Diagnostic Value of Hepcidin in Sepsis: A Systematic Review and Meta-Analysis.

Objectives: To investigate the diagnostic value of hepcidin for sepsis diagnosis. Methods: The relevant literature on hepcidin for sepsis diagnosis published up to October 20, 2023, was systematically searched in the Web of Science, PubMed, Embase, and China Knowledge Network databases. Two researchers screened the literature and extracted relevant data according to the inclusion and exclusion criteria. Study quality was evaluated using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Meta-analysis and calculation of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were performed using State16 and Review Manager 5.3 software. Furthermore, receiver operating characteristic curve (ROC) was plotted, and the respective area under the curve (AUC) was calculated to assess the accuracy of hepcidin. Publication bias was evaluated using Deeks' funnel plot asymmetry test. Results: Overall, 1047 patients from 8 studies were included (625 patients with sepsis and 422 controls). The quality of the literature was relatively moderate. Meta-analysis demonstrated the presence of heterogeneity in the data (I2 > 50%, P < .05), and a randomized model was employed to combine the diagnostic indicators. Regarding its accuracy for sepsis diagnosis, hepcidin demonstrated a pooled sensitivity of 0.88 (95% confidence interval [CI]: 0.76-0.94) and specificity of 0.91 (95% CI: 0.76-0.97). The diagnostic odds ratio was 69.00 (95% CI: 19.00-253.00), and the ROC curve revealed an AUC of 0.95. Additionally, Deeks' funnel plot asymmetry test demonstrated absence of publication bias. Conclusions: Our meta-analysis suggested that hepcidin has a high diagnostic value in sepsis and may be a valuable diagnostic tool.

Human tactile sensing and sensorimotor mechanism: from afferent tactile signals to efferent motor control.

In tactile sensing, decoding the journey from afferent tactile signals to efferent motor commands is a significant challenge primarily due to the difficulty in capturing population-level afferent nerve signals during active touch. This study integrates a finite element hand model with a neural dynamic model by using microneurography data to predict neural responses based on contact biomechanics and membrane transduction dynamics. This research focuses specifically on tactile sensation and its direct translation into motor actions. Evaluations of muscle synergy during in -vivo experiments revealed transduction functions linking tactile signals and muscle activation. These functions suggest similar sensorimotor strategies for grasping influenced by object size and weight. The decoded transduction mechanism was validated by restoring human-like sensorimotor performance on a tendon-driven biomimetic hand. This research advances our understanding of translating tactile sensation into motor actions, offering valuable insights into prosthetic design, robotics, and the development of next-generation prosthetics with neuromorphic tactile feedback.

Machine learning predicts conventional imaging metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) using prostate-specific membrane antigen (PSMA) PET radiomics.

PURPOSE: This study investigated imaging biomarkers derived from PSMA-PET acquired pre- and post-metastasis-directed therapy (MDT) to predict 2-year metastasis-free survival (MFS), which provides valuable early response assessment to improve patient outcomes. MATERIALS/METHODS: An international cohort of 117 oligometastatic castration-sensitive prostate cancer (omCSPC) patients, comprising 34 from John Hopkins Hospital (JHH) and 83 from Baskent University (BU), were treated with stereotactic ablative radiation therapy (SABR) MDT with both pre- and post-MDT PSMA-PET/CT scans acquired. PET radiomic features were analyzed from a CT-PET fusion defined gross tumor volume ((GTV) or zone 1), and a 5 mm expansion ring area outside the GTV (zone 2). A total of 1748 PET radiomic features were extracted from these zones. The six most significant features selected using the Chi2 method, along with five clinical parameters (age, Gleason score, number of total lesions, untreated lesions, and pre-MDT prostate-specific antigen (PSA)) were extracted as inputs to the models. Various machine learning models, including Random Forest, Decision Tree, Support Vector Machine, and Naïve Bayesian, were employed for 2-year MFS prediction and tested using leave-one-out and cross-institution validation. RESULTS: Six radiomic features, including Total Energy, Entropy, and Standard Deviation from pre-PSMA-PET zone 1, Total Energy and Contrast from post-PSMA-PET zone 1, and Entropy from pre-PSMA-PET zone 2, along with five clinical parameters were selected for predicting 2-year MFS. In a leave-one-out test with all the patients, random forest achieved an accuracy of 80 % and an AUC of 0.82 in predicting 2-year MFS. In cross-institution validation, the model correctly predicted 2-year MFS events with an accuracy of 75 % and an AUC of 0.77 for patients from JHH, and an accuracy of 78 % and an AUC of 0.80 for BU patients, respectively. CONCLUSION: Our study demonstrated the promise of using pre- and post-MDT PSMA-PET-based imaging biomarkers for MFS prediction for omCSPC patients.

