Innovative approaches for coronary heart disease management: integrating biomedical sensors, deep learning, and stellate ganglion modulation.

Coronary heart disease (CHD) is a significant global health concern, necessitating continuous advancements in treatment modalities to improve patient outcomes. Traditional Chinese medicine (TCM) offers alternative therapeutic approaches, but integration with modern biomedical technologies remains relatively unexplored. This study aimed to assess the efficacy of a combined treatment approach for CHD, integrating traditional Chinese medicinal interventions with modern biomedical sensors and stellate ganglion modulation. The objective was to evaluate the impact of this combined treatment on symptom relief, clinical outcomes, hemorheological indicators, and inflammatory biomarkers. A randomized controlled trial was conducted on 117 CHD patients with phlegm-turbidity congestion and excessiveness type. Patients were divided into a combined treatment group (CTG) and a traditional Chinese medicinal group (CMG). The CTG group received a combination of herbal decoctions, thread-embedding therapy, and stellate ganglion modulation, while the CMG group only received traditional herbal decoctions. The CTG demonstrated superior outcomes compared to the CMG across multiple parameters. Significant reductions in TCM symptom scores, improved clinical effects, reduced angina manifestation, favorable changes in hemorheological indicators, and decreased serum inflammatory biomarkers were observed in the CTG post-intervention. The combination of traditional Chinese medicinal interventions with modern biomedical sensors and stellate ganglion modulation has shown promising results in improving symptoms, clinical outcomes, and inflammatory markers in CHD patients. This holistic approach enhances treatment efficacy and patient outcomes. Further research and advancements in sensor technology are needed to optimize this approach.

Experimental Study on Geopolymerization of Lunar Soil Simulant under Dry Curing and Sealed Curing.

The construction of lunar surface roads is conducive to improving the efficiency of lunar space transportation. The use of lunar in situ resources is the key to the construction of lunar bases. In order to explore the strength development of a simulated lunar soil geopolymer at lunar temperature, geopolymers with different sodium hydroxide (NaOH) contents were prepared by using simulated lunar regolith materials. The temperature of the high-temperature section of the moon was simulated as the curing condition, and the difference in compressive strength between dry curing and sealed curing was studied. The results show that the high-temperature range of lunar temperature from 52.7 °C to 76.3 °C was the suitable curing period for the geopolymers, and the maximum strength of 72 h was 6.31 MPa when the NaOH content was 8% in the sealed-curing mode. The 72 h strength had a maximum value of 6.87 MPa when the NaOH content was 12% under dry curing. Choosing a suitable solution can reduce the consumption of activators required for geopolymers to obtain unit strength, effectively reduce the quality of materials transported from the Earth for lunar infrastructure construction, and save transportation costs. The microscopic results show that the simulated lunar soil generated gel substances and needle-like crystals under the alkali excitation of NaOH, forming a cluster and network structure to improve the compressive strength of the geopolymer.

Effect of natural polymer materials on skin healing based on internal wound microenvironment: a review.

The concept of wound microenvironment has been discussed for a long time. However, the mechanism of the internal microenvironment is relatively little studied. Here, we present a systematic discussion on the mechanism of natural polymer materials such as chitosan, cellulose, collagen and hyaluronic acid through their effects on the internal wound microenvironment and regulation of wound healing, in order to more comprehensively explain the concept of wound microenvironment and provide a reference for further innovative clinical for the preparation and application of wound healing agents.

Orthogonal light-triggered multiple effects based on photochromic nanoparticles for DNA cleavage and beyond.

Efficient and spatiotemporally controllable cleavage of deoxyribonucleic acid (DNA) is of great significance for both disease treatment (e.g. tumour, bacterial infection, etc) and molecular biology applications (e.g. gene editing). The recently developed light-induced cleavage strategy based on catalytic nanoparticles has been regarded as a promising strategy for DNA controllable cleavage. Although the regulation based on orthogonal light in biomedical applications holds more significant advantages than that based on single light, nanoparticle-mediated DNA cleavage based on orthogonal light has yet to be reported. In this article, for the first time, we demonstrated an orthogonal light-regulated nanosystem for efficient and spatiotemporal DNA cleavage. In this strategy, tungsten oxide (WO3) nanoparticles with photochromic properties were used as nano-antennae to convert the photoenergy from the orthogonal visible light (405 nm) and near-infrared light (808 nm) into chemical energy for DNA cleavage. We verified that only the orthogonal light can trigger high cleavage efficiency on different types of DNA. Moreover, such an orthogonal light-response nano-system can not only induce significant apoptosis of tumour cells, but also effectively eliminate bacterial biofilms.

