decoction in the treatment of postpartum blood stasis.

Postpartum hemorrhage can lead to a variety of maternal complications. Tao Hong Si Wu Decoction (THSWD) is a traditional Chinese medicine used for treating gynecological diseases. However, the active ingredients of THSWD and its pharmacological mechanism of treatment for postpartum blood stasis still remained unclear. In this study, 201 components were identified in THSWD ethanol extract using ultra-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry, including 59 terpenoids and volatile oil, 61 Phenylpropanoids, 41 flavonoids, 22 alkaloids, and other 18 components. A total of 45 active compounds were identified in the blood and 33 active compounds were identified in the uterine. Taking the common components into the blood and into the uterus combined with network pharmacology. It was demonstrated that the active compounds can bind to the core target with good affinity through molecular docking. The results of this study will provide a reference for the quality control and pharmacodynamic material base research of THSWD.

B-LBConA: a medical entity disambiguation model based on Bio-LinkBERT and context-aware mechanism.

BACKGROUND: The main task of medical entity disambiguation is to link mentions, such as diseases, drugs, or complications, to standard entities in the target knowledge base. To our knowledge, models based on Bidirectional Encoder Representations from Transformers (BERT) have achieved good results in this task. Unfortunately, these models only consider text in the current document, fail to capture dependencies with other documents, and lack sufficient mining of hidden information in contextual texts. RESULTS: We propose B-LBConA, which is based on Bio-LinkBERT and context-aware mechanism. Specifically, B-LBConA first utilizes Bio-LinkBERT, which is capable of learning cross-document dependencies, to obtain embedding representations of mentions and candidate entities. Then, cross-attention is used to capture the interaction information of mention-to-entity and entity-to-mention. Finally, B-LBConA incorporates disambiguation clues about the relevance between the mention context and candidate entities via the context-aware mechanism. CONCLUSIONS: Experiment results on three publicly available datasets, NCBI, ADR and ShARe/CLEF, show that B-LBConA achieves a signifcantly more accurate performance compared with existing models.

Rapid separation and characterization of the in vitro metabolites of moscatilin by ultra-high performance liquid chromatography coupled to hybrid quadrupole orbitrap tandem mass spectrometry.

Moscatilin, a bioactive ingredient isolated from Dendrobium moscatum, has been demonstrated to have excellent anti-cancer activity. The goals of the present study were to investigate the metabolic profiles of moscatilin and to identify and characterize its metabolites. In vitro studies were performed by incubating moscatilin (10 µM) with rat, dog, monkey, and human liver microsomes (0.5 mg protein/ml) to generate the metabolites. An analytical method of liquid chromatography combined with hybrid quadrupole orbitrap high-resolution mass spectrometry in full mass/data-dependent tandem mass spectrometry scan was utilized to separate and identify the metabolites in accordance with their accurate masses, formulas, and tandem mass spectrometry fragment ions determination. A total of six phase I metabolites were detected and structurally characterized. The phase I metabolic pathways of moscatilin were hydroxylation, demethylation, and dehydrogenation. In glutathione-supplemented liver microsomes, nine glutathione conjugates were detected and identified. Our results demonstrated that moscatilin was susceptible to bioactivation with the result of ortho quinone and quinone-methide intermediates. The present study provided an overview of the in vitro metabolic profiles of moscatilin, which will aid in the understanding of the efficacy and safety of this active compound.

Constrained transformer network for ECG signal processing and arrhythmia classification.

BACKGROUND: Heart disease diagnosis is a challenging task and it is important to explore useful information from the massive amount of electrocardiogram (ECG) records of patients. The high-precision diagnostic identification of ECG can save clinicians and cardiologists considerable time while helping reduce the possibility of misdiagnosis at the same time.Currently, some deep learning-based methods can effectively perform feature selection and classification prediction, reducing the consumption of manpower. METHODS: In this work, an end-to-end deep learning framework based on convolutional neural network (CNN) is proposed for ECG signal processing and arrhythmia classification. In the framework, a transformer network is embedded in CNN to capture the temporal information of ECG signals and a new link constraint is introduced to the loss function to enhance the classification ability of the embedding vector. RESULTS: To evaluate the proposed method, extensive experiments based on real-world data were conducted. Experimental results show that the proposed model achieve better performance than most baselines. The experiment results also proved that the transformer network pays more attention to the temporal continuity of the data and captures the hidden deep features of the data well. The link constraint strengthens the constraint on the embedded features and effectively suppresses the effect of data imbalance on the results. CONCLUSIONS: In this paper, an end-to-end model is used to process ECG signal and classify arrhythmia. The model combine CNN and Transformer network to extract temporal information in ECG signal and is capable of performing arrhythmia classification with acceptable accuracy. The model can help cardiologists perform assisted diagnosis of heart disease and improve the efficiency of healthcare delivery.

