Micropeptide MPM regulates cardiomyocyte proliferation and heart growth via the AKT pathway.

The role of micropeptide in cardiomyocyte proliferation remains unknown. We found that MPM (micropeptide in mitochondria) was highly expressed in cardiomyocytes. Compared to MPM+/+ mice, MPM knockout (MPM-/-) mice exhibited reduction in left ventricular (LV) mass, myocardial thickness and LV fractional shortening. RNA-sequencing analysis in H9c2, a rat cardiomyocyte cell line, identified downregulation of cell cycle-promoting genes as the most significant alteration in MPM-silencing cells. Consistently, gain- and loss-of-function analyses in H9c2 cells revealed that cardiomyocyte proliferation was repressed by silencing MPM but was promoted by overexpressing MPM. Moreover, the cardiomyocytes in the hearts of MPM-/- mice displayed reduced proliferation rates. Mechanism investigations disclosed that MPM is crucial for AKT activation in cardiomyocytes. We also identified an interaction between MPM and PTPMT1, and found that silencing PTPMT1 attenuated the effect of MPM in activating the AKT pathway, whereas inhibition of the AKT pathway abrogated the role of MPM in promoting cardiomyocyte proliferation. Collectively, these results indicate that MPM may promote cardiomyocyte proliferation and thus heart growth by interacting with PTPMT1 to activate the AKT pathway. Our findings identify the novel function and regulatory network of MPM and highlight the importance of micropeptides in cardiomyocyte proliferation and heart growth.

Major pathological response obtained after neoadjuvant chemotherapy combined with dual immunotherapy for malignant pleural mesothelioma: a case report.

Background: Malignant pleural mesothelioma (MPM) is a rare thoracic malignancy with high morbidity and mortality. A combination of systemic therapy and surgery may be a promising modality for the treatment of MPM, but evidence-based medicine is still lacking. Case Description: Here we report a case of MPM. The patient presented to hospital with cough and sputum. After ineffective symptomatic treatment, computed tomography (CT) examination suggested a malignant tumor of pleural origin. Positron emission tomography/computed tomography (PET/CT) examination suggested no lymph node metastasis or distant metastasis. The pathologic diagnosis of MPM was confirmed after CT-guided puncture biopsy. Next, she underwent 3 courses of neoadjuvant chemotherapy combined with dual immunotherapy (carboplatin and pemetrexed combined with anti-CTLA4 and anti-PD-1), resulting in significant tumor shrinkage. After obtaining the patient's consent and completing a preoperative evaluation, we modified the extrapleural pneumonectomy (EPP) and pleurectomy/decortication (P/D) by performing a lower lobe resection and partial pleurectomy of the left lung. Intraoperative rapid frozen pathology suggested that the margins of the tumor were negative and complete resection was achieved. The postoperative pathology report showed 10% residual viable tumor, so the major pathological response (MPR) was achieved after treatment. Conclusions: MPM might respond well to neoadjuvant chemotherapy and dual immunotherapy, improving the probability of complete surgical resection and attaining an encouraging pathologic response.

A Pragmatic Approach for Rapid, Non-Destructive Assessment of Defect Types in Laser Powder Bed Fusion Based on Melt Pool Monitoring Data.

Process monitoring systems, e.g., systems based on photodiodes, could be used in laser-based powder bed fusion (PBF-LB/M) to measure various process parameters and process signatures to eventually allow for a local, detailed analysis of the produced parts. Here, simple statements only concerning the occurrence of defects in parts are sufficient in many cases, especially with respect to industrial application. Therefore, a pragmatic approach to rapidly infer the occurrence of defects and their types based on in situ data obtained by commercially available process monitoring systems is introduced. In this approach, a color distribution in form of a histogram is determined for each produced part using layer-wise screenshots of the visualized data provided by the monitoring software. Assessment of the histograms of AlSi10Mg samples, which were processed with different parameter combinations, revealed characteristics depending on the prevailing defect types. These characteristics enable the prediction of the occurring defect types without the necessity to apply conventional downstream testing methods, and thus, a straightforward separation of parts with good quality from defective components. Since the approach presented uses the data visualization of the monitoring software, it can be used even when direct access to the raw data is not provided by the machine manufacturer.

