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Accurate evaluation of retinopathy of prematurity (ROP) severity is vital for screening and proper treatment. Current deep-learning-based automated AI systems for assessing ROP severity do not follow clinical guidelines and are opaque. The aim of this study is to develop an interpretable AI system by mimicking the clinical screening process to determine ROP severity level. A total of 6100 RetCam Ⅲ wide-field digital retinal images were collected from Guangdong Women and Children Hospital at Panyu (PY) and Zhongshan Ophthalmic Center (ZOC). A total of 3330 images of 520 pediatric patients from PY were annotated to train an object detection model to detect lesion type and location. A total of 2770 images of 81 pediatric patients from ZOC were annotated for stage, zone, and the presence of plus disease. Integrating stage, zone, and the presence of plus disease according to clinical guidelines yields ROP severity such that an interpretable AI system was developed to provide the stage from the lesion type, the zone from the lesion location, and the presence of plus disease from a plus disease classification model. The ROP severity was calculated accordingly and compared with the assessment of a human expert. Our method achieved an area under the curve (AUC) of 0.95 (95% confidence interval [CI] 0.90–0.98) in assessing the severity level of ROP. Compared with clinical doctors, our method achieved the highest F1 score value of 0.76 in assessing the severity level of ROP. In conclusion, we developed an interpretable AI system for assessing the severity level of ROP that shows significant potential for use in clinical practice for ROP severity level screening. [ABSTRACT FROM AUTHOR]

Simple Summary: The prognosis for patients with relapsed neuroblastoma is poor, and novel treatment options for these patients are needed. Some relapsed neuroblastoma tumors harbor activating mutations in the RAS/MAPK pathway. In prior studies, single agent MEK or IGF1R inhibitors induced transient responses as single agents in neuroblastoma models. In this study, we tested the efficacy of a combination of the MEK inhibitor trametinib and the IGF1R inhibitor ganitumab in RAS-mutated neuroblastoma models. While the trametinib/ganitumab combination decreased cell viability and tumor growth, the combination did not prevent metastasis of RAS-mutated neuroblastoma. Therefore, further studies on the effect of trametinib and ganitumab on neuroblastoma metastasis are necessary before initiating clinical trials of this combination of targeted agents in patients with relapsed neuroblastoma. Activating mutations in the RAS/MAPK pathway are observed in relapsed neuroblastoma. Preclinical studies indicate that these tumors have an increased sensitivity to inhibitors of the RAS/MAPK pathway, such as MEK inhibitors. MEK inhibitors do not induce durable responses as single agents, indicating a need to identify synergistic combinations of targeted agents to provide therapeutic benefit. We previously showed preclinical therapeutic synergy between a MEK inhibitor, trametinib, and a monoclonal antibody specific for IGF1R, ganitumab in RAS-mutated rhabdomyosarcoma. Neuroblastoma cells, like rhabdomyosarcoma cells, are sensitive to the inhibition of the RAS/MAPK and IGF1R/AKT/mTOR pathways. We hypothesized that the combination of trametinib and ganitumab would be effective in RAS-mutated neuroblastoma. In this study, trametinib and ganitumab synergistically suppressed neuroblastoma cell proliferation and induced apoptosis in cell culture. We also observed a delay in tumor initiation and prolongation of survival in heterotopic and orthotopic xenograft models treated with trametinib and ganitumab. However, the growth of both primary and metastatic tumors was observed in animals receiving the combination of trametinib and ganitumab. Therefore, more preclinical work is necessary before testing this combination in patients with relapsed or refractory RAS-mutated neuroblastoma. [ABSTRACT FROM AUTHOR]

Chlorogenic acid (CGA) has demonstrated anti-tumor effects across various cancers, but its role in cholangiocarcinoma (CCA) remains unclear. Our study revealed CGA's potent anti-tumor effects on CCA, significantly suppressing cell proliferation, migration, colony formation, and invasion while inhibiting the epithelial–mesenchymal transition. CGA induced apoptosis, modulated cell cycle progression, and exhibited a stable binding affinity to AKR1B10 in CCA. AKR1B10 was highly expressed in RBE cells, and CGA treatment reduced AKR1B10 expression. Knocking out AKR1B10 inhibited the proliferation of RBE cells, whereas the overexpression of AKR1B10 promoted their proliferation. Additionally, CGA suppressed the proliferation of RBE cells with AKR1B10 overexpression. Mechanistically, AKR1B10 activated AKT, and CGA exerted its inhibitory effect by reducing AKR1B10 levels, thereby suppressing AKT activation. Furthermore, CGA facilitated the polarization of tumor-associated macrophages towards an anti-tumor phenotype and enhanced T-cell cytotoxicity. These findings underscore CGA's potential as a promising therapeutic agent for CCA treatment. [ABSTRACT FROM AUTHOR]