Hydrophobicity and iron coagulation of extracellular polymeric substance from colonial Microcystis.

The bloom-forming cyanobacterium Microcystis occurs mainly as colonial aggregates under the natural conditions. This paper investigated the hydrophobicity and iron coagulation of extracellular polymeric substances (EPSs) from colonial Microcystis in order to understand the impact of EPS on the water treatment process. The higher contents of dissolved EPS (dEPS) and bound EPS (bEPS, mucilaginous matrix around the cells), lower dEPS/bEPS ratio and greater negative zeta potential of bEPS and dEPS were found in colonial Microcystis compared with unicellular Microcystis. XAD resin fractionation analysis indicated that the hydrophobicity could be ranked in an order as follows: bEPS > dEPS > dissolved extracellular organic matter (dEOM) for all the Microcystis strains. Correlation analysis showed that there was a statistically significant correlation between the amounts of carbohydrate and dissolved organic carbon in the hydrophobic fraction of EOM (dEOM, dEPS and bEPS), indicating that the hydrophobicity of Microcystis EOM might be related to carbohydrate. The coagulation experiment showed that for each colonial Microcystis strain, the removal efficiency of bEPS was higher than that of dEPS within the pH range from 3 to 10. The implications of the EPS characteristics were further discussed with respect to water treatment.

Synovial Fluid Macrophage Migration Inhibitory Factor Levels Correlate with Severity of Self-Reported Pain in Knee Osteoarthritis Patients.

BACKGROUND Inflammation is considered as one of the main pathogeneses in OA-induced pain. Macrophage migration inhibitory factor (MIF) is a well known pro-inflammatory cytokine. We aimed to determine whether MIF levels in serum and synovial fluid (SF) are associated with severity of OA-induced pain. MATERIAL AND METHODS We recruited 226 patients with knee OA and 106 controls. Self-reported pain severity of OA patients was evaluated using the Western Ontario McMaster University Osteoarthritis (WOMAC) pain scores. MIF levels were detected using enzyme-linked immunosorbent assay (ELISA). RESULTS OA patients had similar serum MIF levels compared to controls (11.93 [5.68-18.10] vs. 10.06 [6.60-14.61] ng/ml, P>0.05). In OA patients, MIF levels in SF were dramatically lower compared to paired serum samples (3.39 [1.87-5.89] vs. 11.93 [5.68-18.10] ng/ml, P<0.01). MIF levels in SF were significantly correlated with WOMAC pain scores (r=0.237, P<0.001), but MIF levels in serum had no significant correlation with WOMAC pain scores (r=0.009, P=0.898). CONCLUSIONS MIF levels in SF, but not in serum, were independently associated with the severity of self-reported pain in OA patients. The inhibition of MIF signaling pathways may be a novel therapeutic approach for ameliorating OA-induced pain.

Effects of paraquat on photosynthetic pigments, antioxidant enzymes, and gene expression in Chlorella pyrenoidosa under mixotrophic compared with autotrophic conditions.

