Structural basis for FGF hormone signalling.

α/ßKlotho coreceptors simultaneously engage fibroblast growth factor (FGF) hormones (FGF19, FGF21 and FGF23)1,2 and their cognate cell-surface FGF receptors (FGFR1-4) thereby stabilizing the endocrine FGF-FGFR complex3-6. However, these hormones still require heparan sulfate (HS) proteoglycan as an additional coreceptor to induce FGFR dimerization/activation and hence elicit their essential metabolic activities6. To reveal the molecular mechanism underpinning the coreceptor role of HS, we solved cryo-electron microscopy structures of three distinct 1:2:1:1 FGF23-FGFR-αKlotho-HS quaternary complexes featuring the 'c' splice isoforms of FGFR1 (FGFR1c), FGFR3 (FGFR3c) or FGFR4 as the receptor component. These structures, supported by cell-based receptor complementation and heterodimerization experiments, reveal that a single HS chain enables FGF23 and its primary FGFR within a 1:1:1 FGF23-FGFR-αKlotho ternary complex to jointly recruit a lone secondary FGFR molecule leading to asymmetric receptor dimerization and activation. However, αKlotho does not directly participate in recruiting the secondary receptor/dimerization. We also show that the asymmetric mode of receptor dimerization is applicable to paracrine FGFs that signal solely in an HS-dependent fashion. Our structural and biochemical data overturn the current symmetric FGFR dimerization paradigm and provide blueprints for rational discovery of modulators of FGF signalling2 as therapeutics for human metabolic diseases and cancer.

HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses.

While significant strides have been made in predicting neoepitopes that trigger autologous CD4+ T cell responses, accurately identifying the antigen presentation by human leukocyte antigen (HLA) class II molecules remains a challenge. This identification is critical for developing vaccines and cancer immunotherapies. Current prediction methods are limited, primarily due to a lack of high-quality training epitope datasets and algorithmic constraints. To predict the exogenous HLA class II-restricted peptides across most of the human population, we utilized the mass spectrometry data to profile >223 000 eluted ligands over HLA-DR, -DQ, and -DP alleles. Here, by integrating these data with peptide processing and gene expression, we introduce HLAIImaster, an attention-based deep learning framework with adaptive domain knowledge for predicting neoepitope immunogenicity. Leveraging diverse biological characteristics and our enhanced deep learning framework, HLAIImaster is significantly improved against existing tools in terms of positive predictive value across various neoantigen studies. Robust domain knowledge learning accurately identifies neoepitope immunogenicity, bridging the gap between neoantigen biology and the clinical setting and paving the way for future neoantigen-based therapies to provide greater clinical benefit. In summary, we present a comprehensive exploitation of the immunogenic neoepitope repertoire of cancers, facilitating the effective development of "just-in-time" personalized vaccines.

GLI1+ Cells Contribute to Vascular Remodeling in Pulmonary Hypertension.

BACKGROUND: The precise origin of newly formed ACTA2+ (alpha smooth muscle actin-positive) cells appearing in nonmuscularized vessels in the context of pulmonary hypertension is still debatable although it is believed that they predominantly derive from preexisting vascular smooth muscle cells (VSMCs). METHODS: Gli1Cre-ERT2; tdTomatoflox mice were used to lineage trace GLI1+ (glioma-associated oncogene homolog 1-positive) cells in the context of pulmonary hypertension using 2 independent models of vascular remodeling and reverse remodeling: hypoxia and cigarette smoke exposure. Hemodynamic measurements, right ventricular hypertrophy assessment, flow cytometry, and histological analysis of thick lung sections followed by state-of-the-art 3-dimensional reconstruction and quantification using Imaris software were used to investigate the contribution of GLI1+ cells to neomuscularization of the pulmonary vasculature. RESULTS: The data show that GLI1+ cells are abundant around distal, nonmuscularized vessels during steady state, and this lineage contributes to around 50% of newly formed ACTA2+ cells around these normally nonmuscularized vessels. During reverse remodeling, cells derived from the GLI1+ lineage are largely cleared in parallel to the reversal of muscularization. Partial ablation of GLI1+ cells greatly prevented vascular remodeling in response to hypoxia and attenuated the increase in right ventricular systolic pressure and right heart hypertrophy. Single-cell RNA sequencing on sorted lineage-labeled GLI1+ cells revealed an Acta2high fraction of cells with pathways in cancer and MAPK (mitogen-activated protein kinase) signaling as potential players in reprogramming these cells during vascular remodeling. Analysis of human lung-derived material suggests that GLI1 signaling is overactivated in both group 1 and group 3 pulmonary hypertension and can promote proliferation and myogenic differentiation. CONCLUSIONS: Our data highlight GLI1+ cells as an alternative cellular source of VSMCs in pulmonary hypertension and suggest that these cells and the associated signaling pathways represent an important therapeutic target for further studies.

