Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study.

OBJECTIVE: To develop a multi-instance learning (MIL) based artificial intelligence (AI)-assisted diagnosis models by using laryngoscopic images to differentiate benign and malignant vocal fold leukoplakia (VFL). METHODS: The AI system was developed, trained and validated on 5362 images of 551 patients from three hospitals. Automated regions of interest (ROI) segmentation algorithm was utilized to construct image-level features. MIL was used to fusion image level results to patient level features, then the extracted features were modeled by seven machine learning algorithms. Finally, we evaluated the image level and patient level results. Additionally, 50 videos of VFL were prospectively gathered to assess the system's real-time diagnostic capabilities. A human-machine comparison database was also constructed to compare the diagnostic performance of otolaryngologists with and without AI assistance. RESULTS: In internal and external validation sets, the maximum area under the curve (AUC) for image level segmentation models was 0.775 (95 % CI 0.740-0.811) and 0.720 (95 % CI 0.684-0.756), respectively. Utilizing a MIL-based fusion strategy, the AUC at the patient level increased to 0.869 (95 % CI 0.798-0.940) and 0.851 (95 % CI 0.756-0.945). For real-time video diagnosis, the maximum AUC at the patient level reached 0.850 (95 % CI, 0.743-0.957). With AI assistance, the AUC improved from 0.720 (95 % CI 0.682-0.755) to 0.808 (95 % CI 0.775-0.839) for senior otolaryngologists and from 0.647 (95 % CI 0.608-0.686) to 0.807 (95 % CI 0.773-0.837) for junior otolaryngologists. CONCLUSIONS: The MIL based AI-assisted diagnosis system can significantly improve the diagnostic performance of otolaryngologists for VFL and help to make proper clinical decisions.

Multi-Instance Learning for Vocal Fold Leukoplakia Diagnosis Using White Light and Narrow-Band Imaging: A Multicenter Study.

OBJECTIVES: Vocal fold leukoplakia (VFL) is a precancerous lesion of laryngeal cancer, and its endoscopic diagnosis poses challenges. We aim to develop an artificial intelligence (AI) model using white light imaging (WLI) and narrow-band imaging (NBI) to distinguish benign from malignant VFL. METHODS: A total of 7057 images from 426 patients were used for model development and internal validation. Additionally, 1617 images from two other hospitals were used for model external validation. Modeling learning based on WLI and NBI modalities was conducted using deep learning combined with a multi-instance learning approach (MIL). Furthermore, 50 prospectively collected videos were used to evaluate real-time model performance. A human-machine comparison involving 100 patients and 12 laryngologists assessed the real-world effectiveness of the model. RESULTS: The model achieved the highest area under the receiver operating characteristic curve (AUC) values of 0.868 and 0.884 in the internal and external validation sets, respectively. AUC in the video validation set was 0.825 (95% CI: 0.704-0.946). In the human-machine comparison, AI significantly improved AUC and accuracy for all laryngologists (p < 0.05). With the assistance of AI, the diagnostic abilities and consistency of all laryngologists improved. CONCLUSIONS: Our multicenter study developed an effective AI model using MIL and fusion of WLI and NBI images for VFL diagnosis, particularly aiding junior laryngologists. However, further optimization and validation are necessary to fully assess its potential impact in clinical settings. LEVEL OF EVIDENCE: 3 Laryngoscope, 2024.

Innovative utilization of ultra-wide field fundus images and deep learning algorithms for screening high-risk posterior polar cataract.

PURPOSE: To test a cataract shadow projection theory and validate it by developing a deep learning algorithm that enables automatic and stable posterior polar cataract (PPC) screening using fundus images. SETTING: Department of Ophthalmology, Far Eastern Memorial Hospital, New Taipei, Taiwan. DESIGN: Retrospective chart review. METHODS: A deep learning algorithm to automatically detect PPC was developed based on the cataract shadow projection theory. Retrospective data (n = 546) with ultra-wide field fundus images were collected, and various model architectures and fields of view were tested for optimization. RESULTS: The final model achieved 80% overall accuracy, with 88.2% sensitivity and 93.4% specificity in PPC screening on a clinical validation dataset (n = 103). CONCLUSIONS: This study established a significant relationship between PPC and the projected shadow, which may help surgeons to identify potential PPC risks preoperatively and reduce the incidence of posterior capsular rupture during cataract surgery.

