CD87-targeted BiTE and CAR-T cells potently inhibit invasive nonfunctional pituitary adenomas.

Recently, bispecific T-cell engagers (BiTEs) and chimeric antigen receptor-modified T cells (CAR-Ts) have been shown to have high therapeutic efficacy in hematological tumors. CD87 is highly expressed in solid tumors with an oncogenic function. To assess their cytotoxic effects on invasive nonfunctioning pituitary adenomas (iNFPAs), we first examined CD87 expression and its effects on the metabolism of iNFPA cells. We generated CD87-specific BiTE and CAR/IL-12 T cells, and their cytotoxic effects on iNFPAs cells and in mouse models were determined. CD87 had high expression in iNFPA tissue and cell samples but was undetected in noncancerous brain samples. CD87×CD3 BiTE and CD87 CAR/IL-12 T-cells showed antigenic specificity and exerted satisfactory cytotoxic effects, decreasing tumor cell proliferation in vitro and reducing existing tumors in experimental mice. Overall, the above findings suggest that CD87 is a promising target for the immunotherapeutic management of iNFPAs using anti-CD87 BiTE and CD87-specific CAR/IL-12 T cells.

Unraveling dynamic immunological landscapes in intracerebral hemorrhage: insights from single-cell and spatial transcriptomic profiling.

Intracerebral hemorrhage (ICH) poses a formidable challenge in stroke management, with limited therapeutic options, particularly in the realm of immune-targeted interventions. Clinical trials targeting immune responses post-ICH have encountered setbacks, potentially attributable to the substantial cellular heterogeneity and intricate intercellular networks within the brain. Here, we present a pioneering investigation utilizing single-cell RNA sequencing and spatial transcriptome profiling at hyperacute (1 h), acute (24 h), and subacute (7 days) intervals post-ICH, aimed at unraveling the dynamic immunological landscape and spatial distributions within the cerebral tissue. Our comprehensive analysis revealed distinct cell differentiation patterns among myeloid and lymphocyte populations, along with delineated spatial distributions across various brain regions. Notably, we identified a subset of lymphocytes characterized by the expression of Spp1 and Lyz2, termed macrophage-associated lymphocytes, which exhibited close interactions with myeloid cells. Specifically, we observed prominent interactions between Lgmn+Macro-T cells and microglia through the spp1-cd44 pathway during the acute phase post-ICH in the choroid plexus. These findings represent a significant advancement in our understanding of immune cell dynamics at single-cell resolution across distinct post-ICH time points, thereby laying the groundwork for exploring critical temporal windows and informing the development of targeted therapeutic strategies.

The key point of transsphenoidal surgery for infradiaphragmatic craniopharyngioma：Better sellar diaphragm resection.

Background: Craniopharyngiomas have a high recurrence rate and a poor prognosis, and the key methods for reducing recurrences are unknown. The aim of this study was to explore the key points of microscopic or endoscopic transsphenoidal surgery used to treat infradiaphragmatic craniopharyngiomas. Methods: We reviewed the medical records of patients with infradiaphragmatic craniopharyngiomas who were admitted to Peking Union Medical College Hospital between 2011 and 2018. Results: When considering tumor location, all 34 patients had intrasellar tumors, with 19 of them exhibiting suprasellar extensions. Of the 34 patients, 24 patients underwent resection under the microscope and the remaining 10 patients underwent transsphenoidal endoscopic surgery. Gross total tumor resection was achieved in 16 patients. Twelve patients underwent invaded sellar diaphragm resection, while the remaining 22 patients were not. Cerebrospinal fluid leaks occurred during surgery in 18 patients. Visual acuity improved in two patients. After an average follow-up of 31.1 months, 13 patients experienced tumor recurrence. The short term recurrence rate in the sellar diaphragm resection group was significantly lower compared to the non-resected group (P < 0.001). Moreover, based on distinct surgical methods, the endoscope group displayed a reduced short term recurrence rate compared to the microscope group (P = 0.0048). Conclusion: Invaded sellar diaphragm resection emerges as a pivotal maneuver in craniopharyngioma surgery, substantively influencing tumor recurrence. Capitalizing on the advantageous angled lens of endoscopes, surgeons can achieve heightened visualization. Significantly, the endoscopic approach exhibits a superior capacity to curtail recurrence, while effectively managing potential complications, when contrasted with the microscope group.