Photosynthetic plasticity aggravates the susceptibility of magnesium-deficient leaf to high light in rapeseed plants: the importance of Rubisco and mesophyll conductance.

Plants grown under low magnesium (Mg) soils are highly susceptible to encountering light intensities that exceed the capacity of photosynthesis (A), leading to a depression of photosynthetic efficiency and eventually to photooxidation (i.e., leaf chlorosis). Yet, it remains unclear which processes play a key role in limiting the photosynthetic energy utilization of Mg-deficient leaves, and whether the plasticity of A in acclimation to irradiance could have cross-talk with Mg, hence accelerating or mitigating the photodamage. We investigated the light acclimation responses of rapeseed (Brassica napus) grown under low- and adequate-Mg conditions. Magnesium deficiency considerably decreased rapeseed growth and leaf A, to a greater extent under high than under low light, which is associated with higher level of superoxide anion radical and more severe leaf chlorosis. This difference was mainly attributable to a greater depression in dark reaction under high light, with a higher Rubisco fallover and a more limited mesophyll conductance to CO2 (gm ). Plants grown under high irradiance enhanced the content and activity of Rubisco and gm to optimally utilize more light energy absorbed. However, Mg deficiency could not fulfill the need to activate the higher level of Rubisco and Rubisco activase in leaves of high-light-grown plants, leading to lower Rubisco activation and carboxylation rate. Additionally, Mg-deficient leaves under high light invested more carbon per leaf area to construct a compact leaf structure with smaller intercellular airspaces, lower surface area of chloroplast exposed to intercellular airspaces, and CO2 diffusion conductance through cytosol. These caused a more severe decrease in within-leaf CO2 diffusion rate and substrate availability. Taken together, plant plasticity helps to improve photosynthetic energy utilization under high light but aggravates the photooxidative damage once the Mg nutrition becomes insufficient.

Multi-modality attribute learning-based method for drug-protein interaction prediction based on deep neural network.

Identification of active candidate compounds for target proteins, also called drug-protein interaction (DPI) prediction, is an essential but time-consuming and expensive step, which leads to fostering the development of drug discovery. In recent years, deep network-based learning methods were frequently proposed in DPIs due to their powerful capability of feature representation. However, the performance of existing DPI methods is still limited by insufficiently labeled pharmacological data and neglected intermolecular information. Therefore, overcoming these difficulties to perfect the performance of DPIs is an urgent challenge for researchers. In this article, we designed an innovative 'multi-modality attributes' learning-based framework for DPIs with molecular transformer and graph convolutional networks, termed, multi-modality attributes (MMA)-DPI. Specifically, intermolecular sub-structural information and chemical semantic representations were extracted through an augmented transformer module from biomedical data. A tri-layer graph convolutional neural network module was applied to associate the neighbor topology information and learn the condensed dimensional features by aggregating a heterogeneous network that contains multiple biological representations of drugs, proteins, diseases and side effects. Then, the learned representations were taken as the input of a fully connected neural network module to further integrate them in molecular and topological space. Finally, the attribute representations were fused with adaptive learning weights to calculate the interaction score for the DPIs tasks. MMA-DPI was evaluated in different experimental conditions and the results demonstrate that the proposed method achieved higher performance than existing state-of-the-art frameworks.