Integration of PSAd and multiparametric MRI to forecast biopsy outcomes in biopsy-naïve patients with PSA 4~20 ng/ml.

Introduction: This study aims to investigate whether the transrectal ultrasound-guided combined biopsy (CB) improves the detection rates of prostate cancer (PCa) and clinically significant PCa (csPCa) in biopsy-naïve patients. We also aimed to compare the Prostate Imaging Reporting and Data System (PI-RADS v2.1) score, ADC values, and PSA density (PSAd) in predicting csPCa by the combined prostate biopsy. Methods: This retrospective and single-center study included 389 biopsy-naïve patients with PSA level 4~20 ng/ml, of whom 197 underwent prebiopsy mpMRI of the prostate. The mpMRI-based scores (PI-RADS v2.1 scores and ADC values) and clinical parameters were collected and evaluated by logistic regression analyses. Multivariable models based on the mpMRI-based scores and clinical parameters were developed by the logistic regression analyses to forecast biopsy outcomes of CB in biopsy-naïve patients. The ROC curves measured by the AUC values, calibration plots, and DCA were performed to assess multivariable models. Results: The CB can detect more csPCa compared with TRUSB (32.0% vs. 53%). The Spearman correlation revealed that Gleason scores of the prostate biopsy significantly correlated with PI-RADS scores and ADC values. The multivariate logistic regression confirmed that PI-RADS scores 4, 5, and prostate volume were important predictors of csPCa. The PI-RADS+ADC+PSAd (PAP) model had the highest AUCs of 0.913 for predicting csPCa in biopsy-naïve patients with PSA level 4~20 ng/ml. When the biopsy risk threshold of the PAP model was greater than or equal to 0.10, 51% of patients could avoid an unnecessary biopsy, and only 5% of patients with csPCa were missed. Conclusion: The prebiopsy mpMRI and the combined prostate biopsy have a high CDR of csPCa in biopsy-naïve patients. A multivariable model based on the mpMRI-based scores and PSAd could provide a reference for clinicians in forecasting biopsy outcomes in biopsy-naïve patients with PSA 4~20 ng/ml and make a more comprehensive assessment during the decision-making of the prostate biopsy.

Tissue engineering strategies for spiral ganglion neuron protection and regeneration.

Cochlear implants can directly activate the auditory system's primary sensory neurons, the spiral ganglion neurons (SGNs), via circumvention of defective cochlear hair cells. This bypass restores auditory input to the brainstem. SGN loss etiologies are complex, with limited mammalian regeneration. Protecting and revitalizing SGN is critical. Tissue engineering offers a novel therapeutic strategy, utilizing seed cells, biomolecules, and scaffold materials to create a cellular environment and regulate molecular cues. This review encapsulates the spectrum of both human and animal research, collating the factors contributing to SGN loss, the latest advancements in the utilization of exogenous stem cells for auditory nerve repair and preservation, the taxonomy and mechanism of action of standard biomolecules, and the architectural components of scaffold materials tailored for the inner ear. Furthermore, we delineate the potential and benefits of the biohybrid neural interface, an incipient technology in the realm of implantable devices. Nonetheless, tissue engineering requires refined cell selection and differentiation protocols for consistent SGN quality. In addition, strategies to improve stem cell survival, scaffold biocompatibility, and molecular cue timing are essential for biohybrid neural interface integration.

