Hasil untuk "Medical technology"

Xiangbin Liu, Liping Song, Shuai Liu et al.

As an emerging biomedical image processing technology, medical image segmentation has made great contributions to sustainable medical care. Now it has become an important research direction in the field of computer vision. With the rapid development of deep learning, medical image processing based on deep convolutional neural networks has become a research hotspot. This paper focuses on the research of medical image segmentation based on deep learning. First, the basic ideas and characteristics of medical image segmentation based on deep learning are introduced. By explaining its research status and summarizing the three main methods of medical image segmentation and their own limitations, the future development direction is expanded. Based on the discussion of different pathological tissues and organs, the specificity between them and their classic segmentation algorithms are summarized. Despite the great achievements of medical image segmentation in recent years, medical image segmentation based on deep learning has still encountered difficulties in research. For example, the segmentation accuracy is not high, the number of medical images in the data set is small and the resolution is low. The inaccurate segmentation results are unable to meet the actual clinical requirements. Aiming at the above problems, a comprehensive review of current medical image segmentation methods based on deep learning is provided to help researchers solve existing problems.

Bo Liu, Li-Ming Zhan, Li Xu et al.

Medical visual question answering (Med-VQA) has tremendous potential in healthcare. However, the development of this technology is hindered by the lacking of publicly-available and high-quality labeled datasets for training and evaluation. In this paper, we present a large bilingual dataset, SLAKE, with comprehensive semantic labels annotated by experienced physicians and a new structural medical knowledge base for Med-VQA. Besides, SLAKE includes richer modalities and covers more human body parts than the currently available dataset. We show that SLAKE can be used to facilitate the development and evaluation of Med-VQA systems. The dataset can be downloaded from http://www.med-vqa.com/slake.

R. Baker

Overview of membrane science and technology membrane transport theory membrane and modules concentration polarization reverse osmosis ultrafiltration microfiltration gas separation pervaporation ion exchange membrane processes - electrodialysis carrier facilitated transport medical applications of membranes other membranes processed.

Mahmoud Al-Balas, H. Al-Balas, H. Jaber et al.

Background As COVID-19 has been declared as a pandemic disease by the WHO on March 11th, 2020, the global incidence of COVID-19 disease increased dramatically. In response to the COVID-19 situation, Jordan announced the emergency state on the 19th of March, followed by the curfew on 21 March. All educational institutions have been closed as well as educational activities including clinical medical education have been suspended on the 15th of March. As a result, Distance E-learning emerged as a new method of teaching to maintain the continuity of medical education during the COVID-19 pandemic related closure of educational institutions. Distance E-Learning is defined as using computer technology to deliver training, including technology-supported learning either online, offline, or both. Before this period, distance learning was not considered in Jordanian universities as a modality for education. This study aims to explore the situation of distance E-learning among medical students during their clinical years and to identify possible challenges, limitations, satisfaction as well as perspectives for this approach to learning. Methods This cross-sectional study is based on a questionnaire that was designed and delivered to medical students in their clinical years. For this study, the estimated sample size ( n  = 588) is derived from the online Raosoft sample size calculator. Results A total of 652 students have completed the questionnaire, among them, 538 students (82.5%) have participated in distance learning in their medical schools amid COVID-19 pandemic. The overall satisfaction rate in medical distance learning was 26.8%, and it was significantly higher in students with previous experience in distance learning in their medical schools as well as when instructors were actively participating in learning sessions, using multimedia and devoting adequate time for their sessions. The delivery of educational material using synchronous live streaming sessions represented the major modality of teaching and Internet streaming quality and coverage was the main challenge that was reported by 69.1% of students. Conclusion With advances in technologies and social media, distance learning is a new and rapidly growing approach for undergraduate, postgraduate, and health care providers. It may represent an optimal solution to maintain learning processes in exceptional and emergency situations such as COVID-19 pandemic. Technical and infrastructural resources reported as a major challenge for implementing distance learning, so understanding technological, financial, institutional, educators, and student barriers are essential for the successful implementation of distance learning in medical education.

