Excavation of gene markers associated with pancreatic ductal adenocarcinoma based on interrelationships of gene expression.

Pancreatic ductal adenocarcinoma (PDAC) accounts for 95% of all pancreatic cancer cases, posing grave challenges to its diagnosis and treatment. Timely diagnosis is pivotal for improving patient survival, necessitating the discovery of precise biomarkers. An innovative approach was introduced to identify gene markers for precision PDAC detection. The core idea of our method is to discover gene pairs that display consistent opposite relative expression and differential co-expression patterns between PDAC and normal samples. Reversal gene pair analysis and differential partial correlation analysis were performed to determine reversal differential partial correlation (RDC) gene pairs. Using incremental feature selection, the authors refined the selected gene set and constructed a machine-learning model for PDAC recognition. As a result, the approach identified 10 RDC gene pairs. And the model could achieve a remarkable accuracy of 96.1% during cross-validation, surpassing gene expression-based models. The experiment on independent validation data confirmed the model's performance. Enrichment analysis revealed the involvement of these genes in essential biological processes and shed light on their potential roles in PDAC pathogenesis. Overall, the findings highlight the potential of these 10 RDC gene pairs as effective diagnostic markers for early PDAC detection, bringing hope for improving patient prognosis and survival.

Androgen deprivation induces double-null prostate cancer via aberrant nuclear export and ribosomal biogenesis through HGF and Wnt activation.

Androgen deprivation therapy (ADT) targeting androgen/androgen receptor (AR)- signaling pathways is the main therapy for advanced prostate cancer (PCa). However, ADT eventually fails in most patients who consequently develop castration-resistant prostate cancer (CRPC). While more potent AR antagonists and blockers for androgen synthesis were developed to improve clinical outcomes, they also show to induce more diverse CRPC phenotypes. Specifically, the AR- and neuroendocrine-null PCa, DNPC, occurs in abiraterone and enzalutamide-treated patients. Here, we uncover that current ADT induces aberrant HGF/MET signaling activation that further elevates Wnt/ß-catenin signaling in human DNPC samples. Co-activation of HGF/MET and Wnt/ß-catenin axes in mouse prostates induces DNPC-like lesions. Single-cell RNA sequencing analyses identify increased expression and activity of XPO1 and ribosomal proteins in mouse DNPC-like cells. Elevated expression of XPO1 and ribosomal proteins is also identified in clinical DNPC specimens. Inhibition of XPO1 and ribosomal pathways represses DNPC growth in both in vivo and ex vivo conditions, evidencing future therapeutic targets.

Soft Robotic Finger with Energy-Coupled Quadrastability.

The performance of the human finger is a significant inspiration for designing soft robotic fingers that can achieve high speed and high force or perform delicate and complex tasks. Existing soft grippers and actuators can be excellent in specific capabilities. However, it is still challenging for them to meet an all-around performance as the human finger, characterized by high actuation speed, wide grasping range, sensing ability, and gentle and high-load grasping capability. The proposed tendon pulley quadrastable (TPQ) finger has combined these qualities in the conducted gripping tasks. A pair of elastic tendons is utilized as the sole energy reservoir to create a novel energy distribution pattern: energy-coupled quadrastability. An energy model is built to analyze and predict the behaviors of the TPQ finger. Mechanical instability is utilized to enhance the actuation speed. The proposed soft lever mechanism endows the TPQ finger with sensing ability. The energy barrier adjusting plates control the energy barrier, adjusting the sensitivity of both active and passive actuation mechanisms. The transition of four stable states forms preplanned trajectories that are applied to create multiple grasping manners. Experiments show that it can respond to stimuli and finish a grasping task in merely 31 ms, and its payload can reach 33.25 kg. At the same time, it can also handle fragile objects such as a piece of rose and grasp a wide range of objects ranging from a thin nut (3.3 mm in height) or a thin card (0.76 mm thick) to a football (220 mm).

Cardiovascular Impact of Androgen Deprivation Therapy: from Basic Biology to Clinical Practice.