Patient-specific deep learning for 3D protoacoustic image reconstruction and dose verification in proton therapy.

BACKGROUND: Protoacoustic (PA) imaging has the potential to provide real-time 3D dose verification of proton therapy. However, PA images are susceptible to severe distortion due to limited angle acquisition. Our previous studies showed the potential of using deep learning to enhance PA images. As the model was trained using a limited number of patients' data, its efficacy was limited when applied to individual patients. PURPOSE: In this study, we developed a patient-specific deep learning method for protoacoustic imaging to improve the reconstruction quality of protoacoustic imaging and the accuracy of dose verification for individual patients. METHODS: Our method consists of two stages: in the first stage, a group model is trained from a diverse training set containing all patients, where a novel deep learning network is employed to directly reconstruct the initial pressure maps from the radiofrequency (RF) signals; in the second stage, we apply transfer learning on the pre-trained group model using patient-specific dataset derived from a novel data augmentation method to tune it into a patient-specific model. Raw PA signals were simulated based on computed tomography (CT) images and the pressure map derived from the planned dose. The reconstructed PA images were evaluated against the ground truth by using the root mean squared errors (RMSE), structural similarity index measure (SSIM) and gamma index on 10 specific prostate cancer patients. The significance level was evaluated by t-test with the p-value threshold of 0.05 compared with the results from the group model. RESULTS: The patient-specific model achieved an average RMSE of 0.014 ( p < 0.05 ${{{p}}}<{0.05}$ ), and an average SSIM of 0.981 ( p < 0.05 ${{{p}}}<{0.05}$ ), out-performing the group model. Qualitative results also demonstrated that our patient-specific approach acquired better imaging quality with more details reconstructed when comparing with the group model. Dose verification achieved an average RMSE of 0.011 ( p < 0.05 ${{{p}}}<{0.05}$ ), and an average SSIM of 0.995 ( p < 0.05 ${{{p}}}<{0.05}$ ). Gamma index evaluation demonstrated a high agreement (97.4% [ p < 0.05 ${{{p}}}<{0.05}$ ] and 97.9% [ p < 0.05 ${{{p}}}<{0.05}$ ] for 1%/3  and 1%/5 mm) between the predicted and the ground truth dose maps. Our approach approximately took 6 s to reconstruct PA images for each patient, demonstrating its feasibility for online 3D dose verification for prostate proton therapy. CONCLUSIONS: Our method demonstrated the feasibility of achieving 3D high-precision PA-based dose verification using patient-specific deep-learning approaches, which can potentially be used to guide the treatment to mitigate the impact of range uncertainty and improve the precision. Further studies are needed to validate the clinical impact of the technique.

Hyaluronic acid-conjugated methotrexate and 5-fluorouracil for targeted drug delivery.

The delivery of chemotherapeutical drugs via nanomaterials has become a focus of pharmaceutical research over several decades due to improved drug delivery to cancer cells, decreased side effects on normal tissues, and increased therapeutic efficacy. Herein, a novel hyaluronic acid-conjugated methotrexate and 5-fluorouracil nanodrug system has been developed to address the critical limitations associated with the high toxicity and side effects of methotrexate and 5-fluorouracil. Furthermore, this nanodrug system enhances the targeting capacity of drug molecules and facilitates the potential integration of multimodal drug therapies. Concomitantly, the synergistic effects of MTX with 5-fluorouracil have been shown to improve the therapeutic index of MTX while attenuating the associated toxicities of MTX. The structure and micromorphology of the novel nanodrug can be confirmed by 1HNMR, FT-IR, UV-Vis, DLS, TEM, and AFM. Due to the ability of HA to bind to CD44 receptors activated on the surface of cancer cells and its enhanced permeability and retention (EPR) effect, the novel nanodrug we designed and synthesized can effectively target cancer cells. Cell counting Kit-8 (CCK8), flow cytometry, and live-dead staining assays in vitro showed that this nanodrug system had high targeting and antitumor activity against CD44 receptors. By using drugs to act on patient-derived colorectal, liver, and breast cancer organoids, the anticancer effect of the nanodrug was identified and verified. These results showed that the nanodrug system developed in this study may have great potential as a targeted therapy for cancer.

