The relationship between the psychological resilience and post-traumatic growth of college students during the COVID-19 pandemic: a model of conditioned processes mediated by negative emotions and moderated by deliberate rumination.

BACKGROUND: The mental health of university students during the COVID-19 pandemic has attracted the attention of researchers. For the present study researchers constructed a mediation model to explore the relationship between psychological resilience and post-traumatic growth, the mediating role of negative emotions and the moderating role of deliberate rumination in students. METHODS: The Psychological Resilience Scale, Posttraumatic Growth Inventory, Depression-Anxiety-Stress Scale (DASS-21) and Event Related Rumination Inventory were used in a survey of 881 college students. The data were analyzed using SPSS 26.0 and the PROCESS plugin (version 3.3). RESULTS: (1) Psychological resilience is positively related with post-traumatic growth. Deliberate rumination is positively related to psychological resilience, posttraumatic growth, and negative emotions. Psychological resilience, post-traumatic growth and negative emotions are negatively related. (2) Negative emotions mediated the relationship between psychological resilience and post-traumatic growth. (3) Deliberate rumination plays a moderating role in psychological resilience affecting negative emotions. Deliberate rumination plays a moderating role in the extent to which psychological resilience influences PTG through negative emotions. CONCLUSIONS: Psychological resilience affects post-traumatic growth directly and also indirectly through negative emotions. With the increase of mental resilience, the level of negative emotion tended to decrease. When individuals are experiencing negative emotions, high levels of active rumination are more likely to promote post-traumatic growth. This study helps to explore the factors affecting the mental health of college students during the epidemic, thus providing guidance for appropriate mental health interventions.

COATi: statistical pairwise alignment of protein-coding sequences.

Sequence alignment is an essential method in bioinformatics and the basis of many analyses, including phylogenetic inference, ancestral sequence reconstruction, and gene annotation. Sequencing artifacts and errors made during genome assembly, such as abiological frameshifts and incorrect early stop codons, can impact downstream analyses leading to erroneous conclusions in comparative and functional genomic studies. More significantly, while indels can occur both within and between codons in natural sequences, most amino-acid- and codon-based aligners assume that indels only occur between codons. This mismatch between biology and alignment algorithms produces suboptimal alignments and errors in downstream analyses. To address these issues, we present COATi, a statistical, codon-aware pairwise aligner that supports complex insertion-deletion models and can handle artifacts present in genomic data. COATi allows users to reduce the amount of discarded data while generating more accurate sequence alignments. COATi can infer indels both within and between codons, leading to improved sequence alignments. We applied COATi to a dataset containing orthologous protein-coding sequences from humans and gorillas and conclude that 41% of indels occurred between codons, agreeing with previous work in other species. We also applied COATi to semi-empirical benchmark alignments and find that it outperforms several popular alignment programs on several measures of alignment quality and accuracy.

Halloysite-derived mesoporous silica with high ionic conductivity improves Li-S battery performance.

The slow Li+ transport rate in the thick sulfur cathode of the Li-S battery affects its capacity and cycling performance. Herein, Fe-doped highly ordered mesoporous silica material (Fe-HSBA-15) as a sulfur carrier of the Li-S battery shows high ion conductivity (1.10 mS cm-1) and Li+ transference number (0.77). The Fe-HSBA-15/S cell has an initial capacity of up to 1216.7 mA h g-1 at 0.2C and good stability. Impressively, at a high sulfur load of 4.34 mg cm-2, the Fe-HSBA-15/S cell still maintains an area specific capacity of 4.47 mA h cm-2 after 100 cycles. This is because Fe-HSBA-15 improves the Li+ diffusion behavior through the ordered mesoporous structure. Theoretical calculations also confirmed that the doping of iron enhances the adsorption of polysulfides, reduces the band gap and makes the catalytic activity stronger.

Post-COVID-19 Fetal Cardiac Morphology and Systolic Evaluation in Infected Pregnant Women by Fetal Heart Quantification Technology.