DrugMGR: a deep bioactive molecule binding method to identify compounds targeting proteins.

MOTIVATION: Understanding the intermolecular interactions of ligand-target pairs is key to guiding the optimization of drug research on cancers, which can greatly mitigate overburden workloads for wet labs. Several improved computational methods have been introduced and exhibit promising performance for these identification tasks, but some pitfalls restrict their practical applications: (i) first, existing methods do not sufficiently consider how multigranular molecule representations influence interaction patterns between proteins and compounds; and (ii) second, existing methods seldom explicitly model the binding sites when an interaction occurs to enable better prediction and interpretation, which may lead to unexpected obstacles to biological researchers. RESULTS: To address these issues, we here present DrugMGR, a deep multigranular drug representation model capable of predicting binding affinities and regions for each ligand-target pair. We conduct consistent experiments on three benchmark datasets using existing methods and introduce a new specific dataset to better validate the prediction of binding sites. For practical application, target-specific compound identification tasks are also carried out to validate the capability of real-world compound screen. Moreover, the visualization of some practical interaction scenarios provides interpretable insights from the results of the predictions. The proposed DrugMGR achieves excellent overall performance in these datasets, exhibiting its advantages and merits against state-of-the-art methods. Thus, the downstream task of DrugMGR can be fine-tuned for identifying the potential compounds that target proteins for clinical treatment. AVAILABILITY AND IMPLEMENTATION: https://github.com/lixiaokun2020/DrugMGR.

Sufficient potassium improves inorganic phosphate-limited photosynthesis in Brassica napus by enhancing metabolic phosphorus fractions and Rubisco activity.

Crop photosynthesis (A) and productivity are often limited by a combination of nutrient stresses, such that changes in the availability of one nutrient may affect the availability of another nutrient, in turn influencing A. In this study, we examined the synergistic effects of phosphorus (P) and potassium (K) on leaf A in a nutrient amendment experiment, in which P and K were added individually or in combination to Brassica napus grown under P and K co-limitation. The data revealed that the addition of P gradually removed the dominant limiting factor (i.e. the limited availability of P) and improved leaf A. Strikingly, the addition of K synergistically improved the overall uptake of P, mainly by boosting plant growth, and compensated for the physiological demand for P by prioritizing investment in metabolic pools of P (P-containing metabolites and inorganic phosphate, Pi). The enlarged pool of metabolically active P was partially associated with the upregulation of Pi regeneration through release from triose phosphates rather than replacement of P-containing lipids. This process mitigated P restrictions on A by maintaining the ATP/NADPH and NADPH/NADP+ ratios and increasing the content and activity of Rubisco. Our findings demonstrate that sufficient K increased Pi-limited A by enhancing metabolic P fractions and Rubisco activity. Thus, ionic synergism may be exploited to mitigate nutrient-limiting factors to improve crop productivity.

The Carthamus tinctorius L. genome sequence provides insights into synthesis of unsaturated fatty acids.