With the booming development of the Internet of Things (IoT) industry, millions of data are generated every day. How to use and manage these data safely and efficiently has become a hot issue of concern to people. Due to the accumulation of IoT data, the isolated data island phenomenon makes it difficult to connect and interact with each data owner, and the security and privacy of IoT data also become a challenge. Blockchain is a decentralized database technology that uses distributed accounting to ensure reliable data transmission and access, along with smart contracts that can be executed automatically to program and manipulate data. At the same time, blockchain techniques have stronger security and privacy, which can better meet the needs of users. In this paper, we analyze the current management mode and challenges of IoT data and propose an IoT data platform based on blockchain. The proposed platform takes into account important factors including IoT data traceability, IoT data trusted transactions, etc. Our IoT data platform achieves the trusted management and transaction of IoT data. We also propose follow-up optimization solutions to expand the application scope of our platform and achieve more efficient management of IoT data. [ABSTRACT FROM AUTHOR]

To enhance the friction and wear properties of alloys, AlCrTiVNbx high-entropy alloys (HEAs) with various Nb contents were prepared using the arc melting technique and then annealed at 1000 °C for 2 h. The microstructure and hardness changes in the AlCrTiVNbx (x = 0.3, 0.4, and 0.5) HEAs after casting and annealing were studied via scanning electron microscopy, X-ray diffractometry, optical microscopy and the Vickers hardness test. The MFT-EC400 ball disc reciprocating friction and wear tester was used to investigate the wear resistance of the HEAs before and after annealing. The results show that the annealed AlCrTiVNbx HEAs changed from a single-phase structure to a multi-phase structure, and the content of the face-center cubic (FCC) phase and hexagonal close-packed (HCP) phase further increases with the increase in Nb content. The hardness value of the annealed HEAs is greatly enhanced compared with the casting state, and the hardness of the Nb0.5 HEA is increased from 543 HV to 725 HV after annealing. The wear resistance of the alloys after the annealing treatment is also greatly improved, among which Nb0.5 has the best wear resistance. The average friction coefficient of Nb0.5 is 0.154 and the wear rate is 2.117 × 10−5 mm3/(N·m). We believe that the precipitation strengthening after the annealing treatment and the lubrication effect of the FCC phase are the reasons for the significant improvement in wear resistance. The morphology of the samples indicates that the wear mechanism of the alloy includes adhesive wear, abrasive wear and a certain degree of oxidation wear. [ABSTRACT FROM AUTHOR]