Genomic Determinants Associated with Modes of Progression and Patterns of Failure in Metachronous Oligometastatic Castration-sensitive Prostate Cancer.

BACKGROUND AND OBJECTIVE: Oligometastatic castration-sensitive prostate cancer (omCSPC) represents an early state in the progression of metastatic disease for which patients experience better outcomes in comparison to those with higher disease burden. Despite the generally more indolent nature, there is still much heterogeneity, with some patients experiencing a more aggressive clinical course unexplained by clinical features alone. Our aim was to investigate correlation of tumor genomics with the mode of progression (MOP) and pattern of failure (POF) following first treatment (metastasis-directed and/or systemic therapy) for omCSPC. METHODS: We performed an international multi-institutional retrospective study of men treated for metachronous omCSPC who underwent tumor next-generation sequencing with at least 1 yr of follow-up after their first treatment. Descriptive MOP and POF results are reported with respect to the presence of genomic alterations in pathways of interest. MOP was defined as class I, long-term control (LTC; no radiographic progression at last follow-up), class II, oligoprogression (1-3 lesions), or class III, polyprogression (≥4 lesions). POF included the location of lesions at first failure. Genomic pathways of interest included TP53, ATM, RB1, BRCA1/2, SPOP, and WNT (APC, CTNNB1, RNF43). Genomic associations with MOP/POF were compared using χ2 tests. Exploratory analyses revealed that the COSMIC mutational signature and differential gene expression were also correlated with MOP/POF. Overall survival (OS) was calculated via the Kaplan-Meier method from the time of first failure. KEY FINDINGS AND CLINICAL IMPLICATIONS: We included 267 patients in our analysis; the majority had either one (47%) or two (30%) metastatic lesions at oligometastasis. The 3-yr OS rate was significantly associated with MOP (71% for polyprogression vs 91% for oligoprogression; p = 0.005). TP53 mutation was associated with a significantly lower LTC rate (27.6% vs 42.3%; p = 0.04) and RB1 mutation was associated with a high rate of polyprogression (50% vs 19.9%; p = 0.022). Regarding POF, bone failure was significantly more common with tumors harboring TP53 mutations (44.8% vs25.9%; p = 0.005) and less common with SPOP mutations (7.1% vs 31.4%; p = 0.007). Visceral failure was more common with tumors harboring either WNT pathway mutations (17.2% vs 6.8%, p = 0.05) or SPOP mutations (17.9% vs 6.3%; p = 0.04). Finally, visceral and bone failures were associated with distinct gene-expression profiles. CONCLUSIONS AND CLINICAL IMPLICATIONS: Tumor genomics provides novel insight into MOP and POF following treatment for metachronous omCSPC. Patients with TP53 and RB1 mutations have a higher likelihood of progression, and TP53, SPOP, and WNT pathway mutations may have a role in metastatic organotropism. PATIENT SUMMARY: We evaluated cancer progression after a first treatment for metastatic prostate cancer with up to five metastases. We found that mutations in certain genes were associated with the location and extent of further metastasis in these patients.

Tumor-Associated Myeloid Cells Selective Delivery of a Therapeutic Tumor Nano-Vaccine for Overcoming Immune Barriers for Effective and Long-Term Cancer Immunotherapy.