Improving preliminary clinical diagnosis accuracy through knowledge filtering techniques in consultation dialogues.

BACKGROUND AND OBJECTIVE: Symptom descriptions by ordinary people are often inaccurate or vague when seeking medical advice, which often leads to inaccurate preliminary clinical diagnoses. To address this issue, we propose a deep learning model named the knowledgeable diagnostic transformer (KDT) for the natural language processing (NLP)-based preliminary clinical diagnoses. METHODS: The KDT extracts symptom-disease relation triples (h,r,t) from patient symptom descriptions by using a proposed bipartite medical knowledge graph (bMKG). To avoid too many relation triples causing the knowledge noise issue, we propose a knowledge inclusion-exclusion approach (KIA) to eliminate undesirable triples (a knowledge filtering layer). Next, we combine token embedding techniques with the transformer model to predict the diseases that patients may encounter. RESULTS: To train the KDT, a medical diagnosis question-answering dataset (named MDQA dataset) containing large-scale, high-quality questions (patient syndrome description) and answering (diagnosis) corpora with 2.6M entries (1.07GB in size) in Mandarin was built. We also train the KDT with the National Institutes of Health (NIH) English dataset (MedQuAD). The KDT marks a transformative approach by achieving a remarkable accuracy of 99% for different evaluation metrics when compared with the baseline transformers used for the NLP-based preliminary clinical diagnoses approaches. CONCLUSIONS: In essence, our study not only demonstrates the effectiveness of the KDT in enhancing diagnostic precision but also underscores its potential to revolutionize the field of preliminary clinical diagnoses. By harnessing the power of knowledge-based approaches and advanced NLP techniques, we have paved the way for more accurate and reliable diagnoses, ultimately benefiting both healthcare providers and patients. The KDT has the potential to significantly reduce misdiagnoses and improve patient outcomes, marking a pivotal advancement in the realm of medical diagnostics.

Melatonin alleviates valproic acid-induced neural tube defects by modulating Src/PI3K/ERK signaling and oxidative stress.

Neural tube defects (NTDs) represent a developmental disorder of the nervous system that can lead to significant disability in children and impose substantial social burdens. Valproic acid (VPA), a widely prescribed first-line antiepileptic drug for epilepsy and various neurological conditions, has been associated with a 4-fold increase in the risk of NTDs when used during pregnancy. Consequently, urgent efforts are required to identify innovative prevention and treatment approaches for VPA-induced NTDs. Studies have demonstrated that the disruption in the delicate balance between cell proliferation and apoptosis is a crucial factor contributing to NTDs induced by VPA. Encouragingly, our current data reveal that melatonin (MT) significantly inhibits apoptosis while promoting the restoration of neuroepithelial cell proliferation impaired by VPA. Moreover, further investigations demonstrate that MT substantially reduces the incidence of neural tube malformations resulted from VPA exposure, primarily by suppressing apoptosis through the modulation of intracellular reactive oxygen species levels. In addition, the Src/PI3K/ERK signaling pathway appears to play a pivotal role in VPA-induced NTDs, with significant inhibition observed in the affected samples. Notably, MT treatment successfully reinstates Src/PI3K/ERK signaling, thereby offering a potential underlying mechanism for the protective effects of MT against VPA-induced NTDs. In summary, our current study substantiates the considerable protective potential of MT in mitigating VPA-triggered NTDs, thereby offering valuable strategies for the clinical management of VPA-related birth defects.

Diversities of disability caused by lung cancer in the 66 Belt and Road initiative countries: a secondary analysis from the Global Burden of Disease Study 2019.