Construction and Activity Study of a Natural Antibacterial Patch Based on Natural Active Substance-Green Porous Structures.

Bacterial infections are a serious threat to human health, and the rapid emergence of bacterial resistance caused by the abuse of antibiotics exacerbates the seriousness of this problem. Effectively utilizing natural products to construct new antimicrobial strategies is regarded as a promising way to suppress the rapid development of bacterial resistance. In this paper, we fabricated a new type of natural antibacterial patch by using a natural active substance (allicin) as an antibacterial agent and the porous structure of the white pulp of pomelo peel as a scaffold. The antibacterial activity and mechanisms were systematically investigated by using various technologies, including the bacteriostatic circle, plate counting, fluorescence staining, and a scanning electron microscope. Both gram-positive and negative bacteria can be effectively killed by this patch. Moreover, this natural antibacterial patch also showed significant anti-skin infection activity. This study provides a green approach for constructing efficient antibacterial patches.

Physicochemical and microstructural mechanisms for quality changes in lightly salted tilapia (Oreochromis niloticus) fillets during frozen storage.

BACKGROUND: Frozen tilapia fillet has become a leading aquatic product. High drip loss, dry and fibrous mouthfeel, and an unappealing appearance are its main problems. It was hypothesized that light salting could improve the quality, and that the preparation conditions would affect the storage stability of frozen tilapia fillets. RESULTS: The quality changes of lightly salted tilapia fillets were evaluated during frozen storage, and the underlying mechanisms were studied from the physicochemicaland microstructural perspectives. Though the salt content was 1.5% in all samples,the amount of ice crystals in frozen tissues decreased with the descending water content and freezing point (P < 0.05). No intracellular voids were observed in the samples prepared under proper salting conditions, and the myofibers were plump and smooth after freezing-thawing, which contributed to the high water-holding capacity of lightly salted fillets. After 28 days,the water-binding capacity of the salted groups was 14.69%-18.62% higher than that of their unsalted counterparts (P < 0.05). The reduced protein solubility in the salted fillets was likely to have occurred because the solubilized and unfolded proteins interacted more easily during frozen storage. The oxidation degree of myofibrillar proteins was also affected by salting condition, and the fillets with less oxidized sulfhydryl groups maintained high springiness after 28 days of frozen storage. CONCLUSION: The salting condition of 9% NaCl solution for 1 h was recommended for the preparation of lightly salted fillets from freshwater fish, taking into account quality, processing efficiency, and storage stability. The enhanced water-holding capacity and texture of lightly salted tilapia fillets were attributed to modified physicochemical and microstructural properties. These results could provide a scientific basis for the processing and storage of high-quality, frozen, lightly salted fillets from freshwater fish. © 2022 Society of Chemical Industry.

A Pan-Cancer Analysis of Transcriptome and Survival Reveals Prognostic Differentially Expressed LncRNAs and Predicts Novel Drugs for Glioblastoma Multiforme Therapy.

Numerous studies have identified various prognostic long non-coding RNAs (LncRNAs) in a specific cancer type, but a comprehensive pan-cancer analysis for prediction of LncRNAs that may serve as prognostic biomarkers is of great significance to be performed. Glioblastoma multiforme (GBM) is the most common and aggressive malignant adult primary brain tumor. There is an urgent need to identify novel therapies for GBM due to its poor prognosis and universal recurrence. Using available LncRNA expression data of 12 cancer types and survival data of 30 cancer types from online databases, we identified 48 differentially expressed LncRNAs in cancers as potential pan-cancer prognostic biomarkers. Two candidate LncRNAs were selected for validation in GBM. By the expression detection in GBM cell lines and survival analysis in GBM patients, we demonstrated the reliability of the list of pan-cancer prognostic LncRNAs obtained above. By constructing LncRNA-mRNA-drug network in GBM, we predicted novel drug-target interactions for GBM correlated LncRNA. This analysis has revealed common prognostic LncRNAs among cancers, which may provide insights into cancer pathogenesis and novel drug target in GBM.

Deep learning-based fully automated detection and segmentation of lymph nodes on multiparametric-mri for rectal cancer: A multicentre study.

