Discovery of novel biphenyl derivatives as androgen receptor degraders for the treatment of enzalutamide-resistant prostate cancer.

Second-generation AR antagonists, such as enzalutamide, are the primary therapeutic agents for advanced prostate cancer. However, the development of both primary and secondary drug resistance leads to treatment failures and patient mortality. Bifunctional agents that simultaneously antagonize and degrade AR block the AR signaling pathway more completely and exhibit excellent antiproliferative activity against wild-type and drug-resistant prostate cancer cells. Here, we reported the discovery and optimization of a series of biphenyl derivatives as androgen receptor antagonists and degraders. These biphenyl derivatives exhibited potent antiproliferative activity against LNCaP and 22Rv1 cells. Our discoveries enrich the diversity of small molecule AR degraders and offer insights for the development of novel AR degraders for the treatment of enzalutamide-resistant prostate cancer.

De novo transcriptome assembly and molecular response mechanism analysis of a diatom Cyclotella meneghiniana Kützing exposed to cadmium.

Cadmium is a persistent heavy metal commonly found in aquatic ecosystems and has a strong toxic effect on organisms. The sensitivity of phytoplankton to environmental changes and its role as an indicator of aquatic ecosystem health have been well-established. However, the mechanisms by which phytoplankton respond to cadmium remain incompletely understood. In this study, we chose the typical planktonic diatom Cyclotella meneghiniana Kützing, by integrating physiological-biochemical data and transcriptome analysis, to reveal the molecular mechanisms of C. meneghiniana responing to cadmium. Under cadmium stress, the cell density and chlorophyll-a content of C. meneghiniana significantly decreased, while MDA content and SOD activity gradually increased. At 72 h of cadmium stress, we found that at this time point, cell abundance and physiological variation were very significant, therefore we selected 72 h for subsequent analysis. To better understand the cadmium stress response mechanisms of C. meneghiniana, a de novo transcriptome method was used to analyse C. meneghiniana under cadmium stress for 72 h, and 1704 (M vs. CK) and 4788 (H vs. CK) differentially expressed genes were found. Our results showed that the changes in gene expression were closely correlated to the physiological-biochemical changes. Although cadmium stress could promote the nitrogen metabolism pathway, ROS scavenging system, and photosynthesis. While, C. meneghiniana under medium and high concentrations of cadmium can also limit various intracellular metabolic pathways, such as the MAPK pathway and phosphatidylinositol metabolic pathway, and the degree of inhibition increases with the increase of stress concentration. In present study, the complete molecular mechanism of the planktonic diatom response to cadmium has been established, which provided important information for further studies on heavy metal pollutants and the multiple functional genes responsible for cadmium sensitivity and tolerance in planktonic diatoms.

Biomedical Applications of Sulfonylcalix[4]arene-Based Metal-Organic Supercontainers.

Coordination cages sustained by metal-ligand interactions feature polyhedral architectures and well-defined hollow structures, which have attracted significant attention in recent years due to a variety of structure-guided promising applications. Sulfonylcalix[4]arenes-based coordination cages, termed metal-organic supercontainers (MOSCs), that possess unique multi-pore architectures containing an endo cavity and multiple exo cavities, are emerging as a new family of coordination cages. The well-defined built-in multiple binding domains of MOSCs allow the efficient encapsulation of guest molecules, especially for drug delivery. Here, we critically discuss the design strategy, and, most importantly, the recent advances in research surrounding cavity-specified host-guest chemistry and biomedical applications of MOSCs.

Elucidating Flavonoid and Antioxidant Activity in Edible and Medicinal Herbs Woodwardia japonica (L.f.) Sm. Based on HPLC-ESI-TOF-MS and Artificial Neural Network Model: Response to Climatic Factors.

