Epidemiological Study in Antiviral Innate Immunity.

This chapter summarizes the epidemiological study design of natural immune epidemiology studies based on recent COVID-19-related research. The epidemiological studies on antiviral innate immunity have mainly included randomized controlled trials (RCTs) and observational studies. Importantly, this chapter will discuss how to use these methodologies to answer an epidemiological question of natural immunity in the viral infection process based on previous studies. An observational case- or cohort-based study of antiviral innate immunity may support this theoretical hypothesis but is not appropriate for clinical practice or treatment. RCTs are the gold standard for epidemiological studies and occupy a greater role in the hierarchy of evidence.

Prediction of immunotherapy response using mutations to cancer protein assemblies.

While immune checkpoint inhibitors have revolutionized cancer therapy, many patients exhibit poor outcomes. Here, we show immunotherapy responses in bladder and non-small cell lung cancers are effectively predicted by factoring tumor mutation burden (TMB) into burdens on specific protein assemblies. This approach identifies 13 protein assemblies for which the assembly-level mutation burden (AMB) predicts treatment outcomes, which can be combined to powerfully separate responders from nonresponders in multiple cohorts (e.g., 76% versus 37% bladder cancer 1-year survival). These results are corroborated by (i) engineered disruptions in the predictive assemblies, which modulate immunotherapy response in mice, and (ii) histochemistry showing that predicted responders have elevated inflammation. The 13 assemblies have diverse roles in DNA damage checkpoints, oxidative stress, or Janus kinase/signal transducers and activators of transcription signaling and include unexpected genes (e.g., PIK3CG and FOXP1) for which mutation affects treatment response. This study provides a roadmap for using tumor cell biology to factor mutational effects on immune response.

Combination of circulating tumor cells, lncRNAs and DNA methylation for the diagnosis of endometrial carcinoma.

Endometrial carcinoma (EC) is one of the most common gynecological malignant neoplasms, the prognosis of which is strongly related to the time of diagnosis, with an earlier diagnosis leading to a better prognosis. Therefore, effective diagnostic indicators and methods are needed to ensure early detection. The present study explored the following in EC: Circulating tumor cells (CTCs); the long noncoding RNAs (lncRNAs) RP4-616B8.5, RP11-389G6.3 and carboxy-terminal domain (CTD)-2377D24.6; and the methylation of cysteine dioxygenase type 1 (CDO1) and CUGBP Elav-like family member 4 (CELF4). In total, 85 patients, including 71 with EC, and 14 without EC (NO-EC) but with uterine fibroids or polyps, were included in the present study. In total, 46 patients with EC and 8 NO-EC patients underwent CTC detection. In the evaluation of the EC vs. NO-EC groups, the results showed that the CTC-positive rate of the EC group was 80.43% and that the area under the curve (AUC) value of CTCs was 0.8872 (P=0.0098). A total of 35 patients with EC and 14 NO-EC patients underwent detection of the RP4-616B8.5, RP11-389G6.3 and CTD-2377D24.6 lncRNAs. When the levels of the three lncRNAs RP4-616B8.5, RP11-389G6.3 and CTD-2377D24.6 were compared between the EC and NO-EC groups, they were higher in the EC group; the P-values were 0.0002, 0.0001 and <0.0001, respectively, and the AUC values were 0.8184, 0.8347 and 0.8265, respectively. In addition, a total of 35 patients with EC and 8 NO-EC patients underwent CDO1 and CELF4 DNA methylation analysis. The positive rates of the methylated genes CDO1 and CELF4 were 20% (7/35) and 5.71% (2/35), and the P-values of the comparisons between the EC and NO-EC groups were 0.1748 and 0.5004, respectively; the AUC values were 0.6000 and 0.5286. Furthermore, the combination of CTCs, and lncRNAs RP4-616B8.5, RP11-389G6.3 and CTD-2377D24.6 exhibited high performance in the detection of EC (AUC=0.9375).

A Method for Sorting High-Quality Fresh Sichuan Pepper Based on a Multi-Domain Multi-Scale Feature Fusion Algorithm.