Predictive potential of MRI in differentiating the predominant component in biphasic pleural mesothelioma.

PURPOSE: To assess the potential of apparent diffusion coefficient (ADC) values derived from diffusion weighted (DW) MRI preoperatively to predict the predominant histologic component among biphasic pleural mesothelioma (PM) tumors. METHODS: ADC maps were generated from DW MRI scans. Histology and predominant component of biphasic PM were confirmed following surgical resection. Statistical analyses were done with R (R Foundation for Statistical Computing, Vienna, Austria). Average ADC values corresponding to epithelioid- and sarcomatoid-predominant tumors were compared. ADC thresholding was accomplished by recursive partitioning and confirmed with ROC analysis. RESULTS: Eighty-four patients with biphasic PM's, 69 (82 %) epithelioid-predominant (BE) and 15(18 %) sarcomatoid-predominant (BS) tumors were evaluated. Thirty-eight (45 %) patients underwent extrapleural pneumonectomy (EPP), 39 (46 %) had extended pleural decortication (ePDC) and 7 (8 %) had pleural decortication (PDC). ADC values ranged between 0.696 x 10-3 to 1.921 x 10-3 mm2/s. BE tumors demonstrated significantly higher ADC values than BS tumors (p = 0.026). ADC values above 0.94 x 10-3 mm2/s were associated with a significant increase of relative risk of being in group BE over group BS (relative risk: 1.47, 95 %CI: 1.05-2.06, p = 0.027) CONCLUSION: Average ADC values of BE tumors were higher than BS tumors and the two groups can be separated by a cut off value of 0.94 X 10-3 mm2/s.

Advances in Immunotherapy for Malignant Pleural Mesothelioma: From Emerging Strategies to Translational Insights.

MPM stands as a rare malignancy necessitating improved therapeutic strategies due to its limited treatment choices and unfavorable prognosis. The advent of immune checkpoint inhibitors has heralded a paradigm shift in the therapeutic landscape of MPM, offering promising avenues across diverse clinical scenarios. In the context of advanced stages of the disease, Immune check-point inhibitors targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-as-sociated protein 4 (CTLA-4), have exhibited encouraging potential in clinical trials, particularly manifesting efficacy among patients exhibiting disease progression following chemotherapy regimens. Innovative combination regimens, exemplified by the concurrent administration of nivolumab and ipilimumab, have demonstrated marked improvement in survival and patient's benefits. A deeper comprehension of the intricate genetic underpinnings of MPM, encompassing key mutations such as cyclin-dependent kinase inhibitor 2A (CDKN2A), neurofibromin 2 (NF2), and BRCA1-associated protein 1 (BAP1) mutations, has elucidated novel avenues for targeted therapeutic interventions. This review accentuates the transformative capacity of immunotherapy in revolutionizing the therapeutic outlook for MPM, thereby potentially translating into augmented survival rates and offering glimpses of new approaches on the horizon. Despite the persisting challenges, the synergistic crossroads of interdisciplinary research and collaborative clinical endeavors portend a hopeful landscape for MPM treatment.