Woodwardia japonica is a kind of great potential edible and medicinal fern. In a previous study, it was found that flavonoid and antioxidant activity of W. japonica from different sites were different. However, the cause of the differences has still been unclear, which has restricted the utilization of W. japonica. In this paper, flavonoid and antioxidant activity of W. japonica from nine different regions were determined with the method of a colorimetric assay with UV-VIS spectrophotometry and HPLC-ESI-TOF-MS, and the effects of climate factors on flavonoids and antioxidant activities were evaluated by mathematical modeling and statistical methods. The results showed: (1) total flavonoid content (TFC) of W. japonica from Wuyi Mountain (Jiangxi) was the highest, which might be related to the low temperature; (2) the differences of antioxidant activities of W. japonica might be related to precipitation; (3) five flavonols, two flavones and one isoflavone were tentatively identified in W. japonica; (4) flavonol and isoflavone might be affected by sunshine duration, and flavones were probably related to temperature. In conclusion, the effects of climate factors on flavonoids and antioxidants are significant, which would provide an important basis for further exploring the mechanism of climate affecting secondary metabolites.

Comparison of Constituents and Antioxidant Activity of Above-Ground and Underground Parts of Dryopteris crassirhizoma Nakai Based on HS-SPME-GC-MS and UPLC/Q-TOF-MS.

Dryopteris crassirhizoma Nakai is a Chinese traditional medicinal fern plant for heat-clearing and detoxifying, promoting blood circulation and dissipating blood stasis. Previous researches showed that many factors could influence the components of medicinal plants, and the plant part is one of the main factors. So far, only the underground part of D. crassirhizoma, called "Mianma Guanzhong", has been widely sold in the market. However, the above-ground part was usually at low utilization, resulting in a waste of medicinal resources. In order to further develop and utilize the medicinal resources of D. crassirhizoma, the constituents, total flavonoid contents and antioxidant activity of the above-ground and underground parts of D. crassirhizoma were tentatively analyzed and compared based on HS-SPME-GC-MS and UPLC/Q-TOF-MS. The results showed that (1) the volatile components were mainly focused in the above-ground part of D. crassirhizoma, including 3-carene, isoledene, ionene, 4-amino-1-naphthol and furfural. (2) Nonvolatile components of the underground part of D. crassirhizoma contained phenolic acid, flavonoids, phloroglucinol and less fatty acid. (3) The common compounds of the above-ground and underground parts of D. crassirhizoma were phenolic acid and flavaspidic acid AB. (4) Antioxidant activity of the underground part was stronger than that of the above-ground part of D. crassirhizoma. In conclusion, both the above-ground and underground parts of D. crassirhizoma are important medicinal resources worthy of further development.

Testing for Serial Correlation in Autoregressive Exogenous Models with Possible GARCH Errors.

Autoregressive exogenous, hereafter ARX, models are widely adopted in time series-related domains as they can be regarded as the combination of an autoregressive process and a predictive regression. Within a more complex structure, extant diagnostic checking methods face difficulties in remaining validity in many conditions existing in real applications, such as heteroscedasticity and error correlations exhibited between the ARX model itself and its exogenous processes. For these reasons, we propose a new serial correlation test method based on the profile empirical likelihood. Simulation results, as well as two real data examples, show that our method has a good performance in all mentioned conditions.

Testing the Intercept of a Balanced Predictive Regression Model.

Testing predictability is known to be an important issue for the balanced predictive regression model. Some unified testing statistics of desirable properties have been proposed, though their validity depends on a predefined assumption regarding whether or not an intercept term nevertheless exists. In fact, most financial data have endogenous or heteroscedasticity structure, and the existing intercept term test does not perform well in these cases. In this paper, we consider the testing for the intercept of the balanced predictive regression model. An empirical likelihood based testing statistic is developed, and its limit distribution is also derived under some mild conditions. We also provide some simulations and a real application to illustrate its merits in terms of both size and power properties.

Vitronectin: a promising breast cancer serum biomarker for early diagnosis of breast cancer in patients.