OBJECTIVES: Due to the government's liberalization of epidemic control, the current 2019 novel coronavirus disease (COVID-19) has started to spread widely within China. This study aimed to use the fetal heart quantification (fetal HQ) technique to assess the cardiac function and morphology of the fetuses of pregnant women diagnosed with COVID-19 in the early stages of pregnancy. METHODS: Exactly 86 pregnant women diagnosed with COVID-19 infection in early pregnancy (COVID-19 group) and 90 healthy pregnant women (control group) who underwent fetal echocardiography were prospectively included in this study. The fetal HQ technique was applied to compare the differences in the global sphericity index (GSI), global strain values (GS), fractional area change (FAC), and 24-segment fractional shortening (FS) of the left and right ventricles, between the COVID-19 group and the control group. RESULTS: Compared with the control group, the differences in GS and 24-segment FS of the left ventricle in the COVID-19 group were not statistically significant. However, the COVID-19 group showed lower GSI values compared with the control group (1.24 vs 1.28). FAC (48.12%) of the left ventricle and GS (-23.55%), FAC (41.74%) of the right ventricle in the COVID-19 group were reduced compared with FAC (50.50%) of the left ventricle and GS (-27.63%), FAC (46.01%) of the right ventricle in the control group. Segmental analysis revealed reduced FS in segments 20-24 in the COVID-19 group compared with the control group. Right ventricular GS was an independent predictor of adverse pregnancy outcome with an optimal cutoff value of -18.66%. CONCLUSIONS: The results suggest that COVID-19 infection in early pregnancy may have a negative impact on fetal cardiac morphology and function. Fetal HQ may offer a new assessment method for the early identification of fetal cardiac alterations in pregnant women infected with COVID-19.

Rethinking automatic segmentation of gross target volume from a decoupling perspective.

Accurate and reliable segmentation of Gross Target Volume (GTV) is critical in cancer Radiation Therapy (RT) planning, but manual delineation is time-consuming and subject to inter-observer variations. Recently, deep learning methods have achieved remarkable success in medical image segmentation. However, due to the low image contrast and extreme pixel imbalance between GTV and adjacent tissues, most existing methods usually obtained limited performance on automatic GTV segmentation. In this paper, we propose a Heterogeneous Cascade Framework (HCF) from a decoupling perspective, which decomposes the GTV segmentation into independent recognition and segmentation subtasks. The former aims to screen out the abnormal slices containing GTV, while the latter performs pixel-wise segmentation of these slices. With the decoupled two-stage framework, we can efficiently filter normal slices to reduce false positives. To further improve the segmentation performance, we design a multi-level Spatial Alignment Network (SANet) based on the feature pyramid structure, which introduces a spatial alignment module into the decoder to compensate for the information loss caused by downsampling. Moreover, we propose a Combined Regularization (CR) loss and Balance-Sampling Strategy (BSS) to alleviate the pixel imbalance problem and improve network convergence. Extensive experiments on two public datasets of StructSeg2019 challenge demonstrate that our method outperforms state-of-the-art methods, especially with significant advantages in reducing false positives and accurately segmenting small objects. The code is available at https://github.com/shijun18/GTV_AutoSeg.

Chronic hypoxia stabilizes 3ßHSD1 via autophagy suppression.

Progression of prostate cancer depends on androgen receptor, which is usually activated by androgens. Therefore, a mainstay treatment is androgen deprivation therapy. Unfortunately, despite initial treatment response, resistance nearly always develops, and disease progresses to castration-resistant prostate cancer (CRPC), which remains driven by non-gonadal androgens synthesized in prostate cancer tissues. 3ß-Hydroxysteroid dehydrogenase/Δ5-->4 isomerase 1 (3ßHSD1) catalyzes the rate-limiting step in androgen synthesis. However, how 3ßHSD1, especially the "adrenal-permissive" 3ßHSD1(367T) that permits tumor synthesis of androgen from dehydroepiandrosterone (DHEA), is regulated at the protein level is not well understood. Here, we investigate how hypoxia regulates 3ßHSD1(367T) protein levels. Our results show that, in vitro, hypoxia stabilizes 3ßHSD1 protein by suppressing autophagy. Autophagy inhibition promotes 3ßHSD1-dependent tumor progression. Hypoxia represses transcription of autophagy-related (ATG) genes by decreasing histone acetylation. Inhibiting deacetylase (HDAC) restores ATG gene transcription under hypoxia. Therefore, HDAC inhibition may be a therapeutic target for hypoxic tumor cells.

