Macrophages and pulmonary fibrosis: a bibliometric and visual analysis of publications from 1990 to 2023.

Background: The role of macrophages in the symptomatic and structural progression of pulmonary fibrosis (PF) has garnered significant scholarly attention in recent years. This study employs a bibliometric approach to examine the present research status and areas of focus regarding the correlation between macrophages and PF, aiming to provide a comprehensive understanding of their relationship. Methodology: The present study employed VOSviewer, CiteSpace, and Microsoft Excel software to visualize and analyze various aspects such as countries, institutions, authors, journals, co-cited literature, keywords, related genes, and diseases. These analyses were conducted using the Web of Science core collection database. Results: A comprehensive collection of 3,479 records pertaining to macrophages and PF from the period of 1990 to 2023 was obtained. Over the years, there has been a consistent increase in research literature on this topic. Notably, the United States and China exhibited the highest level of collaboration in this field. Through careful analysis, the institutions, authors, and prominent journals that hold significant influence within this particular field have been identified as having the highest publication output. The pertinent research primarily concentrates on the domains of Biology and Medicine. The prevailing keywords encompass pulmonary fibrosis, acute lung injury, idiopathic pulmonary fibrosis, and others. Notably, TGFß1, TNF, and CXCL8 emerge as the most frequently studied targets, primarily associated with signaling pathways such as cytokine-cytokine receptor interaction. Additionally, cluster analysis of related diseases reveals their interconnectedness with ailments such as cancer. Conclusion: The present study employed bibliometric methods to investigate the knowledge structure and developmental trends in the realm of macrophage and PF research. The findings shed light on the introduction and research hotspots that facilitate a more comprehensive understanding of macrophages and PF.

Varying ratios of M/G in alginate to modulate macrophages polarization and its application for wound healing in diabetic.

Alginate (SA) comprises repeating unis of ß-1, 4 linked ß-D-mannuronic acid (M) and α-L-guloronic acid (G) in varying proportions. The M/G ratio greatly impacts its anti-inflammatory properties in tissue healing wound, as less knowledge reported. This study examined the performances of both SA and SA hydrogel crosslinked with copper ions (SA-Cu) with different M/G ratios are studied. SA with higher M/G ratios stimulated macrophage migration and shifted from M0 to the pro-inflammatory Ml phenotype, while lower M/G ratios shifted from M1 to the pro-repair M2 phenotype. Furthermore, SA-Cu hydrogels with lower M/G ratios exhibited enhanced cross-linking degree, mechanical and rheological properties, as well Cu releasing rate. The reason may be attributed to a relative easy binding between Cu ions and G unit among Cu ions, M unit and G unit. In vitro cell evaluation showed that SA-Cu hydrogel with M/G ratio of 1:1 activated M2 macrophages and up-regulated anti-inflammatory cytokines expression more effectively than those of SA-Cu ratios (2:1) and (1:2). In vivo, SA-Cu hydrogel with M/G ratio of 1:1 expedited diabetic wound healing, accelerating infiltration and phenotype shift of M2 macrophages, and enhancing anti-inflammatory factors, epithelialization and collagen deposition in healing phases. This research highlights the significant role of M/G ratios in SA materials in influencing macrophage behavior and inflammatory responses, which would benefit its application field.

FPNC Net: A hydrogenation catalyst image recognition algorithm based on deep learning.

The identification research of hydrogenation catalyst information has always been one of the most important businesses in the chemical industry. In order to aid researchers in efficiently screening high-performance catalyst carriers and tackle the pressing challenge at hand, it is imperative to find a solution for the intelligent recognition of hydrogenation catalyst images. To address the issue of low recognition accuracy caused by adhesion and stacking of hydrogenation catalysts, An image recognition algorithm of hydrogenation catalyst based on FPNC Net was proposed in this paper. In the present study, Resnet50 backbone network was used to extract the features, and spatially-separable convolution kernel was used to extract the multi-scale features of catalyst fringe. In addition, to effectively segment the adhesive regions of stripes, FPN (Feature Pyramid Network) is added to the backbone network for deep and shallow feature fusion. Introducing an attention module to adaptively adjust weights can effectively highlight the target features of the catalyst. The experimental results showed that the FPNC Net model achieved an accuracy of 94.2% and an AP value improvement of 19.37% compared to the original CenterNet model. The improved model demonstrates a significant enhancement in detection accuracy, indicating a high capability for detecting hydrogenation catalyst targets.