Only limited information is available on herbicide toxicity to algae under mixotrophic conditions. In the present study, we studied the effects of the herbicide paraquat on growth, photosynthetic pigments, antioxidant enzymes, and gene expression in Chlorella pyrenoidosa under mixotrophic compared with autotrophic conditions. The mean measured exposure concentrations of paraquat under mixotrophic and autotrophic conditions were in the range of 0.3-3.4 and 0.6-3.6 µM, respectively. Exposure to paraquat for 72 h under both autotrophic and mixotrophic conditions induced decreased growth and chlorophyll (Chl) content, increased superoxide dismutase and peroxidase activities, and decreased transcript abundances of three photosynthesis-related genes (light-independent protochlorophyllide reductase subunit, photosystem II protein D1, and ribulose-1,5-bisphosphate carboxylase/oxygenase large subunit [rbcL]). Compared with autotrophic conditions, the inhibition percentage of growth rate under mixotrophic conditions was lower at 0.8 µM paraquat, whereas it was greater at 1.8 and 3.4 µM paraquat. With exposure to 0.8-3.4 µM paraquat, the inhibition rates of Chl a and b content under mixotrophic conditions (43.1-52.4% and 54.6-59.7%, respectively) were greater compared with autotrophic conditions, whereas the inhibition rate of rbcL gene transcription under mixotrophic conditions (35.7-44.0%) was lower. These data showed that similar to autotrophic conditions, paraquat affected the activities of antioxidant enzymes and decreased Chl synthesis and transcription of photosynthesis-related genes in C. pyrenoidosa under mixotrophic conditions, but a differential susceptibility to paraquat toxicity occurred between autotrophically versus mixotrophically grown cells.

DeepMGT-DTI: Transformer network incorporating multilayer graph information for Drug-Target interaction prediction.

Drug-target interaction (DTI) prediction reduces the cost and time of drug development, and plays a vital role in drug discovery. However, most of research does not fully explore the molecular structures of drug compounds in DTI prediction. To this end, we propose a deep learning model to capture the molecular structure information of drug compounds for DTI prediction. This model utilizes a transformer network incorporating multilayer graph information, which captures the features of a drug's molecular structure so that the interactions between atoms of drug compounds can be explored more deeply. At the same time, a convolutional neural network is employed to capture the local residue information in the target sequence, and effectively extract the feature information of the target. The experiments on the DrugBank dataset showed that the proposed model outperformed previous models based on the structure of target sequences. The results indicate that the improved transformer network fuses the feature information between layers in the graph convolutional neural network and extracts the interaction data for the molecular structure. The drug repositioning experiment on COVID-19 and Alzheimer's disease demonstrated the proposed model's ability to find therapeutic drugs in drug discovery. The code of our model is available at https://github.com/zhangpl109/DeepMGT-DTI.

Swallowing function after acute ischemic stroke: Development and validation of a novel clinical prognostic model.

Background: Predicting the duration of dysphagia after acute ischemic stroke (AIS) is important for clinical treatment decisions. Objective: The purpose of this study is to assess the swallowing function of AIS patients and to develop and validate a prognostic model for the need for nasogastric tube (NGT) in these patients. Materials and methods: We included 554 AIS patients during 2018-2019 as the development group and had 186 AIS patients as the external validation group. The primary end point of the study was the retention of NGT in patients 1 week after admission (Functional Oral Intake Scale ≤ 4). Swallowing function and stroke-associated pneumonia (SAP) at 1 month post-onset were also the objectives of this study. The volume-viscosity swallow test (V-VST) was used to assess the patient's impaired swallowing function. The Predictive model was built by logistic regression. Results: Overall, a total of 104 patients required indwelling NGT at 1 week of AIS onset in development group. The final prognostic model includes 5 variables: age (OR: 1.085, 95%CI: 1.049-1.123), neutrophil-to-lymphocyte ratio (NLR) (OR: 1.332, 95%CI: 1.090-1.626), NIHSS (OR: 1.092, 95%CI: 1.025-1.164), history of drinking (OR: 2.532, 95%CI: 1.452-4.417) and stroke location (Subtentorial vs. Supratentorial, OR: 1.954, 95%CI: 1.088-3.509). The prediction model had an AUC of 0.810, while the external validation group was 0.794. Conclusion: In stroke patients, it is very important to decide early whether to indwell a NGT. The nomogram will support decision making for NGT insertion and help these patients recover from their condition.

OsWHY1 Interacts with OsTRX z and is Essential for Early Chloroplast Development in Rice.