Breast cancer is the most common cancer in women worldwide, identification of new biomarkers for early diagnosis and detection will improve the clinical outcome of breast cancer patients. In the present study, we determined serum levels of vitronectin (VN) in 93 breast cancer patients, 30 benign breast lesions, 9 precancerous lesions, and 30 healthy individuals by enzyme-linked immunosorbent assays. Serum VN level was significantly higher in patients with stage 0-I primary breast cancer than in healthy individuals, patients with benign breast lesion or precancerous lesions, as well as those with breast cancer of higher stages. Serum VN level was significantly and negatively correlated with tumor size, lymph node status, and clinical stage (p < 0.05 in all cases). In addition, VN displayed higher area under curve (AUC) value (0.73, 95 % confidence interval (CI) [0.62-0.84]) than carcinoembryonic antigen (CEA) (0.64, 95 % CI [0.52-0.77]) and cancer antigen 15-3 (CA 15-3) (0.69, 95 % CI [0.58-0.81]) when used to distinguish stage 0-I cancer and normal control. Importantly, the combined use of three biomarkers yielded an improvement in receiver operating characteristic curve with an AUC of 0.83, 95 % CI [0.74-0.92]. Taken together, our current study showed for the first time that serum VN is a promising biomarker for early diagnosis of breast cancer when combined with CEA and CA15-3.

Non-invasive detection of hepatocellular carcinoma serum metabolic profile through surface-enhanced Raman spectroscopy.

The present study aims to identify distinctive Raman spectrum metabolic peaks to predict hepatocellular carcinoma (HCC). We performed a label-free, non-invasive surface-enhanced Raman spectroscopy (SERS) test on 230 serum samples including 47 HCC, 60 normal controls (NC), 68 breast cancer (BC) and 55 lung cancer (LC) by mixing Au@AgNRs with serum directly. Based on the observed SERS spectra, discriminative metabolites including tryptophan, phenylalanine, and etc. were found in HCC, when compared with BC, LC, and NC (P<0.05 in all). Common metabolites-proline, valine, adenine and thymine were found in HCC, BC and LC with compared to NC group (P<0.05). Importantly, Raman spectra of HCC serum biomarker AFP were firstly detected to analyze the HCC prominent peak. Orthogonal partial least squares discriminant analysis was adopted to assess the diagnostic accuracy; area under curve value of HCC is 0.991. This study provides new insights into the HCC metabolites detection through Raman spectroscopy.

Testing serial correlation in a general d-factor model with possible infinite variance.

It is well-known that the presence of serial correlation may result in an inefficient or even biased estimation in time series analysis. In this paper, we consider testing serial correlation in a general d-factor model when the model errors follow the GARCH process, which is frequently used in modeling financial data. Two empirical likelihood-based testing statistics are suggested as a way to deal with problems that might come up with infinite variance. Both statistics are shown to be chi-squared distributed asymptotically under mild conditions. Simulations confirm the excellent finite-sample performance of both tests. Finally, to emphasize the importance of using our tests, we explore the impact of the exchange rate on the stock return using both monthly and daily data from eight countries.

Transcriptome analysis of the effects of different carbon dioxide concentrations on paramylon accumulation in Euglena gracilis Z.

Appropriate concentration of carbon dioxide (CO2) will promote algae growth and metabolism. Building upon this finding, the present study investigated the impact of different CO2 concentrations (5% and 20%) on the carbon sequestration capacity of E. gracilis through aeration culturing, employing a combination of physiological analyses and transcriptome analysis. The results demonstrated that under 5% CO2 concentration, the cell density of E. gracilis was 1.79 times higher than that achieved in an air culture condition, and the paramylon content of E. gracilis was found to be 6.18 times higher than that of the air group. Based on transcriptome analysis, the carbon metabolism of E. gracilis was discussed. Significant up-regulation expression of genes associated with carbon synthesis was validated by an increase in paramylon content. This study revealed that under 5% CO2 conditions, E. gracilis exhibited elevated growth rate and enhanced photosynthetic carbon assimilation efficiency.

Transcriptomic response analysis of ultraviolet mutagenesis combined with high carbon acclimation to promote photosynthetic carbon assimilation in Euglena gracilis.