Chlamydia trachomatis upregulates lncRNA CYTOR to mediate autophagy through miR-206/MAPK1 axis.

Chlamydia trachomatis infection can be regulated by autophagy-related genes. LncRNA CYTOR has been proven to be involved in autophagy. In this research, we investigated the role of CYTOR in autophagy induced by C. trachomatis and the potential mechanisms. After C. trachomatis infection, CYTOR and MAPK1 were up-regulated and miR-206 was down-regulated, meanwhile, the autophagy-related protein Beclin1 and LC3-Ⅱ/LC3-Ⅰ ratio were increased. Interference with CYTOR or overexpression with miR-206 downregulated the autophagy-related protein Beclin1 and the number of autophagic spots LC3, decreased the protein ratio of LC3-II/LC3-I, and upregulated the expression of P62 protein. The luciferase reporter assay confirmed that CYTOR acted as a sponge for miR-206 to target MAPK1. In addition, CYTOR promoted autophagy induced by C. trachomatis infection through the MAPK1/ERK signaling pathway activation. Taken together, we have identified a novel molecular mechanism that the CYTOR/miR-206/MAPK1 axis was involved in the regulation of autophagy in C. trachomatis infection. This work provides an experimental basis for elucidating the pathogenesis of C. trachomatis for the treatment, prevention and control of related infectious diseases.

Turning Ultra-Low Coercivity and Ultra-High Temperature Stability Within 897 K via Continuous Crystal Ordering Fluctuations.

High-performance soft magnetic materials are important for energy conservation and emission reduction. One challenge is achieving a combination of reliable temperature stability, high resistivity, high Curie temperature, and high saturation magnetization in a single material, which often comes at the expense of intrinsic coercivity-a typical trade-off in the family of soft magnetic materials with homogeneous microstructures. Herein, a nanostructured FeCoNiSiAl complex concentrated alloy is developed through a hierarchical structure strategy. This alloy exhibits superior soft magnetic properties up to 897 K, maintaining an ultra-low intrinsic coercivity (13.6 A m-1 at 297 K) over a wide temperature range, a high resistivity (138.08 µΩ cm-1 at 297 K) and the saturation magnetization with only a 16.7% attenuation at 897 K. These unusual property combinations are attributed to the dual-magnetic-state nature with exchange softening due to continuous crystal ordering fluctuations at the atomic scale. By deliberately controlling the microstructure, the comprehensive performance of the alloy can be tuned and controlled. The research provides valuable guidance for the development of soft magnetic materials for high-temperature applications and expands the potential applications of related functional materials in the field of sustainable energy.

Joinpoint regression analysis of recent trends in desmoplastic malignant melanoma incidence and mortality: 15-year multicentre retrospective study.