Stereotactically intracerebral transplantation of neural stem cells for ischemic stroke attenuated inflammatory responses and promoted neurogenesis: an experimental study with monkeys.

BACKGROUND: Ischemic stroke is a common neurovascular disorder with high morbidity and mortality. However, the underlying mechanism of stereotactically intracerebral transplantation of human neural stem cell (hNSC) is not well elucidated. MATERIALS AND METHODS: Four days after ischemic stroke induced by Rose Bengal photo-thrombosis, 7 cynomolgus monkeys were transplanted with hNSCs or vehicles stereotactically and followed up for 84 days. Behavioral assessments, magnetic resonance imaging, blood tests, and pathological analysis were performed before and after treatment. The proteome profiles of the left and right precentral gyrus and hippocampus were evaluated. Extracellular vesicle micro-RNA (miRNA) from the peripheral blood was extracted and analyzed. RESULTS: hNSC transplantation reduced the remaining infarcted lesion volume of cynomolgus monkeys with ischemic stroke without remarkable side effects. Proteomic analyses indicated that hNSC transplantation promoted GABAergic and glutamatergic neurogenesis, and restored the mitochondrial electron transport chain function in the ischemic infarcted left precentral gyrus or hippocampus. Immunohistochemical staining and qRT-PCT confirmed the promoting effects on neurogenesis and revealed that hNSCs attenuated post-infarct inflammatory responses by suppressing resident glia activation and mediating peripheral immune cell infiltration. Consistently, miRNA-sequencing revealed the miRNAs which were related to these pathways were down-regulated after hNSC transplantation. CONCLUSIONS: This study indicates that hNSCs can be effectively and safely used to treat ischemic stroke by promoting neurogenesis, regulating post-infarct inflammatory responses, and restoring mitochondrial function in both the infarct region and hippocampus.

Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients.

OBJECTIVE: To investigate the feasibility and accuracy of predicting locoregional recurrence (LR) in elderly patients with esophageal squamous cell cancer (ESCC) who underwent radical radiotherapy using a pairwise machine learning algorithm. METHODS: The 130 datasets enrolled were randomly divided into a training set and a testing set in a 7:3 ratio. Clinical factors were included and radiomics features were extracted from pretreatment CT scans using pyradiomics-based software, and a pairwise naive Bayes (NB) model was developed. The performance of the model was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). To facilitate practical application, we attempted to construct an automated esophageal cancer diagnosis system based on trained models. RESULTS: To the follow-up date, 64 patients (49.23%) had experienced LR. Ten radiomics features and two clinical factors were selected for modeling. The model demonstrated good prediction performance, with area under the ROC curve of 0.903 (0.829-0.958) for the training cohort and 0.944 (0.849-1.000) for the testing cohort. The corresponding accuracies were 0.852 and 0.914, respectively. Calibration curves showed good agreement, and DCA curve confirmed the clinical validity of the model. The model accurately predicted LR in elderly patients, with a positive predictive value of 85.71% for the testing cohort. CONCLUSIONS: The pairwise NB model, based on pre-treatment enhanced chest CT-based radiomics and clinical factors, can accurately predict LR in elderly patients with ESCC. The esophageal cancer automated diagnostic system embedded with the pairwise NB model holds significant potential for application in clinical practice.

A long-term prognosis study of human USP8-mutated ACTH-secreting pituitary neuroendocrine tumours.