This study employs unmanned aerial vehicles (UAVs) to detect mouse holes in grasslands, offering an effective tool for grassland ecological conservation. We introduce the specially designed CGT-YOLOv5n model, addressing long-standing challenges UAVs face, particularly the decreased detection accuracy in complex grassland environments due to shadows and obstructions. The model incorporates a Context Augmentation Module (CAM) focused on improving the detection of small mouse holes and mitigating the interference of shadows. Additionally, to enhance the model's ability to recognize mouse holes of varied morphologies, we have integrated an omni-dimensional dynamic convolution (ODConv), thereby increasing the model's adaptability to diverse image features. Furthermore, the model includes a Task-Specific Context Decoupling (TSCODE) module, independently refining the contextual semantics and spatial details for classification and regression tasks and significantly improving the detection accuracy. The empirical results show that when the intersection over union (IoU) threshold is set at 0.5, the model's mean average precision (mAP_0.5) for detection accuracy reaches 92.8%. The mean average precision (mAP_0.5:0.95), calculated over different IoU thresholds ranging from 0.5 to 0.95 in increments of 0.05, is 46.2%. These represent improvements of 3.3% and 4.3%, respectively, compared to the original model. Thus, this model contributes significantly to grassland ecological conservation and provides an effective tool for grassland management and mouse pest control in pastoral areas. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) can be used to relay sensing information and computational workloads from ground users (GUs) to a remote base station (RBS) for further processing. In this paper, we employ multiple UAVs to assist with the collection of sensing information in a terrestrial wireless sensor network. All of the information collected by the UAVs can be forwarded to the RBS. We aim to improve the energy efficiency for sensing-data collection and transmission by optimizing UAV trajectory, scheduling, and access-control strategies. Considering a time-slotted frame structure, UAV flight, sensing, and information-forwarding sub-slots are confined to each time slot. This motivates the trade-off study between UAV access-control and trajectory planning. More sensing data in one time slot will take up more UAV buffer space and require a longer transmission time for information forwarding. We solve this problem by a multi-agent deep reinforcement learning approach that takes into consideration a dynamic network environment with uncertain information about the GU spatial distribution and traffic demands. We further devise a hierarchical learning framework with reduced action and state spaces to improve the learning efficiency by exploiting the distributed structure of the UAV-assisted wireless sensor network. Simulation results show that UAV trajectory planning with access control can significantly improve UAV energy efficiency. The hierarchical learning method is more stable in learning and can also achieve higher sensing performance. [ABSTRACT FROM AUTHOR]

The organic-rich shales and mudstones of the Middle Permian are the most important unconventional petroleum targets in the southern Junggar Basin of northwestern China. Although numerous studies have been vigorously conducted on paleoenvironment reconstructions, the organic matter enrichment mechanism is still controversial due to the utilization of problematic geochemical proxies established in early studies. In this study, major and trace elemental compositions, molecular markers, stable carbon isotopic compositions, and organic petrology were used to study multiple factors affecting the accumulation of organic matter in sediments. According to the results, a relatively hydrostatic, brackish, anoxic environment is proposed in the northern periphery of the Bogda Mountain, where the original structure of organic matter could be preserved with non-correlations between the productivity proxies (P and Ba) and TOC. In the western Bogda area, organic-rich sediments were deposited under suboxic conditions, with frequent fluctuation occurring between the top and bottom water columns. The accumulation of organic matter was the result of productivity blooms and rapid sedimentation. This improved study of the enrichment of organic matter in the Middle Permian around the Bogda Mountain can contribute to improved evaluations of the petroleum potential and distinguishing the characteristics of different organic matter enrichment models. [ABSTRACT FROM AUTHOR]

Simple Summary: Currently, there is no effective method to detect the prognosis for hepatocellular carcinoma (HCC). This study used bioinformatics techniques to determine HCC molecular subtypes and prognosis-related biomarkers. A total of 3330 intersectional differentially expressed genes (DEGs) with the same differential direction in four datasets were identified by differential expression analysis. Intersectional DEGs were involved in the cell cycle, FOXO signaling pathway, and complement and coagulation cascades. Then, two subtypes were identified using a non-negative matrix decomposition method. Subtype C2 displayed better overall survival than subtype C1. Moreover, 217 prognostic related-genes were identified using the Cox regression and Kaplan-Meier curves. The area under the curve >0.80 of prognostic relate-genes were selected to construct random survival forest and the least absolute shrinkage and selection operator model and obtained seven feature genes (SORBS2, DHRS1, SLC16A2, RCL1, IGFALS, GNA14 and FANCI). Risk score model and recurrence model were constructed based on feature genes, and FANCI was inferred as a key gene by univariate Cox model. High expression of FANCI was mainly involved in cell cycle, DNA replication and mismatch repair. Interestingly, Single Sample Gene Set Enrichment Analysis was used to quantify immune infiltration and showed that Th2 cells and T helper cells were significantly up regulated in HCC compared to controls. Furthermore, we found the presence of two mutation sites as well as methylation modifications occurred in FANCI. Overall, we identified two types of HCC and identified that FANCI will serve as a potential biomarker for HCC prognosis and be important to the diagnosis and treatment of HCC. Bioinformatics tools were used to identify prognosis-related molecular subtypes and biomarkers of hepatocellular carcinoma (HCC). Differential expression analysis of four datasets identified 3330 overlapping differentially expressed genes (DEGs) in the same direction in all four datasets. Those genes were involved in the cell cycle, FOXO signaling pathway, as well as complement and coagulation cascades. Based on non-negative matrix decomposition, two molecular subtypes of HCC with different prognoses were identified, with subtype C2 showing better overall survival than subtype C1. Cox regression and Kaplan-Meier analysis showed that 217 of the overlapping DEGs were closely associated with HCC prognosis. The subset of those genes showing an area under the curve >0.80 was used to construct random survival forest and least absolute shrinkage and selection operator models, which identified seven feature genes (SORBS2, DHRS1, SLC16A2, RCL1, IGFALS, GNA14, and FANCI) that may be involved in HCC occurrence and prognosis. Based on the feature genes, risk score and recurrence models were constructed, while a univariate Cox model identified FANCI as a key gene involved mainly in the cell cycle, DNA replication, and mismatch repair. Further analysis showed that FANCI had two mutation sites and that its gene may undergo methylation. Single-sample gene set enrichment analysis showed that Th2 and T helper cells are significantly upregulated in HCC patients compared to controls. Our results identify FANCI as a potential prognostic biomarker for HCC. [ABSTRACT FROM AUTHOR]