Domesticated safflower (Carthamus tinctorius L.) is a widely cultivated edible oil crop. However, despite its economic importance, the genetic basis underlying key traits such as oil content, resistance to biotic and abiotic stresses, and flowering time remains poorly understood. Here, we present the genome assembly for C. tinctorius variety Jihong01, which was obtained by integrating Oxford Nanopore Technologies (ONT) and BGI-SEQ500 sequencing results. The assembled genome was 1,061.1 Mb, and consisted of 32,379 protein-coding genes, 97.71% of which were functionally annotated. Safflower had a recent whole genome duplication (WGD) event in evolution history and diverged from sunflower approximately 37.3 million years ago. Through comparative genomic analysis at five seed development stages, we unveiled the pivotal roles of fatty acid desaturase 2 (FAD2) and fatty acid desaturase 6 (FAD6) in linoleic acid (LA) biosynthesis. Similarly, the differential gene expression analysis further reinforced the significance of these genes in regulating LA accumulation. Moreover, our investigation of seed fatty acid composition at different seed developmental stages unveiled the crucial roles of FAD2 and FAD6 in LA biosynthesis. These findings offer important insights into enhancing breeding programs for the improvement of quality traits and provide reference resource for further research on the natural properties of safflower.

Targeting the FGF19-FGFR4 pathway for cholestatic, metabolic, and cancerous diseases.

Human fibroblast growth factor 19 (FGF19, or FGF15 in rodents) plays a central role in controlling bile acid (BA) synthesis through a negative feedback mechanism. This process involves a postprandial crosstalk between the BA-activated ileal farnesoid X receptor and the hepatic Klotho beta (KLB) coreceptor complexed with fibrobalst growth factor receptor 4 (FGFR4) kinase. Additionally, FGF19 regulates glucose, lipid, and energy metabolism by coordinating responses from functional KLB and FGFR1-3 receptor complexes on the periphery. Pharmacologically, native FGF19 or its analogs decrease elevated BA levels, fat content, and collateral tissue damage. This makes them effective in treating both cholestatic diseases such as primary biliary or sclerosing cholangitis (PBC or PSC) and metabolic abnormalities such as nonalcoholic steatohepatitis (NASH). However, chronic administration of FGF19 drives oncogenesis in mice by activating the FGFR4-dependent mitogenic or hepatic regenerative pathway, which could be a concern in humans. Agents that block FGF19 or FGFR4 signaling have shown great potency in preventing FGF19-responsive hepatocellular carcinoma (HCC) development in animal models. Recent phase 1/2 clinical trials have demonstrated promising results for several FGF19-based agents in selectively treating patients with PBC, PSC, NASH, or HCC. This review aims to provide an update on the clinical development of both analogs and antagonists targeting the FGF19-FGFR4 signaling pathway for patients with cholestatic, metabolic, and cancer diseases. We will also analyze potential safety and mechanistic concerns that should guide future research and advanced trials.

Multifunctional Biodegradable Conductive Hydrogel Regulating Microenvironment for Stem Cell Therapy Enhances the Nerve Tissue Repair.

The nerve guidance conduits incorporated with stem cells, which can differentiate into the Schwann cells (SCs) to facilitate myelination, shows great promise for repairing the severe peripheral nerve injury. The innovation of advanced hydrogel materials encapsulating stem cells, is highly demanded for generating supportive scaffolds and adaptive microenvironment for nerve regeneration. Herein, this work demonstrates a novel strategy in regulating regenerative microenvironment for peripheral nerve repair with a biodegradable conductive hydrogel scaffold, which can offer multifunctional capabilities in immune regulation, enhancing angiogenesis, driving SCs differentiation, and promoting axon regrowth. The biodegradable conductive hydrogel is constructed by incorporation of polydopamine-modified silicon phosphorus (SiP@PDA) nanosheets into a mixture of methacryloyl gelatin and decellularized extracellular matrix (GelMA/ECM). The biomimetic electrical microenvironment performs an efficacious strategy to facilitate macrophage polarization toward a pro-healing phenotype (M2), meanwhile the conductive hydrogel supports vascularization in regenerated tissue through sustained Si element release. Furthermore, the MSCs 3D-cultured in GelMA/ECM-SiP@PDA conductive hydrogel exhibits significantly increased expression of genes associated with SC-like cell differentiation, thus facilitating the myelination and axonal regeneration. Collectively, both the in vitro and in vivo studies demonstrates that the rationally designed biodegradable multifunctional hydrogel significantly enhances nerve tissues repair.