BACKGROUND: Recent data reveal a marked rise in the detection and mortality rates of Desmoplastic Malignant Melanoma (DMM). This trend underscores the imperative for an in-depth analysis of DMM's epidemiology, which is crucial for the formulation of precise medical and public health strategies. This investigation seeks to elucidate the variations in the incidence and mortality of DMM over a 15-year period (2005-2019). METHODS: Data on DMM patients was sourced from the Surveillance, Epidemiology, and End Results (SEER) database. Both incidence and incidence-based mortality rates (IBM) were directly extracted from the SEER database. Joinpoint regression was used to analyze and calculate the average annual percent change (AAPC) and its 95% confidence interval (CI). RESULTS: Between 2005 and 2019, 3,384 DMM cases were identified, boasting an age-adjusted incidence rate of 36.3 cases per 1000,000 person-years (95% CI 3.51-3.76) and an IBM of 1.65cases per 1000,000 person-years (95% CI 1.57-1.74). Of these, 2,353 were males (69.53%) and 1,031 were females (30.47%). There were 1894 patients (55.97%) who were over 70 years old. Predominantly, DMM lesions manifested in exposed areas: Limbs (955, 28.22%), Face (906, 26.77%), and Scalp and Neck (865, 25.56%). The incidence of DMM increased significantly at a rate of APC = 0.9% during 2005-2019, while the incidence-based mortality showed a significant upward trend (APC = 7%) during 2005-2012, and slowly increasing trend (APC = 0.6%) during 2012-2019. In contrast to the modest upward trajectory in female incidence and mortality, male incidence initially surged, later declining, while male mortality peaked and stabilized post-2012. The primary sites for incidence and mortality were chronically sun-exposed areas: Face, Scalp and Neck, and Limbs. CONCLUSIONS: In recent years, the incidence and incidence-based mortality of DMM have significantly increased. Each subgroup analysis has different trends, and these trends can provide better support for our exploration of DMM.

Multidimensional Refinement Graph Convolutional Network With Robust Decouple Loss for Fine-Grained Skeleton-Based Action Recognition.

Graph convolutional networks (GCNs) have been widely used in skeleton-based action recognition. However, existing approaches are limited in fine-grained action recognition due to the similarity of interclass data. Moreover, the noisy data from pose extraction increase the challenge of fine-grained recognition. In this work, we propose a flexible attention block called channel-variable spatial-temporal attention (CVSTA) to enhance the discriminative power of spatial-temporal joints and obtain a more compact intraclass feature distribution. Based on CVSTA, we construct a multidimensional refinement GCN (MDR-GCN) that can improve the discrimination among channel-, joint-, and frame-level features for fine-grained actions. Furthermore, we propose a robust decouple loss (RDL) that significantly boosts the effect of the CVSTA and reduces the impact of noise. The proposed method combining MDR-GCN with RDL outperforms the known state-of-the-art skeleton-based approaches on fine-grained datasets, FineGym99 and FSD-10, and also on the coarse NTU-RGB + D 120 dataset and NTU-RGB + D X-view version. Our code is publicly available at https://github.com/dingyn-Reno/MDR-GCN.

Carbon sequestration costs and spatial spillover effects in China's collective forests.

BACKGROUND: Global climate change is one of the major challenges facing the world today, and forests play a crucial role as significant carbon sinks and providers of ecosystem services in mitigating climate change and protecting the environment. China, as one of the largest developing countries globally, owns 60% of its forest resources collectively. Evaluating the carbon sequestration cost of collective forests not only helps assess the contribution of China's forest resources to global climate change mitigation but also provides important evidence for formulating relevant policies and measures. RESULTS: Over the past 30 years, the carbon sequestration cost of collective forests in China has shown an overall upward trend. Except for coastal provinces, southern collective forest areas, as well as some southwestern and northeastern regions, have the advantage of lower carbon sequestration costs. Furthermore, LSTM network predictions indicate that the carbon sequestration cost of collective forests in China will continue to rise. By 2030, the average carbon sequestration cost of collective forests is projected to reach 125 CNY per ton(= 16.06 Euros/t). Additionally, there is spatial correlation in the carbon sequestration cost of collective forests. Timber production, labor costs, and labor prices have negative spatial spillover effects on carbon sequestration costs, while land opportunity costs, forest accumulation, and rural resident consumption have positive spatial spillover effects. CONCLUSION: The results of this study indicate regional disparities in the spatial distribution of carbon sequestration costs of collective forests, with an undeniable upward trend in future cost growth. It is essential to focus on areas with lower carbon sequestration costs and formulate targeted carbon sink economic policies and management measures to maximize the carbon sequestration potential of collective forests and promote the sustainable development of forestry.

Valorization of Nannochloropsis oceanica for integrated co-production of violaxanthin cycle carotenoids.