Mobile crowdsensing is considered as a promising technology to exploit the computing and sensing capabilities of the decentralized wireless sensor nodes. Typically, the quality of information obtained from crowdsensing is largely affected by various factors, such as the diverse requirements of crowdsensing tasks, the varying quality of information across different crowd workers, and the dynamic changes of channels conditions and the sensing environment. In this paper, considering the dynamics' of the crowd workers, we focus on a spatial-temporal crowdsensing model and aim to maximize the value of information at the point of interest, by optimizing the recruiting range and time duration for the crowd workers. In particular, the crowdsensing system includes a mobile access point (MAP) and a set of wireless sensor nodes. As the information requester, the MAP can broadcast its crowdsensing task and then estimate the value of information by collecting the responses from the sensing nodes. Each sensing node in the crowdsensing task will receive a payment from the MAP. We aim to maximize the utility of the information requester by optimizing the recruiting range and waiting time for the sensing nodes. We firstly define a set of value metrics to characterize the MAP's value of information. The optimal recruiting range can be obtained in closed-form expressions. Furthermore, considering the aging effect, we propose a gradient-based method to maximize the spatial-temporal value of information. Specifically, we first determine the optimal recruiting time for the requester and then choose the optimal recruiting range within each time slot. Via simulation, we first compare the sum, max, and min values of information at the requester, and then verify the effectiveness of the gradient-based method to optimize the recruiting time and range to maximize the value of information. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to summarize the electroretinographic oscillatory potential (OP) responses in healthy young children recorded by RETeval. Methods: By using the RETeval system, we recorded the implicit times and amplitudes of the OPs (OP1-5), in 132 healthy children aged from 0 to 11 years old. The age, gender, and data of implicit time and amplitude of each child were recorded and analyzed. Correlation analysis was performed between age and implicit time/amplitude. Results: No correlation was shown between the implicit times and amplitudes with gender. The implicit times and amplitudes of OP1-5 matured over 10 years of age, with exponential time constants of 1.9, 2.2, 1.8, 1.7, and 1.6 years and 2.1, 2.9, 2.8, 3.0, and 3.2 years, respectively. The majority of the trend occurred within the first 4.6 years. Conclusions: In order to diagnose and evaluate vision-related disorders, the OP response is commonly used. The percentiles and age dependence of OP responses calculated and shown in this study could be regarded as reference data in age-matched pediatric patients. [ABSTRACT FROM AUTHOR]

Development of novel anticancer therapeutic candidates is one of the key challenges in medicinal chemistry. Podophyllotoxin and its derivatives, as a potent cytotoxic agent, have been at the center of extensive chemical amendment and pharmacological investigation. Herein, a new series of podophyllotoxin-N-sulfonyl amidine hybrids (4a–4v, 5a–5f) were synthesized by a CuAAC/ring-opening procedure. All the synthesized podophyllotoxins derivatives were evaluated for in vitro cytotoxic activity against a panel of human lung (A-549) cancer cell lines. Different substituents', or functional groups' antiproliferative activities were discussed. The –CF3 group performed best (IC50: 1.65 μM) and exhibited more potent activity than etoposide. Furthermore, molecular docking and dynamics studies were also conducted for active compounds and the results were in good agreement with the observed IC50 values. [ABSTRACT FROM AUTHOR]

