Development of protective fabric systems with spacer fabric and performance evaluation upon hot pressurized steam.

Developing new fabric systems with excellent thermal protective performance is essential to protecting workers from hot pressurized steam hazards. In this study, a laminated fabric was selected and a weft-knitted spacer fabric was developed for steam protective fabric systems. Effects of the configuration of the fabric systems and heat setting of spacer fabric on performances were investigated. The results demonstrate that the developed spacer fabric significantly prolonged skin burn times compared with controls. However, heat setting of spacer fabric had a negligible effect on improving thermal protective performance. Spacer fabric provided superior thermal protection while ensuring thermal comfort and enhancing air permeability, especially for spacer fabric after heat setting. Generally, a fabric system composed of a laminated outer shell and a spacer fabric is the best choice for steam protective clothing. The findings help develop a novel thermal liner to decrease energy transfer and provide better protection from pressurized steam.

An Efficient Muscle Segmentation Method Via Bayesian Fusion of Probabilistic Shape Modeling and Deep Edge Detection.

OBJECTIVE: Paraspinal muscle segmentation and reconstruction from MR images are critical to implement quantitative assessment of chronic and recurrent low back pains. Due to unclear muscle boundaries and shape variations, current segmentation methods demonstrate suboptimal performance with insufficient training samples. This work proposes a novel approach to modeling and inferring muscle shapes that enhances segmentation accuracy and efficiency with few training data. METHODS: Firstly, a probabilistic shape model (PSM) based on Fourier basis functions and Gaussian processes (GPs) is designed to encode 3D muscle shapes, where anatomical meanings are attributed to the model's geometric parameters. Muscle shape variations and correlations are described by the GPs of the geometric parameters, which allow a small size of parameters to model the distribution of muscle shapes. Secondly, a Bayesian framework is developed to achieve entire muscle segmentation by posterior estimations. The framework fuses the geometric prior of the PSM with observations of deep-learning-based edge detections (DED) and sparse manual annotations, by which issues of unclear boundaries and shape variations can be compensated. RESULTS AND CONCLUSION: Experiments on public and clinical datasets demonstrate that, with just three manually annotated slices, our method achieves a Dice similarity coefficient exceeding 90%, which outperforms other methods. Meanwhile, our method needs only a small training dataset and offers rapid inference speeds in clinical applications. SIGNIFICANCE: Our study enables precise assessment of paraspinal muscles in 2D and 3D, aiding clinicians and researchers in understanding muscle changes in various conditions, potentially enhancing treatment outcomes.

Trends and frontiers in signal amplification for aptamer-based tumor detection: A bibliometric analysis.

BACKGROUND: Malignant tumors are one of the leading causes of death worldwide, imposing a substantial economic and social burden. Early detection is the key to improving cure rates and reducing mortality rates, which requires the development of sensitive early detection technologies. Signal amplification techniques play a crucial role in aptamer-based early detection of tumors and are increasingly garnering attention from researchers. AIM: To investigate the current research status, developmental trajectories, and hotspots in signal amplification for aptamer-based tumor detection through bibliometric analysis. METHODS: English publications pertaining to signal amplification in aptamer-based tumor detection were retrieved from the Web of Science Core Collection database. VOSviewer and CiteSpace software were employed to analyze various information within this field, including countries, institutions, authors, co-cited authors, journals, co-cited journals, cited references, and keywords. RESULTS: A total of 757 publications were included in this study. China accounted for 85.47% of all publications, with Nanjing University (China) emerging as the institution with the highest publication output. The most influential authors and journals were Hasanzadeh M. from Iran and "Biosensors and Bioelectronics", respectively. Exosomes and carcinoembryonic antigen (CEA) stood out as the most researched tumor-related molecules. Currently, the predominant signal amplification technique, nanomaterial, and signal transduction method were identified as hybridization chain reactions, gold nanoparticles, and electrochemical methods, respectively. Over the past 3 years, exosomes, CEA, electrochemical biosensors, and nanosheets have emerged as research hotspots, exhibiting a robust burst of intensity. CONCLUSION: This study is the first bibliometric analysis of literature on signal amplification in aptamer-based tumor detection and elucidates the current status, hotspots, and prospective research directions within this realm. Additionally, it provides an important reference for researchers.