OBJECTIVE: Somatic variants in the ubiquitin-specific protease 8 (USP8) gene are the most common genetic cause of Cushing disease. We aimed to explore the relationship between clinical outcomes and USP8 status in a single centre. DESIGN, PATIENTS AND MEASUREMENTS: We investigated the USP8 status in 48 patients with pituitary corticotroph tumours. A median of 62 months of follow-up was conducted after surgery from November 2013 to January 2015. The clinical, biochemical and imaging features were collected and analysed. RESULTS: Seven USP8 variants (p.Ser718Pro, p.Ser719del, p.Pro720Arg, p.Pro720Gln, p.Ser718del, p.Ser718Phe, p.Lys713Arg) were identified in 24 patients (50%). USP8 variants showed a female predominance (100% vs. 75% in wild type [WT], p = .022). Patients with p.Ser719del showed an older age at surgery compared to patients with the p.Pro720Arg variant (47- vs. 24-year-olds, p = .033). Patients with p.Pro720Arg showed a higher rate of macroadenoma compared to patients harbouring the p.Ser718Pro variant (60% vs. 0%, p = .037). No significant differences were observed in serum and urinary cortisol and adrenocorticotropin hormone (ACTH) levels. Immediate surgical remission (79% vs. 75%) and long-term hormone remission (79% vs. 67%) were not significantly different between the two groups. The recurrence rate was 21% (4/19) in patients harbouring USP8 variants and 13% (2/16) in WT patients. Recurrence-free survival presented a tendency to be shorter in USP8-mutated individuals (76.7 vs. 109.2 months, p = .068). CONCLUSIONS: Somatic USP8 variants accounted for 50% of the genetic causes in this cohort with a significant female frequency. A long-term follow-up revealed a tendency toward shorter recurrence-free survival in USP8-mutant patients.

Phase 1 study of safety and preliminary efficacy of intranasal transplantation of human neural stem cells (ANGE-S003) in Parkinson's disease.

BACKGROUND: Intranasal transplantation of ANGE-S003 human neural stem cells showed therapeutic effects and were safe in preclinical models of Parkinson's disease (PD). We investigated the safety and tolerability of this treatment in patients with PD and whether these effects would be apparent in a clinical trial. METHODS: This was a 12-month, single-centre, open-label, dose-escalation phase 1 study of 18 patients with advanced PD assigned to four-time intranasal transplantation of 1 of 3 doses: 1.5 million, 5 million or 15 million of ANGE-S003 human neural stem cells to evaluate their safety and efficacy. RESULTS: 7 patients experienced a total of 14 adverse events in the 12 months of follow-up after treatment. There were no serious adverse events related to ANGE-S003. Safety testing disclosed no safety concerns. Brain MRI revealed no mass formation. In 16 patients who had 12-month Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) data, significant improvement of MDS-UPDRS total score was observed at all time points (p<0.001), starting with month 3 and sustained till month 12. The most substantial improvement was seen at month 6 with a mean reduction of 19.9 points (95% CI, 9.6 to 30.3; p<0.001). There was no association between improvement in clinical outcome measures and cell dose levels. CONCLUSIONS: Treatment with ANGE-S003 is feasible, generally safe and well tolerated, associated with functional improvement in clinical outcomes with peak efficacy achieved at month 6. Intranasal transplantation of neural stem cells represents a new avenue for the treatment of PD, and a larger, longer-term, randomised, controlled phase 2 trial is warranted for further investigation.

Phenotype Transformation of PitNETs.

Phenotype transformation in pituitary neuroendocrine tumors is a little-known and unpredictable clinical phenomenon. Previous studies have not clearly defined and systematically concluded on the causes of this rare phenomenon. Additionally, the mechanisms of phenotype transformation are not well known. We reviewed cases reported in the literature with the aim of defining phenotype transformation in pituitary neuroendocrine tumors. We present an overview of the wide spectrum of phenotype transformation and its clinical features. We also discuss findings on the potential mechanism of this rare transformation, which may be related to PC1/3, the bioactivity of secretory hormones, gene mutations and the plasticity of pituitary neuroendocrine tumors. Clinicians should be aware of this rare phenomenon and more studies on the underlying mechanisms are required.

Considering Context-Specific microRNAs in Ischemic Stroke with Three "W": Where, When, and What.