El mesotelioma pleural maligno (MPM) es una neoplasia poco frecuente que requiere una mejora de las estrategias terapéuticas debido a sus limitadas opciones de tratamiento y a su pronóstico desfavorable. La llegada de los inhibidores de los puntos de control inmunitario ha supuesto un cambio de paradigma en el panorama terapéutico del MPM, ofreciendo vías prometedoras en diversos escenarios clínicos. En el contexto de los estadios avanzados de la enfermedad, los inhibidores de puntos de control inmunitario dirigidos contra la proteína de muerte celular programada 1 (PD-1) y la proteína 4 asociada a los linfocitos T citotóxicos (CTLA-4) han mostrado un potencial alentador en los ensayos clínicos, sobre todo por su eficacia en los pacientes con progresión de la enfermedad tras los regímenes de quimioterapia. Los regímenes combinados innovadores, ejemplificados por la administración concurrente de nivolumab e ipilimumab, han demostrado una mejora significativa de la supervivencia y de los beneficios para los pacientes. Una comprensión más profunda de los complejos fundamentos genéticos del MPM, que abarca mutaciones clave como el inhibidor de la cinasa dependiente de ciclina 2A (CDKN2A), la neurofibromina 2 (NF2) y las mutaciones de la proteína 1 asociada a BRCA1 (BAP1), ha dilucidado nuevas vías para el desarrollo de intervenciones terapéuticas dirigidas. Esta revisión acentúa la capacidad transformadora de la inmunoterapia para revolucionar las perspectivas terapéuticas en el MPM, lo que podría traducirse en un aumento de las tasas de supervivencia y ofrecer nuevos enfoques terapéuticos en el horizonte próximo. A pesar de los retos persistentes, el cruce sinérgico de la investigación interdisciplinar y los esfuerzos clínicos de colaboración auguran un panorama esperanzador en el tratamiento de los MPM.

Monitoring multistage healthcare processes using state space models and a machine learning based framework.

Monitoring healthcare processes, such as surgical outcomes, with a keen focus on detecting changes and unnatural conditions at an early stage is crucial for healthcare professionals and administrators. In line with this goal, control charts, which are the most popular tool in the field of Statistical Process Monitoring, are widely employed to monitor therapeutic processes. Healthcare processes are often characterized by a multistage structure in which several components, states or stages form the final products or outcomes. In such complex scenarios, Multistage Process Monitoring (MPM) techniques become invaluable for monitoring distinct states of the process over time. However, the healthcare sector has seen limited studies employing MPM. This study aims to fill this gap by developing an MPM control chart tailored for healthcare data to promote early detection, confirmation, and patient safety. As it is important to detect unnatural conditions in healthcare processes at an early stage, the statistical control charts are combined with machine learning techniques (i.e., we deal with Intelligent Control Charting, ICC) to enhance detection ability. Through Monte Carlo simulations, our method demonstrates better performance compared to its statistical counterparts. To underline the practical application of the proposed ICC framework, real data from a two-stage thyroid cancer surgery is utilized. This real-world case serves as a compelling illustration of the effectiveness of the developed MPM control chart in a healthcare setting.

Study on large deformation of soil-rock mixed slope based on GPU accelerated material point method.

This study assesses the effect of stone content on the stability of soil-rock mixture slopes and the dynamics of ensuing large displacement landslides using a material point strength reduction method. This method evaluates structural stability by incrementally decreasing material strength parameters. The author created four distinct soil-rock mixture slope models with varying stone contents yet consistent stone size distributions through digital image processing. The initial conditions were established by linearly ramping up the gravity in fixed proportionate steps until the full value was attained. Stability was monitored until a sudden shift in displacement marked the onset of instability. Upon destabilization, the author employed the material point method to reconstruct the landslide dynamics. Due to the substantial computational requirements, the author developed a high-performance GPU-based framework for the material point method, prioritizing the parallelization of the MPM algorithm and the optimization of data structures and memory allocation to exploit GPU parallel processing capabilities. Our results demonstrate a clear positive correlation between stone content and slope stability; increasing stone content from 10 to 20% improved the safety factor from 1.9 to 2.4, and further increments to 30% and 40% ensured comprehensive stability. This study not only sheds light on slope stability and the mechanics of landslides but also underscores the effectiveness of GPU-accelerated methods in handling complex geotechnical simulations.

[Research progress on pathogenesis of malignant mesothelioma].