Targeted screening of multiple anti-inflammatory components from Chrysanthemi indici Flos by ligand fishing with affinity UF-LC/MS.

Chrysanthemi indic Flos (CIF) has been commonly consumed for the treatment of inflammation and related skin diseases. However, the potential bioactive components responsible for its anti-inflammatory and sensitive skin (SS) improvement activities, and the correlated mechanisms of action still remain unknown. In this work, it was firstly found that the CIF extract (CIFE) displayed arrestive free radical scavenging activity on DPPH and ABTS radicals, with no significant difference with positive control Trolox (p > 0.05). Then, compared to the negative group, CIFE markedly decreased the productions of the pro-inflammatory cytokines (IL-1ß, IL-6, PEG2, TNF-α, IFN-γ, NO) in LPS induced RAW264.7 cells in a dose-dependent manner (p < 0.01). Besides, CIFE strongly inhibited the COX-2 and hyaluronidase (HAase) with the IC50 values of 1.06 ± 0.01 µg/mL and 12.22 ± 0.39 µg/mL, indicating higher inhibitory effect than positive control of aspirin of 6.33 ± 0.05 µg/mL (p < 0.01), and comparable inhibitory effect with indometacin of 0.60 ± 0.03 µg/mL, and ascorbic acid of 11.03 ± 0.41 µg/mL (p > 0.05), respectively. Furthermore, kinetic assays with Lineweaver-Burk plot (Michaelis Menten equation) suggested that CIFE reversibly inhibited the COX-2 and HAase, with a mixed characteristics of competitive and non-competitive inhibition. Thereafter, multi-target affinity ultrafiltration liquid chromatography-mass spectrometry (UF-LC/MS) method was employed to fast fish out the potential COX-2 and HAase in CIFE. Herein, 13 components showed various affinity binding degrees to the COX-2 and HAase, while those components with relative binding affinity (RBA) value higher than 3.0, such as linarin and chlorogenic acid isomers, were deemed to be the most bioactive components for the anti-inflammatory and SS improvement activities of CIFE. Finally, the interaction mechanism, including binding energy, inhibition constant, docking sites, and the key amino acids involved in hydrogen bonds between the potential ligands and COX-2/HAase were simulated and confirmed with the molecule docking analysis. In summary, this study showcased the prominent anti-inflammatory and SS improvement activities of CIF, which would provide further insights on this functional medicinal plant to be a natural anti-SS remedy.

Exploring potential inhibitors of acetylcholinesterase, lactate dehydrogenases, and glutathione reductase from Hagenia abyssinica (Bruce) J.F. Gmel. based on multi-target ultrafiltration-liquid chromatography-mass spectrometry and molecular docking.