Objectives: Due to the increase in life expectancy and the aging of the global population, the "Belt and Road" ("B&R") countries are faced with varying degrees of lung cancer threat. The purpose of this study is to analyze the differences in the burden and trend of lung cancer disability in the "B&R" countries from 1990 to 2019 so as to provide an analytical strategic basis to build a healthy "B&R". Methods: Data were derived from the Global Burden of Disease 2019 (GBD 2019). Incidence, mortality, prevalence, the years lived with disability (YLDs), and disability-adjusted life years (DALYs) of lung cancer and those attributable to different risk factors were measured from 1990 to 2019. Trends of disease burden were estimated by using the average annual percent change (AAPC), and the 95% uncertainty interval (UI) was reported. Results: China, India, and the Russian Federation were the three countries with the highest burden of lung cancer in 2019. From 1990 to 2019, the AAPC of incidence, prevalence, mortality, and DALYs generally showed a downward trend in Central Asia (except Georgia) and Eastern Europe, while in China, South Asia (except Bangladesh), most countries in North Africa, and the Middle East, the trend was mainly upward. The AAPC of age-standardized incidence was 1.33% (1.15%-1.50%); the AAPC of prevalence, mortality, and DALYs from lung cancer in China increased by 24% (2.10%-2.38%), 0.94% (0.74%-1.14%), and 0.42% (0.25%-0.59%), respectively. A downward trend of the AAPC values of age-standardized YLD rate in men was shown in the vast majority of "B&R" countries, but for women, most countries had an upward trend. For adults aged 75 years or older, the age-standardized YLD rate showed an increasing trend in most of the "B&R" countries. Except for the DALY rate of lung cancer attributable to metabolic risks, a downward trend of the DALY rate attributable to all risk factors, behavioral risks, and environmental/occupational risks was shown in the vast majority of "B&R" countries. Conclusion: The burden of lung cancer in "B&R" countries varied significantly between regions, genders, and risk factors. Strengthening health cooperation among the "B&R" countries will help to jointly build a community with a shared future for mankind.

A modified SELEX approach to identify DNA aptamers with binding specificity to the major histocompatibility complex presenting ovalbumin model antigen.

Aptamers have sparked significant interest in cell recognition because of their superior binding specificity and biocompatibility. Cell recognition can be mediated by targeting the major histocompatibility complex (MHC) that presents short peptides derived from intracellular antigens. Although numerous antibodies have demonstrated a specific affinity for the peptide-MHC complex, the number of aptamers that exhibit comparable characteristics is limited. Aptamers are usually selected from large libraries via the Systemic Evolution of Ligands by Exponential Enrichment (SELEX), an iterative process of selection and PCR amplification to enrich a pool of aptamers with high affinity. However, the success rate of aptamer identification is low, possibly due to the presence of complementary sequences or sequences rich in guanine and cytosine that are less accessible for primers. Here, we modified SELEX by employing systemic consecutive selections with minimal PCR amplification. We also modified the analysis by selecting aptamers that were identified in multiple selection rounds rather than those that are highly enriched. Using this approach, we were able to identify two aptamers with binding specificity to cells expressing the ovalbumin alloantigen as a proof of concept. These two aptamers were also discovered among the top 150 abundant candidates, despite not being highly enriched, by performing conventional SELEX. Additionally, we found that highly enriched aptamers tend to contain fractions of the primer sequence and have minimal target affinity. Candidate aptamers are easily missed in the conventional SELEX process. Therefore, our modification for SELEX may facilitate the identification of aptamers for more application in diverse biomedical fields. Significance: we modify the conventional method to improve the efficiency in the identification of the aptamer, a single strand of nucleic acid with binding specificity to the target molecule, showing as a proof of concept that this approach is particularly useful to select aptamers that can selectively bind to cells presenting a particular peptide by the major histocompatibility complex (MHC) on the cell surface. Given that cancer cells may express mutant peptide-MHC complexes that are distinct from those expressed by normal cells, this study sheds light on the potential application of aptamers to cancer cell targeting.

AEP-cleaved DDX3X induces alternative RNA splicing events to mediate cancer cell adaptation in harsh microenvironments.

Oxygen and nutrient deprivation are common features of solid tumors. Although abnormal alternative splicing (AS) has been found to be an important driving force in tumor pathogenesis and progression, the regulatory mechanisms of AS that underly the adaptation of cancer cells to harsh microenvironments remain unclear. Here, we found that hypoxia- and nutrient deprivation-induced asparagine endopeptidase (AEP) specifically cleaved DDX3X in a HIF1A-dependent manner. This cleavage yields truncated carboxyl-terminal DDX3X (tDDX3X-C), which translocates and aggregates in the nucleus. Unlike intact DDX3X, nuclear tDDX3X-C complexes with an array of splicing factors and induces AS events of many pre-mRNAs; for example, enhanced exon skipping (ES) in exon 2 of the classic tumor suppressor PRDM2 leads to a frameshift mutation of PRDM2. Intriguingly, the isoform ARRB1-Δexon 13 binds to glycolytic enzymes and regulates glycolysis. By utilizing in vitro assays, glioblastoma organoids, and animal models, we revealed that AEP/tDDX3X-C promoted tumor malignancy via these isoforms. More importantly, high AEP/tDDX3X-C/ARRB1-Δexon 13 in cancerous tissues was tightly associated with poor patient prognosis. Overall, our discovery of the effect of AEP-cleaved DDX3X switching on alternative RNA splicing events identifies a mechanism in which cancer cells adapt to oxygen and nutrient shortages and provides potential diagnostic and/or therapeutic targets.