Thomas F. Heston, Charya Khun

Artificial intelligence-powered generative language models (GLMs), such as ChatGPT, Perplexity AI, and Google Bard, have the potential to provide personalized learning, unlimited practice opportunities, and interactive engagement 24/7, with immediate feedback. However, to fully utilize GLMs, properly formulated instructions are essential. Prompt engineering is a systematic approach to effectively communicating with GLMs to achieve the desired results. Well-crafted prompts yield good responses from the GLM, while poorly constructed prompts will lead to unsatisfactory responses. Besides the challenges of prompt engineering, significant concerns are associated with using GLMs in medical education, including ensuring accuracy, mitigating bias, maintaining privacy, and avoiding excessive reliance on technology. Future directions involve developing more sophisticated prompt engineering techniques, integrating GLMs with other technologies, creating personalized learning pathways, and researching the effectiveness of GLMs in medical education.

M. M. Mir, Gulzar Muzaffar Mir, Nadeem Tufail Raina et al.

Introduction: Medical education is a lifetime learning process stretching from undergraduate to postgraduate, specialty training, and beyond. It also applies to various healthcare professionals, including doctors, nurses, and other allied healthcare professionals. Therefore, it is essential to acknowledge the immense role of artificial intelligence in medical education in the current era of rapidly growing technology. Methods: High-quality data that met the study objectives were included. In addition, comprehensive investigations on articles available in reputable databases such as PubMed, Research Gate, PubMed central, Web of Science, and Google Scholar were considered for literature review. Results: Artificial intelligence has fixed various issues in education during the last decade, including language processing, reasoning, planning, and cognitive modelling. Conclusion: It can be used in medical education in the following forms: Virtual Inquiry System, Medical Distance Learning and Management, and Recording teaching videos in medical schools. It can also enhance the value of the non-analytical humanistic aspects of medicine. The goal of this review article was to present the implications of AI in medical education, now and in the coming years.

Xiaoxia Huang, Qiancheng Wang, Dan Han et al.

Abstract Background The mechanisms underlying cardiac remodeling in aortic valvular (AoV) disease remain poorly understood, partially due to the insufficiency of appropriate preclinical animal models. Here, we present a novel murine model of aortic regurgitation (AR) generated by trans‐apical wire destruction of the AoV. Methods Directed by echocardiography, apical puncture of the left ventricle (LV) was performed in adult male C57BL/6 mice, and a metal guidewire was used to induce AoV destruction. Echocardiography, invasive LV hemodynamic and histological examination were conducted to assess the degree of AR, LV function and remodeling. Results AR mice exhibited rapid aortic regurgitation velocity (424 ± 15.22 mm/s) immediately following successful surgery. Four weeks post‐surgery, echocardiography revealed a 54.6% increase in LV diastolic diameter and a 55.1% decrease in LV ejection fraction in AR mice compared to sham mice. Pressure‐volume catheterization indicated that AR mice had significantly larger LV end‐diastolic volumes (66.2 ± 1.5 μL vs. 41.8 ± 3.4 μL), reduced LV contractility (lower dP/dtmax and Ees), and diminished LV compliance (smaller dP/dtmin and longer Tau) compared to sham mice. Histological examination demonstrated that AR mice had significantly larger cardiomyocyte area and more myocardial fibrosis in LV tissue, as well as a 107% and a 122% increase of heart weight/tibial length and lung weight/tibial length, respectively, relative to sham mice. Conclusions The trans‐apex wire‐induced destruction of the AoV establishes a novel and efficient murine model to develop AR, characterized by significant eccentric LV hypertrophy, heart failure, and pulmonary congestion.

Mingqian Chen, Wen Li, Taoyu Hu et al.

Abstract Quantitative, label-free monitoring of dynamic cell adhesion remains challenging. Meta-Surface Plasmon Resonance Microscopy (Meta-SPRM) is a novel platform integrating bright-field microscopy with engineered Meta-SPR nanocup arrays. This system simultaneously acquires bright-field images and Meta-SPRM signals, enabling their computational separation and co-analysis to provide multifaceted insights into cell-substrate interactions. Meta-SPRM offers sensitive, high-throughput, and long-term label-free quantification of cell adhesion strength and distribution. It captures dynamic processes like cell spreading and migration at micrometer lateral resolution. Notably, Meta-SPRM signals spatially correlate with key focal adhesion proteins (Integrin-β1, Vinculin), and an intrinsic intracellular signal polarity correlates with cell migration direction. Meta-SPRM provides a powerful, label-free tool for dynamic cell adhesion studies, overcoming limitations of traditional methods. Graphical abstract

Changjiao Sun, Hong Gao, Sha Wu et al.