ETHNOPHARMACOLOGICAL RELEVANCE: Parasitic infections impose a significant burden on public health worldwide. European pharmacopoeia records and ethnopharmacological studies indicate that Hagenia abyssinica (Bruce) J.F. Gmel. has traditionally been used to treat a variety of parasitic infections, while the potential antiparasitic compounds remain ambiguous. AIM OF THE STUDY: Acetylcholinesterase (AChE), lactate dehydrogenases (LDH), and glutathione reductase (GR) are the key target enzymes in the survival of parasites. The aim of our work was to screen antiparasitic compounds targeting AChE, LDH, and GR from H. abyssinica. MATERIALS AND METHODS: Ultrafiltration-liquid chromatography-mass spectrometry (UF-LC-MS) combined with molecular docking was used in this study. Therein, the alamarBlue® and Ellman's methods were employed to reveal the antitrypanosomal effect and AChE inhibitory activity. Meanwhile, the UF-LC-MS was carried out to screen the potential active compounds from H. abyssinica. Subsequently, molecular docking was performed to evaluate the binding mechanisms of these active compounds with AChE, LDH, and GR. Finally, the AChE inhibitory activity of potential inhibitors was detected in vitro. RESULTS: H. abyssinica exhibited significant antitrypanosomal and AChE inhibitory activity. Corilagin, brevifolin carboxylic acid, brevifolin, quercetin, and methyl ellagic acid were recognized as potential AChE inhibitors by UF-LC-MS, while methyl brevifolin carboxylate was identified as AChE, LDH, and GR multi-target inhibitor, with binding degree ranged from 20.96% to 49.81%. Molecular docking showed that these potential inhibitors had a strong affinity with AChE, LDH, and GR, with binding energies ranging from -6.98 to -9.67 kcal/mol. These findings were further supported by the observation that corilagin, quercetin, brevifolin carboxylic acid, and methyl brevifolin carboxylate displayed significant AChE inhibitory activity compared with the positive control (gossypol, 0.42 ± 0.04 mM), with IC50 values of 0.15 ± 0.05, 0.56 ± 0.03, 0.99 ± 0.01, and 1.02 ± 0.03 mM, respectively. CONCLUSIONS: This study confirms the antiparasitic potential of H. abyssinica, supporting the traditional use of H. abyssinica in local ethnopharmacology to treat parasites. At the same time, corilagin, brevifolin carboxylic acid, brevifolin, quercetin, methyl ellagic acid, and methyl brevifolin carboxylate exert their anti-parasitic effects by inhibiting AChE, LDH, and GR, and they are expected to be natural lead compounds for the treatment of parasitic diseases.

Artificial intelligence in skeletal metastasis imaging.

In the field of metastatic skeletal oncology imaging, the role of artificial intelligence (AI) is becoming more prominent. Bone metastasis typically indicates the terminal stage of various malignant neoplasms. Once identified, it necessitates a comprehensive revision of the initial treatment regime, and palliative care is often the only resort. Given the gravity of the condition, the diagnosis of bone metastasis should be approached with utmost caution. AI techniques are being evaluated for their efficacy in a range of tasks within medical imaging, including object detection, disease classification, region segmentation, and prognosis prediction in medical imaging. These methods offer a standardized solution to the frequently subjective challenge of image interpretation.This subjectivity is most desirable in bone metastasis imaging. This review describes the basic imaging modalities of bone metastasis imaging, along with the recent developments and current applications of AI in the respective imaging studies. These concrete examples emphasize the importance of using computer-aided systems in the clinical setting. The review culminates with an examination of the current limitations and prospects of AI in the realm of bone metastasis imaging. To establish the credibility of AI in this domain, further research efforts are required to enhance the reproducibility and attain robust level of empirical support.

An enhanced broad-spectrum peptide inhibits Omicron variants in vivo.

The continual emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) poses a major challenge to vaccines and antiviral therapeutics due to their extensive evasion of immunity. Aiming to develop potent and broad-spectrum anticoronavirus inhibitors, we generated A1-(GGGGS)7-HR2m (A1L35HR2m) by introducing an angiotensin-converting enzyme 2 (ACE2)-derived peptide A1 to the N terminus of the viral HR2-derived peptide HR2m through a long flexible linker, which showed significantly improved antiviral activity. Further cholesterol (Chol) modification at the C terminus of A1L35HR2m greatly enhanced the inhibitory activities against SARS-CoV-2, SARS-CoV-2 VOCs, SARS-CoV, and Middle East respiratory syndrome coronavirus (MERS-CoV) pseudoviruses, with IC50 values ranging from 0.16 to 5.53 nM. A1L35HR2m-Chol also potently inhibits spike-protein-mediated cell-cell fusion and the replication of authentic Omicron BA.2.12.1, BA.5, and EG.5.1. Importantly, A1L35HR2m-Chol distributed widely in respiratory tract tissue and had a long half-life (>10 h) in vivo. Intranasal administration of A1L35HR2m-Chol to K18-hACE2 transgenic mice potently inhibited Omicron BA.5 and EG.5.1 infection both prophylactically and therapeutically.