Therapeutic cancer vaccines have the potential to induce regression of established tumors, eradicate microscopic residual lesions, and prevent metastasis and recurrence, but their efficacy is limited by the low antigenicity of soluble antigens and the immunosuppressive tumor-associated macrophages (TAMs) that promote tumor growth. In this study, a novel strategy is reported for overcoming these defenses: a dual-targeting nano-vaccine (NV) based on hepatitis B core antigen (HBcAg) derived virus-like particles (VLPs), N-M2T-gp100 HBc NV, equipped with both SIGNR+ dendritic cells (DCs)/TAMs-targeting ability and high-density display of tumor-associated antigen (TAA). N-M2T-gp100 HBc NVs-based immunotherapy has demonstrated an optimal interaction between tumor-associated antigens (TAAs) and the immune composition of the tumor microenvironment. In a melanoma model, N-M2T-gp100 HBc VLPs significantly reducing in situ and abscopal tumor growth, and provide long-term immune protection. This remarkable anti-tumor effect is achieved by efficiently boosting of T cells and repolarizing of M2-like TAMs. This work opens exciting avenues for the development of personalized tumor vaccines targeting not just melanoma but potentially a broad range of cancer types based on functionalized VLPs.

Examining network structure of impulsivity and depression in adolescents and young adults: A two-sample study.

BACKGROUND: Depression ranks as one of the top five contributors to ill health in youth, the most formative period in life. Extensive research has highlighted the significant role of impulsivity in understanding depression. However, there has been limited exploration into how each dimension of impulsivity uniquely affect depressive symptoms, especially across crucial developmental stages like adolescence and young adulthood. METHODS: This study investigates the unique relationships between impulsivity (assessed by the short UPPS-P scale) and depression (assessed by the Patient Health Questionnaire-9) via network analysis. We analysed data from a total of 2296 participants, comprising 858 adolescents aged 14-17 years and 1438 young adults aged 18-25 years, to estimate both a combined network and age-group specific networks. Key features of the networks, including their structure, global connectivity, and bridge nodes, were compared. RESULTS: The results indicated that age differentially impacts individual depression symptoms, both directly and indirectly, via impulsivity dimensions. The comparison test revealed consistent network structures between the two age groups, with several robust pathways, such as lack of perseverance to concentration difficulties, sensation seeking to suicidal ideation, and negative urgency to feelings of worthlessness. Negative urgency and lack of perseverance were identified as bridge nodes across the two networks. LIMITATIONS: The study employed a cross-sectional design, which limits the ability to estimate causal or temporal relationships. CONCLUSIONS: The current findings highlight the significance of tailoring intervention strategies to individual symptom profiles and assessing negative urgency and lack of perseverance as potential early targets for depression among youth.

A review on 4D cone-beam CT (4D-CBCT) in radiation therapy: Technical advances and clinical applications.

Cone-beam CT (CBCT) is the most commonly used onboard imaging technique for target localization in radiation therapy. Conventional 3D CBCT acquires x-ray cone-beam projections at multiple angles around the patient to reconstruct 3D images of the patient in the treatment room. However, despite its wide usage, 3D CBCT is limited in imaging disease sites affected by respiratory motions or other dynamic changes within the body, as it lacks time-resolved information. To overcome this limitation, 4D-CBCT was developed to incorporate a time dimension in the imaging to account for the patient's motion during the acquisitions. For example, respiration-correlated 4D-CBCT divides the breathing cycles into different phase bins and reconstructs 3D images for each phase bin, ultimately generating a complete set of 4D images. 4D-CBCT is valuable for localizing tumors in the thoracic and abdominal regions where the localization accuracy is affected by respiratory motions. This is especially important for hypofractionated stereotactic body radiation therapy (SBRT), which delivers much higher fractional doses in fewer fractions than conventional fractionated treatments. Nonetheless, 4D-CBCT does face certain limitations, including long scanning times, high imaging doses, and compromised image quality due to the necessity of acquiring sufficient x-ray projections for each respiratory phase. In order to address these challenges, numerous methods have been developed to achieve fast, low-dose, and high-quality 4D-CBCT. This paper aims to review the technical developments surrounding 4D-CBCT comprehensively. It will explore conventional algorithms and recent deep learning-based approaches, delving into their capabilities and limitations. Additionally, the paper will discuss the potential clinical applications of 4D-CBCT and outline a future roadmap, highlighting areas for further research and development. Through this exploration, the readers will better understand 4D-CBCT's capabilities and potential to enhance radiation therapy.