MicroRNAs are short non-coding RNA molecules that function as critical regulators of various biological processes through negative regulation of gene expression post-transcriptionally. Recent studies have indicated that microRNAs are potential biomarkers for ischemic stroke. In this review, we first illustrate the pathogenesis of ischemic stroke and demonstrate the biogenesis and transportation of microRNAs from cells. We then discuss several promising microRNA biomarkers in ischemic stroke in a context-specific manner from three dimensions: biofluids selection for microRNA extraction (Where), the timing of sample collection after ischemic stroke onset (When), and the clinical application of the differential-expressed microRNAs during stroke pathophysiology (What). We show that microRNAs have the utilities in ischemic stroke diagnosis, risk stratification, subtype classification, prognosis prediction, and treatment response monitoring. However, there are also obstacles in microRNA biomarker research, and this review will discuss the possible ways to improve microRNA biomarkers. Overall, microRNAs have the potential to assist clinical treatment, and developing microRNA panels for clinical application is worthwhile.

The advantages of multi-level omics research on stem cell-based therapies for ischemic stroke.

Stem cell transplantation is a potential therapeutic strategy for ischemic stroke. However, despite many years of preclinical research, the application of stem cells is still limited to the clinical trial stage. Although stem cell therapy can be highly beneficial in promoting functional recovery, the precise mechanisms of action that are responsible for this effect have yet to be fully elucidated. Omics analysis provides us with a new perspective to investigate the physiological mechanisms and multiple functions of stem cells in ischemic stroke. Transcriptomic, proteomic, and metabolomic analyses have become important tools for discovering biomarkers and analyzing molecular changes under pathological conditions. Omics analysis could help us to identify new pathways mediated by stem cells for the treatment of ischemic stroke via stem cell therapy, thereby facilitating the translation of stem cell therapies into clinical use. In this review, we summarize the pathophysiology of ischemic stroke and discuss recent progress in the development of stem cell therapies for the treatment of ischemic stroke by applying multi-level omics. We also discuss changes in RNAs, proteins, and metabolites in the cerebral tissues and body fluids under stroke conditions and following stem cell treatment, and summarize the regulatory factors that play a key role in stem cell therapy. The exploration of stem cell therapy at the molecular level will facilitate the clinical application of stem cells and provide new treatment possibilities for the complete recovery of neurological function in patients with ischemic stroke.

Multi-center application of a convolutional neural network for preoperative detection of cavernous sinus invasion in pituitary adenomas.

OBJECTIVE: Cavernous sinus invasion (CSI) plays a pivotal role in determining management in pituitary adenomas. The study aimed to develop a Convolutional Neural Network (CNN) model to diagnose CSI in multiple centers. METHODS: A total of 729 cases were retrospectively obtained in five medical centers with (n = 543) or without CSI (n = 186) from January 2011 to December 2021. The CNN model was trained using T1-enhanced MRI from two pituitary centers of excellence (n = 647). The other three municipal centers (n = 82) as the external testing set were imported to evaluate the model performance. The area-under-the-receiver-operating-characteristic-curve values (AUC-ROC) analyses were employed to evaluate predicted performance. Gradient-weighted class activation mapping (Grad-CAM) was used to determine models' regions of interest. RESULTS: The CNN model achieved high diagnostic accuracy (0.89) in identifying CSI in the external testing set, with an AUC-ROC value of 0.92 (95% CI, 0.88-0.97), better than CSI clinical predictor of diameter (AUC-ROC: 0.75), length (AUC-ROC: 0.80), and the three kinds of dichotomizations of the Knosp grading system (AUC-ROC: 0.70-0.82). In cases with Knosp grade 3A (n = 24, CSI rate, 0.35), the accuracy the model accounted for 0.78, with sensitivity and specificity values of 0.72 and 0.78, respectively. According to the Grad-CAM results, the views of the model were confirmed around the sellar region with CSI. CONCLUSIONS: The deep learning model is capable of accurately identifying CSI and satisfactorily able to localize CSI in multicenters.

Integrating network pharmacology and transcriptomic omics reveals that akebia saponin D attenuates neutrophil extracellular traps-induced neuroinflammation via NTSR1/PKAc/PAD4 pathway after intracerebral hemorrhage.