Novel Bimolecular Fluorescence Complementation (BiFC) Assay for Visualization of the Protein-Protein Interactions and Cellular Protein Complex Localizations.

Investigations of protein-protein interactions (PPIs) are of paramount importance for comprehending cellular processes within biological systems. The bimolecular fluorescence complementation (BiFC) assay presents a convenient methodology for visualizing PPIs within live cells. While a range of fluorescent proteins have been introduced into the BiFC system, there is a growing demand for new fluorescent proteins to accommodate the expanding requirements of researchers. This study describes the introduction of Tagged blue fluorescent protein 2 (TagBFP2) into the BiFC assay to verify the interaction between two proteins, with Enhanced yellow fluorescent protein (EYFP) employed as a positive control. Both fluorescent proteins demonstrated optimal performance in this study. Compared to EYFP, the BiFC system utilizing TagBFP2 yielded a higher signal-to-noise ratio, which facilitated differentiation of the signal of PPIs from noise and enabled employment of other fluorescent proteins within the BiFC assay. Notably, the utilization of a fluorescent secondary antibody in immunofluorescence applications or the tagging of an interest protein with a fluorescent protein occupied the green or yellow channel. Overall, the present article introduces a BiFC assay that is highly straightforward, reliable, and replicable, with the ability to be completed within 1 week. This method requires neither expensive instrumentation nor technical skills of a high order.

Effect of age on postural performance and control strategies during changes in visual input and dual-tasking stances.

Background: With age, people begin to experience deterioration in standing balance, especially when sensory input is suddenly removed or added. Here, we sought to explore the effects of age on postural performance and postural control strategies. Methods: The convenience sample consisted of 15 young, 10 middle-aged, and 14 elderly healthy adults. They were instructed to stand with their feet together in four randomly administered conditions involving visual input removal/addition and single-/dual-tasking. Dual-tasking involved continuous subtraction by 3s. Results: Postural sway displacement in the two older groups seemed larger than that in the younger group; however, neither the main effect of group (F2, 36 = 1.152, p = .327) nor the group × time interaction effect (F4, 27 = 0.229, p = .922) was significant. Greater stiffness of the lower leg muscles was observed in the vision-addition condition than in the vision-removal condition in only the elderly group (t13 = -2.755, p = .016). The dual-tasking condition resulted in smaller sway displacement (F1, 36 = 7.690, p = .009) and greater muscle stiffness (F1, 36 = 5.495, p = .025). In the vision-removal condition, the increase in muscle stiffness due to dual-tasking was significantly larger in the middle-aged (t9 = -3.736, p = .005) and elderly groups (t13 = -2.512, p = .026). Conclusions: In healthy older individuals, age-related changes were observed in control strategies used to maintain standing balance upon changes in visual input. The dual-task paradigm induced the use of an ankle-stiffening strategy in middle-aged and elderly adults.

Preclinical study of LMP1-RNAi-based anti-tumor therapy in EBV-positive nasopharyngeal carcinoma.