PURPOSE OF THE REVIEW: There have been increasing reports of cardiovascular complications of androgen deprivation therapy (ADT) leading to worse outcomes among patients with prostate cancer. While this may result from the direct effects of androgen suppression in the cardiovascular systems, there are ADT-type-specific distinct cardiovascular complications suggestive of mechanisms beyond androgen-mediated. Thus, it is critical to understand the biological and clinical impact of ADT on the cardiovascular system. RECENT FINDINGS: Gonadotropin-releasing hormone (GnRH) agonists cause increased cardiovascular events compared to GnRH antagonists. Androgen receptor antagonists are linked to an increased risk of long QT syndrome, torsades de pointes, and sudden cardiac death. Androgen synthesis inhibitors are associated with increased rates of hypertension, atrial tachyarrhythmia, and, in rare incidences, heart failure. ADT increases the risk of cardiovascular disease. The risk among ADT drugs differs and must be evaluated to develop a medically optimal plan for prostate cancer patients.

An In Vitro Biomechanical Study of the Ectopic Functional Reconstruction of the Transverse Ligament of Atlas.

OBJECTIVE: To evaluate the stability and function of the C1-C2 joint after ectopic functional reconstruction (EFR) of the C1 transverse ligament. METHODS: Eight human cadaveric cervical spines (C0-C4) were subjected to in vitro biomechanical test with moment control. Spine specimens were tested under the following conditions: 1) left intact; 2) destabilized by severing the transverse ligament of atlas; 3) after EFR of the transverse ligament. Range of motion was measured in flexion, extension, lateral bending, and axial rotation. RESULTS: Destabilization significantly increased range of motion in all directions compared with the intact status (P < 0.001). However, after EFR of the transverse ligament, range of motion in all directions was restored to the intact state. Meanwhile, coupling motions were reproduced in the axial rotation. CONCLUSIONS: EFR of the transverse ligament virtually recovers all the physiological functions of the native transverse ligament and might be a promising alternative for the treatment of anterior atlantoaxial dislocation. Further studies are warranted before clinical application of EFR of the transverse ligament.

Stromal androgen signaling acts as tumor niches to drive prostatic basal epithelial progenitor-initiated oncogenesis.

The androgen receptor (AR)-signaling pathways are essential for prostate tumorigenesis. Although significant effort has been devoted to directly targeting AR-expressing tumor cells, these therapies failed in most prostate cancer patients. Here, we demonstrate that loss of AR in stromal sonic-hedgehog Gli1-lineage cells diminishes prostate epithelial oncogenesis and tumor development using in vivo assays and mouse models. Single-cell RNA sequencing and other analyses identified a robust increase of insulin-like growth factor (IGF) binding protein 3 expression in AR-deficient stroma through attenuation of AR suppression on Sp1-regulated transcription, which further inhibits IGF1-induced Wnt/ß-catenin activation in adjacent basal epithelial cells and represses their oncogenic growth and tumor development. Epithelial organoids from stromal AR-deficient mice can regain IGF1-induced oncogenic growth. Loss of human prostate tumor basal cell signatures reveals in basal cells of stromal AR-deficient mice. These data demonstrate a distinct mechanism for prostate tumorigenesis and implicate co-targeting stromal and epithelial AR-signaling for prostate cancer.

Interfacial Strengthening and Self-Monitoring in Carbon Fiber-Reinforced Composites via Carbon Nanotube-Based Damage Sensors.

Carbon fiber-reinforced polymers are important constituents of aerospace materials. However, due to the inert surface of CFs, their interfacial property is relatively weak, which severely hinders their practical applications. Here, we deposited multi-walled carbon nanotubes (MWCNTs) along with a coupling agent on the surface of carbon fiber to improve the interfacial properties of the carbon fiber/resin. Via a simple dip-coating method, the MWCNTs were uniformly distributed on the CF surface with the assistance of the pre-coated coupling agent. The interfacial shear strength between the fiber and the matrix was significant enhanceed when the CF was loaded with the coupling agent and the MWCNTs. In addition, the MWCNTs were used as sensors to in-situ monitor the interfacial state in order to elucidate the interfacial strengthening mechanism. It revealed that the collaborative contribution of the coupling agent and the MWCNTs in the interphase region is the key to the high interfacial strength.

Analysis and modeling of myopia-related factors based on questionnaire survey.