Exploring the molecular mechanism of Yinao Fujian formula on ischemic stroke based on network pharmacology and experimental verification.

Background: Ischemic stroke (IS) is a leading cause of long-term disability and even mortality, threatening people's lives. Yinao Fujian (YNFJ) formula is a Traditional Chinese Medicine formula that has been widely used to treat patients with IS. However, the molecular mechanism of YNFJ for the treatment of IS is still elusive. Our study aimed to explore the potential protective effect and the underlying mechanisms of YNFJ on IS using a network pharmacology approach coupled with experimental validation. Materials and methods: Effective compounds of YNFJ were collected from BATMAN-TCM and TCMSP databases, while IS targets were obtained from GeneCards, OMIM, TTD and DrugBank databases. The protein-protein interaction (PPI) network was constructed to further screen the hub targets of YNFJ in IS treatment. GO and KEGG enrichment analyses were used to identify the critical biological processes and signaling pathways of YNFJ for IS. Moreover, Nissl staining, HE, TTC staining and Tunel staining were used in the MCAO model to prove the neuroprotective effect of YNFJ. Oxidative damage, inflammatory factor release and related pathways were tested in MCAO rat model and hypoxia-induced BV2 cell model, respectively. Results: We found that YNFJ treatment significantly alleviated MCAO-induced nerve damage and apoptosis. Then, network pharmacology screening combined with literature research revealed IL6, TNF, PTGS2, NFKBIA and NFE2L2 as the critical targets in a PPI network. Moreover, the top 20 signaling pathways and biological processes associated with the protective effects of YNFJ on IS were enriched through GO and KEGG analyses. Further analysis indicated that NF-κB and Nrf2/HO-1 signaling pathways might be highly involved in the protective effects of YNFJ on IS. Finally, in vitro and in vivo experiments confirmed that YNFJ inhibited the release of inflammatory factors (IL-6 and TNF-α) and MDA content, and increased the activity of SOD. In terms of the mechanism, YNFJ inhibited the release of inflammatory factors by suppressing the NF-κB pathway and decreased the expression of iNOS and COX-2 to protect microglia from inflammation damage. In addition, YNFJ initiated the dissociation of Keap-1 and Nrf2, and activated the downstream protein HO-1, NQO1, thus decreasing oxidative stress. Conclusion: Taken together, the findings in our research showed that the protective effects of YNFJ on IS were mainly achieved by regulating the NF-κB and Nrf2/HO-1 signaling pathways to inhibit oxidative stress damage and inflammatory damage of microglia.

Inhibition of hepatocellular carcinoma growth via modulation of the miR-221/SOX11 axis by curcumin and berberine.