RNA interference (RNAi) treatment has been proven to be an important therapeutic approach in cancer based on downregulation of target-oncogenes, but its clinical efficacy still needs further investigation. LMP1 is usually presented by Epstein-Barr virus (EBV)-positive tumor cells like EBV-associated nasopharyngeal carcinoma (NPC) and acts as an oncogene in tumorigenesis. However, the mechanism of LMP1 as a proto-oncogene in nasopharyngeal carcinoma is still unclear. Two sequence-specific shRNAs 1 and 2 were designed to target the different nucleotide loci of EBV latent antigen LMP1 gene and a series of in vivo and in vitro experiments were performed to investigate the therapeutic effect of sequence-specific shRNAs targeting LMP1 and its related molecular mechanisms in EBV-positive NPC. LMP1-shRNA2 generated a truncated LMP1 mRNA and protein, whereas LMP1-shRNA1 completely blocked LMP1 mRNA and protein expression. Both LMP1-shRNAs inhibited the proliferation and migration of NPC cells overexpressing LMP1 (NPC-LMP1) as well as the NPC-associated myeloid-derived suppressor cell (MDSC) expansion in vitro. However, LMP1-shRNA2 maintained the immunogenicity of NPC-LMP1 cells, which provoked MHC-class I-dependent T cell recognition. LMP1-shRNAs inhibited tumor growth in nude mice but did not reach statistical significance compared to control groups, while the LDH nanoparticle loaded LMP1-shRNAs and the antigen-specific T cells induced by NPC-LMP1 cells treated with LMP1-shRNA2 significantly reduced tumor growth in vivo. LMP1-RNAi-based anti-tumor therapy could be a new hope for the clinical efficacy of RNAi treatment of tumors like NPC.

Efficient oily wastewater treatment by a novel electroflotation-membrane separation system consisting a Ni-Cu-P membrane prepared by electroless nickel plating.

Electroflotation-membrane separation system with a conductive membrane has recently emerged as a promising technology for oily wastewater treatment. However, the conductive membrane prepared by electroless plating often suffers the problems of low stability and high activation cost. To solve these problems, this work proposed a new strategy regarding surface metallization of polymeric membrane by surface nickel-catalyzed electroless nickel plating of nickel­copper­phosphorus alloys for the first time. It was found that, addition of copper source remarkably enhanced the membranes' hydrophilicity, corrosion resistance and fouling resistance. The Ni-Cu-P membrane had an underwater oil contact angle of up to 140°, and simultaneously possessed rejection rate > 98 % with rather high flux of 65,663.0 L·m-2·h-1 and excellent cycling stability when separating n-hexane/water mixtures under gravity drive. The permeability is higher than the state-of-the-art membranes for oil/water separation. The Ni-Cu-P membrane as the cathode can be assembled into an electroflotation-membrane separation system, allowing to separate oil-in-water emulsion with 99 % rejection. Meanwhile, the applied electric field significantly improved membrane flux and fouling resistance (flux recovery up to 91 %) when separate kaolin suspensions. Polarization curve and Nyquist curve analysis further confirmed that addition of Cu element obviously enhanced corrosion resistance of the Ni modified membrane. This work provided a novel strategy to make up high-efficiency membranes for oily wastewater treatment.

Synergistic Association of Hepatitis B Surface Antigen and Plasma Epstein-Barr Virus DNA Load on Distant Metastasis in Patients With Nasopharyngeal Carcinoma.

Importance: Hepatitis B surface antigen (HBsAg) reportedly increases the risk of distant metastasis among patients with nasopharyngeal carcinoma (NPC). However, the associated potential interaction and changes in hazard ratios (HRs) between HBsAg and different plasma Epstein-Barr (EBV) DNA levels are unknown. Moreover, the potential HBsAg-positive-associated NPC metastatic mechanism remains unclear. Objective: To investigate the prognostic value and biological associations of HBsAg and plasma EBV DNA levels on distant metastasis in patients with NPC. Design, Setting, and Participants: Retrospective cohort study performed at Sun Yat-sen University Cancer Center between January 2010 and January 2013. A total of 792 patients with nonmetastatic NPC were enrolled. The median (range) follow-up time was 62.1 (1.4-83.4) months. Of these patients, 17.8% presented with HBsAg positivity. Cytological experiments were performed to evaluate the role of HBsAg in the invasion and migration of EBV-positive NPC cells. Data analysis was performed from July 2020 to April 2021. Main Outcomes and Measures: The primary end point was distant metastasis-free survival. Association rules were used to identify new rules related to distant metastasis. Interaction plots, univariate and multivariate Cox regression analyses, stratification analysis, and quantification using HRs were conducted. Additionally, cell migration and invasion assays, as well as Western blotting, were performed in the cytological validation. Results: Among the 792 patients, 576 (72.7%) were male, with a median (IQR) age of 45 (38-53) years. The HBsAg-positive group exhibited a significant interaction and increased risk of distant metastasis when plasma EBV DNA cutoff levels were 1.5 × 1000 copies/mL or greater. The HR was 9.16 (95% CI, 2.46-34.14) when the plasma EBV DNA load reached 6 × 1000 copies/mL, which was higher than that in patients with stage IV disease (HR, 2.01; 95% CI, 1.13-3.56; P = .02). In cytological experiments, HBsAg promoted epithelial-mesenchymal transition by upregulating vimentin and fibronectin in EBV-positive NPC cells in vitro, thereby promoting invasion and migration of EBV-positive NPC cells. Conclusions and Relevance: In this cohort study, the observed synergistic association between HBsAg and plasma EBV DNA load represented a novel potential mechanism underlying the increased risk of distant metastasis in patients with NPC. Hence, attention should be paid to patients with NPC with HBsAg positivity, especially when the plasma EBV DNA level is 6 × 1000 copies/mL or greater. Consideration of this synergistic association will contribute to more accurate individualized management.