BACKGROUND: Accurate lymph nodes (LNs) assessment is important for rectal cancer (RC) staging in multiparametric magnetic resonance imaging (mpMRI). However, it is incredibly time-consumming to identify all the LNs in scan region. This study aims to develop and validate a deep-learning-based, fully-automated lymph node detection and segmentation (auto-LNDS) model based on mpMRI. METHODS: In total, 5789 annotated LNs (diameter ≥ 3 mm) in mpMRI from 293 patients with RC in a single center were enrolled. Fused T2-weighted images (T2WI) and diffusion-weighted images (DWI) provided input for the deep learning framework Mask R-CNN through transfer learning to generate the auto-LNDS model. The model was then validated both on the internal and external datasets consisting of 935 LNs and 1198 LNs, respectively. The performance for LNs detection was evaluated using sensitivity, positive predictive value (PPV), and false positive rate per case (FP/vol), and segmentation performance was evaluated using the Dice similarity coefficient (DSC). FINDINGS: For LNs detection, auto-LNDS achieved sensitivity, PPV, and FP/vol of 80.0%, 73.5% and 8.6 in internal testing, and 62.6%, 64.5%, and 8.2 in external testing, respectively, significantly better than the performance of junior radiologists. The time taken for model detection and segmentation was 1.3 s/case, compared with 200 s/case for the radiologists. For LNs segmentation, the DSC of the model was in the range of 0.81-0.82. INTERPRETATION: This deep learning-based auto-LNDS model can achieve pelvic LNseffectively based on mpMRI for RC, and holds great potential for facilitating N-staging in clinical practice.

Establishment and development of national community-based collaborative innovation demonstration areas to achieve the control target of hepatitis B in China.

BACKGROUND: The major infectious diseases of hepatitis B has constituted an acute public health challenge in China. An effective and affordable HBV control model is urgently needed. A national project of Community-based Collaborative Innovation HBV (CCI-HBV) demonstration areas has optimized the existing community healthcare resources and obtained initial results in HBV control. METHODS: Based on the existing community healthcare network, CCI-HBV project combined the community health management and health contract signing service for long-staying residents in hepatitis B screening. Moreover, HBV field research strategy was popularized in CCI-HBV areas. After screening, patients with seropositive results were enrolled in corresponding cohorts and received treatment at an early stage. And the uninfected people received medical supports including health education through new media, behavior intervention and HBV vaccinations. In this process, a cloud-based National Information Platform (NIP) was established to collect and store residents' epidemiological data. In addition, a special quality control team was set up for CCI project. RESULTS: After two rounds of screening, HBsAg positive rate dropped from 5.05% (with 5,173,003 people screened) to 4.57% (with 3,819,675 people screened), while the rate of new HBV infections was 0.28 per 100 person-years in the fixed cohorts of 2,584,322 people. The quality control team completed PPS sampling simultaneously and established the serum sample database with 2,800,000 serum samples for unified testing. CONCLUSIONS: CCI-HBV project has established a large-scale field research to conduct whole-population screening and intervention. We analyzed the HBsAg prevalence and new infection rate of HBV in the fixed population for the epidemic trend and intervention effect. The purpose of CCI-HBV project is to establish and evaluate a practical model of grid management and field strategy, to realize the new goal to control hepatitis B in China. To provide policymakers with a feasible model, our results are directly applicable. TRIAL REGISTRATION: The project was funded by the Major Projects of Science Research for the 11th and 12th five-year plans of China, entitled "The prevention and control of AIDS, viral hepatitis and other major infectious diseases", Grant Nos. 2009ZX10004901, 2011ZX10004901, 2013ZX10004904, 2014ZX10004007 and 2014ZX10004008.

Full convolutional network based multiple side-output fusion architecture for the segmentation of rectal tumors in magnetic resonance images: A multi-vendor study.