Post-harvest selection of high-quality Sichuan pepper is a critical step in the production process. To achieve this, a visual system needs to analyze Sichuan pepper with varying postures and maturity levels. To quickly and accurately sort high-quality fresh Sichuan pepper, this study proposes a multi-scale frequency domain feature fusion module (MSF3M) and a multi-scale dual-domain feature fusion module (MS-DFFM) to construct a multi-scale, multi-domain fusion algorithm for feature fusion of Sichuan pepper images. The MultiDomain YOLOv8 Model network is then built to segment and classify the target Sichuan pepper, distinguishing the maturity level of individual Sichuan peppercorns. A selection method based on the average local pixel value difference is proposed for sorting high-quality fresh Sichuan pepper. Experimental results show that the MultiDomain YOLOv8-seg achieves an mAP50 of 88.8% for the segmentation of fresh Sichuan pepper, with a model size of only 5.84 MB. The MultiDomain YOLOv8-cls excels in Sichuan pepper maturity classification, with an accuracy of 98.34%. Compared to the YOLOv8 baseline model, the MultiDomain YOLOv8 model offers higher accuracy and a more lightweight structure, making it highly effective in reducing misjudgments and enhancing post-harvest processing efficiency in agricultural applications, ultimately increasing producer profits.

Integrating Transcriptomics, Proteomics, and Metabolomics to Investigate the Mechanism of Fetal Placental Overgrowth in Somatic Cell Nuclear Transfer Cattle.

A major factor limiting the development of somatic cell nuclear transfer (SCNT) technology is the low success rate of pregnancy, mainly due to placental abnormalities disrupting the maternal-fetal balance during pregnancy. Although there has been some progress in research on the abnormal enlargement of cloned bovine placenta, there are still few reports on the direct regulatory mechanisms of enlarged cloned bovine placenta tissue. In this study, we conducted sequencing and analysis of transcriptomics, proteomics, and metabolomics of placental tissues from SCNT cattle (n = 3) and control (CON) cattle (n = 3). The omics analysis results indicate abnormalities in biological functions such as protein digestion and absorption, glycolysis/gluconeogenesis, the regulation of lipid breakdown, as well as glycerolipid metabolism, and arginine and proline metabolism in the placenta of SCNT cattle. Integrating these analyses highlights critical metabolic pathways affecting SCNT cattle placenta, including choline metabolism and unsaturated fatty acid biosynthesis. These findings suggest that aberrant expressions of genes, proteins, and metabolites in SCNT placentas affect key pathways in protein digestion, growth hormone function, and energy metabolism. Our results suggest that abnormal protein synthesis, growth hormone function, and energy metabolism in SCNT bovine placental tissues contribute to placental hypertrophy. These findings offer valuable insights for further investigation into the mechanisms underlying SCNT bovine placental abnormalities.

Exploring soil multi-parameter stacking measurement through Raman and NIR dual-spectroscopy.

The excessive use of fertilizers can lead to increased production costs, degraded soil quality, diminished product excellence, and environmental contamination. To address this issue, a solution involving soil testing and customizing fertilizer application has been proposed. The current standard methodology for soil parameter assessment relies on chemical analysis performed by trained laboratory technicians, which only allows for the measurement of one indicator at a time. Hence, a novel approach utilizing the fusion of near-infrared (NIR) and Raman dual-spectral features has been suggested to simultaneously determine five crucial indicators (hydrolyzed N, available P, quick-release K, OM, and pH) in soil with a single scan. In this research, seven preprocessing techniques and four feature extraction methods were initially explored to optimize the composite NIR and Raman feature variables. Subsequently, a regressor with a two-layer network structure (RF, LR, SVR; ELM, and PLS) was developed using the stacking algorithm. This methodology synergizes the strengths of the five base learners, minimizes the risk of overfitting, and demonstrates high computational efficiency for linear data correlations and robust fitting capabilities for nonlinear data correlations. Additionally, it showcases strong generalization capabilities, noise resilience, and robustness. The model produced relevant results for hydrolyzed N, available P, quick release K, OM, and pH measurements, with Rp2 values of 0.9966, 0.9722, 0.9855, 0.9557, and 0.9951, RMSEP values of 2.9547, 2.9972, 7.6550, 0.0765, and 0.0313, and RPD values of 6.0855, 2.4655, 3.0511, 8.3084, and 10.6977. This work delivers a twofold contribution by presenting a swift method for simultaneous measurement of multiple soil parameters, enabling concurrent ploughing, soil surveying, and fertilizer application. Furthermore, it introduces a stacking measurement model based on dual fusion features, showcasing detailed model parameters. The stacking model outperformed mono-spectral models (NIR and Raman) and the dual PLS model in terms of Rp2, RPD, and RMSEP values, and fluctuation ranges, demonstrating enhanced stability, predictive prowess, and reliable observations. Overall, the stacking model offers a cost-effective, rapid, and precise solution for online evaluation of soil physicochemical conditions, catering to the requirements of modern agricultural production well. This innovative approach signifies a significant leap forward and provides a solid theoretical foundation for the enhancement of associated online monitoring systems and tools.