The potential of Euglena gracilis for carbon sequestration offers significant opportunities in the capture and utilization of carbon dioxide (CO2). In this study, a mutant LE-ZW of E. gracilis, capable of efficient growth and carbon sequestration, was obtained through ultraviolet mutagenesis combined with high carbon acclimation. Subsequently, the potential of LE-ZW for carbon assimilation was systematically analyzed. The results demonstrated that the cell density of the LE-ZW was 1.33 times that of the wild type and its carbon sequestration efficiency was 6.67 times that of the wild type when cultured at an optimal CO2 concentration of 5% until day 10. At this time, most key enzyme genes associated with the photosystem membrane protein complex, photosynthetic electron transport chain, antenna protein, and carbon fixation were up-regulated in mutant LE-ZW. Furthermore, after 10 days of culture under 10% CO2, the cell density and carbon sequestration efficiency of LE-ZW reached 1.10 times and 1.54 times of that under 5% CO2, respectively. Transcriptome analysis revealed significant up-regulation of key enzyme genes associated with carbon fixation, central carbon metabolism, and photosynthesis in LE-ZW under a 10% CO2 concentration. Physiological indices such as the amount of oxygen evolution, the values of Fv/Fm, the expression levels of photosynthetic protein genes and the enzyme activity of key enzymes related to photosynthetic carbon assimilation were corroborated by transcriptome data, elucidating that the mutant LE-ZW exhibited augmented photosynthetic carbon sequestration capacity and metabolic activity, thereby demonstrating robust adaptability to a high-carbon environment. This research contributes to a deeper understanding of the carbon assimilation mechanism in photosynthetic protists under elevated CO2 concentrations.

Survival prediction in diffuse large B-cell lymphoma patients: multimodal PET/CT deep features radiomic model utilizing automated machine learning.

PURPOSE: We sought to develop an effective combined model for predicting the survival of patients with diffuse large B-cell lymphoma (DLBCL) based on the multimodal PET-CT deep features radiomics signature (DFR-signature). METHODS: 369 DLBCL patients from two medical centers were included in this study. Their PET and CT images were fused to construct the multimodal PET-CT images using a deep learning fusion network. Then the deep features were extracted from those fused PET-CT images, and the DFR-signature was constructed through an Automated machine learning (AutoML) model. Combined with clinical indexes from the Cox regression analysis, we constructed a combined model to predict the progression-free survival (PFS) and the overall survival (OS) of patients. In addition, the combined model was evaluated in the concordance index (C-index) and the time-dependent area under the ROC curve (tdAUC). RESULTS: A total of 1000 deep features were extracted to build a DFR-signature. Besides the DFR-signature, the combined model integrating metabolic and clinical factors performed best in terms of PFS and OS. For PFS, the C-indices are 0.784 and 0.739 in the training cohort and internal validation cohort, respectively. For OS, the C-indices are 0.831 and 0.782 in the training cohort and internal validation cohort. CONCLUSIONS: DFR-signature constructed from multimodal images improved the classification accuracy of prognosis for DLBCL patients. Moreover, the constructed DFR-signature combined with NCCN-IPI exhibited excellent potential for risk stratification of DLBCL patients.

Multiple stressors determine the process of the benthic diatom community assembly and network stability in urban water bodies in Harbin.

Human activities have triggered biodiversity loss, often resulting in biotic homogenization, which poses a threat to human well-being. Nevertheless, the overall influence of diverse environmental stressors on intra- and inter-community diversity remains insufficiently elucidated. This study aimed to quantify and reveal the impact of environmental stressors on the alpha and beta diversities of benthic diatom communities in the Harbin urban river network during the summer and autumn of 2022 and spring of 2023. The marked seasonal variations observed in alpha and beta diversity indices highlighted the distinct community compositions. Nonetheless, varying types of urban water pollutants were the primary drivers of biotic homogenization in terms of both taxonomic and functional diversities and played a prominent role in steering diversity shifts. These pollutants indirectly led to biotic homogenization by altering water quality parameters and affecting the ecological dynamics of benthic diatom communities. Furthermore, diverse responses to stressors were identified in taxonomic and functional diversities, providing additional insights for understanding ecological shifts in communities. Taxonomic beta diversity was related to environmental filtering, whereas functional beta diversity resulted from stressor-spatial dimension interactions. Our study emphasises that relying solely on traditional water quality monitoring may not fully reveal the current state of river ecosystem protection, and the need to study the continuous changes in biodiversity across seasons in urban waterbodies from the perspective of various stressors is highlighted.