The development of integrated co-production of multiple high-purity carotenoids from microalgal cells holds considerable significance for the valorization of microalgae. In this study, the economical microalga Nannochloropsis oceanica was identified as an accumulator of violaxanthin cycle carotenoids, including violaxanthin, antheraxanthin, and zeaxanthin. Notably, a novel and competent approach for the integrated co-production of violaxanthin cycle carotenoids was explored, encompassing four steps: microalgal cultivation, solvent extraction, octadecylsilyl open-column chromatography, and ethanol precipitation. Under optimal co-production conditions, the purities of the obtained violaxanthin, antheraxanthin, and zeaxanthin all exceeded 92%, with total recovery rates of approximately 51%, 40%, and 60%, respectively. Utilizing nuclear magnetic resonance techniques, the purified violaxanthin, antheraxanthin, and zeaxanthin were identified as all-trans-violaxanthin, all-trans-antheraxanthin, and all-trans-zeaxanthin, respectively. This method held significance for the multiproduct biorefinery of the microalga N. oceanica and carried potential future implications for the violaxanthin cycle carotenoids.

Mediator subunit MED8 interacts with heat shock transcription factor HSF3 to promote fucoxanthin synthesis in the diatom Phaeodactylum tricornutum.

Fucoxanthin, a natural carotenoid that has substantial pharmaceutical value due to its anticancer, antioxidant, antiobesity, and antidiabetic properties, is biosynthesized from glyceraldehyde-3-phosphate (G3P) via a series of enzymatic reactions. However, our understanding of the transcriptional mechanisms involved in fucoxanthin biosynthesis remains limited. Using reverse genetics, the med8 mutant was identified based on its phenotype of reduced fucoxanthin content, and the biological functions of MED8 in fucoxanthin synthesis were characterized using approaches such as gene expression, protein subcellular localization, protein-protein interaction and chromatin immunoprecipitation assay. Gene-editing mutants of MED8 exhibited decreased fucoxanthin content as well as reduced expression levels of six key genes involved in fucoxanthin synthesis, namely DXS, PSY1, ZDS-like, CRTISO5, ZEP1, and ZEP3, when compared to the wild-type (WT) strain. Furthermore, we showed that MED8 interacts with HSF3, and genetic analysis revealed their shared involvement in the genetic pathway governing fucoxanthin synthesis. Additionally, HSF3 was required for MED8 association with the promoters of the six fucoxanthin synthesis genes. In conclusion, MED8 and HSF3 are involved in fucoxanthin synthesis by modulating the expression of the fucoxanthin synthesis genes. Our results increase the understanding of the molecular regulation mechanisms underlying fucoxanthin synthesis in the diatom P. tricornutum.

Effect of Survivin Down-Regulation by Egr1-Survivin shRNA Combined with Radiotherapy on Radiosensitivity of Esophageal Squamous Carcinoma / Efecto de la Regulación Negativa de Survivina por shRNA de Egr1-Survivina Combinado con Radioterapia sobre la Radiosensibilidad del Carcinoma Escamoso de Esófago

SUMMARY: This study is to investigate the effect of survivin down-regulation by Egr1-survivin shRNA combined with radiotherapy on the apoptosis and radiosensitivity of esophageal squamous cell carcinoma ECA109 and KYSE150 cells. ECA109 and KYSE150 cells were transfected with Egr1-survivin shRNA, and then treated with radiotherapy. After 24 h, the mRNA and protein levels of Egr1-survivin were detected by qPCR and Western-Blot. Cell cycle and apoptosis were detected by flow cytometry. Western blot also detected levels of cleavaged Caspase 3 and Caspase 9. YM155 was used as a positive control to inhibit survivin expression. The levels of survivin mRNA and protein in ECA109 and KYSE150 cells treated with Egr1-survivin shRNA combined with radiotherapy were significantly lower than those of the blank control group, the empty vector control group, and, the YM155 + radiotherapy group (P<0.05). Meanwhile, after survivin down-regulation, the ratio of G2 to S phase of ECA109 and KYSE150 cells increased significantly, leading to significant G2 and S phase arrest. Additionally, apoptosis of ECA109 and KYSE150 cells increased significantly (P <0.01). Further, protein levels of cleavaged Caspase 3 and Caspase 9 significantly increased in Egr1-survivin shRNA combined with radiotherapy group. Egr1-survivin shRNA combined with radiotherapy can down-regulate survivin expression, which further increases the apoptosis, and enhances the radiosensitivity of ECA109 and KYSE150 cells.