SIGMA leverages protein structural information to predict the pathogenicity of missense variants.

Leveraging protein structural information to evaluate pathogenicity has been hindered by the scarcity of experimentally determined 3D protein. With the aid of AlphaFold2 predictions, we developed the structure-informed genetic missense mutation assessor (SIGMA) to predict missense variant pathogenicity. In comparison with existing predictors across labeled variant datasets and experimental datasets, SIGMA demonstrates superior performance in predicting missense variant pathogenicity (AUC = 0.933). We found that the relative solvent accessibility of the mutated residue contributed greatly to the predictive ability of SIGMA. We further explored combining SIGMA with other top-tier predictors to create SIGMA+, proving highly effective for variant pathogenicity prediction (AUC = 0.966). To facilitate the application of SIGMA, we pre-computed SIGMA scores for over 48 million possible missense variants across 3,454 disease-associated genes and developed an interactive online platform (https://www.sigma-pred.org/). Overall, by leveraging protein structure information, SIGMA offers an accurate structure-based approach to evaluating the pathogenicity of missense variants.

First-line bevacizumab plus chemotherapy in Chinese patients with stage III/IV epithelial ovarian cancer, fallopian tube cancer or primary peritoneal cancer: a phase III randomized controlled trial.

OBJECTIVE: First-line bevacizumab plus carboplatin and paclitaxel (CP) is approved for stage III/IV ovarian cancer treatment following initial surgical resection, based on global phase III GOG-0218 and ICON7 trials. This study evaluated the efficacy and safety of bevacizumab + CP as first-line ovarian cancer therapy in Chinese patients. METHODS: Patients with newly diagnosed, International Federation of Gynecology and Obstetrics (FIGO) stage III/IV epithelial ovarian, fallopian tube, or primary peritoneal cancer post-primary surgery were randomized 1:1 to receive 6 cycles of CP with bevacizumab/placebo, followed by bevacizumab/placebo maintenance until unacceptable toxicity or disease progression. Primary endpoint was investigator-assessed progression-free survival (PFS). Stratification factors were FIGO stage and debulking status (stage III optimally debulked vs stage III suboptimally debulked vs stage IV) and Eastern Cooperative Oncology Group performance status (0 vs 1 or 2). RESULTS: Of randomized patients, 51 received bevacizumab + CP and 49 received placebo + CP. Median PFS was 22.6 months with bevacizumab + CP (95% confidence interval [CI]=18.6, not estimable) and 12.3 months (95% CI=9.5, 15.0) with placebo + CP (stratified hazard ratio=0.30; 95% CI=0.17, 0.53). Treatment-related grade 3/4 adverse events occurred in 46 of 49 (94%) patients receiving bevacizumab + CP, and 34 of 50 (68%) receiving placebo + CP. CONCLUSION: Bevacizumab + CP showed clinically meaningful improvement in PFS vs placebo + CP, consistent with GOG-0218 results. Safety data were aligned with the known bevacizumab safety profile. These results support first-line bevacizumab + CP therapy in Chinese patients with ovarian cancer. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03635489.

Unraveling the genetic architecture of congenital vertebral malformation with reference to the developing spine.

Congenital vertebral malformation, affecting 0.13-0.50 per 1000 live births, has an immense locus heterogeneity and complex genetic architecture. In this study, we analyze exome/genome sequencing data from 873 probands with congenital vertebral malformation and 3794 control individuals. Clinical interpretation identifies Mendelian etiologies in 12.0% of the probands and reveals a muscle-related disease mechanism. Gene-based burden test of ultra-rare variants identifies risk genes with large effect sizes (ITPR2, TBX6, TPO, H6PD, and SEC24B). To further investigate the biological relevance of the genetic association signals, we perform single-nucleus RNAseq on human embryonic spines. The burden test signals are enriched in the notochord at early developmental stages and myoblast/myocytes at late stages, highlighting their critical roles in the developing spine. Our work provides insights into the developmental biology of the human spine and the pathogenesis of spine malformation.