Abstract Objective The study aims to evaluate the accuracy of an MRI-based artificial intelligence (AI) segmentation cartilage model by comparing it to the natural tibial plateau cartilage. Methods This study included 33 patients (41 knees) with severe knee osteoarthritis scheduled to undergo total knee arthroplasty (TKA). All patients had a thin-section MRI before TKA. Our study is mainly divided into two parts: (i) In order to evaluate the MRI-based AI segmentation cartilage model’s 2D accuracy, the natural tibial plateau was used as gold standard. The MRI-based AI segmentation cartilage model and the natural tibial plateau were represented in binary visualization (black and white) simulated photographed images by the application of Simulation Photography Technology. Both simulated photographed images were compared to evaluate the 2D Dice similarity coefficients (DSC). (ii) In order to evaluate the MRI-based AI segmentation cartilage model’s 3D accuracy. Hand-crafted cartilage model based on knee CT was established. We used these hand-crafted CT-based knee cartilage model as gold standard to evaluate 2D and 3D consistency of between the MRI-based AI segmentation cartilage model and hand-crafted CT-based cartilage model. 3D registration technology was used for both models. Correlations between the MRI-based AI knee cartilage model and CT-based knee cartilage model were also assessed with the Pearson correlation coefficient. Results The AI segmentation cartilage model produced reasonably high two-dimensional DSC. The average 2D DSC between MRI-based AI cartilage model and the tibial plateau cartilage is 0.83. The average 2D DSC between the AI segmentation cartilage model and the CT-based cartilage model is 0.82. As for 3D consistency, the average 3D DSC between MRI-based AI cartilage model and CT-based cartilage model is 0.52. However, the quantification of cartilage segmentation with the AI and CT-based models showed excellent correlation (r = 0.725; P values < 0.05). Conclusion Our study demonstrated that our MRI-based AI cartilage model can reliably extract morphologic features such as cartilage shape and defect location of the tibial plateau cartilage. This approach could potentially benefit clinical practices such as diagnosing osteoarthritis. However, in terms of cartilage thickness and three-dimensional accuracy, MRI-based AI cartilage model underestimate the actual cartilage volume. The previous AI verification methods may not be completely accurate and should be verified with natural cartilage images. Combining multiple verification methods will improve the accuracy of the AI model.

Tuo Wang, Cong Cao, Yu Fan et al.

Abstract Background GABPB1, the gene that encodes two isoforms of the beta subunit of GABP, has been identified as an oncogene in multiple malignant tumors. However, the role and mode of action of GABPB1 in malignant tumors, especially in lung cancer, are not well understood and need further research. Methods Our research focused on examining the biological function of GABPB1 in NSCLC (Non-Small Cell Lung Cancer). We analysed tumor data from public databases to assess the expression of GABPB1 in NSCLC  and its correlation with patient prognosis and investigated GABPB1 expression and methylation patterns in relation to the tumor microenvironment. In parallel, experiments were conducted using short hairpin RNA (shRNA) to suppress the GABPB1 gene in human lung cancer cells to evaluate the effects on cell proliferation, viability, and apoptosis. Results GABPB1 was widely expressed in various tissues of the human body. Compared to that in normal tissues, the expression of this gene was different in multiple tumor tissues. GABPB1 was highly expressed in lung cancer tissues and cell lines. Its expression was associated with molecular subtype and cellular signalling pathways, and a high level of GABPB1 expression was related to a poor prognosis in lung adenocarcinoma patients. The expression and methylation of GABPB1 affect the tumor microenvironment. After suppressing the expression of GABPB1 in both A549 and H1299 cells, we found a decrease in cell growth and expression, the formation of clones and an increase in the apoptosis rate. Conclusions Our research verified that GABPB1 promotes the tumorigenesis of NSCLC and has an inhibitory effect on tumor immunity. The specific role of GABPB1 may vary among different pathological types of NSCLC. This molecule can serve as a prognostic indicator for lung adenocarcinoma, and its methylation may represent a potential breakthrough in treatment by altering the tumor immune microenvironment in lung squamous cell carcinoma. The role and mechanism of action of GABPB1 in NSCLC should be further explored.