The occurrence of malignant mesothelioma is related to exposure of asbestos. And many researchers have conducted in-depth analysis of the molecular changes of mesothelioma, showed that its molecular characteristics were chromosome changes, including chromosome rearrangement, gene mutation and gene deletion. Recent studies have strengthened our understanding of molecular characterization of mesothelioma, such as targeted mutations of tumor suppressor genes, differential gene expression, changes of miRNA and signal pathways. It is of great significance for the early diagnosis, clinical treatment and prognosis of malignant mesothelioma to explore the pathogenesis and development of malignant mesothelioma. This article reviews the research progress on the pathogenesis and carcinogenesis-related molecules of malignant mesothelioma.

Bioinspired Design and Experimental Validation of an Aquatic Snake Robot.

This article presents the design, simulation, and experimental validation of a novel modular aquatic snake robot capable of surface locomotion. The modular structure allows each unit to function independently, facilitating ease of maintenance and adaptability to diverse aquatic environments. Employing the material point method with the moving least squares (MPM-MLS) simulation technique, the robot's dynamic behavior was analyzed, yielding reliable results. The control algorithm, integral to the robot's autonomous navigation, was implemented to enable forward propulsion at high speed, steering, and obstacle detection and avoidance. Extensive testing of the aquatic snake robot was conducted, demonstrating its practical viability. The robot showcased promising swimming capabilities, achieving high speeds and maneuverability. Furthermore, the obstacle detection and avoidance mechanisms were proven effective, showing the robot's ability to navigate through dynamic environments. The presented aquatic snake robot represents an advancement in the field of underwater robotics, offering a modular and versatile solution for tasks ranging from environmental monitoring to search and rescue operations.

The genetic susceptibility in the development of malignant pleural mesothelioma: somatic and germline variants, clinicopathological features and implication in practical medical/surgical care: a narrative review.

Background and Objective: Malignant pleural mesothelioma (MPM) is a very aggressive primary tumor of the pleura whose main risk factor is exposure to asbestos. However, only a minority of exposed people develops MPM and the incidence of MPM cases without an apparent association with asbestos exposure has been increasing in recent years, suggesting that genetic predisposing factors may play a crucial role. In addition, several studies reported familial cases of MPM, suggesting that heredity may be an important and underestimated feature in MPM development. Several candidate genes have been associated with a predisposition to MPM and most of them play a role in DNA repair mechanisms: overall, approximately 20% of MPM cases may be related to genetic predisposition. A particular category of patients with high susceptibility to MPM is represented by carriers of pathogenic variants in the BAP1 gene. Germline variants in BAP1 predispose to the development of MPM following an autosomal dominant pattern of inheritance in the familial cases. MPMs in these patients are significantly less aggressive, and patients require a multidisciplinary approach that involves genetic counseling, medical genetics, pathology, surgical, medical, and radiation oncology expertise. In the present narrative review, we presented a comprehensive overview of genetic susceptibility in the development of MPM. Methods: The narrative review is based on a selective literature carried out in PubMed in 2023. Inclusion criteria were original articles in English language, and clinical trials (randomized, prospective, or retrospective). Key Content and Findings: We summarized the somatic and germline variants and the differences in terms of clinicopathological features and prognosis between gene-related MPM (GR-MPM) and asbestos-related MPM (AR-MPM). We also discussed the indications for screening, genetic testing, and surveillance of patients with BAP1 germline variants. Conclusions: In this narrative review, we have emphasized that the BAP1 gene's harmful germline variations are inherited in an autosomal dominant manner in familial cases. MPMs in individuals with these variations are less severe, and their medical care necessitates a collaborative effort. Additionally, we have outlined the current therapeutic prospects for MPM, including the possibility of gene-specific therapy, which is currently promising but still requires clinical validation.

In vivo deep brain multiphoton fluorescence imaging emitting at NIR-I and NIR-II and excited at NIR-IV.