Covalent Organic Frameworks: The Rising-Star Platforms for the Design of CO2 Separation Membranes.

Membrane-based carbon dioxide (CO2 ) capture and separation technologies have aroused great interest in industry and academia due to their great potential to combat current global warming, reduce energy consumption in chemical separation of raw materials, and achieve carbon neutrality. The emerging covalent organic frameworks (COFs) composed of organic linkers via reversible covalent bonds are a class of porous crystalline polymers with regular and extended structures. The inherent structure and customizable organic linkers give COFs high and permanent porosity, short transport channel, tunable functionality, and excellent stability, thereby enabling them rising-star alternatives for developing advanced CO2 separation membranes. Therefore, the promising research areas ranging from development of COF membranes to their separation applications have emerged. Herein, this review first introduces the main advantages of COFs as the state-of-the-art membranes in CO2 separation, including tunable pore size, modifiable surfaces property, adjustable surface charge, excellent stability. Then, the preparation approaches of COF-based membranes are systematically summarized, including in situ growth, layer-by-layer stacking, blending, and interface engineering. Subsequently, the key advances of COF-based membranes in separating various CO2 mixed gases, such as CO2 /CH4 , CO2 /H2 , CO2 /N2 , and CO2 /He, are comprehensively discussed. Finally, the current issues and further research expectations in this field are proposed.

Efficient oil-water emulsion treatment via novel composite membranes fabricated by CaCO3-based biomineralization and TA-Ti(IV) coating strategy.

Continuous increasing discharge of industrial oily wastewater and frequent occurrence of oil spill accidents have taken heavy tolls on global environment and human health. Organic-inorganic modifications can fabricate superhydrophilic/submerged superoleophobic membranes for efficient oil-water separation/treatment though they still suffer from complex operation, non-environmental friendliness, expensive cost or uneven distribution. Herein, a new strategy regarding tannic acid (TA)-Ti(IV) coating and CaCO3-based biomineralization through simple inkjet printing processes was proposed to modify polyvinylidene fluoride (PVDF) membrane, endowing the membrane with high hydrophilicity (water contact angle (WCA) decreased from 86.01° to 14.94°) and underwater superoleophobicity (underwater contact angle (UOCA) > 155°). The optimized TA-Ti(IV)-CaCO3 modified membrane possessed perfect water permeation to various oil/water emulsions (e.g., 355.7 L·m-2·h-1 for gasoline emulsion) under gravity with superior separation efficiency (>98.8 %), leading the way in oil/water emulsion separation performance of PVDF membranes modified with polyphenolic surfaces to our knowledge. Moreover, the modified membrane displayed rather high flux recovery after eight cycles of filtration while maintaining the original excellent separation efficiency. The modification process proposed in this study is almost independent of the nature of the substrate, and meets the demand for simple, inexpensive, rapid preparation of highly hydrophilic antifouling membranes, showing abroad application prospect for oil-water emulsion separation/treatment.

Preclinical study of LMP1-RNAi-based anti-tumor therapy in EBV-positive nasopharyngeal carcinoma