Microneedle Patch for Transdermal Sequential Delivery of KGF-2 and aFGF to Enhance Burn Wound Therapy.

Severe burn wounds usually destroy key cells' functions of the skin resulting in delayed re-epithelization and wound regeneration. Promoting key cells' activities is crucial for burn wound repair. It is well known that keratinocyte growth factor-2 (KGF-2) participates in the proliferation and morphogenesis of epithelial cells while acidic fibroblast growth factor (aFGF) is a key mediator for fibroblast and endothelial cell growth and differentiation. However, thick eschar and the harsh environment of a burn wound often decrease the delivery efficiency of fibroblast growth factor (FGF) to the wound site. Therefore, herein a novel microneedle patch for sequential transdermal delivery of KGF-2 and aFGF is fabricated to enhance burn wound therapy. aFGF is first loaded in the nanoparticle (NPaFGF) and then encapsulated NPaFGF with KGF-2 in the microneedle patch (KGF-2/NPaFGF@MN). The result shows that KGF-2/NPaFGF@MN can successfully get across the eschar and sequentially release KGF-2 and aFGF. Additional data demonstrated that KGF-2/NPaFGF@MN achieved a quicker wound closure rate with reduced necrotic tissues, faster re-epithelialization, enhanced collagen deposition, and increased neo-vascularization. Further evidence suggests that improved wound healing is regulated by significantly elevated expressions of hypoxia-inducible factor-1 alpha (HIF-1ɑ) and heat shock protein 90 (Hsp90) in burn wounds. All these data proved that KGF-2/NPaFGF@MN is an effective treatment for wound healing of burns.

Macrophage-specific FGF12 promotes liver fibrosis progression in mice.

BACKGROUND AND AIMS: Chronic liver diseases are associated with the development of liver fibrosis. Without treatment, liver fibrosis commonly leads to cirrhosis and HCC. FGF12 is an intracrine factor belonging to the FGF superfamily, but its role in liver homeostasis is largely unknown. This study aimed to investigate the role of FGF12 in the regulation of liver fibrosis. APPROACH AND RESULTS: FGF12 was up-regulated in bile duct ligation (BDL)-induced and CCL 4 -induced liver fibrosis mouse models. Expression of FGF12 was specifically up-regulated in nonparenchymal liver cells, especially in hepatic macrophages. By constructing myeloid-specific FGF12 knockout mice, we found that deletion of FGF12 in macrophages protected against BDL-induced and CCL 4 -induced liver fibrosis. Further results revealed that FGF12 deletion dramatically decreased the population of lymphocyte antigen 6 complex locus C high macrophages in mouse fibrotic liver tissue and reduced the expression of proinflammatory cytokines and chemokines. Meanwhile, loss-of-function and gain-of-function approaches revealed that FGF12 promoted the proinflammatory activation of macrophages, thus inducing HSC activation mainly through the monocyte chemoattractant protein-1/chemokine (C-C motif) receptor 2 axis. Further experiments indicated that the regulation of macrophage activation by FGF12 was mainly mediated through the Janus kinase-signal transducer of activators of transcription pathway. Finally, the results revealed that FGF12 expression correlates with the severity of fibrosis across the spectrum of fibrogenesis in human liver samples. CONCLUSIONS: FGF12 promotes liver fibrosis progression. Therapeutic approaches to inhibit macrophage FGF12 may be used to combat liver fibrosis in the future.

Impact of Skeletal Muscle Loss and Sarcopenia on Outcomes of Locally Advanced Esophageal Cancer during Neoadjuvant Chemoradiation.