Este estudio tuvo como objetivo investigar el efecto de la regulación negativa de survivina por el shRNA de Egr1-survivina combinado con radioterapia sobre la apoptosis y la radiosensibilidad del carcinoma de células escamosas de esófago Células ECA109 y KYSE150. Las células ECA109 y KYSE150 se transfectaron con shRNA de survivina Egr1 y luego se trataron con radioterapia. Después de 24 h, los niveles de ARNm y proteína de Egr1-survivina se detectaron mediante qPCR y Western-Blot. El ciclo celular y la apoptosis se detectaron mediante citometría de flujo. La transferencia Western también detectó niveles de Caspasa 3 y Caspasa 9 escindidas. Se usó YM155 como control positivo para inhibir la expresión de survivina. Los niveles de ARNm y proteína de survivina en células ECA109 y KYSE150 tratadas con shRNA de survivina Egr1 combinado con radioterapia fueron significativamente más bajos que los del grupo control en blanco, el grupo control de vector vacío y el grupo de radioterapia YM155 + (P <0,05). Mientras tanto, después de la regulación negativa de survivina, la proporción entre las fases G2 y S de las células ECA109 y KYSE150 aumentó significativamente, lo que llevó a una detención significativa de las fases G2 y S. Además, la apoptosis de las células ECA109 y KYSE150 aumentó significativamente (P <0,01). Además, los niveles de proteína de Caspasa 3 y Caspasa 9 escindidas aumentaron significativamente en el shRNA de Egr1- survivina combinado con el grupo de radioterapia. El shRNA de survivina de Egr1 combinado con radioterapia puede regular negativamente la expresión de survivina, lo que aumenta aún más la apoptosis y mejora la radiosensibilidad de las células ECA109 y KYSE150.

Design of Power Amplifiers for BDS-3 Terminal Based on InGaP/GaAs HBT MMIC and LGA Technology.

With the development and popularization of the Beidou-3 navigation satellite system (BDS-3), to ensure its unique short message function, it is necessary to integrate a radio frequency (RF) transmitting circuit with high performance in the BDS-3 terminal. As the key device in an RF transmitting circuit, the RF power amplifier (PA) largely determines the comprehensive performance of the circuit with its transmission power, efficiency, linearity, and integration. Therefore, in this paper, an L-band highly integrated PA chip compatible with 3 W and 5 W output power is designed in InGaP/GaAs heterojunction bipolar transistor (HBT) technology combined with temperature-insensitive adaptive bias technology, class-F harmonic suppression technology, analog pre-distortion technology, temperature-insensitive adaptive power detection technology, and land grid array (LGA) packaging technology. Additionally, three auxiliary platforms are proposed, dedicated to the simulation and optimization of the same type of PA designs. The simulation results show that at the supply voltage of 5 V and 3.5 V, the linear gain of the PA chip reaches 39.4 dB and 38.7 dB, respectively; the output power at 1 dB compression point (P1dB) reaches 37.5 dBm and 35.1 dBm, respectively; the saturated output power (Psat) reaches 38.2 dBm and 36.2 dBm, respectively; the power added efficiency (PAE) reaches 51.7% and 48.2%, respectively; and the higher harmonic suppression ratios are less than -62 dBc and -65 dBc, respectively. The size of the PA chip is only 6 × 4 × 1 mm3. The results also show that the PA chip has high gain, high efficiency, and high linearity under both output power conditions, which has obvious advantages over similar PA chip designs and can meet the short message function of the BDS-3 terminal in various application scenarios.