Hepatocellular carcinoma (HCC) is a fatal malignancy that has limited treatment options. This study focused on the potential therapeutic effects of curcumin (CUR) and berberine (BBR) on the miR-221/SRY-box transcription factor 11 (SOX11) axis in HCC. We investigated the combined effects of CUR and BBR on HEPG2 and Huh7 cell survival and miR-221 expression using Cell Counting Kit-8 assays and RT-qPCR, respectively. Western blotting was used to detect changes in the apoptosis-related caspase-3/9 protein levels. We performed bioinformatics analysis and dual-luciferase assays and measured apoptotic protein levels to assess the role of the miR-221/SOX11 axis in mediating the effects of CUR-BBR. Both CUR and BBR suppressed HCC cell growth in a dose-dependent manner, with the most potent combined effect observed at a 2:1 ratio. CUR-BBR treatment significantly downregulated miR-221 expression, and miR-221 overexpression partially reversed the CUR-BBR-mediated decrease in cell survival. In addition, SOX11 was found to be a direct target of miR-221. CUR-BBR treatment upregulated SOX11 expression, and overexpression of SOX11 restored the inhibitory effects of CUR-BBR on cell growth, migration, and invasion and promoted apoptosis in the presence of miR-221. Furthermore, CUR-BBR activated pro-apoptotic proteins caspase-3/9 through the miR-221/SOX11 axis. The combined effect of CUR-BBR played an important role in inhibiting the growth of HCC cells. This combined effect was achieved by regulating the miR-221/SOX11 axis and activating the synthesis of pro-apoptotic proteins. Our findings highlight a promising combined therapeutic approach for HCC and underscore the importance of targeting the miR-221/SOX11 axis.

NR5A2 connects zygotic genome activation to the first lineage segregation in totipotent embryos.

Zygotic genome activation (ZGA) marks the beginning of the embryonic program for a totipotent embryo, which gives rise to the inner cell mass (ICM) where pluripotent epiblast arises, and extraembryonic trophectoderm. However, how ZGA is connected to the first lineage segregation in mammalian embryos remains elusive. Here, we investigated the role of nuclear receptor (NR) transcription factors (TFs), whose motifs are highly enriched and accessible from the 2-cell (2C) to 8-cell (8C) stages in mouse embryos. We found that NR5A2, an NR TF strongly induced upon ZGA, was required for this connection. Upon Nr5a2 knockdown or knockout, embryos developed beyond 2C normally with the zygotic genome largely activated. However, 4-8C-specific gene activation was substantially impaired and Nr5a2-deficient embryos subsequently arrested at the morula stage. Genome-wide chromatin binding analysis showed that NR5A2-bound cis-regulatory elements in both 2C and 8C embryos are strongly enriched for B1 elements where its binding motif is embedded. NR5A2 was not required for the global opening of its binding sites in 2C embryos but was essential to the opening of its 8C-specific binding sites. These 8C-specific, but not 2C-specific, binding sites are enriched near genes involved in blastocyst and stem cell regulation, and are often bound by master pluripotency TFs in blastocysts and embryonic stem cells (ESCs). Importantly, NR5A2 regulated key pluripotency genes Nanog and Pou5f1/Oct4, and primitive endoderm regulatory genes including Gata6 among many early ICM genes, as well as key trophectoderm regulatory genes including Tead4 and Gata3 at the 8C stage. By contrast, master pluripotency TFs NANOG, SOX2, and OCT4 targeted both early and late ICM genes in mouse ESCs. Taken together, these data identify NR5A2 as a key regulator in totipotent embryos that bridges ZGA to the first lineage segregation during mouse early development.

Nanocarriers for gene delivery to the cardiovascular system.

Cardiovascular diseases have posed a great threat to human health. Fortunately, gene therapy holds great promise in the fight against cardiovascular disease (CVD). In gene therapy, it is necessary to select the appropriate carriers to deliver the genes to the target cells of the target organs. There are usually two types of carriers, viral carriers and non-viral carriers. However, problems such as high immunogenicity, inflammatory response, and limited loading capacity have arisen with the use of viral carriers. Therefore, scholars turned their attention to non-viral carriers. Among them, nanocarriers are highly valued because of their easy modification, targeting, and low toxicity. Despite the many successes of gene therapy in the treatment of human diseases, it is worth noting that there are still many problems to be solved in the field of gene therapy for the treatment of cardiovascular diseases. In this review, we give a brief introduction to the common nanocarriers and several common cardiovascular diseases (arteriosclerosis, myocardial infarction, myocardial hypertrophy). On this basis, the application of gene delivery nanocarriers in the treatment of these diseases is introduced in detail.

Rational Design of an Air-Stable, High-Spin Diradical with Diazapyrene.