Epstein-Barr virus (EBV) promotes tumor angiogenesis in nasopharyngeal carcinoma (NPC) by activating store-operated Ca2+ entry. Since such entry has been linked to stromal interaction molecule 1 (STIM1), we examined whether the virus acts via STIM1-dependent Ca2+ signaling to promote tumor angiogenesis in NPC. STIM1 expression was detected in NPC cell lines HK1 and CNE2 that were negative or positive for EBV. STIM1 was knocked down in EBV-positive cells using recombinant lentivirus, then cytosolic Ca2+ levels were measured based on fluorescence resonance energy transfer. Cells were also exposed to epidermal growth factor (EGF), and secretion of vascular endothelial growth factor (VEGF) was measured using an enzyme-linked immunosorbent assay. Endothelial tube formation was quantified in an in vitro angiogenesis assay. Growth of CNE2-EBV xenografts was measured in mice, and angiogenesis was assessed based on immunohistochemical staining against CD31. Paraffin-embedded NPC tissues from patients were assayed for CD31 and STIM1. EGFR and ERK signaling pathways were assessed in NPC cell lines. STIM1 expression was higher in EBV-positive than in EBV-negative NPC cell lines. STIM1 knockdown in EBV-positive NPC cells significantly reduced Ca2+ influx and VEGF production after EGF treatment. STIM1 knockdown also inhibited xenograft growth and angiogenesis. Moreover, CD31 expression level was higher in EBV-positive than EBV-negative NPC tissues, and high expression of CD31 co-localized with high expression of STIM1 in EBV-positive tissues from NPC patients. Viral infection of NPC cells led to higher levels of phosphorylated ERK1/2 after EGF treatment, which STIM1 knockdown partially reversed. Our results suggest that EBV promotes EGF-induced ERK1/2 signaling by activating STIM1-dependent Ca2+ signaling, and that blocking such signaling may inhibit EBV-promoted angiogenesis in NPC. [ABSTRACT FROM AUTHOR]

Stickler syndrome is a connective tissue disorder that affects multiple systems, including the visual system. Seven genes were reported to cause Stickler syndrome in patients with different phenotypes. In this study, we aimed to evaluate the mutation features of the phenotypes of high myopia and retinal detachment. Forty-two probands diagnosed with Stickler syndrome were included. Comprehensive ocular examinations were performed. A targeted gene panel test or whole exome sequencing was used to detect the mutations, and Sanger sequencing was conducted for verification and segregation analysis. Among the 42 probands, 32 (76%) presented with high myopia and 29 (69%), with retinal detachment. Pathogenic mutations were detected in 35 (83%) probands: 27 (64%) probands had COL2A1 mutations, and eight (19%) probands had COL11A1 mutations. Truncational mutations in COL2A1 were present in 21 (78%) probands. Missense mutations in COL2A1 were present in six probands, five of which presented with retinal detachment. De novo COL2A1 mutations were detected in 10 (37%) probands, with a mean paternal childbearing age of 29.64 ± 4.97 years old. The mutation features of probands with high myopia or retinal detachment showed that the probands had a high prevalence of COL2A1 mutations, truncational mutations, and de novo mutations. [ABSTRACT FROM AUTHOR]

Development of novel anticancer therapeutic candidates is one of the key challenges in medicinal chemistry. Podophyllotoxin and its derivatives, as a potent cytotoxic agent, have been at the center of extensive chemical amendment and pharmacological investigation. Herein, a new series of podophyllotoxin- N -sulfonyl amidine hybrids ( 4a - 4v , 5a - 5f ) were synthesized by a CuAAC/ring-opening procedure. All the synthesized podophyllotoxins derivatives were evaluated for in vitro cytotoxic activity against a panel of human lung (A-549) cancer cell lines. Different substituents', or functional groups' antiproliferative activities were discussed. The -CF 3 group performed best (IC 50 : 1.65 μM) and exhibited more potent activity than etoposide. Furthermore, molecular docking and dynamics studies were also conducted for active compounds and the results were in good agreement with the observed IC 50 values.