With the rapid development of science and technology, the trend of low age myopia is becoming increasingly significant. The latest national survey done by the Chinese government found that more than 80% of Chinese teenagers suffer from myopia. Adolescent myopia is closely related to living environment, heredity, and living habits. Quantifying the relationship between myopia and living environment, heredity, and living habits is conductive to the prevention and intervention of adolescent myopia. In this study, we investigated the relationships between four main factors (environment, habits, parental vision, and demographic) and myopia status by analyzing the questionnaire data. Data were collected from Chengdu, China in 2021, including 2808 myopia samples and 5693 non-myopia samples, with a total of 22 features. Then, these 22 features were inputted into three machine learning algorithms to discriminate the two classes of samples. Results show that the computational model could produce an AUC of 0.768. To pick out the most important features which play important roles in classification, we used incremental feature selection strategy to screen the 22 features. As a result, we found that the 4 most influential features with XGBoost could achieve a competitive AUC of 0.764. To further investigate the risk and protective factors affecting adolescent myopia, we used OR values derived from MLE-LR to analyze the relationship between 22 features and adolescent myopia. Results showed that the age variable was the most significant risk factor for myopia, followed by the myopia status of parents. The most protective factor for eyesight is the measure taken by the children, followed by the distance between books and eyes when reading. These discoveries can guide the prevention and control of myopia in children and adolescents.

Zmiz1 is required for mature ß-cell function and mass expansion upon high fat feeding.

OBJECTIVE: Identifying the transcripts which mediate genetic association signals for type 2 diabetes (T2D) is critical to understand disease mechanisms. Studies in pancreatic islets support the transcription factor ZMIZ1 as a transcript underlying a T2D GWAS signal, but how it influences T2D risk is unknown. METHODS: ß-Cell-specific Zmiz1 knockout (Zmiz1ßKO) mice were generated and phenotypically characterised. Glucose homeostasis was assessed in Zmiz1ßKO mice and their control littermates on chow diet (CD) and high fat diet (HFD). Islet morphology and function were examined by immunohistochemistry and in vitro islet function was assessed by dynamic insulin secretion assay. Transcript and protein expression were assessed by RNA sequencing and Western blotting. In islets isolated from genotyped human donors, we assessed glucose-dependent insulin secretion and islet insulin content by static incubation assay. RESULTS: Male and female Zmiz1ßKO mice were glucose intolerant with impaired insulin secretion, compared with control littermates. Transcriptomic profiling of Zmiz1ßKO islets identified over 500 differentially expressed genes including those involved in ß-cell function and maturity, which we confirmed at the protein level. Upon HFD, Zmiz1ßKO mice fail to expand ß-cell mass and become severely diabetic. Human islets from carriers of the ZMIZ1-linked T2D-risk alleles have reduced islet insulin content and glucose-stimulated insulin secretion. CONCLUSIONS: ß-Cell Zmiz1 is required for normal glucose homeostasis. Genetic variation at the ZMIZ1 locus may influence T2D-risk by reducing islet mass expansion upon metabolic stress and the ability to maintain a mature ß-cell state.

Aberrant androgen action in prostatic progenitor cells induces oncogenesis and tumor development through IGF1 and Wnt axes.

Androgen/androgen receptor (AR) signaling pathways are essential for prostate tumorigenesis. However, the fundamental mechanisms underlying the AR functioning as a tumor promoter in inducing prostatic oncogenesis still remain elusive. Here, we demonstrate that a subpopulation of prostatic Osr1 (odd skipped-related 1)-lineage cells functions as tumor progenitors in prostate tumorigenesis. Single cell transcriptomic analyses reveal that aberrant AR activation in these cells elevates insulin-like growth factor 1 (IGF1) signaling pathways and initiates oncogenic transformation. Elevating IGF1 signaling further cumulates Wnt/ß-catenin pathways in transformed cells to promote prostate tumor development. Correlations between altered androgen, IGF1, and Wnt/ß-catenin signaling are also identified in human prostate cancer samples, uncovering a dynamic regulatory loop initiated by the AR through prostate cancer development. Co-inhibition of androgen and Wnt-signaling pathways significantly represses the growth of AR-positive tumor cells in both ex-vivo and in-vivo, implicating co-targeting therapeutic strategies for these pathways to treat advanced prostate cancer.

PSnoD: identifying potential snoRNA-disease associations based on bounded nuclear norm regularization.