BACKGROUND: The impact of changes in skeletal muscle and sarcopenia on outcomes during neoadjuvant chemoradiotherapy (NACR) for patients with esophageal cancer remains controversial. PATIENTS AND METHODS: We retrospectively analyzed the data of patients with locally advanced esophageal squamous cell cancer who received NACR followed by esophagectomy between June 2013 and December 2021. The images at third lumbar vertebra were analyzed to measure the cross-sectional area and calculate skeletal muscle index (SMI) before and after NACR. SMI less than 52.4 cm2/m2 for men and less than 38.5 cm2/m2 for women were defined as sarcopenia. The nonlinearity of the effect of percent changes in SMI (ΔSMI%) to survival outcomes was assessed by restricted cubic splines. RESULTS: Overall, data of 367 patients were analyzed. The survival outcomes between sarcopenia and non-sarcopenia groups had no significant differences before NACR. However, patients in post-NACR sarcopenia group showed poor overall survival (OS) benefit (P = 0.016) and poor disease-free survival (DFS) (P = 0.043). Severe postoperative complication rates were 11.9% in post-NACR sarcopenia group and 5.0% in post-NACR non-sarcopenia group (P = 0.019). There was a significant non-linear relationship between ΔSMI% and survival outcomes (P < 0.05 for non-linear). On the multivariable analysis of OS, ΔSMI% > 12% was the independent prognostic factor (HR 1.76, 95% CI 1.03-2.99, P = 0.039) and significant difference was also found on DFS analysis (P = 0.025). CONCLUSIONS: Patients with post-neoadjuvant chemoradiotherapy sarcopenia have worse survival and adverse short-term outcomes. Moreover, greater loss in SMI is associated with increased risks of death and disease progression during neoadjuvant chemoradiotherapy, with maximum impact noted with SMI loss greater than 12%.

FGF1 ameliorates obesity-associated hepatic steatosis by reversing IGFBP2 hypermethylation.

Obesity is a major contributing factor for metabolic-associated fatty liver disease (MAFLD). Fibroblast growth factor (FGF) 1 is the first paracrine FGF family member identified to exhibit promising metabolic regulatory properties capable of conferring glucose-lowering and insulin-sensitizing effect. This study explores the role and molecular underpinnings of FGF1 in obesity-associated hepatic steatosis. In a mouse high-fat diet (HFD)-induced MAFLD model, chronic treatment with recombinant FGF1(rFGF1) was found to effectively reduce the severity of insulin resistance, hyperlipidemia, and inflammation. FGF1 treatment decreased lipid accumulation in the mouse liver and palmitic acid-treated AML12 cells. These effects were associated with decreased mature form SREBF1 expression and its target genes FASN and SCD1. Interestingly, we uncovered that rFGF1 significantly induced IGFBP2 expression at both mRNA and protein levels in HFD-fed mouse livers and cultured hepatocytes treated with palmitic acid. Adeno-associated virus-mediated IGFBP2 suppression significantly diminished the therapeutic benefit of rFGF1 on MAFLD-associated phenotypes, indicating that IGFBP2 plays a crucial role in the FGF1-mediated reduction of hepatic steatosis. Further analysis revealed that rFGF1 treatment reduces the recruitment of DNA methyltransferase 3 alpha to the IGFBP2 genomic locus, leading to decreased IGFBP2 gene methylation and increased mRNA and protein expression. Collectively, our findings reveal FGF1 modulation of lipid metabolism via epigenetic regulation of IGFBP2 expression, and unravel the therapeutic potential of the FGF1-IGFBP2 axis in metabolic diseases associated with obesity.

Potassium deficiency enhances imbalances in rice water relations under water deficit by decreasing leaf hydraulic conductance.