Asif Naveed Ahmed, Lettie E. Rawlins, Niamat Khan et al.

Abstract Background Hereditary motor and sensory neuropathy (HMSN) refers to a group of inherited progressive peripheral neuropathies characterized by reduced nerve conduction velocity with chronic segmental demyelination and/or axonal degeneration. HMSN is highly clinically and genetically heterogeneous with multiple inheritance patterns and phenotypic overlap with other inherited neuropathies and neurodegenerative diseases. Due to this high complexity and genetic heterogeneity, this study aimed to elucidate the genetic causes of HMSN in Pakistani families using Whole Exome Sequencing (WES) for variant identification and Sanger sequencing for validation and segregation analysis, facilitating accurate clinical diagnosis. Methods Families from Khyber Pakhtunkhwa with at least two members showing HMSN symptoms, who had not previously undergone genetic analysis, were included. Referrals for genetic investigations were based on clinical features suggestive of HMSN by local neurologists. WES was performed on affected individuals from each family, with Sanger sequencing used to validate and analyze the segregation of identified variants among family members. Clinical data including age of onset were assessed for variability among affected individuals, and the success rate of genetic diagnosis was compared with existing literature using proportional differences and Cohen’s h. Results WES identified homozygous pathogenic variants in GDAP1 (c.310 + 4 A > G, p.?), SETX (c.5948_5949del, p.(Asn1984Profs*30), IGHMBP2 (c.1591 C > A, p.(Pro531Thr) and NARS1 (c.1633 C > T, p.(Arg545Cys) as causative for HMSN in five out of nine families, consistent with an autosomal recessive inheritance pattern. Additionally, in families with HMSN, a SETX variant was found to cause cerebellar ataxia, while a NARS1 variant was linked to intellectual disability. Based on American College of Medical Genetics and Genomics criteria, the GDAP1 variant is classified as a variant of uncertain significance, while variants in SETX and IGHMBP2 are classified as pathogenic, and the NARS1 variant is classified as likely pathogenic. The age of onset ranged from 1 to 15 years (Mean = 5.13, SD = 3.61), and a genetic diagnosis was achieved in 55.56% of families with HMSN, with small effect sizes compared to previous studies. Conclusions This study expands the molecular genetic spectrum of HMSN and HMSN plus type neuropathies in Pakistan and facilitates accurate diagnosis, genetic counseling, and clinical management for affected families.

Pengsheng Hui, Yu Jiang, Jie Wang et al.

BackgroundParkinson’s disease (PD) is a prevalent neurodegenerative disorder that significantly benefits from early diagnosis for effective disease management and intervention. Despite advancements in medical technology, there remains a critical gap in the early and non-invasive detection of PD. Current diagnostic methods are often invasive, expensive, or late in identifying the disease, leading to missed opportunities for early intervention.ObjectiveThe goal of this study is to explore the efficiency and accuracy of combining fNIRS technology with machine learning algorithms in diagnosing early-stage PD patients and to evaluate the feasibility of this approach in clinical practice.MethodsUsing an ETG-4000 type near-infrared brain function imaging instrument, data was collected from 120 PD patients and 60 healthy controls. This cross-sectional study employed a multi-channel mode to monitor cerebral blood oxygen changes. The collected data were processed using a general linear model and β values were extracted. Subsequently, four types of machine learning models were developed for analysis: Support vector machine (SVM), K-nearest neighbors (K-NN), random forest (RF), and logistic regression (LR). Additionally, SHapley Additive exPlanations (SHAP) technology was applied to enhance model interpretability.ResultsThe SVM model demonstrated higher accuracy in differentiating between PD patients and control group (accuracy of 85%, f1 score of 0.85, and an area under the ROC curve of 0.95). SHAP analysis identified the four most contributory channels (CH) as CH01, CH04, CH05, and CH08.ConclusionThe model based on the SVM algorithm exhibited good diagnostic performance in the early detection of PD patients. Future early diagnosis of PD should focus on the Frontopolar Cortex (FPC) region.