RNA interference (RNAi) treatment has been proven to be an important therapeutic approach in cancer based on downregulation of target-oncogenes, but its clinical efficacy still needs further investigation. LMP1 is usually presented by Epstein-Barr virus (EBV)-positive tumor cells like EBV-associated nasopharyngeal carcinoma (NPC) and acts as an oncogene in tumorigenesis. However, the mechanism of LMP1 as a proto-oncogene in nasopharyngeal carcinoma is still unclear. Two sequence-specific shRNAs 1 and 2 were designed to target the different nucleotide loci of EBV latent antigen LMP1 gene and a series of in vivo and in vitro experiments were performed to investigate the therapeutic effect of sequence-specific shRNAs targeting LMP1 and its related molecular mechanisms in EBV-positive NPC. LMP1-shRNA2 generated a truncated LMP1 mRNA and protein, whereas LMP1-shRNA1 completely blocked LMP1 mRNA and protein expression. Both LMP1-shRNAs inhibited the proliferation and migration of NPC cells overexpressing LMP1 (NPC-LMP1) as well as the NPC-associated myeloid-derived suppressor cell (MDSC) expansion in vitro. However, LMP1-shRNA2 maintained the immunogenicity of NPC-LMP1 cells, which provoked MHC-class I-dependent T cell recognition. LMP1-shRNAs inhibited tumor growth in nude mice but did not reach statistical significance compared to control groups, while the LDH nanoparticle loaded LMP1-shRNAs and the antigen-specific T cells induced by NPC-LMP1 cells treated with LMP1-shRNA2 significantly reduced tumor growth in vivo. LMP1-RNAi-based anti-tumor therapy could be a new hope for the clinical efficacy of RNAi treatment of tumors like NPC.

Construction and performance analysis of a solar thermophotovoltaic system targeting on the efficient utilization of AM0 space solar radiation.

Solar thermophotovoltaic (STPV) has great potential as efficient power supply source for spacecraft to meet the demand of spacecraft miniaturization. In this work, a novel space STPV system is proposed to achieve the efficient utilization of the AM0 space solar radiation. Metamaterial structures were designed and FDTD method is used to analyze their radiation regulation mechanism. A multi-layer cylindrical periodic structure is used as the absorber which realizes a total absorptance of 0.9283 to AM0 radiation. A cylindrical periodic structure is used as the emitter to reshape the broadband thermal radiation as narrowband to match with the Si/InGaAsSb tandem cell, which realizes a highest TPV efficiency of 51.36%. System performance analysis is conducted and the system presents a highest STPV efficiency of 40.86% and good adaptability under wide range of operating parameters, which reveals its great potential to realize the efficient utilization of AM0 solar radiation for space power supply.

Bed-Exit Behavior Recognition for Real-Time Images within Limited Range.

In the context of behavior recognition, the emerging bed-exit monitoring system demands a rapid deployment in the ward to support mobility and personalization. Mobility means the system can be installed and removed as required without construction; personalization indicates human body tracking is limited to the bed region so that only the target is monitored. To satisfy the above-mentioned requirements, the behavior recognition system aims to: (1) operate in a small-size device, typically an embedded system; (2) process a series of images with narrow fields of view (NFV) to detect bed-related behaviors. In general, wide-range images are preferred to obtain a good recognition performance for diverse behaviors, while NFV images are used with abrupt activities and therefore fit single-purpose applications. This paper develops an NFV-based behavior recognition system with low complexity to realize a bed-exit monitoring application on embedded systems. To achieve effectiveness and low complexity, a queueing-based behavior classification is proposed to keep memories of object tracking information and a specific behavior can be identified from continuous object movement. The experimental results show that the developed system can recognize three bed behaviors, namely off bed, on bed and return, for NFV images with accuracy rates of 95~100%.

Deep learning driven biosynthetic pathways navigation for natural products with BioNavi-NP.

The complete biosynthetic pathways are unknown for most natural products (NPs), it is thus valuable to make computer-aided bio-retrosynthesis predictions. Here, a navigable and user-friendly toolkit, BioNavi-NP, is developed to predict the biosynthetic pathways for both NPs and NP-like compounds. First, a single-step bio-retrosynthesis prediction model is trained using both general organic and biosynthetic reactions through end-to-end transformer neural networks. Based on this model, plausible biosynthetic pathways can be efficiently sampled through an AND-OR tree-based planning algorithm from iterative multi-step bio-retrosynthetic routes. Extensive evaluations reveal that BioNavi-NP can identify biosynthetic pathways for 90.2% of 368 test compounds and recover the reported building blocks as in the test set for 72.8%, 1.7 times more accurate than existing conventional rule-based approaches. The model is further shown to identify biologically plausible pathways for complex NPs collected from the recent literature. The toolkit as well as the curated datasets and learned models are freely available to facilitate the elucidation and reconstruction of the biosynthetic pathways for NPs.