Potassium (K+) is an essential macronutrient for appropriate plant development and physiology. However, little is known about the mechanisms involved in the regulation of leaf water relations by K under water deficit. A pot experiment with two K supplies of 0.45 and 0 g K2O per pot (3 kg soil per pot) and two watering conditions (well-watered and water-deficit) was conducted to explore the effects of K deficiency on canopy transpiration characteristics, leaf water status, photosynthesis, and hydraulic traits in two rice genotypes with contrasting resistance to drought. The results showed that K deficiency reduced canopy transpiration rate by decreasing stomatal conductance, which led to higher canopy temperatures, resulting in limited water deficit tolerance in rice. In addition, K deficiency led to further substantial reductions in leaf relative water content and water potential under water deficit, which increased the imbalance in leaf water relations under water deficit. Notably, K deficiency limited leaf gas exchange by reducing leaf hydraulic conductance, but decreased the intrinsic water use efficiency under water deficit, especially for the drought-resistant cultivar. Further analysis of the underlying process of leaf hydraulic resistance revealed that the key limiting factor of leaf hydraulic conductance under K deficiency was the outside-xylem hydraulic conductance rather than the xylem hydraulic conductance. Overall, our results provide a comprehensive perspective for assessing leaf water relations under K deficiency, water deficit, and their combined stresses, which will be useful for optimal rice fertilization strategies.

MTHFD1L confers a poor prognosis and malignant phenotype in esophageal squamous cell carcinoma by activating the ERK5 signaling pathway.

MTHFD1L, a key enzyme of folate metabolism, is seldom reported in cancer. In this study, we investigate the role of MTHFD1L in the tumorigenicity of esophageal squamous cell carcinoma (ESCC). ESCC tissue microarrays (TMAs) containing 177 samples from 109 patients were utilized to evaluate whether MTHFD1L expression, determined using immunohistochemical analysis, is a prognostic indicator for ESCC patients. The function of MTHFD1L in the migration and invasion of ESCC cells was studied with wound healing, Transwell, and three-dimensional spheroid invasion assays in vitro and a lung metastasis mouse model in vivo. The mRNA microarrays and Ingenuity pathway analysis (IPA) were used to explore the downstream of MTHFD1L. Elevated expression of MTHFD1L in ESCC tissues was significantly associated with poor differentiation and prognosis. These phenotypic assays revealed that MTHFD1L significantly promote the viability and metastasis of ESCC cell in vivo and in vitro. Further detailed analyses of the molecular mechanism demonstrated that the ESCC progression driven by MTHFD1L was through up-regulation ERK5 signaling pathways. These findings reveal that MTHFD1L is positively associated with the aggressive phenotype of ESCC by activating ERK5 signaling pathways, suggesting that MTHFD1L is a new biomarker and a potential molecular therapeutic target for ESCC.

α-Klotho is a non-enzymatic molecular scaffold for FGF23 hormone signalling.

The ageing suppressor α-klotho binds to the fibroblast growth factor receptor (FGFR). This commits FGFR to respond to FGF23, a key hormone in the regulation of mineral ion and vitamin D homeostasis. The role and mechanism of this co-receptor are unknown. Here we present the atomic structure of a 1:1:1 ternary complex that consists of the shed extracellular domain of α-klotho, the FGFR1c ligand-binding domain, and FGF23. In this complex, α-klotho simultaneously tethers FGFR1c by its D3 domain and FGF23 by its C-terminal tail, thus implementing FGF23-FGFR1c proximity and conferring stability. Dimerization of the stabilized ternary complexes and receptor activation remain dependent on the binding of heparan sulfate, a mandatory cofactor of paracrine FGF signalling. The structure of α-klotho is incompatible with its purported glycosidase activity. Thus, shed α-klotho functions as an on-demand non-enzymatic scaffold protein that promotes FGF23 signalling.

Two FGF Receptor Kinase Molecules Act in Concert to Recruit and Transphosphorylate Phospholipase Cγ.