Many studies have proved that small nucleolar RNAs (snoRNAs) play critical roles in the development of various human complex diseases. Discovering the associations between snoRNAs and diseases is an important step toward understanding the pathogenesis and characteristics of diseases. However, uncovering associations via traditional experimental approaches is costly and time-consuming. This study proposed a bounded nuclear norm regularization-based method, called PSnoD, to predict snoRNA-disease associations. Benchmark experiments showed that compared with the state-of-the-art methods, PSnoD achieved a superior performance in the 5-fold stratified shuffle split. PSnoD produced a robust performance with an area under receiver-operating characteristic of 0.90 and an area under precision-recall of 0.55, highlighting the effectiveness of our proposed method. In addition, the computational efficiency of PSnoD was also demonstrated by comparison with other matrix completion techniques. More importantly, the case study further elucidated the ability of PSnoD to screen potential snoRNA-disease associations. The code of PSnoD has been uploaded to https://github.com/linDing-groups/PSnoD. Based on PSnoD, we established a web server that is freely accessed via http://psnod.lin-group.cn/.

Toxicity of triphenyl phosphate toward the marine rotifer Brachionus plicatilis: Changes in key life-history traits, rotifer-algae population dynamics and the metabolomic response.

Triphenyl phosphate (TPhP) is used as a flame retardant that gradually leaks from products into the marine environment and thus may threaten low-trophic-level marine organisms, such as zooplankton. To assess the effect of TPhP on these taxa, we treated the marine rotifer Brachionus plicatilis as a target and examined the changes in key life history parameters and the metabolome after exposure to TPhP at 0.02, 1 and 5 mg/L. Additionally, the rotifer-Phaeocystis population dynamics (a simulation of the prey-predator relationship) were studied under TPhP stress. Our results showed that TPhP at 1 and 5 mg/L reduced the average lifespan and the total offspring number and prolonged the prereproductive time, suggesting damage to survival and fecundity. In the 0.02 mg/L group, no obvious damage occurred in the overall condition of rotifers, but the volume of parental rotifers after the first brood decreased. This implied that rotifers sacrificed somatic growth to reproduction in the initial period of TPhP exposure at the low concentration. All the tested TPhP concentrations altered the rotifer-Phaeocystis population dynamic changes, especially that 1 mg/L TPhP reduced the ability of rotifers to remove this harmful alga, as evidenced by the decrease in the maximum population density of rotifers and the extended time to P. globosa extinction. At the molecular level, metabolomics identified 84 and 206 differentially expressed metabolites, most of which were enriched in glycerophospholipid metabolism, steroid biosynthesis and sphingolipid metabolism. Nile red staining showed a decrease in neutral lipids in rotifers, further indicating a disorder of lipid metabolism induced by TPhP. Moreover, the balance between ROS production and the defense system was disrupted by TPhP, which contributed to its toxicity. This finding will promote the understanding of the ecological risk and mode of action of TPhP in aquatic environments.

Alleviation of Tris(2-chloroethyl) Phosphate Toxicity on the Marine Rotifer Brachionus plicatilis by Polystyrene Microplastics: Features and Molecular Evidence.

As emerging pollutants, microplastics (MPs) and organophosphorus esters (OPEs) coexist in the aquatic environment, posing a potential threat to organisms. Although toxicological studies have been conducted individually, the effects of combined exposure are unknown since MPs can interact with OPEs acting as carriers. In this study, we assessed the response of marine rotifer, Brachionus plicatilis, to co-exposure to polystyrene MPs and tris(2-chloroethyl) phosphate (TCEP) at different concentrations, including population growth, oxidative status, and transcriptomics. Results indicated that 0.1 µm and 1 µm MPs were accumulated in the digestive system, and, even at up to 2000 µg/L, they did not exert obvious damage to the stomach morphology, survival, and reproduction of B. plicatilis. The presence of 1 µm MPs reversed the low population growth rate and high oxidative stress induced by TCEP to the normal level. Some genes involved in metabolic detoxification and stress response were upregulated, such as ABC and Hsp. Subsequent validation showed that P-glycoprotein efflux ability was activated by combined exposure, indicating its important role in the reversal of population growth inhibition. Such results challenge the common perception that MPs aggravate the toxicity of coexisting pollutants and elucidate the molecular mechanism of the limited toxic effects induced by MPs and TCEP.

Risk prediction of diabetes and pre-diabetes based on physical examination data.