Bispecific antibodies provide broad neutralization of emerging beta-coronaviruses by targeting ACE2 and viral spikes.

Human coronaviruses such as SARS-CoV, MERS-CoV, and SARS-CoV-2 have recurrently emerged as significant pathogens, causing severe respiratory illnesses and presenting challenges to monoclonal antibody therapeutics due to their rapid evolution, particularly the diverse variants of SARS-CoV-2. In this study, we utilized "Knob-into-Hole" and "IgG-scFv" technologies to engineer bispecific antibodies (bsAbs) that target both the viral receptor and spike protein, enhancing their neutralization breadth and potency. Our bsAbs, combining anti-SARS-CoV-2 or anti-MERS-CoV antibodies with an anti-ACE2 antibody, demonstrated effective neutralization across a range of SARS-CoV-2 variants, SARS-CoV and MERS-CoV in both pseudovirus and authentic virus assays. Notably, the "IgG-scFv" bsAbs format exhibited superior binding and neutralization capabilities compared to the "Knob-into-Hole" configurations. The most effective of these, "IgG-scFv" H11B11_m336, displayed exceptional neutralization potency against a panel of 24 pseudotyped Beta-Coronaviruses, with IC50 values ranging from 0.001-0.183 µg/mL. Overall, our findings underscore the potential of bsAbs as an effective strategy to meet the immediate challenges posed by existing and emerging pathogens, thereby enhancing global pandemic preparedness.

Enhanced Lithium Extraction from Brines: Prelithiation Effect of FePO4 with Size and Morphology Control.

Extracting lithium resources from seawater and brine can promote the development of the new energy materials industry. The electrochemical method is green and efficient. Iron phosphate (FePO4) crystal, with its 1D ion channel, holds significant potential as a primary lithium extraction electrode material. Li+ encounters a substantial concentration disadvantage in brines, and the co-intercalation of Na+ diminishes Li+ selectivity. To address this issue, this work enhances the energy barrier for Na+ insertion through prelithiation strategies applied to the 1D channels of FePO4 crystal, thereby improving Li+ selectivity, and further investigating the prelithiation effect with particle size and morphology control. The results indicate that the Li(4C-40%)FePO4// Activated carbon(AC) system enhances selectivity of lithium. The Li(4C-40%)FePO4 with size diameter of 2500 nm demonstrates an energy consumption of 0.79 Wh mol-1 and a purity of 97.94% for lithium extraction at a unit lithium extraction of 5.93 mmol g-1 in simulated brine. Li(4C-40%)FePO4-nanoplates demonstrate the most optimal lithium extraction performance among the three morphologies due to their lamellar structure's short ion diffusion path in the [010] channel, favoring Li+ diffusion. The diffusion energy barriers of Li+ and Na+ are calculated using Density Functional Theory (DFT) before and after prelithiation, showing good agreement with experimental results.

Vascular endothelial growth factor receptor 2 as a potential host target for the inhibition of enterovirus replication.