Deep-learning-based survival prediction of patients with lower limb melanoma.

BACKGROUND: For the purpose to examine lower limb melanoma (LLM) and its long-term survival rate, we used data from the Surveillance, Epidemiology and End Results (SEER) database. To estimate the prognosis of LLM patients and assess its efficacy, we used a powerful deep learning and neural network approach called DeepSurv. METHODS: We gathered data on those who had an LLM diagnosis between 2000 and 2019 from the SEER database. We divided the people into training and testing cohorts at a 7:3 ratio using a random selection technique. To assess the likelihood that LLM patients would survive, we compared the results of the DeepSurv model with those of the Cox proportional-hazards (CoxPH) model. Calibration curves, the time-dependent area under the receiver operating characteristic curve (AUC), and the concordance index (C-index) were all used to assess how accurate the predictions were. RESULTS: In this study, a total of 26,243 LLM patients were enrolled, with 7873 serving as the testing cohort and 18,370 as the training cohort. Significant correlations with age, gender, AJCC stage, chemotherapy status, surgery status, regional lymph node removal and the survival outcomes of LLM patients were found by the CoxPH model. The CoxPH model's C-index was 0.766, which signifies a good degree of predicted accuracy. Additionally, we created the DeepSurv model using the training cohort data, which had a higher C-index of 0.852. In addition to calculating the 3-, 5-, and 8-year AUC values, the predictive performance of both models was evaluated. The equivalent AUC values for the CoxPH model were 0.795, 0.767, and 0.847, respectively. The DeepSurv model, in comparison, had better AUC values of 0.872, 0.858, and 0.847. In comparison to the CoxPH model, the DeepSurv model demonstrated greater prediction performance for LLM patients, as shown by the AUC values and the calibration curve. CONCLUSION: We created the DeepSurv model using LLM patient data from the SEER database, which performed better than the CoxPH model in predicting the survival time of LLM patients.

Cost-effectiveness analysis of dostarlimab plus carboplatin-paclitaxel as first-line treatment for advanced endometrial cancer.

Background: A recent phase III clinical trial (NCT03981796) evaluated the efficacy and safety of dostarlimab combined with carboplatin-paclitaxel (DOS-CP) compared to placebo combined with carboplatin-paclitaxel (PLB-CP) as a first-line treatment for advanced endometrial cancer (EC). The NCT03981796 trial demonstrated that DOS-CP significantly improved progression-free survival and overall survival of patients with advanced EC while maintaining an acceptable safety profile. However, DOS-CP is expensive and its cost-effectiveness has not been evaluated. This study aims to evaluate the cost-effectiveness of DOS-CP compared to PLB-CP as a first-line treatment for advanced EC from the perspective of the Chinese healthcare system. Methods: A Markov model with three health states was developed to evaluate the cost-effectiveness of DOS-CP as a first-line treatment for advanced EC. Clinical efficacy data were derived from the NCT03981796 trial, and drug costs were determined based on national tender prices. Other costs and utility values were obtained from published literature. The outcomes assessed included total costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs). The robustness of the model was assessed through one-way sensitivity analysis and probabilistic sensitivity analysis. Results: In comparison to PLB-CP, the ICER of DOS-CP was $98,276.61/QALY for the overall population, $53,063.61/QALY for the dMMR subgroup, and $124,088.56/QALY for the pMMR subgroup. All of these ICER values were higher than the willingness-to-pay threshold of $38,201 per QALY. The most important variable that affected the results of the model was the discount rate, the cost of dostarlimab, and the utility value for progressive disease. Conclusion: From the perspective of the Chinese healthcare system, DOS-CP is unlikely to be a cost-effective first-line treatment option for advanced EC.

Fucoxanthin, a marine derived carotenoid, attenuates surgery-induced cognitive impairments via activating Akt and ERK pathways in aged mice.