The molecular basis by which receptor tyrosine kinases (RTKs) recruit and phosphorylate Src Homology 2 (SH2) domain-containing substrates has remained elusive. We used X-ray crystallography, NMR spectroscopy, and cell-based assays to demonstrate that recruitment and phosphorylation of Phospholipase Cγ (PLCγ), a prototypical SH2 containing substrate, by FGF receptors (FGFR) entails formation of an allosteric 2:1 FGFR-PLCγ complex. We show that the engagement of pTyr-binding pocket of the cSH2 domain of PLCγ by the phosphorylated tail of an FGFR kinase induces a conformational change at the region past the cSH2 core domain encompassing Tyr-771 and Tyr-783 to facilitate the binding/phosphorylation of these tyrosines by another FGFR kinase in trans. Our data overturn the current paradigm that recruitment and phosphorylation of substrates are carried out by the same RTK monomer in cis and disclose an obligatory role for receptor dimerization in substrate phosphorylation in addition to its canonical role in kinase activation.

Study on the Consistency Between Automatic Measurement Based on Convolutional Neural Network Technology and Manual Visual Evaluation in Intracavitary Ultrasonic Cine of Anterior Pelvic.

OBJECTIVES: This study was to evaluate the application of automatic measurement based on convolutional neural network (CNN) technology in intracavitary ultrasound cine of anterior pelvic. METHODS: A total of 500 patients who underwent pelvic floor ultrasound examination at Peking University Shenzhen Hospital from July 2021 to February 2022 were retrospectively retrieved by the picture archiving and communication system (PACS) system, and 300 cases were used as a training set. The training set was labeled by three experienced ultrasound physicians to train CNN models and develop an automatic measurement software. The remaining 200 cases were used as a test set. Automatic measurement software identified relevant anatomical structures frame by frame and determined the two frames with the greatest difference, calculated the bladder neck descent (BND), urethral rotation angle (URA), and retrovesical angle (RA). Meanwhile, two experienced ultrasound physicians evaluated the resting frame and the maximum Valsalva frame on the cines by manual visual evaluation, labeled the anatomical structures in the corresponding frame, such as the inferoposterior margin of pubic symphysis, the mid-axis of pubic symphysis, bladder contour, and urethra in the front, and calculated BND, URA, and RA. Considering that the residual urine volume (RUV) in the bladder may affect the results, enrolled patients were grouped according to the RUV (10-50 mL, 50-100 mL, and >100 mL). The consistency of the results by automatic measurement and manual visual evaluation was evaluated using the intraclass correlation coefficient (ICC) and the Bland-Altman graph. RESULTS: Of the 200 cases in the test set, 120 cases were successfully identified by the CNN automatic software with a 60% recognition rate. In the case of successful identification, the ICC of manual visual evaluation measurement and automatic measurement was 0.936 (BND), 0.911 (URA), 0.756 (RA in rest), and 0.877 (RA at maximum Valsalva), respectively. In addition, the RUV had a negligible effect on the consistency. The Bland-Altman plot shows the proportion of samples outside the limit was below 5%. CONCLUSIONS: CNN-based automatic measurement software exhibited high reliability in anterior pelvic measurement, which results in a significantly enhanced measurement efficiency.

Calcineurin controls proximodistal blastema polarity in zebrafish fin regeneration.

Planarian flatworms regenerate their heads and tails from anterior or posterior wounds and this regenerative blastema polarity is controlled by Wnt/ß-catenin signaling. It is well known that a regeneration blastema of appendages of vertebrates such as fish and amphibians grows distally. However, it remains unclear whether a regeneration blastema in vertebrate appendages can grow proximally. Here, we show that a regeneration blastema in zebrafish fins can grow proximally along the proximodistal axis by calcineurin inhibition. We used fin excavation in adult zebrafish to observe unidirectional regeneration from the anterior cut edge (ACE) to the posterior cut edge (PCE) of the cavity and this unidirectional regeneration polarity occurs as the PCE fails to build blastemas. Furthermore, we found that calcineurin activities in the ACE were greater than in the PCE. Calcineurin inhibition induced PCE blastemas, and calcineurin hyperactivation suppressed fin regeneration. Collectively, these findings identify calcineurin as a molecular switch to specify the PCE blastema of the proximodistal axis and regeneration polarity in zebrafish fin.