Because host kinases are key regulators of multiple signaling pathways in response to viral infections, we previously screened a kinase inhibitor library using rhabdomyosarcoma cells and human intestinal organoids in parallel to identify potent inhibitors against EV-A71 infection. We found that Rho-associated coiled-coil-containing protein kinase (Rock) inhibitor efficiently suppressed the EV-A71 replication and further revealed Rock1 as a novel EV-A71 host factor. In this study, subsequent analysis found that a variety of vascular endothelial growth factor receptor (VEGFR) inhibitors also had potent antiviral effects. Among the hits, Pazopanib, with a selectivity index as high as 254, which was even higher than that of Pirodavir, a potent broad-spectrum picornavirus inhibitor targeting viral capsid protein VP1, was selected for further analysis. We demonstrated that Pazopanib not only efficiently suppressed the replication of EV-A71 in a dose-dependent manner, but also exhibited broad-spectrum anti-enterovirus activity. Mechanistically, Pazopanib probably induces alterations in host cells, thereby impeding viral genome replication and transcription. Notably, VEGFR2 knockdown and overexpression suppressed and facilitated EV-A71 replication, respectively, indicating that VEGFR2 is a novel host dependency factor for EV-A71 replication. Transcriptome analysis further proved that VEGFR2 potentially plays a crucial role in combating EV-A71 infection through the TSAd-Src-PI3K-Akt pathway. These findings expand the range of potential antiviral candidates of anti-enterovirus therapeutics and suggest that VEGFR2 may be a key host factor involved in EV-A71 replication, making it a potential target for the development of anti-enterovirus therapeutics. IMPORTANCE: As the first clinical case was identified in the United States, EV-A71, a significant neurotropic enterovirus, has been a common cause of hand, foot, and mouth disease (HFMD) in infants and young children. Developing an effective antiviral agent for EV-A71 and other human enteroviruses is crucial, as these viral pathogens consistently cause outbreaks in humans. In this study, we demonstrated that multiple inhibitors against VEGFRs effectively reduced EV-A71 replication, with Pazopanib emerging as the top candidate. Furthermore, Pazopanib also attenuated the replication of other enteroviruses, including CVA10, CVB1, EV-D70, and HRV-A, displaying broad-spectrum anti-enterovirus activity. Given that Pazopanib targets various VEGFRs, we narrowed the focus to VEGFR2 using knockdown and overexpression experiments. Transcriptomic analysis suggests that Pazopanib's potential downstream targets involve the TSAd-Src-PI3K-Akt pathway. Our work may contribute to identifying targets for antiviral inhibitors and advancing treatments for human enterovirus infections.

Study on the corrosion behavior and mechanical response of weakly cemented sandstone in alkaline solutions.

This study examines the corrosion characteristics of weakly cemented sandstone under alkaline conditions, evaluating the effects of varying pH levels on its macroscopic degradation, micro-porosity, and mechanical properties, notably uniaxial compressive strength. Findings reveal that heightened alkalinity exacerbates rock damage, although a temporary alleviation in mass loss occurs between pH 9 and 11 due to pore clogging by complexes formed from cations like Ca2+ and Mg2+.Increased alkalinity induces marked changes in pore features, with an observed rise in pore numbers, transformation of pore shapes from elongated to more spherical, and adjustments in porosity, pore size, and roundness. Furthermore, the study confirms a decline in both the rock's compressive strength and elastic modulus as pH rises. These revelations shed light on the role of pH in the corrosion behavior of weakly cemented sandstone under alkaline conditions, providing a fresh perspective for understanding its corrosion mechanisms in such environments.

Zinc and methyl jasmonate improve sugar beet tolerance to high boron stress by enhanced leaf photochemical performance.