Diabetes is a metabolic disorder caused by insufficient insulin secretion and insulin secretion disorders. From health to diabetes, there are generally three stages: health, pre-diabetes and type 2 diabetes. Early diagnosis of diabetes is the most effective way to prevent and control diabetes and its complications. In this work, we collected the physical examination data from Beijing Physical Examination Center from January 2006 to December 2017, and divided the population into three groups according to the WHO (1999) Diabetes Diagnostic Standards: normal fasting plasma glucose (NFG) (FPG < 6.1 mmol/L), mildly impaired fasting plasma glucose (IFG) (6.1 mmol/L ≤ FPG < 7.0 mmol/L) and type 2 diabetes (T2DM) (FPG > 7.0 mmol/L). Finally, we obtained1,221,598 NFG samples, 285,965 IFG samples and 387,076 T2DM samples, with a total of 15 physical examination indexes. Furthermore, taking eXtreme Gradient Boosting (XGBoost), random forest (RF), Logistic Regression (LR), and Fully connected neural network (FCN) as classifiers, four models were constructed to distinguish NFG, IFG and T2DM. The comparison results show that XGBoost has the best performance, with AUC (macro) of 0.7874 and AUC (micro) of 0.8633. In addition, based on the XGBoost classifier, three binary classification models were also established to discriminate NFG from IFG, NFG from T2DM, IFG from T2DM. On the independent dataset, the AUCs were 0.7808, 0.8687, 0.7067, respectively. Finally, we analyzed the importance of the features and identified the risk factors associated with diabetes.

Deep-4mCGP: A Deep Learning Approach to Predict 4mC Sites in Geobacter pickeringii by Using Correlation-Based Feature Selection Technique.

4mC is a type of DNA alteration that has the ability to synchronize multiple biological movements, for example, DNA replication, gene expressions, and transcriptional regulations. Accurate prediction of 4mC sites can provide exact information to their hereditary functions. The purpose of this study was to establish a robust deep learning model to recognize 4mC sites in Geobacter pickeringii. In the anticipated model, two kinds of feature descriptors, namely, binary and k-mer composition were used to encode the DNA sequences of Geobacter pickeringii. The obtained features from their fusion were optimized by using correlation and gradient-boosting decision tree (GBDT)-based algorithm with incremental feature selection (IFS) method. Then, these optimized features were inserted into 1D convolutional neural network (CNN) to classify 4mC sites from non-4mC sites in Geobacter pickeringii. The performance of the anticipated model on independent data exhibited an accuracy of 0.868, which was 4.2% higher than the existing model.

iRice-MS: An integrated XGBoost model for detecting multitype post-translational modification sites in rice.

Post-translational modification (PTM) refers to the covalent and enzymatic modification of proteins after protein biosynthesis, which orchestrates a variety of biological processes. Detecting PTM sites in proteome scale is one of the key steps to in-depth understanding their regulation mechanisms. In this study, we presented an integrated method based on eXtreme Gradient Boosting (XGBoost), called iRice-MS, to identify 2-hydroxyisobutyrylation, crotonylation, malonylation, ubiquitination, succinylation and acetylation in rice. For each PTM-specific model, we adopted eight feature encoding schemes, including sequence-based features, physicochemical property-based features and spatial mapping information-based features. The optimal feature set was identified from each encoding, and their respective models were established. Extensive experimental results show that iRice-MS always display excellent performance on 5-fold cross-validation and independent dataset test. In addition, our novel approach provides the superiority to other existing tools in terms of AUC value. Based on the proposed model, a web server named iRice-MS was established and is freely accessible at http://lin-group.cn/server/iRice-MS.

Deep-4mCW2V: A sequence-based predictor to identify N4-methylcytosine sites in Escherichia coli.

N4-methylcytosine (4mC) is a type of DNA modification which could regulate several biological progressions such as transcription regulation, replication and gene expressions. Precisely recognizing 4mC sites in genomic sequences can provide specific knowledge about their genetic roles. This study aimed to develop a deep learning-based model to predict 4mC sites in the Escherichia coli. In the model, DNA sequences were encoded by word embedding technique 'word2vec'. The obtained features were inputted into 1-D convolutional neural network (CNN) to discriminate 4mC sites from non-4mC sites in Escherichia coli genome. The examination on independent dataset showed that our model could yield the overall accuracy of 0.861, which was about 4.3% higher than the existing model. To provide convenience to scholars, we provided the data and source code of the model which can be freely download from https://github.com/linDing-groups/Deep-4mCW2V.