Stable carbon-based polyradicals exhibiting strong spin-spin coupling and slow depolarization processes are particularly attractive functional materials. A new molecular motif synthesized by a convenient method that allows the integration of stable, high-spin radicals to (hetero)aromatic polycycles has been developed, as illustrated by a non-Kekulé diradical showing a triplet ground state with long persistency (τ1/2 ≈31 h) in air. Compared to the widely used 1,3-phenylene, the newly designed (diaza)pyrene-4,10-diyl moiety is for the first time demonstrated to confer ferromagnetic (FM) spin coupling, allowing delocalized non-disjoint SOMOs. With the X-ray crystallography unambiguously proving the diradical structure, the triplet ground state was thoroughly characterized. A large ΔES-T of 1.1 kcal/mol, proving the strong FM coupling effect, was revealed consistently by superconducting quantum interference device (SQUID) measurements and variable-temperature electron paramagnetic resonance (EPR) spectroscopy, while the zero-field splitting and triplet nutation characters were examined by continuous-wave and pulsed EPR spectroscopy. A millisecond spin-lattice relaxation time was also detected. The current study not only offers a new molecular motif enabling FM coupling between carbon-based spins, but more importantly presents a general method for installing stable polyradicals into functional π-systems.

Host-derived peptide signals regulate Pseudomonas aeruginosa virulence stress via the ParRS and CprRS two-component systems.

Pseudomonas aeruginosa, a versatile bacterium, has dual significance because of its beneficial roles in environmental soil processes and its detrimental effects as a nosocomial pathogen that causes clinical infections. Understanding adaptability to environmental stress is essential. This investigation delves into the complex interplay of two-component system (TCS), specifically ParRS and CprRS, as P. aeruginosa interprets host signals and navigates stress challenges. In this study, through phenotypic and proteomic analyses, the nuanced contributions of ParRS and CprRS to the pathogenesis and resilience mechanisms were elucidated. Furthermore, the indispensable roles of the ParS and CprS extracellular sensor domains in orchestrating signal perception remain unknown. Structural revelations imply a remarkable convergence of TCS sensors in interacting with host peptides, suggesting evolutionary strategies for bacterial adaptation. This pioneering work not only established links between cationic antimicrobial peptide (CAMP) resistance-associated TCSs and virulence modulation in nosocomial bacteria, but also transcended conventional boundaries. These implications extend beyond clinical resistance, permeating into the realm of soil revitalization and environmental guardianship. As it unveils P. aeruginosa intricacies, this study assumes a mantle of guiding strategies to mitigate clinical hazards, harness environmental advantages, and propel sustainable solutions forward.

Efficient degradation of benzalkonium chloride by FeMn-CA300 catalyst activated persulfate process: Surface hydroxyl potentiation mechanism and degradation pathway.

The consumption of disinfectants increased dramatically with the outbreak of the COVID-19 epidemic. Benzalkonium chloride (DDBAC), a cationic surfactant disinfectant for import and export cargoes, is used for effective degradation method. For DDBAC effective degradation, polyhedral Fe-Mn bimetallic catalyst of Prussian blue analogue (FeMn-CA300) was novelty developed for rapid peroxymonosulfate (PMS) activation. Results showed that the Fe/Mn redox and surface hydroxyl groups in the catalyst played an important role in the DDBAC-enhanced degradation. The removal effectiveness of 10 mg L-1 DDBAC was up to 99.4% in 80 min under the initial pH = 7, catalyst dosage of 0.4 g L-1, and PMS concentration of 15 mmol L-1. In addition, FeMn-CA300 had a wide pH applicability range. The results indicated that hydroxyls, sulfate radicals, and singlet oxygen could effectively improve the degradation efficiency, where sulfate radicals played a crucial role. Finally, the corresponding degradation path of DDBAC was further provided according to GC-MS results. The results of this study provide new insights into the degradation of DDBAC, thereby highlighting the great potential of FeMnca300/PMS to control refractory organic compounds in the aqueous phase.