Nutrient imbalances, such as high boron (B) stress, occur within, as well as across, agricultural systems worldwide and have become an important abiotic factor that reduces soil fertility and inhibits plant growth. Sugar beet is a B-loving crop and is better suited to be grown in high B environments, but the methods and mechanisms regarding the enhancement of high-B stress tolerance traits are not clear. The main objective of this research was to elucidate the effects of the alone and/or combined foliar spraying of zinc sulfate (ZnSO4) and methyl jasmonate (MeJA) on the growth parameters, tolerance, and photochemical performance of sugar beet under high-B stress. Results demonstrated that the photosynthetic performance was inhibited under high-B stress, with a reduction of 11.33% in the net photosynthetic rate (Pn) and an increase of 25.30% in the tolerance index. The application of ZnSO4, MeJA, and their combination enhanced sugar beet's adaptability to high-B stress, with an increase in Pn of 9.22%, 4.49%, and 2.85%, respectively, whereas the tolerance index was elevated by 15.33%, 8.21%, and 5.19%, respectively. All three ameliorative treatments resulted in increased photochemical efficiency (Fv/Fm) and the photosynthetic performance index (PIABS) of PSII. Additionally, they enhanced the light energy absorption (ABS/RC) and trapping capacity (DIO/RC), reduced the thermal energy dissipation (TRO/RC), and facilitated the QA to QB transfer in the electron transport chain (ETC) of PSII, which collectively improved the photochemical performance. Therefore, spraying both ZnSO4 and MeJA can better alleviate high-B stress and promote the growth of sugar beet, but the combined spraying effect of ZnSO4 and MeJA is lower than that of individual spraying. This study provides a reference basis for enhancing the ability of sugar beet and other plants to tolerate high-B stress and for sugar beet cultivation in high B areas.

Broad-spectrum coronavirus neutralization induced by hetero RBD-Fc protein vaccine.

In the landscape of infectious diseases, human coronaviruses such as SARS-CoV, MERS-CoV, and SARS-CoV-2 pose significant threats, characterized by severe respiratory illnesses and notable resistance to conventional treatments due to their rapid evolution and the emergence of diverse variants, particularly within SARS-CoV-2. This study investigated the development of broad-spectrum coronavirus vaccines using heterodimeric RBD-Fc proteins engineered through the "Knob-into-Hole" technique. We constructed various recombinant proteins incorporating the receptor-binding domains (RBDs) of different coronaviruses. Heterodimers combining RBDs from SARS-CoV-2 with those of SARS-CoV or MERS-CoV elicited superior neutralizing responses compared to homodimeric proteins in murine models. Additionally, heterotetrameric proteins, specifically D614G_Delta/BA.1_XBB.1.5-RBD and MERS_D614G/BA.1_XBB.1.5-RBD, elicited remarkable breadth and potency in neutralizing all known SARS-CoV-2 variants, SARS-CoV, related sarbecoviruses like GD-Pangolin and WIV1, and even MERS-CoV pseudoviruses. Furthermore, these heterotetrameric proteins also demonstrated enhanced cellular immune responses. These findings underscore the potential of recombinant hetero proteins as a universal vaccine strategy against current and future coronavirus threats.

Tunable Hybrid Hydrogels of Alginate and Cell-Derived dECM to Study the Impact of Matrix Alterations on Epithelial-to-Mesenchymal Transition.

Epithelial-to-mesenchymal transition (EMT) is crucial for tumor progression, being linked to alterations in the extracellular matrix (ECM). Understanding the ECM's role in EMT can uncover new therapeutic targets, yet replicating these interactions in vitro remains challenging. It is shown that hybrid hydrogels of alginate (ALG) and cell-derived decellularized ECM (dECM), with independently tunable composition and stiffness, are useful 3D-models to explore the impact of the breast tumor matrix on EMT. Soft RGD-ALG hydrogels (200 Pa), used as neutral bulk material, supported mammary epithelial cells morphogenesis without spontaneous EMT, allowing to define the gene, protein, and biochemical profiles of cells at different TGFß1-induced EMT states. To mimic the breast tumor composition, dECM from TGFß1-activated fibroblasts (adECM) are generated, which shows upregulation of tumor-associated proteins compared to ndECM from normal fibroblasts. Using hybrid adECM-ALG hydrogels, it is shown that the presence of adECM induces partial EMT in normal epithelial cells, and amplifes TGF-ß1 effects compared to ALG and ndECM-ALG. Increasing the hydrogel stiffness to tumor-like levels (2.5 kPa) have a synergistic effect, promoting a more evident EMT. These findings shed light on the complex interplay between matrix composition and stiffness in EMT, underscoring the utility of dECM-ALG hydrogels as a valuable in vitro platform for cancer research.