Mechanistic understanding of the toxicity of triphenyl phosphate (TPhP) to the marine diatom Phaeodactylum tricornutum: Targeting chloroplast and mitochondrial dysfunction.

Triphenyl phosphate (TPhP) has been widely detected in various environmental media, including seawater, threatening the survival of marine organisms, especially marine planktic algae that are directly exposed to contamination. However, the hazard potential of TPhP on marine algae has not been studied thoroughly and systematically. In this study, a marine diatom, Phaeodactylum tricornutum, was treated with three concentrations of TPhP (0.08, 0.4 and 0.8 mg/L), and after 24 h of exposure, population growth, ultrastructure, physiology and transcriptome changes were investigated. The results reflected that TPhP suppressed the population growth of algae in a concentration-dependent manner, and the 24-h EC50 value was 1.27 mg/L. At all test concentrations, P. tricornutum could absorb more than 70% of TPhP from seawater over 24 h. Ultrastructural observations suggested a distorted lamellar structure with higher TPhP treatments, and the contents of chlorophyll and its precursors were also altered, as were photosynthetic activities. Moreover, 0.8 mg/L TPhP decreased the mitochondrial membrane potential, induced ROS overproduction and disrupted the cell membrane permeability of algal cells. At the transcriptomic level, some differentially expressed genes were enriched in photosynthetic electron transport, carbon fixation, chlorophyll biosynthesis, the TCA cycle and mitochondrial glycolysis. Additionally, 0.8 mg/L TPhP inhibited lipid de novo biosynthesis, suggesting that it may target organelle membranes, thereby contributing to functional defects. Chloroplasts and mitochondria were interpreted to be the subcellular targets of TPhP in P. tricornutum. These data promote the understanding of the toxic action mode of TPhP toward marine diatoms.

Identification of cyclin protein using gradient boost decision tree algorithm.

Cyclin proteins are capable to regulate the cell cycle by forming a complex with cyclin-dependent kinases to activate cell cycle. Correct recognition of cyclin proteins could provide key clues for studying their functions. However, their sequences share low similarity, which results in poor prediction for sequence similarity-based methods. Thus, it is urgent to construct a machine learning model to identify cyclin proteins. This study aimed to develop a computational model to discriminate cyclin proteins from non-cyclin proteins. In our model, protein sequences were encoded by seven kinds of features that are amino acid composition, composition of k-spaced amino acid pairs, tri peptide composition, pseudo amino acid composition, geary correlation, normalized moreau-broto autocorrelation and composition/transition/distribution. Afterward, these features were optimized by using analysis of variance (ANOVA) and minimum redundancy maximum relevance (mRMR) with incremental feature selection (IFS) technique. A gradient boost decision tree (GBDT) classifier was trained on the optimal features. Five-fold cross-validated results showed that our model would identify cyclins with an accuracy of 93.06% and AUC value of 0.971, which are higher than the two recent studies on the same data.

Stromal androgen and hedgehog signaling regulates stem cell niches in pubertal prostate development.

Stromal androgen-receptor (AR) action is essential for prostate development, morphogenesis and regeneration. However, mechanisms underlying how stromal AR maintains the cell niche in support of pubertal prostatic epithelial growth are unknown. Here, using advanced mouse genetic tools, we demonstrate that selective deletion of stromal AR expression in prepubescent Shh-responsive Gli1-expressing cells significantly impedes pubertal prostate epithelial growth and development. Single-cell transcriptomic analyses showed that AR loss in these prepubescent Gli1-expressing cells dysregulates androgen signaling-initiated stromal-epithelial paracrine interactions, leading to growth retardation of pubertal prostate epithelia and significant development defects. Specifically, AR loss elevates Shh-signaling activation in both prostatic stromal and adjacent epithelial cells, directly inhibiting prostatic epithelial growth. Single-cell trajectory analyses further identified aberrant differentiation fates of prostatic epithelial cells directly altered by stromal AR deletion. In vivo recombination of AR-deficient stromal Gli1-lineage cells with wild-type prostatic epithelial cells failed to develop normal prostatic epithelia. These data demonstrate previously unidentified mechanisms underlying how stromal AR-signaling facilitates Shh-mediated cell niches in pubertal prostatic epithelial growth and development.