High-sensitivity silicon carbide divacancy-based temperature sensing.

Color centers in silicon carbide have become potentially versatile quantum sensors. Particularly, wide temperature-range temperature sensing has been realized in recent years. However, the sensitivity is limited due to the short dephasing time of the color centers. In this work, we developed a high-sensitivity silicon carbide divacancy-based thermometer using the thermal Carr-Purcell-Meiboom-Gill (TCPMG) method. First, the zero-field splitting D of the PL6 divacancy as a function of temperature was measured with a linear slope of -99.7 kHz K-1. The coherence times of TCPMG pulses linearly increased with the pulse number and the longest coherence time was about 21 µs, which was ten times higher than . The corresponding temperature-sensing sensitivity was 13.4 mK Hz-1/2, which was about 15 times higher than previous results. Finally, we monitored the laboratory temperature variations for 24 hours using the TCMPG pulse. The experiments pave the way for the application of silicon carbide-based high-sensitivity thermometers in the semiconductor industry, biology, and materials sciences.

Cancer-associated fibroblast-secreted glucosamine alters the androgen biosynthesis program in prostate cancer via HSD3B1 upregulation.

After androgen deprivation, prostate cancer frequently becomes castration resistant (CRPC), with intratumoral androgen production from extragonadal precursors that activate the androgen receptor pathway. 3ß-Hydroxysteroid dehydrogenase-1 (3ßHSD1) is the rate-limiting enzyme for extragonadal androgen synthesis, which together lead to CRPC. Here, we show that cancer-associated fibroblasts (CAFs) increased epithelial 3ßHSD1 expression, induced androgen synthesis, activated the androgen receptor, and induced CRPC. Unbiased metabolomics revealed that CAF-secreted glucosamine specifically induced 3ßHSD1. CAFs induced higher GlcNAcylation in cancer cells and elevated expression of the transcription factor Elk1, which induced higher 3ßHSD1 expression and activity. Elk1 genetic ablation in cancer epithelial cells suppressed CAF-induced androgen biosynthesis in vivo. In patient samples, multiplex fluorescent imaging showed that tumor cells expressed more 3ßHSD1 and Elk1 in CAF-enriched areas compared with CAF-deficient areas. Our findings suggest that CAF-secreted glucosamine increases GlcNAcylation in prostate cancer cells, promoting Elk1-induced HSD3B1 transcription, which upregulates de novo intratumoral androgen synthesis to overcome castration.

Synthetic biology-inspired cell engineering in diagnosis, treatment, and drug development.

The fast-developing synthetic biology (SB) has provided many genetic tools to reprogram and engineer cells for improved performance, novel functions, and diverse applications. Such cell engineering resources can play a critical role in the research and development of novel therapeutics. However, there are certain limitations and challenges in applying genetically engineered cells in clinical practice. This literature review updates the recent advances in biomedical applications, including diagnosis, treatment, and drug development, of SB-inspired cell engineering. It describes technologies and relevant examples in a clinical and experimental setup that may significantly impact the biomedicine field. At last, this review concludes the results with future directions to optimize the performances of synthetic gene circuits to regulate the therapeutic activities of cell-based tools in specific diseases.

A deep learning model with data integration of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical parameters for diagnosing significant liver fibrosis in patients with chronic hepatitis B.