Neutrophils and their production of neutrophil extracellular traps (NETs) significantly contribute to neuroinflammation and brain damage after intracerebral hemorrhage (ICH). Although Akebia saponin D (ASD) demonstrates strong anti-inflammatory activities and blood-brain barrier permeability, its role in regulating NETs formation and neuroinflammation following ICH is uncharted. Our research focused on unraveling the influence of ASD on neuroinflammation mediated by NETs and the mechanisms involved. We found that increased levels of peripheral blood neutrophils post-ICH are correlated with worse prognostic outcomes. Through network pharmacology, we identified ASD as a promising therapeutic target for ICH. ASD administration significantly improved neurobehavioral performance and decreased NETs production in neutrophils. Furthermore, ASD was shown to upregulate the membrane protein NTSR1 and activate the cAMP signaling pathway, confirmed through transcriptome sequencing, western blot, and immunofluorescence. Interestingly, the NTSR1 inhibitor SR48692 significantly nullified ASD's anti-NETs effects and dampened cAMP pathway activation. Mechanistically, suppression of PKAc via H89 negated ASD's anti-NETs effects but did not affect NTSR1. Our study suggests that ASD may reduce NETs formation and neuroinflammation, potentially involving the NTSR1/PKAc/PAD4 pathway post-ICH, underlining the potential of ASD in mitigating neuroinflammation through its anti-NETs properties.

A Bioinspired Flexible Sensor for Electrochemical Probing of Dynamic Redox Disequilibrium in Cancer Cells.

Malignant tumors pose a serious risk to human health. Ascorbic acid (AA) has potential for tumor therapy; however, the mechanism underlying the ability of AA to selectively kill tumor cells remains unclear. AA can cause redox disequilibrium in tumor cells, resulting in the release of abundant reactive oxygen species, represented by hydrogen peroxide (H2 O2 ). Therefore, the detection of H2 O2 changes can provide insight into the selective killing mechanism of AA against tumor cells. In this work, inspired by the ion-exchange mechanism in coral formation, a flexible H2 O2 sensor (PtNFs/CoPi@CC) is constructed to monitor the dynamics of H2 O2 in the cell microenvironment, which exhibits excellent sensitivity and spatiotemporal resolution. Moreover, the findings suggest that dehydroascorbic acid (DHA), the oxidation product of AA, is highly possible the substance that actually acts on tumor cells in AA therapy. Additionally, the intracellular redox disequilibrium and H2 O2 release caused by DHA are positively correlated with the abundance and activity of glucose transporter 1 (GLUT1). In conclusion, this work has revealed the potential mechanism underlying the ability of AA to selectively kill tumor cells through the construction and use of PtNFs/CoPi@CC. The findings provide new insights into the clinical application of AA.

Machine Learning Approaches to Differentiate Sellar-Suprasellar Cystic Lesions on Magnetic Resonance Imaging.

Cystic lesions are common lesions of the sellar region with various pathological types, including pituitary apoplexy, Rathke's cleft cyst, cystic craniopharyngioma, etc. Suggested surgical approaches are not unique when dealing with different cystic lesions. However, cystic lesions with different pathological types were hard to differentiate on MRI with the naked eye by doctors. This study aimed to distinguish different pathological types of cystic lesions in the sellar region using preoperative magnetic resonance imaging (MRI). Radiomics and deep learning approaches were used to extract features from gadolinium-enhanced MRIs of 399 patients enrolled at Peking Union Medical College Hospital over the past 15 years. Paired imaging differentiations were performed on four subtypes, including pituitary apoplexy, cystic pituitary adenoma (cysticA), Rathke's cleft cyst, and cystic craniopharyngioma. Results showed that the model achieved an average AUC value of 0.7685. The model based on a support vector machine could distinguish cystic craniopharyngioma from Rathke's cleft cyst with the highest AUC value of 0.8584. However, distinguishing cystic apoplexy from pituitary apoplexy was difficult and almost unclassifiable with any algorithms on any feature set, with the AUC value being only 0.6641. Finally, the proposed methods achieved an average Accuracy of 0.7532, which outperformed the traditional clinical knowledge-based method by about 8%. Therefore, in this study, we first fill the gap in the existing literature and provide a non-invasive method for accurately differentiating between these lesions, which could improve preoperative diagnosis accuracy and help to make surgery plans in clinical work.