WHIRLY (WHY) family proteins, a small family of single-stranded DNA (ssDNA) binding proteins, are widely found in plants and have multiple functions to regulate plant growth and development. However, WHY in rice has received less attention. In this study, we continued our previous study on OsTRX z that is important for chloroplast development. OsTRX z was discovered to interact with OsWHY1, which was confirmed using yeast two-hybrid, pull-down, and BiFC assays. Subsequently, the oswhy1 mutants were obtained by CRISPR/Cas9, which exhibited an albino phenotype and died after the three-leaf stage. Consistent with this albino phenotype, low amounts of Chl a, Chl b, and Car were detected in the oswhy1-1 mutant. Moreover, the oswhy1-1 mutant had chloroplasts with disrupted architecture and no stacked grana and thylakoid membranes. Subcellular localization showed that the OsWHY1-GFP fusion protein was targeted to the chloroplast. What's more, OsWHY1 was found to be preferentially expressed in young leaves and was involved in chloroplast RNA editing and splicing. Mutation of OsWHY1 significantly affected the expression of chloroplast and ribosome development-related and chlorophyll synthesis-related genes. In conclusion, OsWHY1 contributes to early chloroplast development and normal seedling survival in rice. These results will further elucidate the molecular mechanism of chloroplast development and expand our understanding of WHY1 functions.

RDFNet: A Fast Caries Detection Method Incorporating Transformer Mechanism.

Dental caries is a prevalent disease of the human oral cavity. Given the lack of research on digital images for caries detection, we construct a caries detection dataset based on the caries images annotated by professional dentists and propose RDFNet, a fast caries detection method for the requirement of detecting caries on portable devices. The method incorporates the transformer mechanism in the backbone network for feature extraction, which improves the accuracy of caries detection and uses the FReLU activation function for activating visual-spatial information to improve the speed of caries detection. The experimental results on the image dataset constructed in this study show that the accuracy and speed of the method for caries detection are improved compared with the existing methods, achieving a good balance in accuracy and speed of caries detection, which can be applied to smart portable devices to facilitate human dental health management.

siRNA-Loaded Hydroxyapatite Nanoparticles for KRAS Gene Silencing in Anti-Pancreatic Cancer Therapy.

Pancreatic carcinoma (PC) is greatly induced by the KRAS gene mutation, but effective targeted delivery for gene therapy has not existed. Small interfering ribonucleic acid (siRNA) serves as an advanced therapeutic modality and holds great promise for cancer treatment. However, the development of a non-toxic and high-efficiency carrier system to accurately deliver siRNA into cells for siRNA-targeted gene silencing is still a prodigious challenge. Herein, polyethylenimine (PEI)-modified hydroxyapatite (HAp) nanoparticles (HAp-PEI) were fabricated. The siRNA of the KRAS gene (siKras) was loaded onto the surface of HAp-PEI via electrostatic interaction between siRNA and PEI to design the functionalized HAp-PEI nanoparticle (HAp-PEI/siKras). The HAp-PEI/siKras was internalized into the human PC cells PANC-1 to achieve the maximum transfection efficiency for active tumor targeting. HAp-PEI/siKras effectively knocked down the expression of the KRAS gene and downregulated the expression of the Kras protein in vitro. Furthermore, the treatment with HAp-PEI/siKras resulted in greater anti-PC cells' (PANC-1, BXPC-3, and CFPAC-1) efficacy in vitro. Additionally, the HAp-PEI exhibited no obvious in vitro cytotoxicity in normal pancreatic HPDE6-C7 cells. These findings provided a promising alternative for the therapeutic route of siRNA-targeted gene engineering for anti-pancreatic cancer therapy.

CYFRA21-1 can predict the sensitivity to chemoradiotherapy of non-small-cell lung carcinoma.

BACKGROUND: The increasing panel of systemic therapies enables the individual management of lung cancer patients, even in advanced stages. However, predictive tools indicating the efficacy of chemoradiotherapy (CRT) are badly needed. AIMS: To determine the tumour markers for predicting the therapeutic effect in non-small-cell lung carcinoma (NSCLC) patients treated with CRT. METHODS: The serum levels of cytokeratin 19 fragment antigen 21-1 (CYFRA21-1), neurone-specific enolase (NSE) and carcinoembryonic antigen (CEA) were measured before CRT by enzyme-linked immunosorbent assays, while the tumour responses were assessed according to the World Health Organization (WHO) response criteria. The relationships between pretreatment expression of CYFRA21-1, NSE, CEA and the effectiveness of CRT were analysed. RESULTS: The complete response (CR) rate of the primary tumours estimated by computed tomography in patients with high levels of CYFRA21-1 was 2.9% (2/68) while in cases with low CYFRA21-1 it was 20.3% (12/59) (p = 0.005). The effective rates (CR+PR) in CYFRA21-1 high and low groups were 52.9% (36/68) and 72.9% (43/59), respectively (p = 0.022). CONCLUSIONS: CYFRA21-1 may be a reliable surrogate marker of CRT efficacy in patients with NSCLC.