Lorenzo Bonetti, Daniele Natali, Stefano Pandini et al.

This paper introduces a novel approach to 4D printing tailored structures with reversible two-way shape-memory effect (SME) through material extrusion technology. To this aim, methacrylated poly(ε-caprolactone) (PCL) was synthesized and evaluated from a rheological perspective to determine its suitability for extrusion-based printing. Following a printability assessment, an optimal set of parameters was identified to fabricate 3D structures, UV-crosslinked during printing. Subsequently, a physical and thermo-mechanical characterization of the printed structures was conducted to deepen the understanding of the fabrication process and properties of the obtained structures. To assess the shape-memory properties of the printed structures, both the one-way and two-way SME under load were investigated. Overall, this study opens the floodgates to implementing 4D printing via material extrusion technology, specifically targeting PCL-based semi-crystalline chemically crosslinked polymer networks with two-way SME. Because of its cost-effectiveness, versatility, and user-friendly nature, extrusion-based printing offers noteworthy advantages over other additive manufacturing approaches when reversible behavior of the printed structures is needed. Lastly, a glimpse of potential 4D printed structures from PCL-based semi-crystalline chemically crosslinked polymer networks is presented. The approach described holds significant promise across multiple research and industrial domains, including but not limited to smart actuators, soft robotics, and medical devices.

Chenghu Xu, Dehua Tang, Ying Xie et al.

Background and Aims. Currently sedation is a common practice in colonoscopy to reduce pain of patients and improve the operator satisfaction, whereas its impact on examination quality, especially adenoma detection rate (ADR) is still controversial. Thus, we aimed to investigate the association of sedation with ADR. Methods. Consecutive patients receiving colonoscopy between January 2017 and January 2020 at the Nanjing Drum Tower Hospital, Nanjing, China, were collected. Univariate and multivariate logistic regression models were performed to investigate the association between sedation and ADR. Subgroup analysis and propensity score matching (PSM) analysis, as sensitivity analysis, were performed to validate the independent effect. Results. The ADR was significantly higher in cases with sedation (ADR: 36.9% vs. 29.1%, odds ratio [OR]: 1.42, 95% confidence interval [CI]: 1.31–1.55, P < 0.001 ). Multivariate analysis showed that the sedation was an independent factor associated with ADR (OR: 1.49, 95% CI: 1.35–1.65, P < 0.001 ). The effect was consistent in subgroup analyses ( P > 0.05 ) and PSM analysis (ADR: 37.6% vs. 29.1%, OR: 1.47, 95% CI: 1.33–1.63, P < 0.001 ). Conclusion. Sedation was associated with a higher polyp and ADR s during colonoscopy, which can promote the quality of colonoscopy.

Bruce Nzimande, John P. Makhwitine, Nompumelelo P. Mkhwanazi et al.

The emergence of drug-resistant Human Immunodeficiency Virus-1 strains against anti-HIV therapies in the clinical pipeline, and the persistence of HIV in cellular reservoirs remains a significant concern. Therefore, there is a continuous need to discover and develop new, safer, and effective drugs targeting novel sites to combat HIV-1. The fungal species are gaining increasing attention as alternative sources of anti-HIV compounds or immunomodulators that can escape the current barriers to cure. Despite the potential of the fungal kingdom as a source for diverse chemistries that can yield novel HIV therapies, there are few comprehensive reports on the progress made thus far in the search for fungal species with the capacity to produce anti-HIV compounds. This review provides insights into the recent research developments on natural products produced by fungal species, particularly fungal endophytes exhibiting immunomodulatory or anti-HIV activities. In this study, we first explore currently existing therapies for various HIV-1 target sites. Then we assess the various activity assays developed for gauging antiviral activity production from microbial sources since they are crucial in the early screening phases for discovering novel anti-HIV compounds. Finally, we explore fungal secondary metabolites compounds that have been characterized at the structural level and demonstrate their potential as inhibitors of various HIV-1 target sites.