Case report: Identification of potential prognosis-related LAG3 overexpression and DICER1 mutation in pituitary carcinoma: two cases.

Metastatic PitNETs are a rare life-threatening condition with poor prognosis and documentation. Due to the scarce literature and lack of precise treatment, we hope to better characterise PitNET using the next-generation whole exon sequencing (WES) and RNA sequencing. This case study outlines a 54 years-old man and a 52 years-old woman who were both diagnosed with PitNET and analysis of peripheral blood and tumours were performed by WES and RNA sequencing. Analysis showed that DICER1 mutations in precancerous lesions and LAG3 overexpression were significant in aiding the prognosis and diagnosis of PitNETs. The first case with overexpressed LAG3 and DICER1 mutation died 26 months later, and the second case with LAG3 overexpression achieved partial remission. This study revealed that heightened expression of LAG3 offered promising targets for ICI and mutations in DICER1 could provide markers for effective diagnosis and prognosis.

Resting-state functional connectivity in a non-human primate model of cortical ischemic stroke in area F1.

BACKGROUND: The application of functional MRI to non-human primates after stroke has not yet been undertaken. This is the first study to explore the functional connectivity changes in non-human primate models during acute stages after stroke onset. METHODS: Nineteen healthy male cynomolgus monkeys (4-5 years) were used in this study. The photothrombosis model was employed to induce focal ischemic stroke in F1 area in the monkey's left hemisphere. T1-weighted structural images and resting-state functional magnetic resonance imaging (rs-fMRI) of all subjects were obtained using a 3.0 Tesla MRI system on the third day following stroke. Based on the D99 atlas, the structural and functional changes of bilateral F1 areas in monkeys were analyzed using region of interest (ROI)-based functional connectivity (FC). The bilateral F1 areas were selected as the seed regions due to their crucial role in motor control and their potential to unveil the comprehensive functional reorganization of the motor system at a whole-brain level following stroke. RESULTS: Ischemic lesions were observed after the stroke, with larger lesion volumes associated with poorer neurological dysfunction. Compared with baseline condition, left area F1 demonstrated decreased FC with the left cerebellum, left ventral pons and left 5_(PEa). When the ROI was located in the right area F1, ischemic monkeys showed decreased FC in left ventral pons, left cerebellum, left primary visual cortex and left 5_(PEa), accompanied by increased FC in the right orbitofrontal cortex. Importantly, the degree of altered FC between left area F1 and left cerebellum was associated with upper limb tone. CONCLUSIONS: These results provide valuable insights into the early-stage functional connectivity changes in the F1 areas of monkeys under ischemic conditions, highlighting the potential involvement of specific brain regions in the pathophysiology of ischemic injury.

An artificial intelligence-based prognostic prediction model for hemorrhagic stroke.

PURPOSE: The prognosis following a hemorrhagic stroke is usually extremely poor. Rating scales have been developed to predict the outcomes of patients with intracerebral hemorrhage (ICH). To date, however, the prognostic prediction models have not included the full range of relevant imaging features. We constructed a clinic-imaging fusion model based on convolutional neural networks (CNN) to predict the short-term prognosis of ICH patients. MATERIALS AND METHODS: This was a multi-center retrospective study, which included 1990 patients with ICH. Two CNN-based deep learning models were constructed to predict the neurofunctional outcomes at discharge; these were validated using a nested 5-fold cross-validation approach. The models' predictive efficiency was compared with the original ICH scale and the ICH grading scale. Poor neurological outcome was defined as a Glasgow Outcome Scale (GOS) score of 1-3. RESULTS: The training and test sets included 1599 and 391 patients, respectively. For the test set, the clinic-imaging fusion model had the highest area under the curve (AUC = 0.903), followed by the imaging-based model (AUC = 0.886), the ICH scale (AUC = 0.777), and finally the ICH grading scale (AUC = 0.747). CONCLUSION: The CNN prognostic prediction model based on neuroimaging features was more effective than the ICH scales in predicting the neurological outcomes of ICH patients at discharge. The CNN model's predictive efficiency slightly improved when clinical data were included.