Complementary therapy with Chinese aromatic herbs to promote awakening in a comatose patient: A case report.

RATIONALE: Traumatic brain injury frequently leads to prolonged coma, posing significant medical management challenges. Complementary therapies, including traditional Chinese herbal medicine, have been investigated as potential interventions in comatose patients. Chinese aromatic herbs, such as Borneolum (Bingpian), Moschus (Shexiang), and Acori tatarinowii rhizoma (Shichangpu), have long been believed to be "resuscitation with aromatics" based on traditional Chinese medicines theory. PATIENT CONCERNS: A 16-year-old male was admitted to the intensive rehabilitation unit for further treatment due to prolonged coma and frequent seizures following traumatic brain injury. DIAGNOSES: Western medicine diagnosed the patient as coma, diffuse axonal injury, and epilepsy. According to traditional Chinese medicine theory, the syndrome differentiation indicates a Yin-closed disease. INTERVENTIONS: According to the patient's condition, we use the Chinese aromatic herbs as a complementary therapy. OUTCOMES: Following a month-long administration, the patient's consciousness and electroencephalogram (EEG) background progressively improved. A 6-month follow-up demonstrated full arousal, though with ambulatory EEG revealing mild to moderate abnormality in the background. LESSONS: The addition of Chinese aromatic herbs appears to have a beneficial effect on the patient's consciousness and EEG background. This could be attributed to the herbs' inherent pharmacological properties, as well as their potential to enhance the permeability of the blood-brain barrier to other drugs. This makes them a promising option for complementary therapy.

Enhancing kiwifruit flower pollination detection through frequency domain feature fusion: a novel approach to agricultural monitoring.

The pollination process of kiwifruit flowers plays a crucial role in kiwifruit yield. Achieving accurate and rapid identification of the four stages of kiwifruit flowers is essential for enhancing pollination efficiency. In this study, to improve the efficiency of kiwifruit pollination, we propose a novel full-stage kiwifruit flower pollination detection algorithm named KIWI-YOLO, based on the fusion of frequency-domain features. Our algorithm leverages frequency-domain and spatial-domain information to improve recognition of contour-detailed features and integrates decision-making with contextual information. Additionally, we incorporate the Bi-Level Routing Attention (BRA) mechanism with C3 to enhance the algorithm's focus on critical areas, resulting in accurate, lightweight, and fast detection. The algorithm achieves a m A P 0.5 of 91.6% with only 1.8M parameters, the AP of the Female class and the Male class reaches 95% and 93.5%, which is an improvement of 3.8%, 1.2%, and 6.2% compared with the original algorithm. Furthermore, the Recall and F1-score of the algorithm are enhanced by 5.5% and 3.1%, respectively. Moreover, our model demonstrates significant advantages in detection speed, taking only 0.016s to process an image. The experimental results show that the algorithmic model proposed in this study can better assist the pollination of kiwifruit in the process of precision agriculture production and help the development of the kiwifruit industry.

In vivo toxicity of upconversion nanoparticles (NaYF4:Yb, Er) in zebrafish during early life stages: Developmental toxicity, gut-microbiome disruption, and proinflammatory effects.