OBJECTIVE: To develop and investigate a deep learning model with data integration of ultrasound contrast-enhanced micro-flow (CEMF) cines, B-mode images, and patients' clinical parameters to improve the diagnosis of significant liver fibrosis (≥ F2) in patients with chronic hepatitis B (CHB). METHODS: Of 682 CHB patients who underwent ultrasound and histopathological examinations between October 2016 and May 2020, 218 subjects were included in this retrospective study. We devised a data integration-based deep learning (DIDL) model for assessing ≥ F2 in CHB patients. The model contained three convolutional neural network branches to automatically extract features from ultrasound CEMF cines, B-mode images, and clinical data. The extracted features were fused at the backend of the model for decision-making. The diagnostic performance was evaluated across fivefold cross-validation and compared against the other methods in terms of the area under the receiver operating characteristic curve (AUC), with histopathological results as the reference standard. RESULTS: The mean AUC achieved by the DIDL model was 0.901 [95% CI, 0.857-0.939], which was significantly higher than those of the comparative methods, including the models trained by using only CEMF cines (0.850 [0.794-0.893]), B-mode images (0.813 [0.754-0.862]), or clinical data (0.757 [0.694-0.812]), as well as the conventional TIC method (0.752 [0.689-0.808]), APRI (0.792 [0.734-0.845]), FIB-4 (0.776 [0.714-0.829]), and visual assessments of two radiologists (0.812 [0.754-0.862], and 0.800 [0.739-0.849]), all ps < 0.01, DeLong test. CONCLUSION: The DIDL model with data integration of ultrasound CEMF cines, B-mode images, and clinical parameters showed promising performance in diagnosing significant liver fibrosis for CHB patients. KEY POINTS: • The combined use of ultrasound contrast-enhanced micro-flow cines, B-mode images, and clinical data in a deep learning model has potential to improve the diagnosis of significant liver fibrosis. • The deep learning model with the fusion of features extracted from multimodality data outperformed the conventional methods including mono-modality data-based models, the time-intensity curve-based recognizer, fibrosis biomarkers, and visual assessments by experienced radiologists. • The interpretation of the feature attention maps in the deep learning model may help radiologists get better understanding of liver fibrosis-related features and hence potentially enhancing their diagnostic capacities.

BMX controls 3ßHSD1 and sex steroid biosynthesis in cancer.

Prostate cancer is highly dependent on androgens and the androgen receptor (AR). Hormonal therapies inhibit gonadal testosterone production, block extragonadal androgen biosynthesis, or directly antagonize AR. Resistance to medical castration occurs as castration-resistant prostate cancer (CRPC) and is driven by reactivation of the androgen-AR axis. 3ß-hydroxysteroid dehydrogenase-1 (3ßHSD1) serves as the rate-limiting step for potent androgen synthesis from extragonadal precursors, thereby stimulating CRPC. Genetic evidence in men demonstrates the role of 3ßHSD1 in driving CRPC. In postmenopausal women, 3ßHSD1 is required for synthesis of aromatase substrates and plays an essential role in breast cancer. Therefore, 3ßHSD1 lies at a critical junction for the synthesis of androgens and estrogens, and this metabolic flux is regulated through germline-inherited mechanisms. We show that phosphorylation of tyrosine 344 (Y344) occurs and is required for 3ßHSD1 cellular activity and generation of Δ4, 3-keto-substrates of 5α-reductase and aromatase, including in patient tissues. BMX directly interacts with 3ßHSD1 and is necessary for enzyme phosphorylation and androgen biosynthesis. In vivo blockade of 3ßHSD1 Y344 phosphorylation inhibits CRPC. These findings identify what we believe to be new hormonal therapy pharmacologic vulnerabilities for sex-steroid dependent cancers.

Functional characterization of MdERF113 in apple.

The AP2/ERF family is an important class of transcription factors involved in plant growth and various biological processes. One of the AP2/ERF transcription factors, RAP2.6L, participates in various stresses responses. However, the function of RAP2.6L is largely unknown in apples (Malus domestica). In this study, an apple gene homologous to Arabidopsis AtRAP2.6L, MdERF113, was analyzed by bioinformatic characterization, gene expression analysis and subcellular localization assessment. MdERF113 was highly expressed in the sarcocarp and was responsive to hormonal signals and abiotic stresses. MdERF113-overexpression apple calli were less sensitive to low temperature, drought, salinity, and abscisic acid than wild-type. Subcellular localization revealed that MdERF113 was a nuclear-localized transcription factor, and yeast experiments confirmed that MdERF113 has no autonomous activation activity. Overall, this study indicated that MdERF113 plays a role in regulating plant growth under abiotic conditions.