Multiphoton microscopy (MPM) enables deep brain imaging. Three optical windows: NIR-I, NIR-II, and NIR-III are widely used. Recently, NIR-IV (the 2200 nm window) has been demonstrated to be the last and longest window for deep tissue MPM. However, so far MPM covers only two optical windows labeled by single fluorescent probe, one for emission and one for excitation. Here we demonstrate in vivo deep brain MPM covering three optical windows, with emission at NIR-I, NIR-II, and excitation at NIR-IV, labeled by ICG. The innovations include: (1) characterizing both 3-photon excitation and emission properties of ICG emitting at both NIR-I and NIR-II, in water, plasma, and circulating blood; (2) a home-built multiphoton microscope with simultaneous dual channel detection, with which we demonstrate deep brain MPM 950 µm (NIR-I) and 850 µm (NIR-II) into the mouse brain in vivo, verifying that multi-optical window MPM is promising for deep brain imaging.

Atypical B cells (CD21-CD27-IgD-) correlate with lack of response to checkpoint inhibitor therapy in NSCLC.

INTRODUCTION: Checkpoint inhibitor (CI) therapy has revolutionized treatment for non-small cell lung cancer (NSCLC). However, a proportion of patients do not respond to CI therapy for unknown reasons. Although the current paradigm in anti-tumor immunity evolves around T cells, the presence of tertiary lymphoid structures and memory B cells has been positively correlated with response to CI therapy in NSCLC. In addition, double negative (DN) (CD27- IgD-) B cells have been shown to be abundant in NSCLC compared to healthy lung tissue and inversely correlate with the intratumoral presence of memory B cells. Nonetheless, no study has correlated DN B cells to survival in NSCLC. METHODS: In this study, we evaluated the presence and phenotype of B cells in peripheral blood with flow cytometry of patients with NSCLC and mesothelioma before receiving CI therapy and correlated these with clinical outcome. RESULTS: Non-responding patients showed decreased frequencies of B cells, yet increased frequencies of antigen-experienced CD21- DN (Atypical) B cells compared to responding patients and HC, which was confirmed in patients with mesothelioma treated with CI therapy. CONCLUSIONS: These data show that the frequency of CD21- DN B cells correlates with lack of response to CI therapy in thoracic malignancies. The mechanism by which CD21- DN B cells hamper CI therapy remains unknown. Our findings support the hypothesis that CD21- DN B cells resemble phenotypically identical exhausted B cells that are seen in chronic infection or function as antigen presenting cells that induce regulatory T cells.

Nivolumab and ipilimumab in the real-world setting in patients with mesothelioma.

OBJECTIVES: Nivolumab (anti-PD-1) plus ipilimumab (anti-CTLA-4) is a new first-line treatment combination for patients with pleural mesothelioma. Nivolumab-ipilimumab improved the survival, however, 30.3% of the patients suffered from grade 3-4 treatment related adverse events (TRAE's) and TRAE's led to discontinuation in 23.0% of all patients. Here, we present the first real-world data of nivolumab plus ipilimumab in patients with malignant mesothelioma treated in two mesothelioma expert centers. METHODS: Clinical data of patients with mesothelioma treated with nivolumab and ipilimumab were prospectively collected. Clinical parameters were obtained every visit, CT scans were evaluated every 12 weeks and adverse events were assessed continuously during the treatment. Data on grade 2-5 TRAE's and activity (overall response rate (ORR), duration of response (DOR), disease control rate (DCR), median progression-free survival (mPFS) and median overall survival (mOS) were reported. RESULTS: Between January 2021 and August 2022, 184 patients were treated with nivolumab plus ipilimumab. The median follow-up was 12.1 months (95 %CI 11.1 - 13.1). Grade 3-4 TRAEs were seen in 27.7 % of the patients and 25.0 % discontinued immunotherapy treatment early because of TRAE's. ORR was 21.7 % (95 % CI 15.7-27.7), median DOR was 5.7 months (IQR 3.2-8.7) and DCR at 12 weeks 56.0 % (95 % CI 48.8-63.2). The mPFS was 5.5 months (95 %CI 4.1-6.9), mOS was 14.1 months (95 % CI 11.1-18.2). CONCLUSIONS: Nivolumab plus ipilimumab had an equal efficacy in a real-world comparable population but also a high risk of TRAE's, leading to discontinuation of treatment in 25% of the patients.