Lanthanide-doped upconversion nanoparticles (Ln-UCNPs) have been considered promising materials for various fields, such as biomedical and industrial applications. However, data and reports regarding its toxicity and environmental risks are scarce. Under these circumstances, data must be obtained to fully understand potential toxicity and adverse outcome pathways. In the present study, the toxicity of uncoated Ln-UCNP cores (NaYF4:Yb, Er) was systematically assessed in zebrafish embryos during early developmental stages. Ln-UCNPs were found to have multiple toxic effects, such as effects on survival rates, delayed hatching times, shorter body lengths, altered heart rates and blood circulation (significantly reduced), and neurobehavioral impairments in response to photoperiod stimulation. Bioimaging showed that Ln-UCNPs were distributed on the chorion, eyes, and skin at 72 hpf. However, it accumulates in the pharynx, esophagus, and intestine after oral administration. Ln-UCNPs disrupt the diversity and abundance of host-associated microorganisms (gut microbiota) leading to an increase in the prevalence of harmful bacteria in zebrafish. Transcriptomic and Ingenuity Pathway Analysis (IPA) predicted Interleukin-8 (IL-8) signaling, neuroinflammation, cardiac hypertrophy signaling pathways, immune and inflammation-related response interferon-gamma (ifnγ), and miR-155 as key mediators in regulatory effects. Based on this, a causal network was built showing the strong links between the induced gene expression of differentially expressed genes (DEGs), such as nitric oxide synthase 2 (nos2) and tumor necrosis factor (tnf) upon Ln-UCNPs treatment, and with the downstream adverse outcomes, in particular, the promotion of apoptosis, liver damage, and inflammatory response. Finally, RT-qPCR analysis confirmed the up-regulated expression of nos2 and tnf in the exposed larvae, consistent with the observation of an increased number of fluorescence-labelled neutrophils and macrophages in lyz: DsRed transgenic zebrafish until 120 hpf exposure, which together demonstrated the proinflammatory effects of Ln-UCNPs on organisms. In conclusion, we illustrated the developmental toxicity, disruption of gut-microbiome, and proinflammatory effects of Ln-UCNP cores on zebrafish, and the causal network from IPA analysis may help further elucidate the adverse outcome pathway of Ln-UCNPs.

Identification and quantitative detection of illegal additives in wheat flour based on near-infrared spectroscopy combined with chemometrics.

As a common food raw material in daily life, the quality and safety of wheat flour are directly related to people's health. In this study, a model was developed for the rapid identification and detection of three illegal additives in flour, namely azodicarbonamide (ADA), talcum powder, and gypsum powder. This model utilized a combination of near-infrared spectroscopy with chemometric methods. A one-dimensional convolutional neural network was used to reduce data dimensionality, while a support vector machine was applied for non-linear classification to identify illegal additives in flour. The model achieved a calibration set F1 score of 99.38% and accuracy of 99.63%, with a validation set F1 score of 98.81% and accuracy of 98.89%. Two cascaded wavelength selection methods were introduced: The first method involved backward interval partial least squares (BiPLS) combined with an improved binary particle swarm optimization algorithm (IBPSO). The second method utilized the CARS-IBPSO algorithm, which integrated competitive adaptive reweighted sampling (CARS) with IBPSO. The two cascade wavelength selection methods were used to select feature wavelengths associated with additives and construct partial least squares quantitative detection models. The models constructed using CARS-IBPSO selected feature wavelengths for detecting ADA, talcum powder, and gypsum powder exhibited the highest overall performance. The model achieved validation set determination coefficients of 0.9786, 0.9102, and 0.9226, with corresponding to root mean square errors of 0.0024%, 1.3693%, and 1.6506% and residual predictive deviations of 6.8368, 3.5852, and 3.9253, respectively. Near-infrared spectroscopy in combination with convolutional neural network dimensionality reduction and support vector machine classification enabled rapid identification of various illegal additives. The combination of CARS-IBPSO feature wavelength selection and partial least squares regression models facilitated rapid quantitative detection of these additives. This study introduces a new approach for rapidly and accurately identifying and detecting illegal additives in flour.

Oriented cellulose hydrogel: Directed tissue regeneration for reducing corneal leukoplakia and managing fungal corneal ulcers.