BACKGROUND: Fucoxanthin is the most abundant marine carotenoid derived from brown seaweeds, possesses antioxidant, anti-inflammatory, and neuroprotective properties, and might be benefit for the treatment of neurological disorders. Post-operative cognitive dysfunction (POCD) is a neurological symptom with learning and memory impairments, mainly affecting the elderly after surgery. However, there is no effective treatments for this symptom. PURPOSES: In this study, we evaluated the neuroprotective effects of fucoxanthin against POCD in aged mice after surgery. STUDY DESIGN AND METHODS: The animal model of POCD was established in 12 - 14 month aged mice with a laparotomy. Curcumin was used as a positive control. The beneficial effects of fucoxanthin on POCD was analyzed by behavioral tests. Pro-inflammatory cytokines were measured by Enzyme-linked Immunosorbent Assay (ELISA). And the expressions of key proteins in the Akt and ERK signaling pathways were analyzed by Western blotting analysis. The morphology of microglial cells and astrocytes was explored by immunohistochemical staining. The activity of antioxidant superoxide dismutase (SOD) and catalase (CAT) were measured by anti-oxidative enzyme activity assays. RESULTS: Fucoxanthin at 100 - 200 mg/kg significantly attenuated cognitive dysfunction, with a similar potency as curcumin, in aged mice after surgery. In addition, fucoxanthin and curcumin significantly increased the expression of pAkt, prevented the activation of microglial cells and astrocytes, and inhibited the secretion of pro-inflammatory interleukin-1ß (IL - 1ß) and tumor necrosis factor-α (TNF-α). Furthermore, fucoxanthin and curcumin elevated the ERK pathway and potently increased the activity of antioxidant enzymes. Most importantly, U0126, an inhibitor of the ERK pathway, and wortmannin, an inhibitor of the Akt pathway, significantly abolished the cognitive-enhancing effects, as well as the inhibition of neuroinflammation and the reduction of oxidative stress, induced by fucoxanthin in aged mice after surgery. CONCLUSION: Fucoxanthin might be developed as a functional food or drug for the treatment of POCD by inhibiting neuroinflammation and enhancing antioxidant capacity via the activation of the Akt and ERK signaling pathways.

Valorization of Phaeodactylum tricornutum for integrated preparation of diadinoxanthin and fucoxanthin.

Integrated preparation of high-purity carotenoids from marine microalgae using green and efficient methods still faces enormous challenges. In this study, valorization of the economic Phaeodactylum tricornutum using integrated preparation of diadinoxanthin (Ddx) and fucoxanthin (Fx) was explored containing four steps including algae cultivation, solvent extraction, ODS open-column chromatography, and ethanol precipitation for the first time. Several essential key factors were optimized for simultaneously extracting Ddx and Fx from P. tricornutum. ODS open-column chromatography was used to isolate Ddx and Fx. Purification of Ddx and Fx was accomplished using ethanol precipitation. After optimization, the purity of Ddx and Fx was more than 95%, and the total recovery rates of Ddx and Fx were approximately 55% and 85%, respectively. The purified Ddx and Fx were identified as all-trans-diadinoxanthin and all-trans-fucoxanthin, respectively. The antioxidant capacity of the purified Ddx and Fx was assessed using two tests in vitro: DPPH and ABTS radical assays.

Performances of artificial intelligence in detecting pathologic myopia: a systematic review and meta-analysis.