[Research progress on immunohistochemical diagnostic markers for malignant pleural mesothelioma].

Malignant pleural mesothelioma (MPM) is a malignant tumor originating from the pleura, characterized by insidious onset, strong local invasiveness, short survival period, and poor prognosis. Clinical diagnosis is of paramount importance for the treatment and prognosis of MPM. Currently, the gold standard for diagnosing MPM is the results of histopathological examinations. Immunohistochemistry (IHC) is an effective auxiliary method in pathological diagnosis. Preliminary examinations can use two positive markers and two negative markers to distinguish pleural metastatic tumors, with additional antibodies selected based on differential diagnosis. The combined use of IHC markers plays a crucial role in the differential diagnosis between MPM and other tumors. This article primarily introduces commonly used IHC markers in MPM and the research progress of novel IHC markers in screening and differential diagnosis, aiming to provide reference for the clinical diagnosis and treatment of MPM.

Convolutional Neural Networks for Segmentation of Malignant Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance).

Malignant pleural mesothelioma (MPM) is the most common form of malignant mesothelioma, with exposure to asbestos being the primary cause of the disease. To assess response to treatment, tumor measurements are acquired and evaluated based on a patient's longitudinal computed tomography (CT) scans. Tumor volume, however, is the more accurate metric for assessing tumor burden and response. Automated segmentation methods using deep learning can be employed to acquire volume, which otherwise is a tedious task performed manually. The deep learning-based tumor volume and contours can then be compared with a standard reference to assess the robustness of the automated segmentations. The purpose of this study was to evaluate the impact of probability map threshold on MPM tumor delineations generated using a convolutional neural network (CNN). Eighty-eight CT scans from 21 MPM patients were segmented by a VGG16/U-Net CNN. A radiologist modified the contours generated at a 0.5 probability threshold. Percent difference of tumor volume and overlap using the Dice Similarity Coefficient (DSC) were compared between the standard reference provided by the radiologist and CNN outputs for thresholds ranging from 0.001 to 0.9. CNN annotations consistently yielded smaller tumor volumes than radiologist contours. Reducing the probability threshold from 0.5 to 0.1 decreased the absolute percent volume difference, on average, from 43.96% to 24.18%. Median and mean DSC ranged from 0.58 to 0.60, with a peak at a threshold of 0.5; no distinct threshold was found for percent volume difference. The CNN exhibited deficiencies with specific disease presentations, such as severe pleural effusion or disease in the pleural fissure. No single output threshold in the CNN probability maps was optimal for both tumor volume and DSC. This study emphasized the importance of considering both figures of merit when evaluating deep learning-based tumor segmentations across probability thresholds. This work underscores the need to simultaneously assess tumor volume and spatial overlap when evaluating CNN performance. While automated segmentations may yield comparable tumor volumes to that of the reference standard, the spatial region delineated by the CNN at a specific threshold is equally important.

Graphitic Carbon Nitride/MOFs Hybrid Composite as Highly Selective and Sensitive Electrodes for Calcium Ion Detection.