A Dual-Targeting, Multi-Faceted Biocompatible Nanodrug Optimizes the Microenvironment to Ameliorate Abdominal Aortic Aneurysm.

Abdominal aortic aneurysm (AAA) is a highly lethal cardiovascular disease that currently lacks effective pharmacological treatment given the complex pathophysiology of the disease. Here, single-cell RNA-sequencing data from patients with AAA and a mouse model are analyzed, which reveals pivotal pathological changes, including the M1-like polarization of macrophages and the loss of contractile function in smooth muscle cells (SMCs). Both cell types express the integrin αvß3, allowing for their dual targeting with a single rationally designed molecule. To this end, a biocompatible nanodrug, which is termed EVMS@R-HNC, that consists of the multifunctional drug everolimus (EVMS) encapsulated by the hepatitis B virus core protein modifies to contain the RGD sequence to specifically bind to integrin αvß3 is designed. Both in vitro and in vivo results show that EVMS@R-HNC can target macrophages as well as SMCs. Upon binding of the nanodrug, the EVMS is released intracellularly where it exhibits multiple functions, including inhibiting M1 macrophage polarization, thereby suppressing the self-propagating inflammatory cascade and immune microenvironment imbalance, while preserving the normal contractile function of SMCs. Collectively, these results suggest that EVMS@R-HNC presents a highly promising therapeutic approach for the management of AAA.

Oral biomimetic virus vaccine hydrogel for robust abscopal antitumour efficacy.

Remarkable progress has been made in tumour immunotherapy in recent decades. However, the clinical outcomes of therapeutic interventions remain unpredictable, largely because of inefficient immune responses. To address this challenge and optimise immune stimulation, we present a novel administration route for enhancing the bioavailability of immunotherapeutic drugs. Our approach involves the development of an oral tumour vaccine utilising virus-like particles derived from the Hepatitis B virus core (HBc) antigen. The external surfaces of these particles are engineered to display the model tumour antigen OVA, whereas the interiors are loaded with cytosine phosphoguanosine oligodeoxynucleotide (CpG ODN), resulting in a construct called CpG@OVAHBc with enhanced antigenicity and immune response. For oral delivery, CpG@OVAHBc is encapsulated in a crosslinked dextran hydrogel called CpG@OVAHBc@Dex. The external hydrogel shield safeguards the biomimetic virus particles from degradation by gastric acid and proteases. Upon exposure to intestinal flora, the hydrogel disintegrates, releasing CpG@OVAHBc at the intestinal mucosal site. Owing to its virus-like structure, CpG@OVAHBc exhibits enhanced adhesion to the mucosal surface, facilitating uptake by microfold cells (M cells) and subsequent transmission to antigen-presenting cells. The enzyme-triggered release of this oral hydrogel ensures the integrity of the tumour vaccine within the digestive tract, allowing targeted release and significantly improving bioavailability. Beyond its efficacy, this oral hydrogel vaccine streamlines drug administration, alleviates patient discomfort, and enhances treatment compliance without the need for specialised injection methods. Consequently, our approach expands the horizons of vaccine development in the field of oral drug administration.

Prostate-Specific Membrane Antigen PET Response Associates with Metastasis-Free Survival After Stereotactic Ablative Radiation in Oligometastatic Prostate Cancer.