Fungal corneal ulcer is one of the leading causes of corneal blindness in developing countries. Corneal scars such as leukoplakia are formed due to inflammation, oxidative stress and non-directed repair, which seriously affect the patients' subsequent visual and life quality. In this study, drawing inspiration from the oriented structure of collagen fibers within the corneal stroma, we first proposed the directional arrangement of CuTA-CMHT hydrogel system at micro and macro scales based on the 3D printing extrusion method combined with secondary patterning. It played an antifungal role and induced oriented repair in therapy of fungal corneal ulcer. The results showed that it effectively inhibited Candida albicans, Aspergillus Niger, Fusarium sapropelum, which mainly affects TNF, NF-kappa B, and HIF-1 signaling pathways, achieving effective antifungal functions. More importantly, the fibroblasts interacted with extracellular matrix (ECM) of corneal stroma through formation of focal adhesions, promoted the proliferation and directional migration of cells in vitro, induced the directional alignment of collagen fibers and corneal stromal orthogonally oriented repair in vivo. This process is mainly associated with MYLK, MYL9, and ITGA3 molecules. Furthermore, the downregulation the growth factors TGF-ß and PDGF-ß inhibits myofibroblast development and reduces scar-type ECM production, thereby reducing corneal leukoplakia. It also activates the PI3K-AKT signaling pathway, promoting corneal healing. In conclusion, the oriented CuTA-CMHT hydrogel system mimics the orthogonal arrangement of collagen fibers, inhibits inflammation, eliminates reactive oxygen species, and reduces corneal leukoplakia, which is of great significance in the treatment of fungal corneal ulcer and is expected to write a new chapter in corneal tissue engineering.

Association between medication complexity and follow-up care attendance: insights from a retrospective multicenter cohort study across 1,223 Chinese hospitals.

Background: Patients with Chronic Obstructive Pulmonary Disease (COPD) frequently face substantial medication burdens. Follow-up care on medication management is critical in achieving disease control. This study aimed to analyze the complexity of COPD-specific medication and determine how it impacted patients' attendance on follow-up care. Methods: This multicenter study includes patients with COPD from 1,223 hospitals across 29 provinces in China from January 2021 to November 2022. The medication Regimen Complexity Index (MRCI) score was used to measure COPD-specific medication complexity. The association between medication complexity and follow-up care attendance was evaluated using the Cox Proportional Hazard Model. Results: Among 16,684 patients, only 2,306 (13.8%) returned for follow-up medication management. 20.3% of the patients had high complex medication regimen (MRCI score >15.0). The analysis revealed that compared to those with less complex regimens, patients with more complex medication regimens were significantly less likely to attend the follow-up medication care, with a Hazard Ratio (HR) of 0.82 (95% Confidence Interval [CI], 0.74-0.91). Specifically, patients with more complex dosage forms were 51% less likely to attend the follow-up care (95% CI, 0.43-0.57). This pattern was especially marked among male patients, patients younger than 65 years, and those without comorbid conditions. Conclusion: Higher medication complexity was associated with a decreased likelihood of attending follow-up care. To promote care continuity in chronic disease management, individuals with complex medication regimens should be prioritized for enhanced education. Furthermore, pharmacists collaborating with respiratory physicians to deprescribe and simplify dosage forms should be considered in the disease management process.

[Diagnostic Value of Ultrasound for Thyroid Nodules With a Spoke-Wheel Blood Flow Pattern].

Objective To explore the diagnostic value of ultrasound for thyroid nodules with a spoke-wheel blood flow pattern.Methods The clinical data of the patients with thyroid nodules presenting a spoke-wheel blood flow pattern examined by ultrasound were collected,and the gray-scale ultrasound features of the nodules were recorded.The diagnostic performance of the Thyroid Imaging Reporting and Data System by American College of Radiology (ACR TI-RADS),Chinese Thyroid Imaging Reporting and Data System (C-TIRADS),and combined specific indicators for the thyroid nodules with a spoke-wheel blood flow pattern was evaluated by comparison with the pathological results,which was regarded as the gold standard.Results A total of 64 patients with thyroid nodules were finally included,including 47 patients with malignant nodules and 17 patients with benign nodules.In addition to the general ultrasound features,central scar mostly appeared in malignant nodules (χ2=5.968,P=0.015),while central coarse calcification was more common in benign nodules (χ2=10.899,P=0.001).After the combination of central scar and central gross calcification,the diagnostic performance of ACR TI-RADS and C-TIRADS was improved (both P<0.001).Conclusions When the thyroid nodule shows a spoke-wheel blood flow pattern,one should be cautious of the possibility of malignancy.Combining central scar and central coarse calcification can improve the accuracy of ultrasonic diagnosis.