Overexpression of histone demethylase gene SlJMJ18 and SlJMJ23 from tomato confers cadmium tolerance by regulating metal transport and hormone content in Arabidopsis.

A lower concentration of cadmium (Cd), a hazardous and non-essential element for plant growth, will have deleterious effects on plants and endanger human health. Histone demethylase (JHDM) is important for plants' ability to withstand abiotic stress, according to an increasing number of studies. The degree of expression of the SlJMJ18 and SlJMJ23 genes in different tomato tissues was confirmed by this study. These two genes were responsive to the heavy metals Cd, Hg, Pb, and Cu stress, according to fluorescence quantification and GUS staining. Interestingly, the overexpression transgenic Arabidopsis plants of two genes have different responses to Cd stress. While SlJMJ18-OE lines consistently display Cd resistance but an early-flowering phenotype, SlJMJ23-OE plants have sensitivity during the post-germination stage and then greater tolerance to Cd stress. It was discovered that these two genes may affect cadmium tolerance of plants by regulating the expression of hormone synthesis related genes and hormone contents (BRs and ABA). Moreover, SlJMJ23 may resist cadmium stress by increasing the total phenol content in plants. The functional significance of JMJs is better understood in this study, which also offers a theoretical foundation for the use of molecular technology to develop plants resistant to Cd and an experimental basis for the efficient use of land resources.

Differential protein analysis of saline-alkali promoting the oil accumulation in Nitzschia palea.

BACKGROUND: The increasingly severe salinization of the aquatic environment has led to serious damage to the habitats of aquatic organisms. Benthic diatoms are commonly employed as indicator species for assessing water quality and serve as a reflection of the overall health of the aquatic ecosystem. Nitzschia palea is a common diatom found in freshwater, with high oil content, rapid reproductive rate, and it is a commonly dominant species in various rivers. RESULTS: The results showed that after 4 days (d) of saline-alkali stress, the cell density and chlorophyll a content of Nitzschia palea reached their maximum values. Therefore, we selected Nitzschia palea under 4 d stress for Tandem Mass Tag (TMT) quantitative proteomic analysis to explore the molecular adaptation mechanism of freshwater diatoms under saline-alkali stress. Totally, 854 proteins were enriched, of which 439 differentially expressed proteins were identified. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and subcellular fractionation analysis revealed that these proteins were mainly enriched in the photosynthesis pathway, citric acid cycle (TCA cycle), fatty acid synthesis, and glutathione cycle. CONCLUSIONS: This study aims to reveal the physiological, biochemical and proteomic mechanisms of salt and alkali tolerance and molecular adaptation of Nitzschia palea under different saline-alkali concentrations. This study showed that Nitzschia palea is one candidate of the environmental friendly, renewable bioenergy microalgae. Meantime, Nitzschia palea reveals for the proteome of the freshwater and provides the basis, it became a model algal species for freshwater diatoms.

A new species of genus Crenotia (Bacillariophyta) from Tibet, China.