Purpose: Emerging data suggest that metastasis-directed therapy (MDT) improves outcomes in patients with oligometastatic castration-sensitive prostate cancer (omCSPC). Prostate-specific membrane antigen positron emission tomography (PSMA-PET) can detect occult metastatic disease, and PSMA response has been proposed as a biomarker for treatment response. Herein, we identify and validate a PSMA-PET biomarker for metastasis-free survival (MFS) following MDT in omCSPC. Methods and Materials: We performed an international multi-institutional retrospective study of patients with omCSPC, defined as ≤3 lesions, treated with metastasis-directed stereotactic ablative radiation who underwent PSMA-PET/computed tomography (CT) before and after (median, 6.2 months; range, 2.4-10.9 months) treatment. Pre- and post-MDT PSMA-PET/CT maximum standardized uptake value (SUVmax) was measured for all lesions, and PSMA response was defined as the percent change in SUVmax of the least responsive lesion. PSMA response was both evaluated as a continuous variable and dichotomized into PSMA responders, with a complete/partial response (at least a 30% reduction in SUVmax), and PSMA nonresponders, with stable/progressive disease (less than a 30% reduction in SUVmax). PSMA response was correlated with conventional imaging-defined metastasis-free survival (MFS) via Kaplan-Meier and Cox regression analysis. Results: A total of 131 patients with 261 treated metastases were included in the analysis, with a median follow-up of 29 months (IQR, 18.5-41.3 months). After stereotactic ablative radiation, 70.2% of patients were classified as PSMA responders. Multivariable analysis demonstrated that PSMA response as a continuous variable was associated with a significantly worse MFS (hazard ratio = 1.003; 95% CI, 1.001-1.006; P = .016). Patients classified as PSMA responders were found to have a significantly improved median MFS of 39.9 versus 12 months (P = .001) compared with PSMA nonresponders. Our study is limited as it is a retrospective review of a heterogenous population. Conclusions: After stereotactic ablative radiation, PSMA-PET response appears to be a radiographic biomarker that correlates with MFS in omCSPC. This approach holds promise for guiding clinical management of omCSPC and should be validated in a prospective setting.

SHU9119 and MBP10 are biased ligands at the human melanocortin-4 receptor.

The melanocortin-4 receptor (MC4R), a G protein-coupled receptor, is critically involved in regulating energy homeostasis as well as modulation of reproduction and sexual function. Two peptide antagonists (SHU9119 and MBP10) were derived from the endogenous agonist α-melanocyte stimulating hormone. But their pharmacology at human MC4R is not fully understood. Herein, we performed detailed pharmacological studies of SHU9119 and MBP10 on wild-type (WT) and six naturally occurring constitutively active MC4Rs. Both ligands had no or negligible agonist activity in Gαs-cAMP signaling on WT MC4R, but stimulated extracellular signal-regulated kinases 1 and 2 (ERK1/2) activation on WT and mutant MC4Rs. Mechanistic studies revealed that SHU9119 and MBP10 stimulated ERK1/2 signaling of MC4R by different mechanisms, with SHU9119-stimulated ERK1/2 signaling mediated by phosphatidylinositol 3-kinase (PI3K) and MBP10-initiated ERK1/2 activation through PI3K and ß-arrestin. In summary, our studies demonstrated that SHU9119 and MBP10 were biased ligands for MC4R, preferentially activating ERK1/2 signaling through different mechanisms. SHU9119 acted as a biased ligand and MBP10 behaved as a biased allosteric modulator.

A Randomized Controlled Study of Enhanced External Counterpulsation with Cardiac Rehabilitation in Patients with Nonobstructive Coronary Artery Disease and Coronary Microvascular Dysfunction.

Treatment with enhanced external counterpulsation (EECP) or cardiac rehabilitation (CR) benefits patients with coronary heart disease; this paper intends to explore the feasibility of EECP combined with CR in patients with nonobstructive coronary heart disease (NOCAD) and coronary microcirculation disorders (CMD).In January 2021-2022 month June our income NOCAD patients as the research object, the line of cardiac magnetic resonance (CMR), myocardial perfusion reserve (MPR) < 2.0 coronary microcirculation disorders (CMD, 80 cases). Random indicator method 80 CMD patients divided into two groups, 40 cases in each. Usual treatment group: conventional drugs and CR therapy. EECP treatment group: on the basis of standard treatment group, employ EECP therapy. Comparing the two groups before and after the treatment curative effect cardiac function index, endothelial unction index, adverse cardiovascular events, etc.After EECP treatment, the treatment group showed a higher effective rate compared to the usual treatment group (P < 0.05). EECP group curative effect, left ventricular ejection fraction,plasma NO and vascular endothelial growth factor levels higher than the usual group, the incidence of adverse cardiovascular events is lower than the usual group. The difference was statistically significant (P < 0.05).EECP combined with cardiac rehabilitation in patients with CMD symptoms has better effect and safety and provides reference for treatment of CMD patients.