The metal-organic framework (MOF) is a class of materials that exhibits a notable capacity for electron transfer. This unique framework design offers potential applications in various fields, including catalysis, gas storage, and sensing. Herein, we focused on a specific type of MOF called Ti-MOF. To enhance its properties and functionality, the composite material was prepared by incorporating graphitic carbon nitride (g-C3N4) into the Ti-MOF structure. This composite, known as g-C3N4@Ti-MOF, was selected as the active material for ion detection, specifically targeting calcium ions (Ca2+). To gain a comprehensive understanding of the structural and chemical properties of the g-C3N4@Ti-MOF composite, several analytical techniques were employed to characterize the prepared g-C3N4@Ti-MOF composite, including X-ray diffraction (XRD), SEM-EDX, and FT-IR. For comparison, different pastes were prepared by mixing Ti-MOF or g-C3N4@Ti-MOF, graphite, and o-NPOE as a plasticizer. The divalent Nernstian responses of the two best electrodes, I and II, were 28.15 ± 0.47 and 29.80 ± 0.66 mV decade-1, respectively, with concentration ranges of 1 µM-1 mM and 0.1 µM-1 mM with a content 1.0 mg Ti-MOF: 250 mg graphite: 0.1 mL o-NPOE and 0.5 mg g-C3N4@Ti-MOF: 250 mg graphite: 0.1 mL o-NPOE, respectively. The electrodes showed high sensitivity and selectivity for Ca2+ ions over different species. The suggested electrodes have been successfully employed for Ca2+ ion measurement in various real samples with excellent precision (RSD = 0.74-1.30%) and accuracy (recovery = 98.5-100.2%), and they exhibited good agreement with the HPLC.

Modification of Simple Antenna Pattern Models for Inter-Beam Interference Assessment in Massive Multiple-Input-Multiple-Output Systems.

The occurrence of cross-beam interference in the received signal is one of the main problems that limit the possibilities of massive multiple-input-multiple-output technology (massive-MIMO) in fifth-generation (5G) systems. Thus, the evaluation of the level of this interference is one of the most important procedures in the spatial planning of currently wireless networks. We propose a novel modification of simple antenna pattern models, which is based only on changing the directivity of real antenna system patterns. This approach is independent of the antenna system's type, structure, and analytical description. Based on the developed modification, the original methodology for assessing the signal-to-interference ratio (SIR) from adjacent beams of a common antenna system is presented. The change in the radiation direction and the accompanying change in the complex shape and parameters of the real antenna beam pattern is one of the problems that significantly hinders the evaluation of the analyzed interference. Hence, in the presented methodology, we propose using our modification. In this case, the modification is reduced to a proportional change in the directivity concerning the real antenna system, which results from a change in the beam direction. The simulation studies used a multi-ellipsoidal propagation model and a real massive MIMO antenna pattern description from 3GPP. For the SIR error analysis, the 3GPP pattern is used as a reference. The simulation results show that modifying simple antenna pattern models allows us to obtain an SIR error of no more than 3 dB and 0.1 dB under line-of-sight (LOS) and non-LOS conditions, respectively.

A deep learning-based model (DeepMPM) to help predict survival in patients with malignant pleural mesothelioma.

Background: Malignant pleural mesothelioma (MPM) is a rare disease with limited treatment and poor prognosis, and a precise and reliable means to predicting MPM remains lacking for clinical use. Methods: In the population-based cohort study, we collected clinical characteristics from the Surveillance, Epidemiology, and End Results (SEER) database. According to the time of diagnosis, the SEER data were divided into 2 cohorts: the training cohort (from 2010 to 2016) and the test cohort (from 2017 to 2019). The training cohort was used to train a deep learning-based predictive model derived from DeepSurv theory, which was validated by both the training and the test cohorts. All clinical characteristics were included and analyzed using Cox proportional risk regression or Kaplan-Meier curve to determine the risk factors and protective factors of MPM. Results: The survival model included 3,130 cases (2,208 in the training cohort and 922 in the test cohort). As for model's performance, the area under the receiver operating characteristics curve (AUC) was 0.7037 [95% confidence interval (CI): 0.7030-0.7045] in the training cohort and 0.7076 (95% CI: 0.7067-0.7086) in the test cohort. Older age; male sex, sarcomatoid mesothelioma; and T4, N2, and M1 stage tended to be the risk factors for survival. Meanwhile, epithelioid mesothelioma, surgery, radiotherapy, and chemotherapy tended to be the protective factors. The median overall survival (OS) of patients who underwent surgery combined with radiotherapy was the longest, followed by those who underwent a combination of surgery, radiotherapy, and chemotherapy. Conclusions: Our deep learning-based model precisely could predict the survival of patients with MPM; moreover, multimode combination therapy might provide more meaningful survival benefits.