During the investigation of the freshwater diatoms from Tibet, a monoraphid species was observed from a hot spring near Anduo County, located on a plateau in the central portion of Tibet. This species shares the diagnostic features of Crenotia, such as the valve bent along the transapical axis, striae uniseriate to biseriate from centre to the apices and areolae with special structures located at the end of each stria. We compared the morphological characters of this new species with the others in this genus and show it to be new; it is named Crenotiatibetiasp. nov. This species has small valves with slightly protracted ends with nearly capitate apices, lanceolate axial area, central area unilaterally expanded to the margin, striae uniseriate to biseriate, but, in some valves, the striae are only uniseriate. Areolae are round small to irregular in shape and, at the end of each stria, there is a horseshoe-shaped areola present. Observations of developing valves show all the striae begin biseriate, then they become covered by silica to form uniseriate striae. Comparisons are made amongst the species in this genus and with genera assigned to the Achnanthidiaceae.

Discovery of (2S)-N-(6-Cyano-5-(trifluoromethyl)pyridin-3-yl)-3-(6-(4-cyanophenyl)-3,6-diazabicyclo[3.1.1]heptan-3-yl)-2-hydroxy-2-methylpropanamide as a Highly Potent and Selective Topical Androgen Receptor Antagonist for Androgenetic Alopecia Treatment.

Androgenetic alopecia (AGA) is the most prevalent form of progressive hair loss disorder in both men and women, significantly impacting their appearance and overall quality of life. Overactivation of the AR signaling pathway in dermal papilla cells (DPCs) plays a crucial role in the development and progression of AGA. Considering the severe systemic side effects associated with oral AR antagonists, the idea of developing of topical AR antagonists with rapid metabolic deactivation properties emerged as a promising approach. Herein, through systematic structural optimization, we successfully identified compound 30a as a potent and selective AR antagonist with favorable pharmacokinetic properties, resulting in high skin exposure and low plasma exposure following topical administration. Importantly, in both hair-growth and AGA mouse models, compound 30a showed potent hair-growth-promoting effects without any noticeable toxicity. These findings suggest that compound 30a holds significant potential as a topical AR antagonist for treating AGA patients.

Video sensor-based complex scene analysis with Granger causality.

In this report, we propose a novel framework to explore the activity interactions and temporal dependencies between activities in complex video surveillance scenes. Under our framework, a low-level codebook is generated by an adaptive quantization with respect to the activeness criterion. The Hierarchical Dirichlet Processes (HDP) model is then applied to automatically cluster low-level features into atomic activities. Afterwards, the dynamic behaviors of the activities are represented as a multivariate point-process. The pair-wise relationships between activities are explicitly captured by the non-parametric Granger causality analysis, from which the activity interactions and temporal dependencies are discovered. Then, each video clip is labeled by one of the activity interactions. The results of the real-world traffic datasets show that the proposed method can achieve a high quality classification performance. Compared with traditional K-means clustering, a maximum improvement of 19.19% is achieved by using the proposed causal grouping method.

Impact of Radiation Dose to Circulating Immune Cells on Tumor Control and Survival in Esophageal Cancer.

Background: The immune system is well known to exert tumor immunosurveillance effects, and that immune cells circulating in the peripheral blood affect tumor prognosis. The study investigated the effect of estimated dose of radiation on circulating immune cells (EDRIC) and tumor control for esophageal cancer patients treated with concurrent chemo-radiotherapy. Materials and Methods: A total of 146 esophageal cancer patients treated with radiotherapy between January 2016 and June 2020 were retrospectively identified. We determined EDRIC, known prognostic factors, and the association of these factors with progression-free survival (PFS) and overall survival (OS). Results: The median follow-up was 17.9 months (2.7-60.4 months). The 3-year OS was 39.2%. Severe post-treatment lymphopenia was observed in 84.2% of patients. A negative correlation between EDRIC and absolute lymphocyte count was found (r = -0.679; p < 0.001). Patients with EDRIC ≥10.3 Gy were more likely to demonstrate grade 4 lymphopenia (55.2% vs. 4.5%; p < 0.001). Patients with grade 4 lymphopenia had a worse OS and PFS. On multivariate analysis, EDRIC was independently associated with OS (hazard ratio [HR], 1.142; p = 0.016) and PFS (HR, 1.121; p = 0.019). Conclusions: EDRIC can predict lymphocyte reduction and poor prognosis for esophageal cancer patients treated with radiotherapy.