Anti-adipogenic 18,19-seco-ursane stereoisomers and oleane-type saponins from Ilex cornuta leaves.

Three undescribed seco-ursane stereoisomers, ilexcornutosides A-C, two undescribed triterpenoid saponins, ilexcornutosides D-E, and 11 known triterpenoids were isolated from the leaves of Ilex cornuta Lindl. & Paxton. Ilexcornutosides A-C and F with the same planar structures are unique 13(18)-ene-18,19-seco-ursane skeleton triterpenoids, identified as (3S,12R)-3-O-[ß-d-glucopyranosyl-(1 â†’ 2)-α-l-arabinopyranosyl]-12-hydroxyl-19-oxo-18,19-secours-13(18)-en-28,21-lactone. Among them, ilexcornutosides A and F (or ilexcornutosides B and C) are a pair of diastereomers at the C-20 position; ilexcornutosides A and C (or ilexcornutosides B and F) are a pair of diastereomers with epimerization at the C-21. Their structures were established by extensive spectroscopic (IR, 1D and 2D NMR, and HR-ESI-MS) and chemical analyses. The absolute configurations of ilexcornutosides A, B, D and F were determined by a single crystal X-ray diffraction analysis with a Cu Kα radiation. The inhibitory effect of ilexcornutosides A-F on the PPARγ expression was assessed in the 3T3-L1-Lenti-PPARγ-Luc cells using a single luciferase reporter assay. Ilexcornutosides A and C showed a comparable activity in decrease of the PPARγ expression to the positive control (T0070907) at 5 µM.

Atypical teratoid rhabdoid tumor mimicking type II neurofibromatosis: A case report.

RATIONALE: Brain magnetic resonance imaging (MRI) images of atypical teratoid rhabdoid tumor (ATRT) often present heterogeneous signals of various cells without remarkable features of the disease. We describe a unique case of atypical brain MRI images presenting as an type II neurofibromatosis and explore some diagnostic hints. PATIENT CONCERNS: A 1-year-and-7-month-old boy admitted to our department with a 7-day history of drowsiness and 2-day history of emesis, and his presenting complaint was repeated vomit. On physical examination, he had drowsiness, positive sun set sign, slow light reflection, high muscular tension of limbs and 55 cm head circumference. MRI presented masses of bilateral auditory nerve distribution area, the fourth ventricle and right frontal lobe, obstructive hydrocephalus, and amplified cisterna magna. Particularly, dumbbell shape tumor in left cerebellopontine angle area and the fourth ventricle showed iso- or hypo-intensity on T1-weighted image and mix-intensity on T2-weighted image with irregular frontier, obvious mutual high and low signal on T2-weighted image, and growing along cerebrospinal fluid pathway. DIAGNOSIS: The diagnosis of type II neurofibromatosis (NF-II) was considered pre-operatively. After surgery, postoperative histopathology confirmed the diagnosis of ATRT. INTERVENTIONS: After ventriculo-peritoneal (VP) shunt, no evidence of tumor was inspected in cerebrospinal fluid, and enhancement MRI showed heterogeneous contrast signal on dumbbell shape tumor. We executed an incomplete microsurgery for dumbbell shape lesion in left auditory nerve distribution area and the fourth ventricle for differential diagnosis and facilitating further treatment. OUTCOMES: The patient did not recover well postoperatively and suffered from severe pulmonary infection. Refusing further intervention in view of poor prognosis of ATRT, the patient was transferred to another hospital for rehabilitation care. The patient died from progressive tumor and respiratory failure after 2 months. LESSONS: The diagnosis of ATRT can be challenging, in our case due to the disturbance of bilateral auditory nerve distribution area tumors. Under MRI, Irregular frontier, obvious mutual high and low signal on T2-weighted image, growing along cerebrospinal fluid pathway, and heterogeneous contrast enhancement should lead the clinician to strongly consider ATRT.

TLC-electrostatic field induced spray ionization-MS analysis of diverse structural skeletons and its coupling with TLC bioautography for characterization of lipase inhibitory components in American ginseng.