Examining the unique relationships between problematic use of the internet and impulsive and compulsive tendencies: network approach.

BACKGROUND: Both impulsivity and compulsivity have been identified as risk factors for problematic use of the internet (PUI). Yet little is known about the relationship between impulsivity, compulsivity and individual PUI symptoms, limiting a more precise understanding of mechanisms underlying PUI. AIMS: The current study is the first to use network analysis to (a) examine the unique association among impulsivity, compulsivity and PUI symptoms, and (b) identify the most influential drivers in relation to the PUI symptom community. METHOD: We estimated a Gaussian graphical model consisting of five facets of impulsivity, compulsivity and individual PUI symptoms among 370 Australian adults (51.1% female, mean age = 29.8, s.d. = 11.1). Network structure and bridge expected influence were examined to elucidate differential associations among impulsivity, compulsivity and PUI symptoms, as well as identify influential nodes bridging impulsivity, compulsivity and PUI symptoms. RESULTS: Results revealed that four facets of impulsivity (i.e. negative urgency, positive urgency, lack of premeditation and lack of perseverance) and compulsivity were related to different PUI symptoms. Further, compulsivity and negative urgency were the most influential nodes in relation to the PUI symptom community due to their highest bridge expected influence. CONCLUSIONS: The current findings delineate distinct relationships across impulsivity, compulsivity and PUI, which offer insights into potential mechanistic pathways and targets for future interventions in this space. To realise this potential, future studies are needed to replicate the identified network structure in different populations and determine the directionality of the relationships among impulsivity, compulsivity and PUI symptoms.

Imaging Transcriptomics of the Brain for Schizophrenia.

Schizophrenia is a severe mental disorder with a neurodevelopmental origin. Although schizophrenia results from changes in the brain, the underlying biological mechanisms are unknown. Transcriptomics studies quantitative expression changes or qualitative changes of all genes and isoforms, providing a more meaningful biological insight. Magnetic resonance imaging (MRI) techniques play roles in revealing brain structure and function. We give a narrative focused review on the current transcriptome combined with MRI studies related to schizophrenia and summarize the research methodology and content of these studies to identify the research commonalities as well as the implications for future research, in an attempt to provide new insights into the mechanism, clinical diagnosis, and treatments of schizophrenia.

Consistent Individual Differences Drive Collective Movements in a Tibetan Macaque Group.

Collective movement has emerged as a key area of interest in animal behavior. While individual differences are often viewed as a potential threat to group cohesion, growing evidence suggests that these differences can actually influence an animal's behavior as an initiator or follower during collective movements, thereby driving the group's movement and decision-making processes. To resolve the divergence, we asked how personality can affect the dynamics of collective movements in one group of free-ranging Tibetan macaques (Macaca thibetana) in Huangshan, China. We assessed individual personality using principal component analysis and applied the generalized linear mixed model and linear mixed model to examine the influence of personality on decision making during collective movements. Our findings reveled three distinct personality types among Tibetan macaques: sociability, boldness, and anxiousness. Individuals with higher sociability scores and rank, or those with lower anxiousness scores, were more likely to initiate successful collective movements. Older individuals were less successful in initiating movements compared to young adults. Leaders with lower anxiousness scores or higher rank attracted more followers, with females attracting larger groups than males. As for followers, individuals with higher rank tended to join the collective movement earlier. Additionally, individuals with higher sociability or boldness scores had shorter joining latency in collective movement. Finally, there was a longer joining latency for middle-aged adults compared to young adults. These results suggest that individual differences are a potential driver of collective movements. We provide some insights into the relationships between personality and decision making in Tibetan macaques.