Hasan Pasalari, Angila Ataei-Pirkooh, Mitra Gholami et al.

The surveillance of wastewater treatment plant (WWTP) as the end point of SARS-CoV-2 shed from infected people arise a speculation on transmission of this virus of concern from WWTP in epidemic period. To this end, the present study was developed to comprehensively investigate the presence of SARS-CoV-2 in raw wastewater, effluent and air inhaled by workers and employee in the largest WWTP in Tehran for one-year study period. The monthly raw wastewater, effluent and air samples of WWTP were taken and the SARS-CoV-2 RNA were detected using QIAamp Viral RNA Mini Kit and real-time RT-PCR assay. According to results, the speculation on the presence of SARS-CoV-2 was proved in WWTP by detection this virus in raw wastewater. However, no SARS-CoV-2 was found in both effluent and air of WWTP; this presents the low or no infection for workers and employee in WWTP. Furthermore, further research are needed for detection the SARS-CoV-2 in solid and biomass produced from WWTP processes due to flaks formation, followed by sedimentation in order to better understand the wastewater-based epidemiology and preventive measurement for other epidemics probably encountered in the future.

Yu Lyu, Xiaolin Tian

Deep learning technology has achieved breakthrough research results in the fields of medical computer vision and image processing. Generative adversarial networks (GANs) have demonstrated a capacity for image generation and expression ability. This paper proposes a new method called MWG-UNet (multiple tasking Wasserstein generative adversarial network U-shape network) as a lung field and heart segmentation model, which takes advantages of the attention mechanism to enhance the segmentation accuracy of the generator so as to improve the performance. In particular, the Dice similarity, precision, and F1 score of the proposed method outperform other models, reaching 95.28%, 96.41%, and 95.90%, respectively, and the specificity surpasses the sub-optimal models by 0.28%, 0.90%, 0.24%, and 0.90%. However, the value of the IoU is inferior to the optimal model by 0.69%. The results show the proposed method has considerable ability in lung field segmentation. Our multi-organ segmentation results for the heart achieve Dice similarity and IoU values of 71.16% and 74.56%. The segmentation results on lung fields achieve Dice similarity and IoU values of 85.18% and 81.36%.

Guoguo Ye, Zhixiang Xu, Minghui Yang et al.

Dengue fever (DF) and dengue hemorrhagic fever (DHF) are among the most common tropical diseases affecting humans. To analyze the risk of clinical and transmission of DF/DHF in Shenzhen, the surveillance on patients of all-age patients with dengue virus (DENV) infections was conducted. Our findings revealed that the majority of DENV-infected patients are young to middle-aged males, and the development of the disease is accompanied by abnormal changes in the percentages of neutrophils, lymphocytes, and basophils. Demographic analysis revealed that these patients is concentrated in areas such as Futian District, which may be due to the higher mosquito density and temperature than that in other area. Subsequent, mosquito infection experiments confirmed that the effect of temperature shift on DENV proliferation and transmission. Not only that, constant temperatures can enhance the spread of DENV, even increase the risk of epidemic. Thus, the role of innate immune response should be highlighted in the prediction of severe severity of DENV-infected patients, and temperature should be taken into account in the prevention and control of DENV. Introduction: Dengue fever (DF) and dengue hemorrhagic fever (DHF) are among the most common tropical diseases affecting humans, and which caused by the four dengue virus serotypes (DENV 1–4). Objectives: To analyze the risk of clinical and transmission of DF/DHF in Shenzhen. Methods: The surveillance on patients of all-age patients with dengue virus (DENV) infections was conducted. Results: Our findings revealed that the majority of DENV-infected patients are young to middle-aged males, and the development of the disease is accompanied by abnormal changes in the percentages of neutrophils, lymphocytes, and basophils. Demographic analysis revealed that these patients is concentrated in areas such as Futian District, which may be due to the higher mosquito density and temperature than that in other area. Subsequent, mosquito infection experiments confirmed that the effect of temperature shift on DENV proliferation and transmission. Not only that, constant temperatures can enhance the spread of DENV, even increase the risk of epidemic. Conclusion: 1. Elevated levels of neutrophils, lymphocytes, basophils, and temperature are all significant risk factors for dengue transmission and pathogenesis; 2. Temperature increasing is associated with a higher risk of dengue transmission; 3. Fluctuations in temperature around 28 °C (28 ± 5 °C) would increase dengue transmission.