BACKGROUND/OBJECTIVE: Pathologic myopia (PM) is a major cause of severe visual impairment and blindness, and current applications of artificial intelligence (AI) have covered the diagnosis and classification of PM. This meta-analysis and systematic review aimed to evaluate the overall performance of AI-based models in detecting PM and related complications. METHODS: We searched PubMed, Scopus, Embase, Web of Science and IEEE Xplore for eligible studies before Dec 20, 2022. The methodological quality of included studies was evaluated using the Quality Assessment for Diagnostic Accuracy Studies (QUADAS-2). We calculated the pooled sensitivity (SEN), specificity (SPE) and the summary area under the curve (AUC) using a random effects model, to evaluate the performance of AI in the detection of PM based on fundus or optical coherence tomography (OCT) images. RESULTS: 22 studies were included in the systematic review, and 14 of them were included in the quantitative analysis. Of all included studies, SEN and SPE ranged from 80.0% to 98.7% and from 79.5% to 100.0% for PM detection, respectively. For the detection of PM, the summary AUC was 0.99 (95% confidence interval (CI) 0.97 to 0.99), and the pooled SEN and SPE were 0.95 (95% CI 0.92 to 0.96) and 0.97 (95% CI: 0.94 to 0.98), respectively. For the detection of PM-related choroid neovascularization (CNV), the summary AUC was 0.99 (95% CI: 0.97 to 0.99). CONCLUSION: Our review demonstrated the excellent performance of current AI algorithms in detecting PM and related complications based on fundus and OCT images.

A nomogram for predicting survival in patients with skin non-keratinizing large cell squamous cell carcinoma: A study based on the Surveillance, Epidemiology, and End Results database.

Introduction: This study aimed to develop and validate a nomogram for predicting cancer-specific survival (CSS) in patients with non-keratinized large cell squamous cell carcinoma (NKLCSCC) at 3, 5, and 8 years after diagnosis. Methods: Data on SCC patients were collected from the Surveillance, Epidemiology, and End Results database. Training (70%) and validation (30%) cohorts were generated using random selection of patients. Independent prognostic factors were selected using the backward stepwise Cox regression model. To predict the CSS rates in patients with NKLCSCC at 3, 5, and 8 years after diagnosis, all of the factors were incorporated into the nomogram. Indicators such as the concordance index (C-index), area under the time-dependent receiver operating characteristic curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), calibration curve, and decision-curve analysis (DCA) were then used to validate the performance of the nomogram. Results: This study included 9,811 patients with NKLCSCC. Twelve prognostic factors were identified by Cox regression analysis in the training cohort, which were age, number of regional nodes examined, number of positive regional nodes, sex, race, marital status, American Joint Committee on Cancer (AJCC) stage, surgery status, chemotherapy status, radiotherapy status, summary stage, and income. The constructed nomogram was validated both internally and externally. The nomogram had good discrimination ability, as indicated by the comparatively high C-indices and AUC values. The nomogram was properly calibrated, as indicated by the calibration curves. Our nomogram was superior to the AJCC model, as illustrated by its superior NRI and IDI values. DCA curves indicated the clinical usability of the nomogram. Conclusion: The first nomogram for prognosis predictions of patients with NKLCSCC has been developed and verified. Its performance and usability demonstrated that the nomogram could be utilized in clinical settings. However, additional external verification is still required.

Microphase behaviors and shear moduli of double-network gels: The effect of crosslinking constraints and chain uncrossability.

By performing coarse-grained molecular dynamics simulations, we study the effect of crosslinking and chain uncrossability on the microphase behaviors and mechanical properties of the double-network gels. The double-network systems can be viewed as two separate networks interpenetrating each other uniformly, and the crosslinks in each network are generated, forming a regular cubic lattice. The chain uncrossability is confirmed by appropriately choosing the bonded and nonbonded interaction potentials. Our simulations reveal a close relation between the phase and mechanical properties of the double-network systems and their network topological structures. Depending on the lattice size and the solvent affinity, we have observed two different microphases: one is the aggregation of solvophobic beads around the crosslinking points, which leads to locally polymer-rich domains, and the other is the bunching of polymer strands, which thickens the network edges and thus changes the network periodicity. The former is a representation of the interfacial effect, while the latter is determined by the chain uncrossability. The coalescence of network edges is demonstrated to be responsible for the large relative increase in the shear modulus. Compressing and stretching induced phase transitions are observed in the current double-network systems, and the sharp discontinuous change in the stress that appears at the transition point is found to be related to the bunching or debunching of the network edges. The results suggest that the regulation of network edges has a strong influence on the network mechanical properties.