Malignant Peritoneal Mesothelioma: An In-Depth and Up-to-Date Review of Pathogenesis, Diagnosis, Management and Future Directions.

Malignant peritoneal mesothelioma (MPM) is an extremely rare malignancy usually confined to the abdominal cavity. With an aggressive natural history, morbidity and mortality are consequences of progressive locoregional effects within the peritoneal cavity. The first reported case was in the early 20th century, however, due to the rare nature of the disease and a large gap in understanding of the clinicopathological effects, the next reported MPM cases were only published half a decade later. Since then, there has been exponential growth in our understanding of the disease, however, there are no prospective data and a paucity of literature regarding management. Traditionally, patients were treated with systemic therapy and the outcomes were very poor, with a median survival of less than one year. However, with the advent of cytoreductive surgery and locoregional chemotherapy, there have been significant improvements in survival. Even more recently, with an improved understanding of the molecular pathogenesis of MPM, there have been reports of improved outcomes with novel therapies. Given the disastrous natural history of MPM, the limited data, and the lack of universal treatment guidelines, an in-depth review of the past, present, and future of MPM is critical to improve treatment regimens and, subsequently, patient outcomes.

[Prognostic significance and immune cell infiltration analysis of differentially expressed genes in malignant pleural mesothelioma].

Objective: To explore and analyze differential expressed genes in malignant pleural mesothelioma (MPM) by bioinformatics method, and to study their prognostic value in MPM and their potential role in immunotherapy. Methods: In January 2022, the dataset GSE51024 was downloaded from the GEO database, and MPM (55 cases) and normal tissue (41 cases) samples were obtained. Using R software and HMDD and miRNet database, MPM-related differential genes were screened and co-expressed genes were identified. Co-expressed genes were enriched and functionally annotated, and protein-protein interaction (PPI) networks were constructed and key genes were identified using the STRING database and Cytoscape software. TRRUST and GEPIA databases were used to predict transcription factors of key genes and to analyze prognosis and survival. The correlation between key genes and the degree of infiltration of immune cells was analyzed using TIMER. Results: A total of 435 co-expressed genes were obtained, which were mainly concentrated in the extracellular matrix tissue and the signaling pathways of cell adhesion molecules. Combined with PPI and TRRUST database, seven key MPM prognostic genes were identified. Among them, cyclin 20 (CDC20) , cell cycle checkpoint kinase 1 (CHEK1) , enhancer of Zeste homolog 2 (EZH2) , ribonucleotide reductase subunit M2 (RRM2) , topoisomerase 2A (TOP2A) , ubiquitin like plant homeodomain and ring finger domain 1 (UHRF1) were significantly up-regulated in MPM, while cyclin A1 (CCNA1) was significantly down-regulated. The expressions of CCNA1, CDC20, CHEK1, EZH2, RRM2, TOP2A and UHRF1 genes were significantly associated with MPM overall survival (P<0.05) . The expressions of CDC20, CHEK1, EZH2, RRM2 and TOP2A genes were positively correlated with B cells and dendritic cells (P<0.05) , and negatively correlated with neutrophils (P<0.05) . Conclusion: CCNA1, CDC20, CHEK1, EZH2, RRM2, TOP2A and UHRF1 may be potential prognostic markers in MPM patients, and their expressions may be related to MPM tumor immunity.