Jing Ma, Ruijuan Ma, Xueke Zeng et al.

Abstract Background Platinum-drugs based chemotherapy in clinic increases the potency of tumor cells to produce M2 macrophages, thus leading to poor anti-metastatic activity and immunosuppression. Lysosome metabolism is critical for cancer cell migration and invasion, but how it promotes antitumor immunity in tumours and macrophages is poorly understood and the underlying mechanisms are elusive. The present study aimed to explore a synergistic strategy to dismantle the immunosuppressive microenvironment of tumours and metallodrugs discovery by using the herent metabolic plasticity. Methods Naphplatin was prepared by coordinating an active alkaline moiety to cisplatin, which can regulate the lysosomal functions. Colorectal carcinoma cells were selected to perform the in vivo biological assays. Blood, tumour and spleen tissues were collected and analyzed by flow cytometry to further explore the relationship between anti-tumour activity and immune cells. Transformations of bone marrow derived macrophage (BMDM) and M2-BMDM to the M1 phenotype was confirmed after treatment with naphplatin. The key mechanisms of lysosome-mediated mucolipin-1(Mcoln1) and mitogen-activated protein kinase (MAPK) activation in M2 macrophage polarization have been unveiled. RNA sequencing (RNA-seq) was used to further explore the key mechanism underlying high-mobility group box 1(HMGB1)-mediated Cathepsin L(CTSL)-lysosome function blockade. Results We demonstrated that naphplatin induces divergent lysosomal metabolic programs and reprograms macrophages in tumor cells to terminate the vicious tumour-associated macrophages (TAMs)-MDSCs-Treg triangle. Mechanistically, macrophages treated with naphplatin cause lysosome metabolic activation by triggering Ca2+ release via Mcoln1, which induces the activation of p38 and nuclear factor-κB (NF-κB) and finally results in polarizing M2 macrophages. In contrast, HMGB1-mediated lysosome metabolic blockade in cancer cells is strongly linked to antitumor effects by promoting cytoplasmic translocation of HMGB1. Conclusions This study reveals the crucial strategies of macrophage-based metallodrugs discovery that are able to treat both immunologically “hot” and “cold” cancers. Different from traditional platinum-based antitumour drugs by inhibition of DNAs, we also deliver a strong antitumour strategy by targeting lysosome to induce divergent metabolic programs in macrophages and tumours for cancer immunotherapy.

Zhigang Tian, Xiaohu Zheng, Yingying Huang et al.

Background To enhance the efficacy of adoptive NK cell therapy against solid tumors, NK cells must be modified to resist exhaustion in the tumor microenvironment (TME). However, the molecular checkpoint underlying NK cell exhaustion in the TME remains elusive.Methods We analyzed the correlation between TIPE2 expression and NK cell functional exhaustion in the TME both in humans and mice by single-cell transcriptomic analysis and by using gene reporter mice. We investigated the effects of TIPE2 deletion on adoptively transferred NK cell therapy against cancers by using NK cells from NK-specific Tipe2-deficient mice or peripheral blood-derived or induced pluripotent stem cell (iPSC)-derived human NK cells with TIPE2 deletion by CRISPR/Cas9. We also investigated the potential synergy of double deletion of TIPE2 and another checkpoint molecule, CISH.Results By single-cell transcriptomic analysis and by using gene reporter mice, we found that TIPE2 expression correlated with NK cell exhaustion in the TME both in humans and mice and that the TIPE2high NK cell subset correlated with poorer survival of tumor patients. TIPE2 deletion promoted the antitumor activity of adoptively transferred mouse NK cells and adoptively transferred human NK cells, either derived from peripheral blood or differentiated from iPSCs. TIPE2 deletion rendered NK cells with elevated capacities for tumor infiltration and effector functions. TIPE2 deletion also synergized with CISH deletion to further improve antitumor activity in vivo.Conclusions This study highlighted TIPE2 targeting as a promising approach for enhancing adoptive NK cell therapy against solid tumors.