Natural compounds with diverse structural skeletons have different ionization efficiencies and different mass spectrometry (MS) responses. Some key factors influencing the electrostatic field induced spray ionization (EFISI)-MS for a variety of natural compounds have been optimized and improved. Fifteen reference substances representing ten well-known skeletons of natural products including alkaloids, flavonoids, phenolic acids, lignans, coumarins, anthraquinones, monoterpenoids, sesquiterpenoids, diterpenoids and triterpenoids, were selected and investigated for their EFISI-MSn responses on TLC plates using a dot-blot test. The optimized ionization conditions for these compounds in the positive ion mode were achieved, together with their limits of detection. In addition, to avoid the limitation of some compounds being difficultly ionized in the positive ion mode, the negative ion mode of the TLC-EFISI-MS method was developed and optimized for the first time. By coupling with a TLC bioautographic assay, nine lipase inhibitory components in American ginseng (Panax quinquefolium roots) have been successfully identified/ tentatively identified in situ by their EFISI-MSn data and further confirmed by comparisons of their Rf values and MSn data with those of reference substances. These lipase inhibitory compounds were 24(S)-pseudo-ginsenoside F11, ginsenosides Rg1, Re, XVII, Rc, Rb2/Rb3, Rb1, Ro and malonyl-ginsenoside Rb1. This is the first report that the TLC-EFISI-MSn method is adapted to a broad-spectrum analysis of structural skeletons present in herbal medicines.

Aspergilolide, a steroid lactone produced by an endophytic fungus Aspergillus sp. MBL1612 isolated from Paeonia ostii.

A new steroid lactone aspergilolide (1), and nine known compounds helvolic acid (2), verruculogen (3), tryprostatin B (4), 13-oxofumitremorgin B (5), fumitremorgin C (6), demethoxy fumitremorgin C (7), terezine D (8), aszonalenin (9), 12, 13-dihydroxy-fumitremorgin C (10) from cultures of the endophytic fungus Aspergillus sp. MBL1612. Their chemical structures were determined by a series of extensive spectroscopic methods. All of the compounds were isolated from this genus for the first time. The cytotoxicity against five human cancer cell lines of new compound were detected.

18F-fluorodeoxyglucose positron emission computed tomography for monitoring tumor response in esophageal carcinoma treated with concurrent chemoradiotherapy.

The aim of the present study was to explore the value of 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) in monitoring the early tumor response of esophageal squamous cell carcinoma (ESCC) treated with concurrent chemoradiotherapy (CRT). A total of 48 patients with pathologically proven ESCC were retrospectively analyzed. All patients underwent two serial 18F-FDG PET scans at baseline (pre-CRT) and 40 Gy/4 weeks of starting radiation therapy (inter-CRT). All patients received intensity-modulated radiotherapy (with a total radiation dose of 59.6 Gy) concurrently with cisplatin-based chemotherapy. The maximum standardized uptake value (SUVmax) and metabolic tumor volume (MTV) were measured using 18F-FDG PET. The percentage changes (Δ) in SUVmax and MTV between two serial scans were calculated and were revealed to be associated with the objective tumor response (oTR), according to the Response Evaluation Criteria in Solid Tumors 1.1. Among the 48 patients, 20.8% achieved a complete response, 68.8% exhibited a partial response and the oTR rate was 89.6%. On the pre-CRT PET scans, the mean SUVmax and MTV were 14.1±5.8 and 58.2±25.4 cm3, respectively. Following 40 Gy irradiation over 4 weeks, the mean SUVmax and MTV significantly decreased to 4.3±3.5 and 19.0±12.1 cm3, respectively (P<0.001). A significantly higher ΔSUVmax and ΔMTV was observed in the responders compared with that in the non-responders [0.71±0.16 vs. 0.51±0.26 (P=0.015); and 0.64±0.13 vs. 0.42±0.09 (P=0.001), respectively]. Univariate analysis revealed that ΔSUVmax and ΔMTV were significantly associated with oTR (P=0.010 and P=0.001, respectively). ΔMTV was used as a predictor and a cut-off value of 54% discriminated responders from non-responders with a sensitivity of 69.8% and a specificity of 100% (P=0.001). The area under the receiver operating characteristic curve was 0.837 (95% confidence interval, 0.702-0.928). The results of the present study indicated that interim 18F-FDG PET scans may provide early prognostic value for determining oTR in patients with ESCC undergoing treatment with CRT.