PURPOSE: Accurate segmentation of rectal tumors is a basic and crucial task for diagnosis and treatment of rectal cancer. To avoid tedious manual delineation, an automatic rectal tumor segmentation model is proposed. METHODS: A pretrained Resnet50 model was introduced for feature extraction. To reduce the complexity of the model, all layers after the 13th residual block of ResNet50 were removed, and three side-output modules were added to the hidden layer of ResNet50 to guide multiscale feature learning. The final boundaries of tumors were determined by fusion of the predictions from side-output modules. The proposed model was compared with two other models, and the effects of different region of interest (ROI) sizes, loss functions, and side-output fusion strategy were also evaluated. RESULTS: The models were trained and evaluated on data from four clinical centers; T2-weighted magnetic resonance images (T2W-MRIs) from 461 patients in the first clinical center were used for training, while T2W-MRIs from 51 patients in the same clinical center and 56 patients in three other clinical centers were used for performance evaluation. The proposed model was superior to the two other models and achieved an average Dice similarity coefficient of 82.39%, sensitivity of 86.32%, specificity of 92.25%, and Hausdorff distance of 12.10 px. In addition, when the ROI contained rectal tumors, the smaller the ROI size, the higher the segmentation accuracy. For a certain ROI size, there were no considerable differences in segmentation results among the loss functions. Compared to the models with single side-output module, the proposed model performed better. CONCLUSIONS: The results show that the proposed model has potential clinical applications in rectal cancer treatment, particularly with regard to therapeutic response evaluation and preoperative planning.

Fully convolutional networks (FCNs)-based segmentation method for colorectal tumors on T2-weighted magnetic resonance images.

Segmentation of colorectal tumors is the basis of preoperative prediction, staging, and therapeutic response evaluation. Due to the blurred boundary between lesions and normal colorectal tissue, it is hard to realize accurate segmentation. Routinely manual or semi-manual segmentation methods are extremely tedious, time-consuming, and highly operator-dependent. In the framework of FCNs, a segmentation method for colorectal tumor was presented. Normalization was applied to reduce the differences among images. Borrowing from transfer learning, VGG-16 was employed to extract features from normalized images. We conducted five side-output blocks from the last convolutional layer of each block of VGG-16 along the network, these side-output blocks can deep dive multiscale features, and produced corresponding predictions. Finally, all of the predictions from side-output blocks were fused to determine the final boundaries of the tumors. A quantitative comparison of 2772 colorectal tumor manual segmentation results from T2-weighted magnetic resonance images shows that the average Dice similarity coefficient, positive predictive value, specificity, sensitivity, Hammoude distance, and Hausdorff distance were 83.56, 82.67, 96.75, 87.85%, 0.2694, and 8.20, respectively. The proposed method is superior to U-net in colorectal tumor segmentation (P < 0.05). There is no difference between cross-entropy loss and Dice-based loss in colorectal tumor segmentation (P > 0.05). The results indicate that the introduction of FCNs contributed to accurate segmentation of colorectal tumors. This method has the potential to replace the present time-consuming and nonreproducible manual segmentation method.

Hydroxycamptothecin liposomes based on thermal and magnetic dual-responsive system: preparation, in vitro and in vivo antitumor activity, microdialysis-based tumor pharmacokinetics.

Due to the absence of lactone form of hydroxycamptothecin, the commercially available hydroxycamptothecin injection exhibits inefficient therapeutic effects. In this study, we constructed a novel delivery system (thermosensitive magnetic liposomes) that protects lactone form of hydroxycamptothecin from blood or water. After hydroxycamptothecin was loaded into the thermosensitive magnetic liposome (HCPT/TML), its in vitro and in vivo antitumor activity and microdialysis-based tumour pharmacokinetics were determined. The results demonstrated that HCPT/TMLs possessed favourable physicochemical features and significant cytotoxicity against the Huh-7 cells in vitro. In the in vivo antitumor study and tumour pharmacokinetics, HCPT/TMLs displayed effective targeting delivery and antitumor effects, which corresponded to the determined hydroxycamptothecin concentration in tumour tissue. In conclusion, this thermal and magnetic dual-responsive system can efficiently deliver hydroxycamptothecin to tumour tissue and has great potential application in cancer treatment.

[Study on in vitro microdialysis recovery of hydroxycamptothecine].

OBJECTIVE: To establish the mothod to dectect the microdialysis recovery of HCPT and to investigate the influencing factors, thus to supply experimental basis for in-vivo microdialysis of HCPT. METHOD: The in vitro recovery of HCPT was detected by concentration difference method (increment method and decrement method). The influence of flow rates, medium concentration and temperature on the HCPT recovery and the stability were studied. RESULT: The recovery detected by increment method was the same as by decrement method. The recovery was independent of HCPT concentrations in the medium. The hydroxycamptothecine recovery had good stability and increased as the temperature rose. CONCLUSION: Microdialysis sampling can be used for the pharmacokinetic study of HCPT. Retrodialysis can be used for the determination of the HCPT in vivo recovery.